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Sample records for total order model

  1. A high performance totally ordered multicast protocol

    Science.gov (United States)

    Montgomery, Todd; Whetten, Brian; Kaplan, Simon

    1995-01-01

    This paper presents the Reliable Multicast Protocol (RMP). RMP provides a totally ordered, reliable, atomic multicast service on top of an unreliable multicast datagram service such as IP Multicasting. RMP is fully and symmetrically distributed so that no site bears un undue portion of the communication load. RMP provides a wide range of guarantees, from unreliable delivery to totally ordered delivery, to K-resilient, majority resilient, and totally resilient atomic delivery. These QoS guarantees are selectable on a per packet basis. RMP provides many communication options, including virtual synchrony, a publisher/subscriber model of message delivery, an implicit naming service, mutually exclusive handlers for messages, and mutually exclusive locks. It has commonly been held that a large performance penalty must be paid in order to implement total ordering -- RMP discounts this. On SparcStation 10's on a 1250 KB/sec Ethernet, RMP provides totally ordered packet delivery to one destination at 842 KB/sec throughput and with 3.1 ms packet latency. The performance stays roughly constant independent of the number of destinations. For two or more destinations on a LAN, RMP provides higher throughput than any protocol that does not use multicast or broadcast.

  2. Fractional-Order Total Variation Image Restoration Based on Primal-Dual Algorithm

    OpenAIRE

    Chen, Dali; Chen, YangQuan; Xue, Dingyu

    2013-01-01

    This paper proposes a fractional-order total variation image denoising algorithm based on the primal-dual method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, convergence rate, and blocky effect. The fractional-order total variation model is introduced by generalizing the first-order model, and the corresponding saddle-point and dual formulation are constructed in theory. In order to guarantee $O(1/{N}^{2})$ conv...

  3. TOTAL REWARDS MODEL IN ROMANIAN COMPANIES

    Directory of Open Access Journals (Sweden)

    Elena-Sabina HODOR

    2014-04-01

    Full Text Available Total Rewards Management is a subject of major importance for companies, because, by using models for this, firms can achieve their objectives of high performance. In order to analyse a validated total rewards model in Romanian Accounting and Consulting Companies, it is used The WorldatWork Total Rewards Model, which depict what contributes to applicant attraction and employee motivation and retention. Thus, the methodology of the previous survey is adjusted to the local context. The conclusions for the methodological aspects illustrate that the present research involves three strategic steps in order to achieve the objectives presented: the analysis of organizational environment of the companies from the sample, checking if Total Rewards Model proposed in the previous research is applicable for the same romanian companies from the previous survey, the analysing of the differences between results, and, if necessary, the adaptation of the model for Romania.

  4. Adaptive Second-Order Total Variation: An Approach Aware of Slope Discontinuities

    KAUST Repository

    Lenzen, Frank; Becker, Florian; Lellmann, Jan

    2013-01-01

    Total variation (TV) regularization, originally introduced by Rudin, Osher and Fatemi in the context of image denoising, has become widely used in the field of inverse problems. Two major directions of modifications of the original approach were proposed later on. The first concerns adaptive variants of TV regularization, the second focuses on higher-order TV models. In the present paper, we combine the ideas of both directions by proposing adaptive second-order TV models, including one anisotropic model. Experiments demonstrate that introducing adaptivity results in an improvement of the reconstruction error. © 2013 Springer-Verlag.

  5. Decisions with Uncertain Consequences-A Total Ordering on Loss-Distributions.

    Science.gov (United States)

    Rass, Stefan; König, Sandra; Schauer, Stefan

    2016-01-01

    Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action can be modeled by a random variable, then the decision problem boils down to comparing different effects (random variables) by comparing their distribution functions. Although the full space of probability distributions cannot be ordered, a properly restricted subset of distributions can be totally ordered in a practically meaningful way. We call these loss-distributions, since they provide a substitute for the concept of loss-functions in decision theory. This article introduces the theory behind the necessary restrictions and the hereby constructible total ordering on random loss variables, which enables decisions under uncertainty of consequences. Using data obtained from simulations, we demonstrate the practical applicability of our approach.

  6. Decisions with Uncertain Consequences-A Total Ordering on Loss-Distributions.

    Directory of Open Access Journals (Sweden)

    Stefan Rass

    Full Text Available Decisions are often based on imprecise, uncertain or vague information. Likewise, the consequences of an action are often equally unpredictable, thus putting the decision maker into a twofold jeopardy. Assuming that the effects of an action can be modeled by a random variable, then the decision problem boils down to comparing different effects (random variables by comparing their distribution functions. Although the full space of probability distributions cannot be ordered, a properly restricted subset of distributions can be totally ordered in a practically meaningful way. We call these loss-distributions, since they provide a substitute for the concept of loss-functions in decision theory. This article introduces the theory behind the necessary restrictions and the hereby constructible total ordering on random loss variables, which enables decisions under uncertainty of consequences. Using data obtained from simulations, we demonstrate the practical applicability of our approach.

  7. Higher order total variation regularization for EIT reconstruction.

    Science.gov (United States)

    Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Zhang, Fan; Mueller-Lisse, Ullrich; Moeller, Knut

    2018-01-08

    Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabilize reconstructions. However, it is well known that TV regularization induces staircase effects, which are not realistic in clinical applications. To reduce such artifacts, modified TV regularization terms considering a higher order differential operator were developed in several previous studies. One of them is called total generalized variation (TGV) regularization. TGV regularization has been successively applied in image processing in a regular grid context. In this study, we adapted TGV regularization to the finite element model (FEM) framework for EIT reconstruction. Reconstructions using simulation and clinical data were performed. First results indicate that, in comparison to TV regularization, TGV regularization promotes more realistic images. Graphical abstract Reconstructed conductivity changes located on selected vertical lines. For each of the reconstructed images as well as the ground truth image, conductivity changes located along the selected left and right vertical lines are plotted. In these plots, the notation GT in the legend stands for ground truth, TV stands for total variation method, and TGV stands for total generalized variation method. Reconstructed conductivity distributions from the GREIT algorithm are also demonstrated.

  8. Combined First and Second Order Total Variation Inpainting using Split Bregman

    KAUST Repository

    Papafitsoros, Konstantinos

    2013-07-12

    In this article we discuss the implementation of the combined first and second order total variation inpainting that was introduced by Papafitsoros and Schdönlieb. We describe the algorithm we use (split Bregman) in detail, and we give some examples that indicate the difference between pure first and pure second order total variation inpainting.

  9. Combined First and Second Order Total Variation Inpainting using Split Bregman

    KAUST Repository

    Papafitsoros, Konstantinos; Schoenlieb, Carola Bibiane; Sengul, Bati

    2013-01-01

    In this article we discuss the implementation of the combined first and second order total variation inpainting that was introduced by Papafitsoros and Schdönlieb. We describe the algorithm we use (split Bregman) in detail, and we give some examples that indicate the difference between pure first and pure second order total variation inpainting.

  10. Constrained core solutions for totally positive games with ordered players

    NARCIS (Netherlands)

    van den Brink, J.R.; van der Laan, G.; Vasil'ev, V.

    2014-01-01

    In many applications of cooperative game theory to economic allocation problems, such as river-, polluted river- and sequencing games, the game is totally positive (i.e., all dividends are nonnegative), and there is some ordering on the set of the players. A totally positive game has a nonempty

  11. Maximizing Total Profit in Two-agent Problem of Order Acceptance and Scheduling

    Directory of Open Access Journals (Sweden)

    Mohammad Reisi-Nafchi

    2017-03-01

    Full Text Available In competitive markets, attracting potential customers and keeping current customers is a survival condition for each company. So, paying attention to the requests of customers is important and vital. In this paper, the problem of order acceptance and scheduling has been studied, in which two types of customers or agents compete in a single machine environment. The objective is maximizing sum of the total profit of first agent's accepted orders and the total revenue of second agent. Therefore, only the first agent has penalty and its penalty function is lateness and the second agent's orders have a common due date and this agent does not accept any tardy order. To solve the problem, a mathematical programming, a heuristic algorithm and a pseudo-polynomial dynamic programming algorithm are proposed. Computational results confirm the ability of solving all problem instances up to 70 orders size optimally and also 93.12% of problem instances up to 150 orders size by dynamic programming.

  12. 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.

  13. Automated Decisional Model for Optimum Economic Order Quantity Determination Using Price Regressive Rates

    Science.gov (United States)

    Roşu, M. M.; Tarbă, C. I.; Neagu, C.

    2016-11-01

    The current models for inventory management are complementary, but together they offer a large pallet of elements for solving complex problems of companies when wanting to establish the optimum economic order quantity for unfinished products, row of materials, goods etc. The main objective of this paper is to elaborate an automated decisional model for the calculus of the economic order quantity taking into account the price regressive rates for the total order quantity. This model has two main objectives: first, to determine the periodicity when to be done the order n or the quantity order q; second, to determine the levels of stock: lighting control, security stock etc. In this way we can provide the answer to two fundamental questions: How much must be ordered? When to Order? In the current practice, the business relationships with its suppliers are based on regressive rates for price. This means that suppliers may grant discounts, from a certain level of quantities ordered. Thus, the unit price of the products is a variable which depends on the order size. So, the most important element for choosing the optimum for the economic order quantity is the total cost for ordering and this cost depends on the following elements: the medium price per units, the stock cost, the ordering cost etc.

  14. 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...

  15. 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.

  16. On nonlinear reduced order modeling

    International Nuclear Information System (INIS)

    Abdel-Khalik, Hany S.

    2011-01-01

    When applied to a model that receives n input parameters and predicts m output responses, a reduced order model estimates the variations in the m outputs of the original model resulting from variations in its n inputs. While direct execution of the forward model could provide these variations, reduced order modeling plays an indispensable role for most real-world complex models. This follows because the solutions of complex models are expensive in terms of required computational overhead, thus rendering their repeated execution computationally infeasible. To overcome this problem, reduced order modeling determines a relationship (often referred to as a surrogate model) between the input and output variations that is much cheaper to evaluate than the original model. While it is desirable to seek highly accurate surrogates, the computational overhead becomes quickly intractable especially for high dimensional model, n ≫ 10. In this manuscript, we demonstrate a novel reduced order modeling method for building a surrogate model that employs only 'local first-order' derivatives and a new tensor-free expansion to efficiently identify all the important features of the original model to reach a predetermined level of accuracy. This is achieved via a hybrid approach in which local first-order derivatives (i.e., gradient) of a pseudo response (a pseudo response represents a random linear combination of original model’s responses) are randomly sampled utilizing a tensor-free expansion around some reference point, with the resulting gradient information aggregated in a subspace (denoted by the active subspace) of dimension much less than the dimension of the input parameters space. The active subspace is then sampled employing the state-of-the-art techniques for global sampling methods. The proposed method hybridizes the use of global sampling methods for uncertainty quantification and local variational methods for sensitivity analysis. In a similar manner to

  17. Ordering dynamics of microscopic models with nonconserved order parameter of continuous symmetry

    DEFF Research Database (Denmark)

    Zhang, Z.; Mouritsen, Ole G.; Zuckermann, Martin J.

    1993-01-01

    crystals. For both models, which have a nonconserved order parameter, it is found that the linear scale, R(t), of the evolving order, following quenches to below the transition temperature, grows at late times in an effectively algebraic fashion, R(t)∼tn, with exponent values which are strongly temperature......Numerical Monte Carlo temperature-quenching experiments have been performed on two three-dimensional classical lattice models with continuous ordering symmetry: the Lebwohl-Lasher model [Phys. Rev. A 6, 426 (1972)] and the ferromagnetic isotropic Heisenberg model. Both models describe a transition...... from a disordered phase to an orientationally ordered phase of continuous symmetry. The Lebwohl-Lasher model accounts for the orientational ordering properties of the nematic-isotropic transition in liquid crystals and the Heisenberg model for the ferromagnetic-paramagnetic transition in magnetic...

  18. An adaptive wavelet-network model for forecasting daily total solar-radiation

    International Nuclear Information System (INIS)

    Mellit, A.; Benghanem, M.; Kalogirou, S.A.

    2006-01-01

    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet-networks are feed-forward networks using wavelets as activation functions. Wavelet-networks have been used successfully in various engineering applications such as classification, identification and control problems. In this paper, the use of adaptive wavelet-network architecture in finding a suitable forecasting model for predicting the daily total solar-radiation is investigated. Total solar-radiation is considered as the most important parameter in the performance prediction of renewable energy systems, particularly in sizing photovoltaic (PV) power systems. For this purpose, daily total solar-radiation data have been recorded during the period extending from 1981 to 2001, by a meteorological station in Algeria. The wavelet-network model has been trained by using either the 19 years of data or one year of the data. In both cases the total solar radiation data corresponding to year 2001 was used for testing the model. The network was trained to accept and handle a number of unusual cases. Results indicate that the model predicts daily total solar-radiation values with a good accuracy of approximately 97% and the mean absolute percentage error is not more than 6%. In addition, the performance of the model was compared with different neural network structures and classical models. Training algorithms for wavelet-networks require smaller numbers of iterations when compared with other neural networks. The model can be used to fill missing data in weather databases. Additionally, the proposed model can be generalized and used in different locations and for other weather data, such as sunshine duration and ambient temperature. Finally, an application using the model for sizing a PV-power system is presented in order to confirm the validity of this model

  19. 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...

  20. Calculation of the thermal neutron scattering kernel using the synthetic model. Pt. 2. Zero-order energy transfer kernel

    International Nuclear Information System (INIS)

    Drozdowicz, K.

    1995-01-01

    A comprehensive unified description of the application of Granada's Synthetic Model to the slow-neutron scattering by the molecular systems is continued. Detailed formulae for the zero-order energy transfer kernel are presented basing on the general formalism of the model. An explicit analytical formula for the total scattering cross section as a function of the incident neutron energy is also obtained. Expressions of the free gas model for the zero-order scattering kernel and for total scattering kernel are considered as a sub-case of the Synthetic Model. (author). 10 refs

  1. Research on the decomposition model for China’s National Renewable Energy total target

    International Nuclear Information System (INIS)

    Liu, Zhen; Shi, Yuren; Yan, Jianming; Ou, Xunmin; Lieu, Jenny

    2012-01-01

    It is crucial that China’s renewable energy national target in 2020 is effectively decomposed into respective period targets at the provincial level. In order to resolve problems arising from combining the national and local renewable energy development plan, a total target and period target decomposition model of renewable energy is proposed which considers the resource distribution and energy consumption of different provinces as well as the development characteristics of various renewable energy industries. In the model, the total proposed target is comprised of three shares: basic share, fixed share and floating share target. The target distributed for each province is then determined by the preference relation. That is, when total renewable energy target is distributed, the central government is more concerned about resources potential or energy consumption. Additionally, the growth models for various renewable energy industries are presented, and the period targets of renewable energy in various provinces are proposed in line with regional economic development targets. In order to verify whether the energy target can be achieved, only wind power, solar power, and hydropower are considered in this study. To convenient to assess the performance of local government, the two year period is chosen as an evaluation cycle in the paper. The renewable energy targets per two-year period for each province are calculated based on the overall national renewable energy target, energy requirements and resources distribution. Setting provincial period targets will help policy makers to better implement and supervise the overall renewable energy plan. - Highlights: It is very importance that the national target of renewable energy in 2020 can be effectively decomposed into the stages target of various province. In order to resolve the relation the plan between the national and local renewable energy development planning, a total target and phase target decomposition model

  2. Maillet type theorem for singular first order nonlinear partial differential equations of totally characteristic type. Part II

    Directory of Open Access Journals (Sweden)

    Akira Shirai

    2015-01-01

    Full Text Available In this paper, we study the following nonlinear first order partial differential equation: \\[f(t,x,u,\\partial_t u,\\partial_x u=0\\quad\\text{with}\\quad u(0,x\\equiv 0.\\] The purpose of this paper is to determine the estimate of Gevrey order under the condition that the equation is singular of a totally characteristic type. The Gevrey order is indicated by the rate of divergence of a formal power series. This paper is a continuation of the previous papers [Convergence of formal solutions of singular first order nonlinear partial differential equations of totally characteristic type, Funkcial. Ekvac. 45 (2002, 187-208] and [Maillet type theorem for singular first order nonlinear partial differential equations of totally characteristic type, Surikaiseki Kenkyujo Kokyuroku, Kyoto University 1431 (2005, 94-106]. Especially the last-mentioned paper is regarded as part I of this paper.

  3. 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.

  4. 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).

  5. 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.

  6. 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.

  7. Order of current variance and diffusivity in the rate one totally asymmetric zero range process

    NARCIS (Netherlands)

    Balázs, M.; Komjáthy, J.

    2008-01-01

    We prove that the variance of the current across a characteristic is of order t 2/3 in a stationary constant rate totally asymmetric zero range process, and that the diffusivity has order t 1/3. This is a step towards proving universality of this scaling behavior in the class of one-dimensional

  8. 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.

  9. Multi-Criteria Model for Determining Order Size

    Directory of Open Access Journals (Sweden)

    Katarzyna Jakowska-Suwalska

    2013-01-01

    Full Text Available A multi-criteria model for determining the order size for materials used in production has been presented. It was assumed that the consumption rate of each material is a random variable with a known probability distribution. Using such a model, in which the purchase cost of materials ordered is limited, three criteria were considered: order size, probability of a lack of materials in the production process, and deviations in the order size from the consumption rate in past periods. Based on an example, it has been shown how to use the model to determine the order sizes for polyurethane adhesive and wood in a hard-coal mine. (original abstract

  10. 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.

  11. Measurements and modeling of total solar irradiance in X-class solar flares

    International Nuclear Information System (INIS)

    Moore, Christopher Samuel; Chamberlin, Phillip Clyde; Hock, Rachel

    2014-01-01

    The Total Irradiance Monitor (TIM) from NASA's SOlar Radiation and Climate Experiment can detect changes in the total solar irradiance (TSI) to a precision of 2 ppm, allowing observations of variations due to the largest X-class solar flares for the first time. Presented here is a robust algorithm for determining the radiative output in the TIM TSI measurements, in both the impulsive and gradual phases, for the four solar flares presented in Woods et al., as well as an additional flare measured on 2006 December 6. The radiative outputs for both phases of these five flares are then compared to the vacuum ultraviolet (VUV) irradiance output from the Flare Irradiance Spectral Model (FISM) in order to derive an empirical relationship between the FISM VUV model and the TIM TSI data output to estimate the TSI radiative output for eight other X-class flares. This model provides the basis for the bolometric energy estimates for the solar flares analyzed in the Emslie et al. study.

  12. 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

  13. An efficient flexible-order model for coastal and ocean water waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole

    Current work are directed toward the development of an improved numerical 3D model for fully nonlinear potential water waves over arbitrary depths. The model is high-order accurate, robust and efficient for large-scale problems, and support will be included for flexibility in the description...... as in the original works \\cite{LiFleming1997,BinghamZhang2007}. The new and improved approach employs a GMRES solver with multigrid preconditioning to achieve optimal scaling of the overall solution effort, i.e., directly with $n$ the total number of grid points. A robust method is achieved through a special...

  14. Replenishment policy for Entropic Order Quantity (EnOQ model with two component demand and partial back-logging under inflation

    Directory of Open Access Journals (Sweden)

    Bhanupriya Dash

    2017-09-01

    Full Text Available Background: Replenishment policy for entropic order quantity model with two component demand and partial backlogging under inflation is an important subject in the stock management. Methods: In this paper an inventory model for  non-instantaneous  deteriorating items with stock dependant consumption rate and partial back logged in addition the effect of inflection and time value of money on replacement policy with zero lead time consider was developed. Profit maximization model is formulated by considering the effects of partial backlogging under inflation with cash discounts. Further numerical example presented to evaluate the relative performance between the entropic order quantity and EOQ models separately. Numerical example is present to demonstrate the developed model and to illustrate the procedure. Lingo 13.0 version software used to derive optimal order quantity and total cost of inventory. Finally sensitivity analysis of the optimal solution with respect to different parameters of the system carried out. Results and conclusions: The obtained inventory model is very useful in retail business. This model can extend to total backorder.

  15. 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.

  16. Ranking periodic ordering models on the basis of minimizing total inventory cost

    Directory of Open Access Journals (Sweden)

    Mohammadali Keramati

    2015-06-01

    Full Text Available This paper aims to provide proper policies for inventory under uncertain conditions by comparing different inventory policies. To review the efficiency of these algorithms it is necessary to specify the area in which each of them is applied. Therefore, each of the models has been reviewed under different forms of retailing and they are ranked in terms of their expenses. According to the high values of inventories and their impacts on the costs of the companies, the ranking of various models using the simulation annealing algorithm are presented, which indicates that the proposed model of this paper could perform better than other alternative ones. The results also indicate that the suggested algorithm could save from 4 to 29 percent on costs of inventories.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. Multiplicative noise removal through fractional order tv-based model and fast numerical schemes for its approximation

    Science.gov (United States)

    Ullah, Asmat; Chen, Wen; Khan, Mushtaq Ahmad

    2017-07-01

    This paper introduces a fractional order total variation (FOTV) based model with three different weights in the fractional order derivative definition for multiplicative noise removal purpose. The fractional-order Euler Lagrange equation which is a highly non-linear partial differential equation (PDE) is obtained by the minimization of the energy functional for image restoration. Two numerical schemes namely an iterative scheme based on the dual theory and majorization- minimization algorithm (MMA) are used. To improve the restoration results, we opt for an adaptive parameter selection procedure for the proposed model by applying the trial and error method. We report numerical simulations which show the validity and state of the art performance of the fractional-order model in visual improvement as well as an increase in the peak signal to noise ratio comparing to corresponding methods. Numerical experiments also demonstrate that MMAbased methodology is slightly better than that of an iterative scheme.

  2. Integrating total quality management principles with the requirements of DOE Order 5700.6C

    Energy Technology Data Exchange (ETDEWEB)

    Hedges, D. [Scientific Ecology Group, Inc. (United States)

    1993-03-01

    The Department of Energy has recently required its field offices, contractors, and subcontractors to implement DOE Order 5700.6C, ``Quality Assurance,`` for all work on waste management contracts. The order restructures the 18 criteria of NQA-1 and focuses on the role of management in achieving and assuring quality, performance of activities to achieve and assure quality, and management`s assessment of its performance for the purpose of identifying improvements to be made. The DOE order also introduces elements of the total quality management (TQM) philosophy, which were not present in DOE Order 5700.6B. The research community within DOE has recently issued a document entitled DOE Order 5700.6C Implementation Guide, which is more explicit about the integration of TQM principles with the implementation of DOE Order 5700.6C in research facilities. The Environmental Protection Agency is sponsoring a quality assurance standard (ANSI/ASQC E-4) to replace EPA`s QAMS 005/80. The new standard is consistent with DOE Order 5700.6C, and it also stresses the integration of TQM principles within the quality assurance process. This paper discusses the intent and philosophy of the 10 criteria of the new DOE order, the status of ANSI/ASQC E-4, and how to effectively integrate TQM principles into the quality assurance process as the conversion is made from NQA-1 to DOE Order 5700.6C. The purpose and value of DOE Order 5700.6C Implementation Guide for research will also be discussed.

  3. 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.

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

    Science.gov (United States)

    Qi, Di

    applied in the training phase for calibrating model errors to achieve optimal imperfect model parameters; and total statistical energy dynamics are introduced to improve the model sensitivity in the prediction phase especially when strong external perturbations are exerted. The validity of reduced-order models for predicting statistical responses and intermittency is demonstrated on a series of instructive models with increasing complexity, including the stochastic triad model, the Lorenz '96 model, and models for barotropic and baroclinic turbulence. The skillful low-order modeling methods developed here should also be useful for other applications such as efficient algorithms for data assimilation.

  5. Frequency-domain reduced order models for gravitational waves from aligned-spin compact binaries

    International Nuclear Information System (INIS)

    Pürrer, Michael

    2014-01-01

    Black-hole binary coalescences are one of the most promising sources for the first detection of gravitational waves. Fast and accurate theoretical models of the gravitational radiation emitted from these coalescences are highly important for the detection and extraction of physical parameters. Spinning effective-one-body models for binaries with aligned-spins have been shown to be highly faithful, but are slow to generate and thus have not yet been used for parameter estimation (PE) studies. I provide a frequency-domain singular value decomposition-based surrogate reduced order model that is thousands of times faster for typical system masses and has a faithfulness mismatch of better than ∼0.1% with the original SEOBNRv1 model for advanced LIGO detectors. This model enables PE studies up to signal-to-noise ratios (SNRs) of 20 and even up to 50 for total masses below 50 M ⊙ . This paper discusses various choices for approximations and interpolation over the parameter space that can be made for reduced order models of spinning compact binaries, provides a detailed discussion of errors arising in the construction and assesses the fidelity of such models. (paper)

  6. 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,…

  7. 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.

  8. 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.

  9. Lot-Order Assignment Applying Priority Rules for the Single-Machine Total Tardiness Scheduling with Nonnegative Time-Dependent Processing Times

    Directory of Open Access Journals (Sweden)

    Jae-Gon Kim

    2015-01-01

    Full Text Available Lot-order assignment is to assign items in lots being processed to orders to fulfill the orders. It is usually performed periodically for meeting the due dates of orders especially in a manufacturing industry with a long production cycle time such as the semiconductor manufacturing industry. In this paper, we consider the lot-order assignment problem (LOAP with the objective of minimizing the total tardiness of the orders with distinct due dates. We show that we can solve the LOAP optimally by finding an optimal sequence for the single-machine total tardiness scheduling problem with nonnegative time-dependent processing times (SMTTSP-NNTDPT. Also, we address how the priority rules for the SMTTSP can be modified to those for the SMTTSP-NNTDPT to solve the LOAP. In computational experiments, we discuss the performances of the suggested priority rules and show the result of the proposed approach outperforms that of the commercial optimization software package.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. 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)

  15. A total safety management model

    International Nuclear Information System (INIS)

    Obadia, I.J.; Vidal, M.C.R.; Melo, P.F.F.F.

    2002-01-01

    In nuclear organizations, quality and safety are inextricably linked. Therefore, the search for excellence means reaching excellence in nuclear safety. The International Atomic Energy Agency, IAEA, developed, after the Chernobyl accident, the organizational approach for improving nuclear safety based on the safety culture, which requires a framework necessary to provide modifications in personnel attitudes and behaviors in situations related to safety. This work presents a Total Safety Management Model, based on the Model of Excellence of the Brazilian Quality Award and on the safety culture approach, which represents an alternative to this framework. The Model is currently under validation at the Nuclear Engineering Institute, in Rio de Janeiro, Brazil, and the results of its initial safety culture self assessment are also presented and discussed. (author)

  16. 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.

  17. 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.

  18. 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.

  19. Optimising a Model of Minimum Stock Level Control and a Model of Standing Order Cycle in Selected Foundry Plant

    Directory of Open Access Journals (Sweden)

    Szymszal J.

    2013-09-01

    Full Text Available It has been found that the area where one can look for significant reserves in the procurement logistics is a rational management of the stock of raw materials. Currently, the main purpose of projects which increase the efficiency of inventory management is to rationalise all the activities in this area, taking into account and minimising at the same time the total inventory costs. The paper presents a method for optimising the inventory level of raw materials under a foundry plant conditions using two different control models. The first model is based on the estimate of an optimal level of the minimum emergency stock of raw materials, giving information about the need for an order to be placed immediately and about the optimal size of consignments ordered after the minimum emergency level has occurred. The second model is based on the estimate of a maximum inventory level of raw materials and an optimal order cycle. Optimisation of the presented models has been based on the previously done selection and use of rational methods for forecasting the time series of the delivery of a chosen auxiliary material (ceramic filters to a casting plant, including forecasting a mean size of the delivered batch of products and its standard deviation.

  20. 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.

  1. 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.

  2. Fast prediction and evaluation of eccentric inspirals using reduced-order models

    Science.gov (United States)

    Barta, Dániel; Vasúth, Mátyás

    2018-06-01

    A large number of theoretically predicted waveforms are required by matched-filtering searches for the gravitational-wave signals produced by compact binary coalescence. In order to substantially alleviate the computational burden in gravitational-wave searches and parameter estimation without degrading the signal detectability, we propose a novel reduced-order-model (ROM) approach with applications to adiabatic 3PN-accurate inspiral waveforms of nonspinning sources that evolve on either highly or slightly eccentric orbits. We provide a singular-value decomposition-based reduced-basis method in the frequency domain to generate reduced-order approximations of any gravitational waves with acceptable accuracy and precision within the parameter range of the model. We construct efficient reduced bases comprised of a relatively small number of the most relevant waveforms over three-dimensional parameter-space covered by the template bank (total mass 2.15 M⊙≤M ≤215 M⊙ , mass ratio 0.01 ≤q ≤1 , and initial orbital eccentricity 0 ≤e0≤0.95 ). The ROM is designed to predict signals in the frequency band from 10 Hz to 2 kHz for aLIGO and aVirgo design sensitivity. Beside moderating the data reduction, finer sampling of fiducial templates improves the accuracy of surrogates. Considerable increase in the speedup from several hundreds to thousands can be achieved by evaluating surrogates for low-mass systems especially when combined with high-eccentricity.

