BAYESIAN PARAMETER ESTIMATION IN A MIXED-ORDER MODEL OF BOD DECAY. (U915590)

Science.gov (United States)

We describe a generalized version of the BOD decay model in which the reaction is allowed to assume an order other than one. This is accomplished by making the exponent on BOD concentration a free parameter to be determined by the data. This "mixed-order" model may be ...

Advanced Fluid Reduced Order Models for Compressible Flow.

Energy Technology Data Exchange (ETDEWEB)

Tezaur, Irina Kalashnikova [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maddix, Danielle [Stanford Univ., CA (United States); Mussoni, Erin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Balajewicz, Maciej [Univ. of Illinois, Urbana-Champaign, IL (United States)

2017-09-01

This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.

Modelling stock order flows with non-homogeneous intensities from high-frequency data

Science.gov (United States)

Gorshenin, Andrey K.; Korolev, Victor Yu.; Zeifman, Alexander I.; Shorgin, Sergey Ya.; Chertok, Andrey V.; Evstafyev, Artem I.; Korchagin, Alexander Yu.

2013-10-01

A micro-scale model is proposed for the evolution of such information system as the limit order book in financial markets. Within this model, the flows of orders (claims) are described by doubly stochastic Poisson processes taking account of the stochastic character of intensities of buy and sell orders that determine the price discovery mechanism. The proposed multiplicative model of stochastic intensities makes it possible to analyze the characteristics of the order flows as well as the instantaneous proportion of the forces of buyers and sellers, that is, the imbalance process, without modelling the external information background. The proposed model gives the opportunity to link the micro-scale (high-frequency) dynamics of the limit order book with the macro-scale models of stock price processes of the form of subordinated Wiener processes by means of limit theorems of probability theory and hence, to use the normal variance-mean mixture models of the corresponding heavy-tailed distributions. The approach can be useful in different areas with similar properties (e.g., in plasma physics).

Multi-skyrmion solutions of a sixth order Skyrme model

International Nuclear Information System (INIS)

Floratos, I.

2001-08-01

In this thesis, we study some of the classical properties of an extension of the Skyrme model defined by adding a sixth order derivative term to the Lagrangian. In chapter 1, we review the physical as well as the mathematical motivation behind the study of the Skyrme model and in chapter 2, we give a brief summary of various extended Skyrme models that have been proposed over the last few years. We then define a new sixth order Skyrme model by introducing a dimensionless parameter λ that denotes the mixing between the two higher order terms, the Skyrme term and the sixth order term. In chapter 3 we compute numerically the multi-skyrmion solutions of this extended model and show that they have the same symmetries with the usual skyrmion solutions. In addition, we analyse the dependence of the energy and radius of these classical solutions with respect to the coupling constant λ. We compare our results with experimental data and determine whether this modified model can provide us with better theoretical predictions than the original one. In chapter 4, we use the rational map ansatz, introduced by Houghton, Manton and Sutcliffe, to approximate minimum energy multi-skyrmion solutions with B ≤ 9 of the SU(2) model and with B ≤ 6 of the SU(3) model. We compare our results with the ones obtained numerically and show that the rational map ansatz works just as well for the generalised model as for the pure Skyrme model, at least for B ≤ 5. In chapter 5, we use a generalisation of the rational map ansatz, introduced by loannidou, Piette and Zakrzewski, to construct analytically some topologically non-trivial solutions of the extended model in SU(3). These solutions are spherically symmetric and some of them can be interpreted as bound states of skyrmions. Finally, we use the same ansatz to construct low energy configurations of the SU(N) sixth order Skyrme model. (author)

NMR determination of the order parameter in proton and deuteron glasses

International Nuclear Information System (INIS)

Blinc, R.; Dolinsek, J.; Zalar, B.

1989-01-01

The inhomogeneous broadening of the ND + deuteron, O-D--O deuteron and 87 Rb quadrapole perturbed NMR spectra in Rb 0.56 (ND 4 ) 0.44 D 2 PO 4 is used for a direct determination of the Edwards-Anderson pseudo-spin glass order parameter. The data provide strong support for a model where the basic difference between magnetic spin glasses and proton or deuteron glasses is the presence of an inherent random field resulting from substitutional disorder which linearly couples to the O-D--O pseudo spins. In these systems we do not deal with a transition from a paraelectric to a pseudo-spin glass phase but rather with a transition from an ergodic pseudo-spin glass phase with a single order parameter q to a non-ergodic pseudo-spin glass phase with an infinite number of order parameters. (author). 11 refs.; 6 figs

Declarative Modeling for Production Order Portfolio Scheduling

Directory of Open Access Journals (Sweden)

Banaszak Zbigniew

2014-12-01

Full Text Available A declarative framework enabling to determine conditions as well as to develop decision-making software supporting small- and medium-sized enterprises aimed at unique, multi-project-like and mass customized oriented production is discussed. A set of unique production orders grouped into portfolio orders is considered. Operations executed along different production orders share available resources following a mutual exclusion protocol. A unique product or production batch is completed while following a given activity’s network order. The problem concerns scheduling a newly inserted project portfolio subject to constraints imposed by a multi-project environment The answers sought are: Can a given project portfolio specified by its cost and completion time be completed within the assumed time period in a manufacturing system in hand? Which manufacturing system capability guarantees the completion of a given project portfolio ordered under assumed cost and time constraints? The considered problems regard finding a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a newly ordered project portfolio subject to constraints imposed by a multi-project environment. The main objective is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi-project-like and mass customized oriented production scheduling. Multiple illustrative examples are discussed.

Partially ordered models

NARCIS (Netherlands)

Fernandez, R.; Deveaux, V.

2010-01-01

We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

Science.gov (United States)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.

2017-01-01

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets.

Science.gov (United States)

Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-05-01

Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P  sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Fractional-order in a macroeconomic dynamic model

Science.gov (United States)

David, S. A.; Quintino, D. D.; Soliani, J.

2013-10-01

In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

Determination of astaxanthin in Haematococcus pluvialis by first-order derivative spectrophotometry.

Science.gov (United States)

Liu, Xiao Juan; Juan, Liu Xiao; Wu, Ying Hua; Hua, Wu Ying; Zhao, Li Chao; Chao, Zhao Li; Xiao, Su Yao; Yao, Xiao Su; Zhou, Ai Mei; Mei, Zhou Ai; Liu, Xin; Xin, Liu

2011-01-01

A highly selective, convenient, and precise method, first-order derivative spectrophotometry, was applied for the determination of astaxanthin in Haematococcus pluvialis. Ethyl acetate and ethanol (1:1, v/v) were found to be the best extraction solvent tested due to their high efficiency and low toxicity compared with nine other organic solvents. Astaxanthin coexisting with chlorophyll and beta-carotene was analyzed by first-order derivative spectrophotometry in order to optimize the conditions for the determination of astaxanthin. The results show that when detected at 432 nm, the interfering substances could be eliminated. The dynamic linear range was 2.0-8.0 microg/mL, with a correlation coefficient of 0.9916. The detection threshold was 0.41 microg/mL. The RSD for the determination of astaxanthin was in the range of 0.01-0.06%; the results of recovery test were 98.1-108.0%. The statistical analysis between first-order derivative spectrophotometry and HPLC by T-testing did not exceed their critical values, revealing no significant differences between these two methods. It was proved that first-order derivative spectrophotometry is a rapid and convenient method for the determination of astaxanthin in H. pluvialis that can eliminate the negative effect resulting from the coexistence of astaxanthin with chlorophyll and beta-carotene.

One size does not fit all: On how Markov model order dictates performance of genomic sequence analyses

Science.gov (United States)

Narlikar, Leelavati; Mehta, Nidhi; Galande, Sanjeev; Arjunwadkar, Mihir

2013-01-01

The structural simplicity and ability to capture serial correlations make Markov models a popular modeling choice in several genomic analyses, such as identification of motifs, genes and regulatory elements. A critical, yet relatively unexplored, issue is the determination of the order of the Markov model. Most biological applications use a predetermined order for all data sets indiscriminately. Here, we show the vast variation in the performance of such applications with the order. To identify the ‘optimal’ order, we investigated two model selection criteria: Akaike information criterion and Bayesian information criterion (BIC). The BIC optimal order delivers the best performance for mammalian phylogeny reconstruction and motif discovery. Importantly, this order is different from orders typically used by many tools, suggesting that a simple additional step determining this order can significantly improve results. Further, we describe a novel classification approach based on BIC optimal Markov models to predict functionality of tissue-specific promoters. Our classifier discriminates between promoters active across 12 different tissues with remarkable accuracy, yielding 3 times the precision expected by chance. Application to the metagenomics problem of identifying the taxum from a short DNA fragment yields accuracies at least as high as the more complex mainstream methodologies, while retaining conceptual and computational simplicity. PMID:23267010

Ordering Cost Reduction in Inventory Model with Defective Items and Backorder Price Discount

Directory of Open Access Journals (Sweden)

Karuppuchamy Annadurai

2014-01-01

Full Text Available In the real market, as unsatisfied demands occur, the longer the length of lead time is, the smaller the proportion of backorder would be. In order to make up for the inconvenience and even the losses of royal and patient customers, the supplier may offer a backorder price discount to secure orders during the shortage period. Also, ordering policies determined by conventional inventory models may be inappropriate for the situation in which an arrival lot contains some defective items. To compensate for the inconvenience of backordering and to secure orders, the supplier may offer a price discount on the stockout item. The purpose of this study is to explore a coordinated inventory model including defective arrivals by allowing the backorder price discount and ordering cost as decision variables. There are two inventory models proposed in this paper, one with normally distributed demand and another with distribution free demand. A computer code using the software Matlab 7.0 is developed to find the optimal solution and present numerical examples to illustrate the models. The results in the numerical examples indicate that the savings of the total cost are realized through ordering cost reduction and backorder price discount.

Model selection criteria : how to evaluate order restrictions

NARCIS (Netherlands)

Kuiper, R.M.

2012-01-01

Researchers often have ideas about the ordering of model parameters. They frequently have one or more theories about the ordering of the group means, in analysis of variance (ANOVA) models, or about the ordering of coefficients corresponding to the predictors, in regression models.A researcher might

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

Science.gov (United States)

Gao, Kai; Fu, Shubin; Chung, Eric T.

2018-05-01

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss-Lobatto-Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

A mathematical model for order splitting in a multiple supplier single-item inventory system

DEFF Research Database (Denmark)

Abginehchi, Soheil; Farahani, Reza Zanjirani; Rezapour, Shabnam

2013-01-01

systems. The item acquisition lead times of suppliers are random variables. Backorder is allowed and shortage cost is charged based on not only per unit in shortage but also per time unit. Continuous review (s,Q) policy has been assumed. When the inventory level depletes to a reorder level, the total...... order is split among n suppliers. Since the suppliers have different characteristics, the quantity ordered to different suppliers may be different. The problem is to determine the reorder level and quantity ordered to each supplier so that the expected total cost per time unit, including ordering cost......, procurement cost, inventory holding cost, and shortage cost, is minimized. We also conduct extensive numerical experiments to show the advantages of our model compared with the models in the literature. According to our extensive experiments, the model developed in this paper is the best model...

Gravity model improvement investigation. [improved gravity model for determination of ocean geoid

Science.gov (United States)

Siry, J. W.; Kahn, W. D.; Bryan, J. W.; Vonbun, F. F.

1973-01-01

This investigation was undertaken to improve the gravity model and hence the ocean geoid. A specific objective is the determination of the gravity field and geoid with a space resolution of approximately 5 deg and a height resolution of the order of five meters. The concept of the investigation is to utilize both GEOS-C altimeter and satellite-to-satellite tracking data to achieve the gravity model improvement. It is also planned to determine the geoid in selected regions with a space resolution of about a degree and a height resolution of the order of a meter or two. The short term objectives include the study of the gravity field in the GEOS-C calibration area outlined by Goddard, Bermuda, Antigua, and Cape Kennedy, and also in the eastern Pacific area which is viewed by ATS-F.

Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network

Science.gov (United States)

Yao, Weigang; Liou, Meng-Sing

2012-01-01

The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis

On the Entropy Based Associative Memory Model with Higher-Order Correlations

Directory of Open Access Journals (Sweden)

Masahiro Nakagawa

2010-01-01

Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.

XY model with higher-order exchange.

Science.gov (United States)

Žukovič, Milan; Kalagov, Georgii

2017-08-01

An XY model, generalized by inclusion of up to an infinite number of higher-order pairwise interactions with an exponentially decreasing strength, is studied by spin-wave theory and Monte Carlo simulations. At low temperatures the model displays a quasi-long-range-order phase characterized by an algebraically decaying correlation function with the exponent η=T/[2πJ(p,α)], nonlinearly dependent on the parameters p and α that control the number of the higher-order terms and the decay rate of their intensity, respectively. At higher temperatures the system shows a crossover from the continuous Berezinskii-Kosterlitz-Thouless to the first-order transition for the parameter values corresponding to a highly nonlinear shape of the potential well. The role of topological excitations (vortices) in changing the nature of the transition is discussed.

Identification of reduced-order model for an aeroelastic system from flutter test data

Directory of Open Access Journals (Sweden)

Wei Tang

2017-02-01

Full Text Available Recently, flutter active control using linear parameter varying (LPV framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by synthesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI models by using system identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering technique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.

Model for the orientational ordering of the plant microtubule cortical array

Science.gov (United States)

Hawkins, Rhoda J.; Tindemans, Simon H.; Mulder, Bela M.

2010-07-01

The plant microtubule cortical array is a striking feature of all growing plant cells. It consists of a more or less homogeneously distributed array of highly aligned microtubules connected to the inner side of the plasma membrane and oriented transversely to the cell growth axis. Here, we formulate a continuum model to describe the origin of orientational order in such confined arrays of dynamical microtubules. The model is based on recent experimental observations that show that a growing cortical microtubule can interact through angle dependent collisions with pre-existing microtubules that can lead either to co-alignment of the growth, retraction through catastrophe induction or crossing over the encountered microtubule. We identify a single control parameter, which is fully determined by the nucleation rate and intrinsic dynamics of individual microtubules. We solve the model analytically in the stationary isotropic phase, discuss the limits of stability of this isotropic phase, and explicitly solve for the ordered stationary states in a simplified version of the model.

Model predictive control based on reduced order models applied to belt conveyor system.

Science.gov (United States)

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A comparison of zero-order, first-order, and Monod biotransformation models

International Nuclear Information System (INIS)

Bekins, B.A.; Warren, E.; Godsy, E.M.

1998-01-01

Under some conditions, a first-order kinetic model is a poor representation of biodegradation in contaminated aquifers. Although it is well known that the assumption of first-order kinetics is valid only when substrate concentration, S, is much less than the half-saturation constant, K S , this assumption is often made without verification of this condition. The authors present a formal error analysis showing that the relative error in the first-order approximation is S/K S and in the zero-order approximation the error is K S /S. They then examine the problems that arise when the first-order approximation is used outside the range for which it is valid. A series of numerical simulations comparing results of first- and zero-order rate approximations to Monod kinetics for a real data set illustrates that if concentrations observed in the field are higher than K S , it may be better to model degradation using a zero-order rate expression. Compared with Monod kinetics, extrapolation of a first-order rate to lower concentrations under-predicts the biotransformation potential, while extrapolation to higher concentrations may grossly over-predict the transformation rate. A summary of solubilities and Monod parameters for aerobic benzene, toluene, and xylene (BTX) degradation shows that the a priori assumption of first-order degradation kinetics at sites contaminated with these compounds is not valid. In particular, out of six published values of K S for toluene, only one is greater than 2 mg/L, indicating that when toluene is present in concentrations greater than about a part per million, the assumption of first-order kinetics may be invalid. Finally, the authors apply an existing analytical solution for steady-state one-dimensional advective transport with Monod degradation kinetics to a field data set

In situ and laboratory determined first-order degradation rate constants of specific organic compounds in an aerobic aquifer

DEFF Research Database (Denmark)

Nielsen, P.H.; Bjerg, P.L.; Nielsen, P.

1996-01-01

In situ microcosms (ISM) and laboratory batch microcosms (LBM) were used for determination of the first-order degradation rate constants of benzene, toluene, o-xylene, nitrobenzene, naphthalene, biphenyl, o- and p-dichlorobenzene, 1,1,1 -trichloroethane, tetrachlorometane, trichloroethene......, tetrachloroethene, phenol, o-cresol, 2,4- and 2,6-dichlorophenol, 4,6-o-dichlorocresol, and o- and p-nitrophenol in an aerobic aquifer, All aromatic hydrocarbons were degraded in ISM and LBM experiments. The phenolic hydrocarbons were ail degraded in ISM experiments, but some failed to degrade in LBM experiments....... Chlorinated aliphatic hydrocarbons were degraded neither in ISM nor LBM experiments. Degradation rate constants were determined by a model accounting for kinetic sorption (bicontinuum model), lag phases, and first-order degradation. With a few exceptions, lag phases were less than 2 weeks in both ISM and LBM...

Probabilistic error bounds for reduced order modeling

Energy Technology Data Exchange (ETDEWEB)

Abdo, M.G.; Wang, C.; Abdel-Khalik, H.S., E-mail: abdo@purdue.edu, E-mail: wang1730@purdue.edu, E-mail: abdelkhalik@purdue.edu [Purdue Univ., School of Nuclear Engineering, West Lafayette, IN (United States)

2015-07-01

Reduced order modeling has proven to be an effective tool when repeated execution of reactor analysis codes is required. ROM operates on the assumption that the intrinsic dimensionality of the associated reactor physics models is sufficiently small when compared to the nominal dimensionality of the input and output data streams. By employing a truncation technique with roots in linear algebra matrix decomposition theory, ROM effectively discards all components of the input and output data that have negligible impact on reactor attributes of interest. This manuscript introduces a mathematical approach to quantify the errors resulting from the discarded ROM components. As supported by numerical experiments, the introduced analysis proves that the contribution of the discarded components could be upper-bounded with an overwhelmingly high probability. The reverse of this statement implies that the ROM algorithm can self-adapt to determine the level of the reduction needed such that the maximum resulting reduction error is below a given tolerance limit that is set by the user. (author)

Alternative solution model for the ternary carbonate system CaCO3 - MgCO3 - FeCO3 - II. Calibration of a combined ordering model and mixing model

Science.gov (United States)

McSwiggen, P.L.

1993-01-01

Earlier attempts at solution models for the ternary carbonate system have been unable to adequately accommodate the cation ordering which occurs in some of the carbonate phases. The carbonate solution model of this study combines a Margules type of interaction model with a Bragg-Williams type of ordering model. The ordering model determines the equilibrium state of order for a crystal, from which the cation distribution within the lattice can be obtained. The interaction model addresses the effect that mixing different cation species within a given cation layer has on the total free energy of the system. An ordering model was derived, based on the Bragg-Williams approach; it is applicable to ternary systems involving three cations substituting on two sites, and contains three ordering energy parameters (WCaMg, WCaFe, and WCaMgFe). The solution model of this study involves six Margules-type interaction parameters (W12, W21, W13, W31, W23, and W32). Values for the two sets of energy parameters were calculated from experimental data and from compositional relationships in natural assemblages. ?? 1993 Springer-Verlag.

Mixed-order phase transition in a one-dimensional model.

Science.gov (United States)

Bar, Amir; Mukamel, David

2014-01-10

We introduce and analyze an exactly soluble one-dimensional Ising model with long range interactions that exhibits a mixed-order transition, namely a phase transition in which the order parameter is discontinuous as in first order transitions while the correlation length diverges as in second order transitions. Such transitions are known to appear in a diverse classes of models that are seemingly unrelated. The model we present serves as a link between two classes of models that exhibit a mixed-order transition in one dimension, namely, spin models with a coupling constant that decays as the inverse distance squared and models of depinning transitions, thus making a step towards a unifying framework.

Alternative solution model for the ternary carbonate system CaCO3 - MgCO3 - FeCO3 - I. A ternary Bragg-Williams ordering model

Science.gov (United States)

McSwiggen, P.L.

1993-01-01

The minerals of the ternary carbonate system CaCO3 - MgCO3 - FeCO3 represent a complex series of solid solutions and ordering states. An understanding of those complexities requires a solution model that can both duplicate the subsolidus phase relationships and generate correct values for the activities. Such a solution model must account for the changes in the total energy of the system resulting from a change in the ordering state of the individual constituents. Various ordering models have been applied to binary carbonate systems, but no attempts have previously been made to model the ordering in the ternary system. This study derives a new set of equations that allow for the equilibrium degree of order to be calculated for a system involving three cations mixing on two sites, as in the case of the ternary carbonates. The method is based on the Bragg-Williams approach. From the degree of order, the mole fractions of the three cations in each of the two sites can be determined. Once the site occupancies have been established, a Margules-type mixing model can be used to determine the free energy of mixing in the solid solution and therefore the activities of the various components. ?? 1993 Springer-Verlag.

Synthesis of models for order-sorted first-order theories using linear algebra and constraint solving

Directory of Open Access Journals (Sweden)

Salvador Lucas

2015-12-01

Full Text Available Recent developments in termination analysis for declarative programs emphasize the use of appropriate models for the logical theory representing the program at stake as a generic approach to prove termination of declarative programs. In this setting, Order-Sorted First-Order Logic provides a powerful framework to represent declarative programs. It also provides a target logic to obtain models for other logics via transformations. We investigate the automatic generation of numerical models for order-sorted first-order logics and its use in program analysis, in particular in termination analysis of declarative programs. We use convex domains to give domains to the different sorts of an order-sorted signature; we interpret the ranked symbols of sorted signatures by means of appropriately adapted convex matrix interpretations. Such numerical interpretations permit the use of existing algorithms and tools from linear algebra and arithmetic constraint solving to synthesize the models.

Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

Science.gov (United States)

Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

2017-12-01

An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

A Predictive Model of Multi-Stage Production Planning for Fixed Time Orders

Directory of Open Access Journals (Sweden)

Kozłowski Edward

2014-09-01

Full Text Available The traditional production planning model based upon a deterministic approach is well described in the literature. Due to the uncertain nature of manufacturing processes, such model can however incorrectly represent actual situations on the shop floor. This study develops a mathematical modeling framework for generating production plans in a multistage manufacturing process. The devised model takes into account the stochastic model for predicting the occurrence of faulty products. The aim of the control model is to determine the number of products which should be manufactured in each planning period to minimize both manufacturing costs and potential financial penalties for failing to fulfill the order completely.

What Determines Lean Manufacturing Implementation? A CB-SEM Model

Directory of Open Access Journals (Sweden)

Tan Ching Ng

2018-02-01

Full Text Available This research aims to ascertain the determinants of effective Lean Manufacturing (LM. In this research, Covariance-based Structural Equation Modeling (CB-SEM analysis will be used in order to analyze the determinants. Through CB-SEM analysis, the significant key determinants can be determined and the direct relationships among determinants can be analyzed. Thus, the findings of this research can act as guidelines for achievement of LM effectiveness, not only providing necessary steps for successful implementation of lean, but also helping lean companies to achieve higher level of lean cost and time savings.

Modeling Ability Differentiation in the Second-Order Factor Model

Science.gov (United States)

Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J.

2011-01-01

In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…

A Novel Method for Decoding Any High-Order Hidden Markov Model

Directory of Open Access Journals (Sweden)

Fei Ye

2014-01-01

Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.

Model-order reduction of lumped parameter systems via fractional calculus

Science.gov (United States)

Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio

2018-04-01

This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

Science.gov (United States)

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

A posteriori model validation for the temporal order of directed functional connectivity maps.

Science.gov (United States)

Beltz, Adriene M; Molenaar, Peter C M

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data).

A posteriori model validation for the temporal order of directed functional connectivity maps

Directory of Open Access Journals (Sweden)

Adriene M. Beltz

2015-08-01

Full Text Available A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests, and (b to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates and substantive implications (e.g., higher order lags may be common in resting state data.

Generalized Reduced Order Model Generation, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — M4 Engineering proposes to develop a generalized reduced order model generation method. This method will allow for creation of reduced order aeroservoelastic state...

Investigation of Effectiveness of Order Review and Release Models in Make to Order Supply Chain

Directory of Open Access Journals (Sweden)

Kundu Kaustav

2016-01-01

Full Text Available Nowadays customisation becomes more common due to vast requirement from the customers for which industries are trying to use make-to-order (MTO strategy. Due to high variation in the process, workload control models are extensively used for jobshop companies which usually adapt MTO strategy. Some authors tried to implement workload control models, order review and release systems, in non-repetitive manufacturing companies, where there is a dominant flow in production. Those models are better in shop floor but their performances are never been investigated in high variation situations like MTO supply chain. This paper starts with the introduction of particular issues in MTO companies and a general overview of order review and release systems widely used in the industries. Two order review and release systems, the Limited and Balanced models, particularly suitable for flow shop system are applied to MTO supply chain, where the processing times are difficult to estimate due to high variation. Simulation results show that the Balanced model performs much better than the Limited model if the processing times can be estimated preciously.

Spiking and bursting patterns of fractional-order Izhikevich model

Science.gov (United States)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

A reduced order model of a quadruped walking system

International Nuclear Information System (INIS)

Sano, Akihito; Furusho, Junji; Naganuma, Nobuyuki

1990-01-01

Trot walking has recently been studied by several groups because of its stability and realizability. In the trot, diagonally opposed legs form pairs. While one pair of legs provides support, the other pair of legs swings forward in preparation for the next step. In this paper, we propose a reduced order model for the trot walking. The reduced order model is derived by using two dominant modes of the closed loop system in which the local feedback at each joint is implemented. It is shown by numerical examples that the obtained reduced order model can well approximate the original higher order model. (author)

Dynamical models of happiness with fractional order

Science.gov (United States)

Song, Lei; Xu, Shiyun; Yang, Jianying

2010-03-01

This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.

Hybrid reduced order modeling for assembly calculations

Energy Technology Data Exchange (ETDEWEB)

Bang, Youngsuk, E-mail: ysbang00@fnctech.com [FNC Technology, Co. Ltd., Yongin-si (Korea, Republic of); Abdel-Khalik, Hany S., E-mail: abdelkhalik@purdue.edu [Purdue University, West Lafayette, IN (United States); Jessee, Matthew A., E-mail: jesseema@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States); Mertyurek, Ugur, E-mail: mertyurek@ornl.gov [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

2015-12-15

Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.

Hybrid reduced order modeling for assembly calculations

International Nuclear Information System (INIS)

Bang, Youngsuk; Abdel-Khalik, Hany S.; Jessee, Matthew A.; Mertyurek, Ugur

2015-01-01

Highlights: • Reducing computational cost in engineering calculations. • Reduced order modeling algorithm for multi-physics problem like assembly calculation. • Non-intrusive algorithm with random sampling. • Pattern recognition in the components with high sensitive and large variation. - Abstract: While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system.

Fractional Order Models of Industrial Pneumatic Controllers

Directory of Open Access Journals (Sweden)

Abolhassan Razminia

2014-01-01

Full Text Available This paper addresses a new approach for modeling of versatile controllers in industrial automation and process control systems such as pneumatic controllers. Some fractional order dynamical models are developed for pressure and pneumatic systems with bellows-nozzle-flapper configuration. In the light of fractional calculus, a fractional order derivative-derivative (FrDD controller and integral-derivative (FrID are remodeled. Numerical simulations illustrate the application of the obtained theoretical results in simple examples.

Rich Ground State Chemical Ordering in Nanoparticles: Exact Solution of a Model for Ag-Au Clusters

DEFF Research Database (Denmark)

Larsen, Peter Mahler; Jacobsen, Karsten Wedel; Schiøtz, Jakob

2018-01-01

We show that nanoparticles can have very rich ground state chemical order. This is illustrated by determining the chemical ordering of Ag-Au 309-atom Mackay icosahedral nanoparticles. The energy of the nanoparticles is described using a cluster expansion model, and a Mixed Integer Programming (MIP......) approach is used to find the exact ground state configurations for all stoichiometries. The chemical ordering varies widely between the different stoichiometries, and display a rich zoo of structures with non-trivial ordering....

Simulation of local instabilities with the use of reduced order models

International Nuclear Information System (INIS)

Dykin, V.; Demaziere, C.; Lange, C.; Hennig, D.

2011-01-01

The development of an advanced reduced order model (ROM) with four heated channels, taking into account local, regional and core-wide oscillations, is described. The ROM contains three sub-models: a neutron-kinetic model (describing neutron transport), a thermal- hydraulic model (describing the coolant flow) and a heat transfer model (describing heat transfer between the fuel and the coolant). All these three models are coupled to each other, using two feedback mechanisms: void feedback and doppler feedback. Each of the sub-models is described by a set of reduced ordinary differential equations, derived from the corresponding time space-dependent partial differential equations by using different types of approximations and mathematical techniques. All three models were developed from past ROMs and, subsequently, were modified in order to fit the purpose of our investigations. One of the novelties of the present ROM is that it takes into account the effect of the first three neutronic modes, namely the fundamental, the first and the second azimuthal modes, as well as the effect of local oscillations on these modes. In order to have a proper representation of both azimuthal modes, a four heated channel ROM was developed. Another modification, compared to earlier work, is the determination of the coupling reactivity coefficients for both void fraction and fuel temperature, which were calculated explicitly by evaluating cross-section perturbations with the help of the SIMULATE-3 and the CORESIM codes. The ROM was thereafter applied to a channel instability event that occurred at the Swedish Forsmark-1 BWR in 1996/1997. The time signals for each of the modes were generated from the ROM and compared with the measurements, performed at the plant. Some qualitative comparison between the ROM and the measurements was made. The results could bear some significance in understanding the instability event and its coupling mechanism to core-wide oscillations. (author)

46 CFR 201.3 - Authentication of rules, orders, determinations and decisions of the Administration.

Science.gov (United States)

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Authentication of rules, orders, determinations and decisions of the Administration. 201.3 Section 201.3 Shipping MARITIME ADMINISTRATION, DEPARTMENT OF....3 Authentication of rules, orders, determinations and decisions of the Administration. All rules...

Reduced order for nuclear reactor model in frequency and time domain

International Nuclear Information System (INIS)

Nugroho, D.H.

1997-01-01

In control system theory, a model can be represented by frequency or time domain. In frequency domain, the model was represented by transfer function. in time domain, the model was represented by state space. for the sake of simplification in computation, it is necessary to reduce the model order. the main aim of this research is to find the best in nuclear reactor model. Model order reduction in frequency domain can be done utilizing pole-zero cancellation method; while in time domain utilizing balanced aggregation method the balanced aggregation method was developed by moore (1981). In this paper, the two kinds of method were applied to reduce a nuclear reactor model which was constructed by neutron dynamics and heat transfer equations. to validate that the model characteristics were not change when model order reduction applied, the response was utilized for full and reduced order. it was shown that the nuclear reactor order model can be reduced from order 8 to 2 order 2 is the best order for nuclear reactor model

Reduced order ARMA spectral estimation of ocean waves

Digital Repository Service at National Institute of Oceanography (India)

Mandal, S.; Witz, J.A.; Lyons, G.J.

. After selecting the initial model order based on the Akaike Information Criterion method, a novel model order reduction technique is applied to obtain the final reduced order ARMA model. First estimates of the higher order autoregressive coefficients... of the reduced order ARMA model is obtained. The moving average part is determined based on partial fraction and recursive methods. The above system identification models and model order reduction technique are shown here to be successfully applied...

Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts

Science.gov (United States)

Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.

2017-01-01

This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.

Low-Order Modeling of Dynamic Stall on Airfoils in Incompressible Flow

Science.gov (United States)

Narsipur, Shreyas

flap to model the effect of the separated boundary-layer. Unsteady RANS results for several pitch and plunge motions showed that the differences in aerodynamic loads between steady and unsteady flows can be attributed to the boundary-layer convection lag, which can be modeled by choosing an appropriate value of the time lag parameter, tau2. In order to provide appropriate viscous corrections to inviscid unsteady calculations, the non-linear decambering flap is applied with a time lag determined by the tau2 value, which was found to be independent of motion kinematics for a given airfoil and Reynolds number. The predictions of the aerodynamic loads, unsteady stall, hysteresis loops, and ow reattachment from the low-order model agree well with CFD and experimental results, both for individual cases and for trends between motions. The model was also found to perform as well as existing semi-empirical models while using only a single empirically defined parameter. Inclusion of LEV shedding capabilities and combining the resulting algorithm with phase one's trailing-edge separation model was the primary objective of phase two. Computational results at low and high Reynolds numbers were used to analyze the ow morphology of the LEV to identify the common surface signature associated with LEV initiation at both low and high Reynolds numbers and relate it to the critical leading-edge suction parameter (LESP ) to control the initiation and termination of LEV shedding in the low-order model. The critical LESP, like the tau2 parameter, was found to be independent of motion kinematics for a given airfoil and Reynolds number. Results from the final low-order model compared excellently with CFD and experimental solutions, both in terms of aerodynamic loads and vortex ow pattern predictions. Overall, the final combined dynamic stall model that resulted from the current research was successful in accurately modeling the physics of unsteady ow thereby helping restrict the number of

Group-ICA model order highlights patterns of functional brain connectivity

Directory of Open Access Journals (Sweden)

Ahmed eAbou Elseoud

2011-06-01

Full Text Available Resting-state networks (RSNs can be reliably and reproducibly detected using independent component analysis (ICA at both individual subject and group levels. Altering ICA dimensionality (model order estimation can have a significant impact on the spatial characteristics of the RSNs as well as their parcellation into sub-networks. Recent evidence from several neuroimaging studies suggests that the human brain has a modular hierarchical organization which resembles the hierarchy depicted by different ICA model orders. We hypothesized that functional connectivity between-group differences measured with ICA might be affected by model order selection. We investigated differences in functional connectivity using so-called dual-regression as a function of ICA model order in a group of unmedicated seasonal affective disorder (SAD patients compared to normal healthy controls. The results showed that the detected disease-related differences in functional connectivity alter as a function of ICA model order. The volume of between-group differences altered significantly as a function of ICA model order reaching maximum at model order 70 (which seems to be an optimal point that conveys the largest between-group difference then stabilized afterwards. Our results show that fine-grained RSNs enable better detection of detailed disease-related functional connectivity changes. However, high model orders show an increased risk of false positives that needs to be overcome. Our findings suggest that multilevel ICA exploration of functional connectivity enables optimization of sensitivity to brain disorders.

A modeling of dynamic storage assignment for order picking in beverage warehousing with Drive-in Rack system

Science.gov (United States)

Hadi, M. Z.; Djatna, T.; Sugiarto

2018-04-01

This paper develops a dynamic storage assignment model to solve storage assignment problem (SAP) for beverages order picking in a drive-in rack warehousing system to determine the appropriate storage location and space for each beverage products dynamically so that the performance of the system can be improved. This study constructs a graph model to represent drive-in rack storage position then combine association rules mining, class-based storage policies and an arrangement rule algorithm to determine an appropriate storage location and arrangement of the product according to dynamic orders from customers. The performance of the proposed model is measured as rule adjacency accuracy, travel distance (for picking process) and probability a product become expiry using Last Come First Serve (LCFS) queue approach. Finally, the proposed model is implemented through computer simulation and compare the performance for different storage assignment methods as well. The result indicates that the proposed model outperforms other storage assignment methods.

