Argyros, S A; Tyros, K
2012-01-01
We introduce the higher order spreading models associated to a Banach space $X$. Their definition is based on $\\ff$-sequences $(x_s)_{s\\in\\ff}$ with $\\ff$ a regular thin family and the plegma families. We show that the higher order spreading models of a Banach space $X$ form an increasing transfinite hierarchy $(\\mathcal{SM}_\\xi(X))_{\\xi<\\omega_1}$. Each $\\mathcal{SM}_\\xi (X)$ contains all spreading models generated by $\\ff$-sequences $(x_s)_{s\\in\\ff}$ with order of $\\ff$ equal to $\\xi$. We also provide a study of the fundamental properties of the hierarchy.
Determining Reduced Order Models for Optimal Stochastic Reduced Order Models
Energy Technology Data Exchange (ETDEWEB)
Bonney, Matthew S. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Brake, Matthew R.W. [Sandia National Lab. (SNL-CA), Livermore, CA (United States)
2015-08-01
The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better represent the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.
Directory of Open Access Journals (Sweden)
Johnny Espin
2015-06-01
Full Text Available It is known, though not commonly, that one can describe fermions using a second order in derivatives Lagrangian instead of the first order Dirac one. In this description the propagator is scalar, and the complexity is shifted to the vertex, which contains a derivative operator. In this paper we rewrite the Lagrangian of the fermionic sector of the Standard Model in such second order form. The new Lagrangian is extremely compact, and is obtained from the usual first order Lagrangian by integrating out all primed (or dotted 2-component spinors. It thus contains just half of the 2-component spinors that appear in the usual Lagrangian, which suggests a new perspective on unification. We sketch a natural in this framework SU(2×SU(4⊂SO(9 unified theory.
Thibes, Ronaldo
2016-01-01
We perform the canonical and path integral quantizations of a lower-order derivatives model describing Podolsky's generalized electrodynamics. The physical content of the model shows an auxiliary massive vector field coupled to the usual electromagnetic field. The equivalence with Podolsky's original model is studied at classical and quantum levels. Concerning the dynamical time evolution we obtain a theory with two first-class and two second-class constraints in phase space. We calculate explicitly the corresponding Dirac brackets involving both vector fields. We use the Senjanovic procedure to implement the second-class constraints and the Batalin-Fradkin-Vilkovisky path integral quantization scheme to deal with the symmetries generated by the first-class constraints. The physical interpretation of the results turns out to be simpler due to the reduced derivatives order permeating the equations of motion, Dirac brackets and effective action.
Regularized Reduced Order Models
Wells, David; Xie, Xuping; Iliescu, Traian
2015-01-01
This paper puts forth a regularization approach for the stabilization of proper orthogonal decomposition (POD) reduced order models (ROMs) for the numerical simulation of realistic flows. Two regularized ROMs (Reg-ROMs) are proposed: the Leray ROM (L-ROM) and the evolve-then-filter ROM (EF-ROM). These new Reg-ROMs use spatial filtering to smooth (regularize) various terms in the ROMs. Two spatial filters are used: a POD projection onto a POD subspace (Proj) and a new POD differential filter (DF). The four Reg-ROM/filter combinations are tested in the numerical simulation of the one-dimensional Burgers equation with a small diffusion coefficient and the three-dimensional flow past a circular cylinder at a low Reynolds number (Re = 100). Overall, the most accurate Reg-ROM/filter combination is EF-ROM-DF. Furthermore, the DF generally yields better results than Proj. Finally, the four Reg-ROM/filter combinations are computationally efficient and generally more accurate than the standard Galerkin ROM.
Order and Progress? The Evolution of Brazilian Defense Strategy
2014-03-01
to progress from this stereotype , Brazil needed a catalyst, which came from a charismatic national leader. Toward the end of the Cardoso... advertising the military’s mission to the citizenry in order to gain a stronger voice in domestic affairs and political agendas. Defense strategy and
Progress in all-order breakup reaction theories
Indian Academy of Sciences (India)
R Chatterjee
2010-07-01
Progress in breakup reaction theories, like the distorted wave Born approximation, the continuum discretized coupled channels method and the dynamical eikonal approximation, is brought into focus. The need to calculate exclusive reaction observables and the utility of benchmark tests as arbitrators of theoretical models are discussed.
Progress in Initiator Modeling
Energy Technology Data Exchange (ETDEWEB)
Hrousis, C A; Christensen, J S
2009-05-04
There is great interest in applying magnetohydrodynamic (MHD) simulation techniques to the designs of electrical high explosive (HE) initiators, for the purpose of better understanding a design's sensitivities, optimizing its performance, and/or predicting its useful lifetime. Two MHD-capable LLNL codes, CALE and ALE3D, are being used to simulate the process of ohmic heating, vaporization, and plasma formation in the bridge of an initiator, be it an exploding bridgewire (EBW), exploding bridgefoil (EBF) or slapper type initiator. The initiation of the HE is simulated using Tarver Ignition & Growth reactive flow models. 1-D, 2-D and 3-D models have been constructed and studied. The models provide some intuitive explanation of the initiation process and are useful for evaluating the potential impact of identified aging mechanisms (such as the growth of intermetallic compounds or powder sintering). The end product of this work is a simulation capability for evaluating margin in proposed, modified or aged initiation system designs.
Approximate Deconvolution Reduced Order Modeling
Xie, Xuping; Wang, Zhu; Iliescu, Traian
2015-01-01
This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal decomposition(POD) is used to define the ROM basis and a POD differential filter is used to define the large ROM structures. An approximate deconvolution(AD) approach is used to solve the ROM closure problem and develop a new AD-ROM. This AD-ROM is tested in the numerical simulation of the one-dimensional Burgers equation with a small diffusion coefficient(10^{-3})
Generalized Reduced Order Model Generation Project
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...
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.
Partial order of frustrated Potts model
Energy Technology Data Exchange (ETDEWEB)
Igarashi, Ryo [CCSE, Japan Atomic Energy Agency, Higashi-Ueno, Taito, Tokyo 110-0015 (Japan); Ogata, Masao, E-mail: igarashi.ryo@jaea.go.j [Deaprtment of Physics, University of Tokyo, Hongo, Bunkyo, Tokyo 133-0033 (Japan)
2010-01-01
We investigate a 4-state ferromagnetic Potts model with a special type of geometrical frustration on a three dimensional diamond lattice. We find that the model undergoes unconventional phase transition; half of the spins in the system order in a two dimensional hexagonal-sheet-like structure while the remaining half of the spins stay disordered. The ordered sheets and the disordered sheets stack one after another. We obtain fairly large residual entropy using the Wang-Landau Monte Carlo simulation.
Cancer progression modeling using static sample data.
Sun, Yijun; Yao, Jin; Nowak, Norma J; Goodison, Steve
2014-01-01
As molecular profiling data continues to accumulate, the design of integrative computational analyses that can provide insights into the dynamic aspects of cancer progression becomes feasible. Here, we present a novel computational method for the construction of cancer progression models based on the analysis of static tumor samples. We demonstrate the reliability of the method with simulated data, and describe the application to breast cancer data. Our findings support a linear, branching model for breast cancer progression. An interactive model facilitates the identification of key molecular events in the advance of disease to malignancy.
Mathematical modelling of fractional order circuits
Moreles, Miguel Angel
2016-01-01
In this work a classical derivation of fractional order circuits models is presented. Generalized constitutive equations in terms of fractional Riemann-Liouville derivatives are introduced in the Maxwell's equations. Next the Kirchhoff voltage law is applied in a RCL circuit configuration. A fractional differential equation model is obtained with Caputo derivatives. Thus standard initial conditions apply.
Methods in Model Order Reduction (MOR) field
Institute of Scientific and Technical Information of China (English)
刘志超
2014-01-01
Nowadays, the modeling of systems may be quite large, even up to tens of thousands orders. In spite of the increasing computational powers, direct simulation of these large-scale systems may be impractical. Thus, to industry requirements, analytically tractable and computationally cheap models must be designed. This is the essence task of Model Order Reduction (MOR). This article describes the basics of MOR optimization, various way of designing MOR, and gives the conclusion about existing methods. In addition, it proposed some heuristic footpath.
Dynamical models of happiness with fractional order
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.
A high-order electromagnetic gyrokinetic model
Miyato, N
2013-01-01
A high-order extension is presented for the electromagnetic gyrokinetic formulation in which the parallel canonical momentum is taken as one of phase space coordinates. The high-order displacement vector associated with the guiding-center transformation should be considered in the long wavelength regime. This yields addtional terms in the gyrokinetic Hamiltonian which lead to modifications to the gyrokinetic Poisson and Amp\\`ere equations. In addition, the high-order piece of the guiding-center transformation for the parallel canonical momentum should be also kept in the electromagnetic model. The high-order piece contains the Ba\\~nos drift effect and further modifies the gyrokinetic Amp\\`ere equation.
Order Parameters of the Dilute A Models
Warnaar, S O; Seaton, K A; Nienhuis, B
1993-01-01
The free energy and local height probabilities of the dilute A models with broken $\\Integer_2$ symmetry are calculated analytically using inversion and corner transfer matrix methods. These models possess four critical branches. The first two branches provide new realisations of the unitary minimal series and the other two branches give a direct product of this series with an Ising model. We identify the integrable perturbations which move the dilute A models away from the critical limit. Generalised order parameters are defined and their critical exponents extracted. The associated conformal weights are found to occur on the diagonal of the relevant Kac table. In an appropriate regime the dilute A$_3$ model lies in the universality class of the Ising model in a magnetic field. In this case we obtain the magnetic exponent $\\delta=15$ directly, without the use of scaling relations.
Progressive Damage Modeling of Notched Composites
Aitharaju, Venkat; Aashat, Satvir; Kia, Hamid; Satyanarayana, Arunkumar; Bogert, Philip
2016-01-01
There is an increased interest in using non-crimp fabric reinforced composites for primary and secondary structural weight savings in high performance automobile applications. However, one of the main challenges in implementing these composites is the lack of understanding of damage progression under a wide variety of loading conditions for general configurations. Towards that end, researchers at GM and NASA are developing new damage models to predict accurately the progressive failure of these composites. In this investigation, the developed progressive failure analysis model was applied to study damage progression in center-notched and open-hole tension specimens for various laminate schemes. The results of a detailed study with respect to the effect of element size on the analysis outcome are presented.
ICA Model Order Estimation Using Clustering Method
Directory of Open Access Journals (Sweden)
P. Sovka
2007-12-01
Full Text Available In this paper a novel approach for independent component analysis (ICA model order estimation of movement electroencephalogram (EEG signals is described. The application is targeted to the brain-computer interface (BCI EEG preprocessing. The previous work has shown that it is possible to decompose EEG into movement-related and non-movement-related independent components (ICs. The selection of only movement related ICs might lead to BCI EEG classification score increasing. The real number of the independent sources in the brain is an important parameter of the preprocessing step. Previously, we used principal component analysis (PCA for estimation of the number of the independent sources. However, PCA estimates only the number of uncorrelated and not independent components ignoring the higher-order signal statistics. In this work, we use another approach - selection of highly correlated ICs from several ICA runs. The ICA model order estimation is done at significance level ÃŽÂ± = 0.05 and the model order is less or more dependent on ICA algorithm and its parameters.
Multi-dimensional model order selection
Directory of Open Access Journals (Sweden)
Roemer Florian
2011-01-01
Full Text Available Abstract Multi-dimensional model order selection (MOS techniques achieve an improved accuracy, reliability, and robustness, since they consider all dimensions jointly during the estimation of parameters. Additionally, from fundamental identifiability results of multi-dimensional decompositions, it is known that the number of main components can be larger when compared to matrix-based decompositions. In this article, we show how to use tensor calculus to extend matrix-based MOS schemes and we also present our proposed multi-dimensional model order selection scheme based on the closed-form PARAFAC algorithm, which is only applicable to multi-dimensional data. In general, as shown by means of simulations, the Probability of correct Detection (PoD of our proposed multi-dimensional MOS schemes is much better than the PoD of matrix-based schemes.
State-space size considerations for disease-progression models.
Regnier, Eva D; Shechter, Steven M
2013-09-30
Markov models of disease progression are widely used to model transitions in patients' health state over time. Usually, patients' health status may be classified according to a set of ordered health states. Modelers lump together similar health states into a finite and usually small, number of health states that form the basis of a Markov chain disease-progression model. This increases the number of observations used to estimate each parameter in the transition probability matrix. However, lumping together observably distinct health states also obscures distinctions among them and may reduce the predictive power of the model. Moreover, as we demonstrate, precision in estimating the model parameters does not necessarily improve as the number of states in the model declines. This paper explores the tradeoff between lumping error introduced by grouping distinct health states and sampling error that arises when there are insufficient patient data to precisely estimate the transition probability matrix. Copyright © 2013 John Wiley & Sons, Ltd.
Progress With Nonhuman Animal Models of Addiction.
Crabbe, John C
2016-09-01
Nonhuman animals have been major contributors to the science of the genetics of addiction. Given the explosion of interest in genetics, it is fair to ask, are we making reasonable progress toward our goals with animal models? I will argue that our goals are changing and that overall progress has been steady and seems likely to continue apace. Genetics tools have developed almost incredibly rapidly, enabling both more reductionist and more synthetic or integrative approaches. I believe that these approaches to making progress have been unbalanced in biomedical science, favoring reductionism, particularly in animal genetics. I argue that substantial, novel progress is also likely to come in the other direction, toward synthesis and abstraction. Another area in which future progress with genetic animal models seems poised to contribute more is the reconciliation of human and animal phenotypes, or consilience. The inherent power of the genetic animal models could be more profitably exploited. In the end, animal research has continued to provide novel insights about how genes influence individual differences in addiction risk and consequences. The rules of the genetics game are changing so fast that it is hard to remember how comparatively little we knew even a generation ago. Rather than worry about whether we have been wasting time and resources asking the questions we have been, we should look to the future and see if we can come up with some new ones. The valuable findings from the past will endure, and the sidetracks will be forgotten.