  3. Total tree, merchantable stem and branch volume models for ...

    African Journals Online (AJOL)

    Total tree, merchantable stem and branch volume models for miombo woodlands of Malawi. Daud J Kachamba, Tron Eid. Abstract. The objective of this study was to develop general (multispecies) models for prediction of total tree, merchantable stem and branch volume including options with diameter at breast height (dbh) ...

  4. 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

  5. ISO 9000 and the total quality management models

    OpenAIRE

    Pacios Lozano, Ana Reyes

    1997-01-01

    Establishes the most outstanding differences between the ISO 9000 norms and total quality management as forms or manners of managing quality used in some information services. Compares two models of total quality: European Foundation far Quality Management and Malcolm Baldrige Awards.

  6. Multidemand Multisource Order Quantity Allocation with Multiple Transportation Alternatives

    Directory of Open Access Journals (Sweden)

    Jun Gang

    2015-01-01

    Full Text Available This paper focuses on a multidemand multisource order quantity allocation problem with multiple transportation alternatives. To solve this problem, a bilevel multiobjective programming model under a mixed uncertain environment is proposed. Two levels of decision makers are considered in the model. On the upper level, the purchaser aims to allocate order quantity to multiple suppliers for each demand node with the consideration of three objectives: total purchase cost minimization, total delay risk minimization, and total defect risk minimization. On the lower level, each supplier attempts to optimize the transportation alternatives with total transportation and penalty costs minimization as the objective. In contrast to prior studies, considering the information asymmetry in the bilevel decision, random and fuzzy random variables are used to model uncertain parameters of the construction company and the suppliers. To solve the bilevel model, a solution method based on Kuhn-Tucker conditions, sectional genetic algorithm, and fuzzy random simulation is proposed. Finally, the applicability of the proposed model and algorithm is evaluated through a practical case from a large scale construction project. The results show that the proposed model and algorithm are efficient in dealing with practical order quantity allocation problems.

  7. 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...

  8. Customer Order Decoupling Point Selection Model in Mass Customization Based on MAS

    Institute of Scientific and Technical Information of China (English)

    XU Xuanguo; LI Xiangyang

    2006-01-01

    Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration. Literatures on mass customization have been focused on mechanism of MC, but little on customer order decoupling point selection. The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization. Based on the analysis of other researchers' achievements combining the demand problems of customer and enterprise, a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system. Considering relatively the decision makers of independent functional departments as independent decision agents, a decision agent set is added as the third dimensionality to house of quality, the cubic quality function deployment is formed. The decision-making can be consisted of two procedures: the first one is to build each plane house of quality in various functional departments to express each opinions; the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment. Thus, department decision-making can well use its domain knowledge by ontology, and total decision-making can keep simple by avoiding too many customer requirements.

  9. A Combined First and Second Order Variational Approach for Image Reconstruction

    KAUST Repository

    Papafitsoros, K.

    2013-05-10

    In this paper we study a variational problem in the space of functions of bounded Hessian. Our model constitutes a straightforward higher-order extension of the well known ROF functional (total variation minimisation) to which we add a non-smooth second order regulariser. It combines convex functions of the total variation and the total variation of the first derivatives. In what follows, we prove existence and uniqueness of minimisers of the combined model and present the numerical solution of the corresponding discretised problem by employing the split Bregman method. The paper is furnished with applications of our model to image denoising, deblurring as well as image inpainting. The obtained numerical results are compared with results obtained from total generalised variation (TGV), infimal convolution and Euler\\'s elastica, three other state of the art higher-order models. The numerical discussion confirms that the proposed higher-order model competes with models of its kind in avoiding the creation of undesirable artifacts and blocky-like structures in the reconstructed images-a known disadvantage of the ROF model-while being simple and efficiently numerically solvable. ©Springer Science+Business Media New York 2013.

  10. 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.

  11. 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

  12. 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)

  13. 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.

  14. 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.

  15. Applying total interpretive structural modeling to study factors affecting construction labour productivity

    Directory of Open Access Journals (Sweden)

    Sayali Shrikrishna Sandbhor

    2014-03-01

    Full Text Available Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor analysis thus is an integral part of any study aiming to improve productivity.  Interpretive structural modeling is a methodology for identifying and summarizing relationships among factors which define an issue or problem. It provides a means to arrange the factors in an order as per their complexity. This study attempts to use the latest version of interpretive structural modeling i.e. total interpretive structural modeling to analyze factors negatively affecting construction labour productivity. It establishes interpretive relationship among these factors facilitating improvement in the overall productivity of construction site.

  16. 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. ...

  17. 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.

  18. Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

    Science.gov (United States)

    Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

    2014-06-01

    This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

  19. 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)

  20. 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.

  1. Development of NIR calibration models to assess year-to-year variation in total non-structural carbohydrates in grasses using PLSR

    DEFF Research Database (Denmark)

    Shetty, Nisha; Gislum, René; Jensen, Anne Mette Dahl

    2012-01-01

    Near-infrared (NIR) spectroscopy was used in combination with chemometrics to quantify total nonstructural carbohydrates (TNC) in grass samples in order to overcome year-to-year variation. A total of 1103 above-ground plant and root samples were collected from different field and pot experiments...... and with various experimental designs in the period from 2001 to 2005. A calibration model was developed using partial least squares regression (PLSR). The calibration model on a large data set spanning five years demonstrated that quantification of TNC using NIR spectroscopy was possible with an acceptable low...

  2. A robust optimization model for agile and build-to-order supply chain planning under uncertainties

    DEFF Research Database (Denmark)

    Lalmazloumian, Morteza; Wong, Kuan Yew; Govindan, Kannan

    2016-01-01

    Supply chain planning as one of the most important processes within the supply chain management concept, has a great impact on firms' success or failure. This paper considers a supply chain planning problem of an agile manufacturing company operating in a build-to-order environment under various....... The formulation is a robust optimization model with the objective of minimizing the expected total supply chain cost while maintaining customer service level. The developed multi-product, multi-period, multi-echelon robust mixed-integer linear programming model is then solved using the CPLEX optimization studio...

  3. Total Variation Based Parameter-Free Model for Impulse Noise Removal

    DEFF Research Database (Denmark)

    Sciacchitano, Federica; Dong, Yiqiu; Andersen, Martin Skovgaard

    2017-01-01

    We propose a new two-phase method for reconstruction of blurred images corrupted by impulse noise. In the first phase, we use a noise detector to identify the pixels that are contaminated by noise, and then, in the second phase, we reconstruct the noisy pixels by solving an equality constrained...... total variation minimization problem that preserves the exact values of the noise-free pixels. For images that are only corrupted by impulse noise (i. e., not blurred) we apply the semismooth Newton's method to a reduced problem, and if the images are also blurred, we solve the equality constrained...... reconstruction problem using a first-order primal-dual algorithm. The proposed model improves the computational efficiency (in the denoising case) and has the advantage of being regularization parameter-free. Our numerical results suggest that the method is competitive in terms of its restoration capabilities...

  4. Collaborative problem solving with a total quality model.

    Science.gov (United States)

    Volden, C M; Monnig, R

    1993-01-01

    A collaborative problem-solving system committed to the interests of those involved complies with the teachings of the total quality management movement in health care. Deming espoused that any quality system must become an integral part of routine activities. A process that is used consistently in dealing with problems, issues, or conflicts provides a mechanism for accomplishing total quality improvement. The collaborative problem-solving process described here results in quality decision-making. This model incorporates Ishikawa's cause-and-effect (fishbone) diagram, Moore's key causes of conflict, and the steps of the University of North Dakota Conflict Resolution Center's collaborative problem solving model.

  5. 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....

  6. 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.

  7. 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).

  8. DEVELOPMENT OF THE MODEL OF AN AUTOMATIC GENERATION OF TOTAL AMOUNTS OF COMMISSIONS IN INTERNATIONAL INTERBANK PAYMENTS

    Directory of Open Access Journals (Sweden)

    Dmitry N. Bolotov

    2013-01-01

    Full Text Available The article deals with the main form of international payment - bank transfer and features when it is charging by banks correspondent fees for transit funds in their correspondent accounts. In order to optimize the cost of expenses for international money transfers there is a need to develop models and toolkit of automatic generation of the total amount of commissions in international interbank settlements. Accordingly, based on graph theory, approach to the construction of the model was developed.

  9. Development and validation of a weight-bearing finite element model for total knee replacement.

    Science.gov (United States)

    Woiczinski, M; Steinbrück, A; Weber, P; Müller, P E; Jansson, V; Schröder, Ch

    2016-01-01

    Total knee arthroplasty (TKA) is a successful procedure for osteoarthritis. However, some patients (19%) do have pain after surgery. A finite element model was developed based on boundary conditions of a knee rig. A 3D-model of an anatomical full leg was generated from magnetic resonance image data and a total knee prosthesis was implanted without patella resurfacing. In the finite element model, a restarting procedure was programmed in order to hold the ground reaction force constant with an adapted quadriceps muscle force during a squat from 20° to 105° of flexion. Knee rig experimental data were used to validate the numerical model in the patellofemoral and femorotibial joint. Furthermore, sensitivity analyses of Young's modulus of the patella cartilage, posterior cruciate ligament (PCL) stiffness, and patella tendon origin were performed. Pearson's correlations for retropatellar contact area, pressure, patella flexion, and femorotibial ap-movement were near to 1. Lowest root mean square error for retropatellar pressure, patella flexion, and femorotibial ap-movement were found for the baseline model setup with Young's modulus of 5 MPa for patella cartilage, a downscaled PCL stiffness of 25% compared to the literature given value and an anatomical origin of the patella tendon. The results of the conducted finite element model are comparable with the experimental results. Therefore, the finite element model developed in this study can be used for further clinical investigations and will help to better understand the clinical aspects after TKA with an unresurfaced patella.

  10. 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

  11. 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)

  12. 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.

  13. 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)

  14. 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...

  15. 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.

  16. 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....

  17. An Integrated Model of Material Supplier Selection and Order Allocation Using Fuzzy Extended AHP and Multiobjective Programming

    Directory of Open Access Journals (Sweden)

    Zhi Li

    2013-01-01

    Full Text Available This paper presents a supplier selection and order allocation (SSOA model to solve the problem of a multiperiod supplier selection and then order allocation in the environment of short product life cycle and frequent material purchasing, for example, fast fashion environment in apparel industry. At the first stage, with consideration of multiple decision criteria and the fuzziness of the data involved in deciding the preferences of multiple decision variables in supplier selection, the fuzzy extent analytic hierarchy process (FEAHP is adopted. In the second stage, supplier ranks are inputted into an order allocation model that aims at minimizing the risk of material purchasing and minimizing the total material purchasing costs using a dynamic programming approach, subject to constraints on deterministic customer demand and deterministic supplier capacity. Numerical examples are presented, and computational results are reported.

  18. Composite symmetry-protected topological order and effective models

    Science.gov (United States)

    Nietner, A.; Krumnow, C.; Bergholtz, E. J.; Eisert, J.

    2017-12-01

    Strongly correlated quantum many-body systems at low dimension exhibit a wealth of phenomena, ranging from features of geometric frustration to signatures of symmetry-protected topological order. In suitable descriptions of such systems, it can be helpful to resort to effective models, which focus on the essential degrees of freedom of the given model. In this work, we analyze how to determine the validity of an effective model by demanding it to be in the same phase as the original model. We focus our study on one-dimensional spin-1 /2 systems and explain how nontrivial symmetry-protected topologically ordered (SPT) phases of an effective spin-1 model can arise depending on the couplings in the original Hamiltonian. In this analysis, tensor network methods feature in two ways: on the one hand, we make use of recent techniques for the classification of SPT phases using matrix product states in order to identify the phases in the effective model with those in the underlying physical system, employing Künneth's theorem for cohomology. As an intuitive paradigmatic model we exemplify the developed methodology by investigating the bilayered Δ chain. For strong ferromagnetic interlayer couplings, we find the system to transit into exactly the same phase as an effective spin-1 model. However, for weak but finite coupling strength, we identify a symmetry broken phase differing from this effective spin-1 description. On the other hand, we underpin our argument with a numerical analysis making use of matrix product states.

  19. 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.

  20. 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.

  1. 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

  2. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators.

    Science.gov (United States)

    Backović, Mihailo; Krämer, Michael; Maltoni, Fabio; Martini, Antony; Mawatari, Kentarou; Pellen, Mathieu

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s -channel mediators. We implement such models in the FeynRules/MadGraph5_aMC@NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s -channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties.

  3. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

    Energy Technology Data Exchange (ETDEWEB)

    Backović, Mihailo [Centre for Cosmology, Particle Physics and Phenomenology (CP3), Université catholique de Louvain, 1348, Louvain-la-Neuve (Belgium); Krämer, Michael [Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University, 52056, Aachen (Germany); Maltoni, Fabio; Martini, Antony [Centre for Cosmology, Particle Physics and Phenomenology (CP3), Université catholique de Louvain, 1348, Louvain-la-Neuve (Belgium); Mawatari, Kentarou, E-mail: kentarou.mawatari@vub.ac.be [Theoretische Natuurkunde and IIHE/ELEM, Vrije Universiteit Brussel, and International Solvay Institutes, Pleinlaan 2, 1050, Brussels (Belgium); Pellen, Mathieu [Institute for Theoretical Particle Physics and Cosmology, RWTH Aachen University, 52056, Aachen (Germany)

    2015-10-07

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5{sub a}MC@NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties.

  4. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

    Energy Technology Data Exchange (ETDEWEB)

    Backovic, Mihailo; Maltoni, Fabio; Martini, Antony [Universite catholique de Louvain, Centre for Cosmology, Particle Physics and Phenomenology (CP3), Louvain-la-Neuve (Belgium); Kraemer, Michael; Pellen, Mathieu [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany); Mawatari, Kentarou [Theoretische Natuurkunde and IIHE/ELEM, Vrije Universiteit Brussel, and International Solvay Institutes, Brussels (Belgium)

    2015-10-15

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5{sub a}MC rate at NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties. (orig.)

  5. Higher-order QCD predictions for dark matter production at the LHC in simplified models with s-channel mediators

    International Nuclear Information System (INIS)

    Backovic, Mihailo; Maltoni, Fabio; Martini, Antony; Kraemer, Michael; Pellen, Mathieu; Mawatari, Kentarou

    2015-01-01

    Weakly interacting dark matter particles can be pair-produced at colliders and detected through signatures featuring missing energy in association with either QCD/EW radiation or heavy quarks. In order to constrain the mass and the couplings to standard model particles, accurate and precise predictions for production cross sections and distributions are of prime importance. In this work, we consider various simplified models with s-channel mediators. We implement such models in the FeynRules/MadGraph5 a MC rate at NLO framework, which allows to include higher-order QCD corrections in realistic simulations and to study their effect systematically. As a first phenomenological application, we present predictions for dark matter production in association with jets and with a top-quark pair at the LHC, at next-to-leading order accuracy in QCD, including matching/merging to parton showers. Our study shows that higher-order QCD corrections to dark matter production via s-channel mediators have a significant impact not only on total production rates, but also on shapes of distributions. We also show that the inclusion of next-to-leading order effects results in a sizeable reduction of the theoretical uncertainties. (orig.)

  6. Research on compressive sensing reconstruction algorithm based on total variation model

    Science.gov (United States)

    Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

    2017-12-01

    Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

  7. 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

  8. 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...

  9. A formal model for total quality management

    NARCIS (Netherlands)

    S.C. van der Made-Potuijt; H.B. Bertsch (Boudewijn); L.P.J. Groenewegen

    1996-01-01

    textabstractTotal Quality Management (TQM) is a systematic approach to managing a company. TQM is systematic in the sense that it is uses facts through observation, analysis and measurable goals. There are theoretical descriptions of this management concept, but there is no formal model of it. A

  10. 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...

  11. 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

  12. 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.

  13. 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...

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. 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

  1. QCD next-to-leading order predictions matched to parton showers for vector-like quark models

    CERN Document Server

    Fuks, Benjamin

    2017-02-27

    Vector-like quarks are featured by a wealth of beyond the Standard Model theories and are consequently an important goal of many LHC searches for new physics. Those searches, as well as most related phenomenological studies, however rely on predictions evaluated at the leading-order accuracy in QCD and consider well-defined simplified benchmark scenarios. Adopting an effective bottom-up approach, we compute next-to-leading-order predictions for vector-like-quark pair-production and single production in association with jets, with a weak or with a Higgs boson in a general new physics setup. We additionally compute vector-like-quark contributions to the production of a pair of Standard Model bosons at the same level of accuracy. For all processes under consideration, we focus both on total cross sections and on differential distributions, most these calculations being performed for the first time in our field. As a result, our work paves the way to precise extraction of experimental limits on vector-like quarks...

  2. Low-order models of a single-screw expander for organic Rankine cycle applications

    Science.gov (United States)

    Ziviani, D.; Desideri, A.; Lemort, V.; De Paepe, M.; van den Broek, M.

    2015-08-01

    Screw-type volumetric expanders have been demonstrated to be a suitable technology for organic Rankine cycle (ORC) systems because of higher overall effectiveness and good part-load behaviour over other positive displacement machines. An 11 kWe single-screw expander (SSE) adapted from an air compressor has been tested in an ORC test-rig operating with R245fa as working fluid. A total of 60 steady-steady points have been obtained at four different rotational speeds of the expander in the range between 2000 rpm and 3300 rpm. The maximum electrical power output and overall isentropic effectiveness measured were 7.3 kW and 51.9%, respectively. In this paper, a comparison between two low-order models is proposed in terms of accuracy of the predictions, the robustness of the model and the computational time. The first model is the Pacejka equation-based model and the second is a semi-empirical model derived from a well-known scroll expander model and modified to include the geometric aspects of a single screw expander. The models have been calibrated with the available steady-state measurement points by identifying the proper parameters.

  3. 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

  4. 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.

  5. EOQ Model for Deteriorating Items with exponential time dependent Demand Rate under inflation when Supplier Credit Linked to Order Quantity

    Directory of Open Access Journals (Sweden)

    Rakesh Prakash Tripathi

    2014-05-01

    Full Text Available In paper (2004 Chang studied an inventory model under a situation in which the supplier provides the purchaser with a permissible delay of payments if the purchaser orders a large quantity. Tripathi (2011 also studied an inventory model with time dependent demand rate under which the supplier provides the purchaser with a permissible delay in payments. This paper is motivated by Chang (2004 and Tripathi (2011 paper extending their model for exponential time dependent demand rate. This study develops an inventory model under which the vendor provides the purchaser with a credit period; if the purchaser orders large quantity. In this chapter, demand rate is taken as exponential time dependent. Shortages are not allowed and effect of the inflation rate has been discussed. We establish an inventory model for deteriorating items if the order quantity is greater than or equal to a predetermined quantity. We then obtain optimal solution for finding optimal order quantity, optimal cycle time and optimal total relevant cost. Numerical examples are given for all different cases. Sensitivity of the variation of different parameters on the optimal solution is also discussed. Mathematica 7 software is used for finding numerical examples.

  6. Life course models: improving interpretation by consideration of total effects.

    Science.gov (United States)

    Green, Michael J; Popham, Frank

    2017-06-01

    Life course epidemiology has used models of accumulation and critical or sensitive periods to examine the importance of exposure timing in disease aetiology. These models are usually used to describe the direct effects of exposures over the life course. In comparison with consideration of direct effects only, we show how consideration of total effects improves interpretation of these models, giving clearer notions of when it will be most effective to intervene. We show how life course variation in the total effects depends on the magnitude of the direct effects and the stability of the exposure. We discuss interpretation in terms of total, direct and indirect effects and highlight the causal assumptions required for conclusions as to the most effective timing of interventions. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.

  7. 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.

  8. Total energy calculations from self-energy models

    International Nuclear Information System (INIS)

    Sanchez-Friera, P.

    2001-06-01

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

  9. Total Strain FE Model for Reinforced Concrete Floors on Piles

    NARCIS (Netherlands)

    Hofmeyer, H.; Bos, van den A.A.

    2008-01-01

    A finite element (FE) model using a total strain material model has been developed to predict the behavior of warehouse reinforced concrete floors on piles. The material model (not the FE model itself) was calibrated to material tests. The FE model for the floor structure was checked with full-scale

  10. 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.

  11. 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…

  12. 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…

  13. 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....

  14. 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.

  15. 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.

  16. TOTAL user manual

    Science.gov (United States)

    Johnson, Sally C.; Boerschlein, David P.

    1994-01-01

    Semi-Markov models can be used to analyze the reliability of virtually any fault-tolerant system. However, the process of delineating all of the states and transitions in the model of a complex system can be devastatingly tedious and error-prone. Even with tools such as the Abstract Semi-Markov Specification Interface to the SURE Tool (ASSIST), the user must describe a system by specifying the rules governing the behavior of the system in order to generate the model. With the Table Oriented Translator to the ASSIST Language (TOTAL), the user can specify the components of a typical system and their attributes in the form of a table. The conditions that lead to system failure are also listed in a tabular form. The user can also abstractly specify dependencies with causes and effects. The level of information required is appropriate for system designers with little or no background in the details of reliability calculations. A menu-driven interface guides the user through the system description process, and the program updates the tables as new information is entered. The TOTAL program automatically generates an ASSIST input description to match the system description.

  17. 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.

  18. 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.

  19. 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

  20. Total, Direct, and Indirect Effects in Logit Models

    DEFF Research Database (Denmark)

    Karlson, Kristian Bernt; Holm, Anders; Breen, Richard

    It has long been believed that the decomposition of the total effect of one variable on another into direct and indirect effects, while feasible in linear models, is not possible in non-linear probability models such as the logit and probit. In this paper we present a new and simple method...... average partial effects, as defined by Wooldridge (2002). We present the method graphically and illustrate it using the National Educational Longitudinal Study of 1988...

  1. 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.

  2. 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.

  3. 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).

  4. 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.

  5. 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

  6. Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

    Science.gov (United States)

    CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

    2013-12-01

    Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily

  7. Model-based estimation of finite population total in stratified sampling

    African Journals Online (AJOL)

    The work presented in this paper concerns the estimation of finite population total under model – based framework. Nonparametric regression approach as a method of estimating finite population total is explored. The asymptotic properties of the estimators based on nonparametric regression are also developed under ...

  8. Semiphysiological versus Empirical Modelling of the Population Pharmacokinetics of Free and Total Cefazolin during Pregnancy

    Directory of Open Access Journals (Sweden)

    J. G. Coen van Hasselt

    2014-01-01

    Full Text Available This work describes a first population pharmacokinetic (PK model for free and total cefazolin during pregnancy, which can be used for dose regimen optimization. Secondly, analysis of PK studies in pregnant patients is challenging due to study design limitations. We therefore developed a semiphysiological modeling approach, which leveraged gestation-induced changes in creatinine clearance (CrCL into a population PK model. This model was then compared to the conventional empirical covariate model. First, a base two-compartmental PK model with a linear protein binding was developed. The empirical covariate model for gestational changes consisted of a linear relationship between CL and gestational age. The semiphysiological model was based on the base population PK model and a separately developed mixed-effect model for gestation-induced change in CrCL. Estimates for baseline clearance (CL were 0.119 L/min (RSE 58% and 0.142 L/min (RSE 44% for the empirical and semiphysiological models, respectively. Both models described the available PK data comparably well. However, as the semiphysiological model was based on prior knowledge of gestation-induced changes in renal function, this model may have improved predictive performance. This work demonstrates how a hybrid semiphysiological population PK approach may be of relevance in order to derive more informative inferences.

  9. 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.

  10. 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).

  11. Fast magnetic resonance imaging based on high degree total variation

    Science.gov (United States)

    Wang, Sujie; Lu, Liangliang; Zheng, Junbao; Jiang, Mingfeng

    2018-04-01

    In order to eliminating the artifacts and "staircase effect" of total variation in Compressive Sensing MRI, high degree total variation model is proposed for dynamic MRI reconstruction. the high degree total variation regularization term is used as a constraint to reconstruct the magnetic resonance image, and the iterative weighted MM algorithm is proposed to solve the convex optimization problem of the reconstructed MR image model, In addtion, one set of cardiac magnetic resonance data is used to verify the proposed algorithm for MRI. The results show that the high degree total variation method has a better reconstruction effect than the total variation and the total generalized variation, which can obtain higher reconstruction SNR and better structural similarity.

  12. 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)

  13. 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

  14. Order Aggressiveness and Order Book Dynamics

    OpenAIRE

    Anthony D. Hall; Nikolaus Hautsch

    2004-01-01

    In this paper, we study the determinants of order aggressiveness and traders' order submission strategy in an open limit order book market. Using order book data from the Australian Stock Exchange, we model traders' aggressiveness in market trading, limit order trading as well as in order cancellations on both sides of the market using a six-dimensional autoregressive intensity model. The information revealed by the open order book plays an important role in explaining the degree of order agg...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Predictive models for monitoring and analysis of the total zooplankton

    Directory of Open Access Journals (Sweden)

    Obradović Milica

    2014-01-01

    Full Text Available In recent years, modeling and prediction of total zooplankton abundance have been performed by various tools and techniques, among which data mining tools have been less frequent. The purpose of this paper is to automatically determine the dependency degree and the influence of physical, chemical and biological parameters on the total zooplankton abundance, through design of the specific data mining models. For this purpose, the analysis of key influencers was used. The analysis is based on the data obtained from the SeLaR information system - specifically, the data from the two reservoirs (Gruža and Grošnica with different morphometric characteristics and trophic state. The data is transformed into optimal structure for data analysis, upon which, data mining model based on the Naïve Bayes algorithm is constructed. The results of the analysis imply that in both reservoirs, parameters of groups and species of zooplankton have the greatest influence on the total zooplankton abundance. If these inputs (group and zooplankton species are left out, differences in the impact of physical, chemical and other biological parameters in dependences of reservoirs can be noted. In the Grošnica reservoir, analysis showed that the temporal dimension (months, nitrates, water temperature, chemical oxygen demand, chlorophyll and chlorides, had the key influence with strong relative impact. In the Gruža reservoir, key influence parameters for total zooplankton are: spatial dimension (location, water temperature and physiological groups of bacteria. The results show that the presented data mining model is usable on any kind of aquatic ecosystem and can also serve for the detection of inputs which could be the basis for the future analysis and modeling.

  20. 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

  1. 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...

  2. 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 ...

  3. A delta-rule model of numerical and non-numerical order processing.

    Science.gov (United States)

    Verguts, Tom; Van Opstal, Filip

    2014-06-01

    Numerical and non-numerical order processing share empirical characteristics (distance effect and semantic congruity), but there are also important differences (in size effect and end effect). At the same time, models and theories of numerical and non-numerical order processing developed largely separately. Currently, we combine insights from 2 earlier models to integrate them in a common framework. We argue that the same learning principle underlies numerical and non-numerical orders, but that environmental features determine the empirical differences. Implications for current theories on order processing are pointed out. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  4. 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.

  5. Evaluation of accelerated test parameters for CMOS IC total dose hardness prediction

    International Nuclear Information System (INIS)

    Sogoyan, A.V.; Nikiforov, A.Y.; Chumakov, A.I.

    1999-01-01

    The approach to accelerated test parameters evaluation is presented in order to predict CMOS IC total dose behavior in variable dose-rate environment. The technique is based on the analytical model of MOSFET parameters total dose degradation. The simple way to estimate model parameter is proposed using IC's input-output MOSFET radiation test results. (authors)

  6. Economic analysis model for total energy and economic systems

    International Nuclear Information System (INIS)

    Shoji, Katsuhiko; Yasukawa, Shigeru; Sato, Osamu

    1980-09-01

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

  7. Exercise order affects the total training volume and the ratings of perceived exertion in response to a super-set resistance training session

    Directory of Open Access Journals (Sweden)

    Balsamo S

    2012-02-01

    Full Text Available Sandor Balsamo1–3, Ramires Alsamir Tibana1,2,4, Dahan da Cunha Nascimento1,2, Gleyverton Landim de Farias1,2, Zeno Petruccelli1,2, Frederico dos Santos de Santana1,2, Otávio Vanni Martins1,2, Fernando de Aguiar1,2, Guilherme Borges Pereira4, Jéssica Cardoso de Souza4, Jonato Prestes41Department of Physical Education, Centro Universitário UNIEURO, Brasília, 2GEPEEFS (Resistance training and Health Research Group, Brasília/DF, 3Graduate Program in Medical Sciences, School of Medicine, Universidade de Brasília (UnB, Brasília, 4Graduation Program in Physical Education, Catholic University of Brasilia (UCB, Brasília/DF, BrazilAbstract: The super-set is a widely used resistance training method consisting of exercises for agonist and antagonist muscles with limited or no rest interval between them – for example, bench press followed by bent-over rows. In this sense, the aim of the present study was to compare the effects of different super-set exercise sequences on the total training volume. A secondary aim was to evaluate the ratings of perceived exertion and fatigue index in response to different exercise order. On separate testing days, twelve resistance-trained men, aged 23.0 ± 4.3 years, height 174.8 ± 6.75 cm, body mass 77.8 ± 13.27 kg, body fat 12.0% ± 4.7%, were submitted to a super-set method by using two different exercise orders: quadriceps (leg extension + hamstrings (leg curl (QH or hamstrings (leg curl + quadriceps (leg extension (HQ. Sessions consisted of three sets with a ten-repetition maximum load with 90 seconds rest between sets. Results revealed that the total training volume was higher for the HQ exercise order (P = 0.02 with lower perceived exertion than the inverse order (P = 0.04. These results suggest that HQ exercise order involving lower limbs may benefit practitioners interested in reaching a higher total training volume with lower ratings of perceived exertion compared with the leg extension plus leg curl

  8. 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.