High-order dynamic modeling and parameter identification of structural discontinuities in Timoshenko beams by using reflection coefficients

Science.gov (United States)

Fan, Qiang; Huang, Zhenyu; Zhang, Bing; Chen, Dayue

2013-02-01

Properties of discontinuities, such as bolt joints and cracks in the waveguide structures, are difficult to evaluate by either analytical or numerical methods due to the complexity and uncertainty of the discontinuities. In this paper, the discontinuity in a Timoshenko beam is modeled with high-order parameters and then these parameters are identified by using reflection coefficients at the discontinuity. The high-order model is composed of several one-order sub-models in series and each sub-model consists of inertia, stiffness and damping components in parallel. The order of the discontinuity model is determined based on the characteristics of the reflection coefficient curve and the accuracy requirement of the dynamic modeling. The model parameters are identified through the least-square fitting iteration method, of which the undetermined model parameters are updated in iteration to fit the dynamic reflection coefficient curve with the wave-based one. By using the spectral super-element method (SSEM), simulation cases, including one-order discontinuities on infinite- and finite-beams and a two-order discontinuity on an infinite beam, were employed to evaluate both the accuracy of the discontinuity model and the effectiveness of the identification method. For practical considerations, effects of measurement noise on the discontinuity parameter identification are investigated by adding different levels of noise to the simulated data. The simulation results were then validated by the corresponding experiments. Both the simulation and experimental results show that (1) the one-order discontinuities can be identified accurately with the maximum errors of 6.8% and 8.7%, respectively; (2) and the high-order discontinuities can be identified with the maximum errors of 15.8% and 16.2%, respectively; and (3) the high-order model can predict the complex discontinuity much more accurately than the one-order discontinuity model.

Hybrid reduced order modeling for assembly calculations

Energy Technology Data Exchange (ETDEWEB)

Bang, Y.; Abdel-Khalik, H. S. [North Carolina State University, Raleigh, NC (United States); Jessee, M. A.; Mertyurek, U. [Oak Ridge National Laboratory, Oak Ridge, TN (United States)

2013-07-01

While the accuracy of assembly calculations has considerably improved due to the increase in computer power enabling more refined description of the phase space and use of more sophisticated numerical algorithms, the computational cost continues to increase which limits the full utilization of their effectiveness for routine engineering analysis. Reduced order modeling is a mathematical vehicle that scales down the dimensionality of large-scale numerical problems to enable their repeated executions on small computing environment, often available to end users. This is done by capturing the most dominant underlying relationships between the model's inputs and outputs. Previous works demonstrated the use of the reduced order modeling for a single physics code, such as a radiation transport calculation. This manuscript extends those works to coupled code systems as currently employed in assembly calculations. Numerical tests are conducted using realistic SCALE assembly models with resonance self-shielding, neutron transport, and nuclides transmutation/depletion models representing the components of the coupled code system. (authors)

Heterogeneous traffic flow modelling using second-order macroscopic continuum model

Science.gov (United States)

Mohan, Ranju; Ramadurai, Gitakrishnan

2017-01-01

Modelling heterogeneous traffic flow lacking in lane discipline is one of the emerging research areas in the past few years. The two main challenges in modelling are: capturing the effect of varying size of vehicles, and the lack in lane discipline, both of which together lead to the 'gap filling' behaviour of vehicles. The same section length of the road can be occupied by different types of vehicles at the same time, and the conventional measure of traffic concentration, density (vehicles per lane per unit length), is not a good measure for heterogeneous traffic modelling. First aim of this paper is to have a parsimonious model of heterogeneous traffic that can capture the unique phenomena of gap filling. Second aim is to emphasize the suitability of higher-order models for modelling heterogeneous traffic. Third, the paper aims to suggest area occupancy as concentration measure of heterogeneous traffic lacking in lane discipline. The above mentioned two main challenges of heterogeneous traffic flow are addressed by extending an existing second-order continuum model of traffic flow, using area occupancy for traffic concentration instead of density. The extended model is calibrated and validated with field data from an arterial road in Chennai city, and the results are compared with those from few existing generalized multi-class models.

Determining The Optimal Order Picking Batch Size In Single Aisle Warehouses

NARCIS (Netherlands)

T. Le-Duc (Tho); M.B.M. de Koster (René)

2002-01-01

textabstractThis work aims at investigating the influence of picking batch size to average time in system of orders in a one-aisle warehouse under the assumption that order arrivals follow a Poisson process and items are uniformly distributed over the aisle's length. We model this problem as an

Fractional-order mathematical model of an irrigation main canal pool

Directory of Open Access Journals (Sweden)

Shlomi N. Calderon-Valdez

2015-09-01

Full Text Available In this paper a fractional order model for an irrigation main canal is proposed. It is based on the experiments developed in a laboratory prototype of a hydraulic canal and the application of a direct system identification methodology. The hydraulic processes that take place in this canal are equivalent to those that occur in real main irrigation canals and the results obtained here can therefore be easily extended to real canals. The accuracy of the proposed fractional order model is compared by deriving two other integer-order models of the canal of a complexity similar to that proposed here. The parameters of these three mathematical models have been identified by minimizing the Integral Square Error (ISE performance index existing between the models and the real-time experimental data obtained from the canal prototype. A comparison of the performances of these three models shows that the fractional-order model has the lowest error and therefore the higher accuracy. Experiments showed that our model outperformed the accuracy of the integer-order models by about 25%, which is a significant improvement as regards to capturing the canal dynamics.

Fractional-Order Nonlinear Systems Modeling, Analysis and Simulation

CERN Document Server

Petráš, Ivo

2011-01-01

"Fractional-Order Nonlinear Systems: Modeling, Analysis and Simulation" presents a study of fractional-order chaotic systems accompanied by Matlab programs for simulating their state space trajectories, which are shown in the illustrations in the book. Description of the chaotic systems is clearly presented and their analysis and numerical solution are done in an easy-to-follow manner. Simulink models for the selected fractional-order systems are also presented. The readers will understand the fundamentals of the fractional calculus, how real dynamical systems can be described using fractional derivatives and fractional differential equations, how such equations can be solved, and how to simulate and explore chaotic systems of fractional order. The book addresses to mathematicians, physicists, engineers, and other scientists interested in chaos phenomena or in fractional-order systems. It can be used in courses on dynamical systems, control theory, and applied mathematics at graduate or postgraduate level. ...

A variable-order fractal derivative model for anomalous diffusion

Directory of Open Access Journals (Sweden)

Liu Xiaoting

2017-01-01

Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.

Aeroelastic simulation using CFD based reduced order models

International Nuclear Information System (INIS)

Zhang, W.; Ye, Z.; Li, H.; Yang, Q.

2005-01-01

This paper aims at providing an accurate and efficient method for aeroelastic simulation. System identification is used to get the reduced order models of unsteady aerodynamics. Unsteady Euler codes are used to compute the output signals while 3211 multistep input signals are utilized. LS(Least Squares) method is used to estimate the coefficients of the input-output difference model. The reduced order models are then used in place of the unsteady CFD code for aeroelastic simulation. The aeroelastic equations are marched by an improved 4th order Runge-Kutta method that only needs to compute the aerodynamic loads one time at every time step. The computed results agree well with that of the direct coupling CFD/CSD methods. The computational efficiency is improved 1∼2 orders while still retaining the high accuracy. A standard aeroelastic computing example (isogai wing) with S type flutter boundary is computed and analyzed. It is due to the system has more than one neutral points at the Mach range of 0.875∼0.9. (author)

Reverse time migration by Krylov subspace reduced order modeling

Science.gov (United States)

Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali

2018-04-01

Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.

Algebraic Specifications, Higher-order Types and Set-theoretic Models

DEFF Research Database (Denmark)

Kirchner, Hélène; Mosses, Peter David

2001-01-01

, and power-sets. This paper presents a simple framework for algebraic specifications with higher-order types and set-theoretic models. It may be regarded as the basis for a Horn-clause approximation to the Z framework, and has the advantage of being amenable to prototyping and automated reasoning. Standard......In most algebraic  specification frameworks, the type system is restricted to sorts, subsorts, and first-order function types. This is in marked contrast to the so-called model-oriented frameworks, which provide higer-order types, interpreted set-theoretically as Cartesian products, function spaces...... set-theoretic models are considered, and conditions are given for the existence of initial reduct's of such models. Algebraic specifications for various set-theoretic concepts are considered....

Pricing Exotic Options under a High-Order Markovian Regime Switching Model

Directory of Open Access Journals (Sweden)

Wai-Ki Ching

2007-10-01

Full Text Available We consider the pricing of exotic options when the price dynamics of the underlying risky asset are governed by a discrete-time Markovian regime-switching process driven by an observable, high-order Markov model (HOMM. We assume that the market interest rate, the drift, and the volatility of the underlying risky asset's return switch over time according to the states of the HOMM, which are interpreted as the states of an economy. We will then employ the well-known tool in actuarial science, namely, the Esscher transform to determine an equivalent martingale measure for option valuation. Moreover, we will also investigate the impact of the high-order effect of the states of the economy on the prices of some path-dependent exotic options, such as Asian options, lookback options, and barrier options.

Reduced order modeling of flashing two-phase jets

Energy Technology Data Exchange (ETDEWEB)

Gurecky, William, E-mail: william.gurecky@utexas.edu; Schneider, Erich, E-mail: eschneider@mail.utexas.edu; Ballew, Davis, E-mail: davisballew@utexas.edu

2015-12-01

Highlights: • Accident simulation requires ability to quickly predict two-phase flashing jet's damage potential. • A reduced order modeling methodology informed by experimental or computational data is described. • Zone of influence volumes are calculated for jets of various upstream thermodynamic conditions. - Abstract: In the event of a Loss of Coolant Accident (LOCA) in a pressurized water reactor, the escaping coolant produces a highly energetic flashing jet with the potential to damage surrounding structures. In LOCA analysis, the goal is often to evaluate many break scenarios in a Monte Carlo style simulation to evaluate the resilience of a reactor design. Therefore, in order to quickly predict the damage potential of flashing jets, it is of interest to develop a reduced order model that relates the damage potential of a jet to the pressure and temperature upstream of the break and the distance from the break to a given object upon which the jet is impinging. This work presents framework for producing a Reduced Order Model (ROM) that may be informed by measured data, Computational Fluid Dynamics (CFD) simulations, or a combination of both. The model is constructed by performing regression analysis on the pressure field data, allowing the impingement pressure to be quickly reconstructed for any given upstream thermodynamic condition within the range of input data. The model is applicable to both free and fully impinging two-phase flashing jets.

A stochastic phase-field model determined from molecular dynamics

KAUST Repository

von Schwerin, Erik

2010-03-17

The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.

A stochastic phase-field model determined from molecular dynamics

KAUST Repository

von Schwerin, Erik; Szepessy, Anders

2010-01-01

The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.

Reduced Order Modeling in General Relativity

Science.gov (United States)

Tiglio, Manuel

2014-03-01

Reduced Order Modeling is an emerging yet fast developing filed in gravitational wave physics. The main goals are to enable fast modeling and parameter estimation of any detected signal, along with rapid matched filtering detecting. I will focus on the first two. Some accomplishments include being able to replace, with essentially no lost of physical accuracy, the original models with surrogate ones (which are not effective ones, that is, they do not simplify the physics but go on a very different track, exploiting the particulars of the waveform family under consideration and state of the art dimensional reduction techniques) which are very fast to evaluate. For example, for EOB models they are at least around 3 orders of magnitude faster than solving the original equations, with physically equivalent results. For numerical simulations the speedup is at least 11 orders of magnitude. For parameter estimation our current numbers are about bringing ~100 days for a single SPA inspiral binary neutron star Bayesian parameter estimation analysis to under a day. More recently, it has been shown that the full precessing problem for, say, 200 cycles, can be represented, through some new ideas, by a remarkably compact set of carefully chosen reduced basis waveforms (~10-100, depending on the accuracy requirements). I will highlight what I personally believe are the challenges to face next in this subarea of GW physics and where efforts should be directed. This talk will summarize work in collaboration with: Harbir Antil (GMU), Jonathan Blackman (Caltech), Priscila Canizares (IoA, Cambridge, UK), Sarah Caudill (UWM), Jonathan Gair (IoA. Cambridge. UK), Scott Field (UMD), Chad R. Galley (Caltech), Frank Herrmann (Germany), Han Hestahven (EPFL, Switzerland), Jason Kaye (Brown, Stanford & Courant). Evan Ochsner (UWM), Ricardo Nochetto (UMD), Vivien Raymond (LIGO, Caltech), Rory Smith (LIGO, Caltech) Bela Ssilagyi (Caltech) and MT (UMD & Caltech).

Partial-Order Reduction for GPU Model Checking

NARCIS (Netherlands)

Neele, T.; Wijs, A.; Bosnacki, D.; van de Pol, Jan Cornelis; Artho, C; Legay, A.; Peled, D.

2016-01-01

Model checking using GPUs has seen increased popularity over the last years. Because GPUs have a limited amount of memory, only small to medium-sized systems can be verified. For on-the-fly explicit-state model checking, we improve memory efficiency by applying partial-order reduction. We propose

Validity testing of third-order nonlinear models for synchronous generators

Energy Technology Data Exchange (ETDEWEB)

Arjona, M.A. [Division de Estudios de Posgrado e Investigacion, Instituto Tecnologico de La Laguna Torreon, Coah. (Mexico); Escarela-Perez, R. [Universidad Autonoma Metropolitana - Azcapotzalco, Departamento de Energia, Av. San Pablo 180, Col. Reynosa, C.P. 02200 (Mexico); Espinosa-Perez, G. [Division de Estudios Posgrado de la Facultad de Ingenieria Universidad Nacional Autonoma de Mexico (Mexico); Alvarez-Ramirez, J. [Universidad Autonoma Metropolitana -Iztapalapa, Division de Ciencias Basicas e Ingenieria (Mexico)

2009-06-15

Third-order nonlinear models are commonly used in control theory for the analysis of the stability of both open-loop and closed-loop synchronous machines. However, the ability of these models to describe the electrical machine dynamics has not been tested experimentally. This work focuses on this issue by addressing the parameters identification problem for third-order models for synchronous generators. For a third-order model describing the dynamics of power angle {delta}, rotor speed {omega} and quadrature axis transient EMF E{sub q}{sup '}, it is shown that the parameters cannot be identified because of the effects of the unknown initial condition of E{sub q}{sup '}. To avoid this situation, a model that incorporates the measured electrical power dynamics is considered, showing that state measurements guarantee the identification of the model parameters. Data obtained from a 7 kVA lab-scale synchronous generator and from a 150 MVA finite-element simulation were used to show that, at least for the worked examples, the estimated parameters display only moderate variations over the operating region. This suggests that third-order models can suffice to describe the main dynamical features of synchronous generators, and that third-order models can be used to design and tune power system stabilizers and voltage regulators. (author)

Lagrangian generic second order traffic flow models for node

Directory of Open Access Journals (Sweden)

Asma Khelifi

2018-02-01

Full Text Available This study sheds light on higher order macroscopic traffic flow modeling on road networks, thanks to the generic second order models (GSOM family which embeds a myriad of traffic models. It has been demonstrated that such higher order models are easily solved in Lagrangian coordinates which are compatible with both microscopic and macroscopic descriptions. The generalized GSOM model is reformulated in the Lagrangian coordinate system to develop a more efficient numerical method. The difficulty in applying this approach on networks basically resides in dealing with node dynamics. Traffic flow characteristics at node are different from that on homogeneous links. Different geometry features can lead to different critical research issues. For instance, discontinuity in traffic stream can be an important issue for traffic signal operations, while capacity drop may be crucial for lane-merges. The current paper aims to establish and analyze a new adapted node model for macroscopic traffic flow models by applying upstream and downstream boundary conditions on the Lagrangian coordinates in order to perform simulations on networks of roads, and accompanying numerical method. The internal node dynamics between upstream and downstream links are taken into account of the node model. Therefore, a numerical example is provided to underscore the efficiency of this approach. Simulations show that the discretized node model yields accurate results. Additional kinematic waves and contact discontinuities are induced by the variation of the driver attribute.

Partial Orders and Fully Abstract Models for Concurrency

DEFF Research Database (Denmark)

Engberg, Uffe Henrik

1990-01-01

In this thesis sets of labelled partial orders are employed as fundamental mathematical entities for modelling nondeterministic and concurrent processes thereby obtaining so-called noninterleaving semantics. Based on different closures of sets of labelled partial orders, simple algebraic language...

Height determination at the transfer unit in isotopic distillation of hydrogen on type B7 ordered column packing

International Nuclear Information System (INIS)

Pop, F.; Croitoru, C.; Peculea, M.

2001-01-01

Owing to the low pressure drop implied by ordered column packings these are often utilized for vacuum distillations and separation of mixtures in which the important component occurs at a very low concentration, as for instance is the case of water, deuterium or oxygen isotopic distillation. The paper presents a model for determination of the height of transfer unit (HTU) in the hydrogen isotopic distillation installation, equipped with ordered column packing of B7 type. The computed values for HUT based on the analogy between heat, moment and mass transfer, were compared with the experimental data

Comparisons of Modeling and State of Charge Estimation for Lithium-Ion Battery Based on Fractional Order and Integral Order Methods

Directory of Open Access Journals (Sweden)

Renxin Xiao

2016-03-01

Full Text Available In order to properly manage lithium-ion batteries of electric vehicles (EVs, it is essential to build the battery model and estimate the state of charge (SOC. In this paper, the fractional order forms of Thevenin and partnership for a new generation of vehicles (PNGV models are built, of which the model parameters including the fractional orders and the corresponding resistance and capacitance values are simultaneously identified based on genetic algorithm (GA. The relationships between different model parameters and SOC are established and analyzed. The calculation precisions of the fractional order model (FOM and integral order model (IOM are validated and compared under hybrid test cycles. Finally, extended Kalman filter (EKF is employed to estimate the SOC based on different models. The results prove that the FOMs can simulate the output voltage more accurately and the fractional order EKF (FOEKF can estimate the SOC more precisely under dynamic conditions.

Higher-order RANS turbulence models for separated flows

Data.gov (United States)

National Aeronautics and Space Administration — Higher-order Reynolds-averaged Navier-Stokes (RANS) models are developed to overcome the shortcomings of second-moment RANS models in predicting separated flows....

Ground-state ordering of the J1-J2 model on the simple cubic and body-centered cubic lattices

Science.gov (United States)

Farnell, D. J. J.; Götze, O.; Richter, J.

2016-06-01

The J1-J2 Heisenberg model is a "canonical" model in the field of quantum magnetism in order to study the interplay between frustration and quantum fluctuations as well as quantum phase transitions driven by frustration. Here we apply the coupled cluster method (CCM) to study the spin-half J1-J2 model with antiferromagnetic nearest-neighbor bonds J1>0 and next-nearest-neighbor bonds J2>0 for the simple cubic (sc) and body-centered cubic (bcc) lattices. In particular, we wish to study the ground-state ordering of these systems as a function of the frustration parameter p =z2J2/z1J1 , where z1 (z2) is the number of nearest (next-nearest) neighbors. We wish to determine the positions of the phase transitions using the CCM and we aim to resolve the nature of the phase transition points. We consider the ground-state energy, order parameters, spin-spin correlation functions, as well as the spin stiffness in order to determine the ground-state phase diagrams of these models. We find a direct first-order phase transition at a value of p =0.528 from a state of nearest-neighbor Néel order to next-nearest-neighbor Néel order for the bcc lattice. For the sc lattice the situation is more subtle. CCM results for the energy, the order parameter, the spin-spin correlation functions, and the spin stiffness indicate that there is no direct first-order transition between ground-state phases with magnetic long-range order, rather it is more likely that two phases with antiferromagnetic long range are separated by a narrow region of a spin-liquid-like quantum phase around p =0.55 . Thus the strong frustration present in the J1-J2 Heisenberg model on the sc lattice may open a window for an unconventional quantum ground state in this three-dimensional spin model.

Study of higher order cumulant expansion of U(1) lattice gauge model at finite temperature

International Nuclear Information System (INIS)

Zheng Xite; Lei Chunhong; Li Yuliang; Chen Hong

1993-01-01

The order parameter, Polyakov line , of the U(1) gauge model on N σ 3 x N τ (N τ = 1) lattice by using the cumulant expansion is calculated to the 5-th order. The emphasis is put on the behaviour of the cumulant expansion in the intermediate coupling region. The necessity of higher order expansion is clarified from the connection between the cumulant expansion and the correlation length. The variational parameter in the n-th order calculation is determined by the requirement that corrections of the n-th order expansion to the zeroth order expansion finish. The agreement with the Monte Carlo simulation is obtained not only in the weak and strong coupling regions, but also in the intermediate coupling region except in the very vicinity of the phase transition point

Optimal inventory management and order book modeling

KAUST Repository

Baradel, Nicolas

2018-02-16

We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.

Odd-order o.d.f. expansion coefficient determination. Case of diffraction strain measurements on cubic materials under macrostress loading

International Nuclear Information System (INIS)

Brakman, C.M.

1985-01-01

Diffraction intensity pole figures are often used for the determination of orientation distribution function (o.d.f.) expansion coefficients. The intensity can be seen as a convolution of the o.d.f. times unity with respect to one rotation angle (about the direction of measurement). The 'normal' polycrystalline diffraction experiment only yields the even-order o.d.f. coefficients. The experiment itself imposes a centre of inversion even upon non-centrosymmetric crystals. Crystals may exhibit a centre of inversion themselves. The hkl and anti hanti kanti l contributions to the intensity are indistinguishable then owing to the centre of inversion. As a consequence, the odd-order coefficients cannot be determined. The mean value of a general physical property determined by means of diffraction can be taken as a convolution of the o.d.f. times the single-crystal value of the physical property with respect to the rotation angle mentioned before. The dependency of the physical property on the rotation angle leads to more information being extracted from the o.d.f. in the property's mean-value pole figure. Then, all o.d.f. coefficients may be present in the mean value, i.e. the measurement. Consequently, diffraction-line-shift strain pole figures exhibit even- and odd-order o.d.f. coefficients, present or induced centres of inversion notwithstanding. If the dependency of the single-crystal strain on the rotation angle is known no model of elastic polycrystal coupling is needed. However, this does not occur in practice. The present state of the art does not allow the Kroener model to be used for textured materials. In this paper the Reuss model is used. If the (applied) macrostresses are known, the o.d.f. coefficients can be obtained from the formulae presented. (orig.)

Reduced-order modelling of wind turbines

NARCIS (Netherlands)

Elkington, K.; Slootweg, J.G.; Ghandhari, M.; Kling, W.L.; Ackermann, T.

2012-01-01

In this chapter power system dynamics simulation(PSDS) isused to study the dynamics of large-scale power systems. It is necessary to incorporate models of wind turbine generating systems into PSDS software packages in order to analyse the impact of high wind power penetration on electrical power

A MATHEMATICAL MODELLING APPROACH TO ONE-DAY CRICKET BATTING ORDERS

Directory of Open Access Journals (Sweden)

Matthews Ovens1

2006-12-01

Full Text Available While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players

Model order reduction techniques with applications in finite element analysis

CERN Document Server

Qu, Zu-Qing

2004-01-01

Despite the continued rapid advance in computing speed and memory the increase in the complexity of models used by engineers persists in outpacing them. Even where there is access to the latest hardware, simulations are often extremely computationally intensive and time-consuming when full-blown models are under consideration. The need to reduce the computational cost involved when dealing with high-order/many-degree-of-freedom models can be offset by adroit computation. In this light, model-reduction methods have become a major goal of simulation and modeling research. Model reduction can also ameliorate problems in the correlation of widely used finite-element analyses and test analysis models produced by excessive system complexity. Model Order Reduction Techniques explains and compares such methods focusing mainly on recent work in dynamic condensation techniques: - Compares the effectiveness of static, exact, dynamic, SEREP and iterative-dynamic condensation techniques in producing valid reduced-order mo...

A Meta-Analysis to Determine the Impact of Restaurant Menu Labeling on Calories and Nutrients (Ordered or Consumed) in U.S. Adults.

Science.gov (United States)

Cantu-Jungles, Thaisa M; McCormack, Lacey A; Slaven, James E; Slebodnik, Maribeth; Eicher-Miller, Heather A

2017-09-30

A systematic review and meta-analysis determined the effect of restaurant menu labeling on calories and nutrients chosen in laboratory and away-from-home settings in U.S. adults. Cochrane-based criteria adherent, peer-reviewed study designs conducted and published in the English language from 1950 to 2014 were collected in 2015, analyzed in 2016, and used to evaluate the effect of nutrition labeling on calories and nutrients ordered or consumed. Before and after menu labeling outcomes were used to determine weighted mean differences in calories, saturated fat, total fat, carbohydrate, and sodium ordered/consumed which were pooled across studies using random effects modeling. Stratified analysis for laboratory and away-from-home settings were also completed. Menu labeling resulted in no significant change in reported calories ordered/consumed in studies with full criteria adherence, nor the 14 studies analyzed with ≤1 unmet criteria, nor for change in total ordered carbohydrate, fat, and saturated fat (three studies) or ordered or consumed sodium (four studies). A significant reduction of 115.2 calories ordered/consumed in laboratory settings was determined when analyses were stratified by study setting. Menu labeling away-from-home did not result in change in quantity or quality, specifically for carbohydrates, total fat, saturated fat, or sodium, of calories consumed among U.S. adults.

The second-order decomposition model of nonlinear irregular waves

DEFF Research Database (Denmark)

Yang, Zhi Wen; Bingham, Harry B.; Li, Jin Xuan

2013-01-01

into the first- and the second-order super-harmonic as well as the second-order sub-harmonic components by transferring them into an identical Fourier frequency-space and using a Newton-Raphson iteration method. In order to evaluate the present model, a variety of monochromatic waves and the second...

Transport coefficient computation based on input/output reduced order models

Science.gov (United States)

Hurst, Joshua L.

The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator

A parametric model order reduction technique for poroelastic finite element models.

Science.gov (United States)

Lappano, Ettore; Polanz, Markus; Desmet, Wim; Mundo, Domenico

2017-10-01

This research presents a parametric model order reduction approach for vibro-acoustic problems in the frequency domain of systems containing poroelastic materials (PEM). The method is applied to the Finite Element (FE) discretization of the weak u-p integral formulation based on the Biot-Allard theory and makes use of reduced basis (RB) methods typically employed for parametric problems. The parametric reduction is obtained rewriting the Biot-Allard FE equations for poroelastic materials using an affine representation of the frequency (therefore allowing for RB methods) and projecting the frequency-dependent PEM system on a global reduced order basis generated with the proper orthogonal decomposition instead of standard modal approaches. This has proven to be better suited to describe the nonlinear frequency dependence and the strong coupling introduced by damping. The methodology presented is tested on two three-dimensional systems: in the first experiment, the surface impedance of a PEM layer sample is calculated and compared with results of the literature; in the second, the reduced order model of a multilayer system coupled to an air cavity is assessed and the results are compared to those of the reference FE model.

Spectrophotometric determination of chlorthalidone in pharmaceutical formulations using different order derivative methods

Directory of Open Access Journals (Sweden)

Narmeen S. Abdullah

2017-05-01

Full Text Available Simple, repaid and accurate zero-, first- and second-order derivative spectrophotometric methods have been developed for determination of chlorthalidone (CLT in commercially available tablets. Normal spectrophotometric scan (zero order shows maximum absorbance at 276 nm in methanol solution and a good linearity in the range of 10.0–75.0 μg/mL. Linear relations using first (D1 and second (D2 order derivative methods were obtained at 278 and 288 nm for D1 and 286 and 292 nm for D2.The calibration curves were constructed in the range of 1.0–25.0 μg/mL for D1 (R = 0.998 and D2 (R = 0.999. Different analytical validations were determined (accuracy, precision, specificity, recovery, stability and robustness to demonstrate its suitability for routine quality control labs. All the developed methods were successfully applied to a tablet formulation and the results were compared statistically with each other and with those obtained by the HPLC reference method.

EXAFS, Determination of Short Range Order and Local Structures in Materials

NARCIS (Netherlands)

Koningsberger, D.C.; Prins, R.

1981-01-01

Extended X-ray Absorption Fine Structure (EXAFS) is a powerful method of determining short range order and local structures in materials using X-ray photons produced by a synchrotron light source, or in-house by a high intensity rotating anode X-ray generator. The technique has provided valuable

Low-order aeroelastic models of wind turbines for controller design

DEFF Research Database (Denmark)

Sønderby, Ivan Bergquist

Wind turbine controllers are used to optimize the performance of wind turbines such as to reduce power variations and fatigue and extreme loads on wind turbine components. Accurate tuning and design of modern controllers must be done using low-order models that accurately captures the aeroelastic...... response of the wind turbine. The purpose of this thesis is to investigate the necessary model complexity required in aeroelastic models used for controller design and to analyze and propose methods to design low-order aeroelastic wind turbine models that are suited for model-based control design....... The thesis contains a characterization of the dynamics that influence the open-loop aeroelastic frequency response of a modern wind turbine, based on a high-order aeroelastic wind turbine model. One main finding is that the transfer function from collective pitch to generator speed is affected by two low...

REGIONAL FIRST ORDER PERIODIC AUTOREGRESSIVE MODELS FOR MONTHLY FLOWS

Directory of Open Access Journals (Sweden)

Ceyhun ÖZÇELİK

2008-01-01

Full Text Available First order periodic autoregressive models is of mostly used models in modeling of time dependency of hydrological flow processes. In these models, periodicity of the correlogram is preserved as well as time dependency of processes. However, the parameters of these models, namely, inter-monthly lag-1 autocorrelation coefficients may be often estimated erroneously from short samples, since they are statistics of high order moments. Therefore, to constitute a regional model may be a solution that can produce more reliable and decisive estimates, and derive models and model parameters in any required point of the basin considered. In this study, definitions of homogeneous region for lag-1 autocorrelation coefficients are made; five parametric and non parametric models are proposed to set regional models of lag-1 autocorrelation coefficients. Regional models are applied on 30 stream flow gauging stations in Seyhan and Ceyhan basins, and tested by criteria of relative absolute bias, simple and relative root of mean square errors.

SOLVING FRACTIONAL-ORDER COMPETITIVE LOTKA-VOLTERRA MODEL BY NSFD SCHEMES

Directory of Open Access Journals (Sweden)

S.ZIBAEI

2016-12-01

Full Text Available In this paper, we introduce fractional-order into a model competitive Lotka- Volterra prey-predator system. We will discuss the stability analysis of this fractional system. The non-standard nite difference (NSFD scheme is implemented to study the dynamic behaviors in the fractional-order Lotka-Volterra system. Proposed non-standard numerical scheme is compared with the forward Euler and fourth order Runge-Kutta methods. Numerical results show that the NSFD approach is easy and accurate for implementing when applied to fractional-order Lotka-Volterra model.

Accelerating transient simulation of linear reduced order models.

Energy Technology Data Exchange (ETDEWEB)

Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad

2011-10-01

Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.

Ordering parameters of three-dimensional ordered quantum-dot lattices determined by anomalous x-ray diffraction

International Nuclear Information System (INIS)

Lechner, R.T.; Springholz, G.; Stangl, J.; Raab, A.; Bauer, G.; Schuelli, T.U.; Holy, V.; Metzger, T.H.

2004-01-01

Three dimensional (3D) quantum dot structures can be obtained, e.g., by the growth of self-assembled quantum dot multilayers in which vertically and laterally ordered dot superstructures are formed as a result of the elastic interlayer dot interactions between the dots. This not only results in a significant narrowing of the size distribution, but different 3D interlayer correlations can be obtained by changes in the spacer thickness, as has been demonstrated for the PbSe/PbEuTe quantum dot material system. Apart from microscopic techniques, x-ray diffraction is a very powerful tool to characterize the ordering in such 3D assembled quantum dot structures. However, the analysis of the diffraction spectra is usually complicated by the weak scattering contrast between the self-assembled quantum dots and the surrounding matrix material. In the present work, we therefore employ anomalous x-ray diffraction with synchrotron radiation to drastically enhance the chemical contrast in such multilayers by tuning the wavelength close to an inner shell absorption resonance. This technique is applied to determine the ordering of differently stacked self-assembled PbSe quantum dot lattices fabricated by molecular beam epitaxy. In this case, the x-ray wavelength is tuned to the Pb M-shell at 5.1 Aato enhance the scattering contrast between the PbSe dots and the matrix material in comparison to the results obtained using conventional x-ray wavelengths around 1.5 Aa. As a result, it is shown that the lateral ordering is significantly better for 3D trigonal PbSe dot superlattices as compared to those with 3D hexagonal dot arrangement. (author)

Efficient Model Order Reduction for the Dynamics of Nonlinear Multilayer Sheet Structures with Trial Vector Derivatives

Directory of Open Access Journals (Sweden)

Wolfgang Witteveen

2014-01-01

Full Text Available The mechanical response of multilayer sheet structures, such as leaf springs or car bodies, is largely determined by the nonlinear contact and friction forces between the sheets involved. Conventional computational approaches based on classical reduction techniques or the direct finite element approach have an inefficient balance between computational time and accuracy. In the present contribution, the method of trial vector derivatives is applied and extended in order to obtain a-priori trial vectors for the model reduction which are suitable for determining the nonlinearities in the joints of the reduced system. Findings show that the result quality in terms of displacements and contact forces is comparable to the direct finite element method but the computational effort is extremely low due to the model order reduction. Two numerical studies are presented to underline the method’s accuracy and efficiency. In conclusion, this approach is discussed with respect to the existing body of literature.

Higher Order, Hybrid BEM/FEM Methods Applied to Antenna Modeling

Science.gov (United States)

Fink, P. W.; Wilton, D. R.; Dobbins, J. A.

2002-01-01

In this presentation, the authors address topics relevant to higher order modeling using hybrid BEM/FEM formulations. The first of these is the limitation on convergence rates imposed by geometric modeling errors in the analysis of scattering by a dielectric sphere. The second topic is the application of an Incomplete LU Threshold (ILUT) preconditioner to solve the linear system resulting from the BEM/FEM formulation. The final tOpic is the application of the higher order BEM/FEM formulation to antenna modeling problems. The authors have previously presented work on the benefits of higher order modeling. To achieve these benefits, special attention is required in the integration of singular and near-singular terms arising in the surface integral equation. Several methods for handling these terms have been presented. It is also well known that achieving he high rates of convergence afforded by higher order bases may als'o require the employment of higher order geometry models. A number of publications have described the use of quadratic elements to model curved surfaces. The authors have shown in an EFIE formulation, applied to scattering by a PEC .sphere, that quadratic order elements may be insufficient to prevent the domination of modeling errors. In fact, on a PEC sphere with radius r = 0.58 Lambda(sub 0), a quartic order geometry representation was required to obtain a convergence benefi.t from quadratic bases when compared to the convergence rate achieved with linear bases. Initial trials indicate that, for a dielectric sphere of the same radius, - requirements on the geometry model are not as severe as for the PEC sphere. The authors will present convergence results for higher order bases as a function of the geometry model order in the hybrid BEM/FEM formulation applied to dielectric spheres. It is well known that the system matrix resulting from the hybrid BEM/FEM formulation is ill -conditioned. For many real applications, a good preconditioner is required

Low order physical models of vertical axis wind turbines

Science.gov (United States)

Craig, Anna; Dabiri, John; Koseff, Jeffrey

2016-11-01

In order to examine the ability of low-order physical models of vertical axis wind turbines to accurately reproduce key flow characteristics, experiments were conducted on rotating turbine models, rotating solid cylinders, and stationary porous flat plates (of both uniform and non-uniform porosities). From examination of the patterns of mean flow, the wake turbulence spectra, and several quantitative metrics, it was concluded that the rotating cylinders represent a reasonably accurate analog for the rotating turbines. In contrast, from examination of the patterns of mean flow, it was found that the porous flat plates represent only a limited analog for rotating turbines (for the parameters examined). These findings have implications for both laboratory experiments and numerical simulations, which have previously used analogous low order models in order to reduce experimental/computational costs. NSF GRF and SGF to A.C; ONR N000141211047 and the Gordon and Betty Moore Foundation Grant GBMF2645 to J.D.; and the Bob and Norma Street Environmental Fluid Mechanics Laboratory at Stanford University.