Directory of Open Access Journals (Sweden)
Alok kumar
2011-10-01
Full Text Available This study presents optimal ordering policies for retailer when supplier offers cash discount and two progressive payment schemes for paying of purchasing cost. If the retailer pays the outstanding amount before or at first trade credit period M, the supplier provides r_1cash discount and does not charge any interest. If the retailer pays after M but before or at the second trade period N offered by the supplier, the supplier provides r_2 cash discount and charges interest on unpaid balance at the rate 〖Ic〗_1 . If retailer pays the balance after N, (N>M then the supplier does not provide any cash discount but charges interest on unpaid balance at the rate 〖Ic〗_2. The primary objective of this paper is to minimize the total cost of inventory system. This paper develops an algebraic approach to determine the optimal cycle time, optimal order quantity and optimal relevant cost. Numerical example are also presented to illustrate the result of propose model and solution procedure developed.
Modeling cancer progression via pathway dependencies.
Directory of Open Access Journals (Sweden)
Elena J Edelman
2008-02-01
Full Text Available Cancer is a heterogeneous disease often requiring a complexity of alterations to drive a normal cell to a malignancy and ultimately to a metastatic state. Certain genetic perturbations have been implicated for initiation and progression. However, to a great extent, underlying mechanisms often remain elusive. These genetic perturbations are most likely reflected by the altered expression of sets of genes or pathways, rather than individual genes, thus creating a need for models of deregulation of pathways to help provide an understanding of the mechanisms of tumorigenesis. We introduce an integrative hierarchical analysis of tumor progression that discovers which a priori defined pathways are relevant either throughout or in particular steps of progression. Pathway interaction networks are inferred for these relevant pathways over the steps in progression. This is followed by the refinement of the relevant pathways to those genes most differentially expressed in particular disease stages. The final analysis infers a gene interaction network for these refined pathways. We apply this approach to model progression in prostate cancer and melanoma, resulting in a deeper understanding of the mechanisms of tumorigenesis. Our analysis supports previous findings for the deregulation of several pathways involved in cell cycle control and proliferation in both cancer types. A novel finding of our analysis is a connection between ErbB4 and primary prostate cancer.
A prediction model for progressive disease in systemic sclerosis
Meijs, Jessica; Schouffoer, Anne A; Ajmone Marsan, Nina; Stijnen, Theo; Putter, Hein; Ninaber, Maarten K; Huizinga, Tom W J; de Vries-Bouwstra, Jeska K
2015-01-01
Objective To develop a model that assesses the risk for progressive disease in patients with systemic sclerosis (SSc) over the short term, in order to guide clinical management. Methods Baseline characteristics and 1 year follow-up results of 163 patients with SSc referred to a multidisciplinary healthcare programme were evaluated. Progressive disease was defined as: death, ≥10% decrease in forced vital capacity, ≥15% decrease in diffusing capacity for carbon monoxide, ≥10% decrease in body weight, ≥30% decrease in estimated-glomerular filtration rate, ≥30% increase in modified Rodnan Skin Score (with Δ≥5) or ≥0.25 increase in Scleroderma Health Assessment Questionnaire. The number of patients with progressive disease was determined. Univariable and multivariable logistic regression analyses were used to assess the probability of progressive disease for each individual patient. Performance of the prediction model was evaluated using a calibration plot and area under the receiver operating characteristic curve. Results 63 patients had progressive disease, including 8 patients who died ≤18 months after first evaluation. Multivariable analysis showed that friction rubs, proximal muscular weakness and decreased maximum oxygen uptake as % predicted, adjusted for age, gender and use of immunosuppressive therapy at baseline, were significantly associated with progressive disease. Using the prediction model, the predicted chance for progressive disease increased from a pretest chance of 37% to 67–89%. Conclusions Using the prediction model, the chance for progressive disease for individual patients could be doubled. Friction rubs, proximal muscular weakness and maximum oxygen uptake as % predicted were identified as relevant parameters. PMID:26688749
Recent progress on countercurrent chromatography modeling
Wang, Fengkang; Ito, Yoichiro; Wei, Yun
2014-01-01
As countercurrent chromatography is becoming an established method in chromatography for many kinds of products, it is becoming increasingly important to model the process and to be able to predict the peaks for a given process. The CCC industries are looking for rapid methods to analyze the processes of countercurrent chromatography and select suitable solvent system. In this paper, recent progress is reviewed in the development and demonstration of several types of models of countercurrent ...
Progressive IRP Models for Power Resources Including EPP
Directory of Open Access Journals (Sweden)
Yiping Zhu
2017-01-01
Full Text Available In the view of optimizing regional power supply and demand, the paper makes effective planning scheduling of supply and demand side resources including energy efficiency power plant (EPP, to achieve the target of benefit, cost, and environmental constraints. In order to highlight the characteristics of different supply and demand resources in economic, environmental, and carbon constraints, three planning models with progressive constraints are constructed. Results of three models by the same example show that the best solutions to different models are different. The planning model including EPP has obvious advantages considering pollutant and carbon emission constraints, which confirms the advantages of low cost and emissions of EPP. The construction of progressive IRP models for power resources considering EPP has a certain reference value for guiding the planning and layout of EPP within other power resources and achieving cost and environmental objectives.
Modeling Ability Differentiation in the Second-Order Factor Model
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,…
Modeling ability differentiation in the second-order factor model
Molenaar, D.; Dolan, C.V.; van der Maas, H.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
Recent progress on the Random Conductance Model
Biskup, Marek
2011-01-01
Recent progress on the understanding of the Random Conductance Model is reviewed and commented. A particular emphasis is on the results on the scaling limit of the random walk among random conductances for almost every realization of the environment, observations on the behavior of the effective resistance as well as the scaling limit of certain models of gradient fields with non-convex interactions. The text is an expanded version of the lecture notes for a course delivered at the 2011 Cornell Summer School on Probability.
Progression of Diabetic Capillary Occlusion: A Model.
Directory of Open Access Journals (Sweden)
Xiao Fu
2016-06-01
Full Text Available An explanatory computational model is developed of the contiguous areas of retinal capillary loss which play a large role in diabetic maculapathy and diabetic retinal neovascularization. Strictly random leukocyte mediated capillary occlusion cannot explain the occurrence of large contiguous areas of retinal ischemia. Therefore occlusion of an individual capillary must increase the probability of occlusion of surrounding capillaries. A retinal perifoveal vascular sector as well as a peripheral retinal capillary network and a deleted hexagonal capillary network are modelled using Compucell3D. The perifoveal modelling produces a pattern of spreading capillary loss with associated macular edema. In the peripheral network, spreading ischemia results from the progressive loss of the ladder capillaries which connect peripheral arterioles and venules. System blood flow was elevated in the macular model before a later reduction in flow in cases with progression of capillary occlusions. Simulations differing only in initial vascular network structures but with identical dynamics for oxygen, growth factors and vascular occlusions, replicate key clinical observations of ischemia and macular edema in the posterior pole and ischemia in the retinal periphery. The simulation results also seem consistent with quantitative data on macular blood flow and qualitative data on venous oxygenation. One computational model applied to distinct capillary networks in different retinal regions yielded results comparable to clinical observations in those regions.
Second order closure modeling of turbulent buoyant wall plumes
Zhu, Gang; Lai, Ming-Chia; Shih, Tsan-Hsing
1992-01-01
Non-intrusive measurements of scalar and momentum transport in turbulent wall plumes, using a combined technique of laser Doppler anemometry and laser-induced fluorescence, has shown some interesting features not present in the free jet or plumes. First, buoyancy-generation of turbulence is shown to be important throughout the flow field. Combined with low-Reynolds-number turbulence and near-wall effect, this may raise the anisotropic turbulence structure beyond the prediction of eddy-viscosity models. Second, the transverse scalar fluxes do not correspond only to the mean scalar gradients, as would be expected from gradient-diffusion modeling. Third, higher-order velocity-scalar correlations which describe turbulent transport phenomena could not be predicted using simple turbulence models. A second-order closure simulation of turbulent adiabatic wall plumes, taking into account the recent progress in scalar transport, near-wall effect and buoyancy, is reported in the current study to compare with the non-intrusive measurements. In spite of the small velocity scale of the wall plumes, the results showed that low-Reynolds-number correction is not critically important to predict the adiabatic cases tested and cannot be applied beyond the maximum velocity location. The mean and turbulent velocity profiles are very closely predicted by the second-order closure models. but the scalar field is less satisfactory, with the scalar fluctuation level underpredicted. Strong intermittency of the low-Reynolds-number flow field is suspected of these discrepancies. The trends in second- and third-order velocity-scalar correlations, which describe turbulent transport phenomena, are also predicted in general, with the cross-streamwise correlations better than the streamwise one. Buoyancy terms modeling the pressure-correlation are shown to improve the prediction slightly. The effects of equilibrium time-scale ratio and boundary condition are also discussed.
Advanced Fluid Reduced Order Models for Compressible Flow.
Energy Technology Data Exchange (ETDEWEB)
Tezaur, Irina Kalashnikova; Fike, Jeffrey A.; Carlberg, Kevin Thomas; Barone, Matthew F.; Maddix, Danielle; Mussoni, Erin E.; Balajewicz, Maciej (UIUC)
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.
PROGRESS IN THREE-DIMENSIONALLY ORDERED SELF-ASSEMBLY OF COLLOIDAL SiO2 PARTICLES
Institute of Scientific and Technical Information of China (English)
Qian Zhou; Peng Dong; Bingying Cheng
2003-01-01
Three-dimensionally ordered self-assembly of monodispersed colloidal SiO2 particles involving a structure with periodic alternation of refractive indices represents an advanced field of particuology, colloidal chemistry, materials science, optical physics and information science. Study on such self-assembly not only lays the foundation for the development of advanced functional materials, but also is significant in understanding the principles of nano- and micro-scale processes. Recent progress in three-dimensionally ordered self-assembly of colloidal SiO2 particles is reviewed,inclusive of the authors' investigations.
Modeling Interconnect Variability Using Efficient Parametric Model Order Reduction
Li, Peng; Li, Xin; Pileggi, Lawrence T; Nassif, Sani R
2011-01-01
Assessing IC manufacturing process fluctuations and their impacts on IC interconnect performance has become unavoidable for modern DSM designs. However, the construction of parametric interconnect models is often hampered by the rapid increase in computational cost and model complexity. In this paper we present an efficient yet accurate parametric model order reduction algorithm for addressing the variability of IC interconnect performance. The efficiency of the approach lies in a novel combination of low-rank matrix approximation and multi-parameter moment matching. The complexity of the proposed parametric model order reduction is as low as that of a standard Krylov subspace method when applied to a nominal system. Under the projection-based framework, our algorithm also preserves the passivity of the resulting parametric models.
Progress in Modeling and Simulation of Batteries
Energy Technology Data Exchange (ETDEWEB)
Turner, John A [ORNL
2016-01-01
Modeling and simulation of batteries, in conjunction with theory and experiment, are important research tools that offer opportunities for advancement of technologies that are critical to electric motors. The development of data from the application of these tools can provide the basis for managerial and technical decision-making. Together, these will continue to transform batteries for electric vehicles. This collection of nine papers presents the modeling and simulation of batteries and the continuing contribution being made to this impressive progress, including topics that cover: * Thermal behavior and characteristics * Battery management system design and analysis * Moderately high-fidelity 3D capabilities * Optimization Techniques and Durability As electric vehicles continue to gain interest from manufacturers and consumers alike, improvements in economy and affordability, as well as adoption of alternative fuel sources to meet government mandates are driving battery research and development. Progress in modeling and simulation will continue to contribute to battery improvements that deliver increased power, energy storage, and durability to further enhance the appeal of electric vehicles.
The Optimal Economic Order: the simplest model
J. Tinbergen (Jan)
1992-01-01
textabstractIn the last five years humanity has become faced with the problem of the optimal socioeconomic order more clearly than ever. After the confrontation of capitalism and socialism, which was the core of the Marxist thesis, the fact transpired that capitalism was not the optimal order. It wa
Multi-order Arnoldi-based model order reduction of second-order time-delay systems
Xiao, Zhi-Hua; Jiang, Yao-Lin
2016-09-01
In this paper, we discuss the Krylov subspace-based model order reduction methods of second-order systems with time delays, and present two structure-preserving methods for model order reduction of these second-order systems, which avoid to convert the second-order systems into first-order ones. One method is based on a Krylov subspace by using the Taylor series expansion, the other method is based on the Laguerre series expansion. These two methods are used in the multi-order Arnoldi algorithm to construct the projection matrices. The resulting reduced models can not only preserve the structure of the original systems, but also can match a certain number of approximate moments or Laguerre expansion coefficients. The effectiveness of the proposed methods is demonstrated by two numerical examples.
Variable-fidelity and reduced-order models for aero data for loads predictions
DEFF Research Database (Denmark)
Goertz, Stefan; Zimmermann, Ralf; Han, Zhong Hua
2013-01-01
This paper summarizes recent progress in developing metamodels for efficiently predicting the aerodynamic loads acting on industrial aircraft configurations. We introduce a physics-based approach to reduced-order modeling based on proper orthogonal decomposition of snapshots of the full-order CFD...