  9. 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)

  10. 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.

  11. 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.

  12. 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...

  13. Newton-Gauss Algorithm of Robust Weighted Total Least Squares Model

    Directory of Open Access Journals (Sweden)

    WANG Bin

    2015-06-01

    Full Text Available Based on the Newton-Gauss iterative algorithm of weighted total least squares (WTLS, a robust WTLS (RWTLS model is presented. The model utilizes the standardized residuals to construct the weight factor function and the square root of the variance component estimator with robustness is obtained by introducing the median method. Therefore, the robustness in both the observation and structure spaces can be simultaneously achieved. To obtain standardized residuals, the linearly approximate cofactor propagation law is employed to derive the expression of the cofactor matrix of WTLS residuals. The iterative calculation steps for RWTLS are also described. The experiment indicates that the model proposed in this paper exhibits satisfactory robustness for gross errors handling problem of WTLS, the obtained parameters have no significant difference with the results of WTLS without gross errors. Therefore, it is superior to the robust weighted total least squares model directly constructed with residuals.

  14. 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.

  15. Application of the Polynomial-Based Least Squares and Total Least Squares Models for the Attenuated Total Reflection Fourier Transform Infrared Spectra of Binary Mixtures of Hydroxyl Compounds.

    Science.gov (United States)

    Shan, Peng; Peng, Silong; Zhao, Yuhui; Tang, Liang

    2016-03-01

    An analysis of binary mixtures of hydroxyl compound by Attenuated Total Reflection Fourier transform infrared spectroscopy (ATR FT-IR) and classical least squares (CLS) yield large model error due to the presence of unmodeled components such as H-bonded components. To accommodate these spectral variations, polynomial-based least squares (LSP) and polynomial-based total least squares (TLSP) are proposed to capture the nonlinear absorbance-concentration relationship. LSP is based on assuming that only absorbance noise exists; while TLSP takes both absorbance noise and concentration noise into consideration. In addition, based on different solving strategy, two optimization algorithms (limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm and Levenberg-Marquardt (LM) algorithm) are combined with TLSP and then two different TLSP versions (termed as TLSP-LBFGS and TLSP-LM) are formed. The optimum order of each nonlinear model is determined by cross-validation. Comparison and analyses of the four models are made from two aspects: absorbance prediction and concentration prediction. The results for water-ethanol solution and ethanol-ethyl lactate solution show that LSP, TLSP-LBFGS, and TLSP-LM can, for both absorbance prediction and concentration prediction, obtain smaller root mean square error of prediction than CLS. Additionally, they can also greatly enhance the accuracy of estimated pure component spectra. However, from the view of concentration prediction, the Wilcoxon signed rank test shows that there is no statistically significant difference between each nonlinear model and CLS. © The Author(s) 2016.

  16. 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.

  17. 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.

  18. Application of a system dynamics model to improve the performance of make-to-order production

    Directory of Open Access Journals (Sweden)

    Yi-Lun Elaine Ho

    2015-08-01

    Full Text Available This study provides a system dynamics (SD model of make-to-order (MTO production and discusses the key factors of production improvement. The proposed system can be divided into three subsystems: income/cost, order/production, and human resources (HR. The time delay between customer demand, production demand, order quantity, material demand, and inventory is considered in a practical application. In addition, this paper considers how the cycle time is affected by the total input of HR; how unit transportation cost is influenced by the delivery quantity; and how unit penalty (shortage cost is affected by the amount of shortage. The production capacity, yield, and holding cost needed to satisfy practical demands are all considered. A simulation approach to MTO production for meeting contract requests is presented in this study. Simulation results reveal that the amount of shortage will be the most important factor affecting the policy for the replenishment of material. Although the rise in production capacity leads to a reduced amount of shortage, it does not play a significant role. A sensitivity analysis of the replenishment of material policy is conducted to find out the best suggested policy. The SD model is also shown to quickly simulate changes in system behaviour, which allows an organisation enough time to respond to and conquer any unpredictable situation that might occur.

  19. 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.

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

    Science.gov (United States)

    Narsipur, Shreyas

    Unsteady aerodynamics has been a topic of research since the late 1930's and has increased in popularity among researchers studying dynamic stall in helicopters, insect/bird flight, micro air vehicles, wind-turbine aerodynamics, and ow-energy harvesting devices. Several experimental and computational studies have helped researchers gain a good understanding of the unsteady ow phenomena, but have proved to be expensive and time-intensive for rapid design and analysis purposes. Since the early 1970's, the push to develop low-order models to solve unsteady ow problems has resulted in several semi-empirical models capable of effectively analyzing unsteady aerodynamics in a fraction of the time required by high-order methods. However, due to the various complexities associated with time-dependent flows, several empirical constants and curve fits derived from existing experimental and computational results are required by the semi-empirical models to be an effective analysis tool. The aim of the current work is to develop a low-order model capable of simulating incompressible dynamic-stall type ow problems with a focus on accurately modeling the unsteady ow physics with the aim of reducing empirical dependencies. The lumped-vortex-element (LVE) algorithm is used as the baseline unsteady inviscid model to which augmentations are applied to model unsteady viscous effects. The current research is divided into two phases. The first phase focused on augmentations aimed at modeling pure unsteady trailing-edge boundary-layer separation and stall without leading-edge vortex (LEV) formation. The second phase is targeted at including LEV shedding capabilities to the LVE algorithm and combining with the trailing-edge separation model from phase one to realize a holistic, optimized, and robust low-order dynamic stall model. In phase one, initial augmentations to theory were focused on modeling the effects of steady trailing-edge separation by implementing a non-linear decambering

  1. 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

  2. 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.

  3. 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

  4. 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

  5. Image Restoration Based on the Hybrid Total-Variation-Type Model

    OpenAIRE

    Shi, Baoli; Pang, Zhi-Feng; Yang, Yu-Fei

    2012-01-01

    We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two ${L}^{1}$ -norm terms in the proposed model make it difficultly solved by using some classically numerical methods directly, we first employ the alternating direction method of multipliers (ADMM) to solve a general form of the proposed model. Then, based on the ADMM and the Moreau-Yosida decomposition theory, a more efficient method call...

  6. Target dependence of K+-nucleus total cross sections

    International Nuclear Information System (INIS)

    Jiang, M.F.; Ernst, D.J.; Chen, C.M.

    1995-01-01

    We investigate the total cross section and its target dependence for K + -nucleus scattering using a relativistic momentum-space optical potential model which incorporates relativistically normalized wave functions, invariant two-body amplitudes, covariant kinematics, and an exact full-Fermi averaging integral. The definition of the total cross section in the presence of a Coulomb interaction is reviewed and the total cross section is calculated in a way that is consistent with what is extracted from experiment. In addition, the total cross sections for a nucleus and for the deuteron are calculated utilizing the same theory. This minimizes the dependence of the ratio of these cross sections on the details of the theory. The model dependence of the first-order optical potential calculations is investigated. The theoretical results are found to be systematically below all existing data

  7. 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.

  8. Presenting a Multi Objective Model for Supplier Selection in Order to Reduce Green House Gas Emission under Uncertion Demand

    Directory of Open Access Journals (Sweden)

    Habibollah Mohamadi

    2014-08-01

    Full Text Available Recently, much attention has been given to Stochastic demand due to uncertainty in the real -world. In the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. On the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. The supplier selection plays an important role in the green chain. In this paper, a multi-objective nonlinear integer programming model for selecting a set of supplier considering Stochastic demand is proposed. while the cost of purchasing include the total cost, holding and stock out costs, rejected units, units have been delivered sooner, and total green house gas emissions are minimized, while the obtained total score from the supplier assessment process is maximized. It is assumed, the purchaser provides the different products from the number predetermined supplier to a with Stochastic demand and the uniform probability distribution function. The product price depends on the order quantity for each product line is intended. Multi-objective models using known methods, such as Lp-metric has become an objective function and then uses genetic algorithms and simulated annealing meta-heuristic is solved.

  9. QCD next-to-leading-order predictions matched to parton showers for vector-like quark models.

    Science.gov (United States)

    Fuks, Benjamin; Shao, Hua-Sheng

    2017-01-01

    Vector-like quarks are featured by a wealth of beyond the Standard Model theories and are consequently an important goal of many LHC searches for new physics. Those searches, as well as most related phenomenological studies, however, rely on predictions evaluated at the leading-order accuracy in QCD and consider well-defined simplified benchmark scenarios. Adopting an effective bottom-up approach, we compute next-to-leading-order predictions for vector-like-quark pair production and single production in association with jets, with a weak or with a Higgs boson in a general new physics setup. We additionally compute vector-like-quark contributions to the production of a pair of Standard Model bosons at the same level of accuracy. For all processes under consideration, we focus both on total cross sections and on differential distributions, most these calculations being performed for the first time in our field. As a result, our work paves the way to precise extraction of experimental limits on vector-like quarks thanks to an accurate control of the shapes of the relevant observables and emphasise the extra handles that could be provided by novel vector-like-quark probes never envisaged so far.

  10. Evaluating Performance of Safety Management and Occupational Health Using Total Quality Safety Management Model (TQSM

    Directory of Open Access Journals (Sweden)

    E Mohammadfam

    2015-11-01

    Full Text Available Introduction: All organizations, whether public or private, necessitate performance evaluation systems in regard with growth, stability, and development in the competitive fields. One of the existing models for performance evaluation of occupational health and safety management is Total Quality Safety Management model (TQSM. Therefore, the present study aimed to evaluate performance of safety management and occupational health utilizing TQSM model. Methods: In this descriptive-analytic study, the population consisted of 16 individuals, including managers, supervisors, and members of technical protection and work health committee. Then the participants were asked to respond to TQSM questionnaire before and after the implementation of Occupational Health & Safety Advisory Services 18001 (OHSAS18001. Ultimately, the level of each program as well as the TQSM status were determined before and after the implementation of OHSAS18001. Results: The study results showed that the scores obtained by the company before OHSAS 18001’s implementation, was 43.7 out of 312. After implementing OHSAS 18001 in the company and receiving the related certificate, the total score of safety program that company could obtain was 127.12 out of 312 demonstrating a rise of 83.42 scores (26.8%. The paired t-test revealed that mean difference of TQSM scores before and after OHSAS 18001 implementation was proved to be significant (p> 0.05. Conclusion: The study findings demonstrated that TQSM can be regarded as an appropriate model in order to monitor the performance of safety management system and occupational health, since it possesses the ability to quantitatively evaluate the system performance.

  11. 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)

  12. 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.

  13. The lowest order total electromagnetic correction to the deep inelastic scattering of polarized leptons on polarized nucleons

    International Nuclear Information System (INIS)

    Shumeiko, N.M.; Timoshin, S.I.

    1991-01-01

    Compact formulae for a total 1-loop electromagnetic corrections, including the contribution of electromagnetic hadron effects to the deep inelastic scattering of polarized leptons on polarized nucleons in the quark-parton model have been obtained. The cases of longitudinal and transverse nucleon polarization are considered in detail. A thorough numerical calculation of corrections to cross sections and polarization asymmetries at muon (electron) energies over the range of 200-2000 GeV (10-16 GeV) has been made. It has been established that the contribution of corrections to the hadron current considerably affects the behaviour of longitudinal asymmetry. A satisfactory agreement is found between the model calculations of corrections to the lepton current and the phenomenological calculation results, which makes it possible to find the total 1-loop correction within the framework of a common approach. (Author)

  14. Economic Impacts of Total Water Use Control in the Heihe River Basin in Northwestern China—An Integrated CGE-BEM Modeling Approach

    Directory of Open Access Journals (Sweden)

    Na Li

    2015-03-01

    Full Text Available This paper develops an integrated modeling approach combined with a top-down dynamic computable general equilibrium (CGE model and a bottom-up bio-economic model (BEM to study the economic impact of a total water use control policy in the Heihe river basin, northwestern China. The integrated CGE-BEM model is regionally disaggregated with a variety of crops and livestock, and includes the responses of farmers and consequent feedback effects in the regional economic system. The results show that under the total water use control scenario, the water use structure is changed and water use efficiency is improved. The total water use control policy has limited negative impact on the regional economic growth with only a slightly lower growth rate of 13.38% compared with a growth rate of 14% by 2020 under a business as usual water use scenario. However, the total water use control policy has significant negative impacts on several sectors, especially agriculture and food processing. It is expected cropping systems will change through a replacement of water-intensive crops with water-efficient crops. Farmers’ incomes will decrease by 3.14%. In order to alleviate farmers’ income loss and deal with water use conflicts across different sectors and regions, the promotion of migration of surplus labor from agriculture to non-agricultural sectors and the improvement of water use efficiency in agriculture are needed.

  15. Totally Asymmetric Limit for Models of Heat Conduction

    Science.gov (United States)

    De Carlo, Leonardo; Gabrielli, Davide

    2017-08-01

    We consider one dimensional weakly asymmetric boundary driven models of heat conduction. In the cases of a constant diffusion coefficient and of a quadratic mobility we compute the quasi-potential that is a non local functional obtained by the solution of a variational problem. This is done using the dynamic variational approach of the macroscopic fluctuation theory (Bertini et al. in Rev Mod Phys 87:593, 2015). The case of a concave mobility corresponds essentially to the exclusion model that has been discussed in Bertini et al. (J Stat Mech L11001, 2010; Pure Appl Math 64(5):649-696, 2011; Commun Math Phys 289(1):311-334, 2009) and Enaud and Derrida (J Stat Phys 114:537-562, 2004). We consider here the convex case that includes for example the Kipnis-Marchioro-Presutti (KMP) model and its dual (KMPd) (Kipnis et al. in J Stat Phys 27:6574, 1982). This extends to the weakly asymmetric regime the computations in Bertini et al. (J Stat Phys 121(5/6):843-885, 2005). We consider then, both microscopically and macroscopically, the limit of large externalfields. Microscopically we discuss some possible totally asymmetric limits of the KMP model. In one case the totally asymmetric dynamics has a product invariant measure. Another possible limit dynamics has instead a non trivial invariant measure for which we give a duality representation. Macroscopically we show that the quasi-potentials of KMP and KMPd, which are non local for any value of the external field, become local in the limit. Moreover the dependence on one of the external reservoirs disappears. For models having strictly positive quadratic mobilities we obtain instead in the limit a non local functional having a structure similar to the one of the boundary driven asymmetric exclusion process.

  16. Order aggressiveness and order book dynamics

    DEFF Research Database (Denmark)

    Hall, Anthony D.; Hautsch, Nikolaus

    2006-01-01

    In this paper, we study the determinants of order aggressiveness and traders’ order submission strategy in an open limit order book market. Applying an order classification scheme, we model the most aggressive market orders, limit orders as well as cancellations on both sides of the market...... employing a six-dimensional autoregressive conditional intensity model. Using order book data from the Australian Stock Exchange, we find that market depth, the queued volume, the bid-ask spread, recent volatility, as well as recent changes in both the order flow and the price play an important role...... in explaining the determinants of order aggressiveness. Overall, our empirical results broadly confirm theoretical predictions on limit order book trading. However, we also find evidence for behavior that can be attributed to particular liquidity and volatility effects...

  17. 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....

  18. 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.

  19. Statistical modeling of total crash frequency at highway intersections

    Directory of Open Access Journals (Sweden)

    Arash M. Roshandeh

    2016-04-01

    Full Text Available Intersection-related crashes are associated with high proportion of accidents involving drivers, occupants, pedestrians, and cyclists. In general, the purpose of intersection safety analysis is to determine the impact of safety-related variables on pedestrians, cyclists and vehicles, so as to facilitate the design of effective and efficient countermeasure strategies to improve safety at intersections. This study investigates the effects of traffic, environmental, intersection geometric and pavement-related characteristics on total crash frequencies at intersections. A random-parameter Poisson model was used with crash data from 357 signalized intersections in Chicago from 2004 to 2010. The results indicate that out of the identified factors, evening peak period traffic volume, pavement condition, and unlighted intersections have the greatest effects on crash frequencies. Overall, the results seek to suggest that, in order to improve effective highway-related safety countermeasures at intersections, significant attention must be focused on ensuring that pavements are adequately maintained and intersections should be well lighted. It needs to be mentioned that, projects could be implemented at and around the study intersections during the study period (7 years, which could affect the crash frequency over the time. This is an important variable which could be a part of the future studies to investigate the impacts of safety-related works at intersections and their marginal effects on crash frequency at signalized intersections.

  20. 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...

  1. 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.

  2. 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.

  3. Sensitivity study of cloud/radiation interaction using a second order turbulence radiative-convective model

    International Nuclear Information System (INIS)

    Kao, C.Y.J.; Smith, W.S.

    1993-01-01

    A high resolution one-dimensional version of a second order turbulence convective/radiative model, developed at the Los Alamos National Laboratory, was used to conduct a sensitivity study of a stratocumulus cloud deck, based on data taken at San Nicolas Island during the intensive field observation marine stratocumulus phase of the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE IFO), conducted during July, 1987. Initial profiles for liquid water potential temperature, and total water mixing ratio were abstracted from the FIRE data. The dependence of the diurnal behavior in liquid water content, cloud top height, and cloud base height were examined for variations in subsidence rate, sea surface temperature, and initial inversion strength. The modelled diurnal variation in the column integrated liquid water agrees quite well with the observed data, for the case of low subsidence. The modelled diurnal behavior for the height of the cloud top and base show qualitative agreement with the FIRE data, although the overall height of the cloud layer is about 200 meters too high

  4. Should All Patients Be Included in Alternative Payment Models for Primary Total Hip Arthroplasty and Total Knee Arthroplasty?

    Science.gov (United States)

    Rozell, Joshua C; Courtney, Paul M; Dattilo, Jonathan R; Wu, Chia H; Lee, Gwo-Chin

    2016-09-01

    Alternative payment models in total joint replacement incentivize cost effective health care delivery and reward reductions in length of stay (LOS), complications, and readmissions. If not adjusted for patient comorbidities, they may encourage restrictive access to health care. We prospectively evaluated 802 consecutive primary total hip arthroplasty and total knee arthroplasty patients evaluating comorbidities associated with increased LOS and readmissions. During this 9-month period, 115 patients (14.3%) required hospitalization >3 days and 16 (1.99%) were readmitted within 90 days. Univariate analysis demonstrated that preoperative narcotic use, heart failure, stroke, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), and liver disease were more likely to require hospitalization >3 days. In multivariate analysis, CKD and COPD were independent risk factors for LOS >3 days. A Charlson comorbidity index >5 points was associated with increased LOS and readmissions. Patients with CKD, COPD, and Charlson comorbidity index >5 points should not be included in alternative payment model for THA and TKA. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. 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...

  6. 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

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

  13. 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)

  14. 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

  15. A Reduced Order, One Dimensional Model of Joint Response

    Energy Technology Data Exchange (ETDEWEB)

    DOHNER,JEFFREY L.

    2000-11-06

    As a joint is loaded, the tangent stiffness of the joint reduces due to slip at interfaces. This stiffness reduction continues until the direction of the applied load is reversed or the total interface slips. Total interface slippage in joints is called macro-slip. For joints not undergoing macro-slip, when load reversal occurs the tangent stiffness immediately rebounds to its maximum value. This occurs due to stiction effects at the interface. Thus, for periodic loads, a softening and rebound hardening cycle is produced which defines a hysteretic, energy absorbing trajectory. For many jointed sub-structures, this hysteretic trajectory can be approximated using simple polynomial representations. This allows for complex joint substructures to be represented using simple non-linear models. In this paper a simple one dimensional model is discussed.

  16. 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.

  17. 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.

  18. Effects of different components of Mao Dongqing's total flavonoids and total saponins on transient ischemic attack (TIA) model of rats.

    Science.gov (United States)

    Miao, Ming-San; Peng, Meng-Fan; Ma, Rui-Juan; Bai, Ming; Liu, Bao-Song

    2018-03-01

    Objective: To study the effects of the different components of the total flavonoids and total saponins from Mao Dongqing's active site on the rats of TIA model, determine the optimal reactive components ratio of Mao Dongqing on the rats of TIA. Methods: TIA rat model was induced by tail vein injection of tert butyl alcohol, the blank group was injected with the same amount of physiological saline, then behavioral score wasevaluated. Determination the level of glutamic acid in serum, the activity of Na+-K+-ATP enzyme, CA ++ -ATP enzyme and Mg ++ -ATP enzyme in Brain tissue, observe the changes of hippocampus in brain tissue, the comprehensive weight method was used to evaluate the efficacy of each component finally. Results: The contents of total flavonoids and total saponins in the active part of Mao Dongqing can significantly improve the pathological changes of brain tissue in rats, improve the activity of Na + -K + -ATP enzyme, Ca ++ -ATP enzyme and Mg ++ -ATP enzyme in the brain of rats, and reduce the level of glutamic acid in serum. The most significant of the contents was the ratio of 10:6. The different proportions of total flavonoids and total saponins in the active part of Mao Dongqing all has a better effect on the rats with TIA, and the ratio of 10:6 is the best active component for preventing and controlling TIA.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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…

  6. 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.

  7. 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

  8. 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.

  9. Order Batching in Warehouses by Minimizing Total Tardiness: A Hybrid Approach of Weighted Association Rule Mining and Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Amir Hossein Azadnia

    2013-01-01

    Full Text Available One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardiness which consists of four phases. First of all, weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach.

  10. 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.

  11. Image Restoration Based on the Hybrid Total-Variation-Type Model

    Directory of Open Access Journals (Sweden)

    Baoli Shi

    2012-01-01

    Full Text Available We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two L1-norm terms in the proposed model make it difficultly solved by using some classically numerical methods directly, we first employ the alternating direction method of multipliers (ADMM to solve a general form of the proposed model. Then, based on the ADMM and the Moreau-Yosida decomposition theory, a more efficient method called the proximal point method (PPM is proposed and the convergence of the proposed method is proved. Some numerical results demonstrate the viability and efficiency of the proposed model and methods.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 3D modeling of the total electric field induced by transcranial magnetic stimulation using the boundary element method

    Energy Technology Data Exchange (ETDEWEB)

    Salinas, F S; Lancaster, J L; Fox, P T [Research Imaging Center, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229 (United States)

    2009-06-21

    Transcranial magnetic stimulation (TMS) delivers highly localized brain stimulations via non-invasive externally applied magnetic fields. This non-invasive, painless technique provides researchers and clinicians with a unique tool capable of stimulating both the central and peripheral nervous systems. However, a complete analysis of the macroscopic electric fields produced by TMS has not yet been performed. In this paper, we addressed the importance of the secondary E-field created by surface charge accumulation during TMS using the boundary element method (BEM). 3D models were developed using simple head geometries in order to test the model and compare it with measured values. The effects of tissue geometry, size and conductivity were also investigated. Finally, a realistically shaped head model was used to assess the effect of multiple surfaces on the total E-field. Secondary E-fields have the greatest impact at areas in close proximity to each tissue layer. Throughout the head, the secondary E-field magnitudes typically range from 20% to 35% of the primary E-field's magnitude. The direction of the secondary E-field was generally in opposition to the primary E-field; however, for some locations, this was not the case (i.e. going from high to low conductivity tissues). These findings show that realistically shaped head geometries are important for accurate modeling of the total E-field.

  19. 3D modeling of the total electric field induced by transcranial magnetic stimulation using the boundary element method

    International Nuclear Information System (INIS)

    Salinas, F S; Lancaster, J L; Fox, P T

    2009-01-01

    Transcranial magnetic stimulation (TMS) delivers highly localized brain stimulations via non-invasive externally applied magnetic fields. This non-invasive, painless technique provides researchers and clinicians with a unique tool capable of stimulating both the central and peripheral nervous systems. However, a complete analysis of the macroscopic electric fields produced by TMS has not yet been performed. In this paper, we addressed the importance of the secondary E-field created by surface charge accumulation during TMS using the boundary element method (BEM). 3D models were developed using simple head geometries in order to test the model and compare it with measured values. The effects of tissue geometry, size and conductivity were also investigated. Finally, a realistically shaped head model was used to assess the effect of multiple surfaces on the total E-field. Secondary E-fields have the greatest impact at areas in close proximity to each tissue layer. Throughout the head, the secondary E-field magnitudes typically range from 20% to 35% of the primary E-field's magnitude. The direction of the secondary E-field was generally in opposition to the primary E-field; however, for some locations, this was not the case (i.e. going from high to low conductivity tissues). These findings show that realistically shaped head geometries are important for accurate modeling of the total E-field.

  20. 3D modeling of the total electric field induced by transcranial magnetic stimulation using the boundary element method

    Science.gov (United States)

    Salinas, F. S.; Lancaster, J. L.; Fox, P. T.

    2009-06-01

    Transcranial magnetic stimulation (TMS) delivers highly localized brain stimulations via non-invasive externally applied magnetic fields. This non-invasive, painless technique provides researchers and clinicians with a unique tool capable of stimulating both the central and peripheral nervous systems. However, a complete analysis of the macroscopic electric fields produced by TMS has not yet been performed. In this paper, we addressed the importance of the secondary E-field created by surface charge accumulation during TMS using the boundary element method (BEM). 3D models were developed using simple head geometries in order to test the model and compare it with measured values. The effects of tissue geometry, size and conductivity were also investigated. Finally, a realistically shaped head model was used to assess the effect of multiple surfaces on the total E-field. Secondary E-fields have the greatest impact at areas in close proximity to each tissue layer. Throughout the head, the secondary E-field magnitudes typically range from 20% to 35% of the primary E-field's magnitude. The direction of the secondary E-field was generally in opposition to the primary E-field; however, for some locations, this was not the case (i.e. going from high to low conductivity tissues). These findings show that realistically shaped head geometries are important for accurate modeling of the total E-field.

  1. The Total Quality Management Model Department of Personnel State of Colorado,

    Science.gov (United States)

    A panel of three members will present the Total Quality Management model recently designed for the Department of Personnel, State of Colorado. This model was selected to increase work quality and productivity of the Department and to exemplify Governor Romer’s commitment to quality work within state government.

  2. 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.

  3. 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

  4. Detection limit calculations for different total reflection techniques

    International Nuclear Information System (INIS)

    Sanchez, H.J.

    2000-01-01

    In this work, theoretical calculations of detection limits for different total-reflection techniques are presented.. Calculations include grazing incidence (TXRF) and gracing exit (GEXRF) conditions. These calculations are compared with detection limits obtained for conventional x-ray fluorescence (XRF). In order to compute detection limits the Shiraiwa and Fujino's model to calculate x-ray fluorescence intensities was used. This model made certain assumptions and approximations to achieve the calculations, specially in the case of the geometrical conditions of the sample, and the incident and takeoff beams. Nevertheless the calculated data of detection limits for conventional XRF and total-reflection XRF show a good agreement with previous results. The model proposed here allows to analyze the different sources of background and the influence of the excitation geometry, which contribute to the understanding of the physical processes involved in the XRF analysis by total reflection. Finally, a comparison between detection limits in total-reflection analysis at grazing incidence and at grazing exit is carried out. Here a good agreement with the theoretical predictions of the reversibility principle is found, showing that detection limits are similar for both techniques. (author)

  5. 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 ...

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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

  12. 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

  13. On the existence of positive periodic solutions for totally nonlinear neutral differential equations of the second-order with functional delay

    Directory of Open Access Journals (Sweden)

    Emmanuel K. Essel

    2014-01-01

    Full Text Available We prove that the totally nonlinear second-order neutral differential equation \\[\\frac{d^2}{dt^2}x(t+p(t\\frac{d}{dt}x(t+q(th(x(t\\] \\[=\\frac{d}{dt}c(t,x(t-\\tau(t+f(t,\\rho(x(t,g(x(t-\\tau(t\\] has positive periodic solutions by employing the Krasnoselskii-Burton hybrid fixed point theorem.

  14. 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.

  15. 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.

  16. Assessment of Ex-Vitro Anaerobic Digestion Kinetics of Crop Residues Through First Order Exponential Models: Effect of LAG Phase Period and Curve Factor

    Directory of Open Access Journals (Sweden)

    Abdul Razaque Sahito

    2013-04-01

    Full Text Available Kinetic studies of AD (Anaerobic Digestion process are useful to predict the performance of digesters and design appropriate digesters and also helpful in understanding inhibitory mechanisms of biodegradation. The aim of this study was to assess the anaerobic kinetics of crop residues digestion with buffalo dung. Seven crop residues namely, bagasse, banana plant waste, canola straw, cotton stalks, rice straw, sugarcane trash and wheat straw were selected from the field and were analyzed on MC (Moisture Contents, TS (Total Solids and VS (Volatile Solids with standard methods. In present study, three first order exponential models namely exponential model, exponential lag phase model and exponential curve factor model were used to assess the kinetics of the AD process of crop residues and the effect of lag phase and curve factor was analyzed based on statistical hypothesis testing and on information theory. Assessment of kinetics of the AD of crop residues and buffalo dung follows the first order kinetics. Out of the three models, the simple exponential model was the poorest model, while the first order exponential curve factor model is the best fit model. In addition to statistical hypothesis testing, the exponential curve factor model has least value of AIC (Akaike's Information Criterion and can generate methane production data more accurately. Furthermore, there is an inverse linear relationship between the lag phase period and the curve factor.