A Mathematical Modelling Approach to One-Day Cricket Batting Orders

Science.gov (United States)

Bukiet, Bruce; Ovens, Matthews

2006-01-01

While scoring strategies and player performance in cricket have been studied, there has been little published work about the influence of batting order with respect to One-Day cricket. We apply a mathematical modelling approach to compute efficiently the expected performance (runs distribution) of a cricket batting order in an innings. Among other applications, our method enables one to solve for the probability of one team beating another or to find the optimal batting order for a set of 11 players. The influence of defence and bowling ability can be taken into account in a straightforward manner. In this presentation, we outline how we develop our Markov Chain approach to studying the progress of runs for a batting order of non- identical players along the lines of work in baseball modelling by Bukiet et al., 1997. We describe the issues that arise in applying such methods to cricket, discuss ideas for addressing these difficulties and note limitations on modelling batting order for One-Day cricket. By performing our analysis on a selected subset of the possible batting orders, we apply the model to quantify the influence of batting order in a game of One Day cricket using available real-world data for current players. Key Points Batting order does effect the expected runs distribution in one-day cricket. One-day cricket has fewer data points than baseball, thus extreme values have greater effect on estimated probabilities. Dismissals rare and probabilities very small by comparison to baseball. Probability distribution for lower order batsmen is potentially skewed due to increased risk taking. Full enumeration of all possible line-ups is impractical using a single average computer. PMID:24357943

Detecting memory and structure in human navigation patterns using Markov chain models of varying order.

Science.gov (United States)

Singer, Philipp; Helic, Denis; Taraghi, Behnam; Strohmaier, Markus

2014-01-01

One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form) and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.

Detecting memory and structure in human navigation patterns using Markov chain models of varying order.

Directory of Open Access Journals (Sweden)

Philipp Singer

Full Text Available One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.

A system dynamics model to determine products mix

Directory of Open Access Journals (Sweden)

Mahtab Hajghasem

2014-02-01

Full Text Available This paper presents an implementation of system dynamics model to determine appropriate product mix by considering various factors such as labor, materials, overhead, etc. for an Iranian producer of cosmetic and sanitary products. The proposed model of this paper considers three hypotheses including the relationship between product mix and profitability, optimum production capacity and having minimum amount of storage to take advantage of low cost production. The implementation of system dynamics on VENSIM software package has confirmed all three hypotheses of the survey and suggested that in order to reach better mix product, it is necessary to reach optimum production planning, take advantage of all available production capacities and use inventory management techniques.

Antiferromagnetic order in the Hubbard model on the Penrose lattice

Science.gov (United States)

Koga, Akihisa; Tsunetsugu, Hirokazu

2017-12-01

We study an antiferromagnetic order in the ground state of the half-filled Hubbard model on the Penrose lattice and investigate the effects of quasiperiodic lattice structure. In the limit of infinitesimal Coulomb repulsion U →+0 , the staggered magnetizations persist to be finite, and their values are determined by confined states, which are strictly localized with thermodynamics degeneracy. The magnetizations exhibit an exotic spatial pattern, and have the same sign in each of cluster regions, the size of which ranges from 31 sites to infinity. With increasing U , they continuously evolve to those of the corresponding spin model in the U =∞ limit. In both limits of U , local magnetizations exhibit a fairly intricate spatial pattern that reflects the quasiperiodic structure, but the pattern differs between the two limits. We have analyzed this pattern change by a mode analysis by the singular value decomposition method for the fractal-like magnetization pattern projected into the perpendicular space.

Optimal inventory management and order book modeling

KAUST Repository

Baradel, Nicolas; Bouchard, Bruno; Evangelista, David; Mounjid, Othmane

2018-01-01

We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic

PD/PID controller tuning based on model approximations: Model reduction of some unstable and higher order nonlinear models

Directory of Open Access Journals (Sweden)

Christer Dalen

2017-10-01

Full Text Available A model reduction technique based on optimization theory is presented, where a possible higher order system/model is approximated with an unstable DIPTD model by using only step response data. The DIPTD model is used to tune PD/PID controllers for the underlying possible higher order system. Numerous examples are used to illustrate the theory, i.e. both linear and nonlinear models. The Pareto Optimal controller is used as a reference controller.

The Ising model coupled to 2d orders

Science.gov (United States)

Glaser, Lisa

2018-04-01

In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter β and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in Surya (2012 Class. Quantum Grav. 29 132001) and the Ising model can be correlated or uncorrelated on the random orders and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.

Generalized modeling of the fractional-order memcapacitor and its character analysis

Science.gov (United States)

Guo, Zhang; Si, Gangquan; Diao, Lijie; Jia, Lixin; Zhang, Yanbin

2018-06-01

Memcapacitor is a new type of memory device generalized from the memristor. This paper proposes a generalized fractional-order memcapacitor model by introducing the fractional calculus into the model. The generalized formulas are studied and the two fractional-order parameter α, β are introduced where α mostly affects the fractional calculus value of charge q within the generalized Ohm's law and β generalizes the state equation which simulates the physical mechanism of a memcapacitor into the fractional sense. This model will be reduced to the conventional memcapacitor as α = 1 , β = 0 and to the conventional memristor as α = 0 , β = 1 . Then the numerical analysis of the fractional-order memcapacitor is studied. And the characteristics and output behaviors of the fractional-order memcapacitor applied with sinusoidal charge are derived. The analysis results have shown that there are four basic v - q and v - i curve patterns when the fractional order α, β respectively equal to 0 or 1, moreover all v - q and v - i curves of the other fractional-order models are transition curves between the four basic patterns.

Latent Partially Ordered Classification Models and Normal Mixtures

Science.gov (United States)

Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith

2013-01-01

Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…

Understanding agent-based models of financial markets: A bottom-up approach based on order parameters and phase diagrams

Science.gov (United States)

Lye, Ribin; Tan, James Peng Lung; Cheong, Siew Ann

2012-11-01

We describe a bottom-up framework, based on the identification of appropriate order parameters and determination of phase diagrams, for understanding progressively refined agent-based models and simulations of financial markets. We illustrate this framework by starting with a deterministic toy model, whereby N independent traders buy and sell M stocks through an order book that acts as a clearing house. The price of a stock increases whenever it is bought and decreases whenever it is sold. Price changes are updated by the order book before the next transaction takes place. In this deterministic model, all traders based their buy decisions on a call utility function, and all their sell decisions on a put utility function. We then make the agent-based model more realistic, by either having a fraction fb of traders buy a random stock on offer, or a fraction fs of traders sell a random stock in their portfolio. Based on our simulations, we find that it is possible to identify useful order parameters from the steady-state price distributions of all three models. Using these order parameters as a guide, we find three phases: (i) the dead market; (ii) the boom market; and (iii) the jammed market in the phase diagram of the deterministic model. Comparing the phase diagrams of the stochastic models against that of the deterministic model, we realize that the primary effect of stochasticity is to eliminate the dead market phase.

The Meaning of Higher-Order Factors in Reflective-Measurement Models

Science.gov (United States)

Eid, Michael; Koch, Tobias

2014-01-01

Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…

Comparing higher order models for the EORTC QLQ-C30

DEFF Research Database (Denmark)

Gundy, Chad M; Fayers, Peter M; Grønvold, Mogens

2012-01-01

To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire.......To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire....

Compact state-space models for complex superconducting radio-frequency structures based on model order reduction and concatenation methods

International Nuclear Information System (INIS)

Flisgen, Thomas

2015-01-01

The modeling of large chains of superconducting cavities with couplers is a challenging task in computational electrical engineering. The direct numerical treatment of these structures can easily lead to problems with more than ten million degrees of freedom. Problems of this complexity are typically solved with the help of parallel programs running on supercomputing infrastructures. However, these infrastructures are expensive to purchase, to operate, and to maintain. The aim of this thesis is to introduce and to validate an approach which allows for modeling large structures on a standard workstation. The novel technique is called State-Space Concatenations and is based on the decomposition of the complete structure into individual segments. The radio-frequency properties of the generated segments are described by a set of state-space equations which either emerge from analytical considerations or from numerical discretization schemes. The model order of these equations is reduced using dedicated model order reduction techniques. In a final step, the reduced-order state-space models of the segments are concatenated in accordance with the topology of the complete structure. The concatenation is based on algebraic continuity constraints of electric and magnetic fields on the decomposition planes and results in a compact state-space system of the complete radio-frequency structure. Compared to the original problem, the number of degrees of freedom is drastically reduced, i.e. a problem with more than ten million degrees of freedom can be reduced on a standard workstation to a problem with less than one thousand degrees of freedom. The final state-space system allows for determining frequency-domain transfer functions, field distributions, resonances, and quality factors of the complete structure in a convenient manner. This thesis presents the theory of the state-space concatenation approach and discusses several validation and application examples. The examples

Stability and Hopf Bifurcation of Fractional-Order Complex-Valued Single Neuron Model with Time Delay

Science.gov (United States)

Wang, Zhen; Wang, Xiaohong; Li, Yuxia; Huang, Xia

2017-12-01

In this paper, the problems of stability and Hopf bifurcation in a class of fractional-order complex-valued single neuron model with time delay are addressed. With the help of the stability theory of fractional-order differential equations and Laplace transforms, several new sufficient conditions, which ensure the stability of the system are derived. Taking the time delay as the bifurcation parameter, Hopf bifurcation is investigated and the critical value of the time delay for the occurrence of Hopf bifurcation is determined. Finally, two representative numerical examples are given to show the effectiveness of the theoretical results.

Second-order kinetic model for the sorption of cadmium onto tree fern: a comparison of linear and non-linear methods.

Science.gov (United States)

Ho, Yuh-Shan

2006-01-01

A comparison was made of the linear least-squares method and a trial-and-error non-linear method of the widely used pseudo-second-order kinetic model for the sorption of cadmium onto ground-up tree fern. Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. A type 1 pseudo-second-order linear kinetic model has the highest coefficient of determination. Results show that the non-linear method may be a better way to obtain the desired parameters.

Lattice Boltzmann model for high-order nonlinear partial differential equations.

Science.gov (United States)

Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang

2018-01-01

In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂_{t}ϕ+∑_{k=1}^{m}α_{k}∂_{x}^{k}Π_{k}(ϕ)=0 (1≤k≤m≤6), α_{k} are constant coefficients, Π_{k}(ϕ) are some known differential functions of ϕ. As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K(n,n)-Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009)1672-179910.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009)PHYADX0378-437110.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.

Lattice Boltzmann model for high-order nonlinear partial differential equations

Science.gov (United States)

Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang

2018-01-01

In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂tϕ +∑k=1mαk∂xkΠk(ϕ ) =0 (1 ≤k ≤m ≤6 ), αk are constant coefficients, Πk(ϕ ) are some known differential functions of ϕ . As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K (n ,n ) -Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009), 10.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009), 10.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.

Covariant quantization of infinite spin particle models, and higher order gauge theories

International Nuclear Information System (INIS)

Edgren, Ludde; Marnelius, Robert

2006-01-01

Further properties of a recently proposed higher order infinite spin particle model are derived. Infinitely many classically equivalent but different Hamiltonian formulations are shown to exist. This leads to a condition of uniqueness in the quantization process. A consistent covariant quantization is shown to exist. Also a recently proposed supersymmetric version for half-odd integer spins is quantized. A general algorithm to derive gauge invariances of higher order Lagrangians is given and applied to the infinite spin particle model, and to a new higher order model for a spinning particle which is proposed here, as well as to a previously given higher order rigid particle model. The latter two models are also covariantly quantized

Group theory for magnetic structure determination: Recent developments and quadrupolar ordering analysis

Energy Technology Data Exchange (ETDEWEB)

Sikora, W. [Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, al.Mickiewicza 30, 30-059 Cracow (Poland)]. E-mail: sikora@novell.ftj.agh.edu.pl; Pytlik, L. [Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, al.Mickiewicza 30, 30-059 Cracow (Poland); Bialas, F. [Nowy Sacz School of Busines-National Louis University, 33-300 Nowy Sacz (Poland); Malinowski, J. [Faculty of Physics and Applied Computer Science, AGH-University of Science and Technology, al.Mickiewicza 30, 30-059 Cracow (Poland)

2007-09-13

In this paper, the recent developments in practical applications of symmetry analysis are described. The theoretical basis shortly described in Section 1 has been implemented in several computer applications, one of which is the program 'MODY-win', developed by the authors of the paper. The program calculates the so-called basis vectors of irreducible representations of a given symmetry group, which can be used for calculation of possible ordering modes. Its practical application is demonstrated on some examples, presenting the recent aspects of using the symmetry analysis to description of various types of ordering encountered in solids. The scalar-type ordering (occupation probability) is discussed shortly for occupation of interstitial sites by hydrogen atoms in inter-metallic compounds. The description of vector ordering is demonstrated on the magnetic ordering modes, with special attention focused on the freedom that is left in the structure after imposing all the symmetry constraints. In practice, the final ordering mode usually contains some free parameters that cannot be determined from the symmetry itself. The last application presented in the paper is the description of quadrupolar ordering, recently found in some compounds of 4f (5f) elements. For the latter case, an additional advantage is demonstrated by calculation of possible displacements of neighboring atoms after the establishment of non-zero quadrupolar order parameter on the central atom.

Experimental determination of order in non-equilibrium solids using colloidal gels

International Nuclear Information System (INIS)

Gao Yongxiang; Kilfoil, Maria

2004-01-01

The idea of quantifying order in disordered systems has been introduced recently by Torquato and co-workers (2000 Phys. Rev. E 62 993-1001). We are interested in the application of this idea to measure structure in non-equilibrium systems. Here we focus on gels, using as a model system colloidal gels formed from hard spheres with polymer added to the systems to induce a controlled, weak attraction. To describe the structure of the gels we use real space imaging via confocal microscopy to obtain the full three-dimensional structure. We measure experimentally both translational order and bond angle correlations, defining a new (refined) translational order parameter that is sensitive to long range order in these non-random packings. This metric is also sensitive to anisotropy, which should be important in the many physical situations where an external force is present. The bond angle distribution shows coordinated organization. To give a clearer physical picture for gels, we compare the experimental data to computer generated hard sphere systems

Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor

Science.gov (United States)

Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik

2017-11-01

Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.

Shape determinative slice localization for patient-specific masseter modeling using shape-based interpolation

Energy Technology Data Exchange (ETDEWEB)

Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering (Singapore); Biomedical Imaging Lab., Agency for Science Technology and Research (Singapore); Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering (Singapore); Dept. of Preventive Dentistry, National Univ. of Singapore (Singapore); Ong, S.H. [Dept. of Electrical and Computer Engineering, National Univ. of Singapore (Singapore); Div. of Bioengineering, National Univ. of Singapore (Singapore); Liu, J.; Nowinski, W.L. [Biomedical Imaging Lab., Agency for Science Technology and Research (Singapore); Goh, P.S. [Dept. of Diagnostic Radiology, National Univ. of Singapore (Singapore)

2007-06-15

The masseter plays a critical role in the mastication system. A hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets. The main contribution here is the localizing of determinative slices in the data sets where clinicians are required to perform manual segmentations in order for an accurate model to be built. Shape-based criteria were used to locate the candidates for determinative slices and fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Five masseter models were built in our work and the average overlap indices ({kappa}) achieved is 85.2%. This indicates that there is good agreement between the models and the manual contour tracings. In addition, the time taken, as compared to manually segmenting all the slices, is significantly lesser. (orig.)

Shape determinative slice localization for patient-specific masseter modeling using shape-based interpolation

International Nuclear Information System (INIS)

Ng, H.P.; Foong, K.W.C.; Ong, S.H.; Liu, J.; Nowinski, W.L.; Goh, P.S.

2007-01-01

The masseter plays a critical role in the mastication system. A hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets. The main contribution here is the localizing of determinative slices in the data sets where clinicians are required to perform manual segmentations in order for an accurate model to be built. Shape-based criteria were used to locate the candidates for determinative slices and fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Five masseter models were built in our work and the average overlap indices (κ) achieved is 85.2%. This indicates that there is good agreement between the models and the manual contour tracings. In addition, the time taken, as compared to manually segmenting all the slices, is significantly lesser. (orig.)

Modeling the self-assembly of ordered nanoporous materials

Energy Technology Data Exchange (ETDEWEB)

Monson, Peter [Univ. of Massachusetts, Amherst, MA (United States); Auerbach, Scott [Univ. of Massachusetts, Amherst, MA (United States)

2017-11-13

This report describes progress on a collaborative project on the multiscale modeling of the assembly processes in the synthesis of nanoporous materials. Such materials are of enormous importance in modern technology with application in the chemical process industries, biomedicine and biotechnology as well as microelectronics. The project focuses on two important classes of materials: i) microporous crystalline materials, such as zeolites, and ii) ordered mesoporous materials. In the first case the pores are part of the crystalline structure, while in the second the structures are amorphous on the atomistic length scale but where surfactant templating gives rise to order on the length scale of 2 - 20 nm. We have developed a modeling framework that encompasses both these kinds of materials. Our models focus on the assembly of corner sharing silica tetrahedra in the presence of structure directing agents. We emphasize a balance between sufficient realism in the models and computational tractibility given the complex many-body phenomena. We use both on-lattice and off-lattice models and the primary computational tools are Monte Carlo simulations with sampling techniques and ensembles appropriate to specific situations. Our modeling approach is the first to capture silica polymerization, nanopore crystallization, and mesopore formation through computer-simulated self assembly.

Mechanical model for filament buckling and growth by phase ordering.

Science.gov (United States)

Rey, Alejandro D; Abukhdeir, Nasser M

2008-02-05

A mechanical model of open filament shape and growth driven by phase ordering is formulated. For a given phase-ordering driving force, the model output is the filament shape evolution and the filament end-point kinematics. The linearized model for the slope of the filament is the Cahn-Hilliard model of spinodal decomposition, where the buckling corresponds to concentration fluctuations. Two modes are predicted: (i) sequential growth and buckling and (ii) simultaneous buckling and growth. The relation among the maximum buckling rate, filament tension, and matrix viscosity is given. These results contribute to ongoing work in smectic A filament buckling.

Linear and nonlinear stability analysis in BWRs applying a reduced order model

Energy Technology Data Exchange (ETDEWEB)

Olvera G, O. A.; Espinosa P, G.; Prieto G, A., E-mail: omar_olverag@hotmail.com [Universidad Autonoma Metropolitana, Unidad Iztapalapa, San Rafael Atlixco No. 186, Col. Vicentina, 09340 Ciudad de Mexico (Mexico)

2016-09-15

Boiling Water Reactor (BWR) stability studies are generally conducted through nonlinear reduced order models (Rom) employing various techniques such as bifurcation analysis and time domain numerical integration. One of those models used for these studies is the March-Leuba Rom. Such model represents qualitatively the dynamic behavior of a BWR through a one-point reactor kinetics, a one node representation of the heat transfer process in fuel, and a two node representation of the channel Thermal hydraulics to account for the void reactivity feedback. Here, we study the effect of this higher order model on the overall stability of the BWR. The change in the stability boundaries is determined by evaluating the eigenvalues of the Jacobian matrix. The nonlinear model is also integrated numerically to show that in the nonlinear region, the system evolves to stable limit cycles when operating close to the stability boundary. We also applied a new technique based on the Empirical Mode Decomposition (Emd) to estimate a parameter linked with stability in a BWR. This instability parameter is not exactly the classical Decay Ratio (Dr), but it will be linked with it. The proposed method allows decomposing the analyzed signal in different levels or mono-component functions known as intrinsic mode functions (Imf). One or more of these different modes can be associated to the instability problem in BWRs. By tracking the instantaneous frequencies (calculated through Hilbert Huang Transform (HHT) and the autocorrelation function (Acf) of the Imf linked to instability. The estimation of the proposed parameter can be achieved. The current methodology was validated with simulated signals of the studied model. (Author)

Linear and nonlinear stability analysis in BWRs applying a reduced order model

International Nuclear Information System (INIS)

Olvera G, O. A.; Espinosa P, G.; Prieto G, A.

2016-09-01

Boiling Water Reactor (BWR) stability studies are generally conducted through nonlinear reduced order models (Rom) employing various techniques such as bifurcation analysis and time domain numerical integration. One of those models used for these studies is the March-Leuba Rom. Such model represents qualitatively the dynamic behavior of a BWR through a one-point reactor kinetics, a one node representation of the heat transfer process in fuel, and a two node representation of the channel Thermal hydraulics to account for the void reactivity feedback. Here, we study the effect of this higher order model on the overall stability of the BWR. The change in the stability boundaries is determined by evaluating the eigenvalues of the Jacobian matrix. The nonlinear model is also integrated numerically to show that in the nonlinear region, the system evolves to stable limit cycles when operating close to the stability boundary. We also applied a new technique based on the Empirical Mode Decomposition (Emd) to estimate a parameter linked with stability in a BWR. This instability parameter is not exactly the classical Decay Ratio (Dr), but it will be linked with it. The proposed method allows decomposing the analyzed signal in different levels or mono-component functions known as intrinsic mode functions (Imf). One or more of these different modes can be associated to the instability problem in BWRs. By tracking the instantaneous frequencies (calculated through Hilbert Huang Transform (HHT) and the autocorrelation function (Acf) of the Imf linked to instability. The estimation of the proposed parameter can be achieved. The current methodology was validated with simulated signals of the studied model. (Author)

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang; Youssef, Marzouk; Willcox, Karen

2014-01-01

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce

SIMPLE MODELS OF THREE COUPLED PT -SYMMETRIC WAVE GUIDES ALLOWING FOR THIRD-ORDER EXCEPTIONAL POINTS

Directory of Open Access Journals (Sweden)

Jan Schnabel

2017-12-01

Full Text Available We study theoretical models of three coupled wave guides with a PT-symmetric distribution of gain and loss. A realistic matrix model is developed in terms of a three-mode expansion. By comparing with a previously postulated matrix model it is shown how parameter ranges with good prospects of finding a third-order exceptional point (EP3 in an experimentally feasible arrangement of semiconductors can be determined. In addition it is demonstrated that continuous distributions of exceptional points, which render the discovery of the EP3 difficult, are not only a feature of extended wave guides but appear also in an idealised model of infinitely thin guides shaped by delta functions.

Generalized Reduced Order Modeling of Aeroservoelastic Systems

Science.gov (United States)

Gariffo, James Michael

Transonic aeroelastic and aeroservoelastic (ASE) modeling presents a significant technical and computational challenge. Flow fields with a mixture of subsonic and supersonic flow, as well as moving shock waves, can only be captured through high-fidelity CFD analysis. With modern computing power, it is realtively straightforward to determine the flutter boundary for a single structural configuration at a single flight condition, but problems of larger scope remain quite costly. Some such problems include characterizing a vehicle's flutter boundary over its full flight envelope, optimizing its structural weight subject to aeroelastic constraints, and designing control laws for flutter suppression. For all of these applications, reduced-order models (ROMs) offer substantial computational savings. ROM techniques in general have existed for decades, and the methodology presented in this dissertation builds on successful previous techniques to create a powerful new scheme for modeling aeroelastic systems, and predicting and interpolating their transonic flutter boundaries. In this method, linear ASE state-space models are constructed from modal structural and actuator models coupled to state-space models of the linearized aerodynamic forces through feedback loops. Flutter predictions can be made from these models through simple eigenvalue analysis of their state-transition matrices for an appropriate set of dynamic pressures. Moreover, this analysis returns the frequency and damping trend of every aeroelastic branch. In contrast, determining the critical dynamic pressure by direct time-marching CFD requires a separate run for every dynamic pressure being analyzed simply to obtain the trend for the critical branch. The present ROM methodology also includes a new model interpolation technique that greatly enhances the benefits of these ROMs. This enables predictions of the dynamic behavior of the system for flight conditions where CFD analysis has not been explicitly

Package Equivalent Reactor Networks as Reduced Order Models for Use with CAPE-OPEN Compliant Simulation

Energy Technology Data Exchange (ETDEWEB)

Meeks, E.; Chou, C. -P.; Garratt, T.

2013-03-31

Engineering simulations of coal gasifiers are typically performed using computational fluid dynamics (CFD) software, where a 3-D representation of the gasifier equipment is used to model the fluid flow in the gasifier and source terms from the coal gasification process are captured using discrete-phase model source terms. Simulations using this approach can be very time consuming, making it difficult to imbed such models into overall system simulations for plant design and optimization. For such system-level designs, process flowsheet software is typically used, such as Aspen Plus® [1], where each component where each component is modeled using a reduced-order model. For advanced power-generation systems, such as integrated gasifier/gas-turbine combined-cycle systems (IGCC), the critical components determining overall process efficiency and emissions are usually the gasifier and combustor. Providing more accurate and more computationally efficient reduced-order models for these components, then, enables much more effective plant-level design optimization and design for control. Based on the CHEMKIN-PRO and ENERGICO software, we have developed an automated methodology for generating an advanced form of reduced-order model for gasifiers and combustors. The reducedorder model offers representation of key unit operations in flowsheet simulations, while allowing simulation that is fast enough to be used in iterative flowsheet calculations. Using high-fidelity fluiddynamics models as input, Reaction Design’s ENERGICO® [2] software can automatically extract equivalent reactor networks (ERNs) from a CFD solution. For the advanced reduced-order concept, we introduce into the ERN a much more detailed kinetics model than can be included practically in the CFD simulation. The state-of-the-art chemistry solver technology within CHEMKIN-PRO allows that to be accomplished while still maintaining a very fast model turn-around time. In this way, the ERN becomes the basis for

Modeling and analysis of fractional order DC-DC converter.

Science.gov (United States)

Radwan, Ahmed G; Emira, Ahmed A; AbdelAty, Amr M; Azar, Ahmad Taher

2017-07-11

Due to the non-idealities of commercial inductors, the demand for a better model that accurately describe their dynamic response is elevated. So, the fractional order models of Buck, Boost and Buck-Boost DC-DC converters are presented in this paper. The detailed analysis is made for the two most common modes of converter operation: Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). Closed form time domain expressions are derived for inductor currents, voltage gain, average current, conduction time and power efficiency where the effect of the fractional order inductor is found to be strongly present. For example, the peak inductor current at steady state increases with decreasing the inductor order. Advanced Design Systems (ADS) circuit simulations are used to verify the derived formulas, where the fractional order inductor is simulated using Valsa Constant Phase Element (CPE) approximation and Generalized Impedance Converter (GIC). Different simulation results are introduced with good matching to the theoretical formulas for the three DC-DC converter topologies under different fractional orders. A comprehensive comparison with the recently published literature is presented to show the advantages and disadvantages of each approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Computation of External Quality Factors for RF Structures by Means of Model Order Reduction and a Perturbation Approach

CERN Document Server

Flisgen, Thomas; van Rienen, Ursula

2016-01-01

External quality factors are significant quantities to describe losses via waveguide ports in radio frequency resonators. The current contribution presents a novel approach to determine external quality factors by means of a two-step procedure: First, a state-space model for the lossless radio frequency structure is generated and its model order is reduced. Subsequently, a perturbation method is applied on the reduced model so that external losses are accounted for. The advantage of this approach results from the fact that the challenges in dealing with lossy systems are shifted to the reduced order model. This significantly saves computational costs. The present paper provides a short overview on existing methods to compute external quality factors. Then, the novel approach is introduced and validated in terms of accuracy and computational time by means of commercial software.

AN OVERVIEW OF REDUCED ORDER MODELING TECHNIQUES FOR SAFETY APPLICATIONS

Energy Technology Data Exchange (ETDEWEB)

Mandelli, D.; Alfonsi, A.; Talbot, P.; Wang, C.; Maljovec, D.; Smith, C.; Rabiti, C.; Cogliati, J.

2016-10-01

The RISMC project is developing new advanced simulation-based tools to perform Computational Risk Analysis (CRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermal-hydraulic behavior of the reactors primary and secondary systems, but also external event temporal evolution and component/system ageing. Thus, this is not only a multi-physics problem being addressed, but also a multi-scale problem (both spatial, µm-mm-m, and temporal, seconds-hours-years). As part of the RISMC CRA approach, a large amount of computationally-expensive simulation runs may be required. An important aspect is that even though computational power is growing, the overall computational cost of a RISMC analysis using brute-force methods may be not viable for certain cases. A solution that is being evaluated to assist the computational issue is the use of reduced order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RISMC analysis computational cost by decreasing the number of simulation runs; for this analysis improvement we used surrogate models instead of the actual simulation codes. This article focuses on the use of reduced order modeling techniques that can be applied to RISMC analyses in order to generate, analyze, and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (microseconds instead of hours/days).

An exactly solvable model for first- and second-order transitions

International Nuclear Information System (INIS)

Klushin, L I; Skvortsov, A M; Gorbunov, A A

1998-01-01

The possibility of an exact analytical description of first-order and second-order transitions is demonstrated using a specific microscopic model. Predictions using the exactly calculated partition function are compared with those based on the Landau and Yang-Lee approaches. The model employed is an adsorbed polymer chain with an arbitrary number of links and an external force applied to its end, for which the variation of the partition function with the adsorption interaction parameter and the magnitude of the applied force is calculated. In the thermodynamic limit, the system has one isotropic and two anisotropic, ordered phases, each of which is characterized by two order parameters and between which first-order and second-order transitions occur and a bicritical point exists. The Landau free energy is found exactly as a function of each order parameter separately and, near the bicritical point, as a function of both of them simultaneously. An exact analytical formula is found for the distribution of the complex zeros of the partition function in first-order and second-order phase transitions. Hypotheses concerning the way in which the free energy and the positions of the complex zeros scale with the number of particles N in the system are verified. (reviews of topical problems)

Predicting Statistical Response and Extreme Events in Uncertainty Quantification through Reduced-Order Models

Science.gov (United States)

Qi, D.; Majda, A.

2017-12-01

A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with

The fractional-order modeling and synchronization of electrically coupled neuron systems

KAUST Repository

Moaddy, K.

2012-11-01

In this paper, we generalize the integer-order cable model of the neuron system into the fractional-order domain, where the long memory dependence of the fractional derivative can be a better fit for the neuron response. Furthermore, the chaotic synchronization with a gap junction of two or multi-coupled-neurons of fractional-order are discussed. The circuit model, fractional-order state equations and the numerical technique are introduced in this paper for individual and multiple coupled neuron systems with different fractional-orders. Various examples are introduced with different fractional orders using the non-standard finite difference scheme together with the Grünwald-Letnikov discretization process which is easily implemented and reliably accurate. © 2011 Elsevier Ltd. All rights reserved.

The fractional-order modeling and synchronization of electrically coupled neuron systems

KAUST Repository

Moaddy, K.; Radwan, Ahmed G.; Salama, Khaled N.; Momani, Shaher M.; Hashim, Ishak

2012-01-01

In this paper, we generalize the integer-order cable model of the neuron system into the fractional-order domain, where the long memory dependence of the fractional derivative can be a better fit for the neuron response. Furthermore, the chaotic synchronization with a gap junction of two or multi-coupled-neurons of fractional-order are discussed. The circuit model, fractional-order state equations and the numerical technique are introduced in this paper for individual and multiple coupled neuron systems with different fractional-orders. Various examples are introduced with different fractional orders using the non-standard finite difference scheme together with the Grünwald-Letnikov discretization process which is easily implemented and reliably accurate. © 2011 Elsevier Ltd. All rights reserved.

A Reduced-Order Model of Transport Phenomena for Power Plant Simulation

Energy Technology Data Exchange (ETDEWEB)

Paul Cizmas; Brian Richardson; Thomas Brenner; Raymond Fontenot

2009-09-30

A reduced-order model based on proper orthogonal decomposition (POD) has been developed to simulate transient two- and three-dimensional isothermal and non-isothermal flows in a fluidized bed. Reduced-order models of void fraction, gas and solids temperatures, granular energy, and z-direction gas and solids velocity have been added to the previous version of the code. These algorithms are presented and their implementation is discussed. Verification studies are presented for each algorithm. A number of methods to accelerate the computations performed by the reduced-order model are presented. The errors associated with each acceleration method are computed and discussed. Using a combination of acceleration methods, a two-dimensional isothermal simulation using the reduced-order model is shown to be 114 times faster than using the full-order model. In the pursue of achieving the objectives of the project and completing the tasks planned for this program, several unplanned and unforeseen results, methods and studies have been generated. These additional accomplishments are also presented and they include: (1) a study of the effect of snapshot sampling time on the computation of the POD basis functions, (2) an investigation of different strategies for generating the autocorrelation matrix used to find the POD basis functions, (3) the development and implementation of a bubble detection and tracking algorithm based on mathematical morphology, (4) a method for augmenting the proper orthogonal decomposition to better capture flows with discontinuities, such as bubbles, and (5) a mixed reduced-order/full-order model, called point-mode proper orthogonal decomposition, designed to avoid unphysical due to approximation errors. The limitations of the proper orthogonal decomposition method in simulating transient flows with moving discontinuities, such as bubbling flows, are discussed and several methods are proposed to adapt the method for future use.

Reduced-Order Computational Model for Low-Frequency Dynamics of Automobiles

Directory of Open Access Journals (Sweden)

A. Arnoux

2013-01-01

Full Text Available A reduced-order model is constructed to predict, for the low-frequency range, the dynamical responses in the stiff parts of an automobile constituted of stiff and flexible parts. The vehicle has then many elastic modes in this range due to the presence of many flexible parts and equipment. A nonusual reduced-order model is introduced. The family of the elastic modes is not used and is replaced by an adapted vector basis of the admissible space of global displacements. Such a construction requires a decomposition of the domain of the structure in subdomains in order to control the spatial wave length of the global displacements. The fast marching method is used to carry out the subdomain decomposition. A probabilistic model of uncertainties is introduced. The parameters controlling the level of uncertainties are estimated solving a statistical inverse problem. The methodology is validated with a large computational model of an automobile.

Identification and modelling of travel behaviour determinants in order to find succesful interventions

NARCIS (Netherlands)

Jonkers, E.; Martens, Marieke Hendrikje; Vonk, T.; van der Lindt, M.

2012-01-01

To ease some of the major problems in the field of mobility and transport a change in travel and driving behaviour is needed. At this moment, too many travellers use the car and drive at the same moment in time. In order to change travel behaviour various measures can be taken. However, often one

Approaches for Reduced Order Modeling of Electrically Actuated von Karman Microplates

KAUST Repository

Saghir, Shahid

2016-07-25

This article presents and compares different approaches to develop reduced order models for the nonlinear von Karman rectangular microplates actuated by nonlinear electrostatic forces. The reduced-order models aim to investigate the static and dynamic behavior of the plate under small and large actuation forces. A fully clamped microplate is considered. Different types of basis functions are used in conjunction with the Galerkin method to discretize the governing equations. First we investigate the convergence with the number of modes retained in the model. Then for validation purpose, a comparison of the static results is made with the results calculated by a nonlinear finite element model. The linear eigenvalue problem for the plate under the electrostatic force is solved for a wide range of voltages up to pull-in. Results among the various reduced-order modes are compared and are also validated by comparing to results of the finite-element model. Further, the reduced order models are employed to capture the forced dynamic response of the microplate under small and large vibration amplitudes. Comparison of the different approaches are made for this case. Keywords: electrically actuated microplates, static analysis, dynamics of microplates, diaphragm vibration, large amplitude vibrations, nonlinear dynamics

Marginal and Interaction Effects in Ordered Response Models

OpenAIRE

Debdulal Mallick

2009-01-01

In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the interaction term. I present consistent estimators of both marginal and interaction effects in ordered response models. This procedure is general and can easily be extended to other discrete choice models. I ...