Dynamical numerical model for nematic order reconstruction
Lombardo, G.; Ayeb, H.; Barberi, R.
2008-05-01
In highly frustrated calamitic nematic liquid crystals, a strong elastic distortion can be confined on a few nanometers. The classical elastic theory fails to describe such systems and a more complete description based on the tensor order parameter Q is required. A finite element method is used to implement the Q dynamics by a variational principle and it is shown that a uniaxial nematic configuration can evolve passing through transient biaxial states. This solution, which connects two competing uniaxial nematic textures, is known as “nematic order reconstruction.”
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
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...
Order and Disorder in Product Innovation Models
Pina e Cunha, Miguel; Gomes, Jorge F.S.
2003-01-01
This article argues that the conceptual development of product innovation models goes hand in hand with paradigmatic changes in the field of organization science. Remarkable similarities in the change of organizational perspectives and product innovation models are noticeable. To illustrate how chan
INTRUSION DETECTION BASED ON THE SECOND-ORDER STOCHASTIC MODEL
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper presents a new method based on a second-order stochastic model for computer intrusion detection. The results show that the performance of the second-order stochastic model is better than that of a first-order stochastic model. In this study, different window sizes are also used to test the performance of the model. The detection results show that the second-order stochastic model is not so sensitive to the window size, comparing with the first-order stochastic model and other previous researches. The detection result of window sizes 6 and 10 is the same.
Progress towards Continental River Dynamics modeling
Yu, Cheng-Wei; Zheng, Xing; Liu, Frank; Maidment, Daivd; Hodges, Ben
2017-04-01
The high-resolution National Water Model (NWM), launched by U.S. National Oceanic and Atmospheric Administration (NOAA) in August 2016, has shown it is possible to provide real-time flow prediction in rivers and streams across the entire continental United States. The next step for continental-scale modeling is moving from reduced physics (e.g. Muskingum-Cunge) to full dynamic modeling with the Saint-Venant equations. The Simulation Program for River Networks (SPRNT) provides a computational approach for the Saint-Venant equations, but obtaining sufficient channel bathymetric data and hydraulic roughness is seen as a critical challenge. However, recent work has shown the Height Above Nearest Drainage (HAND) method can be applied with the National Elevation Dataset (NED) to provide automated estimation of effective channel bathymetry suitable for large-scale hydraulic simulations. The present work examines the use of SPRNT with the National Hydrography Dataset (NHD) and HAND-derived bathymetry for automated generation of rating curves that can be compared to existing data. The approach can, in theory, be applied to every stream reach in the NHD and thus provide flood guidance where none is available. To test this idea we generated 2000+ rating curves in two catchments in Texas and Alabama (USA). Field data from the USGS and flood records from an Austin, Texas flood in May 2015 were used as validation. Large-scale implementation of this idea requires addressing several critical difficulties associated with numerical instabilities, including ill-posed boundary conditions generated in automated model linkages and inconsistencies in the river geometry. A key to future progress is identifying efficient approaches to isolate numerical instability contributors in a large time-space varying solution. This research was supported in part by the National Science Foundation under grant number CCF-1331610.
Model Order Reduction for Electronic Circuits:
DEFF Research Database (Denmark)
Hjorth, Poul G.; Shontz, Suzanne
Electronic circuits are ubiquitous; they are used in numerous industries including: the semiconductor, communication, robotics, auto, and music industries (among many others). As products become more and more complicated, their electronic circuits also grow in size and complexity. This increased ...... in the semiconductor industry. Circuit simulation proceeds by using Maxwell’s equations to create a mathematical model of the circuit. The boundary element method is then used to discretize the equations, and the variational form of the equations are then solved on the graph network....
SOME PROGRESS IN THE LATTICE BOLTMANN MODEL
Institute of Scientific and Technical Information of China (English)
FENG SHI-DE; TSUTAHARA MICHIHISA; JI ZHONG-ZHEN
2001-01-01
A lattice Boltzmann equation model has been developed by using the equilibrium distribution function of the Maxwell-Boltzmann-like form, which is third order in fluid velocity uα. The criteria of energy conservation between the macroscopic physical quantities and the microscopic particles are introduced into the model, thus the thermal hydrodynamic equations containing the effect of buoyancy force can be recovered in terms of the Taylor and ChapmanEnskog asymptotic expansion methods. The two-dimensional thermal convection phenomena in a square cavity and between two concentric cylinders have been calculated by implementing a heat flux boundary condition. Both numerical results are in good agreement with the conventional numerical results.
Progress towards a Venus reference cloud model
Wilson, Colin; Ignatiev, Nikolay; Marcq, Emmanuel
Venus is completely enveloped by clouds. The main cloud layers stretch from altitudes of 48 - 75 km, with additional tenuous hazes found at altitudes 30 - 100 km. Clouds play a crucial role in governing atmospheric circulation, chemistry and climate on all planets, but particularly so on Venus due to the optical thickness of the atmosphere. The European Space Agency’s Venus Express (VEx) satellite has carried out a wealth of observations of Venus clouds since its arrival at Venus in April 2006. Many VEx observations are relevant to cloud science - from imagers and spectrometers to solar, stellar and radio occultation - each covering different altitude ranges, spectral ranges and atmospheric constituents. We have formed an International Team at the International Space Science Institute to bring together scientists from each of the relevant Venus Express investigation teams as well as from previous missions, as well as those developing computational and analytical models of clouds and hazes. The aims of the project are (1) to create self-consistent reference cloud/haze models which capture not only a mean cloud structure but also its main modes of variability; and (2) to bring together modelers and observers, to reach an understanding of clouds and hazes on Venus which matches all observables and is physically consistent. Our approach is to first to assemble an averaged cloud profile for low latitudes, showing how cloud number abundances and other observables vary as a function of altitude, consistent with all available observations. In a second step, we will expand this work to produce a reference cloud profile which varies with latitude and local solar time, as well as optical thickness of the cloud. We will present our status in progressing towards this goal. We acknowledge the support of the International Space Science Institute of Berne, Switzerland, in hosting our Team’s meetings.
Soepenberg, G.D.; Land, M.J.; Gaalman, G.J.C.
This paper describes the development of a new tool for facilitating the diagnosis of logistic improvement opportunities in make-to-order (MTO) companies. Competitiveness of these companies increasingly imposes needs upon delivery reliability. In order to achieve high delivery reliability, both the
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 languages...
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 < 10 -20 ) by using probabilistic topic models to summarize clinical data into up to 32 topics. Many of these latent topics yield natural clinical interpretations (e.g., "critical care," "pneumonia," "neurologic evaluation"). Existing order 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.
Sliding Mode Control Design via Reduced Order Model Approach
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper presents a design of continuous-time sliding mode control for the higher order systems via reduced order model. It is shown that a continuous-time sliding mode control designed for the reduced order model gives similar performance for the higher order system. The method is illustrated by numerical examples. The paper also introduces a technique for design of a sliding surface such that the system satisfies a cost-optimality condition when on the sliding surface.
Fractional-order in a macroeconomic dynamic model
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.
Innovative first order elimination kinetics working model for easy learning
Directory of Open Access Journals (Sweden)
Navin Budania
2016-06-01
Conclusions: First order elimination kinetics is easily understood with the help of above working model. More and more working models could be developed for teaching difficult topics. [Int J Basic Clin Pharmacol 2016; 5(3.000: 862-864
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...
Research on Modeling of Hydropneumatic Suspension Based on Fractional Order
Junwei Zhang; Sizhong Chen; Yuzhuang Zhao; Jianbo Feng; Chang Liu; Ying Fan
2015-01-01
With such excellent performance as nonlinear stiffness, adjustable vehicle height, and good vibration resistance, hydropneumatic suspension (HS) has been more and more applied to heavy vehicle and engineering vehicle. Traditional modeling methods are still confined to simple models without taking many factors into consideration. A hydropneumatic suspension model based on fractional order (HSM-FO) is built with the advantage of fractional order (FO) in viscoelastic material modeling considerin...
Exponential order statistic models of software reliability growth
Miller, D. R.
1986-01-01
Failure times of a software reliability growth process are modeled as order statistics of independent, nonidentically distributed exponential random variables. The Jelinsky-Moranda, Goel-Okumoto, Littlewood, Musa-Okumoto Logarithmic, and Power Law models are all special cases of Exponential Order Statistic Models, but there are many additional examples also. Various characterizations, properties and examples of this class of models are developed and presented.
On the Economic Order Quantity Model With Transportation Costs
S.I. Birbil (Ilker); K. Bulbul; J.B.G. Frenk (Hans); H.M. Mulder (Henry)
2009-01-01
textabstractWe consider an economic order quantity type model with unit out-of-pocket holding costs, unit opportunity costs of holding, fixed ordering costs and general transportation costs. For these models, we analyze the associated optimization problem and derive an easy procedure for determining
Model-order reduction of biochemical reaction networks
Rao, Shodhan; Schaft, Arjan van der; Eunen, Karen van; Bakker, Barbara M.; Jayawardhana, Bayu
2013-01-01
In this paper we propose a model-order reduction method for chemical reaction networks governed by general enzyme kinetics, including the mass-action and Michaelis-Menten kinetics. The model-order reduction method is based on the Kron reduction of the weighted Laplacian matrix which describes the gr
Reduced order modeling of steady flows subject to aerodynamic constraints
DEFF Research Database (Denmark)
Zimmermann, Ralf; Vendl, Alexander; Goertz, Stefan
2014-01-01
A novel reduced-order modeling method based on proper orthogonal decomposition for predicting steady, turbulent flows subject to aerodynamic constraints is introduced. Model-order reduction is achieved by replacing the governing equations of computational fluid dynamics with a nonlinear weighted ...
Second-order model selection in mixture experiments
Energy Technology Data Exchange (ETDEWEB)
Redgate, P.E.; Piepel, G.F.; Hrma, P.R.
1992-07-01
Full second-order models for q-component mixture experiments contain q(q+l)/2 terms, which increases rapidly as q increases. Fitting full second-order models for larger q may involve problems with ill-conditioning and overfitting. These problems can be remedied by transforming the mixture components and/or fitting reduced forms of the full second-order mixture model. Various component transformation and model reduction approaches are discussed. Data from a 10-component nuclear waste glass study are used to illustrate ill-conditioning and overfitting problems that can be encountered when fitting a full second-order mixture model. Component transformation, model term selection, and model evaluation/validation techniques are discussed and illustrated for the waste glass example.
Capabilities and accessibility: a model for progress
Directory of Open Access Journals (Sweden)
Nick Tyler
2011-11-01
Full Text Available Accessibility is seen to be a core issue which relates directly to the quality of life: if a person cannot reach and use a facility then they cannot take advantage of the benefits that the facility is seeking to provide. In some cases this is about being able to take part in an activity for enjoyment, but in some it is a question of the exercise of human rights – access to healthcare, education, voting and other citizens’ rights. This paper argues that such an equitable accessibility approach requires understanding of the relationships between the capabilities that a person has and the capabilities required of them by society in order to achieve the accessibility they seek. The Capabilities Model, which has been developed at UCL is an attempt to understand this relationship and the paper sets out an approach to quantifying the capabilities in a way that allows designers and implementers of environmental construction and operation to have a more robust approach to their decisions about providing accessibility.
On Local Homogeneity and Stochastically Ordered Mixed Rasch Models
Kreiner, Svend; Hansen, Mogens; Hansen, Carsten Rosenberg
2006-01-01
Mixed Rasch models add latent classes to conventional Rasch models, assuming that the Rasch model applies within each class and that relative difficulties of items are different in two or more latent classes. This article considers a family of stochastically ordered mixed Rasch models, with ordinal latent classes characterized by increasing total…
Four Order Electrostatic Discharge Circuit Model and its Simulation
Directory of Open Access Journals (Sweden)
Xiaodong Wang
2012-12-01
Full Text Available According to the international electrotechnical commission issued IEC61000-4-2 test standard, through the electrostatic discharge current waveform characteristics analysis and numerical experiment method, and construct a new ESD current expression. Using Laplasse transform, established the ESD system mathematical model. According to the mathematical model, construction of passive four order ESD system circuit model and active four order ESD system circuit model, and simulation. The simulation results meet the IEC61000-4-2 standard, and verify the consistency of the ESD current expression, the mathematical model and the circuit model.
Order reduction of large-scale linear oscillatory system models
Energy Technology Data Exchange (ETDEWEB)
Trudnowksi, D.J. (Pacific Northwest Lab., Richland, WA (United States))
1994-02-01
Eigen analysis and signal analysis techniques of deriving representations of power system oscillatory dynamics result in very high-order linear models. In order to apply many modern control design methods, the models must be reduced to a more manageable order while preserving essential characteristics. Presented in this paper is a model reduction method well suited for large-scale power systems. The method searches for the optimal subset of the high-order model that best represents the system. An Akaike information criterion is used to define the optimal reduced model. The method is first presented, and then examples of applying it to Prony analysis and eigenanalysis models of power systems are given.
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.
First and Higher Order Effects on Zero Order Radiative Transfer Model
Neelam, M.; Mohanty, B.