  17. Assessment of ex-vitro anaerobic digestion kinetics of crop residues through first order exponential models: effect of lag phase period and curve factor

    International Nuclear Information System (INIS)

    Sahito, A.R.; Brohi, K.M.

    2013-01-01

    Kinetic studies of AD (Anaerobic Digestion) process are useful to predict the performance of digesters and design appropriate digesters and also helpful in understanding inhibitory mechanisms of biodegradation. The aim of this study was to assess the anaerobic kinetics of crop residues digestion with buffalo dung. Seven crop residues namely, bagasse, banana plant waste, canola straw, cotton stalks, rice straw, sugarcane trash and wheat straw were selected from the field and were analyzed on MC (Moisture Contents), TS (Total Solids) and VS (Volatile Solids) with standard methods. In present study, three first order exponential models namely exponential model, exponential lag phase model and exponential curve factor model were used to assess the kinetics of the AD process of crop residues and the effect of lag phase and curve factor was analyzed based on statistical hypothesis testing and on information theory. Assessment of kinetics of the AD of crop residues and buffalo dung follows the first order kinetics. Out of the three models, the simple exponential model was the poorest model, while the first order exponential curve factor model is the best fit model. In addition to statistical hypothesis testing, the exponential curve factor model has least value of AIC (Akaike's Information Criterion) and can generate methane production data more accurately. Furthermore, there is an inverse linear relationship between the lag phase period and the curve factor. (author)

  18. 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).

  19. 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.

  20. Sensitivity analysis on the priority order of the radiological worker allocation model using goal programming

    International Nuclear Information System (INIS)

    Jung, Hae Yong; Lee, Kun Jai

    1998-01-01

    In nuclear power plant, it has been the important object to reduce the occupational radiation exposure (ORE). Recently, the optimization concept of management science has been studied to reduce the ORE in nuclear power plant. In optimization of the worker allocation, the collective dose, working time, individual dose, and total number of worker must be considered and their priority orders must be thought because the main constraint is necessary for determining the constraints variable of the radiological worker allocation problem. The ultimate object of this study is to look into the change of the optimal allocation of the radiological worker as priority order changes. In this study, the priority order is the characteristic of goal programming that is a kind of multi-objective linear programming. From a result of study using goal programming, the total number of worker and collective dose of worker have changed as the priority order has changed and the collective dose limit have played an important role in reducing the ORE

  1. 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.

  2. 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.

  3. 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%.

  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.

  5. 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.

  6. 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 ...

  7. 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.

  8. Exact extreme-value statistics at mixed-order transitions.

    Science.gov (United States)

    Bar, Amir; Majumdar, Satya N; Schehr, Grégory; Mukamel, David

    2016-05-01

    We study extreme-value statistics for spatially extended models exhibiting mixed-order phase transitions (MOT). These are phase transitions that exhibit features common to both first-order (discontinuity of the order parameter) and second-order (diverging correlation length) transitions. We consider here the truncated inverse distance squared Ising model, which is a prototypical model exhibiting MOT, and study analytically the extreme-value statistics of the domain lengths The lengths of the domains are identically distributed random variables except for the global constraint that their sum equals the total system size L. In addition, the number of such domains is also a fluctuating variable, and not fixed. In the paramagnetic phase, we show that the distribution of the largest domain length l_{max} converges, in the large L limit, to a Gumbel distribution. However, at the critical point (for a certain range of parameters) and in the ferromagnetic phase, we show that the fluctuations of l_{max} are governed by novel distributions, which we compute exactly. Our main analytical results are verified by numerical simulations.

  9. 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.

  10. 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.

  11. 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.

  12. 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)

  13. 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

  14. 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.

  15. 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.)

  16. 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.

  17. Total Quality Management, a New Culture Model of the Enterprise

    Directory of Open Access Journals (Sweden)

    Constantin Dumitrescu

    2006-10-01

    Full Text Available The paper brings bags of clarifications about concept definition and bases principles of TQM, presenting the critical factors during the implementation of those fundamentals. Also, it has been proposed a lot of models to present the Total Quality Management, being also presented its evolution.

  18. 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)

  19. 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...

  20. 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.

  1. 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.

  2. 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)

  3. Code development for eigenvalue total sensitivity analysis and total uncertainty analysis

    International Nuclear Information System (INIS)

    Wan, Chenghui; Cao, Liangzhi; Wu, Hongchun; Zu, Tiejun; Shen, Wei

    2015-01-01

    Highlights: • We develop a new code for total sensitivity and uncertainty analysis. • The implicit effects of cross sections can be considered. • The results of our code agree well with TSUNAMI-1D. • Detailed analysis for origins of implicit effects is performed. - Abstract: The uncertainties of multigroup cross sections notably impact eigenvalue of neutron-transport equation. We report on a total sensitivity analysis and total uncertainty analysis code named UNICORN that has been developed by applying the direct numerical perturbation method and statistical sampling method. In order to consider the contributions of various basic cross sections and the implicit effects which are indirect results of multigroup cross sections through resonance self-shielding calculation, an improved multigroup cross-section perturbation model is developed. The DRAGON 4.0 code, with application of WIMSD-4 format library, is used by UNICORN to carry out the resonance self-shielding and neutron-transport calculations. In addition, the bootstrap technique has been applied to the statistical sampling method in UNICORN to obtain much steadier and more reliable uncertainty results. The UNICORN code has been verified against TSUNAMI-1D by analyzing the case of TMI-1 pin-cell. The numerical results show that the total uncertainty of eigenvalue caused by cross sections can reach up to be about 0.72%. Therefore the contributions of the basic cross sections and their implicit effects are not negligible

  4. 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

  5. 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

  6. 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.

  7. 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

  8. Mixed Higher Order Variational Model for Image Recovery

    Directory of Open Access Journals (Sweden)

    Pengfei Liu

    2014-01-01

    Full Text Available A novel mixed higher order regularizer involving the first and second degree image derivatives is proposed in this paper. Using spectral decomposition, we reformulate the new regularizer as a weighted L1-L2 mixed norm of image derivatives. Due to the equivalent formulation of the proposed regularizer, an efficient fast projected gradient algorithm combined with monotone fast iterative shrinkage thresholding, called, FPG-MFISTA, is designed to solve the resulting variational image recovery problems under majorization-minimization framework. Finally, we demonstrate the effectiveness of the proposed regularization scheme by the experimental comparisons with total variation (TV scheme, nonlocal TV scheme, and current second degree methods. Specifically, the proposed approach achieves better results than related state-of-the-art methods in terms of peak signal to ratio (PSNR and restoration quality.

  9. 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…

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. The Total Cross Section at the LHC: Models and Experimental Consequences

    CERN Document Server

    Cudell, J R

    2010-01-01

    I review the predictions of the total cross section for many models, and point out that some of them lead to the conclusion that the standard experimental analysis may lead to systematic errors much larger than expected.

  15. The Role of Electron Transport and Trapping in MOS Total-Dose Modeling

    International Nuclear Information System (INIS)

    Fleetwood, D.M.; Winokur, P.S.; Riewe, L.C.; Flament, O.; Paillet, P.; Leray, J.L.

    1999-01-01

    Radiation-induced hole and electron transport and trapping are fundamental to MOS total-dose models. Here we separate the effects of electron-hole annihilation and electron trapping on the neutralization of radiation-induced charge during switched-bias irradiation for hard and soft oxides, via combined thermally stimulated current (TSC) and capacitance-voltage measurements. We also show that present total-dose models cannot account for the thermal stability of deeply trapped electrons near the Si/SiO 2 interface, or the inability of electrons in deep or shallow traps to contribute to TSC at positive bias following (1) room-temperature, (2) high-temperature, or (3) switched-bias irradiation. These results require revisions of modeling parameters and boundary conditions for hole and electron transport in SiO 2 . The nature of deep and shallow electron traps in the near-interfacial SiO 2 is discussed

  16. 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)

  17. MODEL SISTEM PREDIKSI ENSEMBLE TOTAL HUJAN BULANAN DENGAN NILAI PEMBOBOT (KASUS WILAYAH KABUPATEN INDRAMAYU

    Directory of Open Access Journals (Sweden)

    Yunus Subagyo Swarinoto

    2014-08-01

    Full Text Available Manajemen air menjadi sangat penting khususnya di wilayah yang rentan terhadap ketersediaan air. Mengingat hujan di atas normal dapat mengakibatkan banjir, sedangkan hujan di bawah normal mengakibatkan kekeringan. Untuk itu prediksi unsur iklim hujan ini menjadi penting. Model sistem prediksi ensemble berbasis model sistem prediksi tunggal ANFIS, Wavelet-ANFIS, Wavelet ARIMA, dan ARIMA total hujan bulanan telah disimulasikan di wilayah Kabupaten Indramayu. Model sistem prediksi ensemble total hujan bulanan ini dibentuk dengan teknik pembobotan. Nilai pembobot didasarkan pada nilai koefisien korelasi Pearson (r yang diperoleh selama masa pelatihan dengan series data 1991-2000. Hasil pengolahan data 2001-2009 menunjukkan kisaran nilai r didapat 0,45-0,83 untuk ANFIS; 0,20-0,53 untuk Wavelet-ANFIS; 0,50-0,95 untuk Wavelet-ARIMA; 0,14-0,66 untuk ARIMA; dan 0,58-0,94 untuk Ensemble. Secara spasial, luaran model sistem prediksi ensemble total hujan bulanan di wilayah Kabupaten Indramayu menunjukkan hasil yang konsisten lebih baik daripada luaran model sistem prediksi tunggal pembentuknya.   Water management is very important especially for region which is vulnarable to the water availability. Above normal rainfal condition causes flood, meanwhile below normal one triggers to the drought occurences. Coping with this situation, the rainfall prediction output is needed. The ensemble prediction system model (EPSM based on several single prediction system models (SPSMs such as ANFIS, Wavelet-ANFIS, Wavelet ARIMA, and ARIMA on monthly rainfall total, has been simulated within Indramayu district. The EPSM was developed and based on the weighting technique. This weighting is computed based on the value of Pearson correlation coefficient (r which has been gained during the training period of 1991-2000. Results of 2001-2009 model running show the value of r are 0,45-0,83 for ANFIS; 0,20-0,53 for Wavelet- ANFIS;  0,50-0,95 for Wavelet-ARIMA; 0,14-0,66 for

  18. 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.

  19. 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.

  20. 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.

  1. Preformed and regenerated phosphate in ocean general circulation models: can right total concentrations be wrong?

    Directory of Open Access Journals (Sweden)

    O. Duteil

    2012-05-01

    Full Text Available Phosphate distributions simulated by seven state-of-the-art biogeochemical ocean circulation models are evaluated against observations of global ocean nutrient distributions. The biogeochemical models exhibit different structural complexities, ranging from simple nutrient-restoring to multi-nutrient NPZD type models. We evaluate the simulations using the observed volume distribution of phosphate. The errors in these simulated volume class distributions are significantly larger when preformed phosphate (or regenerated phosphate rather than total phosphate is considered. Our analysis reveals that models can achieve similarly good fits to observed total phosphate distributions for a~very different partitioning into preformed and regenerated nutrient components. This has implications for the strength and potential climate sensitivity of the simulated biological carbon pump. We suggest complementing the use of total nutrient distributions for assessing model skill by an evaluation of the respective preformed and regenerated nutrient components.

  2. 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.

  3. 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...

  4. 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

  5. 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.

  6. 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.

  7. 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).

  8. Total cross sections of hadron interactions at high energies in low constituents number model

    International Nuclear Information System (INIS)

    Abramovskij, V.A.; Radchenko, N.V.

    2009-01-01

    We consider QCD hadrons interaction model in which gluons density is low in initial state wave function in rapidity space and real hadrons are produced from color strings decay. In this model behavior of total cross sections of pp, pp bar, π ± p, K ± p, γp, and γγ interactions is well described. The value of proton-proton total cross section at LHC energy is predicted

  9. 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.

  10. 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.

  11. 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.

  12. Total dose and dose rate models for bipolar transistors in circuit simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Campbell, Phillip Montgomery; Wix, Steven D.

    2013-05-01

    The objective of this work is to develop a model for total dose effects in bipolar junction transistors for use in circuit simulation. The components of the model are an electrical model of device performance that includes the effects of trapped charge on device behavior, and a model that calculates the trapped charge densities in a specific device structure as a function of radiation dose and dose rate. Simulations based on this model are found to agree well with measurements on a number of devices for which data are available.

  13. 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.

  14. 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

  15. Effect of the patient-to-patient communication model on dysphagia caused by total laryngectomy.

    Science.gov (United States)

    Tian, L; An, R; Zhang, J; Sun, Y; Zhao, R; Liu, M

    2017-03-01

    The study aimed to evaluate the effect of a patient-to-patient communication model on dysphagia in laryngeal cancer patients after total laryngectomy. Sixty-five patients who had undergone total laryngectomy were randomly divided into three groups: a routine communication group, a patient communication group (that received the patient-to-patient communication model) and a physician communication group. Questionnaires were used to compare quality of life and swallowing problems among all patient groups. The main factors causing dysphagia in total laryngectomy patients were related to fear and mental health. The patient communication group had improved visual analogue scale scores at one week after starting to eat. Quality of life in swallowing disorders questionnaire scores were significantly higher in the patient communication and physician communication groups than in the routine communication group. In addition, swallowing problems were much more severe in patients educated to high school level and above than in others. The patient-to-patient communication model can be used to resolve swallowing problems caused by psychological factors in total laryngectomy patients.

  16. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    International Nuclear Information System (INIS)

    Dong Suyalatu; Deng Yan-Bin; Huang Yong-Chang

    2017-01-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network . (paper)

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. Development and Validation of Perioperative Risk-Adjustment Models for Hip Fracture Repair, Total Hip Arthroplasty, and Total Knee Arthroplasty.

    Science.gov (United States)

    Schilling, Peter L; Bozic, Kevin J

    2016-01-06

    Comparing outcomes across providers requires risk-adjustment models that account for differences in case mix. The burden of data collection from the clinical record can make risk-adjusted outcomes difficult to measure. The purpose of this study was to develop risk-adjustment models for hip fracture repair (HFR), total hip arthroplasty (THA), and total knee arthroplasty (TKA) that weigh adequacy of risk adjustment against data-collection burden. We used data from the American College of Surgeons National Surgical Quality Improvement Program to create derivation cohorts for HFR (n = 7000), THA (n = 17,336), and TKA (n = 28,661). We developed logistic regression models for each procedure using age, sex, American Society of Anesthesiologists (ASA) physical status classification, comorbidities, laboratory values, and vital signs-based comorbidities as covariates, and validated the models with use of data from 2012. The derivation models' C-statistics for mortality were 80%, 81%, 75%, and 92% and for adverse events were 68%, 68%, 60%, and 70% for HFR, THA, TKA, and combined procedure cohorts. Age, sex, and ASA classification accounted for a large share of the explained variation in mortality (50%, 58%, 70%, and 67%) and adverse events (43%, 45%, 46%, and 68%). For THA and TKA, these three variables were nearly as predictive as models utilizing all covariates. HFR model discrimination improved with the addition of comorbidities and laboratory values; among the important covariates were functional status, low albumin, high creatinine, disseminated cancer, dyspnea, and body mass index. Model performance was similar in validation cohorts. Risk-adjustment models using data from health records demonstrated good discrimination and calibration for HFR, THA, and TKA. It is possible to provide adequate risk adjustment using only the most predictive variables commonly available within the clinical record. This finding helps to inform the trade-off between model performance and data

  4. Can a mathematical model predict an individual's trait-like response to both total and partial sleep loss?

    Science.gov (United States)

    Ramakrishnan, Sridhar; Lu, Wei; Laxminarayan, Srinivas; Wesensten, Nancy J; Rupp, Tracy L; Balkin, Thomas J; Reifman, Jaques

    2015-06-01

    Humans display a trait-like response to sleep loss. However, it is not known whether this trait-like response can be captured by a mathematical model from only one sleep-loss condition to facilitate neurobehavioural performance prediction of the same individual during a different sleep-loss condition. In this paper, we investigated the extent to which the recently developed unified mathematical model of performance (UMP) captured such trait-like features for different sleep-loss conditions. We used the UMP to develop two sets of individual-specific models for 15 healthy adults who underwent two different sleep-loss challenges (order counterbalanced; separated by 2-4 weeks): (i) 64 h of total sleep deprivation (TSD) and (ii) chronic sleep restriction (CSR) of 7 days of 3 h nightly time in bed. We then quantified the extent to which models developed using psychomotor vigilance task data under TSD predicted performance data under CSR, and vice versa. The results showed that the models customized to an individual under one sleep-loss condition accurately predicted performance of the same individual under the other condition, yielding, on average, up to 50% improvement over non-individualized, group-average model predictions. This finding supports the notion that the UMP captures an individual's trait-like response to different sleep-loss conditions. © 2014 European Sleep Research Society.

  5. Estimating total evaporation at the field scale using the SEBS model ...

    African Journals Online (AJOL)

    Estimating total evaporation at the field scale using the SEBS model and data infilling ... of two infilling techniques to create a daily satellite-derived ET time series. ... and produced R2 and RMSE values of 0.33 and 2.19 mm∙d-1, respectively, ...

  6. To the calculation of differential and total cross sections of γπ interactions

    International Nuclear Information System (INIS)

    Duplij, S.A.

    1980-01-01

    The differential and total cross sections of different charge channels of the γπ→ππ process are calculated. At the threshold energies the vector dominance model predicts twice as large values of the total cross sections than the current algebra. In resonance the total cross section of photoproduction on a neutral pion is 10-50 μb, on a charged pion - 5-10μb, at near-threshold energies (Esub(γ)=300-600 MeV) both cross sections are of the 20-40 nb order. For the γπ→ππ process the differential cross sections according to the invariant mass of two pions are obtained for different charge channels. At the threshold energies the total cross sections of the γπ→ππ process is of the 0.1-1 nb order

  7. 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

  8. 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

  9. Estimation of Total Nitrogen and Phosphorus in New England Streams Using Spatially Referenced Regression Models

    Science.gov (United States)

    Moore, Richard Bridge; Johnston, Craig M.; Robinson, Keith W.; Deacon, Jeffrey R.

    2004-01-01

    The U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA) and the New England Interstate Water Pollution Control Commission (NEIWPCC), has developed a water-quality model, called SPARROW (Spatially Referenced Regressions on Watershed Attributes), to assist in regional total maximum daily load (TMDL) and nutrient-criteria activities in New England. SPARROW is a spatially detailed, statistical model that uses regression equations to relate total nitrogen and phosphorus (nutrient) stream loads to nutrient sources and watershed characteristics. The statistical relations in these equations are then used to predict nutrient loads in unmonitored streams. The New England SPARROW models are built using a hydrologic network of 42,000 stream reaches and associated watersheds. Watershed boundaries are defined for each stream reach in the network through the use of a digital elevation model and existing digitized watershed divides. Nutrient source data is from permitted wastewater discharge data from USEPA's Permit Compliance System (PCS), various land-use sources, and atmospheric deposition. Physical watershed characteristics include drainage area, land use, streamflow, time-of-travel, stream density, percent wetlands, slope of the land surface, and soil permeability. The New England SPARROW models for total nitrogen and total phosphorus have R-squared values of 0.95 and 0.94, with mean square errors of 0.16 and 0.23, respectively. Variables that were statistically significant in the total nitrogen model include permitted municipal-wastewater discharges, atmospheric deposition, agricultural area, and developed land area. Total nitrogen stream-loss rates were significant only in streams with average annual flows less than or equal to 2.83 cubic meters per second. In streams larger than this, there is nondetectable in-stream loss of annual total nitrogen in New England. Variables that were statistically significant in the total

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. Pseudo Boolean Programming for Partially Ordered Genomes

    Science.gov (United States)

    Angibaud, Sébastien; Fertin, Guillaume; Thévenin, Annelyse; Vialette, Stéphane

    Comparing genomes of different species is a crucial problem in comparative genomics. Different measures have been proposed to compare two genomes: number of common intervals, number of adjacencies, number of reversals, etc. These measures are classically used between two totally ordered genomes. However, genetic mapping techniques often give rise to different maps with some unordered genes. Starting from a partial order between genes of a genome, one method to find a total order consists in optimizing a given measure between a linear extension of this partial order and a given total order of a close and well-known genome. However, for most common measures, the problem turns out to be NP-hard. In this paper, we propose a (0,1)-linear programming approach to compute a linear extension of one genome that maximizes the number of common intervals (resp. the number of adjacencies) between this linear extension and a given total order. Next, we propose an algorithm to find linear extensions of two partial orders that maximize the number of adjacencies.

  17. 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.

  18. 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)

  19. Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

    Science.gov (United States)

    Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

    2009-07-01

    Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

  20. 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

  1. 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.

  2. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    Science.gov (United States)

    Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

    2017-10-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

  3. Analysis of Challenges for Management Education in India Using Total Interpretive Structural Modelling

    Science.gov (United States)

    Mahajan, Ritika; Agrawal, Rajat; Sharma, Vinay; Nangia, Vinay

    2016-01-01

    Purpose: The purpose of this paper is to identify challenges for management education in India and explain their nature, significance and interrelations using total interpretive structural modelling (TISM), an innovative version of Warfield's interpretive structural modelling (ISM). Design/methodology/approach: The challenges have been drawn from…

  4. 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.

  5. 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.

  6. 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.

  7. How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

    Science.gov (United States)

    Xu, Kuan-Man

    2015-01-01

    Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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...

  13. 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

  14. 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)

  15. 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

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Statistical model of hadrons multiple production in space of total angular momentum and isotopic spin

    International Nuclear Information System (INIS)

    Gridneva, S.A.; Rus'kin, V.I.

    1980-01-01

    Basic features of the statistical model of multiple hadron production based on microcanonical distribution and taking into account the laws of conservation of total angular momentum, isotopic spin, p-, G-, C-eveness and Bose-Einstein statistics requirements are given. The model predictions are compared with experimental data on anti NN annihilation at rest and e + e - annihilation in hadrons at annihilation total energy from 2 to 3 GeV [ru

  1. 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.

  2. 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

  3. The Role of Electron Transport and Trapping in MOS Total-Dose Modeling

    International Nuclear Information System (INIS)

    Flament, O.; Fleetwood, D.M.; Leray, J.L.; Paillet, P.; Riewe, L.C.; Winokur, P.S.

    1999-01-01

    Deep and shallow electron traps form in irradiated thermal SiO 2 as a natural response to hole transport and trapping. The density and stability of these defects are discussed, as are their implications for total-dose modeling

  4. First order phase transition of a long polymer chain

    International Nuclear Information System (INIS)

    Aristoff, David; Radin, Charles

    2011-01-01

    We consider a model consisting of a self-avoiding polygon occupying a variable density of the sites of a square lattice. A fixed energy is associated with each 90 0 bend of the polygon. We use a grand canonical ensemble, introducing parameters μ and β to control average density and average (total) energy of the polygon, and show by Monte Carlo simulation that the model has a first order, nematic phase transition across a curve in the β-μ plane.

  5. Application of total care time and payment per unit time model for physician reimbursement for common general surgery operations.

    Science.gov (United States)

    Chatterjee, Abhishek; Holubar, Stefan D; Figy, Sean; Chen, Lilian; Montagne, Shirley A; Rosen, Joseph M; Desimone, Joseph P

    2012-06-01

    The relative value unit system relies on subjective measures of physician input in the care of patients. A payment per unit time model incorporates surgeon reimbursement to the total care time spent in the operating room, postoperative in-house, and clinic time to define payment per unit time. We aimed to compare common general surgery operations by using the total care time and payment per unit time method in order to demonstrate a more objective measurement for physician reimbursement. Average total physician payment per case was obtained for 5 outpatient operations and 4 inpatient operations in general surgery. Total care time was defined as the sum of operative time, 30 minutes per hospital day, and 30 minutes per office visit for each operation. Payment per unit time was calculated by dividing the physician reimbursement per case by the total care time. Total care time, physician payment per case, and payment per unit time for each type of operation demonstrated that an average payment per time spent for inpatient operations was $455.73 and slightly more at $467.51 for outpatient operations. Partial colectomy with primary anastomosis had the longest total care time (8.98 hours) and the least payment per unit time ($188.52). Laparoscopic gastric bypass had the highest payment per time ($707.30). The total care time and payment per unit time method can be used as an adjunct to compare reimbursement among different operations on an institutional level as well as on a national level. Although many operations have similar payment trends based on time spent by the surgeon, payment differences using this methodology are seen and may be in need of further review. Copyright © 2012 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  6. 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.

  7. Microgrid Stability Controller Based on Adaptive Robust Total SMC

    OpenAIRE

    Su, Xiaoling; Han, Minxiao; Guerrero, Josep M.; Sun, Hai

    2015-01-01

    This paper presents a microgrid stability controller (MSC) in order to provide existing distributed generation units (DGs) the additional functionality of working in islanding mode without changing their control strategies in grid-connected mode and to enhance the stability of the microgrid. Microgrid operating characteristics and mathematical models of the MSC indicate that the system is inherently nonlinear and time-variable. Therefore, this paper proposes an adaptive robust total sliding...

  8. Deformation analysis with Total Least Squares

    Directory of Open Access Journals (Sweden)

    M. Acar

    2006-01-01

    Full Text Available Deformation analysis is one of the main research fields in geodesy. Deformation analysis process comprises measurement and analysis phases. Measurements can be collected using several techniques. The output of the evaluation of the measurements is mainly point positions. In the deformation analysis phase, the coordinate changes in the point positions are investigated. Several models or approaches can be employed for the analysis. One approach is based on a Helmert or similarity coordinate transformation where the displacements and the respective covariance matrix are transformed into a unique datum. Traditionally a Least Squares (LS technique is used for the transformation procedure. Another approach that could be introduced as an alternative methodology is the Total Least Squares (TLS that is considerably a new approach in geodetic applications. In this study, in order to determine point displacements, 3-D coordinate transformations based on the Helmert transformation model were carried out individually by the Least Squares (LS and the Total Least Squares (TLS, respectively. The data used in this study was collected by GPS technique in a landslide area located nearby Istanbul. The results obtained from these two approaches have been compared.

  9. The Effect of Units Lost Due to Deterioration in Fuzzy Economic Order Quantity (FEOQ) Model

    OpenAIRE

    M. Pattnaik

    2013-01-01

    For several decades, the Economic Order Quantity (EOQ) model and its variations have received much attention from researchers. Recently, there has been an investigation into an EOQ model incorporating effect of units lost due to deterioration in infinite planning horizon with crisp decision environment. Accounting for holding and ordering cost, as has traditionally been the case of modeling inventory systems in fuzzy environment are investigated which are not precisely known and defined on a ...

  10. Higher-Order Extended Lagrangian Born-Oppenheimer Molecular Dynamics for Classical Polarizable Models.

    Science.gov (United States)

    Albaugh, Alex; Head-Gordon, Teresa; Niklasson, Anders M N

    2018-02-13

    Generalized extended Lagrangian Born-Oppenheimer molecular dynamics (XLBOMD) methods provide a framework for fast iteration-free simulations of models that normally require expensive electronic ground state optimizations prior to the force evaluations at every time step. XLBOMD uses dynamically driven auxiliary degrees of freedom that fluctuate about a variationally optimized ground state of an approximate "shadow" potential which approximates the true reference potential. While the requirements for such shadow potentials are well understood, constructing such potentials in practice has previously been ad hoc, and in this work, we present a systematic development of XLBOMD shadow potentials that match the reference potential to any order. We also introduce a framework for combining friction-like dissipation for the auxiliary degrees of freedom with general-order integration, a combination that was not previously possible. These developments are demonstrated with a simple fluctuating charge model and point induced dipole polarization models.

  11. Two-Stage orders sequencing system for mixed-model assembly

    Science.gov (United States)

    Zemczak, M.; Skolud, B.; Krenczyk, D.

    2015-11-01

    In the paper, the authors focus on the NP-hard problem of orders sequencing, formulated similarly to Car Sequencing Problem (CSP). The object of the research is the assembly line in an automotive industry company, on which few different models of products, each in a certain number of versions, are assembled on the shared resources, set in a line. Such production type is usually determined as a mixed-model production, and arose from the necessity of manufacturing customized products on the basis of very specific orders from single clients. The producers are nowadays obliged to provide each client the possibility to determine a huge amount of the features of the product they are willing to buy, as the competition in the automotive market is large. Due to the previously mentioned nature of the problem (NP-hard), in the given time period only satisfactory solutions are sought, as the optimal solution method has not yet been found. Most of the researchers that implemented inaccurate methods (e.g. evolutionary algorithms) to solving sequencing problems dropped the research after testing phase, as they were not able to obtain reproducible results, and met problems while determining the quality of the received solutions. Therefore a new approach to solving the problem, presented in this paper as a sequencing system is being developed. The sequencing system consists of a set of determined rules, implemented into computer environment. The system itself works in two stages. First of them is connected with the determination of a place in the storage buffer to which certain production orders should be sent. In the second stage of functioning, precise sets of sequences are determined and evaluated for certain parts of the storage buffer under certain criteria.