Fractional order creep model for dam concrete considering degree of hydration

Science.gov (United States)

Huang, Yaoying; Xiao, Lei; Bao, Tengfei; Liu, Yu

2018-05-01

Concrete is a material that is an intermediate between an ideal solid and an ideal fluid. The creep of concrete is related not only to the loading age and duration, but also to its temperature and temperature history. Fractional order calculus is a powerful tool for solving physical mechanics modeling problems. Using a software element based on the generalized Kelvin model, a fractional order creep model of concrete considering the loading age and duration is established. Then, the hydration rate of cement is considered in terms of the degree of hydration, and the fractional order creep model of concrete considering the degree of hydration is established. Moreover, uniaxial tensile creep tests of dam concrete under different curing temperatures were conducted, and the results were combined with the creep test data and complex optimization method to optimize the parameters of a new creep model. The results show that the fractional tensile creep model based on hydration degree can better describe the tensile creep properties of concrete, and this model involves fewer parameters than the 8-parameter model.

Identification and non-integer order modelling of synchronous machines operating as generator

Directory of Open Access Journals (Sweden)

Szymon Racewicz

2012-09-01

Full Text Available This paper presents an original mathematical model of a synchronous generator using derivatives of fractional order. In contrast to classical models composed of a large number of R-L ladders, it comprises half-order impedances, which enable the accurate description of the electromagnetic induction phenomena in a wide frequency range, while minimizing the order and number of model parameters. The proposed model takes into account the skin eff ect in damper cage bars, the eff ects of eddy currents in rotor solid parts, and the saturation of the machine magnetic circuit. The half-order transfer functions used for modelling these phenomena were verifi ed by simulation of ferromagnetic sheet impedance using the fi nite elements method. The analysed machine’s parameters were identified on the basis of SSFR (StandStill Frequency Response characteristics measured on a gradually magnetised synchronous machine.

Determination of bone mineral volume fraction using impedance analysis and Bruggeman model

Energy Technology Data Exchange (ETDEWEB)

Ciuchi, Ioana Veronica; Olariu, Cristina Stefania, E-mail: oocristina@yahoo.com; Mitoseriu, Liliana, E-mail: lmtsr@uaic.ro

2013-11-20

Highlights: • Mineral volume fraction of a bone sample was determined. • Dielectric properties for bone sample and for the collagen type I were determined by impedance spectroscopy. • Bruggeman effective medium approximation was applied in order to evaluate mineral volume fraction of the sample. • The computed values were compared with ones derived from a histogram test performed on SEM micrographs. -- Abstract: Measurements by impedance spectroscopy and Bruggeman effective medium approximation model were employed in order to determine the mineral volume fraction of dry bone. This approach assumes that two or more phases are present into the composite: the matrix (environment) and the other ones are inclusion phases. A fragment of femur diaphysis dense bone from a young pig was investigated in its dehydrated state. Measuring the dielectric properties of bone and its main components (hydroxyapatite and collagen) and using the Bruggeman approach, the mineral volume filling factor was determined. The computed volume fraction of the mineral volume fraction was confirmed by a histogram test analysis based on the SEM microstructures. In spite of its simplicity, the method provides a good approximation for the bone mineral volume fraction. The method which uses impedance spectroscopy and EMA modeling can be further developed by considering the conductive components of the bone tissue as a non-invasive in situ impedance technique for bone composition evaluation and monitoring.

Determination of bone mineral volume fraction using impedance analysis and Bruggeman model

International Nuclear Information System (INIS)

Ciuchi, Ioana Veronica; Olariu, Cristina Stefania; Mitoseriu, Liliana

2013-01-01

Highlights: • Mineral volume fraction of a bone sample was determined. • Dielectric properties for bone sample and for the collagen type I were determined by impedance spectroscopy. • Bruggeman effective medium approximation was applied in order to evaluate mineral volume fraction of the sample. • The computed values were compared with ones derived from a histogram test performed on SEM micrographs. -- Abstract: Measurements by impedance spectroscopy and Bruggeman effective medium approximation model were employed in order to determine the mineral volume fraction of dry bone. This approach assumes that two or more phases are present into the composite: the matrix (environment) and the other ones are inclusion phases. A fragment of femur diaphysis dense bone from a young pig was investigated in its dehydrated state. Measuring the dielectric properties of bone and its main components (hydroxyapatite and collagen) and using the Bruggeman approach, the mineral volume filling factor was determined. The computed volume fraction of the mineral volume fraction was confirmed by a histogram test analysis based on the SEM microstructures. In spite of its simplicity, the method provides a good approximation for the bone mineral volume fraction. The method which uses impedance spectroscopy and EMA modeling can be further developed by considering the conductive components of the bone tissue as a non-invasive in situ impedance technique for bone composition evaluation and monitoring

Robust simulation of buckled structures using reduced order modeling

International Nuclear Information System (INIS)

Wiebe, R.; Perez, R.A.; Spottswood, S.M.

2016-01-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties. (paper)

Robust simulation of buckled structures using reduced order modeling

Science.gov (United States)

Wiebe, R.; Perez, R. A.; Spottswood, S. M.

2016-09-01

Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties.

Mixed-order phase transition in a minimal, diffusion-based spin model.

Science.gov (United States)

Fronczak, Agata; Fronczak, Piotr

2016-07-01

In this paper we exactly solve, within the grand canonical ensemble, a minimal spin model with the hybrid phase transition. We call the model diffusion based because its Hamiltonian can be recovered from a simple dynamic procedure, which can be seen as an equilibrium statistical mechanics representation of a biased random walk. We outline the derivation of the phase diagram of the model, in which the triple point has the hallmarks of the hybrid transition: discontinuity in the average magnetization and algebraically diverging susceptibilities. At this point, two second-order transition curves meet in equilibrium with the first-order curve, resulting in a prototypical mixed-order behavior.

First-order regional seismotectonic model for South Africa

CSIR Research Space (South Africa)

Singh, M

2011-10-01

Full Text Available A first-order seismotectonic model was created for South Africa. This was done using four logical steps: geoscientific data collection, characterisation, assimilation and zonation. Through the definition of subunits of concentrations of earthquake...

Theory and Low-Order Modeling of Unsteady Airfoil Flows

Science.gov (United States)

Ramesh, Kiran

is hypothesized, and verified with experimental and computational data, that LEV formation always occurs at the same critical value of LESP irrespective of motion kinematics. Further, the applicability of the LESP criterion in influencing the occurrence of LEV formation is demonstrated. To model the growth and convection of leading-edge vortices, the unsteady thin-airfoil theory is augmented with discrete-vortex shedding from the leading edge. The LESP criterion is used to predict and modulate the shedding of leading-edge vorticity. Comparisons with experiments and CFD for test-cases with different airfoils, Reynolds numbers and motion kinematics, show that the method performs remarkably well in predicting force coefficients and flowfields for unsteady flows. The use of a single empirical parameter - the critical LESP value, allows the determination of onset, growth and termination of leading-edge vortex shedding. In the final part of the research, the discrete-vortex model is extended to flows where the freestream velocity is varying or small in comparison with motion velocity. With this extension, the method is made applicable to a larger set of 2D flows such as perching and hovering maneuvers, gusts, and sinusoidally varying freestream. Abstractions of perching and hovering are designed as test cases and used to validate the low-order model's performance in highly-unsteady, vortex-dominated flows. Alongside development of the low-order methodology, several features of unsteady flows are studied and analyzed with the aid of CFD and experiments. While remaining computationally inexpensive and retaining the essential flow-physics, the method is seen to be successful in prediction of both force coefficients and flow histories.

Model Penentuan Ukuran Batch Produksi dan Bufferstock untuk Sistem Produksi Mengalami Penurunan Kinerja dengan Mempertimbangkan Perubahan Order Awal

Directory of Open Access Journals (Sweden)

Ivan D Wangsa

2016-04-01

Full Text Available This study develops a model that involves information the preliminary order. At first, the manufacturer provides the preliminary order for the coming week (five days varies from day to day and is received on Friday. Change in the preliminary order for a given day is announced one day before and this is viewed as it occurs randomly. Moreover, production systems experience performance degradation (deterioration. Status of the production process shifts from in control to out of control that is identified by the last inspection. Inspection is done by sampling. At the time of the status of out of control the probability of producing non-conforming system component that is charged to the restoration cost and warranty costs.This paper is looking for a solution for determining the production batch size and the buffer stock to reduce total cost. The decision variables are production run period (T and buffer factor (m. Having obtained the variables T and m, then the variable production batch size (QT and the buffer stock (BT can be determined sequentially. Heuristic methods used are Silver-Meal (SM and Least Unit Cost (LUC to obtain a solution for each model. Numerical examples are given to demonstrate the performance of the models. From the numerical results, it appears that LUC method is better than SM method.

A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time?

Directory of Open Access Journals (Sweden)

Mingbo eCai

2012-11-01

Full Text Available When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006a. We present here a novel neural model that can explain temporal order judgments (TOJs and their recalibration. Our model employs three ubiquitous features of neural systems: 1 information pooling, 2 opponent processing, and 3 synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding before and after, and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analogue to the motion aftereffect. In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the motion aftereffect.

Using genetic algorithm to determine the optimal order quantities for multi-item multi-period under warehouse capacity constraints in kitchenware manufacturing

Science.gov (United States)

Saraswati, D.; Sari, D. K.; Johan, V.

2017-11-01

The study was conducted on a manufacturer that produced various kinds of kitchenware with kitchen sink as the main product. There were four types of steel sheets selected as the raw materials of the kitchen sink. The problem was the manufacturer wanted to determine how much steel sheets to order from a single supplier to meet the production requirements in a way to minimize the total inventory cost. In this case, the economic order quantity (EOQ) model was developed using all-unit discount as the price of steel sheets and the warehouse capacity was limited. Genetic algorithm (GA) was used to find the minimum of the total inventory cost as a sum of purchasing cost, ordering cost, holding cost and penalty cost.

A non-Linear transport model for determining shale rock characteristics

Science.gov (United States)

Ali, Iftikhar; Malik, Nadeem

2016-04-01

Unconventional hydrocarbon reservoirs consist of tight porous rocks which are characterised by nano-scale size porous networks with ultra-low permeability [1,2]. Transport of gas through them is not well understood at the present time, and realistic transport models are needed in order to determine rock properties and for estimating future gas pressure distribution in the reservoirs. Here, we consider a recently developed non-linear gas transport equation [3], ∂p-+ U ∂p- = D ∂2p-, t > 0, (1) ∂t ∂x ∂x2 complimented with suitable initial and boundary conditions, in order to determine shale rock properties such as the permeability K, the porosity φ and the tortuosity, τ. In our new model, the apparent convection velocity, U = U(p,px), and the apparent diffusivity D = D(p), are both highly non-linear functions of the pressure. The model incorporate various flow regimes (slip, surface diffusion, transition, continuum) based upon the Knudsen number Kn, and also includes Forchchiemers turbulence correction terms. In application, the model parameters and associated compressibility factors are fully pressure dependent, giving the model more realism than previous models. See [4]. Rock properties are determined by solving an inverse problem, with model parameters adjustment to minimise the error between the model simulation and available data. It is has been found that the proposed model performs better than previous models. Results and details of the model will be presented at the conference. Corresponding author: namalik@kfupm.edu.sa and nadeem_malik@cantab.net References [1] Cui, X., Bustin, A.M. and Bustin, R., "Measurements of gas permeability and diffusivity of tight reservoir rocks: different approaches and their applications", Geofluids 9, 208-223 (2009). [2] Chiba R., Fomin S., Chugunov V., Niibori Y. and Hashida T., "Numerical Simulation of Non Fickian Diffusion and Advection in a Fractured Porous Aquifer", AIP Conference Proceedings 898, 75 (2007

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang

2014-01-06

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.

A micro-hydrology computation ordering algorithm

Science.gov (United States)

Croley, Thomas E.

1980-11-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented "node" definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing microhydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies.

A micro-hydrology computation ordering algorithm

International Nuclear Information System (INIS)

Croley, T.E. II

1980-01-01

Discrete-distributed-parameter models are essential for watershed modelling where practical consideration of spatial variations in watershed properties and inputs is desired. Such modelling is necessary for analysis of detailed hydrologic impacts from management strategies and land-use effects. Trade-offs between model validity and model complexity exist in resolution of the watershed. Once these are determined, the watershed is then broken into sub-areas which each have essentially spatially-uniform properties. Lumped-parameter (micro-hydrology) models are applied to these sub-areas and their outputs are combined through the use of a computation ordering technique, as illustrated by many discrete-distributed-parameter hydrology models. Manual ordering of these computations requires fore-thought, and is tedious, error prone, sometimes storage intensive and least adaptable to changes in watershed resolution. A programmable algorithm for ordering micro-hydrology computations is presented that enables automatic ordering of computations within the computer via an easily understood and easily implemented node definition, numbering and coding scheme. This scheme and the algorithm are detailed in logic flow-charts and an example application is presented. Extensions and modifications of the algorithm are easily made for complex geometries or differing micro-hydrology models. The algorithm is shown to be superior to manual ordering techniques and has potential use in high-resolution studies. (orig.)

Integrable higher order deformations of Heisenberg supermagnetic model

International Nuclear Information System (INIS)

Guo Jiafeng; Yan Zhaowen; Wang Shikun; Wu Ke; Zhao Weizhong

2009-01-01

The Heisenberg supermagnet model is an integrable supersymmetric system and has a close relationship with the strong electron correlated Hubbard model. In this paper, we investigate the integrable higher order deformations of Heisenberg supermagnet models with two different constraints: (i) S 2 =3S-2I for S is an element of USPL(2/1)/S(U(2)xU(1)) and (ii) S 2 =S for S is an element of USPL(2/1)/S(L(1/1)xU(1)). In terms of the gauge transformation, their corresponding gauge equivalent counterparts are derived.

Next-to-leading order corrections to the valon model

Indian Academy of Sciences (India)

A seminumerical solution to the valon model at next-to-leading order (NLO) in the Laguerre polynomials is presented. We used the valon model to generate the structure of proton with respect to the Laguerre polynomials method. The results are compared with H1 data and other parametrizations.

Nonlinear Growth Models as Measurement Models: A Second-Order Growth Curve Model for Measuring Potential.

Science.gov (United States)

McNeish, Daniel; Dumas, Denis

2017-01-01

Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.

Appraising Birth Order in Career Assessment: Linkages to Holland's and Super's Models.

Science.gov (United States)

Leong, Frederick T. L.; Hartung, Paul J.; Goh, David; Gaylor, Michael

2001-01-01

Study 1 (n=159) found significant differences in vocational personality types, interests, and values depending on birth order. Study 2 (n=119) found significant differences in occupational interests by birth order. Both results support Alfred Adler's theory that birth order determines aspects of vocational behavior. (Contains 33 references.) (SK)

Exact Sampling and Decoding in High-Order Hidden Markov Models

NARCIS (Netherlands)

Carter, S.; Dymetman, M.; Bouchard, G.

2012-01-01

We present a method for exact optimization and sampling from high order Hidden Markov Models (HMMs), which are generally handled by approximation techniques. Motivated by adaptive rejection sampling and heuristic search, we propose a strategy based on sequentially refining a lower-order language

Venus gravity and topography: 60th degree and order model

Science.gov (United States)

Konopliv, A. S.; Borderies, N. J.; Chodas, P. W.; Christensen, E. J.; Sjogren, W. L.; Williams, B. G.; Balmino, G.; Barriot, J. P.

1993-01-01

We have combined the most recent Pioneer Venus Orbiter (PVO) and Magellan (MGN) data with the earlier 1978-1982 PVO data set to obtain a new 60th degree and order spherical harmonic gravity model and a 120th degree and order spherical harmonic topography model. Free-air gravity maps are shown over regions where the most marked improvement has been obtained (Ishtar-Terra, Alpha, Bell and Artemis). Gravity versus topography relationships are presented as correlations per degree and axes orientation.

Model order reduction for complex high-tech systems

NARCIS (Netherlands)

Lutowska, A.; Hochstenbach, M.E.; Schilders, W.H.A.; Michielsen, B.; Poirier, J.R.

2012-01-01

This paper presents a computationally efficient model order reduction (MOR) technique for interconnected systems. This MOR technique preserves block structures and zero blocks and exploits separate MOR approximations for the individual sub-systems in combination with low rank approximations for the

A statistical-thermodynamic model for ordering phenomena in thin film intermetallic structures

International Nuclear Information System (INIS)

Semenova, Olga; Krachler, Regina

2008-01-01

Ordering phenomena in bcc (110) binary thin film intermetallics are studied by a statistical-thermodynamic model. The system is modeled by an Ising approach that includes only nearest-neighbor chemical interactions and is solved in a mean-field approximation. Vacancies and anti-structure atoms are considered on both sublattices. The model describes long-range ordering and simultaneously short-range ordering in the thin film. It is applied to NiAl thin films with B2 structure. Vacancy concentrations, thermodynamic activity profiles and the virtual critical temperature of order-disorder as a function of film composition and thickness are presented. The results point to an important role of vacancies in near-stoichiometric and Ni-rich NiAl thin films

Path-Integral Monte Carlo Determination of the Fourth-Order Virial Coefficient for a Unitary Two-Component Fermi Gas with Zero-Range Interactions.

Science.gov (United States)

Yan, Yangqian; Blume, D

2016-06-10

The unitary equal-mass Fermi gas with zero-range interactions constitutes a paradigmatic model system that is relevant to atomic, condensed matter, nuclear, particle, and astrophysics. This work determines the fourth-order virial coefficient b_{4} of such a strongly interacting Fermi gas using a customized ab initio path-integral Monte Carlo (PIMC) algorithm. In contrast to earlier theoretical results, which disagreed on the sign and magnitude of b_{4}, our b_{4} agrees within error bars with the experimentally determined value, thereby resolving an ongoing literature debate. Utilizing a trap regulator, our PIMC approach determines the fourth-order virial coefficient by directly sampling the partition function. An on-the-fly antisymmetrization avoids the Thomas collapse and, combined with the use of the exact two-body zero-range propagator, establishes an efficient general means to treat small Fermi systems with zero-range interactions.

A single-vendor and a single-buyer integrated inventory model with ordering cost reduction dependent on lead time

Science.gov (United States)

Vijayashree, M.; Uthayakumar, R.

2017-09-01

Lead time is one of the major limits that affect planning at every stage of the supply chain system. In this paper, we study a continuous review inventory model. This paper investigates the ordering cost reductions are dependent on lead time. This study addressed two-echelon supply chain problem consisting of a single vendor and a single buyer. The main contribution of this study is that the integrated total cost of the single vendor and the single buyer integrated system is analyzed by adopting two different (linear and logarithmic) types ordering cost reductions act dependent on lead time. In both cases, we develop effective solution procedures for finding the optimal solution and then illustrative numerical examples are given to illustrate the results. The solution procedure is to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries from the single vendor and the single buyer in one production run, so that the integrated total cost incurred has the minimum value. Ordering cost reduction is the main aspect of the proposed model. A numerical example is given to validate the model. Numerical example solved by using Matlab software. The mathematical model is solved analytically by minimizing the integrated total cost. Furthermore, the sensitivity analysis is included and the numerical examples are given to illustrate the results. The results obtained in this paper are illustrated with the help of numerical examples. The sensitivity of the proposed model has been checked with respect to the various major parameters of the system. Results reveal that the proposed integrated inventory model is more applicable for the supply chain manufacturing system. For each case, an algorithm procedure of finding the optimal solution is developed. Finally, the graphical representation is presented to illustrate the proposed model and also include the computer flowchart in each model.

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

Science.gov (United States)

Donahue, Aaron S.; Caldwell, Peter M.

2018-02-01

Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

State reduced order models for the modelling of the thermal behavior of buildings

Energy Technology Data Exchange (ETDEWEB)

Menezo, Christophe; Bouia, Hassan; Roux, Jean-Jacques; Depecker, Patrick [Institute National de Sciences Appliquees de Lyon, Villeurbanne Cedex, (France). Centre de Thermique de Lyon (CETHIL). Equipe Thermique du Batiment]. E-mail: menezo@insa-cethil-etb.insa-lyon.fr; bouia@insa-cethil-etb.insa-lyon.fr; roux@insa-cethil-etb.insa-lyon.fr; depecker@insa-cethil-etb.insa-lyon.fr

2000-07-01

This work is devoted to the field of building physics and related to the reduction of heat conduction models. The aim is to enlarge the model libraries of heat and mass transfer codes through limiting the considerable dimensions reached by the numerical systems during the modelling process of a multizone building. We show that the balanced realization technique, specifically adapted to the coupling of reduced order models with the other thermal phenomena, turns out to be very efficient. (author)

Reduced-order modeling of piezoelectric energy harvesters with nonlinear circuits under complex conditions

Science.gov (United States)

Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong

2018-04-01

A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.

Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

Directory of Open Access Journals (Sweden)

Mohammad Ali Baghapour

2017-07-01

Full Text Available In developing a specific WQI (Water Quality Index, many water quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi Criteria Decision Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes are considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts are taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. All calculations are carried out by using the expertise software called Group Fuzzy Decision Making (GFDM. The highest and the lowest weight values, 0.999 and 0.073 respectively, are related to Hg and temperature. Regarding the type of consumption that is drinking, the parameters’ weights and ranks are consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement from the decision making group. This study indicates that the weight of parameters in determining water quality largely depends on the experts’ opinions and

Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

Directory of Open Access Journals (Sweden)

Mohammad Ali Baghapour

2017-07-01

Full Text Available In developing a specific WQI (Water Quality Index, many quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi-Criteria Decision- Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes were considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts were taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. The highest and the lowest weight values, 0.999 and 0.073 respectively, were related to Hg and temperature. Regarding the type of consumption that was drinking, the parameters’ weights and ranks were consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement with the decision-making group. This study indicated that the weight of parameters in determining water quality largely depends on the experts’ opinions and approaches. Moreover, using the FOWA model provides results accurate and closer- to-reality on the significance of

Modeling Human Behaviour with Higher Order Logic: Insider Threats

DEFF Research Database (Denmark)

Boender, Jaap; Ivanova, Marieta Georgieva; Kammuller, Florian

2014-01-01

it to the sociological process of logical explanation. As a case study on modeling human behaviour, we present the modeling and analysis of insider threats as a Higher Order Logic theory in Isabelle/HOL. We show how each of the three step process of sociological explanation can be seen in our modeling of insider’s state......, its context within an organisation and the effects on security as outcomes of a theorem proving analysis....

Validation of a RANS transition model using a high-order weighted compact nonlinear scheme

Science.gov (United States)

Tu, GuoHua; Deng, XiaoGang; Mao, MeiLiang

2013-04-01

A modified transition model is given based on the shear stress transport (SST) turbulence model and an intermittency transport equation. The energy gradient term in the original model is replaced by flow strain rate to saving computational costs. The model employs local variables only, and then it can be conveniently implemented in modern computational fluid dynamics codes. The fifth-order weighted compact nonlinear scheme and the fourth-order staggered scheme are applied to discrete the governing equations for the purpose of minimizing discretization errors, so as to mitigate the confusion between numerical errors and transition model errors. The high-order package is compared with a second-order TVD method on simulating the transitional flow of a flat plate. Numerical results indicate that the high-order package give better grid convergence property than that of the second-order method. Validation of the transition model is performed for transitional flows ranging from low speed to hypersonic speed.

Reduced-order LPV model of flexible wind turbines from high fidelity aeroelastic codes

DEFF Research Database (Denmark)

Adegas, Fabiano Daher; Sønderby, Ivan Bergquist; Hansen, Morten Hartvig

2013-01-01

of high-order linear time invariant (LTI) models. Firstly, the high-order LTI models are locally approximated using modal and balanced truncation and residualization. Then, an appropriate coordinate transformation is applied to allow interpolation of the model matrices between points on the parameter...

Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

Science.gov (United States)

Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.

2011-01-01

We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

Determination of thermodynamical coefficients for Mo-W alloys according to short-range order parameters

International Nuclear Information System (INIS)

Erokhin, L.N.; Mokrov, A.P.; Shivrin, O.N.; Khanina, N.I.

1986-01-01

A method is proposed for determining thermodynamical coefficients according to short-range order parameters. The method approbation for Mo-W alloys has shown a good agreement between the thermodynamical and diffusion data. The Mo-W system in the concentration range under study is close to the ideal one. The calculated relative error of determination of interdiffusion coefficients in alloys of the Mo-W system does not exceed 16%

A fuzzy multi-criteria decision model for integrated suppliers selection and optimal order allocation in the green supply chain

Directory of Open Access Journals (Sweden)

Hamzeh Amin-Tahmasbi

2018-09-01

Full Text Available Today, with the advancement of technology in the production process of various products, the achievement of sustainable production and development has become one of the main concerns of factories and manufacturing organizations. In the same vein, many manufacturers try to select suppliers in their upstream supply chains that have the best performance in terms of sustainable development criteria. In this research, a new multi-criteria decision-making model for selecting suppliers and assigning orders in the green supply chain is presented with a fuzzy optimization approach. Due to uncertainty in supplier capacity as well as customer demand, the problem is formulated as a fuzzy multi-objective linear programming (FMOLP. The proposed model for the selection of suppliers of SAPCO Corporation is evaluated. Firstly, in order to select and rank suppliers in a green supply chain, a network structure of criteria has defined with five main criteria of cost, quality, delivery, technology and environmental benefits. Subsequently, using incomplete fuzzy linguistic relationships, pair-wise comparisons between the criteria and sub-criteria as well as the operation of the options will be assessed. The results of these comparisons rank the existing suppliers in terms of performance and determine the utility of them. The output of these calculations (utility index is used in the optimization model. Subsequently, in the order allocation process, the two functions of the target cost of purchase and purchase value are optimized simultaneously. Finally, the order quantity is determined for each supplier in each period.

A simplified parsimonious higher order multivariate Markov chain model

Science.gov (United States)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, a simplified parsimonious higher-order multivariate Markov chain model (SPHOMMCM) is presented. Moreover, parameter estimation method of TPHOMMCM is give. Numerical experiments shows the effectiveness of TPHOMMCM.

Fundamental Frequency and Model Order Estimation Using Spatial Filtering

DEFF Research Database (Denmark)

Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll

2014-01-01

extend this procedure to account for inharmonicity using unconstrained model order estimation. The simulations show that beamforming improves the performance of the joint estimates of fundamental frequency and the number of harmonics in low signal to interference (SIR) levels, and an experiment......In signal processing applications of harmonic-structured signals, estimates of the fundamental frequency and number of harmonics are often necessary. In real scenarios, a desired signal is contaminated by different levels of noise and interferers, which complicate the estimation of the signal...... parameters. In this paper, we present an estimation procedure for harmonic-structured signals in situations with strong interference using spatial filtering, or beamforming. We jointly estimate the fundamental frequency and the constrained model order through the output of the beamformers. Besides that, we...

Collaborative Research and Development (CR&D). Task Order 0049: Tribological Modeling

Science.gov (United States)

2008-05-01

scratch test for TiN on stainless steel with better substrate mechanical properties. This present study was focused on the study of stress distribution...AFRL-RX-WP-TR-2010-4189 COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Task Order 0049: Tribological Modeling Young Sup Kang Universal...SUBTITLE COLLABORATIVE RESEARCH AND DEVELOPMENT (CR&D) Task Order 0049: Tribological Modeling 5a. CONTRACT NUMBER F33615-03-D-5801-0049 5b

Constructing set-valued fundamental diagrams from jamiton solutions in second order traffic models

KAUST Repository

Seibold, Benjamin

2013-09-01

Fundamental diagrams of vehicular traiic ow are generally multivalued in the congested ow regime. We show that such set-valued fundamental diagrams can be constructed systematically from simple second order macroscopic traiic models, such as the classical Payne-Whitham model or the inhomogeneous Aw-Rascle-Zhang model. These second order models possess nonlinear traveling wave solutions, called jamitons, and the multi-valued parts in the fundamental diagram correspond precisely to jamiton-dominated solutions. This study shows that transitions from function-valued to set-valued parts in a fundamental diagram arise naturally in well-known second order models. As a particular consequence, these models intrinsically reproduce traiic phases. © American Institute of Mathematical Sciences.

Constructing set-valued fundamental diagrams from jamiton solutions in second order traffic models

KAUST Repository

Seibold, Benjamin; Flynn, Morris R.; Kasimov, Aslan R.; Rosales, Rodolfo Rubé n

2013-01-01

Fundamental diagrams of vehicular traiic ow are generally multivalued in the congested ow regime. We show that such set-valued fundamental diagrams can be constructed systematically from simple second order macroscopic traiic models, such as the classical Payne-Whitham model or the inhomogeneous Aw-Rascle-Zhang model. These second order models possess nonlinear traveling wave solutions, called jamitons, and the multi-valued parts in the fundamental diagram correspond precisely to jamiton-dominated solutions. This study shows that transitions from function-valued to set-valued parts in a fundamental diagram arise naturally in well-known second order models. As a particular consequence, these models intrinsically reproduce traiic phases. © American Institute of Mathematical Sciences.

49 CFR 397.219 - Waiver determination and order.

Science.gov (United States)

2010-10-01

... rational basis; (3) Whether the highway routing designation of the State, political subdivision thereof, or... readily identifiable by the Administrator as one who may be affected by the order. A copy of each order is... with § 397.223, an order issued under this section constitutes the final agency decision regarding...

Empirical analyses of a choice model that captures ordering among attribute values

DEFF Research Database (Denmark)

Mabit, Stefan Lindhard

2017-01-01

an alternative additionally because it has the highest price. In this paper, we specify a discrete choice model that takes into account the ordering of attribute values across alternatives. This model is used to investigate the effect of attribute value ordering in three case studies related to alternative-fuel...... vehicles, mode choice, and route choice. In our application to choices among alternative-fuel vehicles, we see that especially the price coefficient is sensitive to changes in ordering. The ordering effect is also found in the applications to mode and route choice data where both travel time and cost...

Determination of the absolute second-order rate constant for the reaction Na + O3 → NaO + O2

International Nuclear Information System (INIS)

Husain, David; Marshall, Paul; Plane, J.M.C.

1985-01-01

The absolute second-order rate constant for the reaction Na + O 3 -> NaO + O 2 (k 1 ) has been determined by time-resolved atomic resonance absorption spectroscopy at lambda = 589 nm [Na(3 2 Psub(j)) 2 Ssub(1/2))] following pulsed irradiation, coupled with monitoring of O 3 by light absorption in the ultra-violet; this yields k 1 (500 K) = 4(+4,-2) x 10 -10 cm 3 molecule -1 s -1 , resolving large differences for various estimates of this important quantity used in modelling the sodium layer in the mesosphere. (author)

Average inactivity time model, associated orderings and reliability properties

Science.gov (United States)

Kayid, M.; Izadkhah, S.; Abouammoh, A. M.

2018-02-01

In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.

The confluence model: birth order as a within-family or between-family dynamic?

Science.gov (United States)

Zajonc, R B; Sulloway, Frank J

2007-09-01

The confluence model explains birth-order differences in intellectual performance by quantifying the changing dynamics within the family. Wichman, Rodgers, and MacCallum (2006) claimed that these differences are a between-family phenomenon--and hence are not directly related to birth order itself. The study design and analyses presented by Wichman et al. nevertheless suffer from crucial shortcomings, including their use of unfocused tests, which cause statistically significant trends to be overlooked. In addition, Wichman et al. treated birth-order effects as a linear phenomenon thereby ignoring the confluence model's prediction that these two samples may manifest opposing results based on age. This article cites between- and within-family data that demonstrate systematic birth-order effects as predicted by the confluence model. The corpus of evidence invoked here offers strong support for the assumption of the confluence model that birth-order differences in intellectual performance are primarily a within-family phenomenon.

An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

KAUST Repository

Nam, Sungsik; Alouini, Mohamed-Slim; Yang, Hongchuan

2010-01-01

Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs

Using Contaminant Transport Modeling to Determine Historical Discharges at the Surface

Science.gov (United States)

Fogwell, T. W.

2013-12-01

When it is determined that a contaminated site needs to be remediated, the issue of who is going to pay for that remediation is an immediate concern. This means that there needs to be a determination of who the responsible parties are for the existing contamination. Seldom is it the case that records have been made and kept of the surface contaminant discharges. In many cases it is possible to determine the relative amount of contaminant discharge at the surface of the various responsible parties by employing a careful analysis of the history of contaminant transport through the surface, through the vadose zone, and within the saturated zone. The process begins with the development of a dynamic conceptual site model that takes into account the important features of the transport of the contaminants through the vadose zone and in the groundwater. The parameters for this model can be derived from flow data available for the site. The resulting contaminant transport model is a composite of the vadose zone transport model, together with the saturated zone (groundwater) flow model. Any calibration of the model should be carefully employed in order to avoid using information about the conclusions of the relative discharge amounts of the responsible parties in determining the calibrated parameters. Determination of the leading edge of the plume is an important first step. It is associated with the first discharges from the surface of the site. If there were several discharging parties at the same time, then it is important to establish a chemical or isotopic signature of the chemicals that were discharged. The time duration of the first discharger needs to be determined as accurately as possible in order to establish the appropriate characterization of the leading portion of the resulting plume in the groundwater. The information about the first discharger and the resulting part of the plume associated with this discharger serves as a basis for the determination of the

A tridiagonal parsimonious higher order multivariate Markov chain model

Science.gov (United States)

Wang, Chao; Yang, Chuan-sheng

2017-09-01

In this paper, we present a tridiagonal parsimonious higher-order multivariate Markov chain model (TPHOMMCM). Moreover, estimation method of the parameters in TPHOMMCM is give. Numerical experiments illustrate the effectiveness of TPHOMMCM.

Identification of the reduced order models of a BWR reactor

International Nuclear Information System (INIS)

Hernandez S, A.

2004-01-01

The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)

Determination of Dacarbazine Φ-Order Photokinetics, Quantum Yields, and Potential for Actinometry.

Science.gov (United States)

Maafi, Mounir; Lee, Lok-Yan

2015-10-01

The characterization of drugs' photodegradation kinetics is more accurately achieved by means of the recently developed Φ-order kinetics than by the zero-, first-, and/or second-order classical treatments. The photodegradation of anti-cancer dacarbazine (DBZ) in ethanol has been investigated and found to obey Φ-order kinetics when subjected to continuous and monochromatic irradiation of various wavelengths. Its photochemical efficiency was proven to be wavelength dependent in the 220-350 nm range, undergoing a 50-fold increase. Albeit this variation was well defined by a sigmoid pattern, the overall photoreactivity of DBZ was proven to depend also on the contributions of reactants and experimental attributes. The usefulness of DBZ to serve as a drug-actinometer has been investigated using the mathematical framework of Φ-order kinetics. It has been shown that DBZ in ethanol can represent a good candidate for reliable actinometry in the range 270-350 nm. A detailed and easy-to-implement procedure has been proposed for DBZ actinometry. This procedure could advantageously be implemented prior to the determination of the photodegradation quantum yields. This approach might be found useful for the development of many drug actinometers as alternatives to quinine hydrochloride. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Positioning of chromosomes in human spermatozoa is determined by ordered centromere arrangement.