2014-12-01
Microwave radiative transfer model are valuable tool in understanding the complex land surface interactions. Past literature has largely focused on local sensitivity analysis for factor priotization and ignoring the interactions between the variables and uncertainties around them. Since land surface interactions are largely nonlinear, there always exist uncertainties, heterogeneities and interactions thus it is important to quantify them to draw accurate conclusions. In this effort, we used global sensitivity analysis to address the issues of variable uncertainty, higher order interactions, factor priotization and factor fixing for zero-order radiative transfer (ZRT) model. With the to-be-launched Soil Moisture Active Passive (SMAP) mission of NASA, it is very important to have a complete understanding of ZRT for soil moisture retrieval to direct future research and cal/val field campaigns. This is a first attempt to use GSA technique to quantify first order and higher order effects on brightness temperature from ZRT model. Our analyses reflect conditions observed during the growing agricultural season for corn and soybeans in two different regions in - Iowa, U.S.A and Winnipeg, Canada. We found that for corn fields in Iowa, there exist significant second order interactions between soil moisture, surface roughness parameters (RMS height and correlation length) and vegetation parameters (vegetation water content, structure and scattering albedo), whereas in Winnipeg, second order interactions are mainly due to soil moisture and vegetation parameters. But for soybean fields in both Iowa and Winnipeg, we found significant interactions only to exist between soil moisture and surface roughness parameters.
Stochastic Models for Phylogenetic Trees on Higher-order Taxa
Aldous, David; Popovic, Lea
2007-01-01
Simple stochastic models for phylogenetic trees on species have been well studied. But much paleontology data concerns time series or trees on higher-order taxa, and any broad picture of relationships between extant groups requires use of higher-order taxa. A coherent model for trees on (say) genera should involve both a species-level model and a model for the classification scheme by which species are assigned to genera. We present a general framework for such models, and describe three alternate classification schemes. Combining with the species-level model of Aldous-Popovic (2005), one gets models for higher-order trees, and we initiate analytic study of such models. In particular we derive formulas for the lifetime of genera, for the distribution of number of species per genus, and for the offspring structure of the tree on genera.
Model order reduction techniques with applications in finite element analysis
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...
Modeling of higher order systems using artificial bee colony algorithm
Directory of Open Access Journals (Sweden)
Aytekin Bağış
2016-05-01
Full Text Available In this work, modeling of the higher order systems based on the use of the artificial bee colony (ABC algorithm were examined. Proposed model parameters for the sample systems in the literature were obtained by using the algorithm, and its performance was presented comparatively with the other methods. Simulation results show that the ABC algorithm based system modeling approach can be used as an efficient and powerful method for higher order systems.
Dual equivalence in models with higher-order derivatives
Bazeia, D; Nascimento, J R S; Ribeiro, R F; Wotzasek, C
2003-01-01
We introduce a class of higher-order derivative models in (2,1) space-time dimensions. The models are described by a vector field, and contain a Proca-like mass term which prevents gauge invariance. We use the gauge embedding procedure to generate another class of higher-order derivative models, gauge-invariant and dual to the former class. We also show that the gauge embedding approach works appropriately when the vector field couples with fermionic matter.
Modelling Limit Order Execution Times from Market Data
Kim, Adlar; Farmer, Doyne; Lo, Andrew
2007-03-01
Although the term ``liquidity'' is widely used in finance literatures, its meaning is very loosely defined and there is no quantitative measure for it. Generally, ``liquidity'' means an ability to quickly trade stocks without causing a significant impact on the stock price. From this definition, we identified two facets of liquidity -- 1.execution time of limit orders, and 2.price impact of market orders. The limit order is an order to transact a prespecified number of shares at a prespecified price, which will not cause an immediate execution. On the other hand, the market order is an order to transact a prespecified number of shares at a market price, which will cause an immediate execution, but are subject to price impact. Therefore, when the stock is liquid, market participants will experience quick limit order executions and small market order impacts. As a first step to understand market liquidity, we studied the facet of liquidity related to limit order executions -- execution times. In this talk, we propose a novel approach of modeling limit order execution times and show how they are affected by size and price of orders. We used q-Weibull distribution, which is a generalized form of Weibull distribution that can control the fatness of tail to model limit order execution times.
Cosmic Acceleration in a Model of Fourth Order Gravity
Banerjee, Shreya; Singh, Tejinder P
2015-01-01
We investigate a fourth order model of gravity, having a free length parameter, and no cosmological constant or dark energy. We consider cosmological evolution of a flat Friedmann universe in this model for the case that the length parameter is of the order of present Hubble radius. By making a suitable choice for the present value of the Hubble parameter, and value of third derivative of the scale factor (the jerk) we find that the model can explain cosmic acceleration to the same degree of accuracy as the standard concordance model. If the free length parameter is assumed to be time-dependent, and of the order of the Hubble parameter of the corresponding epoch, the model can still explain cosmic acceleration, and provides a possible resolution of the cosmic coincidence problem. We also compare redshift drift in this model, with that in the standard model.
Symmetry and partial order reduction techniques in model checking Rebeca
Jaghouri, M.M.; Sirjani, M.; Mousavi, M.R.; Movaghar, A.
2007-01-01
Rebeca is an actor-based language with formal semantics that can be used in modeling concurrent and distributed software and protocols. In this paper, we study the application of partial order and symmetry reduction techniques to model checking dynamic Rebeca models. Finding symmetry based equivalen
Building Higher-Order Markov Chain Models with EXCEL
Ching, Wai-Ki; Fung, Eric S.; Ng, Michael K.
2004-01-01
Categorical data sequences occur in many applications such as forecasting, data mining and bioinformatics. In this note, we present higher-order Markov chain models for modelling categorical data sequences with an efficient algorithm for solving the model parameters. The algorithm can be implemented easily in a Microsoft EXCEL worksheet. We give a…
Model and Controller Order Reduction for Infinite Dimensional Systems
Directory of Open Access Journals (Sweden)
Fatmawati
2010-05-01
Full Text Available This paper presents a reduced order model problem using reciprocal transformation and balanced truncation followed by low order controller design of infinite dimensional systems. The class of systems considered is that of an exponentially stable state linear systems (A, B, C, where operator A has a bounded inverse, and the operator B and C are of finite-rank and bounded. We can connect the system (A, B, C with its reciprocal system via the solutions of the Lyapunov equations. The realization of the reciprocal system is reduced by balanced truncation. This result is further translated using reciprocal transformation as the reduced-order model for the systems (A, B, C. Then the low order controller is designed based on the reduced order model. The numerical examples are studied using simulations of Euler-Bernoulli beam to show the closed-loop performance.
Atmospheric Turbulence Modeling for Aerospace Vehicles: Fractional Order Fit
Kopasakis, George (Inventor)
2015-01-01
An improved model for simulating atmospheric disturbances is disclosed. A scale Kolmogorov spectral may be scaled to convert the Kolmogorov spectral into a finite energy von Karman spectral and a fractional order pole-zero transfer function (TF) may be derived from the von Karman spectral. Fractional order atmospheric turbulence may be approximated with an integer order pole-zero TF fit, and the approximation may be stored in memory.
Second-Order Model Reduction Based on Gramians
Directory of Open Access Journals (Sweden)
Cong Teng
2012-01-01
Full Text Available Some new and simple Gramian-based model order reduction algorithms are presented on second-order linear dynamical systems, namely, SVD methods. Compared to existing Gramian-based algorithms, that is, balanced truncation methods, they are competitive and more favorable for large-scale systems. Numerical examples show the validity of the algorithms. Error bounds on error systems are discussed. Some observations are given on structures of Gramians of second order linear systems.
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.
High order fluid model for ionization fronts in streamer discharges
Markosyan, A.; Dujko, S.; Ebert, U.; Almeida, P.G.C.; Alves, L.L.; Guerra, V.
2012-01-01
A high order fluid model for streamer dynamics is developed by closing the system after the 4th mo- ment of the Boltzmann equation in local mean energy approximation. This is done by approximating the high order pressure tensor in the heat flux equation through the previous moments. The electric fi
Energy Technology Data Exchange (ETDEWEB)
Caskey, C.T.; Nelson, D.L.
1992-12-01
Progress is reported on gathering X chromosome specific libraries and integrating those with the library produced in this project. Further studies on understanding Fragile X Syndrome and other hereditary diseases related to the X chromosome are described. (DT)
Reduced-order models for vertical human-structure interaction
Van Nimmen, Katrien; Lombaert, Geert; De Roeck, Guido; Van den Broeck, Peter
2016-09-01
For slender and lightweight structures, the vibration serviceability under crowd- induced loading is often critical in design. Currently, designers rely on equivalent load models, upscaled from single-person force measurements. Furthermore, it is important to consider the mechanical interaction with the human body as this can significantly reduce the structural response. To account for these interaction effects, the contact force between the pedestrian and the structure can be modelled as the superposition of the force induced by the pedestrian on a rigid floor and the force resulting from the mechanical interaction between the structure and the human body. For the case of large crowds, however, this approach leads to models with a very high system order. In the present contribution, two equivalent reduced-order models are proposed to approximate the dynamic behaviour of the full-order coupled crowd-structure system. A numerical study is performed to evaluate the impact of the modelling assumptions on the structural response to pedestrian excitation. The results show that the full-order moving crowd model can be well approximated by a reduced-order model whereby the interaction with the pedestrians in the crowd is modelled using a single (equivalent) SDOF system.
Modeling Business Processes with Azzurra: Order Fulﬁlment
Canobbio, Giulia; Dalpiaz, Fabiano
2012-01-01
Azzurra is a specification language for modeling and enacting business processes. Azzurra is founded on social concepts, such as roles, agents and commitments among them, and Azzurra models are social models consisting of networks of commitments. As such, Azzurra models support the flexible enactment of business processes, and provide a semantic notion of actor accountability and business process compliance. In this technical report, we apply Azzurra to the order fulfilment exemplar from ...
Fractional-Order Nonlinear Systems Modeling, Analysis and Simulation
Petráš, Ivo
2011-01-01
"Fractional-Order Nonlinear Systems: Modeling, Analysis and Simulation" presents a study of fractional-order chaotic systems accompanied by Matlab programs for simulating their state space trajectories, which are shown in the illustrations in the book. Description of the chaotic systems is clearly presented and their analysis and numerical solution are done in an easy-to-follow manner. Simulink models for the selected fractional-order systems are also presented. The readers will understand the fundamentals of the fractional calculus, how real dynamical systems can be described using fractional derivatives and fractional differential equations, how such equations can be solved, and how to simulate and explore chaotic systems of fractional order. The book addresses to mathematicians, physicists, engineers, and other scientists interested in chaos phenomena or in fractional-order systems. It can be used in courses on dynamical systems, control theory, and applied mathematics at graduate or postgraduate level. ...
A High-Order Multiscale Global Atmospheric Model
Nair, Ram
2016-04-01
The High-Order Method Modeling Environment (HOMME), developed at NCAR, is a petascale hydrostatic framework, which employs the cubed-sphere grid system and high-order continuous or discontinuous Galerkin (DG) methods. Recently, the HOMME framework is being extended to a non-hydrostatic dynamical core, named as the "High-Order Multiscale Atmospheric Model (HOMAM)." The spatial discretization is based on DG or high-order finite-volume methods. Orography is handled by the terrain-following height-based coordinate system. To alleviate the stringent CFL stability requirement resulting from the vertical aspects of the dynamics, an operator-splitting time integration scheme based on the horizontally explicit and vertically implicit (HEVI) philosophy is adopted for HOMAM. Preliminary results with the benchmark test cases proposed in the Dynamical Core Model Intercomparison project (DCMIP) test-suite will be presented in the seminar.
The Renormalization of the Electroweak Standard Model to All Orders
Kraus, E
1998-01-01
We give the renormalization of the standard model of electroweak interactions to all orders of perturbation theory by using the method of algebraic renormalization, which is based on general properties of renormalized perturbation theory and not on a specific regularization scheme. The Green functions of the standard model are uniquely constructed to all orders, if one defines the model by the Slavnov-Taylor identity, Ward-identities of rigid symmetry and a specific form of the abelian local gauge Ward-identity, which continues the Gell-Mann Nishijima relation to higher orders. Special attention is directed to the mass diagonalization of massless and massive neutral vectors and ghosts. For obtaining off-shell infrared finite expressions it is required to take into account higher order corrections into the functional symmetry operators. It is shown, that the normalization conditions of the on-shell schemes are in agreement with the most general symmetry transformations allowed by the algebraic constraints.
NEW METHOD FOR LOW ORDER SPECTRAL MODEL AND ITS APPLICATION
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In order to overcome the deficiency in classical method of low order spectral model, a new method for low order spectral model was advanced. Through calculating the multiple correlation coefficients between combinations of different functions and the recorded data under the least square criterion, the truncated functions which can mostly reflect the studied physical phenomenon were objectively distilled from these data. The new method overcomes the deficiency of artificially selecting the truncated functions in the classical low order spectral model. The new method being applied to study the inter-annual variation of summer atmospheric circulation over Northern Hemisphere, the truncated functions were obtained with the atmospheric circulation data of June 1994 and June 1998. The mechanisms for the two-summer atmospheric circulation variations over Northern Hemisphere were obtained with two-layer quasi-geostrophic baroclinic equation.
Order reduction for a model of marine bacteriophage evolution
Pagliarini, Silvia; Korobeinikov, Andrei
2017-02-01
A typical mechanistic model of viral evolution necessary includes several time scales which can differ by orders of magnitude. Such a diversity of time scales makes analysis of these models difficult. Reducing the order of a model is highly desirable when handling such a model. A typical approach applied to such slow-fast (or singularly perturbed) systems is the time scales separation technique. Constructing the so-called quasi-steady-state approximation is the usual first step in applying the technique. While this technique is commonly applied, in some cases its straightforward application can lead to unsatisfactory results. In this paper we construct the quasi-steady-state approximation for a model of evolution of marine bacteriophages based on the Beretta-Kuang model. We show that for this particular model the quasi-steady-state approximation is able to produce only qualitative but not quantitative fit.