  12. An efficient flexible-order model for 3D nonlinear water waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole

    2009-01-01

    The flexible-order, finite difference based fully nonlinear potential flow model described in [H.B. Bingham, H. Zhang, On the accuracy of finite difference solutions for nonlinear water waves, J. Eng. Math. 58 (2007) 211-228] is extended to three dimensions (3D). In order to obtain an optimal......, robustness and energy conservation are presented together with demonstrations of grid independent iteration count and optimal scaling of the solution effort. Calculations are made for 3D nonlinear wave problems for steep nonlinear waves and a shoaling problem which show good agreement with experimental...

  13. A New Model of the Fractional Order Dynamics of the Planetary Gears

    Directory of Open Access Journals (Sweden)

    Vera Nikolic-Stanojevic

    2013-01-01

    Full Text Available A theoretical model of planetary gears dynamics is presented. Planetary gears are parametrically excited by the time-varying mesh stiffness that fluctuates as the number of gear tooth pairs in contact changes during gear rotation. In the paper, it has been indicated that even the small disturbance in design realizations of this gear cause nonlinear properties of dynamics which are the source of vibrations and noise in the gear transmission. Dynamic model of the planetary gears with four degrees of freedom is used. Applying the basic principles of analytical mechanics and taking the initial and boundary conditions into consideration, it is possible to obtain the system of equations representing physical meshing process between the two or more gears. This investigation was focused to a new model of the fractional order dynamics of the planetary gear. For this model analytical expressions for the corresponding fractional order modes like one frequency eigen vibrational modes are obtained. For one planetary gear, eigen fractional modes are obtained, and a visualization is presented. By using MathCAD the solution is obtained.

  14. An updated fracture-flow model for total-system performance assessment of Yucca Mountain

    International Nuclear Information System (INIS)

    Gauthier, J.H.

    1994-01-01

    Improvements have been made to the fracture-flow model being used in the total-system performance assessment of a potential high-level radioactive waste repository at Yucca Mountain, Nevada. The ''weeps model'' now includes (1) weeps of varied sizes, (2) flow-pattern fluctuations caused by climate change, and (3) flow-pattern perturbations caused by repository heat generation. Comparison with the original weeps model indicates that allowing weeps of varied sizes substantially reduces the number of weeps and the number of containers contacted by weeps. However, flow-pattern perturbations caused by either climate change or repository heat generation greatly increases the number of containers contacted by weeps. In preliminary total-system calculations, using a phenomenological container-failure and radionuclide-release model, the weeps model predicts that radionuclide releases from a high-level radioactive waste repository at Yucca Mountain will be below the EPA standard specified in 40 CFR 191, but that the maximum radiation dose to an individual could be significant. Specific data from the site are required to determine the validity of the weep-flow mechanism and to better determine the parameters to which the dose calculation is sensitive

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

    OpenAIRE

    Monalisha Pattnaik

    2014-01-01

    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 ...

  16. Total pollution effect of urban surface runoff.

    Science.gov (United States)

    Luo, Hongbing; Luo, Lin; Huang, Gu; Liu, Ping; Li, Jingxian; Hu, Sheng; Wang, Fuxiang; Xu, Rui; Huang, Xiaoxue

    2009-01-01

    For pollution research with regard to urban surface runoff, most sampling strategies to date have focused on differences in land usage. With single land-use sampling, total surface runoff pollution effect cannot be evaluated unless every land usage spot is monitored. Through a new sampling strategy known as mixed stormwater sampling for a street community at discharge outlet adjacent to river, this study assessed the total urban surface runoff pollution effect caused by a variety of land uses and the pollutants washed off from the rain pipe system in the Futian River watershed in Shenzhen City of China. The water quality monitoring indices were COD (chemical oxygen demand), TSS (total suspend solid), TP (total phosphorus), TN (total nitrogen) and BOD (biochemical oxygen demand). The sums of total pollution loads discharged into the river for the four indices of COD, TSS, TN, and TP over all seven rainfall events were very different. The mathematical model for simulating total pollution loads was established from discharge outlet mixed stormwater sampling of total pollution loads on the basis of four parameters: rainfall intensity, total land area, impervious land area, and pervious land area. In order to treat surface runoff pollution, the values of MFF30 (mass first flush ratio) and FF30 (first 30% of runoff volume) can be considered as split-flow control criteria to obtain more effective and economical design of structural BMPs (best management practices) facilities.

  17. Absolute total cross sections for noble gas systems

    International Nuclear Information System (INIS)

    Kam, P. van der.

    1981-01-01

    This thesis deals with experiments on the elastic scattering of Ar, Kr and Xe, using the molecular beam technique. The aim of this work was the measurement of the absolute value of the total cross section and the behaviour of the total cross section, Q, as function of the relative velocity g of the scattering partners. The author gives an extensive analysis of the glory structure in the total cross section and parametrizes the experimental results using a semiclassical model function. This allows a detailed comparison of the phase and amplitude of the predicted and measured glory undulations. He indicates how the depth and position of the potential well should be changed in order to come to an optimum description of the glory structure. With this model function he has also been able to separate the glory and attractive contribution to Q, and using the results from the extrapolation measurements he has obtained absolute values for Qsub(a). From these absolute values he has calculated the parameter C 6 that determines the strength of the attractive region of the potential. In two of the four investigated gas combinations the obtained values lie outside the theoretical bounds. (Auth.)

  18. Theory and Low-Order Modeling of Unsteady Airfoil Flows

    Science.gov (United States)

    Ramesh, Kiran

    Unsteady flow phenomena are prevalent in a wide range of problems in nature and engineering. These include, but are not limited to, aerodynamics of insect flight, dynamic stall in rotorcraft and wind turbines, leading-edge vortices in delta wings, micro-air vehicle (MAV) design, gust handling and flow control. The most significant characteristics of unsteady flows are rapid changes in the circulation of the airfoil, apparent-mass effects, flow separation and the leading-edge vortex (LEV) phenomenon. Although experimental techniques and computational fluid dynamics (CFD) methods have enabled the detailed study of unsteady flows and their underlying features, a reliable and inexpensive loworder method for fast prediction and for use in control and design is still required. In this research, a low-order methodology based on physical principles rather than empirical fitting is proposed. The objective of such an approach is to enable insights into unsteady phenomena while developing approaches to model them. The basis of the low-order model developed here is unsteady thin-airfoil theory. A time-stepping approach is used to solve for the vorticity on an airfoil camberline, allowing for large amplitudes and nonplanar wakes. On comparing lift coefficients from this method against data from CFD and experiments for some unsteady test cases, it is seen that the method predicts well so long as LEV formation does not occur and flow over the airfoil is attached. The formation of leading-edge vortices (LEVs) in unsteady flows is initiated by flow separation and the formation of a shear layer at the airfoil's leading edge. This phenomenon has been observed to have both detrimental (dynamic stall in helicopters) and beneficial (high-lift flight in insects) effects. To predict the formation of LEVs in unsteady flows, a Leading Edge Suction Parameter (LESP) is proposed. This parameter is calculated from inviscid theory and is a measure of the suction at the airfoil's leading edge. It

  19. Efficient response spectrum analysis of a reactor using Model Order Reduction

    International Nuclear Information System (INIS)

    Oh, Jin Ho; Choi, Jin Bok; Ryu, Jeong Soo

    2012-01-01

    A response spectrum analysis (RSA) has been widely used to evaluate the structural integrity of various structural components in the nuclear industry. However, solving the large and complex structural systems numerically using the RSA requires a considerable amount of computational resources and time. To overcome this problem, this paper proposes the RSA based on the model order reduction (MOR) technique achieved by applying a projection from a higher order to a lower order space using Krylov subspaces generated by the Arnoldi algorithm. The dynamic characteristics of the final reduced system are almost identical with those of the full system by matching the moments of the reduced system with those of the full system up to the required nth order. It is remarkably efficient in terms of computation time and does not require a global system. Numerical examples demonstrate that the proposed method saves computational costs effectively, and provides a reduced system framework that predicts the accurate responses of a global system

  20. Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.

    Science.gov (United States)

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

    2017-09-01

    Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Teaching Higher Order Thinking in the Introductory MIS Course: A Model-Directed Approach

    Science.gov (United States)

    Wang, Shouhong; Wang, Hai

    2011-01-01

    One vision of education evolution is to change the modes of thinking of students. Critical thinking, design thinking, and system thinking are higher order thinking paradigms that are specifically pertinent to business education. A model-directed approach to teaching and learning higher order thinking is proposed. An example of application of the…

  2. Stable reduced-order models of generalized dynamical systems using coordinate-transformed Arnoldi algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Silveira, L.M.; Kamon, M.; Elfadel, I.; White, J. [Massachusetts Inst. of Technology, Cambridge, MA (United States)

    1996-12-31

    Model order reduction based on Krylov subspace iterative methods has recently emerged as a major tool for compressing the number of states in linear models used for simulating very large physical systems (VLSI circuits, electromagnetic interactions). There are currently two main methods for accomplishing such a compression: one is based on the nonsymmetric look-ahead Lanczos algorithm that gives a numerically stable procedure for finding Pade approximations, while the other is based on a less well characterized Arnoldi algorithm. In this paper, we show that for certain classes of generalized state-space systems, the reduced-order models produced by a coordinate-transformed Arnoldi algorithm inherit the stability of the original system. Complete Proofs of our results will be given in the final paper.

  3. Shipment Consolidation Policy under Uncertainty of Customer Order for Sustainable Supply Chain Management

    Directory of Open Access Journals (Sweden)

    Kyunghoon Kang

    2017-09-01

    Full Text Available With increasing concern over the environment, shipment consolidation has become one of a main initiative to reduce CO2 emissions and transportation cost among the logistics service providers. Increased delivery time caused by shipment consolidation may lead to customer’s order cancellation. Thus, order cancellation should be considered as a factor in order uncertainty to determine the optimal shipment consolidation policy. We develop mathematical models for quantity-based and time-based policies and obtain optimality properties for the models. Efficient algorithms using optimal properties are provided to compute the optimal parameters for ordering and shipment decisions. To compare the performances of the quantity-based policy with the time-based policy, extensive numerical experiments are conducted, and the total cost is compared.

  4. An Isotonic Partial Credit Model for Ordering Subjects on the Basis of Their Sum Scores

    Science.gov (United States)

    Ligtvoet, Rudy

    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. However, the PCM is very restrictive with respect…

  5. Measurement of characteristic to total spectrum ratio of tungsten X-ray spectra for the validation of the modified Tbc model

    International Nuclear Information System (INIS)

    Lopez G, A. H.; Costa, P. R.; Tomal, A.

    2014-08-01

    Primary X-ray spectra were measured in the range of 80 to 150 kV in order to validate a computer program based on a semiempirical model for X-ray spectra evaluation(tbc and mod). The ratio between the characteristic lines and total spectrum was considered for comparing the simulated results and experimental data. The raw spectra measured by the Cd Te detector were corrected by the detector efficiency, Compton effects and characteristic Cd and Te X-rays escape peaks, using a software specifically developed. The software Origin 8.5.1 was used to calculate the spectra and characteristic peaks areas. The obtained result shows that the experimental spectra have higher effective energy than the simulated spectra computed with tbc and mod software. The behavior of the ratio between the characteristic lines and total spectrum for simulated data presents discrepancy with the experimental result. Computed results are in good agreement with theoretical data published by Green, for spectra obtained with 3.04 mm of additional aluminum filtration. The difference of characteristic to total spectrum ratio between experimental and simulated data increases with the tube voltage. (Author)

  6. Measurement of characteristic to total spectrum ratio of tungsten X-ray spectra for the validation of the modified Tbc model

    Energy Technology Data Exchange (ETDEWEB)

    Lopez G, A. H.; Costa, P. R. [University of Sao Paulo, Institute of Physics, Laboratory of Radiation Dosimetry and Medical Physics, Matao Street, alley R, 187, 66318 Sao Paulo (Brazil); Tomal, A., E-mail: ahlopezg@usp.br [Universidade Federal de Goias, Physics Institute, Campus Samambaia, 131 Goiania, Goias (Brazil)

    2014-08-15

    Primary X-ray spectra were measured in the range of 80 to 150 kV in order to validate a computer program based on a semiempirical model for X-ray spectra evaluation(tbc and mod). The ratio between the characteristic lines and total spectrum was considered for comparing the simulated results and experimental data. The raw spectra measured by the Cd Te detector were corrected by the detector efficiency, Compton effects and characteristic Cd and Te X-rays escape peaks, using a software specifically developed. The software Origin 8.5.1 was used to calculate the spectra and characteristic peaks areas. The obtained result shows that the experimental spectra have higher effective energy than the simulated spectra computed with tbc and mod software. The behavior of the ratio between the characteristic lines and total spectrum for simulated data presents discrepancy with the experimental result. Computed results are in good agreement with theoretical data published by Green, for spectra obtained with 3.04 mm of additional aluminum filtration. The difference of characteristic to total spectrum ratio between experimental and simulated data increases with the tube voltage. (Author)

  7. Twisted quantum double model of topological order with boundaries

    Science.gov (United States)

    Bullivant, Alex; Hu, Yuting; Wan, Yidun

    2017-10-01

    We generalize the twisted quantum double model of topological orders in two dimensions to the case with boundaries by systematically constructing the boundary Hamiltonians. Given the bulk Hamiltonian defined by a gauge group G and a 3-cocycle in the third cohomology group of G over U (1 ) , a boundary Hamiltonian can be defined by a subgroup K of G and a 2-cochain in the second cochain group of K over U (1 ) . The consistency between the bulk and boundary Hamiltonians is dictated by what we call the Frobenius condition that constrains the 2-cochain given the 3-cocyle. We offer a closed-form formula computing the ground-state degeneracy of the model on a cylinder in terms of the input data only, which can be naturally generalized to surfaces with more boundaries. We also explicitly write down the ground-state wave function of the model on a disk also in terms of the input data only.

  8. Power law-based local search in spider monkey optimisation for lower order system modelling

    Science.gov (United States)

    Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala

    2017-01-01

    The nature-inspired algorithms (NIAs) have shown efficiency to solve many complex real-world optimisation problems. The efficiency of NIAs is measured by their ability to find adequate results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This paper presents a solution for lower order system modelling using spider monkey optimisation (SMO) algorithm to obtain a better approximation for lower order systems and reflects almost original higher order system's characteristics. Further, a local search strategy, namely, power law-based local search is incorporated with SMO. The proposed strategy is named as power law-based local search in SMO (PLSMO). The efficiency, accuracy and reliability of the proposed algorithm is tested over 20 well-known benchmark functions. Then, the PLSMO algorithm is applied to solve the lower order system modelling problem.

  9. Uncertainty Model for Total Solar Irradiance Estimation on Australian Rooftops

    Science.gov (United States)

    Al-Saadi, Hassan; Zivanovic, Rastko; Al-Sarawi, Said

    2017-11-01

    The installations of solar panels on Australian rooftops have been in rise for the last few years, especially in the urban areas. This motivates academic researchers, distribution network operators and engineers to accurately address the level of uncertainty resulting from grid-connected solar panels. The main source of uncertainty is the intermittent nature of radiation, therefore, this paper presents a new model to estimate the total radiation incident on a tilted solar panel. Where a probability distribution factorizes clearness index, the model is driven upon clearness index with special attention being paid for Australia with the utilization of best-fit-correlation for diffuse fraction. The assessment of the model validity is achieved with the adoption of four goodness-of-fit techniques. In addition, the Quasi Monte Carlo and sparse grid methods are used as sampling and uncertainty computation tools, respectively. High resolution data resolution of solar irradiations for Adelaide city were used for this assessment, with an outcome indicating a satisfactory agreement between actual data variation and model.

  10. Orderly Discharging Strategy for Electric Vehicles at Workplace Based on Time-of-Use Price

    Directory of Open Access Journals (Sweden)

    Lixing Chen

    2016-01-01

    Full Text Available According to the parking features of electric vehicles (EVs and load of production unit, a power supply system including EVs charging station was established, and an orderly discharging strategy for EVs was proposed as well to reduce the basic tariff of producer and improve the total benefits of EV discharging. Based on the target of maximizing the annual income of producer, considering the total benefits of EV discharging, the electric vehicle aggregator (EVA and time-of-use (TOU price were introduced to establish the optimization scheduling model of EVs discharging. Furthermore, an improved artificial fish swarm algorithm (IAFSA combined with the penalty function methods was applied to solve the model. It can be shown from the simulation results that the optimal solution obtained by IAFSA is regarded as the orderly discharging strategy for EVs, which could reduce the basic tariff of producer and improve the total benefits of EV discharging.

  11. Connection between weighted LPC and higher-order statistics for AR model estimation

    NARCIS (Netherlands)

    Kamp, Y.; Ma, C.

    1993-01-01

    This paper establishes the relationship between a weighted linear prediction method used for robust analysis of voiced speech and the autoregressive modelling based on higher-order statistics, known as cumulants

  12. A novel approach to quantifying the sensitivity of current and future cosmological datasets to the neutrino mass ordering through Bayesian hierarchical modeling

    Science.gov (United States)

    Gerbino, Martina; Lattanzi, Massimiliano; Mena, Olga; Freese, Katherine

    2017-12-01

    We present a novel approach to derive constraints on neutrino masses, as well as on other cosmological parameters, from cosmological data, while taking into account our ignorance of the neutrino mass ordering. We derive constraints from a combination of current as well as future cosmological datasets on the total neutrino mass Mν and on the mass fractions fν,i =mi /Mν (where the index i = 1 , 2 , 3 indicates the three mass eigenstates) carried by each of the mass eigenstates mi, after marginalizing over the (unknown) neutrino mass ordering, either normal ordering (NH) or inverted ordering (IH). The bounds on all the cosmological parameters, including those on the total neutrino mass, take therefore into account the uncertainty related to our ignorance of the mass hierarchy that is actually realized in nature. This novel approach is carried out in the framework of Bayesian analysis of a typical hierarchical problem, where the distribution of the parameters of the model depends on further parameters, the hyperparameters. In this context, the choice of the neutrino mass ordering is modeled via the discrete hyperparameterhtype, which we introduce in the usual Markov chain analysis. The preference from cosmological data for either the NH or the IH scenarios is then simply encoded in the posterior distribution of the hyperparameter itself. Current cosmic microwave background (CMB) measurements assign equal odds to the two hierarchies, and are thus unable to distinguish between them. However, after the addition of baryon acoustic oscillation (BAO) measurements, a weak preference for the normal hierarchical scenario appears, with odds of 4 : 3 from Planck temperature and large-scale polarization in combination with BAO (3 : 2 if small-scale polarization is also included). Concerning next-generation cosmological experiments, forecasts suggest that the combination of upcoming CMB (COrE) and BAO surveys (DESI) may determine the neutrino mass hierarchy at a high statistical

  13. Improving actuation efficiency through variable recruitment hydraulic McKibben muscles: modeling, orderly recruitment control, and experiments.

    Science.gov (United States)

    Meller, Michael; Chipka, Jordan; Volkov, Alexander; Bryant, Matthew; Garcia, Ephrahim

    2016-11-03

    Hydraulic control systems have become increasingly popular as the means of actuation for human-scale legged robots and assistive devices. One of the biggest limitations to these systems is their run time untethered from a power source. One way to increase endurance is by improving actuation efficiency. We investigate reducing servovalve throttling losses by using a selective recruitment artificial muscle bundle comprised of three motor units. Each motor unit is made up of a pair of hydraulic McKibben muscles connected to one servovalve. The pressure and recruitment state of the artificial muscle bundle can be adjusted to match the load in an efficient manner, much like the firing rate and total number of recruited motor units is adjusted in skeletal muscle. A volume-based effective initial braid angle is used in the model of each recruitment level. This semi-empirical model is utilized to predict the efficiency gains of the proposed variable recruitment actuation scheme versus a throttling-only approach. A real-time orderly recruitment controller with pressure-based thresholds is developed. This controller is used to experimentally validate the model-predicted efficiency gains of recruitment on a robot arm. The results show that utilizing variable recruitment allows for much higher efficiencies over a broader operating envelope.

  14. A Hybrid PO - Higher-Order Hierarchical MoM Formulation using Curvilinear Geometry Modeling

    DEFF Research Database (Denmark)

    Jørgensen, E.; Meincke, Peter; Breinbjerg, Olav

    2003-01-01

    which implies a very modest memory requirement. Nevertheless, the hierarchical feature of the basis functions maintains the ability to treat small geometrical details efficiently. In addition, the scatterer is modelled with higher-order curved patches which allows accurate modelling of curved surfaces...

  15. Concentration and flux of total and dissolved phosphorus, total nitrogen, chloride, and total suspended solids for monitored tributaries of Lake Champlain, 1990-2012

    Science.gov (United States)

    Medalie, Laura

    2014-01-01

    Annual and daily concentrations and fluxes of total and dissolved phosphorus, total nitrogen, chloride, and total suspended solids were estimated for 18 monitored tributaries to Lake Champlain by using the Weighted Regressions on Time, Discharge, and Seasons regression model. Estimates were made for 21 or 23 years, depending on data availability, for the purpose of providing timely and accessible summary reports as stipulated in the 2010 update to the Lake Champlain “Opportunities for Action” management plan. Estimates of concentration and flux were provided for each tributary based on (1) observed daily discharges and (2) a flow-normalizing procedure, which removed the random fluctuations of climate-related variability. The flux bias statistic, an indicator of the ability of the Weighted Regressions on Time, Discharge, and Season regression models to provide accurate representations of flux, showed acceptable bias (less than ±10 percent) for 68 out of 72 models for total and dissolved phosphorus, total nitrogen, and chloride. Six out of 18 models for total suspended solids had moderate bias (between 10 and 30 percent), an expected result given the frequently nonlinear relation between total suspended solids and discharge. One model for total suspended solids with a very high bias was influenced by a single extreme value; however, removal of that value, although reducing the bias substantially, had little effect on annual fluxes.

  16. Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

    Science.gov (United States)

    Xu, Qiang; Ding, Shuai; An, Jingwen

    2017-12-01

    This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

  17. System Response Analysis and Model Order Reduction, Using Conventional Method, Bond Graph Technique and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lubna Moin

    2009-04-01

    Full Text Available This research paper basically explores and compares the different modeling and analysis techniques and than it also explores the model order reduction approach and significance. The traditional modeling and simulation techniques for dynamic systems are generally adequate for single-domain systems only, but the Bond Graph technique provides new strategies for reliable solutions of multi-domain system. They are also used for analyzing linear and non linear dynamic production system, artificial intelligence, image processing, robotics and industrial automation. This paper describes a unique technique of generating the Genetic design from the tree structured transfer function obtained from Bond Graph. This research work combines bond graphs for model representation with Genetic programming for exploring different ideas on design space tree structured transfer function result from replacing typical bond graph element with their impedance equivalent specifying impedance lows for Bond Graph multiport. This tree structured form thus obtained from Bond Graph is applied for generating the Genetic Tree. Application studies will identify key issues and importance for advancing this approach towards becoming on effective and efficient design tool for synthesizing design for Electrical system. In the first phase, the system is modeled using Bond Graph technique. Its system response and transfer function with conventional and Bond Graph method is analyzed and then a approach towards model order reduction is observed. The suggested algorithm and other known modern model order reduction techniques are applied to a 11th order high pass filter [1], with different approach. The model order reduction technique developed in this paper has least reduction errors and secondly the final model retains structural information. The system response and the stability analysis of the system transfer function taken by conventional and by Bond Graph method is compared and

  18. Accuracy Analysis of the Zero-Order Hold Model for Digital Pulsewidth Modulation

    DEFF Research Database (Denmark)

    Ma, Junpeng; Wang, Xiongfei; Blaabjerg, Frede

    2018-01-01

    This paper analyzes the accuracy of the zero-order hold (ZOH) model for the digital pulsewidth modulator (DPWM) in the s-domain. The s-domain model and the exact z-domain model for the control loop of the single-phase inverter with L-type filter is elaborated for quantifying the deviation...... of the ZOH model for DPWM. The influence of the different computational delay and duty-cycle update modes on this deviation is analyzed in detail. The compensation method for this deviation of the ZOH model is proposed for accurately predicting the stability region of the control system in the s...

  19. Asymptotic behaviour of pion-pion total cross-sections

    Energy Technology Data Exchange (ETDEWEB)

    Greynat, David [Dipartimento di Scienze Fisiche, Universita di Napoli “Federico II”,Via Cintia, 80126 Napoli (Italy); Rafael, Eduardo de [Aix-Marseille Université, CNRS,CPT, UMR 7332, 13288 Marseille (France); Université de Toulon, CNRS,CPT, UMR 7332, 83957 La Garde (France); Vulvert, Grégory [Departament de Física Teórica, IFIC,CSIC - Universitat de València, Apt. Correus 22085, E-46071 València (Spain)

    2014-03-24

    We derive a sum rule which shows that the Froissart-Martin bound for the asymptotic behaviour of the ππ total cross sections at high energies, if modulated by the Lukaszuk-Martin coefficient of the leading log{sup 2} s behaviour, cannot be an optimal bound in QCD. We next compute the total cross sections for π{sup +}π{sup −}, π{sup ±}π{sup 0} and π{sup 0}π{sup 0} scattering within the framework of the constituent chiral quark model (CχQM) in the limit of a large number of colours N{sub c} and discuss their asymptotic behaviours. The same ππ cross sections are also discussed within the general framework of Large-N{sub c} QCD and we show that it is possible to make an Ansatz for the isospin I=1 and I=0 spectrum which satisfy the Froissart-Martin bound with coefficients which, contrary to the Lukaszuk-Martin coefficient, are not singular in the chiral limit and have the correct Large-N{sub c} counting. We finally propose a simple phenomenological model which matches the low energy behaviours of the σ{sub π{sup ±}π{sup 0total}}(s) cross section predicted by the CχQM with the high energy behaviour predicted by the Large-N{sub c} Ansatz. The magnitude of these cross sections at very high energies is of the order of those observed for the pp and pp-bar scattering total cross sections.

  20. Rapid Estimation Method for State of Charge of Lithium-Ion Battery Based on Fractional Continual Variable Order Model

    Directory of Open Access Journals (Sweden)

    Xin Lu

    2018-03-01

    Full Text Available In recent years, the fractional order model has been employed to state of charge (SOC estimation. The non integer differentiation order being expressed as a function of recursive factors defining the fractality of charge distribution on porous electrodes. The battery SOC affects the fractal dimension of charge distribution, therefore the order of the fractional order model varies with the SOC at the same condition. This paper proposes a new method to estimate the SOC. A fractional continuous variable order model is used to characterize the fractal morphology of charge distribution. The order identification results showed that there is a stable monotonic relationship between the fractional order and the SOC after the battery inner electrochemical reaction reaches balanced. This feature makes the proposed model particularly suitable for SOC estimation when the battery is in the resting state. Moreover, a fast iterative method based on the proposed model is introduced for SOC estimation. The experimental results showed that the proposed iterative method can quickly estimate the SOC by several iterations while maintaining high estimation accuracy.

  1. 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.

  2. Statistical modeling of road contribution as emission sources to total suspended particles (TSP) under MCF model downtown Medellin - Antioquia - Colombia, 2004

    International Nuclear Information System (INIS)

    Gomez, Miryam; Saldarriaga, Julio; Correa, Mauricio; Posada, Enrique; Castrillon M, Francisco Javier

    2007-01-01

    Sand fields, constructions, carbon boilers, roads, and biologic sources are air-contaminant-constituent factors in down town Valle de Aburra, among others. the distribution of road contribution data to total suspended particles according to the source receptor model MCF, source correlation modeling, is nearly a gamma distribution. Chi-square goodness of fit is used to model statistically. This test for goodness of fit also allows estimating the parameters of the distribution utilizing maximum likelihood method. As convergence criteria, the estimation maximization algorithm is used. The mean of road contribution data to total suspended particles according to the source receptor model MCF, is straightforward and validates the road contribution factor to the atmospheric pollution of the zone under study

  3. Using Higher-Order Dynamic Bayesian Networks to Model Periodic Data from the Circadian Clock of Arabidopsis Thaliana

    Science.gov (United States)

    Daly, Rónán; Edwards, Kieron D.; O'Neill, John S.; Aitken, Stuart; Millar, Andrew J.; Girolami, Mark

    Modelling gene regulatory networks in organisms is an important task that has recently become possible due to large scale assays using technologies such as microarrays. In this paper, the circadian clock of Arabidopsis thaliana is modelled by fitting dynamic Bayesian networks to luminescence data gathered from experiments. This work differs from previous modelling attempts by using higher-order dynamic Bayesian networks to explicitly model the time lag between the various genes being expressed. In order to achieve this goal, new techniques in preprocessing the data and in evaluating a learned model are proposed. It is shown that it is possible, to some extent, to model these time delays using a higher-order dynamic Bayesian network.