Directory of Open Access Journals (Sweden)

Olga S Mudrak

Full Text Available The intranuclear positioning of chromosomes (CHRs is a well-documented fact; however, mechanisms directing such ordering remain unclear. Unlike somatic cells, human spermatozoa contain distinct spatial markers and have asymmetric nuclei which make them a unique model for localizing CHR territories and matching peri-centromere domains. In this study, we established statistically preferential longitudinal and lateral positioning for eight CHRs. Both parameters demonstrated a correlation with the CHR gene densities but not with their sizes. Intranuclear non-random positioning of the CHRs was found to be driven by a specific linear order of centromeres physically interconnected in continuous arrays. In diploid spermatozoa, linear order of peri-centromeres was identical in two genome sets and essentially matched the arrangement established for haploid cells. We propose that the non-random longitudinal order of CHRs in human spermatozoa is generated during meiotic stages of spermatogenesis. The specific arrangement of sperm CHRs may serve as an epigenetic basis for differential transcription/replication and direct spatial CHR organization during early embryogenesis.

Simulation Furrow Irrigation by Winsrfr4.1 in order to Determine the Optimum Length of Furrow

Directory of Open Access Journals (Sweden)

Mona Golabi

2017-02-01

Full Text Available Introduction: Surface irrigation methods are the most common methods for irrigation of agricultural land. These methods are superior to sprinkler, drip and underground irrigation, because they have lower costs of funding and implementation, is inexpensive, needed maintenance of equipment is simple and does not require skilled labor. New requirements for the use of municipal water, energy, industrial, and military intends to further improve the performance of surface irrigation systems. In other words, the low efficiency of surface irrigation is not related to the method of it, but the weakness is because of the design, implementation and management. Due to the special place of Khuzestan province in southwest of Iran in agriculture and applied surface irrigation for most of the farms in this province, in the present study was simulated water flow in furrow irrigation by using WinSRFR4.1 and the optimum length of furrow was determined in the experimental farm of the Water Sciences Engineering Shoshtar University. For this purpose, advance and recession of flow were simulated by Zero inertia and Kinematic wave model and result were compared with observed data. Materials and Methods: In order to calculate and predicte advance and recession curves field measurement is necessary, but it takes a lot of time and cost. Therefore, the use of mathematical models and software for access information is important. In this research the amount of advance in furrow irrigation was measured and the results were compared with simulation of WinSRFR4.1.Field experiments was conducted in the research field of Water Sciences Engineering Shoshtar University. Data were collected from three furrows. The lengths of them were 60, 80 and 100 meters. Irrigation was performed under three discharges (1, 1.25 and 1.5 L/s, with three iterations. Three experiments furrows were provided which central furrow was for measurement data and side furrows were as buffer furrow. Before

Ordering phenomena and non-equilibrium properties of lattice gas models

International Nuclear Information System (INIS)

Fiig, T.

1994-03-01

This report falls within the general field of ordering processes and non-equilibrium properties of lattice gas models. The theory of diffuse scattering of lattice gas models originating from a random distribution of clusters is considered. We obtain relations between the diffuse part of the structure factor S dif (q), the correlation function C(r), and the size distribution of clusters D(n). For a number of distributions we calculate S dif (q) exactly in one dimension, and discuss the possibility for a Lorentzian and a Lorentzian square lineshape to arise. We discuss the two- and three-dimensional oxygen ordering processes in the high T c superconductor YBa 2 Cu 3 O 6+x based on a simple anisotropic lattice gas model. We calculate the structural phase diagram by Monte Carlo simulation and compared the results with experimental data. The structure factor of the oxygen ordering properties has been calculated in both two and three dimensions by Monte Carlo simulation. We report on results obtained from large scale computations on the Connection Machine, which are in excellent agreement with recent neutron diffraction data. In addition we consider the effect of the diffusive motion of metal-ion dopants on the oxygen ordering properties on YBa 2 Cu 3 O 6+x . The stationary properties of metastability in long-range interaction models are studied by application of a constrained transfer matrix (CTM) formalism. The model considered, which exhibits several metastable states, is an extension of the Blume Capel model to include weak long-range interactions. We show, that the decay rate of the metastable states is closely related to the imaginary part of the equilibrium free-energy density obtained from the CTM formalism. We discuss a class of lattice gas model for dissipative transport in the framework of a Langevin description, which is capable of producing power law spectra for the density fluctuations. We compare with numerical results obtained from simulations of a

Performance of a reduced-order FSI model for flow-induced vocal fold vibration

Science.gov (United States)

Luo, Haoxiang; Chang, Siyuan; Chen, Ye; Rousseau, Bernard; PhonoSim Team

2017-11-01

Vocal fold vibration during speech production involves a three-dimensional unsteady glottal jet flow and three-dimensional nonlinear tissue mechanics. A full 3D fluid-structure interaction (FSI) model is computationally expensive even though it provides most accurate information about the system. On the other hand, an efficient reduced-order FSI model is useful for fast simulation and analysis of the vocal fold dynamics, which can be applied in procedures such as optimization and parameter estimation. In this work, we study performance of a reduced-order model as compared with the corresponding full 3D model in terms of its accuracy in predicting the vibration frequency and deformation mode. In the reduced-order model, we use a 1D flow model coupled with a 3D tissue model that is the same as in the full 3D model. Two different hyperelastic tissue behaviors are assumed. In addition, the vocal fold thickness and subglottal pressure are varied for systematic comparison. The result shows that the reduced-order model provides consistent predictions as the full 3D model across different tissue material assumptions and subglottal pressures. However, the vocal fold thickness has most effect on the model accuracy, especially when the vocal fold is thin.

Comparison of Mass Transfer Models for Determination of the Intestinal Permeability

Directory of Open Access Journals (Sweden)

P Zakeri-Milani

2008-09-01

Full Text Available Background and the purpose of the study: In determination of the permeability of the intestinal wall by external perfusion techniques, several models have been proposed. In the present study three models were used for experimental results that differ in their convection and diffusion assumptions. Material and Methods: Permeability coefficients for 13 compounds (metoprolol, propranolol, naproxen, ketoprofen, furosemide, hydrochlorothiazide, cimetidine, ranitidine, atenolol, piroxicam, antipyrine, ibuprofen and carbamazepine with known human intestinal permeability values were determined in anaesthetized rats by different mass transfer models and plotted versus the observed human intestinal permeabilities. Results: The calculated dimensionless wall permeability values were in the range of 0.37 - 4.85, 0.38-6.54 and 0.41-16.59 for complete radial mixing, mixing tank and laminar flow models respectively. The results indicated that all of the models work relatively well for our data despite fundamentally different assumptions. The wall permeabilities were in the order laminar flow > mixing tank > complete radial mixing. Conclusion: Although laminar flow model provides the most direct measure of the intrinsic wall permeability, it has limitations for highly permeable drugs such as ibuprofen. The normal physiological hydrodynamics is more complex and more investigation is required to find out the real hydrodynamics.

HOKF: High Order Kalman Filter for Epilepsy Forecasting Modeling.

Science.gov (United States)

Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee

2017-08-01

Epilepsy forecasting has been extensively studied using high-order time series obtained from scalp-recorded electroencephalography (EEG). An accurate seizure prediction system would not only help significantly improve patients' quality of life, but would also facilitate new therapeutic strategies to manage epilepsy. This paper thus proposes an improved Kalman Filter (KF) algorithm to mine seizure forecasts from neural activity by modeling three properties in the high-order EEG time series: noise, temporal smoothness, and tensor structure. The proposed High-Order Kalman Filter (HOKF) is an extension of the standard Kalman filter, for which higher-order modeling is limited. The efficient dynamic of HOKF system preserves the tensor structure of the observations and latent states. As such, the proposed method offers two main advantages: (i) effectiveness with HOKF results in hidden variables that capture major evolving trends suitable to predict neural activity, even in the presence of missing values; and (ii) scalability in that the wall clock time of the HOKF is linear with respect to the number of time-slices of the sequence. The HOKF algorithm is examined in terms of its effectiveness and scalability by conducting forecasting and scalability experiments with a real epilepsy EEG dataset. The results of the simulation demonstrate the superiority of the proposed method over the original Kalman Filter and other existing methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimization in Fuzzy Economic Order Quantity (FEOQ Model with Deteriorating Inventory and Units Lost

Directory of Open Access Journals (Sweden)

Monalisha Pattnaik

2014-09-01

Full Text Available Background: This model presents the effect of deteriorating items in fuzzy optimal instantaneous replenishment for finite planning horizon. Accounting for holding cost per unit per unit time and ordering cost per order have traditionally been the case of modeling inventory systems in fuzzy environment. These imprecise parameters defined on a bounded interval on the axis of real numbers and the physical characteristics of stocked items dictate the nature of inventory policies implemented to manage and control in the production system.   Methods: The modified fuzzy EOQ (FEOQ model is introduced, it assumes that a percentage of the on-hand inventory is wasted due to deterioration and considered as an enhancement to EOQ model to determine the optimal replenishment quantity so that the net profit is maximized. In theoretical analysis, the necessary and sufficient conditions of the existence and uniqueness of the optimal solutions are proved and further the concavity of the fuzzy net profit function is established. Computational algorithm using the software LINGO 13.0 version is developed to find the optimal solution.   Results and conclusions: The results of the numerical analysis enable decision-makers to quantify the effect of units lost due to deterioration on optimizing the fuzzy net profit for the retailer. Finally, sensitivity analyses of the optimal solution with respect the major parameters are also carried out. Furthermore fuzzy decision making is shown to be superior then crisp decision making in terms of profit maximization. 

A Reduced Order Model to Predict Transient Flows around Straight Bladed Vertical Axis Wind Turbines

Directory of Open Access Journals (Sweden)

Soledad Le Clainche

2018-03-01

Full Text Available We develop a reduced order model to represent the complex flow behaviour around vertical axis wind turbines. First, we simulate vertical axis turbines using an accurate high order discontinuous Galerkin–Fourier Navier–Stokes Large Eddy Simulation solver with sliding meshes and extract flow snapshots in time. Subsequently, we construct a reduced order model based on a high order dynamic mode decomposition approach that selects modes based on flow frequency. We show that only a few modes are necessary to reconstruct the flow behaviour of the original simulation, even for blades rotating in turbulent regimes. Furthermore, we prove that an accurate reduced order model can be constructed using snapshots that do not sample one entire turbine rotation (but only a fraction of it, which reduces the cost of generating the reduced order model. Additionally, we compare the reduced order model based on the high order Navier–Stokes solver to fast 2D simulations (using a Reynolds Averaged Navier–Stokes turbulent model to illustrate the good performance of the proposed methodology.

A fourth order spline collocation approach for a business cycle model

Science.gov (United States)

Sayfy, A.; Khoury, S.; Ibdah, H.

2013-10-01

A collocation approach, based on a fourth order cubic B-splines is presented for the numerical solution of a Kaleckian business cycle model formulated by a nonlinear delay differential equation. The equation is approximated and the nonlinearity is handled by employing an iterative scheme arising from Newton's method. It is shown that the model exhibits a conditionally dynamical stable cycle. The fourth-order rate of convergence of the scheme is verified numerically for different special cases.

Structural Orders of Wheat Starch Do Not Determine the In Vitro Enzymatic Digestibility.

Science.gov (United States)

Wang, Shujun; Wang, Shaokang; Liu, Lu; Wang, Shuo; Copeland, Les

2017-03-01

In this study, we elucidated the underlying mechanisms that are responsible for the rate-limiting step for wheat starch digestion. Wheat starch samples with a degree of gelatinization (DG) ranging from 0 to 100% were prepared. As DG increased, the ordered structures of the starch were disrupted increasingly. In contrast, almost all of the increase in the rate and extent of in vitro enzymatic digestion coincided with a DG of only 6% and a minor loss of structural order. As DG increased beyond 6%, digestibility of the starch increased only slightly. We propose that the access and binding of enzymes to starch is greatly increased with only a small DG, which is followed by the simultaneous hydrolysis of crystalline and amorphous areas in gelatinized starch. In vitro enzymatic digestibility of starch was determined predominantly by enzyme binding to starch rather than the ordered structures of starch.

Unidimensional factor models imply weaker partial correlations than zero-order correlations.

Science.gov (United States)

van Bork, Riet; Grasman, Raoul P P P; Waldorp, Lourens J

2018-06-01

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.

Determination of the Young modulus relaxation of high orders from dynamic experiments on crystals

International Nuclear Information System (INIS)

Topchyan, I.I.; Dokhner, R.D.

1977-01-01

A theoretical investigation into the inelastic behaviour of a crystal under the effect of a periodic load was carried out. Both the dimentional and module effects in the interaction of anisotropic point effects with the applied-stress fields and also the anharmonism of the interatomic interaction forces were taken into account. In this case the crystal deformation can be presented as a superposition of higher-order harmonics with a frequency multiple of that of the field applied. It is shown that the phase shift in the first harmonic determines the usually measured internal friction and depends exclusively on the dimentional effect in the interaction of defects with elastic-stress fields. The phase shift in the higher-order harmonics is due both to dimentional and module effects and it is possible, by measuring shift, to determine the ratios between the elastic modules of a defect

A Third-Order Item Response Theory Model for Modeling the Effects of Domains and Subdomains in Large-Scale Educational Assessment Surveys

Science.gov (United States)

Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia

2014-01-01

Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…

Development of Boundary Condition Independent Reduced Order Thermal Models using Proper Orthogonal Decomposition

Science.gov (United States)

Raghupathy, Arun; Ghia, Karman; Ghia, Urmila

2008-11-01

Compact Thermal Models (CTM) to represent IC packages has been traditionally developed using the DELPHI-based (DEvelopment of Libraries of PHysical models for an Integrated design) methodology. The drawbacks of this method are presented, and an alternative method is proposed. A reduced-order model that provides the complete thermal information accurately with less computational resources can be effectively used in system level simulations. Proper Orthogonal Decomposition (POD), a statistical method, can be used to reduce the order of the degree of freedom or variables of the computations for such a problem. POD along with the Galerkin projection allows us to create reduced-order models that reproduce the characteristics of the system with a considerable reduction in computational resources while maintaining a high level of accuracy. The goal of this work is to show that this method can be applied to obtain a boundary condition independent reduced-order thermal model for complex components. The methodology is applied to the 1D transient heat equation.

A reduced-order vortex model of three-dimensional unsteady non-linear aerodynamics

Science.gov (United States)

Eldredge, Jeff D.

2014-11-01

Rapid, large-amplitude maneuvers of low aspect ratio wings are inherent to biologically-inspired flight. These give rise to unsteady phenomena associated with the interactions among the coherent structures shed from wing edges. The objective of this work is to distill these phenomena into a low-order physics-based dynamical model. The model is based on interconnected vortex loops, composed of linear segments between a small number of vertices. Thus, the dynamics of the fluid are reduced to tracking the evolution of the vertices, whose motions are determined from the velocity field induced by the loops and wing motion. The feature that distinguishes this method from previous treatments is that the vortex loops, analogous to point vortices in our two-dimensional model, have time-varying strength. That is, the flux of vorticity from the wing is concentrated in the constituent segments. Chains of interconnected loops can be shed from any edge of the wing. The evolution equation for the loop vertices is based on the impulse matching principle developed in previous work. We demonstrate the model in various maneuvers, including impulse starts of low aspect ratio wings, oscillatory pitching, etc., and compare with experimental results and high-fidelity simulations where applicable. This work was supported by AFOSR under Award FA9550-11-1-0098.

A NEUTRON DIFFRACTION DETERMINATION OF SHORT RANGE ORDER IN A Ni63.7Zr36.3 GLASS

OpenAIRE

Bellissent , R.; Bigot , J.; Calvayrac , Y.; Lefebvre , S.; Quivy , A.

1985-01-01

A precise determination of the three partial structure factors for the eutectic composition Ni63.7Zr36.3 has been carried out using neutron diffraction on three isotopically substituted glasses. The use of a "zero alloy" yields a direct determination of the Bhatia-Thornton structure factor SCC. Evidence for the existence of strong chemical short-range order and a clear size effect is obtained. Due to this chemical order, the partial structure factors cannot be consistent with the ones calcula...

Reduced order dynamic model for polysaccharides molecule attached to an atomic force microscope

International Nuclear Information System (INIS)

Tang Deman; Li Aiqin; Attar, Peter; Dowell, Earl H.

2004-01-01

A dynamic analysis and numerical simulation has been conducted of a polysaccharides molecular structure (a ten (10) single-α-D-glucose molecule chain) connected to a moving atomic force microscope (AFM). Sinusoidal base excitation of the AFM cantilevered beam is considered. First a linearized perturbation model is constructed for the complex polysaccharides molecular structure. Then reduced order (dynamic) models based upon a proper orthogonal decomposition (POD) technique are constructed using global modes for both the linearized perturbation model and for the full nonlinear model. The agreement between the original and reduced order models (ROM/POD) is very good even when only a few global modes are included in the ROM for either the linear case or for the nonlinear case. The computational advantage of the reduced order model is clear from the results presented

Hybrid Reduced Order Modeling Algorithms for Reactor Physics Calculations

Science.gov (United States)

Bang, Youngsuk

Reduced order modeling (ROM) has been recognized as an indispensable approach when the engineering analysis requires many executions of high fidelity simulation codes. Examples of such engineering analyses in nuclear reactor core calculations, representing the focus of this dissertation, include the functionalization of the homogenized few-group cross-sections in terms of the various core conditions, e.g. burn-up, fuel enrichment, temperature, etc. This is done via assembly calculations which are executed many times to generate the required functionalization for use in the downstream core calculations. Other examples are sensitivity analysis used to determine important core attribute variations due to input parameter variations, and uncertainty quantification employed to estimate core attribute uncertainties originating from input parameter uncertainties. ROM constructs a surrogate model with quantifiable accuracy which can replace the original code for subsequent engineering analysis calculations. This is achieved by reducing the effective dimensionality of the input parameter, the state variable, or the output response spaces, by projection onto the so-called active subspaces. Confining the variations to the active subspace allows one to construct an ROM model of reduced complexity which can be solved more efficiently. This dissertation introduces a new algorithm to render reduction with the reduction errors bounded based on a user-defined error tolerance which represents the main challenge of existing ROM techniques. Bounding the error is the key to ensuring that the constructed ROM models are robust for all possible applications. Providing such error bounds represents one of the algorithmic contributions of this dissertation to the ROM state-of-the-art. Recognizing that ROM techniques have been developed to render reduction at different levels, e.g. the input parameter space, the state space, and the response space, this dissertation offers a set of novel

Universal block diagram based modeling and simulation schemes for fractional-order control systems.

Science.gov (United States)

Bai, Lu; Xue, Dingyü

2017-05-08

Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Trimming a hazard logic tree with a new model-order-reduction technique

Science.gov (United States)

Porter, Keith; Field, Edward; Milner, Kevin R

2017-01-01

The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

Science.gov (United States)

Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

Science.gov (United States)

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Deterministic three-half-order kinetic model for microbial degradation of added carbon substrates in soil

International Nuclear Information System (INIS)

Brunner, W.; Focht, D.D.

1984-01-01

The kinetics of mineralization of carbonaceous substrates has been explained by a deterministic model which is applicable to either growth or nongrowth conditions in soils. The mixed-order nature of the model does not require a priori decisions about reaction order, discontinuity period of lag or stationary phase, or correction for endogenous mineralization rates. The integrated equation is simpler than the integrated form of the Monod equation because of the following: (i) only two, rather than four, interdependent constants have to be determined by nonlinear regression analysis, (ii) substrate or product formation can be expressed explicitly as a function of time, (iii) biomass concentration does not have to be known, and (iv) the required initial estimate for the nonlinear regression analysis can be easily obtained from a linearized form rather than from an interval estimate of a differential equation. 14 CO 2 evolution data from soil have been fitted to the model equation. All data except those from irradiated soil gave us better fits by residual sum of squares (RSS) by assuming growth in soil was linear (RSS =0.71) as opposed to exponential (RSS = 2.87). The underlying reasons for growth (exponential versus linear), no growth, and relative degradation rates of substrates are consistent with the basic mechanisms from which the model is derived. 21 references

Anisotropic Third-Order Regularization for Sparse Digital Elevation Models

KAUST Repository

Lellmann, Jan; Morel, Jean-Michel; Schö nlieb, Carola-Bibiane

2013-01-01

features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE

Impaired Processing of Serial Order Determines Working Memory Impairments in Alzheimer's Disease.

Science.gov (United States)

De Belder, Maya; Santens, Patrick; Sieben, Anne; Fias, Wim

2017-01-01

Working memory (WM) problems are commonly observed in Alzheimer's disease (AD), but the affected mechanisms leading to impaired WM are still insufficiently understood. The ability to efficiently process serial order in WM has been demonstrated to be fundamental to fluent daily life functioning. The decreased capability to mentally process serial position in WM has been put forward as the underlying explanation for generally compromised WM performance. Determine which mechanisms, such as order processing, are responsible for deficient WM functioning in AD. A group of AD patients (n = 32) and their partners (n = 25), assigned to the control group, were submitted to an extensive battery of neuropsychological and experimental tasks, assessing general cognitive state and functioning of several aspects related to serial order WM. The results revealed an impaired ability to bind item information to serial position within WM in AD patients compared to controls. It was additionally observed that AD patients experienced specific difficulties with directing spatial attention when searching for item information stored in WM. The processing of serial order and the allocation of attentional resources are both disrupted, explaining the generally reduced WM functioning in AD patients. Further studies should now clarify whether this observation could explain disease-related problems for other cognitive functions such as verbal expression, auditory comprehension, or planning.

Second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence.

Science.gov (United States)

Zheng, Guo; Wang, Jue; Wang, Lin; Zhou, Muchun; Xin, Yu; Song, Minmin

2017-11-15

The general formulae for second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence are derived and validated by the Bessel-Gaussian Schell-model beams and cosine-Gaussian-correlated Schell-model beams. Our finding shows that the second-order moments of partially coherent Schell-model beams are related to the second-order partial derivatives of source spectral degree of coherence at the origin. The formulae we provide are much more convenient to analyze and research propagation problems in turbulence.

Reduced order modeling in topology optimization of vibroacoustic problems

DEFF Research Database (Denmark)

Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas

2017-01-01

complex 3D parts. The optimization process can therefore become highly time consuming due to the need to solve a large system of equations at each iteration. Projection-based parametric Model Order Reduction (pMOR) methods have successfully been applied for reducing the computational cost of material......There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...

U.S. Army Engineering and Support Center, Huntsville, Price Reasonableness Determinations for Federal Supply Schedule Orders for Supplies Need Improvement

Science.gov (United States)

2016-03-29

Army Engineering and Support Center, Huntsville, Price Reasonableness Determinations for Federal Supply Schedule Orders for Supplies Need...0207.000) │ i Results in Brief U.S. Army Engineering and Support Center, Huntsville, Price Reasonableness Determinations for Federal Supply Schedule...officers made determinations of fair and reasonable pricing for General Services Administration Federal supply schedule orders awarded for purchases

Strategies for Reduced-Order Models in Uncertainty Quantification of Complex Turbulent Dynamical Systems

Science.gov (United States)

Qi, Di

Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are

Modeling vehicle operating speed on urban roads in Montreal: a panel mixed ordered probit fractional split model.

Science.gov (United States)

Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis F

2013-10-01

Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate

Vascular stents: Coupling full 3-D with reduced-order structural models

International Nuclear Information System (INIS)

Avdeev, I; Shams, M

2010-01-01

Self-expanding nitinol stents are used to treat peripheral arterial disease. The peripheral arteries are subjected to a combination of mechanical forces such as compression, torsion, bending, and contraction. Most commercially available peripheral self-expanding stents are composed of a series of sub-millimeter V-shaped struts, which are laser-cut from a nitinol tube and surface-treated for better fatigue performance. The numerical stent models must accurately predict location and distribution of local stresses and strains caused by large arterial deformations. Full 3-D finite element non-linear analysis of an entire stent is computationally expensive to the point of being prohibitive, especially for longer stents. Reduced-order models based on beam or shell elements are fairly accurate in capturing global deformations, but are not very helpful in predicting stent failure. We propose a mixed approach that combines the full 3-D model and reduced-order models. Several global-local, full 3-D/reduced-order finite element models of a peripheral self-expanding stent were validated and compared with experimental data. The kinematic constraint method used to couple various elements together was found to be very efficient and easily applicable to commercial FEA codes. The proposed mixed models can be used to accurately predict stent failure based on realistic (patient-specific), non-linear kinematic behavior of peripheral arteries.

The influence of fragmentation models on the determination of the strong coupling constant in e+e- annihilation into hadrons

International Nuclear Information System (INIS)

Behrend, H.J.; Chen, C.; Fenner, H.; Schachter, M.J.; Schroeder, V.; Sindt, H.; D'Agostini, G.; Apel, W.D.; Banerjee, S.; Bodenkamp, J.; Chrobaczek, D.; Engler, J.; Fluegge, G.; Fries, D.C.; Fues, W.; Gamerdinger, K.; Hopp, G.; Kuester, H.; Mueller, H.; Randoll, H.; Schmidt, G.; Schneider, H.; Boer, W. de; Buschhorn, G.; Grindhammer, G.; Grosse-Wiesmann, P.; Gunderson, B.; Kiesling, C.; Kotthaus, R.; Kruse, U.; Lierl, H.; Lueers, D.; Oberlack, H.; Schacht, P.; Colas, P.; Cordier, A.; Davier, M.; Fournier, D.; Grivaz, J.F.; Haissinski, J.; Journe, V.; Klarsfeld, A.; Laplanche, F.; Le Diberder, F.; Mallik, U.; Veillet, J.J.; Field, J.H.; George, R.; Goldberg, M.; Grossetete, B.; Hamon, O.; Kapusta, F.; Kovacs, F.; London, G.; Poggioli, L.; Rivoal, M.; Aleksan, R.; Bouchez, J.; Carnesecchi, G.; Cozzika, G.; Ducros, Y.; Gaidot, A.; Jadach, S.; Lavagne, Y.; Pamela, J.; Pansart, J.P.; Pierre, F.

1983-01-01

Hadronic events obtained with the CELLO detector at PETRA were compared with first-order QCD predictions using two different models for the fragmentation of quarks and gluons, the Hoyer model and the Lund model. Both models are in reasonable agreement with the data, although they do not completely reproduce the details of many distributions. Several methods have been applied to determine the strong coupling constant αsub(s). Although within one model the value of αsub(s) varies by 20% among the different methods, the values determined using the Lund model are 30% or more larger (depending on the method used) than the values determined with the Hoyer model. Our results using the Hoyer model are in agreement with previous results based on this approach. (orig.)

Competing orders in the Hofstadter t -J model

Science.gov (United States)

Tu, Wei-Lin; Schindler, Frank; Neupert, Titus; Poilblanc, Didier

2018-01-01

The Hofstadter model describes noninteracting fermions on a lattice in the presence of an external magnetic field. Motivated by the plethora of solid-state phases emerging from electron interactions, we consider an interacting version of the Hofstadter model, including a Hubbard repulsion U . We investigate this model in the large-U limit corresponding to a t -J Hamiltonian with an external (orbital) magnetic field. By using renormalized mean-field theory supplemented by exact diagonalization calculations of small clusters, we find evidence for competing symmetry-breaking phases, exhibiting (possibly coexisting) charge, bond, and superconducting orders. Topological properties of the states are also investigated, and some of our results are compared to related experiments involving ultracold atoms loaded on optical lattices in the presence of a synthetic gauge field.

Anisotropic Third-Order Regularization for Sparse Digital Elevation Models

KAUST Repository

Lellmann, Jan

2013-01-01

We consider the problem of interpolating a surface based on sparse data such as individual points or level lines. We derive interpolators satisfying a list of desirable properties with an emphasis on preserving the geometry and characteristic features of the contours while ensuring smoothness across level lines. We propose an anisotropic third-order model and an efficient method to adaptively estimate both the surface and the anisotropy. Our experiments show that the approach outperforms AMLE and higher-order total variation methods qualitatively and quantitatively on real-world digital elevation data. © 2013 Springer-Verlag.

Testing static tradeoff theiry against pecking order models of capital ...

African Journals Online (AJOL)

We test two models with the purpose of finding the best empirical explanation for corporate financing choice of a cross section of 27 Nigerian quoted companies. The models were developed to represent the Static tradeoff Theory and the Pecking order Theory of capital structure with a view to make comparison between ...

Effective high-order solver with thermally perfect gas model for hypersonic heating prediction

International Nuclear Information System (INIS)

Jiang, Zhenhua; Yan, Chao; Yu, Jian; Qu, Feng; Ma, Libin

2016-01-01

Highlights: • Design proper numerical flux for thermally perfect gas. • Line-implicit LUSGS enhances efficiency without extra memory consumption. • Develop unified framework for both second-order MUSCL and fifth-order WENO. • The designed gas model can be applied to much wider temperature range. - Abstract: Effective high-order solver based on the model of thermally perfect gas has been developed for hypersonic heat transfer computation. The technique of polynomial curve fit coupling to thermodynamics equation is suggested to establish the current model and particular attention has been paid to the design of proper numerical flux for thermally perfect gas. We present procedures that unify five-order WENO (Weighted Essentially Non-Oscillatory) scheme in the existing second-order finite volume framework and a line-implicit method that improves the computational efficiency without increasing memory consumption. A variety of hypersonic viscous flows are performed to examine the capability of the resulted high order thermally perfect gas solver. Numerical results demonstrate its superior performance compared to low-order calorically perfect gas method and indicate its potential application to hypersonic heating predictions for real-life problem.

Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model

KAUST Repository

Mo, Qianxing; Liang, Faming

2010-01-01

approach to ChIP-chip data through an Ising model with high-order interactions. The proposed method naturally takes into account the intrinsic spatial structure of the data and can be used to analyze data from multiple platforms with different genomic

Correlation effects of third-order perturbation in the extended Hubbard model

International Nuclear Information System (INIS)

Wei, G.Z.; Nie, H.Q.; Li, L.; Zhang, K.Y.

1989-01-01

Using the local approach, a third-order perturbation calculation has been performed to investigate the effects of intra-atomic electron correlation and electron and spin correlation between nearest neighbour sites in the extended Hubbard model. It was found that significant correction of the third order over the second order results and, in comparison with the results of the third-order perturbation where only the intra-atomic electron correlation is included, the influence of the electron and spin correlation between nearest neighbour sites on the correlation energy is non-negligible. 17 refs., 3 figs

Flexible implementation of the Ensemble Model with arbitrary order of moments

Energy Technology Data Exchange (ETDEWEB)

Ackermann, W. [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder (TEMF), Schlossgartenstrasse 8, D 64289 Darmstadt (Germany)]. E-mail: ackermann@temf.tu-darmstadt.de; Weiland, T. [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder (TEMF), Schlossgartenstrasse 8, D 64289 Darmstadt (Germany)]. E-mail: thomas.weiland@temf.tu-darmstadt.de

2006-03-01

The Ensemble Model takes advantage of an approach to express the phase space particle distribution function in terms of the first, second and higher order moments instead of considering individual particles. Based on a new flexible implementation, an arbitrary number of orders can be processed and automatically converted into proper update equations for the simulation program V-Code. In this paper the influence of the introduction of higher order moments on the beam dynamics simulation is investigated. The achievable accuracy and the numerical efforts are compared with the ones obtained from the lower order calculations.

Low-order dynamical system model of a fully developed turbulent channel flow

Science.gov (United States)

Hamilton, Nicholas; Tutkun, Murat; Cal, Raúl Bayoán

2017-06-01

A reduced order model of a turbulent channel flow is composed from a direct numerical simulation database hosted at the Johns Hopkins University. Snapshot proper orthogonal decomposition (POD) is used to identify the Hilbert space from which the reduced order model is obtained, as the POD basis is defined to capture the optimal energy content by mode. The reduced order model is defined by coupling the evolution of the dynamic POD mode coefficients through their respective time derivative with a least-squares polynomial fit of terms up to third order. Parameters coupling the dynamics of the POD basis are defined in analog to those produced in the classical Galerkin projection. The resulting low-order dynamical system is tested for a range of basis modes demonstrating that the non-linear mode interactions do not lead to a monotonic decrease in error propagation. A basis of five POD modes accounts for 50% of the integrated turbulence kinetic energy but captures only the largest features of the turbulence in the channel flow and is not able to reflect the anticipated flow dynamics. Using five modes, the low-order model is unable to accurately reproduce Reynolds stresses, and the root-mean-square error of the predicted stresses is as great as 30%. Increasing the basis to 28 modes accounts for 90% of the kinetic energy and adds intermediate scales to the dynamical system. The difference between the time derivatives of the random coefficients associated with individual modes and their least-squares fit is amplified in the numerical integration leading to unstable long-time solutions. Periodic recalibration of the dynamical system is undertaken by limiting the integration time to the range of the sampled data and offering the dynamical system new initial conditions. Renewed initial conditions are found by pushing the mode coefficients in the end of the integration time toward a known point along the original trajectories identified through a least-squares projection. Under

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Science.gov (United States)

Wan, Zhong Yi; Vlachas, Pantelis; Koumoutsakos, Petros; Sapsis, Themistoklis

2018-01-01

The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN) architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM) regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more significant in

Data-assisted reduced-order modeling of extreme events in complex dynamical systems.

Directory of Open Access Journals (Sweden)

Zhong Yi Wan

Full Text Available The prediction of extreme events, from avalanches and droughts to tsunamis and epidemics, depends on the formulation and analysis of relevant, complex dynamical systems. Such dynamical systems are characterized by high intrinsic dimensionality with extreme events having the form of rare transitions that are several standard deviations away from the mean. Such systems are not amenable to classical order-reduction methods through projection of the governing equations due to the large intrinsic dimensionality of the underlying attractor as well as the complexity of the transient events. Alternatively, data-driven techniques aim to quantify the dynamics of specific, critical modes by utilizing data-streams and by expanding the dimensionality of the reduced-order model using delayed coordinates. In turn, these methods have major limitations in regions of the phase space with sparse data, which is the case for extreme events. In this work, we develop a novel hybrid framework that complements an imperfect reduced order model, with data-streams that are integrated though a recurrent neural network (RNN architecture. The reduced order model has the form of projected equations into a low-dimensional subspace that still contains important dynamical information about the system and it is expanded by a long short-term memory (LSTM regularization. The LSTM-RNN is trained by analyzing the mismatch between the imperfect model and the data-streams, projected to the reduced-order space. The data-driven model assists the imperfect model in regions where data is available, while for locations where data is sparse the imperfect model still provides a baseline for the prediction of the system state. We assess the developed framework on two challenging prototype systems exhibiting extreme events. We show that the blended approach has improved performance compared with methods that use either data streams or the imperfect model alone. Notably the improvement is more

Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit

International Nuclear Information System (INIS)

Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua J.; Talbot, Paul W.; Rinaldi, Ivan; Maljovec, Dan; Wang, Bei; Pascucci, Valerio; Zhao, Haihua

2015-01-01

The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.

Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit

Energy Technology Data Exchange (ETDEWEB)

Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cogliati, Joshua J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talbot, Paul W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rinaldi, Ivan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Maljovec, Dan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Bei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pascucci, Valerio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2015-09-01

The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.