Modeling Human Behaviour with Higher Order Logic: Insider Threats
DEFF Research Database (Denmark)
Boender, Jaap; Ivanova, Marieta Georgieva; Kammuller, Florian
2014-01-01
In this paper, we approach the problem of modeling the human component in technical systems with a view on the difference between the use of model and theory in sociology and computer science. One aim of this essay is to show that building of theories and models for sociology can be compared...... 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...
Endogenizing technological progress: The MESEMET model
P.A.G. van Bergeijk (Peter); G.H.A. van Hagen; R.A. de Mooij (Ruud); J. van Sinderen (Jarig)
1997-01-01
textabstractThis paper endogenizes technology and human capital formation in the MESEM model that was developed by van Sinderen (Economic Modelling, 1993, 13, 285-300). Tax allowances for private R&D expenditures and public expenditures on both education and R& D are effective instruments to stimula
Next-to-leading order corrections to the valon model
Indian Academy of Sciences (India)
G R Bouroun; E Esfandyari
2016-01-01
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.
Data-Driven Model Order Reduction for Bayesian Inverse Problems
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.
Prognosis Research Strategy (PROGRESS 3: prognostic model research.
Directory of Open Access Journals (Sweden)
Ewout W Steyerberg
Full Text Available Prognostic models are abundant in the medical literature yet their use in practice seems limited. In this article, the third in the PROGRESS series, the authors review how such models are developed and validated, and then address how prognostic models are assessed for their impact on practice and patient outcomes, illustrating these ideas with examples.
New models of neoplastic progression in Barrett's oesophagus
Pavlov, Kirill; Maley, Carlo C.
2010-01-01
Research in Barrett's oesophagus, and neoplastic progression to OAC (oesophageal adenocarcinoma), is hobbled by the lack of good pre-clinical models that capture the evolutionary dynamics of Barrett's cell populations. Current models trade off tractability for realism. Computational models are perha
A Fractional Order Recovery SIR Model from a Stochastic Process.
Angstmann, C N; Henry, B I; McGann, A V
2016-03-01
Over the past several decades, there has been a proliferation of epidemiological models with ordinary derivatives replaced by fractional derivatives in an ad hoc manner. These models may be mathematically interesting, but their relevance is uncertain. Here we develop an SIR model for an epidemic, including vital dynamics, from an underlying stochastic process. We show how fractional differential operators arise naturally in these models whenever the recovery time from the disease is power-law distributed. This can provide a model for a chronic disease process where individuals who are infected for a long time are unlikely to recover. The fractional order recovery model is shown to be consistent with the Kermack-McKendrick age-structured SIR model, and it reduces to the Hethcote-Tudor integral equation SIR model. The derivation from a stochastic process is extended to discrete time, providing a stable numerical method for solving the model equations. We have carried out simulations of the fractional order recovery model showing convergence to equilibrium states. The number of infecteds in the endemic equilibrium state increases as the fractional order of the derivative tends to zero.
Progress in Global Multicompartmental Modelling of DDT
Stemmler, I.; Lammel, G.
2009-04-01
Dichlorophenyltrichloroethane, DDT, and its major metabolite dichlorophenyldichloroethylene, DDE, are long-lived in the environment (persistent) and circulate since the 1950s. They accumulate along food chains, cause detrimental effects in marine and terrestrial wild life, and pose a hazard for human health. DDT was widely used as an insecticide in the past and is still in use in a number of tropical countries to combat vector borne diseases like malaria and typhus. It is a multicompartmental substance with only a small mass fraction residing in air. A global multicompartment chemistry transport model (MPI-MCTM; Semeena et al., 2006) is used to study the environmental distribution and fate of dichlorodiphenyltrichloroethane (DDT). For the first time a horizontally and vertically resolved global model was used to perform a long-term simulation of DDT and DDE. The model is based on general circulation models for the ocean (MPIOM; Marsland et al., 2003) and atmosphere (ECHAM5). In addition, an oceanic biogeochemistry model (HAMOCC5.1; Maier-Reimer et al., 2005 ) and a microphysical aerosol model (HAM; Stier et al., 2005 ) are included. Multicompartmental substances are cycling in atmosphere (3 phases), ocean (3 phases), top soil (3 phases), and vegetation surfaces. The model was run for 40 years forced with historical agricultural application data of 1950-1990. The model results show that the global environmental contamination started to decrease in air, soil and vegetation after the applications peaked in 1965-70. In some regions, however, the DDT mass had not yet reached a maximum in 1990 and was still accumulating mass until the end of the simulation. Modelled DDT and DDE concentrations in atmosphere, ocean and soil are evaluated by comparison with observational data. The evaluation of the model results indicate that degradation of DDE in air was underestimated. Also for DDT, the discrepancies between model results and observations are related to uncertainties of
Flood Progression Modelling and Impact Analysis
DEFF Research Database (Denmark)
Mioc, Darka; Anton, François; Nickerson, B.
People living in the lower valley of the St. John River, New Brunswick, Canada, frequently experience flooding when the river overflows its banks during spring ice melt and rain. To better prepare the population of New Brunswick for extreme flooding, we developed a new flood prediction model...... that computes floodplain polygons before the flood occurs. This allows emergency managers to access the impact of the flood before it occurs and make the early decisions for evacuation of the population and flood rescue. This research shows that the use of GIS and LiDAR technologies combined with hydrological...... modelling can significantly improve the decision making and visualization of flood impact needed for emergency planning and flood rescue. Furthermore, the 3D GIS application we developed for modelling flooded buildings and infrastructure provides a better platform for modelling and visualizing flood...
Projection-Based Reduced Order Modeling for Spacecraft Thermal Analysis
Qian, Jing; Wang, Yi; Song, Hongjun; Pant, Kapil; Peabody, Hume; Ku, Jentung; Butler, Charles D.
2015-01-01
This paper presents a mathematically rigorous, subspace projection-based reduced order modeling (ROM) methodology and an integrated framework to automatically generate reduced order models for spacecraft thermal analysis. Two key steps in the reduced order modeling procedure are described: (1) the acquisition of a full-scale spacecraft model in the ordinary differential equation (ODE) and differential algebraic equation (DAE) form to resolve its dynamic thermal behavior; and (2) the ROM to markedly reduce the dimension of the full-scale model. Specifically, proper orthogonal decomposition (POD) in conjunction with discrete empirical interpolation method (DEIM) and trajectory piece-wise linear (TPWL) methods are developed to address the strong nonlinear thermal effects due to coupled conductive and radiative heat transfer in the spacecraft environment. Case studies using NASA-relevant satellite models are undertaken to verify the capability and to assess the computational performance of the ROM technique in terms of speed-up and error relative to the full-scale model. ROM exhibits excellent agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) along with salient computational acceleration (up to two orders of magnitude speed-up) over the full-scale analysis. These findings establish the feasibility of ROM to perform rational and computationally affordable thermal analysis, develop reliable thermal control strategies for spacecraft, and greatly reduce the development cycle times and costs.
An Order Statistics Approach to the Halo Model for Galaxies
Paul, Niladri; Paranjape, Aseem; Sheth, Ravi K.
2017-01-01
We use the Halo Model to explore the implications of assuming that galaxy luminosities in groups are randomly drawn from an underlying luminosity function. We show that even the simplest of such order statistics models - one in which this luminosity function p(L) is universal - naturally produces a number of features associated with previous analyses based on the `central plus Poisson satellites' hypothesis. These include the monotonic relation of mean central luminosity with halo mass, the Lognormal distribution around this mean, and the tight relation between the central and satellite mass scales. In stark contrast to observations of galaxy clustering, however, this model predicts no luminosity dependence of large scale clustering. We then show that an extended version of this model, based on the order statistics of a halo mass dependent luminosity function p(L|m), is in much better agreement with the clustering data as well as satellite luminosities, but systematically under-predicts central luminosities. This brings into focus the idea that central galaxies constitute a distinct population that is affected by different physical processes than are the satellites. We model this physical difference as a statistical brightening of the central luminosities, over and above the order statistics prediction. The magnitude gap between the brightest and second brightest group galaxy is predicted as a by-product, and is also in good agreement with observations. We propose that this order statistics framework provides a useful language in which to compare the Halo Model for galaxies with more physically motivated galaxy formation models.
Reduced Order Internal Models in the Frequency Domain
Laakkonen, Petteri; Paunonen, Lassi
2016-01-01
The internal model principle states that all robustly regulating controllers must contain a suitably reduplicated internal model of the signal to be regulated. Using frequency domain methods, we show that the number of the copies may be reduced if the class of perturbations in the problem is restricted. We present a two step design procedure for a simple controller containing a reduced order internal model achieving robust regulation. The results are illustrated with an example of a five tank...
On the verification of PGD reduced-order models
Pled, Florent; Chamoin, Ludovic; Ladevèze, Pierre
2014-01-01
International audience; In current computational mechanics practice, multidimensional as well as multiscale or parametric models encountered in a wide variety of scientific and engineering fields often require either the resolution of significantly large complexity problems or the direct calculation of very numerous solutions of such complex models. In this framework, the use of model order reduction allows to dramatically reduce the computational requirements engendered by the increasing mod...
Optimal ordering policies for continuous review perishable inventory models.
Weiss, H J
1980-01-01
This paper extends the notions of perishable inventory models to the realm of continuous review inventory systems. The traditional perishable inventory costs of ordering, holding, shortage or penalty, disposal and revenue are incorporated into the continuous review framework. The type of policy that is optimal with respect to long run average expected cost is presented for both the backlogging and lost-sales models. In addition, for the lost-sales model the cost function is presented and analyzed.
A first-order thermal model for building design
Energy Technology Data Exchange (ETDEWEB)
Mathews, E.H. [Centre for Experimental and Numerical Thermoflow, Univ. of Pretoria (South Africa); Richards, P.G. [Centre for Experimental and Numerical Thermoflow, Univ. of Pretoria (South Africa); Lombard, C. [Centre for Experimental and Numerical Thermoflow, Univ. of Pretoria (South Africa)
1994-12-31
Simplified thermal models of buildings can successfully be applied in building design. This paper describes the derivation and validation of a first-order thermal model which has a clear physical interpretation, is based on uncomplicated calculation procedures and requires limited input information. Because extensive simplifications and assumptions are inherent in the development of the model, a comprehensive validation study is reported. The validity of the thermal model was proven with 70 validation studies in 32 buildings comprising a wide range of thermal characteristics. The accuracy of predictions compares well with other sophisticated programs. The proposed model is considered to be eminently suitable for incorporation in an efficient design tool. (orig.)
Abnormal Waves Modelled as Second-order Conditional Waves
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2005-01-01
The paper presents results for the expected second order short-crested wave conditional of a given wave crest at a specific point in time and space. The analysis is based on the second order Sharma and Dean shallow water wave theory. Numerical results showing the importance of the spectral density......, the water depth and the directional spreading on the conditional mean wave profile are presented. Application of conditional waves to model and explain abnormal waves, e.g. the well-known New Year Wave measured at the Draupner platform January 1st 1995, is discussed. Whereas the wave profile can be modelled...... quite well by the second order conditional wave including directional spreading and finite water depth the probability to encounter such a wave is still, however, extremely rare. The use of the second order conditional wave as initial condition to a fully non-linear three-dimensional analysis...
Denker, Elsa; Manuel, Michaël; Leclère, Lucas; Le Guyader, Hervé; Rabet, Nicolas
2008-03-01
Nematogenesis, the production of stinging cells (nematocytes) in Cnidaria, can be considered as a model neurogenic process. Most molecular data concern the freshwater polyp Hydra, in which nematocyte production is scattered throughout the body column ectoderm, the mature cells then migrating to the tentacles. We have characterized tentacular nematogenesis in the Clytia hemisphaerica hydromedusa and found it to be confined to the ectoderm of the tentacle bulb, a specialized swelling at the tentacle base. Analysis by a variety of light and electron microscope techniques revealed that while cellular aspects of nematogenesis are similar to Hydra, the spatio-temporal characteristics are markedly more ordered. The tentacle bulb nematogenic ectoderm (TBE) was found to be polarized, with a clear progression of successive nematoblast stages from a proximal zone (comprising a majority of undifferentiated cells) to the distal end where the tentacle starts. Pulse-chase labelling experiments demonstrated a continuous displacement of differentiating nematoblasts towards the tentacle tip, and that nematogenesis proceeds more rapidly in Clytia than in Hydra. Compact expression domains of orthologues of known nematogenesis-associated genes (Piwi, dickkopf-3, minicollagens and NOWA) were correspondingly staggered along the TBE. These distinct characteristics make the Clytia TBE a promising experimental system for understanding the mechanisms regulating nematogenesis.
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).
Identification of slow molecular order parameters for Markov model construction
Perez-Hernandez, Guillermo; Giorgino, Toni; de Fabritiis, Gianni; Noé, Frank
2013-01-01
A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes, involving (i) identification of the structural changes involved in these processes, and (ii) estimation of the rates or timescales at which these slow processes occur. Most of the approaches to this task, including Markov models, Master-equation models, and kinetic network models, start by discretizing the high-dimensional state space and then characterize relaxation processes in terms of the eigenvectors and eigenvalues of a discrete transition matrix. The practical success of such an approach depends very much on the ability to finely discretize the slow order parameters. How can this task be achieved in a high-dimensional configuration space without relying on subjective guesses of the slow order parameters? In this paper, we use the variational principle of conformation dynamics to derive an optimal way of identifying the "slow subspace" of a large set of prior order parameters - either g...
Using of "pseudo-second-order model" in adsorption.