  4. Compound waves in a higher order nonlinear model of thermoviscous fluids

    DEFF Research Database (Denmark)

    Rønne Rasmussen, Anders; Sørensen, Mads Peter; Gaididei, Yuri B.

    2016-01-01

    A generalized traveling wave ansatz is used to investigate compound shock waves in a higher order nonlinear model of a thermoviscous fluid. The fluid velocity potential is written as a traveling wave plus a linear function of space and time. The latter offers the possibility of predicting...

  5. Finite Time Control for Fractional Order Nonlinear Hydroturbine Governing System via Frequency Distributed Model

    Directory of Open Access Journals (Sweden)

    Bin Wang

    2016-01-01

    Full Text Available This paper studies the application of frequency distributed model for finite time control of a fractional order nonlinear hydroturbine governing system (HGS. Firstly, the mathematical model of HGS with external random disturbances is introduced. Secondly, a novel terminal sliding surface is proposed and its stability to origin is proved based on the frequency distributed model and Lyapunov stability theory. Furthermore, based on finite time stability and sliding mode control theory, a robust control law to ensure the occurrence of the sliding motion in a finite time is designed for stabilization of the fractional order HGS. Finally, simulation results show the effectiveness and robustness of the proposed scheme.

  6. 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

  7. Autologous Stem Cell Transplantation in Patients With Multiple Myeloma: An Activity-based Costing Analysis, Comparing a Total Inpatient Model Versus an Early Discharge Model.

    Science.gov (United States)

    Martino, Massimo; Console, Giuseppe; Russo, Letteria; Meliado', Antonella; Meliambro, Nicola; Moscato, Tiziana; Irrera, Giuseppe; Messina, Giuseppe; Pontari, Antonella; Morabito, Fortunato

    2017-08-01

    Activity-based costing (ABC) was developed and advocated as a means of overcoming the systematic distortions of traditional cost accounting. We calculated the cost of high-dose chemotherapy and autologous stem cell transplantation (ASCT) in patients with multiple myeloma using the ABC method, through 2 different care models: the total inpatient model (TIM) and the early-discharge outpatient model (EDOM) and compared this with the approved diagnosis related-groups (DRG) Italian tariffs. The TIM and EDOM models involved a total cost of €28,615.15 and €16,499.43, respectively. In the TIM model, the phase with the greatest economic impact was the posttransplant (recovery and hematologic engraftment) with 36.4% of the total cost, whereas in the EDOM model, the phase with the greatest economic impact was the pretransplant (chemo-mobilization, apheresis procedure, cryopreservation, and storage) phase, with 60.4% of total expenses. In an analysis of each episode, the TIM model comprised a higher absorption than the EDOM. In particular, the posttransplant represented 36.4% of the total costs in the TIM and 17.7% in EDOM model, respectively. The estimated reduction in cost per patient using an EDOM model was over €12,115.72. The repayment of the DRG in Calabrian Region for the ASCT procedure is €59,806. Given the real cost of the transplant, the estimated cost saving per patient is €31,190.85 in the TIM model and €43,306.57 in the EDOM model. In conclusion, the actual repayment of the DRG does not correspond to the real cost of the ASCT procedure in Italy. Moreover, using the EDOM, the cost of ASCT is approximately the half of the TIM model. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. CT image construction of a totally deflated lung using deformable model extrapolation

    International Nuclear Information System (INIS)

    Sadeghi Naini, Ali; Pierce, Greg; Lee, Ting-Yim

    2011-01-01

    Purpose: A novel technique is proposed to construct CT image of a totally deflated lung from a free-breathing 4D-CT image sequence acquired preoperatively. Such a constructed CT image is very useful in performing tumor ablative procedures such as lung brachytherapy. Tumor ablative procedures are frequently performed while the lung is totally deflated. Deflating the lung during such procedures renders preoperative images ineffective for targeting the tumor. Furthermore, the problem cannot be solved using intraoperative ultrasound (U.S.) images because U.S. images are very sensitive to small residual amount of air remaining in the deflated lung. One possible solution to address these issues is to register high quality preoperative CT images of the deflated lung with their corresponding low quality intraoperative U.S. images. However, given that such preoperative images correspond to an inflated lung, such CT images need to be processed to construct CT images pertaining to the lung's deflated state. Methods: To obtain the CT images of deflated lung, we present a novel image construction technique using extrapolated deformable registration to predict the deformation the lung undergoes during full deflation. The proposed construction technique involves estimating the lung's air volume in each preoperative image automatically in order to track the respiration phase of each 4D-CT image throughout a respiratory cycle; i.e., the technique does not need any external marker to form a respiratory signal in the process of curve fitting and extrapolation. The extrapolated deformation field is then applied on a preoperative reference image in order to construct the totally deflated lung's CT image. The technique was evaluated experimentally using ex vivo porcine lung. Results: The ex vivo lung experiments led to very encouraging results. In comparison with the CT image of the deflated lung we acquired for the purpose of validation, the constructed CT image was very similar. The

  9. Disturbance estimation of nuclear power plant by using reduced-order model

    International Nuclear Information System (INIS)

    Tashima, Shin-ichi; Wakabayashi, Jiro

    1983-01-01

    An estimation method is proposed of multiplex disturbances which occur in a nuclear power plant. The method is composed of two parts: (i) the identification of a simplified model of multi-input and multi-output to describe the related system response, and (ii) the design of a Kalman filter to estimate the multiplex disturbance. Concerning the simplified model, several observed signals are firstly selected as output variables which can well represent the system response caused by the disturbances. A reduced-order model is utilized for designing the disturbance estimator. This is based on the following two considerations. The first is that the disturbance is assumed to be of a quasistatic nature. The other is based on the intuition that there exist a few dominant modes between the disturbances and the selected observed signals and that most of the non-dominant modes which remain may not affect the accuracy of the disturbance estimator. The reduced-order model is furtherly transformed to a single-output model using a linear combination of the output signals, where the standard procedure of the structural identification is evaded. The parameters of the model thus transformed are calculated by the generalized least square method. As for the multiplex disturbance estimator, the Kalman filtering method is applied by compromising the following three items : (a) quick response to disturbance, (b) reduction of estimation error in the presence of observation noises, and (c) the elimination of cross-interference between the disturbances to the plant and the estimates from the Kalman filter. The effectiveness of the proposed method is verified through some computer experiments using a BWR plant simulator. (author)

  10. A Novel Entropy-Based Decoding Algorithm for a Generalized High-Order Discrete Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Jason Chin-Tiong Chan

    2018-01-01

    Full Text Available The optimal state sequence of a generalized High-Order Hidden Markov Model (HHMM is tracked from a given observational sequence using the classical Viterbi algorithm. This classical algorithm is based on maximum likelihood criterion. We introduce an entropy-based Viterbi algorithm for tracking the optimal state sequence of a HHMM. The entropy of a state sequence is a useful quantity, providing a measure of the uncertainty of a HHMM. There will be no uncertainty if there is only one possible optimal state sequence for HHMM. This entropy-based decoding algorithm can be formulated in an extended or a reduction approach. We extend the entropy-based algorithm for computing the optimal state sequence that was developed from a first-order to a generalized HHMM with a single observational sequence. This extended algorithm performs the computation exponentially with respect to the order of HMM. The computational complexity of this extended algorithm is due to the growth of the model parameters. We introduce an efficient entropy-based decoding algorithm that used reduction approach, namely, entropy-based order-transformation forward algorithm (EOTFA to compute the optimal state sequence of any generalized HHMM. This EOTFA algorithm involves a transformation of a generalized high-order HMM into an equivalent first-order HMM and an entropy-based decoding algorithm is developed based on the equivalent first-order HMM. This algorithm performs the computation based on the observational sequence and it requires OTN~2 calculations, where N~ is the number of states in an equivalent first-order model and T is the length of observational sequence.

  11. Total inpatient treatment costs in patients with severe burns: towards a more accurate reimbursement model.

    Science.gov (United States)

    Mehra, Tarun; Koljonen, Virve; Seifert, Burkhardt; Volbracht, Jörk; Giovanoli, Pietro; Plock, Jan; Moos, Rudolf Maria

    2015-01-01

    Reimbursement systems have difficulties depicting the actual cost of burn treatment, leaving care providers with a significant financial burden. Our aim was to establish a simple and accurate reimbursement model compatible with prospective payment systems. A total of 370 966 electronic medical records of patients discharged in 2012 to 2013 from Swiss university hospitals were reviewed. A total of 828 cases of burns including 109 cases of severe burns were retained. Costs, revenues and earnings for severe and nonsevere burns were analysed and a linear regression model predicting total inpatient treatment costs was established. The median total costs per case for severe burns was tenfold higher than for nonsevere burns (179 949 CHF [167 353 EUR] vs 11 312 CHF [10 520 EUR], interquartile ranges 96 782-328 618 CHF vs 4 874-27 783 CHF, p <0.001). The median of earnings per case for nonsevere burns was 588 CHF (547 EUR) (interquartile range -6 720 - 5 354 CHF) whereas severe burns incurred a large financial loss to care providers, with median earnings of -33 178 CHF (30 856 EUR) (interquartile range -95 533 - 23 662 CHF). Differences were highly significant (p <0.001). Our linear regression model predicting total costs per case with length of stay (LOS) as independent variable had an adjusted R2 of 0.67 (p <0.001 for LOS). Severe burns are systematically underfunded within the Swiss reimbursement system. Flat-rate DRG-based refunds poorly reflect the actual treatment costs. In conclusion, we suggest a reimbursement model based on a per diem rate for treatment of severe burns.

  12. An updated fracture-flow model for total-system performance assessment of Yucca Mountain

    International Nuclear Information System (INIS)

    Gauthier, J.H.

    1994-01-01

    Improvements have been made to the fracture-flow model being used in the total-system performance assessment of a potential high-level radioactive waste repository at Yucca Mountain, Nevada. The open-quotes weeps modelclose quotes now includes (1) weeps of varied sizes, (2) flow-pattern fluctuations caused by climate change, and (3) flow-pattern perturbations caused by repository heat generation. Comparison with the original weeps model indicates that allowing weeps of varied sizes substantially reduces the number of weeps and the number of containers contacted by weeps. However, flow-pattern perturbations caused by either climate change or repository heat generation greatly increases the number of containers contacted by weeps. In preliminary total-system calculations, using a phenomenological container-failure and radionuclide-release model, the weeps model predicts that radionuclide releases from a high-level radioactive waste repository at Yucca Mountain will be below the EPA standard specified in 40 CFR 191, but that the maximum radiation dose to an individual could be significant. Specific data from the site are required to determine the validity of the weep-flow mechanism and to better determine the parameters to which the dose calculation is sensitive

  13. 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

  14. Development and analysis of a twelfth degree and order gravity model for Mars

    Science.gov (United States)

    Christensen, E. J.; Balmino, G.

    1979-01-01

    Satellite geodesy techniques previously applied to artificial earth satellites have been extended to obtain a high-resolution gravity field for Mars. Two-way Doppler data collected by 10 Deep Space Network (DSN) stations during Mariner 9 and Viking 1 and 2 missions have been processed to obtain a twelfth degree and order spherical harmonic model for the martian gravitational potential. The quality of this model was evaluated by examining the rms residuals within the fit and the ability of the model to predict the spacecraft state beyond the fit. Both indicators show that more data and higher degree and order harmonics will be required to further refine our knowledge of the martian gravity field. The model presented shows much promise, since it resolves local gravity features which correlate highly with the martian topography. An isostatic analysis based on this model, as well as an error analysis, shows rather complete compensation on a global (long wavelength) scale. Though further model refinements are necessary to be certain, local (short wavelength) features such as the shield volcanos in Tharsis appear to be uncompensated. These are interpreted to place some bounds on the internal structure of Mars.

  15. Incorporating social groups' responses in a descriptive model for second- and higher-order impact identification

    International Nuclear Information System (INIS)

    Sutheerawatthana, Pitch; Minato, Takayuki

    2010-01-01

    The response of a social group is a missing element in the formal impact assessment model. Previous discussion of the involvement of social groups in an intervention has mainly focused on the formation of the intervention. This article discusses the involvement of social groups in a different way. A descriptive model is proposed by incorporating a social group's response into the concept of second- and higher-order effects. The model is developed based on a cause-effect relationship through the observation of phenomena in case studies. The model clarifies the process by which social groups interact with a lower-order effect and then generate a higher-order effect in an iterative manner. This study classifies social groups' responses into three forms-opposing, modifying, and advantage-taking action-and places them in six pathways. The model is expected to be used as an analytical tool for investigating and identifying impacts in the planning stage and as a framework for monitoring social groups' responses during the implementation stage of a policy, plan, program, or project (PPPPs).

  16. Higher-order anisotropies in the blast-wave model: Disentangling flow and density field anisotropies

    Energy Technology Data Exchange (ETDEWEB)

    Cimerman, Jakub [Czech Technical University in Prague, FNSPE, Prague (Czech Republic); Comenius University, FMPI, Bratislava (Slovakia); Tomasik, Boris [Czech Technical University in Prague, FNSPE, Prague (Czech Republic); Univerzita Mateja Bela, FPV, Banska Bystrica (Slovakia); Csanad, Mate; Loekoes, Sandor [Eoetvoes Lorand University, Budapest (Hungary)

    2017-08-15

    We formulate a generalisation of the blast-wave model which is suitable for the description of higher-order azimuthal anisotropies of the hadron production. The model includes anisotropy in the density profile as well as an anisotropy in the transverse expansion velocity field. We then study how these two kinds of anisotropies influence the single-particle distributions and the correlation radii of two-particle correlation functions. Particularly we focus on the third-order anisotropy and consideration is given averaging over different orientations of the event plane. (orig.)

  17. The Nordic Model in a Global Company Situated in Norway. Challenging Institutional Orders?

    Directory of Open Access Journals (Sweden)

    Elin Kvande

    2012-11-01

    Full Text Available In this article, we explore the impact of internationalization as organizational processes where institutional actors meet in local contexts and negotiate the institutional order. The internationalization of working life implies that different traditions and practices meet and challenge each other. The focus is on how important elements of the Nordic micro model like cooperation between employees and employers and regulation of working hours are implemented in a global company situated in Norway. In general, it seems that employees and employers cooperate in line with this tradition in the Nordic micro model. Norwegian manager’s practices are described to be in accordance with Scandinavian management traditions, while managers from the United States appear to practice management consistent with the liberal working life model. The findings show a tension-filled clash between two different management practices, which indicates that the Nordic micro model in this field might be under pressure. Manager’s recommendation to the employees was not to become members of the trade union. The absence of trade unions in the organization implies that employees and employers are not cooperating on a collective level. This means that only parts of the regulatory arrangement related to participation and cooperation are implemented. Findings concerning working time and the relation to the institutional order represented by the Norwegian Work Environment Act indicate a clear tension between different institutional traditions in the organization. The company does not respect the Norwegian in working time regulations. These regulations are seen as counterproductive for a company that competes in the international market. This devaluation of the regulations in the Nordic model implies that the institutional order represented in the Nordic micro model is challenged.

  18. Computation of nonlinear water waves with a high-order Boussinesq model

    DEFF Research Database (Denmark)

    Fuhrman, David R.; Madsen, Per A.; Bingham, Harry

    2005-01-01

    Computational highlights from a recently developed high-order Boussinesq model are shown. The model is capable of treating fully nonlinear waves (up to the breaking point) out to dimensionless depths of (wavenumber times depth) kh \\approx 25. Cases considered include the study of short......-crested waves in shallow/deep water, resulting in hexagonal/rectangular surface patterns; crescent waves, resulting from unstable perturbations of plane progressive waves; and highly-nonlinear wave-structure interactions. The emphasis is on physically demanding problems, and in eachcase qualitative and (when...

  19. Factors affecting medication-order processing time.

    Science.gov (United States)

    Beaman, M A; Kotzan, J A

    1982-11-01

    The factors affecting medication-order processing time at one hospital were studied. The order processing time was determined by directly observing the time to process randomly selected new drug orders on all three work shifts during two one-week periods. An order could list more than one drug for an individual patient. The observer recorded the nature, location, and cost of the drugs ordered, as well as the time to process the order. The time and type of interruptions also were noted. The time to process a drug order was classified as six dependent variables: (1) total time, (2) work time, (3) check time, (4) waiting time I--time from arrival on the dumbwaiter until work was initiated, (5) waiting time II--time between completion of the work and initiation of checking, and (6) waiting time III--time after the check was completed until the order left on the dumbwaiter. The significant predictors of each of the six dependent variables were determined using stepwise multiple regression. The total time to process a prescription order was 58.33 +/- 48.72 minutes; the urgency status of the order was the only significant determinant of total time. Urgency status also significantly predicted the three waiting-time variables. Interruptions and the number of drugs on the order were significant determinants of work time and check time. Each telephone interruption increased the work time by 1.72 minutes. While the results of this study cannot be generalized to other institutions, pharmacy managers can use the method of determining factors that affect medication-order processing time to identify problem areas in their institutions.

  20. Heavy-traffic limits for polling models with exhaustive service and non-FCFS service orders

    NARCIS (Netherlands)

    P. Vis (Petra); R. Bekker (Rene); R.D. van der Mei (Rob)

    2015-01-01

    htmlabstractWe study cyclic polling models with exhaustive service at each queue under a variety of non-FCFS (first-come-first-served) local service orders, namely last-come-first-served with and without preemption, random-order-of-service, processor sharing, the multi-class priority scheduling with

  1. 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.

  2. 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.

  3. Correlations between corneal and total wavefront aberrations

    Science.gov (United States)

    Mrochen, Michael; Jankov, Mirko; Bueeler, Michael; Seiler, Theo

    2002-06-01

    Purpose: Corneal topography data expressed as corneal aberrations are frequently used to report corneal laser surgery results. However, the optical image quality at the retina depends on all optical elements of the eye such as the human lens. Thus, the aim of this study was to investigate the correlations between the corneal and total wavefront aberrations and to discuss the importance of corneal aberrations for representing corneal laser surgery results. Methods: Thirty three eyes of 22 myopic subjects were measured with a corneal topography system and a Tschernig-type wavefront analyzer after the pupils were dilated to at least 6 mm in diameter. All measurements were centered with respect to the line of sight. Corneal and total wavefront aberrations were calculated up to the 6th Zernike order in the same reference plane. Results: Statistically significant correlations (p the corneal and total wavefront aberrations were found for the astigmatism (C3,C5) and all 3rd Zernike order coefficients such as coma (C7,C8). No statistically significant correlations were found for all 4th to 6th order Zernike coefficients except for the 5th order horizontal coma C18 (p equals 0.003). On average, all Zernike coefficients for the corneal aberrations were found to be larger compared to Zernike coefficients for the total wavefront aberrations. Conclusions: Corneal aberrations are only of limited use for representing the optical quality of the human eye after corneal laser surgery. This is due to the lack of correlation between corneal and total wavefront aberrations in most of the higher order aberrations. Besides this, the data present in this study yield towards an aberration balancing between corneal aberrations and the optical elements within the eye that reduces the aberration from the cornea by a certain degree. Consequently, ideal customized ablations have to take both, corneal and total wavefront aberrations, into consideration.

  4. Carl Schmitt's attitude towards total war and total enemy on the eve of the outbreak of WWII

    Directory of Open Access Journals (Sweden)

    Molnar Aleksandar

    2010-01-01

    Full Text Available Carl Schmitt is usually perceived as the theorist of total state, total war and total hostility. In the article, the author however tries to show that from 1937 to 1944, Schmitt was arguing that total war and total hostility were dangerous for Germany (as well as for the rest of Europe and warned against perpetuation of all efforts to totalize enemy that started in 1914. In his theoretical endeavors in this period there was place for the total state only - and especially for the total state strong enough to resist temptation of declaring total war on total enemy. The total state he recommended Hitler and his Nazi comrades was German Reich, as a part of Europe ordered and divided in the huge spaces (Grossraumordnung. Positioned in the centre of Europe, between the rest of the powers (France, Italy, USSR as well as the Scandinavian states, Germany should be careful enough to wage war only against its Eastern enemies (Poland and maybe USSR and only in order to achieve 'just' borders. Occupying in this way its huge space Germany should devote itself to the task of exploitation of various peoples such as Poles, Chechs and Slovaks, which were perceived as incapable of having their states and doomed to serve the master race - the Germans.

  5. The Effect of Units Lost Due to Deterioration in Fuzzy Economic Order Quantity (FEOQ Model

    Directory of Open Access Journals (Sweden)

    M. Pattnaik

    2013-07-01

    Full Text Available For several decades, the Economic Order Quantity (EOQ model and its variations have received much attention from researchers. Recently, there has been an investigation into an EOQ model incorporating effect of units lost due to deterioration in infinite planning horizon with crisp decision environment. Accounting for holding and ordering cost, as has traditionally been the case of modeling inventory systems in fuzzy environment are investigated which are not precisely known and defined on a bounded interval of real numbers. The question is how reliable are the EOQ models when items stocked deteriorate one time. This paper introduces Fuzzy Economic Order Quantity (FEOQ model in which it assumes that units lost due to deterioration is included in the objective function to properly model the problem in finite planning horizon. The numerical analysis shows that an appropriate fuzzy policy can benefit the retailer and that is significant, especially for deteriorating items is shown to be superior to that of crisp decision making. A computational algorithm using LINGO 13.0 and MATLAB (R2009a software are developed to find the optimal solution. Sensitivity analysis of the optimal solution is also studied and managerial insights are drawn which shows the influence of key model parameters.

  6. Empirical tight-binding modeling of ordered and disordered semiconductor structures

    International Nuclear Information System (INIS)

    Mourad, Daniel

    2010-01-01

    In this thesis, we investigate the electronic and optical properties of pure as well as of substitutionally alloyed II-VI and III-V bulk semiconductors and corresponding semiconductor quantum dots by means of an empirical tight-binding (TB) model. In the case of the alloyed systems of the type A x B 1-x , where A and B are the pure compound semiconductor materials, we study the influence of the disorder by means of several extensions of the TB model with different levels of sophistication. Our methods range from rather simple mean-field approaches (virtual crystal approximation, VCA) over a dynamical mean-field approach (coherent potential approximation, CPA) up to calculations where substitutional disorder is incorporated on a finite ensemble of microscopically distinct configurations. In the first part of this thesis, we cover the necessary fundamentals in order to properly introduce the TB model of our choice, the effective bond-orbital model (EBOM). In this model, one s- and three p-orbitals per spin direction are localized on the sites of the underlying Bravais lattice. The matrix elements between these orbitals are treated as free parameters in order to reproduce the properties of one conduction and three valence bands per spin direction and can then be used in supercell calculations in order to model mixed bulk materials or pure as well as mixed quantum dots. Part II of this thesis deals with unalloyed systems. Here, we use the EBOM in combination with configuration interaction calculations for the investigation of the electronic and optical properties of truncated pyramidal GaN quantum dots embedded in AlN with an underlying zincblende structure. Furthermore, we develop a parametrization of the EBOM for materials with a wurtzite structure, which allows for a fit of one conduction and three valence bands per spin direction throughout the whole Brillouin zone of the hexagonal system. In Part III, we focus on the influence of alloying on the electronic and

  7. Total output operation chart optimization of cascade reservoirs and its application

    International Nuclear Information System (INIS)

    Jiang, Zhiqiang; Ji, Changming; Sun, Ping; Wang, Liping; Zhang, Yanke

    2014-01-01

    Highlights: • We propose a new double nested model for cascade reservoirs operation optimization. • We use two methods to extract the output distribution ratio. • The adopted two methods perform better than the widely used methods at present. • Stepwise regression method performs better than mean value method on the whole. - Abstract: With the rapid development of cascade hydropower stations in recent decades, the cascade system composed of multiple reservoirs needs unified operation and management. However, the output distribution problem has not yet been solved reasonably when the total output of cascade system obtained, which makes the full utilization of hydropower resources in cascade reservoirs very difficult. Discriminant criterion method is a traditional and common method to solve the output distribution problem at present, but some shortcomings cannot be ignored in the practical application. In response to the above concern, this paper proposes a new total output operation chart optimization model and a new optimal output distribution model, the two models constitute to a double nested model with the goal of maximizing power generation. This paper takes the cascade reservoirs of Li Xianjiang River in China as an instance to obtain the optimal total output operation chart by the proposed double nested model and the 43 years historical runoff data, progressive searching method and progressive optimality algorithm are used in solving the model. In order to take the obtained total output operation chart into practical operation, mean value method and stepwise regression method are adopted to extract the output distribution ratios on the basis of the optimal simulation intermediate data. By comparing with discriminant criterion method and conventional method, the combined utilization of total output operation chart and output distribution ratios presents better performance in terms of power generation and assurance rate, which proves it is an effective

  8. Temporal aggregation in first order cointegrated vector autoregressive models

    DEFF Research Database (Denmark)

    La Cour, Lisbeth Funding; Milhøj, Anders

    We study aggregation - or sample frequencies - of time series, e.g. aggregation from weekly to monthly or quarterly time series. Aggregation usually gives shorter time series but spurious phenomena, in e.g. daily observations, can on the other hand be avoided. An important issue is the effect of ...... of aggregation on the adjustment coefficient in cointegrated systems. We study only first order vector autoregressive processes for n dimensional time series Xt, and we illustrate the theory by a two dimensional and a four dimensional model for prices of various grades of gasoline...

  9. Beacon satellite studies and modelling of total electron contents of the ionosphere

    International Nuclear Information System (INIS)

    Tyagi, T.R.

    1990-01-01

    An attempt is made to highlight some of the beacon satellite studies, particularly those relating to total electron content (TEC) and scintillations, with special attention to Indian subcontinent observations. The modelling of TEC is described. The scope of new experiments for specific problem is indicated. (author). 78 refs., 12 figs

  10. Ordering Dynamics in Neuron Activity Pattern Model: An Insight to Brain Functionality.

    Directory of Open Access Journals (Sweden)

    Jasleen Gundh

    Full Text Available We study the domain ordering kinetics in d = 2 ferromagnets which corresponds to populated neuron activities with both long-ranged interactions, V(r ∼ r-n and short-ranged interactions. We present the results from comprehensive Monte Carlo (MC simulations for the nonconserved Ising model with n ≥ 2, interaction range considering near and far neighbors. Our model results could represent the long-ranged neuron kinetics (n ≤ 4 in consistent with the same dynamical behaviour of short-ranged case (n ≥ 4 at far below and near criticality. We found that emergence of fast and slow kinetics of long and short ranged case could imitate the formation of connections among near and distant neurons. The calculated characteristic length scale in long-ranged interaction is found to be n independent (L(t ∼ t1/(n-2, whereas short-ranged interaction follows L(t ∼ t1/2 law and approximately preserve universality in domain kinetics. Further, we did the comparative study of phase ordering near the critical temperature which follows different behaviours of domain ordering near and far critical temperature but follows universal scaling law.

  11. A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics

    Science.gov (United States)

    Kerfriden, P.; Goury, O.; Rabczuk, T.; Bordas, S.P.A.

    2013-01-01

    We propose in this paper a reduced order modelling technique based on domain partitioning for parametric problems of fracture. We show that coupling domain decomposition and projection-based model order reduction permits to focus the numerical effort where it is most needed: around the zones where damage propagates. No a priori knowledge of the damage pattern is required, the extraction of the corresponding spatial regions being based solely on algebra. The efficiency of the proposed approach is demonstrated numerically with an example relevant to engineering fracture. PMID:23750055

  12. Interacting gaps model, dynamics of order book, and stock-market fluctuations

    Czech Academy of Sciences Publication Activity Database

    Svorenčík, A.; Slanina, František

    2007-01-01

    Roč. 57, - (2007), s. 453-462 ISSN 1434-6028 R&D Projects: GA MŠk 1P04OCP10.001 Institutional research plan: CEZ:AV0Z10100520 Keywords : interacting gaps model * dynamics of order book * stock - market fluctuations Subject RIV: BE - Theoretical Physics Impact factor: 1.356, year: 2007

  13. On the parameter estimation of first order IMA model corrupted with ...

    African Journals Online (AJOL)

    In this paper, we showed how the autocovariance functions can be used to estimate the true parameters of IMA(1) models corrupted with white noise . We performed simulation studies to demonstrate our findings. The simulation studies showed that under the presence of errors in not more than 30% of total data points, our ...

  14. Dividend Per Share, Retained Earnings, Book Value And Total Debt On Stock Price: Approximation Valuation Model Dividend Per Share, Retained Earnings, Book Value, dan Total Debt terhadap Harga Saham: Pendekatan Valuation Model.

    OpenAIRE

    khikmah, Khoirul

    2011-01-01

    This study examines to dividend per share, retained earnings, book valueand total debt on stock price: approximation valuation model. Data in this studyare manufacture firms listed on Indonesia Stock Exchange in 2005 – 2008. Linearregression analysis used to analysis this data. Result of regression analysis findsthat dividend per share, retained earnings, book value and total debt on stock pricehave significant effect to stock price. Dividend per share and book value havesignificant effect in...