Ground-state properties of ordered, partially ordered, and random Cu-Au and Ni-Pt alloys

DEFF Research Database (Denmark)

Ruban, Andrei; Abrikosov, I. A.; Skriver, Hans Lomholt

1995-01-01

We have studied the ground-state properties of ordered, partially ordered, and random Cu-Au and Ni-Pt alloys at the stoichiometric 1/4, 1/2, and 3/4 compositions in the framework of the multisublattice single-site (SS) coherent potential approximation (CPA). Charge-transfer effects in the random ...... for the ordered alloys are in good agreement with experimental data. For all the alloys the calculated ordering energy and the equilibrium lattices parameters are found to be almost exact quadratic functions of the long-range-order parameter....... and the partially ordered alloys are included in the screened impurity model. The prefactor in the Madelung energy is determined by the requirement that the total energy obtained in direct SS CPA calculations should equal the total energy given by the Connolly-Williams expansion based on Green’s function...

Using Count Data and Ordered Models in National Forest Recreation Demand Analysis

Science.gov (United States)

Simões, Paula; Barata, Eduardo; Cruz, Luis

2013-11-01

This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.

John Carroll’s Views on Intelligence: Bi-Factor vs. Higher-Order Models

Directory of Open Access Journals (Sweden)

A. Alexander Beaujean

2015-10-01

Full Text Available The development of factor models is inextricably tied to the history of intelligence research. One of the most commonly-cited scholars in the field is John Carroll, whose three-stratum theory of cognitive ability has been one of the most influential models of cognitive ability in the past 20 years. Nonetheless, there is disagreement about how Carroll conceptualized the factors in his model. Some argue that his model is best represented through a higher-order model, while others argue that a bi-factor model is a better representation. Carroll was explicit about what he perceived the best way to represent his model, but his writings are not always easy to understand. In this article, I clarify his position by first describing the details and implications of bi-factor and higher-order models then show that Carroll’s published views are better represented by a bi-factor model.

First-order metal-insulator transitions in the extended Hubbard model due to self-consistent screening of the effective interaction

Science.gov (United States)

Schüler, M.; van Loon, E. G. C. P.; Katsnelson, M. I.; Wehling, T. O.

2018-04-01

While the Hubbard model is the standard model to study Mott metal-insulator transitions, it is still unclear to what extent it can describe metal-insulator transitions in real solids, where nonlocal Coulomb interactions are always present. By using a variational principle, we clarify this issue for short- and long-range nonlocal Coulomb interactions for half-filled systems on bipartite lattices. We find that repulsive nonlocal interactions generally stabilize the Fermi-liquid regime. The metal-insulator phase boundary is shifted to larger interaction strengths to leading order linearly with nonlocal interactions. Importantly, nonlocal interactions can raise the order of the metal-insulator transition. We present a detailed analysis of how the dimension and geometry of the lattice as well as the temperature determine the critical nonlocal interaction leading to a first-order transition: for systems in more than two dimensions with nonzero density of states at the Fermi energy the critical nonlocal interaction is arbitrarily small; otherwise, it is finite.

Post processing of optically recognized text via second order hidden Markov model

Science.gov (United States)

Poudel, Srijana

In this thesis, we describe a postprocessing system on Optical Character Recognition(OCR) generated text. Second Order Hidden Markov Model (HMM) approach is used to detect and correct the OCR related errors. The reason for choosing the 2nd order HMM is to keep track of the bigrams so that the model can represent the system more accurately. Based on experiments with training data of 159,733 characters and testing of 5,688 characters, the model was able to correct 43.38 % of the errors with a precision of 75.34 %. However, the precision value indicates that the model introduced some new errors, decreasing the correction percentage to 26.4%.

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters

Energy Technology Data Exchange (ETDEWEB)

Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California Santa-Barbara; Bullo, Francesco [University of California Santa-Barbara; Dhople, Sairaj V. [University of Minnesota

2017-08-21

Next-generation power networks will contain large numbers of grid-connected inverters satisfying a significant fraction of system load. Since each inverter model has a relatively large number of dynamic states, it is impractical to analyze complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model with lumped parameters for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. We show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as any individual inverter in the system. Numerical simulations validate the reduced-order model.

Influence of the Choice of Lunar Gravity Model on Orbit Determination for Lunar Orbiters

Directory of Open Access Journals (Sweden)

Young-Rok Kim

2018-01-01

Full Text Available We examine the influence of the lunar gravity model on the orbit determination (OD of a lunar orbiter operating in a 100 km high, lunar polar orbit. Doppler and sequential range measurements by three Deep Space Network antennas and one Korea Deep Space Antenna were used. For measurement simulation and OD analysis, STK11 and ODTK6 were utilized. GLGM2, LP100K, LP150Q, GRAIL420A, and GRAIL660B were used for investigation of lunar gravity model selection effect. OD results were assessed by position and velocity uncertainties with error covariance and an external orbit comparison using simulated true orbit. The effect of the lunar gravity models on the long-term OD, degree and order level, measurement-acquisition condition, and lunar altitude was investigated. For efficiency verification, computational times for the five lunar gravity models were compared. Results showed that significant improvements to OD accuracy are observed by applying a GRAIL-based model; however, applying a full order and degree gravity modeling is not always the best strategy, owing to the computational burden. Consequently, we consider that OD using GRAIL660B with 70 × 70 degree and order is the most efficient strategy for mission preanalysis. This study provides useful guideline for KPLO OD analysis during nominal mission operation.

Joint Ordering and Pricing Decisions for New Repeat-Purchase Products

OpenAIRE

Wu, Xiang; Zhang, Jinlong

2015-01-01

This paper studies ordering and pricing problems for new repeat-purchase products. We incorporate the repeat-purchase rate and price effects into the Bass model to characterize the demand pattern. We consider two decision models: (1) two-stage decision model, in which the sales division chooses a price to maximize the gross profit and the purchasing division determines an optimal ordering decision to minimize the total cost under a given demand subsequently, and (2) joint decision model, in w...

First Order Fire Effects Model: FOFEM 4.0, user's guide

Science.gov (United States)

Elizabeth D. Reinhardt; Robert E. Keane; James K. Brown

1997-01-01

A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.

Spin model for nontrivial types of magnetic order in inverse-perovskite antiferromagnets

Science.gov (United States)

Mochizuki, Masahito; Kobayashi, Masaya; Okabe, Reoya; Yamamoto, Daisuke

2018-02-01

Nontrivial magnetic orders in the inverse-perovskite manganese nitrides are theoretically studied by constructing a classical spin model describing the magnetic anisotropy and frustrated exchange interactions inherent in specific crystal and electronic structures of these materials. With a replica-exchange Monte Carlo technique, a theoretical analysis of this model reproduces the experimentally observed triangular Γ5 g and Γ4 g spin-ordered patterns and the systematic evolution of magnetic orders. Our Rapid Communication solves a 40-year-old problem of nontrivial magnetism for the inverse-perovskite manganese nitrides and provides a firm basis for clarifying the magnetism-driven negative thermal expansion phenomenon discovered in this class of materials.

An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions

Energy Technology Data Exchange (ETDEWEB)

Oña, J. de; Oña, R. de; Eboli, L.; Forciniti, C.; Mazzulla, G.

2016-07-01

Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. (Author)

Magnetic order and Kondo effect in the Anderson-lattice model

International Nuclear Information System (INIS)

Bernhard, B.H.; Aguiar, C.; Kogoutiouk, I.; Coqblin, B.

2007-01-01

The Anderson-lattice model has been extensively developed to account for the properties of many anomalous rare-earth compounds and in particular for the competition between the Kondo effect and an antiferromagnetic (AF) phase in a cubic lattice. Here we apply the higher-order decoupling of the equations of motion for the Green Functions (GF) introduced in [H.G. Luo, S.J. Wang, Phys. Rev. B 62 (2000) 1485]. We obtain an improved description of the phase diagram, where the AF phase subsists in a smaller range of the model parameters. As higher-order GF are included in the chain of equations, we are able to calculate directly the local spin-flip correlation function † ↓ d † ↑ f ↑ d ↓ >. As a further improvement to the previous approximation of [B.H. Bernhard, C. Aguiar, B. Coqblin, Physica B 378-380 (2006) 712], we obtain a reduced range of existence for the AF phase for the symmetric half-filled case and then we discuss the competition between the AF order and the Kondo effect as a function of the band filling

Time-Frequency Analysis Using Warped-Based High-Order Phase Modeling

Directory of Open Access Journals (Sweden)

Ioana Cornel

2005-01-01

Full Text Available The high-order ambiguity function (HAF was introduced for the estimation of polynomial-phase signals (PPS embedded in noise. Since the HAF is a nonlinear operator, it suffers from noise-masking effects and from the appearance of undesired cross-terms when multicomponents PPS are analyzed. In order to improve the performances of the HAF, the multi-lag HAF concept was proposed. Based on this approach, several advanced methods (e.g., product high-order ambiguity function (PHAF have been recently proposed. Nevertheless, performances of these new methods are affected by the error propagation effect which drastically limits the order of the polynomial approximation. This phenomenon acts especially when a high-order polynomial modeling is needed: representation of the digital modulation signals or the acoustic transient signals. This effect is caused by the technique used for polynomial order reduction, common for existing approaches: signal multiplication with the complex conjugated exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We will prove that this method reduces considerably the effect of error propagation. Namely, with this order reduction method, the estimation error at a given order will depend only on the performances of the estimation method.

Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions

International Nuclear Information System (INIS)

Zhang, Yuxiao; Zhang, Jianming; Liu, Yang; Huang, Hui; Kang, Zhenhui

2012-01-01

Highlights: ► Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. ► MPCS was covalently modified by cysteine (MPCS–CO–Cys). ► MPCS–CO–Cys was first time used in electrochemical detection of heavy metal ions. ► Heavy metal ions such as Pb 2+ and Cd 2+ can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.

A Reduced Order Model for the Design of Oxy-Coal Combustion Systems

Directory of Open Access Journals (Sweden)

Steven L. Rowan

2015-01-01

Full Text Available Oxy-coal combustion is one of the more promising technologies currently under development for addressing the issues associated with greenhouse gas emissions from coal-fired power plants. Oxy-coal combustion involves combusting the coal fuel in mixtures of pure oxygen and recycled flue gas (RFG consisting of mainly carbon dioxide (CO2. As a consequence, many researchers and power plant designers have turned to CFD simulations for the study and design of new oxy-coal combustion power plants, as well as refitting existing air-coal combustion facilities to oxy-coal combustion operations. While CFD is a powerful tool that can provide a vast amount of information, the simulations themselves can be quite expensive in terms of computational resources and time investment. As a remedy, a reduced order model (ROM for oxy-coal combustion has been developed to supplement the CFD simulations. With this model, it is possible to quickly estimate the average outlet temperature of combustion flue gases given a known set of mass flow rates of fuel and oxidant entering the power plant boiler as well as determine the required reactor inlet mass flow rates for a desired outlet temperature. Several cases have been examined with this model. The results compare quite favorably to full CFD simulation results.

Determination of the mass transfer limiting step of dye adsorption onto commercial adsorbent by using mathematical models.

Science.gov (United States)

Marin, Pricila; Borba, Carlos Eduardo; Módenes, Aparecido Nivaldo; Espinoza-Quiñones, Fernando R; de Oliveira, Silvia Priscila Dias; Kroumov, Alexander Dimitrov

2014-01-01

Reactive blue 5G dye removal in a fixed-bed column packed with Dowex Optipore SD-2 adsorbent was modelled. Three mathematical models were tested in order to determine the limiting step of the mass transfer of the dye adsorption process onto the adsorbent. The mass transfer resistance was considered to be a criterion for the determination of the difference between models. The models contained information about the external, internal, or surface adsorption limiting step. In the model development procedure, two hypotheses were applied to describe the internal mass transfer resistance. First, the mass transfer coefficient constant was considered. Second, the mass transfer coefficient was considered as a function of the dye concentration in the adsorbent. The experimental breakthrough curves were obtained for different particle diameters of the adsorbent, flow rates, and feed dye concentrations in order to evaluate the predictive power of the models. The values of the mass transfer parameters of the mathematical models were estimated by using the downhill simplex optimization method. The results showed that the model that considered internal resistance with a variable mass transfer coefficient was more flexible than the other ones and this model described the dynamics of the adsorption process of the dye in the fixed-bed column better. Hence, this model can be used for optimization and column design purposes for the investigated systems and similar ones.

First-order inflation

International Nuclear Information System (INIS)

Kolb, E.W.

1991-01-01

In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been reviewed. In this talk I will discuss some models for first-order inflation, and emphasize unique signatures that result if inflation is realized in a first-order transition. Before discussing first-order inflation, I will briefly review some of the history of inflation to demonstrate how first-order inflation differs from other models. (orig.)

Determination of cognitive development: postnonclassical theoretical model

Directory of Open Access Journals (Sweden)

Irina N. Pogozhina

2015-09-01

Full Text Available The aim of this research is to develop a postnonclassical cognitive processes content determination model in which mental processes are considered as open selfdeveloping, self-organizing systems. Three types of systems (dynamic, statistical, developing were analysed and compared on the basis of the description of the external and internal characteristics of causation, types of causal chains (dependent, independent and their interactions, as well as the nature of the relationship between the elements of the system (hard, probabilistic, mixed. Mechanisms of open non-equilibrium nonlinear systems (dissipative and four dissipative structures emergence conditions are described. Determination models of mental and behaviour formation and development that were developed under various theoretical approaches (associationism, behaviorism, gestaltism, psychology of intelligence by Piaget, Vygotsky culture historical approach, activity approach and others are mapped on each other as the models that describe behaviour of the three system types mentioned above. The development models of the mental sphere are shown to be different by the following criteria: 1 allocated determinants amount; 2 presence or absence of the system own activity that results in selecting the model not only external, but also internal determinants; 3 types of causal chains (dependent-independent-blended; 4 types of relationships between the causal chain that ultimately determines the subsequent system determination type as decisive (a tough dynamic pattern or stochastic (statistical regularity. The continuity of postnonclassical, classical and non-classical models of mental development determination are described. The process of gradual refinement, complexity, «absorption» of the mental determination by the latter models is characterized. The human mental can be deemed as the functioning of the open developing non-equilibrium nonlinear system (dissipative. The mental sphere is

Next-to-leading order corrections to the valon model

Indian Academy of Sciences (India)

Next-to-leading order corrections to the valon model. G R BOROUN. ∗ and E ESFANDYARI. Physics Department, Razi University, Kermanshah 67149, Iran. ∗. Corresponding author. E-mail: grboroun@gmail.com; boroun@razi.ac.ir. MS received 17 January 2014; revised 31 October 2014; accepted 21 November 2014.

Symmetries of th-Order Approximate Stochastic Ordinary Differential Equations

OpenAIRE

Fredericks, E.; Mahomed, F. M.

2012-01-01

Symmetries of $n$ th-order approximate stochastic ordinary differential equations (SODEs) are studied. The determining equations of these SODEs are derived in an Itô calculus context. These determining equations are not stochastic in nature. SODEs are normally used to model nature (e.g., earthquakes) or for testing the safety and reliability of models in construction engineering when looking at the impact of random perturbations.

Reduced order methods for modeling and computational reduction

CERN Document Server

Rozza, Gianluigi

2014-01-01

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.  Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects. This...

Higher-order ice-sheet modelling accelerated by multigrid on graphics cards

Science.gov (United States)

Brædstrup, Christian; Egholm, David

2013-04-01

Higher-order ice flow modelling is a very computer intensive process owing primarily to the nonlinear influence of the horizontal stress coupling. When applied for simulating long-term glacial landscape evolution, the ice-sheet models must consider very long time series, while both high temporal and spatial resolution is needed to resolve small effects. The use of higher-order and full stokes models have therefore seen very limited usage in this field. However, recent advances in graphics card (GPU) technology for high performance computing have proven extremely efficient in accelerating many large-scale scientific computations. The general purpose GPU (GPGPU) technology is cheap, has a low power consumption and fits into a normal desktop computer. It could therefore provide a powerful tool for many glaciologists working on ice flow models. Our current research focuses on utilising the GPU as a tool in ice-sheet and glacier modelling. To this extent we have implemented the Integrated Second-Order Shallow Ice Approximation (iSOSIA) equations on the device using the finite difference method. To accelerate the computations, the GPU solver uses a non-linear Red-Black Gauss-Seidel iterator coupled with a Full Approximation Scheme (FAS) multigrid setup to further aid convergence. The GPU finite difference implementation provides the inherent parallelization that scales from hundreds to several thousands of cores on newer cards. We demonstrate the efficiency of the GPU multigrid solver using benchmark experiments.

Extreme learning machine for reduced order modeling of turbulent geophysical flows

Science.gov (United States)

San, Omer; Maulik, Romit

2018-04-01

We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition-based reduced order models for quasistationary geophysical turbulent flows. An extreme learning machine concept is introduced for computing an eddy-viscosity closure dynamically to incorporate the effects of the truncated modes. We consider a four-gyre wind-driven ocean circulation problem as our prototype setting to assess the performance of the proposed data-driven approach. Our framework provides a significant reduction in computational time and effectively retains the dynamics of the full-order model during the forward simulation period beyond the training data set. Furthermore, we show that the method is robust for larger choices of time steps and can be used as an efficient and reliable tool for long time integration of general circulation models.

Geometrical aspects of operator ordering terms in gauge invariant quantum models

International Nuclear Information System (INIS)

Houston, P.J.

1990-01-01

Finite-dimensional quantum models with both boson and fermion degrees of freedom, and which have a gauge invariance, are studied here as simple versions of gauge invariant quantum field theories. The configuration space of these finite-dimensional models has the structure of a principal fibre bundle and has defined on it a metric which is invariant under the action of the bundle or gauge group. When the gauge-dependent degrees of freedom are removed, thereby defining the quantum models on the base of the principal fibre bundle, extra operator ordering terms arise. By making use of dimensional reduction methods in removing the gauge dependence, expressions are obtained here for the operator ordering terms which show clearly their dependence on the geometry of the principal fibre bundle structure. (author)

First-order inflation

International Nuclear Information System (INIS)

Kolb, E.W.; Chicago Univ., IL

1990-09-01

In the original proposal, inflation occurred in the process of a strongly first-order phase transition. This model was soon demonstrated to be fatally flawed. Subsequent models for inflation involved phase transitions that were second-order, or perhaps weakly first-order; some even involved no phase transition at all. Recently the possibility of inflation during a strongly first-order phase transition has been revived. In this talk I will discuss some models for first-order inflation, and emphasize unique signatures that result in inflation is realized in a first-order transition. Before discussing first-order inflation, I will briefly review some of the history of inflation to demonstrate how first-order inflation differs from other models. 58 refs., 3 figs

A Reduced-order NLTE Kinetic Model for Radiating Plasmas of Outer Envelopes of Stellar Atmospheres

Energy Technology Data Exchange (ETDEWEB)

Munafò, Alessandro [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 206A Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States); Mansour, Nagi N. [NASA Ames Research Center, Moffett Field, 94035 CA (United States); Panesi, Marco, E-mail: munafo@illinois.edu, E-mail: nagi.n.mansour@nasa.gov, E-mail: m.panesi@illinois.edu [Aerospace Engineering Department, University of Illinois at Urbana-Champaign, 306 Talbot Lab., 104 S. Wright Street, Urbana, IL 61801 (United States)

2017-04-01

The present work proposes a self-consistent reduced-order NLTE kinetic model for radiating plasmas found in the outer layers of stellar atmospheres. A detailed collisional-radiative kinetic mechanism is constructed by leveraging the most up-to-date set of ab initio and experimental data available in the literature. This constitutes the starting point for the derivation of a reduced-order model, obtained by lumping the bound energy states into groups. In order to determine the needed thermo-physical group properties, uniform and Maxwell–Boltzmann energy distributions are used to reconstruct the energy population of each group. Finally, the reduced set of governing equations for the material gas and the radiation field is obtained based on the moment method. Applications consider the steady flow across a shock wave in partially ionized hydrogen. The results clearly demonstrate that adopting a Maxwell–Boltzmann grouping allows, on the one hand, for a substantial reduction of the number of unknowns and, on the other, to maintain accuracy for both gas and radiation quantities. Also, it is observed that, when neglecting line radiation, the use of two groups already leads to a very accurate resolution of the photo-ionization precursor, internal relaxation, and radiative cooling regions. The inclusion of line radiation requires adopting just one additional group to account for optically thin losses in the α , β , and γ lines of the Balmer and Paschen series. This trend has been observed for a wide range of shock wave velocities.

Pairing of parafermions of order 2: seniority model

International Nuclear Information System (INIS)

Nelson, Charles A

2004-01-01

As generalizations of the fermion seniority model, four multi-mode Hamiltonians are considered to investigate some of the consequences of the pairing of parafermions of order 2. Two- and four-particle states are explicitly constructed for H A ≡ -GA†A with A† ≡ 1/2 Σ m>0 c† m c† -m and the distinct H C ≡ -GC†C with C† ≡ 1/2 Σ m>0 c† -m c† m , and for the time-reversal invariant H (-) ≡ -G(A† - C†)(A - C) and H (+) ≡ -G(A† + C†)(A + C), which has no analogue in the fermion case. The spectra and degeneracies are compared with those of the usual fermion seniority model

Spatial Model for Determining the Optimum Placement of Logistics Centers in a Predefined Economic Area

Directory of Open Access Journals (Sweden)

Ramona Iulia Țarțavulea (Dieaconescu

2016-08-01

Full Text Available The process of globalization has stimulated the demand for logistics services at a level of speed and increased efficiency, which involves using of techniques, tools, technologies and modern models in supply chain management. The aim of this research paper is to present a model that can be used in order to achieve an optimized supply chain, associated with minimum transportation costs. The utilization of spatial modeling for determining the optimal locations for logistics centers in a predefined economic area is proposd in this paper. The principal methods used to design the model are mathematic optimization and linear programming. The output data of the model are the precise placement of one up to ten logistics centers, in terms of minimum operational costs for delivery from the optimum locations to consumer points. The results of the research indicate that by using the proposed model, an efficient supply chain that is consistent with optimization of transport can be designed, in order to streamline the delivery process and thus reduce operational costs

Utility of low-order linear nuclear-power-plant models in plant diagnostics and control

International Nuclear Information System (INIS)

Tylee, J.L.

1981-01-01

A low-order, linear model of a pressurized water reactor (PWR) plant is described and evaluated. The model consists of 23 linear, first-order difference equations and simulates all subsystems of both the primary and secondary sides of the plant. Comparisons between the calculated model response and available test data show the model to be an adequate representation of the actual plant dynamics. Suggested use for the model in an on-line digital plant diagnostics and control system are presented

Tracer disposition kinetics in the determination of local cerebral blood flow by a venous equilibrium model, tube model, and distributed model

International Nuclear Information System (INIS)

Sawada, Y.; Sugiyama, Y.; Iga, T.; Hanano, M.

1987-01-01

Tracer distribution kinetics in the determination of local cerebral blood flow (LCBF) were examined by using three models, i.e., venous equilibrium, tube, and distributed models. The technique most commonly used for measuring LCBF is the tissue uptake method, which was first developed and applied by Kety. The measurement of LCBF with the 14 C-iodoantipyrine (IAP) method is calculated by using an equation derived by Kety based on the Fick's principle and a two-compartment model of blood-tissue exchange and tissue concentration at a single data point. The procedure, in which the tissue is to be in equilibrium with venous blood, will be referred to as the tissue equilibration model. In this article, effects of the concentration gradient of tracer along the length of the capillary (tube model) and the transverse heterogeneity in the capillary transit time (distributed model) on the determination of LCBF were theoretically analyzed for the tissue sampling method. Similarities and differences among these models are explored. The rank order of the LCBF calculated by using arterial blood concentration time courses and the tissue concentration of tracer based on each model were tube model (model II) less than distributed model (model III) less than venous equilibrium model (model I). Data on 14 C-IAP kinetics reported by Ohno et al. were employed. The LCBFs calculated based on model I were 45-260% larger than those in models II or III. To discriminate among three models, we propose to examine the effect of altering the venous infusion time of tracer on the apparent tissue-to-blood concentration ratio (lambda app). A range of the ratio of the predicted lambda app in models II or III to that in model I was from 0.6 to 1.3

Statistically accurate low-order models for uncertainty quantification in turbulent dynamical systems.

Science.gov (United States)

Sapsis, Themistoklis P; Majda, Andrew J

2013-08-20

A framework for low-order predictive statistical modeling and uncertainty quantification in turbulent dynamical systems is developed here. These reduced-order, modified quasilinear Gaussian (ROMQG) algorithms apply to turbulent dynamical systems in which there is significant linear instability or linear nonnormal dynamics in the unperturbed system and energy-conserving nonlinear interactions that transfer energy from the unstable modes to the stable modes where dissipation occurs, resulting in a statistical steady state; such turbulent dynamical systems are ubiquitous in geophysical and engineering turbulence. The ROMQG method involves constructing a low-order, nonlinear, dynamical system for the mean and covariance statistics in the reduced subspace that has the unperturbed statistics as a stable fixed point and optimally incorporates the indirect effect of non-Gaussian third-order statistics for the unperturbed system in a systematic calibration stage. This calibration procedure is achieved through information involving only the mean and covariance statistics for the unperturbed equilibrium. The performance of the ROMQG algorithm is assessed on two stringent test cases: the 40-mode Lorenz 96 model mimicking midlatitude atmospheric turbulence and two-layer baroclinic models for high-latitude ocean turbulence with over 125,000 degrees of freedom. In the Lorenz 96 model, the ROMQG algorithm with just a single mode captures the transient response to random or deterministic forcing. For the baroclinic ocean turbulence models, the inexpensive ROMQG algorithm with 252 modes, less than 0.2% of the total, captures the nonlinear response of the energy, the heat flux, and even the one-dimensional energy and heat flux spectra.

Short-Term Memory for Serial Order: A Recurrent Neural Network Model

Science.gov (United States)

Botvinick, Matthew M.; Plaut, David C.

2006-01-01

Despite a century of research, the mechanisms underlying short-term or working memory for serial order remain uncertain. Recent theoretical models have converged on a particular account, based on transient associations between independent item and context representations. In the present article, the authors present an alternative model, according…

Are Quantum Models for Order Effects Quantum?

Science.gov (United States)

Moreira, Catarina; Wichert, Andreas

2017-12-01

The application of principles of Quantum Mechanics in areas outside of physics has been getting increasing attention in the scientific community in an emergent disciplined called Quantum Cognition. These principles have been applied to explain paradoxical situations that cannot be easily explained through classical theory. In quantum probability, events are characterised by a superposition state, which is represented by a state vector in a N-dimensional vector space. The probability of an event is given by the squared magnitude of the projection of this superposition state into the desired subspace. This geometric approach is very useful to explain paradoxical findings that involve order effects, but do we really need quantum principles for models that only involve projections? This work has two main goals. First, it is still not clear in the literature if a quantum projection model has any advantage towards a classical projection. We compared both models and concluded that the Quantum Projection model achieves the same results as its classical counterpart, because the quantum interference effects play no role in the computation of the probabilities. Second, it intends to propose an alternative relativistic interpretation for rotation parameters that are involved in both classical and quantum models. In the end, instead of interpreting these parameters as a similarity measure between questions, we propose that they emerge due to the lack of knowledge concerned with a personal basis state and also due to uncertainties towards the state of world and towards the context of the questions.

Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments

Science.gov (United States)

Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh

2018-03-01

Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.

Ammonium removal from aqueous solutions by clinoptilolite: determination of isotherm and thermodynamic parameters and comparison of kinetics by the double exponential model and conventional kinetic models.

Science.gov (United States)

Tosun, Ismail

2012-03-01

The adsorption isotherm, the adsorption kinetics, and the thermodynamic parameters of ammonium removal from aqueous solution by using clinoptilolite in aqueous solution was investigated in this study. Experimental data obtained from batch equilibrium tests have been analyzed by four two-parameter (Freundlich, Langmuir, Tempkin and Dubinin-Radushkevich (D-R)) and four three-parameter (Redlich-Peterson (R-P), Sips, Toth and Khan) isotherm models. D-R and R-P isotherms were the models that best fitted to experimental data over the other two- and three-parameter models applied. The adsorption energy (E) from the D-R isotherm was found to be approximately 7 kJ/mol for the ammonium-clinoptilolite system, thereby indicating that ammonium is adsorbed on clinoptilolite by physisorption. Kinetic parameters were determined by analyzing the nth-order kinetic model, the modified second-order model and the double exponential model, and each model resulted in a coefficient of determination (R(2)) of above 0.989 with an average relative error lower than 5%. A Double Exponential Model (DEM) showed that the adsorption process develops in two stages as rapid and slow phase. Changes in standard free energy (∆G°), enthalpy (∆H°) and entropy (∆S°) of ammonium-clinoptilolite system were estimated by using the thermodynamic equilibrium coefficients.

Ammonium Removal from Aqueous Solutions by Clinoptilolite: Determination of Isotherm and Thermodynamic Parameters and Comparison of Kinetics by the Double Exponential Model and Conventional Kinetic Models

Directory of Open Access Journals (Sweden)

İsmail Tosun

2012-03-01

Full Text Available The adsorption isotherm, the adsorption kinetics, and the thermodynamic parameters of ammonium removal from aqueous solution by using clinoptilolite in aqueous solution was investigated in this study. Experimental data obtained from batch equilibrium tests have been analyzed by four two-parameter (Freundlich, Langmuir, Tempkin and Dubinin-Radushkevich (D-R and four three-parameter (Redlich-Peterson (R-P, Sips, Toth and Khan isotherm models. D-R and R-P isotherms were the models that best fitted to experimental data over the other two- and three-parameter models applied. The adsorption energy (E from the D-R isotherm was found to be approximately 7 kJ/mol for the ammonium-clinoptilolite system, thereby indicating that ammonium is adsorbed on clinoptilolite by physisorption. Kinetic parameters were determined by analyzing the nth-order kinetic model, the modified second-order model and the double exponential model, and each model resulted in a coefficient of determination (R2 of above 0.989 with an average relative error lower than 5%. A Double Exponential Model (DEM showed that the adsorption process develops in two stages as rapid and slow phase. Changes in standard free energy (∆G°, enthalpy (∆H° and entropy (∆S° of ammonium-clinoptilolite system were estimated by using the thermodynamic equilibrium coefficients.

Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yuxiao; Zhang, Jianming [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Liu, Yang, E-mail: yangl@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Huang, Hui [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Kang, Zhenhui, E-mail: zhkang@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China)

2012-04-15

Highlights: Black-Right-Pointing-Pointer Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. Black-Right-Pointing-Pointer MPCS was covalently modified by cysteine (MPCS-CO-Cys). Black-Right-Pointing-Pointer MPCS-CO-Cys was first time used in electrochemical detection of heavy metal ions. Black-Right-Pointing-Pointer Heavy metal ions such as Pb{sup 2+} and Cd{sup 2+} can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.

Where to start? Bottom-up attention improves working memory by determining encoding order.

Science.gov (United States)

Ravizza, Susan M; Uitvlugt, Mitchell G; Hazeltine, Eliot

2016-12-01

The present study aimed to characterize the mechanism by which working memory is enhanced for items that capture attention because of their novelty or saliency-that is, via bottom-up attention. The first experiment replicated previous research by corroborating that bottom-up attention directed to an item is sufficient for enhancing working memory and, moreover, generalized the effect to the domain of verbal working memory. The subsequent 3 experiments sought to determine how bottom-up attention affects working memory. We considered 2 hypotheses: (1) Bottom-up attention enhances the encoded representation of the stimulus, similar to how voluntary attention functions, or (2) It affects the order of encoding by shifting priority onto the attended stimulus. By manipulating how stimuli were presented (simultaneous/sequential display) and whether the cue predicted the tested items, we found evidence that bottom-up attention improves working memory performance via the order of encoding hypothesis. This finding was observed across change detection and free recall paradigms. In contrast, voluntary attention improved working memory regardless of encoding order and showed greater effects on working memory. We conclude that when multiple information sources compete, bottom-up attention prioritizes the location at which encoding should begin. When encoding order is set, bottom-up attention has little or no benefit to working memory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Modal-based reduced-order model of BWR out-of phase instabilities

International Nuclear Information System (INIS)

Turso, J.A.; Edwards, R.M.; March-Leuba, J.

1995-01-01

For the past 40 yr, reduced-order modeling of boiling water reactor (BWR) dynamic behavior has been accomplished by several researchers. These models have been primarily concerned with providing insight into the so-called corewide neutron flux oscillation, where the power at each radial location in the core oscillates in unison. This is generally considered to be an illustration of the fundamental neutronic mode excited by the core thermal hydraulics. The time dependence of the fundamental mode is typically described by the point-kinetics equations, with one or more delayed-neutron groups. Thermal-hydraulic excitation of the first azimuthal harmonic mode, the so-called out-of-phase (OOP) instability, has been observed in operating BWRs. The temporal behavior of a low-order model of this phenomenon can be characterized using the modal point-kinetics formulation developed in this paper

HIGHLY-ACCURATE MODEL ORDER REDUCTION TECHNIQUE ON A DISCRETE DOMAIN

Directory of Open Access Journals (Sweden)

L. D. Ribeiro

2015-09-01

Full Text Available AbstractIn this work, we present a highly-accurate technique of model order reduction applied to staged processes. The proposed method reduces the dimension of the original system based on null values of moment-weighted sums of heat and mass balance residuals on real stages. To compute these sums of weighted residuals, a discrete form of Gauss-Lobatto quadrature was developed, allowing a high degree of accuracy in these calculations. The locations where the residuals are cancelled vary with time and operating conditions, characterizing a desirable adaptive nature of this technique. Balances related to upstream and downstream devices (such as condenser, reboiler, and feed tray of a distillation column are considered as boundary conditions of the corresponding difference-differential equations system. The chosen number of moments is the dimension of the reduced model being much lower than the dimension of the complete model and does not depend on the size of the original model. Scaling of the discrete independent variable related with the stages was crucial for the computational implementation of the proposed method, avoiding accumulation of round-off errors present even in low-degree polynomial approximations in the original discrete variable. Dynamical simulations of distillation columns were carried out to check the performance of the proposed model order reduction technique. The obtained results show the superiority of the proposed procedure in comparison with the orthogonal collocation method.

Ordering the Preference Hierarchies for Internal Finance, Bank Loans, Bond and Share Issues

OpenAIRE

Leo de Haan; Jeroen Hinloopen

2002-01-01

We estimate the incremental financing decision for a sample of some 150Dutch companies for the years 1984 through 1997, thereby distinguishinginternal finance and three types of external finance: bank borrowing, bondissues and share issues. First, we estimate a multinomial logit model whichconfirms several predictions of both the static trade-off theory and thepecking-order theory as to the determinants of financing choices. Next, weuse ordered probit models to determine which financing hiera...

Multivariable robust adaptive controller using reduced-order model

Directory of Open Access Journals (Sweden)

Wei Wang

1990-04-01

Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.

Markovian Model in High Order Sequence Prediction From Log-Motif Patterns in Agbada Paralic Section, Niger Delta, Nigeria

International Nuclear Information System (INIS)

Olabode, S. O.; Adekoya, J. A.