Ho, Yuh-Shan
2014-01-01
A research paper's contribution exists not only in its originality and creativity but also in its continuity and development for research that follows. However, the author easily ignores it. Citation error and quotation error occurred very frequently in a scientific paper. Numerous researchers use secondary references without knowing the original idea from authors. Sulaymon et al. (Environ Sci Pollut Res 20:3011-3023, 2013) and Spiridon et al. (Environ Sci Pollut Res 20:6367-6381, 2013) presented wrong pseudo-second-order models in Environmental Science and Pollution Research, vol. 20. This comment pointed the errors of the kinetic models and offered information for citing original idea of pseudo-second-order kinetic expression. In order to stop the proliferation of the mistake, it is suggested to cite the original paper for the kinetic model which provided greater accuracy and more details about the kinetic expression.
Reduced order modeling of some fluid flows of industrial interest
Energy Technology Data Exchange (ETDEWEB)
Alonso, D; Terragni, F; Velazquez, A; Vega, J M, E-mail: josemanuel.vega@upm.es [E.T.S.I. Aeronauticos, Universidad Politecnica de Madrid, 28040 Madrid (Spain)
2012-06-01
Some basic ideas are presented for the construction of robust, computationally efficient reduced order models amenable to be used in industrial environments, combined with somewhat rough computational fluid dynamics solvers. These ideas result from a critical review of the basic principles of proper orthogonal decomposition-based reduced order modeling of both steady and unsteady fluid flows. In particular, the extent to which some artifacts of the computational fluid dynamics solvers can be ignored is addressed, which opens up the possibility of obtaining quite flexible reduced order models. The methods are illustrated with the steady aerodynamic flow around a horizontal tail plane of a commercial aircraft in transonic conditions, and the unsteady lid-driven cavity problem. In both cases, the approximations are fairly good, thus reducing the computational cost by a significant factor. (review)
Research on Modeling of Hydropneumatic Suspension Based on Fractional Order
Directory of Open Access Journals (Sweden)
Junwei Zhang
2015-01-01
Full Text Available With such excellent performance as nonlinear stiffness, adjustable vehicle height, and good vibration resistance, hydropneumatic suspension (HS has been more and more applied to heavy vehicle and engineering vehicle. Traditional modeling methods are still confined to simple models without taking many factors into consideration. A hydropneumatic suspension model based on fractional order (HSM-FO is built with the advantage of fractional order (FO in viscoelastic material modeling considering the mechanics property of multiphase medium of HS. Then, the detailed calculation method is proposed based on Oustaloup filtering approximation algorithm. The HSM-FO is implemented in Matlab/Simulink, and the results of comparison among the simulation curve of fractional order, integral order, and the curve of real experiment prove the feasibility and validity of HSM-FO. The damping force property of the suspension system under different fractional orders is also studied. In the end of this paper, several conclusions concerning HSM-FO are drawn according to analysis of simulation.
Low Order Empirical Galerkin Models for Feedback Flow Control
Tadmor, Gilead; Noack, Bernd
2005-11-01
Model-based feedback control restrictions on model order and complexity stem from several generic considerations: real time computation, the ability to either measure or reliably estimate the state in real time and avoiding sensitivity to noise, uncertainty and numerical ill-conditioning are high on that list. Empirical POD Galerkin models are attractive in the sense that they are simple and (optimally) efficient, but are notoriously fragile, and commonly fail to capture transients and control effects. In this talk we review recent efforts to enhance empirical Galerkin models and make them suitable for feedback design. Enablers include `subgrid' estimation of turbulence and pressure representations, tunable models using modes from multiple operating points, and actuation models. An invariant manifold defines the model's dynamic envelope. It must be respected and can be exploited in observer and control design. These ideas are benchmarked in the cylinder wake system and validated by a systematic DNS investigation of a 3-dimensional Galerkin model of the controlled wake.
Nonlocal order parameters for the 1D Hubbard model.
Montorsi, Arianna; Roncaglia, Marco
2012-12-07
We characterize the Mott-insulator and Luther-Emery phases of the 1D Hubbard model through correlators that measure the parity of spin and charge strings along the chain. These nonlocal quantities order in the corresponding gapped phases and vanish at the critical point U(c)=0, thus configuring as hidden order parameters. The Mott insulator consists of bound doublon-holon pairs, which in the Luther-Emery phase turn into electron pairs with opposite spins, both unbinding at U(c). The behavior of the parity correlators is captured by an effective free spinless fermion model.
A test of first order scaling in Nf =2 QCD: a progress report
Bonati, C; D'Elia, M; Di Giacomo, A; Pica, C
2008-01-01
We present the status of our analysis on the order of the finite temperature transition in QCD with two flavors of degenerate fermions. Our new simulations on large lattices support the hypothesis of the first order nature of the transition, showing a preliminary two state signal. We will discuss the implications and the next steps in our analysis.
Assess progress being made for the KTeV electromagnetic calorimeter crystal order in France
Childress, S. R.
1993-08-01
This report contains a record of our activities at the Quartz & Silice facility during this visit. Significant progress was achieved in illustrating the importance and practical application of particular measurements in characterizing crystal quality, and in understanding problems with crystal polishing techniques currently being used. Detailed discussions with Quartz & Silice personnel on these issues were held, as were discussions on current production and furnace growth cycle options which may significantly increase ingot production rates.
Fuzzy Economic Order Quantity Inventory Models Without Backordering
Institute of Scientific and Technical Information of China (English)
WANG Xiaobin; TANG Wansheng; ZHAO Ruiqing
2007-01-01
In economic order quantity models without backordering, both the stock cost of each unit quantity and the order cost of each cycle are characterized as independent fuzzy variables rather than fuzzy numbers as in previous studies. Based on an expected value criterion or a credibility criterion, a fuzzy expected value model and a fuzzy dependent hance programming (DCP) model are constructed. The purpose of the fuzzy expected value model is to find the optimal order quantity such that the fuzzy expected value of the total cost is minimal. The fuzzy DCP model is used to find the optimal order quantity for maximizing the credibility of an event such that the total cost in the planning periods does not exceed a certain budget level.Fuzzy simulations are designed to calculate the expected value of the fuzzy objective function and the credibility of each fuzzy event. A particle swarm optimization (PSO) algorithm based on a fuzzy simulation is designed, by integrating the fuzzy simulation and the PSO algorithm. Finally, a numerical example is given to illustrate the feasibility and validity of the proposed algorithm.
Model Order Reduction for Fluid Dynamics with Moving Solid Boundary
Gao, Haotian; Wei, Mingjun
2016-11-01
We extended the application of POD-Galerkin projection for model order reduction from usual fixed-domain problems to more general fluid-solid systems when moving boundary/interface is involved. The idea is similar to numerical simulation approaches using embedded forcing terms to represent boundary motion and domain change. However, such a modified approach will not get away with the unsteadiness of boundary terms which appear as time-dependent coefficients in the new Galerkin model. These coefficients need to be pre-computed for prescribed motion, or worse, to be computed at each time step for non-prescribed motion. The extra computational cost gets expensive in some cases and eventually undermines the value of using reduced-order models. One solution is to decompose the moving boundary/domain to orthogonal modes and derive another low-order model with fixed coefficients for boundary motion. Further study shows that the most expensive integrations resulted from the unsteady motion (in both original and domain-decomposition approaches) have almost negligible impact on the overall dynamics. Dropping these expensive terms reduces the computation cost by at least one order while no obvious effect on model accuracy is noticed. Supported by ARL.
Ordering kinetics in model systems with inhibited interfacial adsorption
DEFF Research Database (Denmark)
Willart, J.-F.; Mouritsen, Ole G.; Naudts, J.
1992-01-01
The ordering kinetics in two-dimensional Ising-like spin moels with inhibited interfacial adsorption are studied by computer-simulation calculations. The inhibited interfacial adsorption is modeled by a particular interfacial adsorption condition on the structure of the domain wall between...... neighboring domains. This condition can be either hard, as modeled by a singularity in the domain-boundary potential, or soft, as modeled by a version of the Blume-Capel model. The results show that the effect of the steric hindrance, be it hard or soft, is only manifested in the amplitude, A...
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
DOE Order 5820.2A implementation status, progress and problems
Energy Technology Data Exchange (ETDEWEB)
Waldo, L.C. [Dept. of Energy, Washington, DC (United States). Waste Operations Div.; Shepard, M.D. [BDM Corp., Germantown, MD (United States); Wilhite, E.L. [Westinghouse Savannah River Co., Aiken, SC (United States). Savannah River Lab.
1989-11-01
The Department of Energy`s Order governing management of radioactive waste, DOE Order 5820.2A, was revised effective September 26, 1988. Chapter III of the Order contains prescriptive requirements for managing low-level waste. These requirements ensure that all DOE low-level radioactive and mixed waste will be managed in a systematic manner to achieve required performance., The Order defines performance objectives for low-level waste management to limit the dose received by the general public from waste operations, to protect groundwater resources, and to protect inadvertent intruders. For low-level waste disposal operations, the Order requires that a radiological performance assessment be prepared to demonstrate compliance with the performance objectives. The Order also requires that the radiological performance assessments be reviewed by a Peer Review Panel, established by the Order. This paper will summarize the requirements for radioactive waste management and discuss the degree of compliance achieved to date. The Department`s preliminary schedule and anticipated cost to achieve full compliance with the requirements will also be discussed.
Parameterized reduced-order models using hyper-dual numbers.
Energy Technology Data Exchange (ETDEWEB)
Fike, Jeffrey A.; Brake, Matthew Robert
2013-10-01
The goal of most computational simulations is to accurately predict the behavior of a real, physical system. Accurate predictions often require very computationally expensive analyses and so reduced order models (ROMs) are commonly used. ROMs aim to reduce the computational cost of the simulations while still providing accurate results by including all of the salient physics of the real system in the ROM. However, real, physical systems often deviate from the idealized models used in simulations due to variations in manufacturing or other factors. One approach to this issue is to create a parameterized model in order to characterize the effect of perturbations from the nominal model on the behavior of the system. This report presents a methodology for developing parameterized ROMs, which is based on Craig-Bampton component mode synthesis and the use of hyper-dual numbers to calculate the derivatives necessary for the parameterization.
An Order Statistics Approach to the Halo Model for Galaxies
Paul, Niladri; Sheth, Ravi K
2016-01-01
We use the Halo Model to explore the implications of assuming that galaxy luminosities in groups are randomly drawn from an underlying luminosity function. We show that even the simplest of such order statistics models -- one in which this luminosity function $p(L)$ is universal -- naturally produces a number of features associated with previous analyses based on the `central plus Poisson satellites' hypothesis. These include the monotonic relation of mean central luminosity with halo mass, the Lognormal distribution around this mean, and the tight relation between the central and satellite mass scales. In stark contrast to observations of galaxy clustering, however, this model predicts $\\textit{no}$ luminosity dependence of large scale clustering. We then show that an extended version of this model, based on the order statistics of a $\\textit{halo mass dependent}$ luminosity function $p(L|m)$, is in much better agreement with the clustering data as well as satellite luminosities, but systematically under-pre...
Reduced order modeling of grid-connected photovoltaic inverter systems
Wasynczuk, O.; Krause, P. C.; Anwah, N. A.
1988-04-01
This report summarizes the development of reduced order models of three-phase, line- and self-commutated inverter systems. This work was performed as part of the National Photovoltaics Program within the United States Department of Energy and was supervised by Sandia National Laboratories. The overall objective of the national program is to promote the development of low cost, reliable terrestrial photovoltaic systems for widespread use in residential, commercial and utility applications. The purpose of the effort reported herein is to provide reduced order models of three-phase, line- and self-commutated PV systems suitable for implementation into transient stability programs, which are commonly used to predict the stability characteristics of large-scale power systems. The accuracy of the reduced models is verified by comparing the response characteristics predicted therefrom with the response established using highly detailed PV system models in which the inverter switching is represented in detail.
Numerical modeling of higher order magnetic moments in UXO discrimination
Sanchez, V.; Yaoguo, L.; Nabighian, M.N.; Wright, D.L.
2008-01-01
The surface magnetic anomaly observed in unexploded ordnance (UXO) clearance is mainly dipolar, and consequently, the dipole is the only magnetic moment regularly recovered in UXO discrimination. The dipole moment contains information about the intensity of magnetization but lacks information about the shape of the target. In contrast, higher order moments, such as quadrupole and octupole, encode asymmetry properties of the magnetization distribution within the buried targets. In order to improve our understanding of magnetization distribution within UXO and non-UXO objects and to show its potential utility in UXO clearance, we present a numerical modeling study of UXO and related metallic objects. The tool for the modeling is a nonlinear integral equation describing magnetization within isolated compact objects of high susceptibility. A solution for magnetization distribution then allows us to compute the magnetic multipole moments of the object, analyze their relationships, and provide a depiction of the anomaly produced by different moments within the object. Our modeling results show the presence of significant higher order moments for more asymmetric objects, and the fields of these higher order moments are well above the noise level of magnetic gradient data. The contribution from higher order moments may provide a practical tool for improved UXO discrimination. ?? 2008 IEEE.
A reduced order model for nonlinear vibroacoustic problems
Directory of Open Access Journals (Sweden)
Ouisse Morvan
2012-07-01
Full Text Available This work is related to geometrical nonlinearities applied to thin plates coupled with fluid-filled domain. Model reduction is performed to reduce the computation time. Reduced order model (ROM is issued from the uncoupled linear problem and enriched with residues to describe the nonlinear behavior and coupling effects. To show the efficiency of the proposed method, numerical simulations in the case of an elastic plate closing an acoustic cavity are presented.
Robust simulation of buckled structures using reduced order modeling
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.