  15. Qualità totale e mobilità totale Total Quality and Total Mobility

    Directory of Open Access Journals (Sweden)

    Giuseppe Trieste

    2010-05-01

    Full Text Available FIABA ONLUS (Italian Fund for Elimination of Architectural Barriers was founded in 2000 with the aim of promoting a culture of equal opportunities and, above all, it has as its main goal to involve public and private institutions to create a really accessible and usable environment for everyone. Total accessibility, Total usability and Total mobility are key indicators to define quality of life within cities. A supportive environment that is free of architectural, cultural and psychological barriers allows everyone to live with ease and universality. In fact, people who access to goods and services in the urban context can use to their advantage time and space, so they can do their activities and can maintain relationships that are deemed significant for their social life. The main aim of urban accessibility is to raise the comfort of space for citizens, eliminating all barriers that discriminate people, and prevent from an equality of opportunity. “FIABA FUND - City of ... for the removal of architectural barriers” is an idea of FIABA that has already affected many regions of Italy as Lazio, Lombardy, Campania, Abruzzi and Calabria. It is a National project which provides for opening a bank account in the cities of referring, in which for the first time, all together, individuals and private and public institutions can make a donation to fund initiatives for the removal of architectural barriers within its own territory for a real and effective total accessibility. Last February the fund was launched in Rome with the aim of achieving a Capital without barriers and a Town European model of accessibility and usability. Urban mobility is a prerequisite to access to goods and services, and to organize activities related to daily life. FIABA promotes the concept of sustainable mobility for all, supported by the European Commission’s White Paper. We need a cultural change in management and organization of public means, which might focus on

  16. A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means

    Science.gov (United States)

    Polak, Marike; De Rooij, Mark; Heiser, Willem J.

    2012-01-01

    In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…

  17. Venus spherical harmonic gravity model to degree and order 60

    Science.gov (United States)

    Konopliv, Alex S.; Sjogren, William L.

    1994-01-01

    The Magellan and Pioneer Venus Orbiter radiometric tracking data sets have been combined to produce a 60th degree and order spherical harmonic gravity field. The Magellan data include the high-precision X-band gravity tracking from September 1992 to May 1993 and post-aerobraking data up to January 5, 1994. Gravity models are presented from the application of Kaula's power rule for Venus and an alternative a priori method using surface accelerations. Results are given as vertical gravity acceleration at the reference surface, geoid, vertical Bouguer, and vertical isostatic maps with errors for the vertical gravity and geoid maps included. Correlation of the gravity with topography for the different models is also discussed.

  18. Ordered LOGIT Model approach for the determination of financial distress.

    Science.gov (United States)

    Kinay, B

    2010-01-01

    Nowadays, as a result of the global competition encountered, numerous companies come up against financial distresses. To predict and take proactive approaches for those problems is quite important. Thus, the prediction of crisis and financial distress is essential in terms of revealing the financial condition of companies. In this study, financial ratios relating to 156 industrial firms that are quoted in the Istanbul Stock Exchange are used and probabilities of financial distress are predicted by means of an ordered logit regression model. By means of Altman's Z Score, the dependent variable is composed by scaling the level of risk. Thus, a model that can compose an early warning system and predict financial distress is proposed.

  19. The Role of Hybrid Make-to-Stock (MTS) - Make-to-Order (MTO) and Economic Order Quantity (EOQ) Inventory Control Models in Food and Beverage Processing Industry

    Science.gov (United States)

    Najhan Mohd Nagib, Ahmad; Naufal Adnan, Ahmad; Ismail, Azianti; Halim, Nurul Hayati Abdul; Syuhadah Khusaini, Nurul

    2016-11-01

    The inventory model had been utilized since the early 1900s. The implementation of the inventory management model is generally to ensure that an organisation is able to fulfil customer's demand at the lowest possible cost to improve profitability. This paper focuses on reviewing previous published papers regarding inventory control model mainly in the food and beverage processing industry. The author discusses four inventory models, which are the make-to-stock (MTS), make-to-order (MTO), economic order quantity (EOQ), and hybrid of MTS-MTO models. The issues raised by the researchers on the above techniques as well as the elements need to be considered upon selection have been discussed in this paper. The main objective of the study is to highlight the important role played by these inventory control models in the food and beverage processing industry.

  20. Multiscale high-order/low-order (HOLO) algorithms and applications

    International Nuclear Information System (INIS)

    Chacón, L.; Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W.; Willert, J.A.; Womeldorff, G.

    2017-01-01

    We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

  1. Multiscale high-order/low-order (HOLO) algorithms and applications

    Energy Technology Data Exchange (ETDEWEB)

    Chacón, L., E-mail: chacon@lanl.gov [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Chen, G.; Knoll, D.A.; Newman, C.; Park, H.; Taitano, W. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Willert, J.A. [Institute for Defense Analyses, Alexandria, VA 22311 (United States); Womeldorff, G. [Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)

    2017-02-01

    We review the state of the art in the formulation, implementation, and performance of so-called high-order/low-order (HOLO) algorithms for challenging multiscale problems. HOLO algorithms attempt to couple one or several high-complexity physical models (the high-order model, HO) with low-complexity ones (the low-order model, LO). The primary goal of HOLO algorithms is to achieve nonlinear convergence between HO and LO components while minimizing memory footprint and managing the computational complexity in a practical manner. Key to the HOLO approach is the use of the LO representations to address temporal stiffness, effectively accelerating the convergence of the HO/LO coupled system. The HOLO approach is broadly underpinned by the concept of nonlinear elimination, which enables segregation of the HO and LO components in ways that can effectively use heterogeneous architectures. The accuracy and efficiency benefits of HOLO algorithms are demonstrated with specific applications to radiation transport, gas dynamics, plasmas (both Eulerian and Lagrangian formulations), and ocean modeling. Across this broad application spectrum, HOLO algorithms achieve significant accuracy improvements at a fraction of the cost compared to conventional approaches. It follows that HOLO algorithms hold significant potential for high-fidelity system scale multiscale simulations leveraging exascale computing.

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

    KAUST Repository

    Mo, Qianxing

    2010-01-29

    ChIP-chip experiments are procedures that combine chromatin immunoprecipitation (ChIP) and DNA microarray (chip) technology to study a variety of biological problems, including protein-DNA interaction, histone modification, and DNA methylation. The most important feature of ChIP-chip data is that the intensity measurements of probes are spatially correlated because the DNA fragments are hybridized to neighboring probes in the experiments. We propose a simple, but powerful Bayesian hierarchical 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 resolutions. The model parameters are estimated using the Gibbs sampler. The proposed method is illustrated using two publicly available data sets from Affymetrix and Agilent platforms, and compared with three alternative Bayesian methods, namely, Bayesian hierarchical model, hierarchical gamma mixture model, and Tilemap hidden Markov model. The numerical results indicate that the proposed method performs as well as the other three methods for the data from Affymetrix tiling arrays, but significantly outperforms the other three methods for the data from Agilent promoter arrays. In addition, we find that the proposed method has better operating characteristics in terms of sensitivities and false discovery rates under various scenarios. © 2010, The International Biometric Society.

  3. Reduced-Order Modeling of Unsteady Aerodynamics Across Multiple Mach Regimes

    Science.gov (United States)

    2013-01-01

    elastic deformation, has been the subject of intensive study and has been treated in a number of textbooks , including Refs. 9–11, as well as review...simulations, which can be quite computationally-intensive. Reduced-order models (ROMs) o er a solution to these competing demands of accuracy and e ciency...regimes, from subsonic to hypersonic ight. The correction factor term allows the ROM to be accurate over a range of vehicle elastic modal deformation

  4. Neutrino masses and their ordering: global data, priors and models

    Science.gov (United States)

    Gariazzo, S.; Archidiacono, M.; de Salas, P. F.; Mena, O.; Ternes, C. A.; Tórtola, M.

    2018-03-01

    We present a full Bayesian analysis of the combination of current neutrino oscillation, neutrinoless double beta decay and Cosmic Microwave Background observations. Our major goal is to carefully investigate the possibility to single out one neutrino mass ordering, namely Normal Ordering or Inverted Ordering, with current data. Two possible parametrizations (three neutrino masses versus the lightest neutrino mass plus the two oscillation mass splittings) and priors (linear versus logarithmic) are exhaustively examined. We find that the preference for NO is only driven by neutrino oscillation data. Moreover, the values of the Bayes factor indicate that the evidence for NO is strong only when the scan is performed over the three neutrino masses with logarithmic priors; for every other combination of parameterization and prior, the preference for NO is only weak. As a by-product of our Bayesian analyses, we are able to (a) compare the Bayesian bounds on the neutrino mixing parameters to those obtained by means of frequentist approaches, finding a very good agreement; (b) determine that the lightest neutrino mass plus the two mass splittings parametrization, motivated by the physical observables, is strongly preferred over the three neutrino mass eigenstates scan and (c) find that logarithmic priors guarantee a weakly-to-moderately more efficient sampling of the parameter space. These results establish the optimal strategy to successfully explore the neutrino parameter space, based on the use of the oscillation mass splittings and a logarithmic prior on the lightest neutrino mass, when combining neutrino oscillation data with cosmology and neutrinoless double beta decay. We also show that the limits on the total neutrino mass ∑ mν can change dramatically when moving from one prior to the other. These results have profound implications for future studies on the neutrino mass ordering, as they crucially state the need for self-consistent analyses which explore the

  5. Vague Sets Security Measure for Steganographic System Based on High-Order Markov Model

    Directory of Open Access Journals (Sweden)

    Chun-Juan Ouyang

    2017-01-01

    Full Text Available Security measure is of great importance in both steganography and steganalysis. Considering that statistical feature perturbations caused by steganography in an image are always nondeterministic and that an image is considered nonstationary, in this paper, the steganography is regarded as a fuzzy process. Here a steganographic security measure is proposed. This security measure evaluates the similarity between two vague sets of cover images and stego images in terms of n-order Markov chain to capture the interpixel correlation. The new security measure has proven to have the properties of boundedness, commutativity, and unity. Furthermore, the security measures of zero order, first order, second order, third order, and so forth are obtained by adjusting the order value of n-order Markov chain. Experimental results indicate that the larger n is, the better the measuring ability of the proposed security measure will be. The proposed security measure is more sensitive than other security measures defined under a deterministic distribution model, when the embedding is low. It is expected to provide a helpful guidance for designing secure steganographic algorithms or reliable steganalytic methods.

  6. Second-order sliding mode controller with model reference adaptation for automatic train operation

    Science.gov (United States)

    Ganesan, M.; Ezhilarasi, D.; Benni, Jijo

    2017-11-01

    In this paper, a new approach to model reference based adaptive second-order sliding mode control together with adaptive state feedback is presented to control the longitudinal dynamic motion of a high speed train for automatic train operation with the objective of minimal jerk travel by the passengers. The nonlinear dynamic model for the longitudinal motion of the train comprises of a locomotive and coach subsystems is constructed using multiple point-mass model by considering the forces acting on the vehicle. An adaptation scheme using Lyapunov criterion is derived to tune the controller gains by considering a linear, stable reference model that ensures the stability of the system in closed loop. The effectiveness of the controller tracking performance is tested under uncertain passenger load, coupler-draft gear parameters, propulsion resistance coefficients variations and environmental disturbances due to side wind and wet rail conditions. The results demonstrate improved tracking performance of the proposed control scheme with a least jerk under maximum parameter uncertainties when compared to constant gain second-order sliding mode control.

  7. A novel approach to quantifying the sensitivity of current and future cosmological datasets to the neutrino mass ordering through Bayesian hierarchical modeling

    Directory of Open Access Journals (Sweden)

    Martina Gerbino

    2017-12-01

    Full Text Available We present a novel approach to derive constraints on neutrino masses, as well as on other cosmological parameters, from cosmological data, while taking into account our ignorance of the neutrino mass ordering. We derive constraints from a combination of current as well as future cosmological datasets on the total neutrino mass Mν and on the mass fractions fν,i=mi/Mν (where the index i=1,2,3 indicates the three mass eigenstates carried by each of the mass eigenstates mi, after marginalizing over the (unknown neutrino mass ordering, either normal ordering (NH or inverted ordering (IH. The bounds on all the cosmological parameters, including those on the total neutrino mass, take therefore into account the uncertainty related to our ignorance of the mass hierarchy that is actually realized in nature. This novel approach is carried out in the framework of Bayesian analysis of a typical hierarchical problem, where the distribution of the parameters of the model depends on further parameters, the hyperparameters. In this context, the choice of the neutrino mass ordering is modeled via the discrete hyperparameter htype, which we introduce in the usual Markov chain analysis. The preference from cosmological data for either the NH or the IH scenarios is then simply encoded in the posterior distribution of the hyperparameter itself. Current cosmic microwave background (CMB measurements assign equal odds to the two hierarchies, and are thus unable to distinguish between them. However, after the addition of baryon acoustic oscillation (BAO measurements, a weak preference for the normal hierarchical scenario appears, with odds of 4:3 from Planck temperature and large-scale polarization in combination with BAO (3:2 if small-scale polarization is also included. Concerning next-generation cosmological experiments, forecasts suggest that the combination of upcoming CMB (COrE and BAO surveys (DESI may determine the neutrino mass hierarchy at a high

  8. Asymptotic behaviour of pion-pion total cross-sections

    International Nuclear Information System (INIS)

    Greynat, David; Rafael, Eduardo de; Vulvert, Grégory

    2014-01-01

    We derive a sum rule which shows that the Froissart-Martin bound for the asymptotic behaviour of the ππ total cross sections at high energies, if modulated by the Lukaszuk-Martin coefficient of the leading log 2  s behaviour, cannot be an optimal bound in QCD. We next compute the total cross sections for π + π − , π ± π 0 and π 0 π 0 scattering within the framework of the constituent chiral quark model (CχQM) in the limit of a large number of colours N c and discuss their asymptotic behaviours. The same ππ cross sections are also discussed within the general framework of Large-N c QCD and we show that it is possible to make an Ansatz for the isospin I=1 and I=0 spectrum which satisfy the Froissart-Martin bound with coefficients which, contrary to the Lukaszuk-Martin coefficient, are not singular in the chiral limit and have the correct Large-N c counting. We finally propose a simple phenomenological model which matches the low energy behaviours of the σ π ± π 0 total (s) cross section predicted by the CχQM with the high energy behaviour predicted by the Large-N c Ansatz. The magnitude of these cross sections at very high energies is of the order of those observed for the pp and pp-bar scattering total cross sections

  9. SECOND ORDER LEAST SQUARE ESTIMATION ON ARCH(1 MODEL WITH BOX-COX TRANSFORMED DEPENDENT VARIABLE

    Directory of Open Access Journals (Sweden)

    Herni Utami

    2014-03-01

    Full Text Available Box-Cox transformation is often used to reduce heterogeneity and to achieve a symmetric distribution of response variable. In this paper, we estimate the parameters of Box-Cox transformed ARCH(1 model using second-order leastsquare method and then we study the consistency and asymptotic normality for second-order least square (SLS estimators. The SLS estimation was introduced byWang (2003, 2004 to estimate the parameters of nonlinear regression models with independent and identically distributed errors

  10. 2nd-order optical model of the isotopic dependence of heavy ion absorption cross sections for radiation transport studies

    Science.gov (United States)

    Cucinotta, Francis A.; Yan, Congchong; Saganti, Premkumar B.

    2018-01-01

    Heavy ion absorption cross sections play an important role in radiation transport codes used in risk assessment and for shielding studies of galactic cosmic ray (GCR) exposures. Due to the GCR primary nuclei composition and nuclear fragmentation leading to secondary nuclei heavy ions of charge number, Z with 3 ≤ Z ≥ 28 and mass numbers, A with 6 ≤ A ≥ 60 representing about 190 isotopes occur in GCR transport calculations. In this report we describe methods for developing a data-base of isotopic dependent heavy ion absorption cross sections for interactions. Calculations of a 2nd-order optical model solution to coupled-channel solutions to the Eikonal form of the nucleus-nucleus scattering amplitude are compared to 1st-order optical model solutions. The 2nd-order model takes into account two-body correlations in the projectile and target ground-states, which are ignored in the 1st-order optical model. Parameter free predictions are described using one-body and two-body ground state form factors for the isotopes considered and the free nucleon-nucleon scattering amplitude. Root mean square (RMS) matter radii for protons and neutrons are taken from electron and muon scattering data and nuclear structure models. We report on extensive comparisons to experimental data for energy-dependent absorption cross sections for over 100 isotopes of elements from Li to Fe interacting with carbon and aluminum targets. Agreement between model and experiments are generally within 10% for the 1st-order optical model and improved to less than 5% in the 2nd-order optical model in the majority of comparisons. Overall the 2nd-order optical model leads to a reduction in absorption compared to the 1st-order optical model for heavy ion interactions, which influences estimates of nuclear matter radii.

  11. A curious example involving ordered compactifications

    Directory of Open Access Journals (Sweden)

    Thomas A. Richmond

    2002-10-01

    Full Text Available For a certain product X x Y where X is compact, connected, totally ordered space, we find that the semilattice K0 (X x Y of ordered compactifications of X x Y is isomorphic to a collection of Galois connections and to a collection of functions F which determines a quasi-uniformity on an extended set X U {+∞}, from which the topology and order on X is easily recovered. It is well-known that each ordered compactification of an ordered space X x Y corresponds to a totally bounded quasi-uniformity on X x Y compatible with the topology  and order on X x Y, and thus K0 (X x Y may be viewed as a collection of quasi-uniformities on X x Y. By the results here, these quasi-uniformities on X x Y determine a quasi-uniformity on the related space X U {+∞}.

  12. High-Order Model and Dynamic Filtering for Frame Rate Up-Conversion.

    Science.gov (United States)

    Bao, Wenbo; Zhang, Xiaoyun; Chen, Li; Ding, Lianghui; Gao, Zhiyong

    2018-08-01

    This paper proposes a novel frame rate up-conversion method through high-order model and dynamic filtering (HOMDF) for video pixels. Unlike the constant brightness and linear motion assumptions in traditional methods, the intensity and position of the video pixels are both modeled with high-order polynomials in terms of time. Then, the key problem of our method is to estimate the polynomial coefficients that represent the pixel's intensity variation, velocity, and acceleration. We propose to solve it with two energy objectives: one minimizes the auto-regressive prediction error of intensity variation by its past samples, and the other minimizes video frame's reconstruction error along the motion trajectory. To efficiently address the optimization problem for these coefficients, we propose the dynamic filtering solution inspired by video's temporal coherence. The optimal estimation of these coefficients is reformulated into a dynamic fusion of the prior estimate from pixel's temporal predecessor and the maximum likelihood estimate from current new observation. Finally, frame rate up-conversion is implemented using motion-compensated interpolation by pixel-wise intensity variation and motion trajectory. Benefited from the advanced model and dynamic filtering, the interpolated frame has much better visual quality. Extensive experiments on the natural and synthesized videos demonstrate the superiority of HOMDF over the state-of-the-art methods in both subjective and objective comparisons.

  13. DETERMINANTS OF SOVEREIGN RATING: FACTOR BASED ORDERED PROBIT MODELS FOR PANEL DATA ANALYSIS MODELING FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Dilek Teker

    2013-01-01

    Full Text Available The aim of this research is to compose a new rating methodology and provide credit notches to 23 countries which of 13 are developed and 10 are emerging. There are various literature that explains the determinants of credit ratings. Following the literature, we select 11 variables for our model which of 5 are eliminated by the factor analysis. We use specific dummies to investigate the structural breaks in time and cross section such as pre crises, post crises, BRIC membership, EU membership, OPEC membership, shipbuilder country and platinum reserved country. Then we run an ordered probit model and give credit notches to the countries. We use FITCH ratings as benchmark. Thus, at the end we compare the notches of FITCH with the ones we derive out of our estimated model.

  14. Generalized Bragg-Williams model for the size-dependent order-disorder transition of bimetallic nanoparticles

    International Nuclear Information System (INIS)

    Li, Y J; Qi, W H; Wang, M P; Liu, J F; Xiong, S Y; Huang, B Y

    2011-01-01

    Considering the different effects of exterior atoms (face, edge and corner atoms), the Bragg-Williams model is generalized to account for the size, shape and composition-dependent order-disorder transition of bimetallic nanoparticles (NPs) with B 2 , L1 0 and L1 2 ordered structures. The results show that the order-disorder temperatures T C,p are different for different shapes even in the identical particle size. The order of order-disorder temperatures of different shapes varies for different sizes. The long-range order parameter decreases with the increase in temperature in all size ranges and decreases smoothly in large sizes, but drops dramatically in small sizes. Moreover, it is also found that the order-disorder temperature of bimetallic NPs rises with increasing particle sizes and decreases with a deviation from the ideal compositions. The present predictions are consistent with the available literature results, indicating its capability in predicting other order-disorder transition phenomena of bimetallic NPs.

  15. A Comparison Of Joint Ordering Rule And Other Inventory Order Systems

    OpenAIRE

    ÖZGEN, Hüseyin

    2013-01-01

    The typical manuracturing corporation has about fourty or fifty percent of its total assets invested in inventory items Because of this reason inventory control is considered to be one of the most important problems that deserves a special attention of top management There are several diferent inventory control techniques that can be used in inventory management The joint ordering rule discused here is some of the most powerful techniques This paper presents a comparison of joint order...

  16. Effects of the Rabdosia rubescens total flavonoids on focal cerebral ischemia reperfusion model in rats

    Directory of Open Access Journals (Sweden)

    Mingsan Miao

    2017-05-01

    Full Text Available The effect of the Rabdosia rubescens total flavonoids on focal cerebral ischemia reperfusion model in rats was observed. The model group, nimodipine group, cerebral collateral group, and large, medium and small dose group of the Rabdosia rubescens total flavonoids were administered with corresponding drugs but sham operation group and model group were administered the same volume of 0.5%CMC, 1 times a day, continuous administration of 7 d. After 1 h at 7 d to medicine, left incision in the middle of the neck of rats after anesthesia, we can firstly expose and isolate the left common carotid artery (CCA, and then expose external carotid artery (ECA and internal carotid artery (ICA. The common carotid artery and the external carotid artery are ligated. Then internal carotid artery with arterial clamp is temporarily clipped. Besides, cut the incision of 0.2 mm from 5 cm of the bifurcation of the common carotid artery. A thread Line bolt is inserted with more than 18–20 mm from bifurcation of CCA into the internal carotid artery until there is resistance. Then the entrance of the middle cerebral artery is blocked and internal carotid artery is ligated (the blank group only exposed the left blood vessel without Plugging wire. Finally it is gently pulled out the plug line after 2 h. Results: Compared with the model mice, Rabdosia rubescens total flavonoids can significantly relieve the injury of brain in hippocampus and cortex nerve cells; experimental rat focal cerebral ischemia was to improve again perfusion model of nerve function defect score mortality; significantly reduce brain homogenate NOS activity and no content, MDA, IL-1, TNF-a, ICAM-1 content; increase in brain homogenate SOD and ATPase activity (P < 0.05, P < 0.01; and reduce the serum S-100β protein content. Each dose group of the Rabdosia rubescens total flavonoids has a better Improvement effect on focal cerebral ischemia reperfusion model in rats.

  17. Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling

    Directory of Open Access Journals (Sweden)

    Eric R. Edelman

    2017-06-01

    Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related

  18. Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.

    Science.gov (United States)

    Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A

    2017-01-01

    For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.

  19. A dynamic neural field model of temporal order judgments.

    Science.gov (United States)

    Hecht, Lauren N; Spencer, John P; Vecera, Shaun P

    2015-12-01

    Temporal ordering of events is biased, or influenced, by perceptual organization-figure-ground organization-and by spatial attention. For example, within a region assigned figural status or at an attended location, onset events are processed earlier (Lester, Hecht, & Vecera, 2009; Shore, Spence, & Klein, 2001), and offset events are processed for longer durations (Hecht & Vecera, 2011; Rolke, Ulrich, & Bausenhart, 2006). Here, we present an extension of a dynamic field model of change detection (Johnson, Spencer, Luck, & Schöner, 2009; Johnson, Spencer, & Schöner, 2009) that accounts for both the onset and offset performance for figural and attended regions. The model posits that neural populations processing the figure are more active, resulting in a peak of activation that quickly builds toward a detection threshold when the onset of a target is presented. This same enhanced activation for some neural populations is maintained when a present target is removed, creating delays in the perception of the target's offset. We discuss the broader implications of this model, including insights regarding how neural activation can be generated in response to the disappearance of information. (c) 2015 APA, all rights reserved).

  20. Modeling real shim fields for very high degree (and order) B0 shimming of the human brain at 9.4 T.

    Science.gov (United States)

    Chang, Paul; Nassirpour, Sahar; Henning, Anke

    2018-01-01

    To describe the process of calibrating a B 0 shim system using high-degree (or high order) spherical harmonic models of the measured shim fields, to provide a method that considers amplitude dependency of these models, and to show the advantage of very high-degree B 0 shimming for whole-brain and single-slice applications at 9.4 Tesla (T). An insert shim with up to fourth and partial fifth/sixth degree (order) spherical harmonics was used with a Siemens 9.4T scanner. Each shim field was measured and modeled as input for the shimming algorithm. Optimal shim currents can therefore be calculated in a single iteration. A range of shim currents was used in the modeling to account for possible amplitude nonlinearities. The modeled shim fields were used to compare different degrees of whole-brain B 0 shimming on healthy subjects. The ideal shim fields did not correctly shim the subject brains. However, using the modeled shim fields improved the B 0 homogeneity from 55.1 (second degree) to 44.68 Hz (partial fifth/sixth degree) on the whole brains of 9 healthy volunteers, with a total applied current of 0.77 and 6.8 A, respectively. The necessity of calibrating the shim system was shown. Better B 0 homogeneity drastically reduces signal dropout and distortions for echo-planar imaging, and significantly improves the linewidths of MR spectroscopy imaging. Magn Reson Med 79:529-540, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

  1. Tsunami generation, propagation, and run-up with a high-order Boussinesq model

    DEFF Research Database (Denmark)

    Fuhrman, David R.; Madsen, Per A.

    2009-01-01

    In this work we extend a high-order Boussinesq-type (finite difference) model, capable of simulating waves out to wavenumber times depth kh landslide-induced tsunamis. The extension is straight forward, requiring only....... The Boussinesq-type model is then used to simulate numerous tsunami-type events generated from submerged landslides, in both one and two horizontal dimensions. The results again compare well against previous experiments and/or numerical simulations. The new extension compliments recently developed run...

  2. Influence of time delay on fractional-order PI-controlled system for a second-order oscillatory plant model with time delay

    Directory of Open Access Journals (Sweden)

    Sadalla Talar

    2017-12-01

    Full Text Available The paper aims at presenting the influence of an open-loop time delay on the stability and tracking performance of a second-order open-loop system and continuoustime fractional-order PI controller. The tuning method of this controller is based on Hermite- Biehler and Pontryagin theorems, and the tracking performance is evaluated on the basis of two integral performance indices, namely IAE and ISE. The paper extends the results and methodology presented in previous work of the authors to analysis of the influence of time delay on the closed-loop system taking its destabilizing properties into account, as well as concerning possible application of the presented results and used models.

  3. High order Fuchsian equations for the square lattice Ising model: χ-tilde(5)

    International Nuclear Information System (INIS)

    Bostan, A; Boukraa, S; Guttmann, A J; Jensen, I; Hassani, S; Zenine, N; Maillard, J-M

    2009-01-01

    We consider the Fuchsian linear differential equation obtained (modulo a prime) for χ-tilde (5) , the five-particle contribution to the susceptibility of the square lattice Ising model. We show that one can understand the factorization of the corresponding linear differential operator from calculations using just a single prime. A particular linear combination of χ-tilde (1) and χ-tilde (3) can be removed from χ-tilde (5) and the resulting series is annihilated by a high order globally nilpotent linear ODE. The corresponding (minimal order) linear differential operator, of order 29, splits into factors of small orders. A fifth-order linear differential operator occurs as the left-most factor of the 'depleted' differential operator and it is shown to be equivalent to the symmetric fourth power of L E , the linear differential operator corresponding to the elliptic integral E. This result generalizes what we have found for the lower order terms χ-tilde (3) and χ-tilde (4) . We conjecture that a linear differential operator equivalent to a symmetric (n - 1) th power of L E occurs as a left-most factor in the minimal order linear differential operators for all χ-tilde (n) 's

  4. A Structural Equation Model of Customer Satisfaction and Future Purchase of Mail-Order Speciality Food

    Directory of Open Access Journals (Sweden)

    Mai, L.W.

    2006-01-01

    Full Text Available Analyses the relationship between satisfaction with mail-order speciality food attributes, overall satisfaction, and likelihood of future purchase using a structural equation model. The results indicate that customer satisfaction is associated with both service and product features of mail order speciality food.

  5. A Time Scheduling Model of Logistics Service Supply Chain Based on the Customer Order Decoupling Point: A Perspective from the Constant Service Operation Time

    Science.gov (United States)

    Yang, Yi; Xu, Haitao; Liu, Xiaoyan; Wang, Yijia; Liang, Zhicheng

    2014-01-01

    In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC. PMID:24715818

  6. A time scheduling model of logistics service supply chain based on the customer order decoupling point: a perspective from the constant service operation time.