2002-01-01

Markovian model in the elucidation of high order sequence was applied to repetitive events of regressive and transgressive phases in the Agbada paralic section Niger Delta. The repetitive events are made up of delta front, delta topset and fluvio-deltaic sediments. The sediments consist of sands, sandstones, siltstones and shales in various proportions. Five wells: MN1, AA1, NP2, NP6 and NP8 were studied.Summary of biostratigraphic report and well log-motif patterns was used to delineate the third order depositional sequences in the wells.Various Markovian properties - observed transition frequency matrix, observed transition probability matrix, fixed probability vector, expected random matrix (randomised transition matrix) and difference matrix were determined for stacked high order sequence (high frequency cyclic events) nested within the third-order sequences using the log-motif patterns for the various sand bodies and shales. Flow diagrams were constructed for each of the depositional sequences to know the likely occurrence of number of cycles.Upward transition matrix between the log-motif patterns and flow diagram to elucidate cyclicity show that the overall regressive sequence of the Niger Delta has been modified by deltaic depositional elements and fluctuations in sea level. The predictions of higher order sequence within third order sequences from Markovian Properties provide good basis for correlation within the depositional sequences. The model has also been used to decipher the dominant depositional processes during the formation of the sequences. Discrete reservoir intervals and seal potentials within the sequences were also predicted from the flow diagrams constructed

REDUCED ISOTROPIC CRYSTAL MODEL WITH RESPECT TO THE FOURTH-ORDER ELASTIC MODULI

Directory of Open Access Journals (Sweden)

O. Burlayenko

2018-04-01

Full Text Available Using a reduced isotropic crystal model the relationship between the fourth-order elastic moduli of an isotropic medium and the independent components of the fourth-order elastic moduli tensor of real crystals of various crystal systems is found. To calculate the coefficients of these relations, computer algebra systems Redberry and Mathematica for working with high order tensors in the symbolic and explicit form were used, in light of the overly complex computation. In an isotropic medium, there are four independent fourth order elastic moduli. This is due to the presence of four invariants for an eighth-rank tensor in the three-dimensional space, that has symmetries over the pairs of indices. As an example, the moduli of elasticity of an isotropic medium corresponding to certain crystals of cubic system are given (LiF, NaCl, MgO, CaF2. From the obtained results it can be seen that the reduced isotropic crystal model can be most effectively applied to high-symmetry crystal systems.

A note on monotonicity of item response functions for ordered polytomous item response theory models.

Science.gov (United States)

Kang, Hyeon-Ah; Su, Ya-Hui; Chang, Hua-Hua

2018-03-08

A monotone relationship between a true score (τ) and a latent trait level (θ) has been a key assumption for many psychometric applications. The monotonicity property in dichotomous response models is evident as a result of a transformation via a test characteristic curve. Monotonicity in polytomous models, in contrast, is not immediately obvious because item response functions are determined by a set of response category curves, which are conceivably non-monotonic in θ. The purpose of the present note is to demonstrate strict monotonicity in ordered polytomous item response models. Five models that are widely used in operational assessments are considered for proof: the generalized partial credit model (Muraki, 1992, Applied Psychological Measurement, 16, 159), the nominal model (Bock, 1972, Psychometrika, 37, 29), the partial credit model (Masters, 1982, Psychometrika, 47, 147), the rating scale model (Andrich, 1978, Psychometrika, 43, 561), and the graded response model (Samejima, 1972, A general model for free-response data (Psychometric Monograph no. 18). Psychometric Society, Richmond). The study asserts that the item response functions in these models strictly increase in θ and thus there exists strict monotonicity between τ and θ under certain specified conditions. This conclusion validates the practice of customarily using τ in place of θ in applied settings and provides theoretical grounds for one-to-one transformations between the two scales. © 2018 The British Psychological Society.

An Online Method for Interpolating Linear Parametric Reduced-Order Models

KAUST Repository

Amsallem, David; Farhat, Charbel

2011-01-01

A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.

New second order Mumford-Shah model based on Γ-convergence approximation for image processing

Science.gov (United States)

Duan, Jinming; Lu, Wenqi; Pan, Zhenkuan; Bai, Li

2016-05-01

In this paper, a second order variational model named the Mumford-Shah total generalized variation (MSTGV) is proposed for simultaneously image denoising and segmentation, which combines the original Γ-convergence approximated Mumford-Shah model with the second order total generalized variation (TGV). For image denoising, the proposed MSTGV can eliminate both the staircase artefact associated with the first order total variation and the edge blurring effect associated with the quadratic H1 regularization or the second order bounded Hessian regularization. For image segmentation, the MSTGV can obtain clear and continuous boundaries of objects in the image. To improve computational efficiency, the implementation of the MSTGV does not directly solve its high order nonlinear partial differential equations and instead exploits the efficient split Bregman algorithm. The algorithm benefits from the fast Fourier transform, analytical generalized soft thresholding equation, and Gauss-Seidel iteration. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed model.

Order α'(two-loop) equivalence of the string equations of motion and the σ-model Weyl invariance conditions

International Nuclear Information System (INIS)

Metsaev, R.R.; Tseytlin, A.A.

1987-01-01

We prove the on-shell equivalence of the order α' terms in the string effective equations (for the graviton, dilaton and the antisymmetric tensor) to the vanishing of the corresponding (two-loop) terms in the Weyl anomaly coefficients for the general bosonic σ-model. We first determine the α' term in the string effective action starting with the known expression for the 3- and 4-point string amplitudes. Then we compute the two-loop β-function in the general σ-model with the antisymmetric tensor coupling. Special emphasis is made on the renormalization scheme dependence of the β-function. Our result disagrees with the previously known one and cannot be manifestly expressed in terms of the generalized curvature for the connection with torsion. We also prove (to the order α' 2 ) that the parallelizable spaces are solutions of the string equations of motion and establish the complete 3-loop expression for the 'central charge' coefficient. (orig.)

Orientation and Order of the Amide Group of Sphingomyelin in Bilayers Determined by Solid-State NMR

Science.gov (United States)

Matsumori, Nobuaki; Yamaguchi, Toshiyuki; Maeta, Yoshiko; Murata, Michio

2015-01-01

Sphingomyelin (SM) and cholesterol (Chol) are considered essential for the formation of lipid rafts; however, the types of molecular interactions involved in this process, such as intermolecular hydrogen bonding, are not well understood. Since, unlike other phospholipids, SM is characterized by the presence of an amide group, it is essential to determine the orientation of the amide and its order in the lipid bilayers to understand the nature of the hydrogen bonds in lipid rafts. For this study, 1′-13C-2-15N-labeled and 2′-13C-2-15N-labeled SMs were prepared, and the rotational-axis direction and order parameters of the SM amide in bilayers were determined based on 13C and 15N chemical-shift anisotropies and intramolecular 13C-15N dipole coupling constants. Results revealed that the amide orientation was minimally affected by Chol, whereas the order was enhanced significantly in its presence. Thus, Chol likely promotes the formation of an intermolecular hydrogen-bond network involving the SM amide without significantly changing its orientation, providing a higher order to the SM amide. To our knowledge, this study offers new insight into the significance of the SM amide orientation with regard to molecular recognition in lipid rafts, and therefore provides a deeper understanding of the mechanism of their formation. PMID:26083921

Analysis of credit linked demand in an inventory model with varying ordering cost.

Science.gov (United States)

Banu, Ateka; Mondal, Shyamal Kumar

2016-01-01

In this paper, we have considered an economic order quantity model for deteriorating items with two-level trade credit policy in which a delay in payment is offered by a supplier to a retailer and also an another delay in payment is offered by the retailer to his/her all customers. Here, it is proposed that the demand function is dependent on the length of the customer's credit period and also the duration of offering the credit period. In this article, it is considered that the retailer's ordering cost per order depends on the number of replenishment cycles. The objective of this model is to establish a deterministic EOQ model of deteriorating items for the retailer to decide the position of customers credit period and the number of replenishment cycles in finite time horizon such that the retailer gets the maximum profit. Also, the model is explained with the help of some numerical examples.

Fluctuation effects in first-order phase transitions: Theory and model for martensitic transformations

DEFF Research Database (Denmark)

Lindgård, Per-Anker; Mouritsen, Ole G.

1990-01-01

We discuss central questions in weak, first-order structural transitions by means of a magnetic analog model. A theory including fluctuation effects is developed for the model, showing a dynamical response with softening, fading modes and a growing central peak. The model is also analyzed by a two......-dimensional Monte Carlo simulation, showing clear precursor phenomena near the first-order transition and spontaneous nucleation. The kinetics of the domain growth is studied and found to be exceedingly slow. The results are applicable for martensitic transformations and structural surface...

The lattice Boltzmann model for the second-order Benjamin–Ono equations

International Nuclear Information System (INIS)

Lai, Huilin; Ma, Changfeng

2010-01-01

In this paper, in order to extend the lattice Boltzmann method to deal with more complicated nonlinear equations, we propose a 1D lattice Boltzmann scheme with an amending function for the second-order (1 + 1)-dimensional Benjamin–Ono equation. With the Taylor expansion and the Chapman–Enskog expansion, the governing evolution equation is recovered correctly from the continuous Boltzmann equation. The equilibrium distribution function and the amending function are obtained. Numerical simulations are carried out for the 'good' Boussinesq equation and the 'bad' one to validate the proposed model. It is found that the numerical results agree well with the analytical solutions. The present model can be used to solve more kinds of nonlinear partial differential equations

Leading-order classical Lagrangians for the nonminimal standard-model extension

Science.gov (United States)

Reis, J. A. A. S.; Schreck, M.

2018-03-01

In this paper, we derive the general leading-order classical Lagrangian covering all fermion operators of the nonminimal standard-model extension (SME). Such a Lagrangian is considered to be the point-particle analog of the effective field theory description of Lorentz violation that is provided by the SME. At leading order in Lorentz violation, the Lagrangian obtained satisfies the set of five nonlinear equations that govern the map from the field theory to the classical description. This result can be of use for phenomenological studies of classical bodies in gravitational fields.

Determination of the Factors Influencing Store Preference in Erzurum by a Multinomial Logit Model

Directory of Open Access Journals (Sweden)

Hüseyin ÖZER

2008-12-01

Full Text Available The main objective of this study is to determine factors influencing store preference of the store costumers in Erzurum in terms of some characteristics of the store and its product and costumers’ demographic characteristics (sex, age, marital status, level of education and their income level. In order to carry out this objective, Pearson chi-square test is applied to determine whether there is a relationship between the store preference and customer, stores, and some characteristics of products and a multinominal logit model is fitted by stepwise regression method to the cross-section data compiled from a questionnaire applied to 384 store costumers in the center of Erzurum province. According to the model estimation and test results, the variables of marital status (married, education (primary and cheapness (unimportant for Migros; education (middle for Özmar and marital status (married for the other stores are determined as statistically significant at the level of 5 percent

Numerical Analysis of Fractional Order Epidemic Model of Childhood Diseases

Directory of Open Access Journals (Sweden)

Fazal Haq

2017-01-01

Full Text Available The fractional order Susceptible-Infected-Recovered (SIR epidemic model of childhood disease is considered. Laplace–Adomian Decomposition Method is used to compute an approximate solution of the system of nonlinear fractional differential equations. We obtain the solutions of fractional differential equations in the form of infinite series. The series solution of the proposed model converges rapidly to its exact value. The obtained results are compared with the classical case.

The influence of discovery learning model application to the higher order thinking skills student of Srijaya Negara Senior High School Palembang on the animal kingdom subject matter

Science.gov (United States)

Riandari, F.; Susanti, R.; Suratmi

2018-05-01

This study aimed to find out the information in concerning the influence of discovery learning model application to the higher order thinking skills at the tenth grade students of Srijaya Negara senior high school Palembang on the animal kingdom subject matter. The research method used was pre-experimental with one-group pretest-posttest design. The researchconducted at Srijaya Negara senior high school Palembang academic year 2016/2017. The population sample of this research was tenth grade students of natural science 2. Purposive sampling techniquewas applied in this research. Data was collected by(1) the written test, consist of pretest to determine the initial ability and posttest to determine higher order thinking skills of students after learning by using discovery learning models. (2) Questionnaire sheet, aimed to investigate the response of the students during the learning process by using discovery learning models. The t-test result indicated there was significant increasement of higher order thinking skills students. Thus, it can be concluded that the application of discovery learning modelhad a significant effect and increased to higher order thinking skills students of Srijaya Negara senior high school Palembang on the animal kingdom subject matter.

Vortex network community based reduced-order force model

Science.gov (United States)

Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko

2017-11-01

We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).

26 CFR 1.6664-3 - Ordering rules for determining the total amount of penalties imposed.

Science.gov (United States)

2010-04-01

... OF THE TREASURY (CONTINUED) INCOME TAX (CONTINUED) INCOME TAXES Additions to the Tax, Additional... that the taxpayers made a timely estimated tax payment of $1,500 for 1989 which they failed to claim... imposed. (a) In general. This section provides rules for determining the order in which adjustments to a...

Jacobian projection reduced-order models for dynamic systems with contact nonlinearities

Science.gov (United States)

Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.

2018-02-01

In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.

Basic first-order model theory in Mizar

Directory of Open Access Journals (Sweden)

Marco Bright Caminati

2010-01-01

Full Text Available The author has submitted to Mizar Mathematical Library a series of five articles introducing a framework for the formalization of classical first-order model theory.In them, Goedel's completeness and Lowenheim-Skolem theorems have also been formalized for the countable case, to offer a first application of it and to showcase its utility.This is an overview and commentary on some key aspects of this setup.It features exposition and discussion of a new encoding of basic definitions and theoretical gears needed for the task, remarks about the design strategies and approaches adopted in their implementation, and more general reflections about proof checking induced by the work done.

Unconventional and intertwined orders of the low-dimensional Hubbard model

International Nuclear Information System (INIS)

Leprevost, Alexandre

2015-01-01

The understanding of superconductivity exhibited at high critical temperature by certain transition metal oxides remains a central issue in theoretical condensed matter physics. In this context, and since the historical proposal by P. W. Anderson, the repulsive Hubbard model in two dimensions became a paradigm in an attempt to capture the essential properties of non-conventional superconducting materials. However, the determination of the exact ground state encounters the exponential complexity of the quantum many-body problem. The main purpose of this thesis is to develop a variational scheme free of any hypothesis concerning magnetic, charge or superconducting orders likely to emerge from the Hamiltonian at low energy. The originality of the approach is found in the introduction of correlations by restoring, before variation, symmetries deliberately broken in a trial state given by a superposition of versatile wavefunctions of Hartree-Fock and Bogoliubov-de Gennes types. For small clusters of two and four sites, we show analytically that this symmetry entangled mean field method allows to find the exact ground state regardless of the strength of the on-site interaction. For larger hole-doped clusters and in the strongly correlated regime, we highlight an arrangement of magnetic moments in a spiral or in a spin density wave that is then accompanied by inhomogeneities in the form of regularly distributed stripes. Moreover, such orders are intertwined with long range d-wave pairing correlations, which, in the thermodynamic limit, sign superconductivity. These results are obtained through systematic simulations in a four-leg tube geometry that can be realized experimentally using cold atoms trapped in optical lattices. (author) [fr

Third-order least squares modelling of milling state term for improved computation of stability boundaries

Directory of Open Access Journals (Sweden)

C.G. Ozoegwu

2016-01-01

Full Text Available The general least squares model for milling process state term is presented. A discrete map for milling stability analysis that is based on the third-order case of the presented general least squares milling state term model is first studied and compared with its third-order counterpart that is based on the interpolation theory. Both numerical rate of convergence and chatter stability results of the two maps are compared using the single degree of freedom (1DOF milling model. The numerical rate of convergence of the presented third-order model is also studied using the two degree of freedom (2DOF milling process model. Comparison gave that stability results from the two maps agree closely but the presented map demonstrated reduction in number of needed calculations leading to about 30% savings in computational time (CT. It is seen in earlier works that accuracy of milling stability analysis using the full-discretization method rises from first-order theory to second-order theory and continues to rise to the third-order theory. The present work confirms this trend. In conclusion, the method presented in this work will enable fast and accurate computation of stability diagrams for use by machinists.

Large-order behavior of nondecoupling effects in the standard model and triviality

International Nuclear Information System (INIS)

Aoki, K.

1994-01-01

We compute some nondecoupling effects in the standard model, such as the ρ parameter, to all orders in the coupling constant expansion. We analyze their large order behavior and explicitly show how they are related to the nonperturbative cutoff dependence of these nondecoupling effects due to the triviality of the theory

Topological order in an exactly solvable 3D spin model

International Nuclear Information System (INIS)

Bravyi, Sergey; Leemhuis, Bernhard; Terhal, Barbara M.

2011-01-01

Research highlights: RHtriangle We study exactly solvable spin model with six-qubit nearest neighbor interactions on a 3D face centered cubic lattice. RHtriangle The ground space of the model exhibits topological quantum order. RHtriangle Elementary excitations can be geometrically described as the corners of rectangular-shaped membranes. RHtriangle The ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. RHtriangle Logical operators acting on the encoded qubits are described in terms of closed strings and closed membranes. - Abstract: We study a 3D generalization of the toric code model introduced recently by Chamon. This is an exactly solvable spin model with six-qubit nearest-neighbor interactions on an FCC lattice whose ground space exhibits topological quantum order. The elementary excitations of this model which we call monopoles can be geometrically described as the corners of rectangular-shaped membranes. We prove that the creation of an isolated monopole separated from other monopoles by a distance R requires an operator acting on Ω(R 2 ) qubits. Composite particles that consist of two monopoles (dipoles) and four monopoles (quadrupoles) can be described as end-points of strings. The peculiar feature of the model is that dipole-type strings are rigid, that is, such strings must be aligned with face-diagonals of the lattice. For periodic boundary conditions the ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. We describe a complete set of logical operators acting on the encoded qubits in terms of closed strings and closed membranes.

[Social determinants of odontalgia in epidemiological studies: theoretical review and proposed conceptual model].

Science.gov (United States)

Bastos, João Luiz Dornelles; Gigante, Denise Petrucci; Peres, Karen Glazer; Nedel, Fúlvio Borges

2007-01-01

The epidemiological literature has been limited by the absence of a theoretical framework reflecting the complexity of causal mechanisms for the occurrence of health phenomena / disease conditions. In the field of oral epidemiology, such lack of theory also prevails, since dental caries the leading topic in oral research has been often studied through a biological and reductionist viewpoint. One of the most important consequences of dental caries is dental pain (odontalgia), which has received little attention in studies with sophisticated theoretical models and powerful designs to establish causal relationships. The purpose of this study is to review the scientific literature on the determinants of odontalgia and to discuss theories proposed for the explanation of the phenomenon. Conceptual models and emerging theories on the social determinants of oral health are revised, in an attempt to build up links with the bio-psychosocial pain model, proposing a more elaborate causal model for odontalgia. The framework suggests causal pathways between social structure and oral health through material, psychosocial and behavioral pathways. Aspects of the social structure are highlighted in order to relate them to odontalgia, stressing their importance in discussions of causal relationships in oral health research.

Fractional order modeling and control of dissimilar redundant actuating system used in large passenger aircraft

Directory of Open Access Journals (Sweden)

Salman IJAZ

2018-05-01

Full Text Available In this paper, a methodology has been developed to address the issue of force fighting and to achieve precise position tracking of control surface driven by two dissimilar actuators. The nonlinear dynamics of both actuators are first approximated as fractional order models. Based on the identified models, three fractional order controllers are proposed for the whole system. Two Fractional Order PID (FOPID controllers are dedicated to improving transient response and are designed in a position feedback configuration. In order to synchronize the actuator dynamics, a third fractional order PI controller is designed, which feeds the force compensation signal in position feedback loop of both actuators. Nelder-Mead (N-M optimization technique is employed in order to optimally tune controller parameters based on the proposed performance criteria. To test the proposed controllers according to real flight condition, an external disturbance of higher amplitude that acts as airload is applied directly on the control surface. In addition, a disturbance signal function of system states is applied to check the robustness of proposed controller. Simulation results on nonlinear system model validated the performance of the proposed scheme as compared to optimal PID and high gain PID controllers. Keywords: Aerospace, Fractional order control, Model identification, Nelder-Mead optimization, Robustness

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

Science.gov (United States)

Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José

2017-05-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant-Friedrichs-Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational

Empirical Reduced-Order Modeling for Boundary Feedback Flow Control

Directory of Open Access Journals (Sweden)

Seddik M. Djouadi

2008-01-01

Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.

Reduced-Order Structure-Preserving Model for Parallel-Connected Three-Phase Grid-Tied Inverters: Preprint

Energy Technology Data Exchange (ETDEWEB)

Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Purba, Victor [University of Minnesota; Jafarpour, Saber [University of California, Santa Barbara; Bullo, Francesco [University of California, Santa Barbara; Dhople, Sairaj [University of Minnesota

2017-08-31

Given that next-generation infrastructures will contain large numbers of grid-connected inverters and these interfaces will be satisfying a growing fraction of system load, it is imperative to analyze the impacts of power electronics on such systems. However, since each inverter model has a relatively large number of dynamic states, it would be impractical to execute complex system models where the full dynamics of each inverter are retained. To address this challenge, we derive a reduced-order structure-preserving model for parallel-connected grid-tied three-phase inverters. Here, each inverter in the system is assumed to have a full-bridge topology, LCL filter at the point of common coupling, and the control architecture for each inverter includes a current controller, a power controller, and a phase-locked loop for grid synchronization. We outline a structure-preserving reduced-order inverter model for the setting where the parallel inverters are each designed such that the filter components and controller gains scale linearly with the power rating. By structure preserving, we mean that the reduced-order three-phase inverter model is also composed of an LCL filter, a power controller, current controller, and PLL. That is, we show that the system of parallel inverters can be modeled exactly as one aggregated inverter unit and this equivalent model has the same number of dynamical states as an individual inverter in the paralleled system. Numerical simulations validate the reduced-order models.

The order of chaos on a Bianch IX cosmological model

Energy Technology Data Exchange (ETDEWEB)

Bugalho, H; da Silva, A R; Ramos, J S

1986-12-01

The purpose of this paper is to analyze the chaotic behavior that can arise on a type-IX cosmological model using methods from dynamic systems theory and symbolic dynamics. Specifically, instead of the Belinski-Khalatnikov-Lifschitz model, we use the iterates of a monotonously increasing map of the circle with a discontinuity, and for the Hamiltonian dynamics of Misner's Mixmaster model we introduce the iterates of a noninvertible map. An equivalence between these two models can easily be brought upon by translating them in symbolic dynamical terms. The resulting symbolic orbits can be inserted in an ordered tree structure set, and so we can present an effective counting and referentation of all period orbits.

Determination of a suitable set of loss models for centrifugal compressor performance prediction

Directory of Open Access Journals (Sweden)

Elkin I. GUTIÉRREZ VELÁSQUEZ

2017-10-01

Full Text Available Performance prediction in preliminary design stages of several turbomachinery components is a critical task in order to bring the design processes of these devices to a successful conclusion. In this paper, a review and analysis of the major loss mechanisms and loss models, used to determine the efficiency of a single stage centrifugal compressor, and a subsequent examination to determine an appropriate loss correlation set for estimating the isentropic efficiency in preliminary design stages of centrifugal compressors, were developed. Several semi-empirical correlations, commonly used to predict the efficiency of centrifugal compressors, were implemented in FORTRAN code and then were compared with experimental results in order to establish a loss correlation set to determine, with good approximation, the isentropic efficiency of single stage compressor. The aim of this study is to provide a suitable loss correlation set for determining the isentropic efficiency of a single stage centrifugal compressor, because, with a large amount of loss mechanisms and correlations available in the literature, it is difficult to ascertain how many and which correlations to employ for the correct prediction of the efficiency in the preliminary stage design of a centrifugal compressor. As a result of this study, a set of correlations composed by nine loss mechanisms for single stage centrifugal compressors, conformed by a rotor and a diffuser, are specified.

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

Energy Technology Data Exchange (ETDEWEB)

Liu, Youshan, E-mail: ysliu@mail.iggcas.ac.cn [State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 (China); Teng, Jiwen, E-mail: jwteng@mail.iggcas.ac.cn [State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 (China); Xu, Tao, E-mail: xutao@mail.iggcas.ac.cn [State Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029 (China); CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100101 (China); Badal, José, E-mail: badal@unizar.es [Physics of the Earth, Sciences B, University of Zaragoza, Pedro Cerbuna 12, 50009 Zaragoza (Spain)

2017-05-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant–Friedrichs–Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational

Higher-order triangular spectral element method with optimized cubature points for seismic wavefield modeling

International Nuclear Information System (INIS)

Liu, Youshan; Teng, Jiwen; Xu, Tao; Badal, José

2017-01-01

The mass-lumped method avoids the cost of inverting the mass matrix and simultaneously maintains spatial accuracy by adopting additional interior integration points, known as cubature points. To date, such points are only known analytically in tensor domains, such as quadrilateral or hexahedral elements. Thus, the diagonal-mass-matrix spectral element method (SEM) in non-tensor domains always relies on numerically computed interpolation points or quadrature points. However, only the cubature points for degrees 1 to 6 are known, which is the reason that we have developed a p-norm-based optimization algorithm to obtain higher-order cubature points. In this way, we obtain and tabulate new cubature points with all positive integration weights for degrees 7 to 9. The dispersion analysis illustrates that the dispersion relation determined from the new optimized cubature points is comparable to that of the mass and stiffness matrices obtained by exact integration. Simultaneously, the Lebesgue constant for the new optimized cubature points indicates its surprisingly good interpolation properties. As a result, such points provide both good interpolation properties and integration accuracy. The Courant–Friedrichs–Lewy (CFL) numbers are tabulated for the conventional Fekete-based triangular spectral element (TSEM), the TSEM with exact integration, and the optimized cubature-based TSEM (OTSEM). A complementary study demonstrates the spectral convergence of the OTSEM. A numerical example conducted on a half-space model demonstrates that the OTSEM improves the accuracy by approximately one order of magnitude compared to the conventional Fekete-based TSEM. In particular, the accuracy of the 7th-order OTSEM is even higher than that of the 14th-order Fekete-based TSEM. Furthermore, the OTSEM produces a result that can compete in accuracy with the quadrilateral SEM (QSEM). The high accuracy of the OTSEM is also tested with a non-flat topography model. In terms of computational

Hemi-ordered nanoporous carbon electrode material for highly selective determination of nitrite in physiological and environmental systems

Energy Technology Data Exchange (ETDEWEB)

Zhou, Shenghai; Wu, Hongmin; Wu, Ying; Shi, Hongyan; Feng, Xun; Jiang, Shang; Chen, Jian; Song, Wenbo, E-mail: wbsong@jlu.edu.cn

2014-08-01

Hemi-ordered nanoporous carbon (HONC) was obtained from a mesoporous silica template through a nano-replication method using furfuryl alcohol as the carbon source. The structure and morphology of HONC were characterized and analyzed in detail by X-ray diffraction, N{sub 2}-sorption, Raman spectroscopy and transmission electron microscopy. HONC was then demonstrated as active electrode material for selective determination of nitrite in either physiological or environmental system. Well separated oxidation peaks of ascorbic acid, dopamine, uric acid and nitrite were observed in physiological system, and simultaneous discrimination of catechol, hydroquinone, resorcinol and nitrite in environmental system was also accomplished. Distinctly improved performances for selective determination of nitrite (such as significantly fast and sensitive current response with especially high selectivity) coexisted with ascorbic acid, dopamine and uric acid in the physiological system, as well as with catechol, hydroquinone and resorcinol in the environmental system were achieved at HONC electrode material. The excellent discriminating ability and high selectivity for NO{sub 2}{sup −} determination were ascribed to the good electronic conductivity, unique hemi-ordered porous structure, large surface area and large number of edge plane defect sites contained on the surface of nanopore walls of HONC. Results in this work demonstrated that HONC is one of the promising catalytic electrode materials for nitrite sensor fabrication. - Highlights: • Hemi-ordered nanoporous carbon as an active electrode material • Good discriminating ability towards NO{sub 2}{sup −} from physiological or environmental system • Highly selective determination of nitrite with fast and sensitive current response.

Application of aggregation techniques for model order reduction of nuclear plants for operator guidance systems

International Nuclear Information System (INIS)

Zwingelstein, G.C.

1980-12-01

After a short description of a disturbance analysis system for nuclear plant based on real time dynamic modelling and simulation, a scheme for generating aggregated reduced models of high order systems is presented. This method allows the choice of dominant dynamic modes and its efficiency is illustrated for the case of a 29th order nuclear plant model

Index-aware model order reduction : LTI DAEs in electric networks

NARCIS (Netherlands)

Banagaaya, N.; Schilders, W.H.A.; Ali, G.; Tischendorf, C.

2014-01-01

Purpose Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues. Design/methodology/approach Most methods first do an index reduction before reducing a

Determination of sex-ratio by birth order in an urban community in Manipur.

Science.gov (United States)

Brogen, Akoijam S; Shantibala, K; Rajkumari, Bishwalata; Laishram, Jalina

2009-01-01

To determine the sex ratio by birth order and to assess the sex preference of the couples in an urban community. A cross sectional study, in an urban community in Manipur, was conducted among the currently married couples. Data on background characteristics of the couple, family pedigree chart (of the offspring) including history of abortion, stillbirth, death of child of the couple, sex preference and Pre-natal Diagnostic Techniques (Regulation and Prevention of Misuse) Act [PNDT Act] were collected through a structured interview. Data were analyzed using descriptive and chi-square statistics. There were a total of 1777 births to the 855 couples interviewed. There were 900 females per 1000 males for the 1st birth order but the sex ratio was favorable towards females in the 2nd, 3rd and 4th birth orders. Among both the husbands and wives, being more educated was significantly associated (p<0.05) with preferring lesser number of children, using new technology for sex selection and having heard of the PNDT Act. Majority of those who wanted to use new technology for sex selection (128, 56.6%) preferred to have male child. Sex ratio in this community was favorable towards females, though it was less among the first born babies.

Anomalous NMR Relaxation in Cartilage Matrix Components and Native Cartilage: Fractional-Order Models

Science.gov (United States)

Magin, Richard L.; Li, Weiguo; Velasco, M. Pilar; Trujillo, Juan; Reiter, David A.; Morgenstern, Ashley; Spencer, Richard G.

2011-01-01

We present a fractional-order extension of the Bloch equations to describe anomalous NMR relaxation phenomena (T1 and T2). The model has solutions in the form of Mittag-Leffler and stretched exponential functions that generalize conventional exponential relaxation. Such functions have been shown by others to be useful for describing dielectric and viscoelastic relaxation in complex, heterogeneous materials. Here, we apply these fractional-order T1 and T2 relaxation models to experiments performed at 9.4 and 11.7 Tesla on type I collagen gels, chondroitin sulfate mixtures, and to bovine nasal cartilage (BNC), a largely isotropic and homogeneous form of cartilage. The results show that the fractional-order analysis captures important features of NMR relaxation that are typically described by multi-exponential decay models. We find that the T2 relaxation of BNC can be described in a unique way by a single fractional-order parameter (α), in contrast to the lack of uniqueness of multi-exponential fits in the realistic setting of a finite signal-to-noise ratio. No anomalous behavior of T1 was observed in BNC. In the single-component gels, for T2 measurements, increasing the concentration of the largest components of cartilage matrix, collagen and chondroitin sulfate, results in a decrease in α, reflecting a more restricted aqueous environment. The quality of the curve fits obtained using Mittag-Leffler and stretched exponential functions are in some cases superior to those obtained using mono- and bi-exponential models. In both gels and BNC, α appears to account for microstructural complexity in the setting of an altered distribution of relaxation times. This work suggests the utility of fractional-order models to describe T2 NMR relaxation processes in biological tissues. PMID:21498095

An MGF-based unified framework to determine the joint statistics of partial sums of ordered random variables

KAUST Repository

Nam, Sungsik

2010-11-01

Order statistics find applications in various areas of communications and signal processing. In this paper, we introduce an unified analytical framework to determine the joint statistics of partial sums of ordered random variables (RVs). With the proposed approach, we can systematically derive the joint statistics of any partial sums of ordered statistics, in terms of the moment generating function (MGF) and the probability density function (PDF). Our MGF-based approach applies not only when all the K ordered RVs are involved but also when only the Ks(Ks < K) best RVs are considered. In addition, we present the closed-form expressions for the exponential RV special case. These results apply to the performance analysis of various wireless communication systems over fading channels. © 2006 IEEE.

Modeling 3D PCMI using the Extended Finite Element Method with higher order elements

Energy Technology Data Exchange (ETDEWEB)

Jiang, W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Spencer, Benjamin W. [Idaho National Lab. (INL), Idaho Falls, ID (United States)

2017-03-31

This report documents the recent development to enable XFEM to work with higher order elements. It also demonstrates the application of higher order (quadratic) elements to both 2D and 3D models of PCMI problems, where discrete fractures in the fuel are represented using XFEM. The modeling results demonstrate the ability of the higher order XFEM to accurately capture the effects of a crack on the response in the vicinity of the intersecting surfaces of cracked fuel and cladding, as well as represent smooth responses in the regions away from the crack.

Limit order book and its modeling in terms of Gibbs Grand-Canonical Ensemble

Science.gov (United States)

Bicci, Alberto

2016-12-01

In the domain of so called Econophysics some attempts have been already made for applying the theory of thermodynamics and statistical mechanics to economics and financial markets. In this paper a similar approach is made from a different perspective, trying to model the limit order book and price formation process of a given stock by the Grand-Canonical Gibbs Ensemble for the bid and ask orders. The application of the Bose-Einstein statistics to this ensemble allows then to derive the distribution of the sell and buy orders as a function of price. As a consequence we can define in a meaningful way expressions for the temperatures of the ensembles of bid orders and of ask orders, which are a function of minimum bid, maximum ask and closure prices of the stock as well as of the exchanged volume of shares. It is demonstrated that the difference between the ask and bid orders temperatures can be related to the VAO (Volume Accumulation Oscillator), an indicator empirically defined in Technical Analysis of stock markets. Furthermore the derived distributions for aggregate bid and ask orders can be subject to well defined validations against real data, giving a falsifiable character to the model.

Dynamics of a Fractional Order HIV Infection Model with Specific Functional Response and Cure Rate

Directory of Open Access Journals (Sweden)

Adnane Boukhouima

2017-01-01

Full Text Available We propose a fractional order model in this paper to describe the dynamics of human immunodeficiency virus (HIV infection. In the model, the infection transmission process is modeled by a specific functional response. First, we show that the model is mathematically and biologically well posed. Second, the local and global stabilities of the equilibria are investigated. Finally, some numerical simulations are presented in order to illustrate our theoretical results.

The importance and use of asymptotic freedom beyond the leading order

International Nuclear Information System (INIS)

Duke, D.W.

1979-05-01

The theoretical and phenomenological importance of asymptotic freedom beyond the leading order is discussed. The two main topics are (1) the determination of the fundamental scale Λ, and (2) ambiguities in parton model definitions when using the higher order effects of asymptotic freedom. (author)

Analysis of a decision model in the context of equilibrium pricing and order book pricing

Science.gov (United States)

Wagner, D. C.; Schmitt, T. A.; Schäfer, R.; Guhr, T.; Wolf, D. E.

2014-12-01

An agent-based model for financial markets has to incorporate two aspects: decision making and price formation. We introduce a simple decision model and consider its implications in two different pricing schemes. First, we study its parameter dependence within a supply-demand balance setting. We find realistic behavior in a wide parameter range. Second, we embed our decision model in an order book setting. Here, we observe interesting features which are not present in the equilibrium pricing scheme. In particular, we find a nontrivial behavior of the order book volumes which reminds of a trend switching phenomenon. Thus, the decision making model alone does not realistically represent the trading and the stylized facts. The order book mechanism is crucial.