Atmospheric Turbulence Modeling for Aero Vehicles: Fractional Order Fits
Kopasakis, George
2015-01-01
Atmospheric turbulence models are necessary for the design of both inlet/engine and flight controls, as well as for studying coupling between the propulsion and the vehicle structural dynamics for supersonic vehicles. Models based on the Kolmogorov spectrum have been previously utilized to model atmospheric turbulence. In this paper, a more accurate model is developed in its representative fractional order form, typical of atmospheric disturbances. This is accomplished by first scaling the Kolmogorov spectral to convert them into finite energy von Karman forms and then by deriving an explicit fractional circuit-filter type analog for this model. This circuit model is utilized to develop a generalized formulation in frequency domain to approximate the fractional order with the products of first order transfer functions, which enables accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.
A multi agent model for the limit order book dynamics
Bartolozzi, M.
2010-01-01
In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book.aEuro (c) The agents follow a noise decision making process where the
Higher-Order Item Response Models for Hierarchical Latent Traits
Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming
2013-01-01
Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…
Vectorial electron transfer in spatially ordered arrays. Progress report, January 1991--January 1994
Energy Technology Data Exchange (ETDEWEB)
Fox, M.A.
1994-01-01
Objective was to find methods for rapid, controlled placement of light absorbers, relays, and multi-electron catalysts at defined sites with respect to a semiconductor or metal surface and thus to develop methods for preparing chemically modified photoactive surfaces as artificial photosynthetic units. Progress has been made in four areas: synthesis of new materials for directional electron transfer, preparation and characterization of anisotropic composites containing organic and inorganic components, elaboration of mechanisms of electrocatalysis, and development of new methods for surface modification of metals and semiconductors.
Update rules and interevent time distributions: Slow ordering vs. no ordering in the Voter Model
Fernández-Gracia, Juan; Miguel, M San
2011-01-01
We introduce a general methodology of update rules accounting for arbitrary interevent time distributions in simulations of interacting agents. In particular we consider update rules that depend on the state of the agent, so that the update becomes part of the dynamical model. As an illustration we consider the voter model in fully-connected, random and scale free networks with an update probability inversely proportional to the persistence, that is, the time since the last event. We find that in the thermodynamic limit, at variance with standard updates, the system orders slowly. The approach to the absorbing state is characterized by a power law decay of the density of interfaces, observing that the mean time to reach the absorbing state might be not well defined.
Progress in studying scintillator proportionality: Phenomenological model
Energy Technology Data Exchange (ETDEWEB)
Bizarri, Gregory; Cherepy, Nerine; Choong, Woon-Seng; Hull, Giulia; Moses, William; Payne, Sephen; Singh, Jai; Valentine, John; Vasilev, Andrey; Williams, Richard
2009-04-30
We present a model to describe the origin of non-proportional dependence of scintillator light yield on the energy of an ionizing particle. The non-proportionality is discussed in terms of energy relaxation channels and their linear and non-linear dependences on the deposited energy. In this approach, the scintillation response is described as a function of the deposited energy deposition and the kinetic rates of each relaxation channel. This mathematical framework allows both a qualitative interpretation and a quantitative fitting representation of scintillation non-proportionality response as function of kinetic rates. This method was successfully applied to thallium doped sodium iodide measured with SLYNCI, a new facility using the Compton coincidence technique. Finally, attention is given to the physical meaning of the dominant relaxation channels, and to the potential causes responsible for the scintillation non-proportionality. We find that thallium doped sodium iodide behaves as if non-proportionality is due to competition between radiative recombinations and non-radiative Auger processes.
Bilinear reduced order approximate model of parabolic distributed solar collectors
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.
Reduced order modeling of fluid/structure interaction.
Energy Technology Data Exchange (ETDEWEB)
Barone, Matthew Franklin; Kalashnikova, Irina; Segalman, Daniel Joseph; Brake, Matthew Robert
2009-11-01
This report describes work performed from October 2007 through September 2009 under the Sandia Laboratory Directed Research and Development project titled 'Reduced Order Modeling of Fluid/Structure Interaction.' This project addresses fundamental aspects of techniques for construction of predictive Reduced Order Models (ROMs). A ROM is defined as a model, derived from a sequence of high-fidelity simulations, that preserves the essential physics and predictive capability of the original simulations but at a much lower computational cost. Techniques are developed for construction of provably stable linear Galerkin projection ROMs for compressible fluid flow, including a method for enforcing boundary conditions that preserves numerical stability. A convergence proof and error estimates are given for this class of ROM, and the method is demonstrated on a series of model problems. A reduced order method, based on the method of quadratic components, for solving the von Karman nonlinear plate equations is developed and tested. This method is applied to the problem of nonlinear limit cycle oscillations encountered when the plate interacts with an adjacent supersonic flow. A stability-preserving method for coupling the linear fluid ROM with the structural dynamics model for the elastic plate is constructed and tested. Methods for constructing efficient ROMs for nonlinear fluid equations are developed and tested on a one-dimensional convection-diffusion-reaction equation. These methods are combined with a symmetrization approach to construct a ROM technique for application to the compressible Navier-Stokes equations.
A first order system model of fracture healing
Institute of Scientific and Technical Information of China (English)
WANG Xiao-ping; ZHANG Xian-long; LI Zhu-guo; YU Xin-gang
2005-01-01
A first order system model is proposed for simulating the influence of stress stimulation on fracture strength during fracture healing. To validate the model, the diaphyses of bilateral tibiae in 70 New Zealand rabbits were osteotomized and fixed with rigid plates and stress-relaxation plates, respectively. Stress shielding rate and ultimate bending strength of the healing bone were measured at 2 to 48 weeks postoperatively. Ratios of stress stimulation and fracture strength of the healing bone to those of intact bone were taken as the system input and output. The assumed first order system model can approximate the experimental data on fracture strength from the input of stress stimulation over time, both for the rigid plate group and the stress-relaxation plate group, with different system parameters of time constant and gain. The fitting curve indicates that the effect of mechanical stimulus occurs mainly in late stages of healing. First order system can model the stress adaptation process of fracture healing. This approach presents a simple bio-mathematical model of the relationship between stress stimulation and fracture strength, and has the potential to optimize planning of functional exercises and conduct parametric studies.
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.
RECENT PROGRESS IN NONLINEAR EDDY-VISCOSITY TURBULENCE MODELING
Institute of Scientific and Technical Information of China (English)
符松; 郭阳; 钱炜祺; 王辰
2003-01-01
This article presents recent progresses in turbulence modeling in the Unit for Turbulence Simulation in the Department of Engineering Mechanics at Tsinghua University. The main contents include: compact Non-Linear Eddy-Viscosity Model (NLEVM) based on the second-moment closure, near-wall low-Re non-linear eddy-viscosity model and curvature sensitive turbulence model.The models have been validated in a wide range of complex flow test cases and the calculated results show that the present models exhibited overall good performance.
Directory of Open Access Journals (Sweden)
Lubna Moin
2009-04-01
analyzed. The approach towards the Genetic Tree formation from the Bond Graph is also developed. The model order reduction using Genetic Tree is in progress.
Directory of Open Access Journals (Sweden)
Shahid Ali
2009-04-01
analyzed. The approach towards the Genetic Tree formation from the Bond Graph is also developed. The model order reduction using Genetic Tree is in progress.
Anisotropic Third-Order Regularization for Sparse Digital Elevation Models
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.
Recent progress of ordered mesoporous silica-supported chiral metallic catalysts
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LIU Rui
2013-02-01
Full Text Available Recently,ordered silica-based mesoporous chiral organometallics-functionalized heterogeneous catalysts have attracted extensive research interest due to their excellent properties,such as easy preparation,high activity and convenient recycle.This review mainly summarizesthe generally prepared strategy and the silica-based organometallics-functionalized heterogeneous catalysts reported in the literatures.
Bayesian model evidence for order selection and correlation testing.
Johnston, Leigh A; Mareels, Iven M Y; Egan, Gary F
2011-01-01
Model selection is a critical component of data analysis procedures, and is particularly difficult for small numbers of observations such as is typical of functional MRI datasets. In this paper we derive two Bayesian evidence-based model selection procedures that exploit the existence of an analytic form for the linear Gaussian model class. Firstly, an evidence information criterion is proposed as a model order selection procedure for auto-regressive models, outperforming the commonly employed Akaike and Bayesian information criteria in simulated data. Secondly, an evidence-based method for testing change in linear correlation between datasets is proposed, which is demonstrated to outperform both the traditional statistical test of the null hypothesis of no correlation change and the likelihood ratio test.
An improved model for reduced-order physiological fluid flows
San, Omer; 10.1142/S0219519411004666
2012-01-01
An improved one-dimensional mathematical model based on Pulsed Flow Equations (PFE) is derived by integrating the axial component of the momentum equation over the transient Womersley velocity profile, providing a dynamic momentum equation whose coefficients are smoothly varying functions of the spatial variable. The resulting momentum equation along with the continuity equation and pressure-area relation form our reduced-order model for physiological fluid flows in one dimension, and are aimed at providing accurate and fast-to-compute global models for physiological systems represented as networks of quasi one-dimensional fluid flows. The consequent nonlinear coupled system of equations is solved by the Lax-Wendroff scheme and is then applied to an open model arterial network of the human vascular system containing the largest fifty-five arteries. The proposed model with functional coefficients is compared with current classical one-dimensional theories which assume steady state Hagen-Poiseuille velocity pro...
Empirical Reduced-Order Modeling for Boundary Feedback Flow Control
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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.
Analytical Higher-Order Model for Flexible and Stretchable Sensors
Institute of Scientific and Technical Information of China (English)
ZHANG Yongfang; ZHU Hongbin; LIU Cheng; LIU Xu; LIU Fuxi; L Yanjun
2015-01-01
The stretchable sensor wrapped around a foldable airfoil or embedded inside of it has great potential for use in the monitoring of the structural status of the foldable airfoil. The design methodology is important to the development of the stretchable sensor for status monitoring on the foldable airfoil. According to the requirement of mechanical flexibility of the sensor, the combined use of a layered flexible structural formation and a strain isolation layer is implemented. An analytical higher-order model is proposed to predict the stresses of the strain-isolation layer based on the shear-lag model for the safe design of the flexible and stretchable sensors. The normal stress and shear stress equations in the constructed structure of the sensors are obtained by the proposed model. The stress distribution in the structure is investigated when bending load is applied to the structures. The numerical results show that the proposed model can predict the variation of normal stress and shear stress along the thickness of the strain-isolation (polydimethylsiloxane) layer accurately. The results by the proposed model are in good agreement with the finite element method, in which the normal stress is variable while the shear stress is invariable along the thickness direction of strain-isolation layer. The high-order model is proposed to predict the stresses of the layered structure of the flexible and stretchable sensor for monitoring the status of the foldable airfoil.
A multi agent model for the limit order book dynamics
Bartolozzi, M.
2010-11-01
In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a stochastic variable, the market sentiment, which we define as a mixture of public and private information. The model, despite making just few basic assumptions over the trading strategies of the agents, is able to reproduce several empirical features of the high-frequency dynamics of the market microstructure not only related to the price movements but also to the deposition of the orders in the book.
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...
Directory of Open Access Journals (Sweden)
Nita H. Shah
2011-01-01
Full Text Available The terminal condition of inventory level to be zero at the end of the cycle time adopted by Soni and Shah (2008, 2009 is not viable when demand is stock-dependent. To rectify this assumption, we extend their model for (1 an ending – inventory to be non-zero; (2 limited floor space; (3 a profit maximization model; (4 selling price to be a decision variable, and (5 units in inventory deteriorate at a constant rate. The algorithm is developed to search for the optimal decision policy. The working of the proposed model is supported with a numerical example. Sensitivity analysis is carried out to investigate critical parameters.
Wave Transformation Modeling with Effective Higher-Order Finite Elements
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Tae-Hwa Jung
2016-01-01
Full Text Available This study introduces a finite element method using a higher-order interpolation function for effective simulations of wave transformation. Finite element methods with a higher-order interpolation function usually employ a Lagrangian interpolation function that gives accurate solutions with a lesser number of elements compared to lower order interpolation function. At the same time, it takes a lot of time to get a solution because the size of the local matrix increases resulting in the increase of band width of a global matrix as the order of the interpolation function increases. Mass lumping can reduce computation time by making the local matrix a diagonal form. However, the efficiency is not satisfactory because it requires more elements to get results. In this study, the Legendre cardinal interpolation function, a modified Lagrangian interpolation function, is used for efficient calculation. Diagonal matrix generation by applying direct numerical integration to the Legendre cardinal interpolation function like conducting mass lumping can reduce calculation time with favorable accuracy. Numerical simulations of regular, irregular and solitary waves using the Boussinesq equations through applying the interpolation approaches are carried out to compare the higher-order finite element models on wave transformation and examine the efficiency of calculation.
Regularization method for calibrated POD reduced-order models
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El Majd Badr Abou
2014-01-01
Full Text Available In this work we present a regularization method to improve the accuracy of reduced-order models based on Proper Orthogonal Decomposition. The bench mark configuration retained corresponds to a case of relatively simple dynamics: a two-dimensional flow around a cylinder for a Reynolds number of 200. Finally, we show for this flow configuration that this procedure is efficient in term of reduction of errors.
The Complexity of Model Checking Higher-Order Fixpoint Logic
DEFF Research Database (Denmark)
Axelsson, Roland; Lange, Martin; Somla, Rafal
2007-01-01
of solving rather large parity games of small index. As a consequence of this we obtain an ExpTime upper bound on the expression complexity of each HFLk,m. The lower bound is established by a reduction from the word problem for alternating (k-1)-fold exponential space bounded Turing Machines. As a corollary...... provides complexity results for its model checking problem. In particular we consider its fragments HFLk,m which are formed using types of bounded order k and arity m only. We establish k-ExpTime-completeness for model checking each HFLk,m fragment. For the upper bound we reduce the problem to the problem...