    Science.gov (United States)

    Liu, Weihua; Yang, Yi; Xu, Haitao; Liu, Xiaoyan; Wang, Yijia; Liang, Zhicheng

    2014-01-01

    In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC.

  7. First-Order SPICE Modeling of Extreme-Temperature 4H-SiC JFET Integrated Circuits

    Science.gov (United States)

    Neudeck, Philip G.; Spry, David J.; Chen, Liang-Yu

    2016-01-01

    A separate submission to this conference reports that 4H-SiC Junction Field Effect Transistor (JFET) digital and analog Integrated Circuits (ICs) with two levels of metal interconnect have reproducibly demonstrated electrical operation at 500 C in excess of 1000 hours. While this progress expands the complexity and durability envelope of high temperature ICs, one important area for further technology maturation is the development of reasonably accurate and accessible computer-aided modeling and simulation tools for circuit design of these ICs. Towards this end, we report on development and verification of 25 C to 500 C SPICE simulation models of first order accuracy for this extreme-temperature durable 4H-SiC JFET IC technology. For maximum availability, the JFET IC modeling is implemented using the baseline-version SPICE NMOS LEVEL 1 model that is common to other variations of SPICE software and importantly includes the body-bias effect. The first-order accuracy of these device models is verified by direct comparison with measured experimental device characteristics.

  8. A study of the one dimensional total generalised variation regularisation problem

    KAUST Repository

    Papafitsoros, Konstantinos

    2015-03-01

    © 2015 American Institute of Mathematical Sciences. In this paper we study the one dimensional second order total generalised variation regularisation (TGV) problem with L2 data fitting term. We examine the properties of this model and we calculate exact solutions using simple piecewise affine functions as data terms. We investigate how these solutions behave with respect to the TGV parameters and we verify our results using numerical experiments.

  9. A study of the one dimensional total generalised variation regularisation problem

    KAUST Repository

    Papafitsoros, Konstantinos; Bredies, Kristian

    2015-01-01

    © 2015 American Institute of Mathematical Sciences. In this paper we study the one dimensional second order total generalised variation regularisation (TGV) problem with L2 data fitting term. We examine the properties of this model and we calculate exact solutions using simple piecewise affine functions as data terms. We investigate how these solutions behave with respect to the TGV parameters and we verify our results using numerical experiments.

  10. A semi-implicit, second-order-accurate numerical model for multiphase underexpanded volcanic jets

    Directory of Open Access Journals (Sweden)

    S. Carcano

    2013-11-01

    Full Text Available An improved version of the PDAC (Pyroclastic Dispersal Analysis Code, Esposti Ongaro et al., 2007 numerical model for the simulation of multiphase volcanic flows is presented and validated for the simulation of multiphase volcanic jets in supersonic regimes. The present version of PDAC includes second-order time- and space discretizations and fully multidimensional advection discretizations in order to reduce numerical diffusion and enhance the accuracy of the original model. The model is tested on the problem of jet decompression in both two and three dimensions. For homogeneous jets, numerical results are consistent with experimental results at the laboratory scale (Lewis and Carlson, 1964. For nonequilibrium gas–particle jets, we consider monodisperse and bidisperse mixtures, and we quantify nonequilibrium effects in terms of the ratio between the particle relaxation time and a characteristic jet timescale. For coarse particles and low particle load, numerical simulations well reproduce laboratory experiments and numerical simulations carried out with an Eulerian–Lagrangian model (Sommerfeld, 1993. At the volcanic scale, we consider steady-state conditions associated with the development of Vulcanian and sub-Plinian eruptions. For the finest particles produced in these regimes, we demonstrate that the solid phase is in mechanical and thermal equilibrium with the gas phase and that the jet decompression structure is well described by a pseudogas model (Ogden et al., 2008. Coarse particles, on the other hand, display significant nonequilibrium effects, which associated with their larger relaxation time. Deviations from the equilibrium regime, with maximum velocity and temperature differences on the order of 150 m s−1 and 80 K across shock waves, occur especially during the rapid acceleration phases, and are able to modify substantially the jet dynamics with respect to the homogeneous case.

  11. Study of p-4He Total Reaction cross section using Glauber and Modified Glauber Models

    International Nuclear Information System (INIS)

    Tag El Din, I.M.A.; Taha, M.M.; Hassan, S.S.A.

    2012-01-01

    The total nuclear reaction cross-section for p - 4 He in the energy range from 25 to 1000 MeV is calculated within Glauber and modified Glauber models. The modified Glauber model is introduced via both Coulomb trajectory of the projectile and calculation of the effective radius of interaction. The effects of density dependent total cross-section and phase variation of nucleon-nucleon scattering amplitude are studied. It is pointed out that the phase variation of the nucleon-nucleon amplitude plays a significant role in describing σR at E p 2 at e = e0 = 0 and γ=2fm 2 at e = e0 = 0.17fm -3 .

  12. Second-order gauge-invariant perturbations during inflation

    International Nuclear Information System (INIS)

    Finelli, F.; Marozzi, G.; Vacca, G. P.; Venturi, G.

    2006-01-01

    The evolution of gauge invariant second-order scalar perturbations in a general single field inflationary scenario are presented. Different second-order gauge-invariant expressions for the curvature are considered. We evaluate perturbatively one of these second order curvature fluctuations and a second-order gauge-invariant scalar field fluctuation during the slow-roll stage of a massive chaotic inflationary scenario, taking into account the deviation from a pure de Sitter evolution and considering only the contribution of super-Hubble perturbations in mode-mode coupling. The spectra resulting from their contribution to the second order quantum correlation function are nearly scale-invariant, with additional logarithmic corrections with respect to the first order spectrum. For all scales of interest the amplitude of these spectra depends on the total number of e-folds. We find, on comparing first and second order perturbation results, an upper limit to the total number of e-folds beyond which the two orders are comparable

  13. Structure of ordered and disordered α-brass

    International Nuclear Information System (INIS)

    Mu''ller, S.; Zunger, Alex

    2001-01-01

    Alloys of copper and zinc (brass) have been widely used since Neolithic times due to the discovery that unlike regular copper this alloy can be worked ''cold'' around a 3:1 copper-to-zinc ratio. While it is now known that the as-grown system is a disordered fcc solid solution, no 3:1 ordered phase has yet been directly observed even though the negative mixing enthalpy of the disordered alloy suggests ordering tendencies. Moreover, neutron scattering experiments have been deduced that this disordered alloy contains peculiar chains of Zn atoms. We have expressed the first-principles calculated total energy of general Cu-Zn fcc-lattice configurations using a mixed-space cluster expansion. Application of Monte Carlo--simulated annealing to this generalized Ising-like Hamiltonian produces the predicted low-temperature ground state as well as finite-temperature phase diagram and short-range order. We find (i) that at low temperature the disordered fcc alloy will order into the DO 23 structure, (ii) the high-temperature short-range order in close agreement with experiment, and (iii) chains of Zn atoms in the [001] direction, as seen experimentally. Furthermore, our model allows a detailed study of the influence and importance of strain on the phase stability

  14. Compiler-Directed Transformation for Higher-Order Stencils

    Energy Technology Data Exchange (ETDEWEB)

    Basu, Protonu [Univ. of Utah, Salt Lake City, UT (United States); Hall, Mary [Univ. of Utah, Salt Lake City, UT (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Straalen, Brian Van [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Colella, Phillip [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-07-20

    As the cost of data movement increasingly dominates performance, developers of finite-volume and finite-difference solutions for partial differential equations (PDEs) are exploring novel higher-order stencils that increase numerical accuracy and computational intensity. This paper describes a new compiler reordering transformation applied to stencil operators that performs partial sums in buffers, and reuses the partial sums in computing multiple results. This optimization has multiple effect son improving stencil performance that are particularly important to higher-order stencils: exploits data reuse, reduces floating-point operations, and exposes efficient SIMD parallelism to backend compilers. We study the benefit of this optimization in the context of Geometric Multigrid (GMG), a widely used method to solvePDEs, using four different Jacobi smoothers built from 7-, 13-, 27-and 125-point stencils. We quantify performance, speedup, andnumerical accuracy, and use the Roofline model to qualify our results. Ultimately, we obtain over 4× speedup on the smoothers themselves and up to a 3× speedup on the multigrid solver. Finally, we demonstrate that high-order multigrid solvers have the potential of reducing total data movement and energy by several orders of magnitude.

  15. Generalizing the order and the parameters of macro-operators by explanation-based learning - Extension of Explanation-Based Learning on Partial Order

    International Nuclear Information System (INIS)

    Li, Huihua

    1992-01-01

    The traditional generalization methods such as FIKE's macro-operator learning and Explanation-Based Learning (EBL) deal with totally ordered plans. They generalize only the plan operators and the conditions under which the generalized plan can be applied in its initial total order, but not the partial order among operators in which the generalized plan can be successfully executed. In this paper, we extend the notion of the EBL on the partial order of plans. A new method is presented for learning, from a totally or partially ordered plan, partially ordered macro-operators (generalized plans) each of which requires a set of the weakest conditions for its reuse. It is also valuable for generalizing partially ordered plans. The operators are generalized in the FIKE's triangle table. We introduce the domain axioms to generate the constraints for the consistency of generalized states. After completing the triangle table with the information concerning the operator destructions (interactions), we obtain the global explanation of the partial order on the operators. Then, we represent all the necessary ordering relations by a directed graph. The exploitation of this graph permits to explicate the dependence between the partial orders and the constraints among the parameters of generalized operators, and allows all the solutions to be obtained. (author) [fr

  16. A unified model for transfer alignment at random misalignment angles based on second-order EKF

    International Nuclear Information System (INIS)

    Cui, Xiao; Qin, Yongyuan; Yan, Gongmin; Liu, Zhenbo; Mei, Chunbo

    2017-01-01

    In the transfer alignment process of inertial navigation systems (INSs), the conventional linear error model based on the small misalignment angle assumption cannot be applied to large misalignment situations. Furthermore, the nonlinear model based on the large misalignment angle suffers from redundant computation with nonlinear filters. This paper presents a unified model for transfer alignment suitable for arbitrary misalignment angles. The alignment problem is transformed into an estimation of the relative attitude between the master INS (MINS) and the slave INS (SINS), by decomposing the attitude matrix of the latter. Based on the Rodriguez parameters, a unified alignment model in the inertial frame with the linear state-space equation and a second order nonlinear measurement equation are established, without making any assumptions about the misalignment angles. Furthermore, we employ the Taylor series expansions on the second-order nonlinear measurement equation to implement the second-order extended Kalman filter (EKF2). Monte-Carlo simulations demonstrate that the initial alignment can be fulfilled within 10 s, with higher accuracy and much smaller computational cost compared with the traditional unscented Kalman filter (UKF) at large misalignment angles. (paper)

  17. A unified model for transfer alignment at random misalignment angles based on second-order EKF

    Science.gov (United States)

    Cui, Xiao; Mei, Chunbo; Qin, Yongyuan; Yan, Gongmin; Liu, Zhenbo

    2017-04-01

    In the transfer alignment process of inertial navigation systems (INSs), the conventional linear error model based on the small misalignment angle assumption cannot be applied to large misalignment situations. Furthermore, the nonlinear model based on the large misalignment angle suffers from redundant computation with nonlinear filters. This paper presents a unified model for transfer alignment suitable for arbitrary misalignment angles. The alignment problem is transformed into an estimation of the relative attitude between the master INS (MINS) and the slave INS (SINS), by decomposing the attitude matrix of the latter. Based on the Rodriguez parameters, a unified alignment model in the inertial frame with the linear state-space equation and a second order nonlinear measurement equation are established, without making any assumptions about the misalignment angles. Furthermore, we employ the Taylor series expansions on the second-order nonlinear measurement equation to implement the second-order extended Kalman filter (EKF2). Monte-Carlo simulations demonstrate that the initial alignment can be fulfilled within 10 s, with higher accuracy and much smaller computational cost compared with the traditional unscented Kalman filter (UKF) at large misalignment angles.

  18. 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.

  19. Statistical identification with hidden Markov models of large order splitting strategies in an equity market

    Science.gov (United States)

    Vaglica, Gabriella; Lillo, Fabrizio; Mantegna, Rosario N.

    2010-07-01

    Large trades in a financial market are usually split into smaller parts and traded incrementally over extended periods of time. We address these large trades as hidden orders. In order to identify and characterize hidden orders, we fit hidden Markov models to the time series of the sign of the tick-by-tick inventory variation of market members of the Spanish Stock Exchange. Our methodology probabilistically detects trading sequences, which are characterized by a significant majority of buy or sell transactions. We interpret these patches of sequential buying or selling transactions as proxies of the traded hidden orders. We find that the time, volume and number of transaction size distributions of these patches are fat tailed. Long patches are characterized by a large fraction of market orders and a low participation rate, while short patches have a large fraction of limit orders and a high participation rate. We observe the existence of a buy-sell asymmetry in the number, average length, average fraction of market orders and average participation rate of the detected patches. The detected asymmetry is clearly dependent on the local market trend. We also compare the hidden Markov model patches with those obtained with the segmentation method used in Vaglica et al (2008 Phys. Rev. E 77 036110), and we conclude that the former ones can be interpreted as a partition of the latter ones.

  20. Mixed-order phase transition in a two-step contagion model with a single infectious seed.

    Science.gov (United States)

    Choi, Wonjun; Lee, Deokjae; Kahng, B

    2017-02-01

    Percolation is known as one of the most robust continuous transitions, because its occupation rule is intrinsically local. As one of the ways to break the robustness, occupation is allowed to more than one species of particles and they occupy cooperatively. This generalized percolation model undergoes a discontinuous transition. Here we investigate an epidemic model with two contagion steps and characterize its phase transition analytically and numerically. We find that even though the order parameter jumps at a transition point r_{c}, then increases continuously, it does not exhibit any critical behavior: the fluctuations of the order parameter do not diverge at r_{c}. However, critical behavior appears in mean outbreak size, which diverges at the transition point in a manner that the ordinary percolation shows. Such a type of phase transition is regarded as a mixed-order phase transition. We also obtain scaling relations of cascade outbreak statistics when the order parameter jumps at r_{c}.

  1. 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)

  2. 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)

  3. On the long-range order of Lieb-Mattis model of quantum antiferromagnet

    International Nuclear Information System (INIS)

    Gochev, I.G.; Tonchev, N.S.

    1991-09-01

    The spontaneous magnetization m and the root-mean-square order parameter m 0 of the Lieb-Mattis model for arbitrary temperature and spin values s are obtained. For the ratio r(T,s)=m/m 0 the value r(T,s)=√3 is found. (author). 8 refs

  4. 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

  5. Analytical and Numerical solutions of a nonlinear alcoholism model via variable-order fractional differential equations

    Science.gov (United States)

    Gómez-Aguilar, J. F.

    2018-03-01

    In this paper, we analyze an alcoholism model which involves the impact of Twitter via Liouville-Caputo and Atangana-Baleanu-Caputo fractional derivatives with constant- and variable-order. Two fractional mathematical models are considered, with and without delay. Special solutions using an iterative scheme via Laplace and Sumudu transform were obtained. We studied the uniqueness and existence of the solutions employing the fixed point postulate. The generalized model with variable-order was solved numerically via the Adams method and the Adams-Bashforth-Moulton scheme. Stability and convergence of the numerical solutions were presented in details. Numerical examples of the approximate solutions are provided to show that the numerical methods are computationally efficient. Therefore, by including both the fractional derivatives and finite time delays in the alcoholism model studied, we believe that we have established a more complete and more realistic indicator of alcoholism model and affect the spread of the drinking.

  6. 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

  7. 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

  8. First-order dynamical phase transition in models of glasses: an approach based on ensembles of histories

    International Nuclear Information System (INIS)

    Garrahan, Juan P; Jack, Robert L; Lecomte, Vivien; Duijvendijk, Kristina van; Wijland, Frederic van; Pitard, Estelle

    2009-01-01

    We investigate the dynamics of kinetically constrained models of glass formers by analysing the statistics of trajectories of the dynamics, or histories, using large deviation function methods. We show that, in general, these models exhibit a first-order dynamical transition between active and inactive dynamical phases. We argue that the dynamical heterogeneities displayed by these systems are a manifestation of dynamical first-order phase coexistence. In particular, we calculate dynamical large deviation functions, both analytically and numerically, for the Fredrickson-Andersen model, the East model, and constrained lattice gas models. We also show how large deviation functions can be obtained from a Landau-like theory for dynamical fluctuations. We discuss possibilities for similar dynamical phase-coexistence behaviour in other systems with heterogeneous dynamics

  9. Building and Running the Yucca Mountain Total System Performance Model in a Quality Environment

    International Nuclear Information System (INIS)

    D.A. Kalinich; K.P. Lee; J.A. McNeish

    2005-01-01

    A Total System Performance Assessment (TSPA) model has been developed to support the Safety Analysis Report (SAR) for the Yucca Mountain High-Level Waste Repository. The TSPA model forecasts repository performance over a 20,000-year simulation period. It has a high degree of complexity due to the complexity of its underlying process and abstraction models. This is reflected in the size of the model (a 27,000 element GoldSim file), its use of dynamic-linked libraries (14 DLLs), the number and size of its input files (659 files totaling 4.7 GB), and the number of model input parameters (2541 input database entries). TSPA model development and subsequent simulations with the final version of the model were performed to a set of Quality Assurance (QA) procedures. Due to the complexity of the model, comments on previous TSPAs, and the number of analysts involved (22 analysts in seven cities across four time zones), additional controls for the entire life-cycle of the TSPA model, including management, physical, model change, and input controls were developed and documented. These controls did not replace the QA. procedures, rather they provided guidance for implementing the requirements of the QA procedures with the specific intent of ensuring that the model development process and the simulations performed with the final version of the model had sufficient checking, traceability, and transparency. Management controls were developed to ensure that only management-approved changes were implemented into the TSPA model and that only management-approved model runs were performed. Physical controls were developed to track the use of prototype software and preliminary input files, and to ensure that only qualified software and inputs were used in the final version of the TSPA model. In addition, a system was developed to name, file, and track development versions of the TSPA model as well as simulations performed with the final version of the model

  10. Low-order modelling of a drop on a highly-hydrophobic substrate: statics and dynamics

    Science.gov (United States)

    Wray, Alexander W.; Matar, Omar K.; Davis, Stephen H.

    2017-11-01

    We analyse the behaviour of droplets resting on highly-hydrophobic substrates. This problem is of practical interest due to its appearance in many physical contexts involving the spreading, wetting, and dewetting of fluids on solid substrates. In mathematical terms, it exhibits an interesting challenge as the interface is multi-valued as a function of the natural Cartesian co-ordinates, presenting a stumbling block to typical low-order modelling techniques. Nonetheless, we show that in the static case, the interfacial shape is governed by the Young-Laplace equation, which may be solved explicitly in terms of elliptic functions. We present simple low-order expressions that faithfully reproduce the shapes. We then consider the dynamic case, showing that the predictions of our low-order model compare favourably with those obtained from direct numerical simulations. We also examine the characteristic flow regimes of interest. EPSRC, UK, MEMPHIS program Grant (EP/K003976/1), RAEng Research Chair (OKM).

  11. Ordered groups and infinite permutation groups

    CERN Document Server

    1996-01-01

    The subjects of ordered groups and of infinite permutation groups have long en­ joyed a symbiotic relationship. Although the two subjects come from very different sources, they have in certain ways come together, and each has derived considerable benefit from the other. My own personal contact with this interaction began in 1961. I had done Ph. D. work on sequence convergence in totally ordered groups under the direction of Paul Conrad. In the process, I had encountered "pseudo-convergent" sequences in an ordered group G, which are like Cauchy sequences, except that the differences be­ tween terms of large index approach not 0 but a convex subgroup G of G. If G is normal, then such sequences are conveniently described as Cauchy sequences in the quotient ordered group GIG. If G is not normal, of course GIG has no group structure, though it is still a totally ordered set. The best that can be said is that the elements of G permute GIG in an order-preserving fashion. In independent investigations around that t...

  12. Dynamics and phenomenology of higher order gravity cosmological models

    Science.gov (United States)

    Moldenhauer, Jacob Andrew

    2010-10-01

    I present here some new results about a systematic approach to higher-order gravity (HOG) cosmological models. The HOG models are derived from curvature invariants that are more general than the Einstein-Hilbert action. Some of the models exhibit late-time cosmic acceleration without the need for dark energy and fit some current observations. The open question is that there are an infinite number of invariants that one could select, and many of the published papers have stressed the need to find a systematic approach that will allow one to study methodically the various possibilities. We explore a new connection that we made between theorems from the theory of invariants in general relativity and these cosmological models. In summary, the theorems demonstrate that curvature invariants are not all independent from each other and that for a given Ricci Segre type and Petrov type (symmetry classification) of the space-time, there exists a complete minimal set of independent invariants (a basis) in terms of which all the other invariants can be expressed. As an immediate consequence of the proposed approach, the number of invariants to consider is dramatically reduced from infinity to four invariants in the worst case and to only two invariants in the cases of interest, including all Friedmann-Lemaitre-Robertson-Walker metrics. We derive models that pass stability and physical acceptability conditions. We derive dynamical equations and phase portrait analyses that show the promise of the systematic approach. We consider observational constraints from magnitude-redshift Supernovae Type Ia data, distance to the last scattering surface of the Cosmic Microwave Background radiation, and Baryon Acoustic Oscillations. We put observational constraints on general HOG models. We constrain different forms of the Gauss-Bonnet, f(G), modified gravity models with these observations. We show some of these models pass solar system tests. We seek to find models that pass physical and

  13. Fractional order models of viscoelasticity as an alternative in the analysis of red blood cell (RBC) membrane mechanics.

    Science.gov (United States)

    Craiem, Damian; Magin, Richard L

    2010-01-20

    New lumped-element models of red blood cell mechanics can be constructed using fractional order generalizations of springs and dashpots. Such 'spring-pots' exhibit a fractional order viscoelastic behavior that captures a wide spectrum of experimental results through power-law expressions in both the time and frequency domains. The system dynamics is fully described by linear fractional order differential equations derived from first order stress-strain relationships using the tools of fractional calculus. Changes in the composition or structure of the membrane are conveniently expressed in the fractional order of the model system. This approach provides a concise way to describe and quantify the biomechanical behavior of membranes, cells and tissues.

  14. Lattice Supersymmetry and Order-Disorder Coexistence in the Tricritical Ising Model

    Science.gov (United States)

    O'Brien, Edward; Fendley, Paul

    2018-05-01

    We introduce and analyze a quantum spin or Majorana chain with a tricritical Ising point separating a critical phase from a gapped phase with order-disorder coexistence. We show that supersymmetry is not only an emergent property of the scaling limit but also manifests itself on the lattice. Namely, we find explicit lattice expressions for the supersymmetry generators and currents. Writing the Hamiltonian in terms of these generators allows us to find the ground states exactly at a frustration-free coupling. These confirm the coexistence between two (topologically) ordered ground states and a disordered one in the gapped phase. Deforming the model by including explicit chiral symmetry breaking, we find the phases persist up to an unusual chiral phase transition where the supersymmetry becomes exact even on the lattice.

  15. 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.

  16. Control-oriented reduced order modeling of dipteran flapping flight

    Science.gov (United States)

    Faruque, Imraan

    Flying insects achieve flight stabilization and control in a manner that requires only small, specialized neural structures to perform the essential components of sensing and feedback, achieving unparalleled levels of robust aerobatic flight on limited computational resources. An engineering mechanism to replicate these control strategies could provide a dramatic increase in the mobility of small scale aerial robotics, but a formal investigation has not yet yielded tools that both quantitatively and intuitively explain flapping wing flight as an "input-output" relationship. This work uses experimental and simulated measurements of insect flight to create reduced order flight dynamics models. The framework presented here creates models that are relevant for the study of control properties. The work begins with automated measurement of insect wing motions in free flight, which are then used to calculate flight forces via an empirically-derived aerodynamics model. When paired with rigid body dynamics and experimentally measured state feedback, both the bare airframe and closed loop systems may be analyzed using frequency domain system identification. Flight dynamics models describing maneuvering about hover and cruise conditions are presented for example fruit flies (Drosophila melanogaster) and blowflies (Calliphorids). The results show that biologically measured feedback paths are appropriate for flight stabilization and sexual dimorphism is only a minor factor in flight dynamics. A method of ranking kinematic control inputs to maximize maneuverability is also presented, showing that the volume of reachable configurations in state space can be dramatically increased due to appropriate choice of kinematic inputs.

  17. Dose optimization with first-order total-variation minimization for dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hojin; Li Ruijiang; Lee, Rena; Goldstein, Thomas; Boyd, Stephen; Candes, Emmanuel; Xing Lei [Department of Electrical Engineering, Stanford University, Stanford, California 94305-9505 (United States) and Department of Radiation Oncology, Stanford University, Stanford, California 94305-5847 (United States); Department of Radiation Oncology, Stanford University, Stanford, California 94305-5847 (United States); Department of Radiation Oncology, Ehwa University, Seoul 158-710 (Korea, Republic of); Department of Electrical Engineering, Stanford University, Stanford, California 94305-9505 (United States); Department of Statistics, Stanford University, Stanford, California 94305-4065 (United States); Department of Radiation Oncology, Stanford University, Stanford, California 94305-5304 (United States)

    2012-07-15

    Purpose: A new treatment scheme coined as dense angularly sampled and sparse intensity modulated radiation therapy (DASSIM-RT) has recently been proposed to bridge the gap between IMRT and VMAT. By increasing the angular sampling of radiation beams while eliminating dispensable segments of the incident fields, DASSIM-RT is capable of providing improved conformity in dose distributions while maintaining high delivery efficiency. The fact that DASSIM-RT utilizes a large number of incident beams represents a major computational challenge for the clinical applications of this powerful treatment scheme. The purpose of this work is to provide a practical solution to the DASSIM-RT inverse planning problem. Methods: The inverse planning problem is formulated as a fluence-map optimization problem with total-variation (TV) minimization. A newly released L1-solver, template for first-order conic solver (TFOCS), was adopted in this work. TFOCS achieves faster convergence with less memory usage as compared with conventional quadratic programming (QP) for the TV form through the effective use of conic forms, dual-variable updates, and optimal first-order approaches. As such, it is tailored to specifically address the computational challenges of large-scale optimization in DASSIM-RT inverse planning. Two clinical cases (a prostate and a head and neck case) are used to evaluate the effectiveness and efficiency of the proposed planning technique. DASSIM-RT plans with 15 and 30 beams are compared with conventional IMRT plans with 7 beams in terms of plan quality and delivery efficiency, which are quantified by conformation number (CN), the total number of segments and modulation index, respectively. For optimization efficiency, the QP-based approach was compared with the proposed algorithm for the DASSIM-RT plans with 15 beams for both cases. Results: Plan quality improves with an increasing number of incident beams, while the total number of segments is maintained to be about the

  18. Statistics of fermions in the Randall-Wilkins model for kinetics of general order

    International Nuclear Information System (INIS)

    Nieto H, B.; Azorin N, J.; Vazquez C, G.A.

    2004-01-01

    As a theoretical planning of the thermoluminescence phenomena (Tl), we study the behavior of the systems formed by fermions, which are related with this phenomenon establishing a generalization of the Randall-Wilkins model, as for first order kinetics as for general order (equation of May and Partridge) in which we consider a of Fermi-Dirac statistics. As consequence of this study a new variable is manifested: the chemical potential, also we establish its relationship with some of the other magnitudes already known in Tl. (Author)

  19. Excitonic Order and Superconductivity in the Two-Orbital Hubbard Model: Variational Cluster Approach

    Science.gov (United States)

    Fujiuchi, Ryo; Sugimoto, Koudai; Ohta, Yukinori

    2018-06-01

    Using the variational cluster approach based on the self-energy functional theory, we study the possible occurrence of excitonic order and superconductivity in the two-orbital Hubbard model with intra- and inter-orbital Coulomb interactions. It is known that an antiferromagnetic Mott insulator state appears in the regime of strong intra-orbital interaction, a band insulator state appears in the regime of strong inter-orbital interaction, and an excitonic insulator state appears between them. In addition to these states, we find that the s±-wave superconducting state appears in the small-correlation regime, and the dx2 - y2-wave superconducting state appears on the boundary of the antiferromagnetic Mott insulator state. We calculate the single-particle spectral function of the model and compare the band gap formation due to the superconducting and excitonic orders.

  20. A Primal-Dual Approach for a Total Variation Wasserstein Flow

    KAUST Repository

    Benning, Martin; Calatroni, Luca; Dü ring, Bertram; Schö nlieb, Carola-Bibiane

    2013-01-01

    We consider a nonlinear fourth-order diffusion equation that arises in denoising of image densities. We propose an implicit time-stepping scheme that employs a primal-dual method for computing the subgradient of the total variation seminorm. The constraint on the dual variable is relaxed by adding a penalty term, depending on a parameter that determines the weight of the penalisation. The paper is furnished with some numerical examples showing the denoising properties of the model considered. © 2013 Springer-Verlag.