Roof planes detection via a second-order variational model

Science.gov (United States)

Benciolini, Battista; Ruggiero, Valeria; Vitti, Alfonso; Zanetti, Massimo

2018-04-01

The paper describes a unified automatic procedure for the detection of roof planes in gridded height data. The procedure exploits the Blake-Zisserman (BZ) model for segmentation in both 2D and 1D, and aims to detect, to model and to label roof planes. The BZ model relies on the minimization of a functional that depends on first- and second-order derivatives, free discontinuities and free gradient discontinuities. During the minimization, the relative strength of each competitor is controlled by a set of weight parameters. By finding the minimum of the approximated BZ functional, one obtains: (1) an approximation of the data that is smoothed solely within regions of homogeneous gradient, and (2) an explicit detection of the discontinuities and gradient discontinuities of the approximation. Firstly, input data is segmented using the 2D BZ. The maps of data and gradient discontinuities are used to isolate building candidates and planar patches (i.e. regions with homogeneous gradient) that correspond to roof planes. Connected regions that can not be considered as buildings are filtered according to both patch dimension and distribution of the directions of the normals to the boundary. The 1D BZ model is applied to the curvilinear coordinates of boundary points of building candidates in order to reduce the effect of data granularity when the normals are evaluated. In particular, corners are preserved and can be detected by means of gradient discontinuity. Lastly, a total least squares model is applied to estimate the parameters of the plane that best fits the points of each planar patch (orthogonal regression with planar model). Refinement of planar patches is performed by assigning those points that are close to the boundaries to the planar patch for which a given proximity measure assumes the smallest value. The proximity measure is defined to account for the variance of a fitting plane and a weighted distance of a point from the plane. The effectiveness of the

A critical look at the kinetic models of thermoluminescence-II. Non-first order kinetics

International Nuclear Information System (INIS)

Sunta, C M; Ayta, W E F; Chubaci, J F D; Watanabe, S

2005-01-01

Non-first order (FO) kinetics models are of three types; second order (SO), general order (GO) and mixed order (MO). It is shown that all three of these have constraints in their energy level schemes and their applicable parameter values. In nature such restrictions are not expected to exist. The thermoluminescence (TL) glow peaks produced by these models shift their position and change their shape as the trap occupancies change. Such characteristics are very unlike those found in samples of real materials. In these models, in general, retrapping predominates over recombination. It is shown that the quasi-equilibrium (QE) assumption implied in the derivation of the TL equation of these models is quite valid, thus disproving earlier workers' conclusion that QE cannot be held under retrapping dominant conditions. However notwithstanding their validity, they suffer from the shortcomings as stated above and have certain lacunae. For example, the kinetic order (KO) parameter and the pre-exponential factor which are assumed to be the constant parameters of the GO kinetics expression turn out to be variables when this expression is applied to plausible physical models. Further, in glow peak characterization using the GO expression, the quality of fit is found to deteriorate when the best fitted value of KO parameter is different from 1 and 2. This means that the found value of the basic parameter, namely the activation energy, becomes subject to error. In the MO kinetics model, the value of the KO parameter α would change with dose, and thus in this model also, as in the GO model, no single value of KO can be assigned to a given glow peak. The paper discusses TL of real materials having characteristics typically like those of FO kinetics. Theoretically too, a plausible physical model of TL emission produces glow peaks which have characteristics of FO kinetics under a wide variety of parametric combinations. In the background of the above findings, it is suggested that

Higher order and heavy quark mass effects in the determination of parton distribution functions

Energy Technology Data Exchange (ETDEWEB)

Bertone, Valerio

2013-07-01

The present thesis was devoted to the study of the inclusion of higher-order corrections and heavy quark mass effects in a PDF determination. This has been carried out in the NNPDF framework resulting originally in the NNPDF2.1 sets, which were at a later stage supplemented by the first LHC data leading to the most recent NNPDF2.3 sets. In Chapter 1 the concept of Parton Distribution Function (PDF) was introduced. We have shown how the analytical computation of the Deep-Inelastic-Scattering (DIS) process at order α{sub s} in QCD leads to initial-stale collinear divergences which, using the factorization theorem, can be reabsorbed into the PDFs. The energy dependence of PDFs is fully determined and the task is then reduced to the determination of the x (Bjorken variable) dependence. In Chapter 2 a detailed discussion of the factorization schemes presently available to include heavy quark mass effects into DIS structure functions has been given. It emerged that there are two possible basic approaches to the calculation of the DIS structure functions. In the first approach, the so-called Fixed-Flavour-Number Scheme (FFNS), the calculation is performed retaining the quark mass of the heavy flavours which provide a ''natural'' regulator for the infrared divergences. In the second approach, called Zero-Mass Variable-Flavour-Number Scheme (ZM-VFNS), the heavy quark masses are instead set to zero and this gives rise to the usual final-state collinear divergences that are absorbed into the PDFs. In addition, in the ZM-VFNS, the number of active flavours is assumed to increase by one unity as the energy of the process crosses the energy threshold of a given heavy quark. In order to obtain a factorization scheme that is accurate both at large and low energies, several prescriptions that interpolate between FFNS at low energy and ZM-VFNS at large energy have been proposed and implemented in as many PDF fits. In Chapter 2 they have been described showing how they behave for

Higher order and heavy quark mass effects in the determination of parton distribution functions

Energy Technology Data Exchange (ETDEWEB)

Bertone, Valerio

2013-07-01

The present thesis was devoted to the study of the inclusion of higher-order corrections and heavy quark mass effects in a PDF determination. This has been carried out in the NNPDF framework resulting originally in the NNPDF2.1 sets, which were at a later stage supplemented by the first LHC data leading to the most recent NNPDF2.3 sets. In Chapter 1 the concept of Parton Distribution Function (PDF) was introduced. We have shown how the analytical computation of the Deep-Inelastic-Scattering (DIS) process at order α{sub s} in QCD leads to initial-stale collinear divergences which, using the factorization theorem, can be reabsorbed into the PDFs. The energy dependence of PDFs is fully determined and the task is then reduced to the determination of the x (Bjorken variable) dependence. In Chapter 2 a detailed discussion of the factorization schemes presently available to include heavy quark mass effects into DIS structure functions has been given. It emerged that there are two possible basic approaches to the calculation of the DIS structure functions. In the first approach, the so-called Fixed-Flavour-Number Scheme (FFNS), the calculation is performed retaining the quark mass of the heavy flavours which provide a ''natural'' regulator for the infrared divergences. In the second approach, called Zero-Mass Variable-Flavour-Number Scheme (ZM-VFNS), the heavy quark masses are instead set to zero and this gives rise to the usual final-state collinear divergences that are absorbed into the PDFs. In addition, in the ZM-VFNS, the number of active flavours is assumed to increase by one unity as the energy of the process crosses the energy threshold of a given heavy quark. In order to obtain a factorization scheme that is accurate both at large and low energies, several prescriptions that interpolate between FFNS at low energy and ZM-VFNS at large energy have been proposed and implemented in as many PDF fits. In Chapter 2 they have been described showing

Higher order and heavy quark mass effects in the determination of parton distribution functions

International Nuclear Information System (INIS)

Bertone, Valerio

2013-01-01

The present thesis was devoted to the study of the inclusion of higher-order corrections and heavy quark mass effects in a PDF determination. This has been carried out in the NNPDF framework resulting originally in the NNPDF2.1 sets, which were at a later stage supplemented by the first LHC data leading to the most recent NNPDF2.3 sets. In Chapter 1 the concept of Parton Distribution Function (PDF) was introduced. We have shown how the analytical computation of the Deep-Inelastic-Scattering (DIS) process at order α s in QCD leads to initial-stale collinear divergences which, using the factorization theorem, can be reabsorbed into the PDFs. The energy dependence of PDFs is fully determined and the task is then reduced to the determination of the x (Bjorken variable) dependence. In Chapter 2 a detailed discussion of the factorization schemes presently available to include heavy quark mass effects into DIS structure functions has been given. It emerged that there are two possible basic approaches to the calculation of the DIS structure functions. In the first approach, the so-called Fixed-Flavour-Number Scheme (FFNS), the calculation is performed retaining the quark mass of the heavy flavours which provide a ''natural'' regulator for the infrared divergences. In the second approach, called Zero-Mass Variable-Flavour-Number Scheme (ZM-VFNS), the heavy quark masses are instead set to zero and this gives rise to the usual final-state collinear divergences that are absorbed into the PDFs. In addition, in the ZM-VFNS, the number of active flavours is assumed to increase by one unity as the energy of the process crosses the energy threshold of a given heavy quark. In order to obtain a factorization scheme that is accurate both at large and low energies, several prescriptions that interpolate between FFNS at low energy and ZM-VFNS at large energy have been proposed and implemented in as many PDF fits. In Chapter 2 they have been described showing how

Implementation of higher-order vertical finite elements in ISSM v4.13 for improved ice sheet flow modeling over paleoclimate timescales

Science.gov (United States)

Cuzzone, Joshua K.; Morlighem, Mathieu; Larour, Eric; Schlegel, Nicole; Seroussi, Helene

2018-05-01

Paleoclimate proxies are being used in conjunction with ice sheet modeling experiments to determine how the Greenland ice sheet responded to past changes, particularly during the last deglaciation. Although these comparisons have been a critical component in our understanding of the Greenland ice sheet sensitivity to past warming, they often rely on modeling experiments that favor minimizing computational expense over increased model physics. Over Paleoclimate timescales, simulating the thermal structure of the ice sheet has large implications on the modeled ice viscosity, which can feedback onto the basal sliding and ice flow. To accurately capture the thermal field, models often require a high number of vertical layers. This is not the case for the stress balance computation, however, where a high vertical resolution is not necessary. Consequently, since stress balance and thermal equations are generally performed on the same mesh, more time is spent on the stress balance computation than is otherwise necessary. For these reasons, running a higher-order ice sheet model (e.g., Blatter-Pattyn) over timescales equivalent to the paleoclimate record has not been possible without incurring a large computational expense. To mitigate this issue, we propose a method that can be implemented within ice sheet models, whereby the vertical interpolation along the z axis relies on higher-order polynomials, rather than the traditional linear interpolation. This method is tested within the Ice Sheet System Model (ISSM) using quadratic and cubic finite elements for the vertical interpolation on an idealized case and a realistic Greenland configuration. A transient experiment for the ice thickness evolution of a single-dome ice sheet demonstrates improved accuracy using the higher-order vertical interpolation compared to models using the linear vertical interpolation, despite having fewer degrees of freedom. This method is also shown to improve a model's ability to capture sharp

Construction of special eye models for investigation of chromatic and higher-order aberrations of eyes.

Science.gov (United States)

Zhai, Yi; Wang, Yan; Wang, Zhaoqi; Liu, Yongji; Zhang, Lin; He, Yuanqing; Chang, Shengjiang

2014-01-01

An achromatic element eliminating only longitudinal chromatic aberration (LCA) while maintaining transverse chromatic aberration (TCA) is established for the eye model, which involves the angle formed by the visual and optical axis. To investigate the impacts of higher-order aberrations on vision, the actual data of higher-order aberrations of human eyes with three typical levels are introduced into the eye model along visual axis. Moreover, three kinds of individual eye models are established to investigate the impacts of higher-order aberrations, chromatic aberration (LCA+TCA), LCA and TCA on vision under the photopic condition, respectively. Results show that for most human eyes, the impact of chromatic aberration on vision is much stronger than that of higher-order aberrations, and the impact of LCA in chromatic aberration dominates. The impact of TCA is approximately equal to that of normal level higher-order aberrations and it can be ignored when LCA exists.

Birth Order and Susceptibility to Peer Modeling Influences in Young Boys

Science.gov (United States)

Finley, Gordon E.; Cheyne, James A.

1976-01-01

Susceptibility to peer modeling influences as a function of birth order was studied by examining the data of 390 boys from kindergarten through third grade who previously had participated in moral transgression experiments. (MS)

Testing the Processing Hypothesis of word order variation using a probabilistic language model

NARCIS (Netherlands)

Bloem, J.

2016-01-01

This work investigates the application of a measure of surprisal to modeling a grammatical variation phenomenon between near-synonymous constructions. We investigate a particular variation phenomenon, word order variation in Dutch two-verb clusters, where it has been established that word order

Low degree Earth's gravity coefficients determined from different space geodetic observations and climate models

Science.gov (United States)

Wińska, Małgorzata; Nastula, Jolanta

2017-04-01

Large scale mass redistribution and its transport within the Earth system causes changes in the Earth's rotation in space, gravity field and Earth's ellipsoid shape. These changes are observed in the ΔC21, ΔS21, and ΔC20 spherical harmonics gravity coefficients, which are proportional to the mass load-induced Earth rotational excitations. In this study, linear trend, decadal, inter-annual, and seasonal variations of low degree spherical harmonics coefficients of Earth's gravity field, determined from different space geodetic techniques, Gravity Recovery and Climate Experiment (GRACE), satellite laser ranging (SLR), Global Navigation Satellite System (GNSS), Earth rotation, and climate models, are examined. In this way, the contribution of each measurement technique to interpreting the low degree surface mass density of the Earth is shown. Especially, we evaluate an usefulness of several climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5) to determine the low degree Earth's gravity coefficients using GRACE satellite observations. To do that, Terrestrial Water Storage (TWS) changes from several CMIP5 climate models are determined and then these simulated data are compared with the GRACE observations. Spherical harmonics ΔC21, ΔS21, and ΔC20 changes are calculated as the sum of atmosphere and ocean mass effect (GAC values) taken from GRACE and a land surface hydrological estimate from the selected CMIP5 climate models. Low degree Stokes coefficients of the surface mass density determined from GRACE, SLR, GNSS, Earth rotation measurements and climate models are compared to each other in order to assess their consistency. The comparison is done by using different types of statistical and signal processing methods.

Reduced order modeling and parameter identification of a building energy system model through an optimization routine

International Nuclear Information System (INIS)

Harish, V.S.K.V.; Kumar, Arun

2016-01-01

Highlights: • A BES model based on 1st principles is developed and solved numerically. • Parameters of lumped capacitance model are fitted using the proposed optimization routine. • Validations are showed for different types of building construction elements. • Step response excitations for outdoor air temperature and relative humidity are analyzed. - Abstract: Different control techniques together with intelligent building technology (Building Automation Systems) are used to improve energy efficiency of buildings. In almost all control projects, it is crucial to have building energy models with high computational efficiency in order to design and tune the controllers and simulate their performance. In this paper, a set of partial differential equations are formulated accounting for energy flow within the building space. These equations are then solved as conventional finite difference equations using Crank–Nicholson scheme. Such a model of a higher order is regarded as a benchmark model. An optimization algorithm has been developed, depicted through a flowchart, which minimizes the sum squared error between the step responses of the numerical and the optimal model. Optimal model of the construction element is nothing but a RC-network model with the values of Rs and Cs estimated using the non-linear time invariant constrained optimization routine. The model is validated with comparing the step responses with other two RC-network models whose parameter values are selected based on a certain criteria. Validations are showed for different types of building construction elements viz., low, medium and heavy thermal capacity elements. Simulation results show that the optimal model closely follow the step responses of the numerical model as compared to the responses of other two models.

Joint Ordering and Pricing Decisions for New Repeat-Purchase Products

Directory of Open Access Journals (Sweden)

Xiang Wu

2015-01-01

Full Text Available This paper studies ordering and pricing problems for new repeat-purchase products. We incorporate the repeat-purchase rate and price effects into the Bass model to characterize the demand pattern. We consider two decision models: (1 two-stage decision model, in which the sales division chooses a price to maximize the gross profit and the purchasing division determines an optimal ordering decision to minimize the total cost under a given demand subsequently, and (2 joint decision model, in which the firm makes ordering and pricing decisions simultaneously to maximize the profit. We combine the generalized Bass model with dynamic lot sizing model to formulate the joint decision model. We apply both models to a specific imported food provided by an online fresh produce retailer in Central China, solve them by Gaussian Random-Walk and Wagner-Whitin based algorithms, and observe three results. First, joint pricing and ordering decisions bring more significant profits than making pricing and ordering decisions sequentially. Second, a great initiative in adoption significantly increases price premium and profit. Finally, the optimal price shows a U-shape (i.e., decreases first and increases later relationship and the profit increases gradually with the repeat-purchase rate when it is still not very high.

Bilinear reduced order approximate model of parabolic distributed solar collectors

KAUST Repository

Elmetennani, Shahrazed

2015-07-01

This paper proposes a novel, low dimensional and accurate approximate model for the distributed parabolic solar collector, by means of a modified gaussian interpolation along the spatial domain. The proposed reduced model, taking the form of a low dimensional bilinear state representation, enables the reproduction of the heat transfer dynamics along the collector tube for system analysis. Moreover, presented as a reduced order bilinear state space model, the well established control theory for this class of systems can be applied. The approximation efficiency has been proven by several simulation tests, which have been performed considering parameters of the Acurex field with real external working conditions. Model accuracy has been evaluated by comparison to the analytical solution of the hyperbolic distributed model and its semi discretized approximation highlighting the benefits of using the proposed numerical scheme. Furthermore, model sensitivity to the different parameters of the gaussian interpolation has been studied.

Analysing workplace violence towards health care staff in public hospitals using alternative ordered response models: the case of north-eastern Turkey.

Science.gov (United States)

Çelik, Ali Kemal; Oktay, Erkan; Çebi, Kübranur

2017-09-01

The main objective of this article is to determine key factors that may have a significant effect on the verbal abuse, emotional abuse and physical assault of health care workers in north-eastern Turkey. A self-administered survey was completed by 450 health care workers in three well-established hospitals in Erzurum, Turkey. Because of the discrete and ordered nature of the dependent variable of the survey, the data were analysed using four distinctive ordered response models. Results revealed that several key variables were found to be a significant determinant of workplace violence, such as the type of health institution, occupational position, weekly working hours, weekly shift hours, number of daily patient contacts, age group of the respondents, experience in the health sector, training against workplace violence and current policies of the hospitals and the Turkish Ministry of Health.

An order insertion scheduling model of logistics service supply chain considering capacity and time factors.

Science.gov (United States)

Liu, Weihua; Yang, Yi; Wang, Shuqing; Liu, Yang

2014-01-01

Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.

A Frank mixture copula family for modeling higher-order correlations of neural spike counts

International Nuclear Information System (INIS)

Onken, Arno; Obermayer, Klaus

2009-01-01

In order to evaluate the importance of higher-order correlations in neural spike count codes, flexible statistical models of dependent multivariate spike counts are required. Copula families, parametric multivariate distributions that represent dependencies, can be applied to construct such models. We introduce the Frank mixture family as a new copula family that has separate parameters for all pairwise and higher-order correlations. In contrast to the Farlie-Gumbel-Morgenstern copula family that shares this property, the Frank mixture copula can model strong correlations. We apply spike count models based on the Frank mixture copula to data generated by a network of leaky integrate-and-fire neurons and compare the goodness of fit to distributions based on the Farlie-Gumbel-Morgenstern family. Finally, we evaluate the importance of using proper single neuron spike count distributions on the Shannon information. We find notable deviations in the entropy that increase with decreasing firing rates. Moreover, we find that the Frank mixture family increases the log likelihood of the fit significantly compared to the Farlie-Gumbel-Morgenstern family. This shows that the Frank mixture copula is a useful tool to assess the importance of higher-order correlations in spike count codes.

Reduced order models, inertial manifolds, and global bifurcations: searching instability boundaries in nuclear power systems

International Nuclear Information System (INIS)

Suarez-Antola, Roberto; Ministerio de Industria, Energia y Mineria, Montevideo

2011-01-01

One of the goals of nuclear power systems design and operation is to restrict the possible states of certain critical subsystems to remain inside a certain bounded set of admissible states and state variations. In the framework of an analytic or numerical modeling process of a BWR power plant, this could imply first to find a suitable approximation to the solution manifold of the differential equations describing the stability behavior, and then a classification of the different solution types concerning their relation with the operational safety of the power plant. Inertial manifold theory gives a foundation for the construction and use of reduced order models (ROM's) of reactor dynamics to discover and characterize meaningful bifurcations that may pass unnoticed during digital simulations done with full scale computer codes of the nuclear power plant. The March-Leuba's BWR ROM is generalized and used to exemplify the analytical approach developed here. A nonlinear integral-differential equation in the logarithmic power is derived. Introducing a KBM Ansatz, a coupled set of two nonlinear ordinary differential equations is obtained. Analytical formulae are derived for the frequency of oscillation and the parameters that determine the stability of the steady states, including sub- and supercritical PAH bifurcations. A Bautin's bifurcation scenario seems possible on the power-flow plane: near the boundary of stability, a region where stable steady states are surrounded by unstable limit cycles surrounded at their turn by stable limit cycles. The analytical results are compared with recent digital simulations and applications of semi-analytical bifurcation theory done with reduced order models of BWR. (author)

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

Science.gov (United States)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

Simulation model of a single-server order picking workstation using aggregate process times

NARCIS (Netherlands)

Andriansyah, R.; Etman, L.F.P.; Rooda, J.E.; Biles, W.E.; Saltelli, A.; Dini, C.

2009-01-01

In this paper we propose a simulation modeling approach based on aggregate process times for the performance analysis of order picking workstations in automated warehouses with first-in-first-out processing of orders. The aggregate process time distribution is calculated from tote arrival and

Optimal ordering quantities for substitutable deteriorating items under joint replenishment with cost of substitution

Science.gov (United States)

Mishra, Vinod Kumar

2017-09-01

In this paper we develop an inventory model, to determine the optimal ordering quantities, for a set of two substitutable deteriorating items. In this inventory model the inventory level of both items depleted due to demands and deterioration and when an item is out of stock, its demands are partially fulfilled by the other item and all unsatisfied demand is lost. Each substituted item incurs a cost of substitution and the demands and deterioration is considered to be deterministic and constant. Items are order jointly in each ordering cycle, to take the advantages of joint replenishment. The problem is formulated and a solution procedure is developed to determine the optimal ordering quantities that minimize the total inventory cost. We provide an extensive numerical and sensitivity analysis to illustrate the effect of different parameter on the model. The key observation on the basis of numerical analysis, there is substantial improvement in the optimal total cost of the inventory model with substitution over without substitution.

Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations

Science.gov (United States)

Mitry, Mina

Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.

A Study of Enhanced, Higher Order Boussinesq-Type Equations and Their Numerical Modelling

DEFF Research Database (Denmark)

Banijamali, Babak

model is designated for the solution of higher-order Boussinesq-type equations, formulated in terms of the horizontal velocity at an arbitrary depth vector. Various discretisation techniques and grid definitions have been considered in this endeavour, undertaking a detailed analysis of the selected......This project has encompassed efforts in two separate veins: on the one hand, the acquiring of highly accurate model equations of the Boussinesq-type, and on the other hand, the theoretical and practical work in implementing such equations in the form of conventional numerical models, with obvious...... potential for applications to the realm of numerical modelling in coastal engineering. The derivation and analysis of several forms of higher-order in dispersion and non-linearity Boussinesq-type equations have been undertaken, obtaining and investigating the properties of a new and generalised class...

Soft-edged magnet models for higher-order beam-optics map codes

International Nuclear Information System (INIS)

Walstrom, P.L.

2004-01-01

Continuously varying surface and volume source-density distributions are used to model magnetic fields inside of cylindrical volumes. From these distributions, a package of subroutines computes on-axis generalized gradients and their derivatives at arbitrary points on the magnet axis for input to the numerical map-generating subroutines of the Lie-algebraic map code Marylie. In the present version of the package, the magnet menu includes: (1) cylindrical current-sheet or radially thick current distributions with either open boundaries or with a surrounding cylindrical boundary with normal field lines (which models high-permeability iron), (2) Halbach-type permanent multipole magnets, either as sheet magnets or as radially thick magnets, (3) modeling of arbitrary fields inside a cylinder by use of a fictitious current sheet. The subroutines provide on-axis gradients and their z derivatives to essentially arbitrary order, although in the present third- and fifth-order Marylie only the zeroth through sixth derivatives are needed. The formalism is especially useful in beam-optics applications, such as magnetic lenses, where realistic treatment of fringe-field effects is needed

Model Simultan Penentuan Toleransi Komponen Produk Rakitan dan Pabrik dalam Kolaborasi Manufaktur Make-to-Order

Directory of Open Access Journals (Sweden)

M. Imron Mustajib

2010-01-01

Full Text Available This paper discusses the development of simultaneous optimization model to determine component tolerance of assembly product and plant for manufacturing processes by considering quality tolerance limits, and delivery time constraint to minimize total cost in collaboration environment of make-to-order manufacturing systems. Total cost of the system consists of manufacturing costs and quality loss costs as the tolerance function, operational costs for multi-plant manufacturing collaboration which includes: setup costs, material handling costs, operating costs of assembly, manual operations costs, and transportation costs. Formulation of the model developed uses mixed integer non linear programming as a method of solution search. In the numerical examples presented, the optimization process results an optimal solution. Optimal solution is not sensitive if the changes in quality tolerance constraint and delivery time constraint is not large. While the addition of an alternative plant for producing a component can changes the alternative plant selected

Finite temperature CPN-1 model and long range Neel order

International Nuclear Information System (INIS)

Ichinose, Ikuo; Yamamoto, Hisashi.

1989-09-01

We study in d space-dimensions the finite temperature behavior of long range Neel order (LRNO) in CP N-1 model as a low energy effective field theory of the antiferromagnetic Heisenberg model. For d≤1, or d≤2 at any nonzero temperature, LRNO disappears, in agreement with Mermin-Wagner-Coleman's theorem. For d=3 in the weak coupling region, LRNO exists below the critical temperature T N (Neel temperature). T N decreases as the interlayer coupling becomes relatively weak compared with that within Cu-O layers. (author)

Magnetic ordering of four particle exchange model in BCC 3He

International Nuclear Information System (INIS)

Ishikawa, Koji; Okada, Isamu

1978-01-01

The low temperature magnetic ordering of BCC 3 He within the mean field approximation was studied. A model including four particle exchange interactions was considered. Two types of cyclic quadrupole exchange process, planar and folded, were taken into account. Assuming four sublattices, it was considered to minimize the spin energy with respect to the classical spin vector and to find out four ordered states at the absolute zero point. They are antiferromagnetic (AF), weak ferromagnetic (WF) and two kinds of simple cubic antiferromagnetic states (SCAF). The condition for the existence of each ordered state is given, and the free energies of the ordered states are calculated in the mean field approximation. The transition between AF or SCAF and the paramagnetic states is of the first order. The phase diagram is drawn in the parameter space. The phase diagram was obtained numerically at Hetherington and Willard's value and at its neighbouring values. The difference between the present result and HW's is that of magnetic field direction in the perpendicular simple cubic antiferromagnetic states. The second order transition disappears, and the WF state changes gradually into AF state. With respect to the first order transition, the transition temperature increases with magnetic field. In this case, a critical magnetic field exists. (Kato, T

Fractional-Order Discrete-Time Laguerre Filters: A New Tool for Modeling and Stability Analysis of Fractional-Order LTI SISO Systems

Directory of Open Access Journals (Sweden)

Rafał Stanisławski

2016-01-01

Full Text Available This paper presents new results on modeling and analysis of dynamics of fractional-order discrete-time linear time-invariant single-input single-output (LTI SISO systems by means of new, two-layer, “fractional-order discrete-time Laguerre filters.” It is interesting that the fractionality of the filters at the upper system dynamics layer is directly projected from the lower Laguerre-based approximation layer for the Grünwald-Letnikov difference. A new stability criterion for discrete-time fractional-order Laguerre-based LTI SISO systems is introduced and supplemented with a stability preservation analysis. Both the stability criterion and the stability preservation analysis bring up rather surprising results, which is illustrated with simulation examples.

Development and validation of different methods manipulating zero order and first order spectra for determination of the partially overlapped mixture benazepril and amlodipine: A comparative study

Science.gov (United States)

Hemdan, A.

2016-07-01

Three simple, selective, and accurate spectrophotometric methods have been developed and then validated for the analysis of Benazepril (BENZ) and Amlodipine (AML) in bulk powder and pharmaceutical dosage form. The first method is the absorption factor (AF) for zero order and amplitude factor (P-F) for first order spectrum, where both BENZ and AML can be measured from their resolved zero order spectra at 238 nm or from their first order spectra at 253 nm. The second method is the constant multiplication coupled with constant subtraction (CM-CS) for zero order and successive derivative subtraction-constant multiplication (SDS-CM) for first order spectrum, where both BENZ and AML can be measured from their resolved zero order spectra at 240 nm and 238 nm, respectively, or from their first order spectra at 214 nm and 253 nm for Benazepril and Amlodipine respectively. The third method is the novel constant multiplication coupled with derivative zero crossing (CM-DZC) which is a stability indicating assay method for determination of Benazepril and Amlodipine in presence of the main degradation product of Benazepril which is Benazeprilate (BENZT). The three methods were validated as per the ICH guidelines and the standard curves were found to be linear in the range of 5-60 μg/mL for Benazepril and 5-30 for Amlodipine, with well accepted mean correlation coefficient for each analyte. The intra-day and inter-day precision and accuracy results were well within the acceptable limits.

Optimizing lengths of confidence intervals: fourth-order efficiency in location models

NARCIS (Netherlands)

Klaassen, C.; Venetiaan, S.

2010-01-01

Under regularity conditions the maximum likelihood estimator of the location parameter in a location model is asymptotically efficient among translation equivariant estimators. Additional regularity conditions warrant third- and even fourth-order efficiency, in the sense that no translation

Adaptive parametric model order reduction technique for optimization of vibro-acoustic models: Application to hearing aid design

Science.gov (United States)

Creixell-Mediante, Ester; Jensen, Jakob S.; Naets, Frank; Brunskog, Jonas; Larsen, Martin

2018-06-01

Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we present an adaptive pMOR technique where the construction of the projection basis is embedded in the optimization process and requires fewer full system analyses, while the accuracy of the reduced system is monitored by a cheap error indicator. The performance of the proposed method is evaluated for a 4-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system.

Reduced-Order Models for Load Management in the Power Grid

Science.gov (United States)

Alizadeh, Mahnoosh

In recent years, considerable research efforts have been directed towards designing control schemes that can leverage the inherent flexibility of electricity demand that is not tapped into in today's electricity markets. It is expected that these control schemes will be carried out by for-profit entities referred to as aggregators that operate at the edge of the power grid network. While the aggregator control problem is receiving much attention, more high-level questions of how these aggregators should plan their market participation, interact with the main grid and with each other, remain rather understudied. Answering these questions requires a large-scale model for the aggregate flexibility that can be harnessed from the a population of customers, particularly for residences and small businesses. The contribution of this thesis towards this goal is divided into three parts: In Chapter 3, a reduced-order model for a large population of heterogeneous appliances is provided by clustering load profiles that share similar degrees of freedom together. The use of such reduced-order model for system planning and optimal market decision making requires a foresighted approximation of the number of appliances that will join each cluster. Thus, Chapter 4 provides a systematic framework to generate such forecasts for the case of Electric Vehicles, based on real-world battery charging data. While these two chapters set aside the economic side that is naturally involved with participation in demand response programs and mainly focus on the control problem, Chapter 5 is dedicated to the study of optimal pricing mechanisms in order to recruit heterogeneous customers in a demand response program in which an aggregator can directly manage their appliances' load under their specified preferences. Prices are proportional to the wholesale market savings that can result from each recruitment event.

The economic order decision with continuous dynamic pricing and batch supply

NARCIS (Netherlands)

van den Berg, A.H.J.; Herings, P.J.J.; Peters, H.J.M.

2014-01-01

We study an infinite horizon model, where a seller orders his product in batches of fixed size. A sales strategy determines both the order moments and the sales path between these moments. Under some natural conditions on the seller’s revenue function, the strategy that maximizes the seller’s

Experimental design for estimating unknown groundwater pumping using genetic algorithm and reduced order model

Science.gov (United States)

Ushijima, Timothy T.; Yeh, William W.-G.

2013-10-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.

An isotonic partial credit model for ordering subjects on the basis of their sum scores

NARCIS (Netherlands)

Ligtvoet, R.

2012-01-01

In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable.

Perturbation theory in large order

International Nuclear Information System (INIS)

Bender, C.M.

1978-01-01

For many quantum mechanical models, the behavior of perturbation theory in large order is strikingly simple. For example, in the quantum anharmonic oscillator, which is defined by -y'' + (x 2 /4 + ex 4 /4 - E) y = 0, y ( +- infinity) = 0, the perturbation coefficients, A/sub n/, in the expansion for the ground-state energy, E(ground state) approx. EPSILON/sub n = 0//sup infinity/ A/sub n/epsilon/sup n/, simplify dramatically as n → infinity: A/sub n/ approx. (6/π 3 )/sup 1/2/(-3)/sup n/GAMMA(n + 1/2). Methods of applied mathematics are used to investigate the nature of perturbation theory in quantum mechanics and show that its large-order behavior is determined by the semiclassical content of the theory. In quantum field theory the perturbation coefficients are computed by summing Feynman graphs. A statistical procedure in a simple lambda phi 4 model for summing the set of all graphs as the number of vertices → infinity is presented. Finally, the connection between the large-order behavior of perturbation theory in quantum electrodynamics and the value of α, the charge on the electron, is discussed. 7 figures

Quantifying and modeling birth order effects in autism.

Directory of Open Access Journals (Sweden)

Tychele Turner

Full Text Available Autism is a complex genetic disorder with multiple etiologies whose molecular genetic basis is not fully understood. Although a number of rare mutations and dosage abnormalities are specific to autism, these explain no more than 10% of all cases. The high heritability of autism and low recurrence risk suggests multifactorial inheritance from numerous loci but other factors also intervene to modulate risk. In this study, we examine the effect of birth rank on disease risk which is not expected for purely hereditary genetic models. We analyzed the data from three publicly available autism family collections in the USA for potential birth order effects and studied the statistical properties of three tests to show that adequate power to detect these effects exist. We detect statistically significant, yet varying, patterns of birth order effects across these collections. In multiplex families, we identify V-shaped effects where middle births are at high risk; in simplex families, we demonstrate linear effects where risk increases with each additional birth. Moreover, the birth order effect is gender-dependent in the simplex collection. It is currently unknown whether these patterns arise from ascertainment biases or biological factors. Nevertheless, further investigation of parental age-dependent risks yields patterns similar to those observed and could potentially explain part of the increased risk. A search for genes considering these patterns is likely to increase statistical power and uncover novel molecular etiologies.

Self-Determination and Social Order

Directory of Open Access Journals (Sweden)

Fabio Macioce

2012-12-01

Full Text Available In this essay I will try to demonstrate that the principle of self‐determination is based on a formal and individualistic view of liberty rights. I also propose a different perspective that takes into account the relationships rather than the individual. I will show how this result can only be achieved through a different ascription of rights to individuals: in particular, I will try to demonstrate 1 that any social practices express specific values, 2 that these values are the result of historical and cultural circumstances, 3 that they are subject to an ongoing public debate, and finally 4 that only if the individual praxis is consistent with these values can it lead to recognition of rights.

SDSS-II: Determination of shape and color parameter coefficients for SALT-II fit model

Energy Technology Data Exchange (ETDEWEB)

Dojcsak, L.; Marriner, J.; /Fermilab

2010-08-01