On fractional order composite model reference adaptive control
Wei, Yiheng; Sun, Zhenyuan; Hu, Yangsheng; Wang, Yong
2016-08-01
This paper presents a novel composite model reference adaptive control approach for a class of fractional order linear systems with unknown constant parameters. The method is extended from the model reference adaptive control. The parameter estimation error of our method depends on both the tracking error and the prediction error, whereas the existing method only depends on the tracking error, which makes our method has better transient performance in the sense of generating smooth system output. By the aid of the continuous frequency distributed model, stability of the proposed approach is established in the Lyapunov sense. Furthermore, the convergence property of the model parameters estimation is presented, on the premise that the closed-loop control system is stable. Finally, numerical simulation examples are given to demonstrate the effectiveness of the proposed schemes.
Second Order Model for Strongly Sheared Compressible Turbulence
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marzougui hamed
2015-01-01
Full Text Available In this paper, we propose a model designed to describe a strongly sheared compressible homogeneous turbulent flows. Such flows are far from equilibrium and are well represented by the A3 and A4 cases of the DNS of Sarkar. Speziale and Xu developed a relaxation model in incompressible turbulence able to take into account significant departures from equilibrium. In a previous paper, Radhia et al. proposed a relaxation model similar to that of Speziale and Xu .This model is based on an algebraic representation of the Reynolds stress tensor, much simpler than that of Speziale and Xu and it gave a good result for rapid axisymetric contraction. In this work, we propose to extend the Radhia et al’s. model to compressible homogenous turbulence. This model is based on the pressure-strain model of Launder et al., where we incorporate turbulent Mach number in order to take into account compressibility effects. To assess this model, two numerical simulations were performed which are similar to the cases A3 and A4 of the DNS of Sarkar.
Update rules and interevent time distributions: slow ordering versus no ordering in the voter model.
Fernández-Gracia, J; Eguíluz, V M; San Miguel, M
2011-07-01
We introduce a general methodology of update rules accounting for arbitrary interevent time (IET) distributions in simulations of interacting agents. We consider in particular update rules that depend on the state of the agent, so that the update becomes part of the dynamical model. As an illustration we consider the voter model in fully connected, random, and scale-free networks with an activation probability inversely proportional to the time since the last action, where an action can be an update attempt (an exogenous update) or a change of state (an endogenous update). We find that in the thermodynamic limit, at variance with standard updates and the exogenous update, the system orders slowly for the endogenous update. The approach to the absorbing state is characterized by a power-law decay of the density of interfaces, observing that the mean time to reach the absorbing state might be not well defined. The IET distributions resulting from both update schemes show power-law tails.
Update rules and interevent time distributions: Slow ordering versus no ordering in the voter model
Fernández-Gracia, J.; Eguíluz, V. M.; San Miguel, M.
2011-07-01
We introduce a general methodology of update rules accounting for arbitrary interevent time (IET) distributions in simulations of interacting agents. We consider in particular update rules that depend on the state of the agent, so that the update becomes part of the dynamical model. As an illustration we consider the voter model in fully connected, random, and scale-free networks with an activation probability inversely proportional to the time since the last action, where an action can be an update attempt (an exogenous update) or a change of state (an endogenous update). We find that in the thermodynamic limit, at variance with standard updates and the exogenous update, the system orders slowly for the endogenous update. The approach to the absorbing state is characterized by a power-law decay of the density of interfaces, observing that the mean time to reach the absorbing state might be not well defined. The IET distributions resulting from both update schemes show power-law tails.
Progress in wall turbulence 2 understanding and modelling
Jimenez, Javier; Marusic, Ivan
2016-01-01
This is the proceedings of the ERCOFTAC Workshop on Progress in Wall Turbulence: Understanding and Modelling, that was held in Lille, France from June 18 to 20, 2014. The workshop brought together world specialists of near wall turbulence and stimulated exchanges between them around up-to-date theories, experiments, simulations and numerical models. This book contains a coherent collection of recent results on near wall turbulence including theory, new experiments, DNS, and modeling with RANS, LES.The fact that both physical understanding and modeling by different approaches are addressed by the best specialists in a single workshop is original.
Inferring tree causal models of cancer progression with probability raising.
Directory of Open Access Journals (Sweden)
Loes Olde Loohuis
Full Text Available Existing techniques to reconstruct tree models of progression for accumulative processes, such as cancer, seek to estimate causation by combining correlation and a frequentist notion of temporal priority. In this paper, we define a novel theoretical framework called CAPRESE (CAncer PRogression Extraction with Single Edges to reconstruct such models based on the notion of probabilistic causation defined by Suppes. We consider a general reconstruction setting complicated by the presence of noise in the data due to biological variation, as well as experimental or measurement errors. To improve tolerance to noise we define and use a shrinkage-like estimator. We prove the correctness of our algorithm by showing asymptotic convergence to the correct tree under mild constraints on the level of noise. Moreover, on synthetic data, we show that our approach outperforms the state-of-the-art, that it is efficient even with a relatively small number of samples and that its performance quickly converges to its asymptote as the number of samples increases. For real cancer datasets obtained with different technologies, we highlight biologically significant differences in the progressions inferred with respect to other competing techniques and we also show how to validate conjectured biological relations with progression models.
Order-parameter model for unstable multilane traffic flow
Lubashevsky; Mahnke
2000-11-01
We discuss a phenomenological approach to the description of unstable vehicle motion on multilane highways that explains in a simple way the observed sequence of the "free flow synchronized mode jam" phase transitions as well as the hysteresis in these transitions. We introduce a variable called an order parameter that accounts for possible correlations in the vehicle motion at different lanes. So, it is principally due to the "many-body" effects in the car interaction in contrast to such variables as the mean car density and velocity being actually the zeroth and first moments of the "one-particle" distribution function. Therefore, we regard the order parameter as an additional independent state variable of traffic flow. We assume that these correlations are due to a small group of "fast" drivers and by taking into account the general properties of the driver behavior we formulate a governing equation for the order parameter. In this context we analyze the instability of homogeneous traffic flow that manifested itself in the above-mentioned phase transitions and gave rise to the hysteresis in both of them. Besides, the jam is characterized by the vehicle flows at different lanes which are independent of one another. We specify a certain simplified model in order to study the general features of the car cluster self-formation under the "free flow synchronized motion" phase transition. In particular, we show that the main local parameters of the developed cluster are determined by the state characteristics of vehicle motion only.
Reduced order methods for modeling and computational reduction
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...
Cross gramian approximation with Laguerre polynomials for model order reduction
Perev, Kamen
2015-11-01
This paper considers the problem of model order reduction by approximate balanced truncation with Laguerre polynomials approximation of the system cross gramian. The cross gramian contains information both for the reachability of the system as well as for its observability. The main property of the cross gramian for a square symmetric stable linear system is that its square is equal to the product of the reachability and observability gramians and therefore, the absolute values of its eigenvalues are equal to the Hankel singular values. This is the reason to use the cross gramian for computing balancing transformations for model reduction. Laguerre polynomial series representations are used to approximate the cross gramian of the system at infinity. The orthogonal polynomials of Laguerre possess good convergence properties and allow to reduce the computational complexity of the model reduction problem. Numerical experiments are performed confirming the effectiveness of the proposed method.
A theoretical model to describe progressions and regressions for exercise rehabilitation.
Blanchard, Sam; Glasgow, Phil
2014-08-01
This article aims to describe a new theoretical model to simplify and aid visualisation of the clinical reasoning process involved in progressing a single exercise. Exercise prescription is a core skill for physiotherapists but is an area that is lacking in theoretical models to assist clinicians when designing exercise programs to aid rehabilitation from injury. Historical models of periodization and motor learning theories lack any visual aids to assist clinicians. The concept of the proposed model is that new stimuli can be added or exchanged with other stimuli, either intrinsic or extrinsic to the participant, in order to gradually progress an exercise whilst remaining safe and effective. The proposed model maintains the core skills of physiotherapists by assisting clinical reasoning skills, exercise prescription and goal setting. It is not limited to any one pathology or rehabilitation setting and can adapted by any level of skilled clinician.
gems: An R Package for Simulating from Disease Progression Models
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Nello Blaser
2015-03-01
Full Text Available Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death, displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.
Electroviscoelasticity of liquid/liquid interfaces: fractional-order model.
Spasic, Aleksandar M; Lazarevic, Mihailo P
2005-02-01
A number of theories that describe the behavior of liquid-liquid interfaces have been developed and applied to various dispersed systems, e.g., Stokes, Reiner-Rivelin, Ericksen, Einstein, Smoluchowski, and Kinch. A new theory of electroviscoelasticity describes the behavior of electrified liquid-liquid interfaces in fine dispersed systems and is based on a new constitutive model of liquids. According to this model liquid-liquid droplet or droplet-film structure (collective of particles) is considered as a macroscopic system with internal structure determined by the way the molecules (ions) are tuned (structured) into the primary components of a cluster configuration. How the tuning/structuring occurs depends on the physical fields involved, both potential (elastic forces) and nonpotential (resistance forces). All these microelements of the primary structure can be considered as electromechanical oscillators assembled into groups, so that excitation by an external physical field may cause oscillations at the resonant/characteristic frequency of the system itself (coupling at the characteristic frequency). Up to now, three possible mathematical formalisms have been discussed related to the theory of electroviscoelasticity. The first is the tension tensor model, where the normal and tangential forces are considered, only in mathematical formalism, regardless of their origin (mechanical and/or electrical). The second is the Van der Pol derivative model, presented by linear and nonlinear differential equations. Finally, the third model presents an effort to generalize the previous Van der Pol equation: the ordinary time derivative and integral are now replaced with the corresponding fractional-order time derivative and integral of order p<1.
A Segmented Signal Progression Model for the Modern Streetcar System
Directory of Open Access Journals (Sweden)
Baojie Wang
2015-01-01
Full Text Available This paper is on the purpose of developing a segmented signal progression model for modern streetcar system. The new method is presented with the following features: (1 the control concept is based on the assumption of only one streetcar line operating along an arterial under a constant headway and no bandwidth demand for streetcar system signal progression; (2 the control unit is defined as a coordinated intersection group associated with several streetcar stations, and the control joints must be streetcar stations; (3 the objective function is built to ensure the two-way streetcar arrival times distributing within the available time of streetcar phase; (4 the available time of streetcar phase is determined by timing schemes, intersection structures, track locations, streetcar speeds, and vehicular accelerations; (5 the streetcar running speed is constant separately whether it is in upstream or downstream route; (6 the streetcar dwell time is preset according to historical data distribution or charging demand. The proposed method is experimentally examined in Hexi New City Streetcar Project in Nanjing, China. In the experimental results, the streetcar system operation and the progression impacts are shown to affect transit and vehicular traffic. The proposed model presents promising outcomes through the design of streetcar system segmented signal progression, in terms of ensuring high streetcar system efficiency and minimizing negative impacts on transit and vehicular traffic.
Low-order models of biogenic ocean mixing
Dabiri, J. O.; Rosinelli, D.; Koumoutsakos, P.
2009-12-01
Biogenic ocean mixing, the process whereby swimming animals may affect ocean circulation, has primarily been studied using order-of-magnitude theoretical estimates and a small number of field observations. We describe numerical simulations of arrays of simplified animal shapes migrating in inviscid fluid and at finite Reynolds numbers. The effect of density stratification is modeled in the fluid dynamic equations of motion by a buoyancy acceleration term, which arises due to perturbations to the density field by the migrating bodies. The effects of fluid viscosity, body spacing, and array configuration are investigated to identify scenarios in which a meaningful contribution to ocean mixing by swimming animals is plausible.
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...
Second order kinetic Kohn-Sham lattice model
Solorzano, Sergio; Herrmann, Hans
2016-01-01
In this work we introduce a new semi-implicit second order correction scheme to the kinetic Kohn-Sham lattice model. The new approach is validated by performing realistic exchange-correlation energy calculations of atoms and dimers of the first two rows of the periodic table finding good agreement with the expected values. Additionally we simulate the ethane molecule where we recover the bond lengths and compare the results with standard methods. Finally, we discuss the current applicability of pseudopotentials within the lattice kinetic Kohn-Sham approach.
High-order Boussinesq-type modelling of nonlinear wave phenomena in deep and shallow water
DEFF Research Database (Denmark)
Madsen, Per A.; Fuhrman, David R.
2010-01-01
In this work, we start with a review of the development of Boussinesq theory for water waves covering the period from 1872 to date. Previous reviews have been given by Dingemans,1 Kirby,2,3 and Madsen & Schäffer.4 Next, we present our most recent high-order Boussinesq-type formulation valid...... for fully nonlinear and highly dispersive waves traveling over a rapidly varying bathymetry. Finally, we cover applications of this Boussinesq model, and we study a number of nonlinear wave phenomena in deep and shallow water. These include (1) Kinematics in highly nonlinear progressive deep-water waves; (2......) Kinematics in progressive solitary waves; (3) Reflection of solitary waves from a vertical wall; (4) Reflection and diffraction around a vertical plate; (5) Quartet and quintet interactions and class I and II instabilities; (6) Extreme events from focused directionally spread waveelds; (7) Bragg scattering...
High-order Boussinesq-type modelling of nonlinear wave phenomena in deep and shallow water
DEFF Research Database (Denmark)
Madsen, Per A.; Fuhrman, David R.
2010-01-01
In this work, we start with a review of the development of Boussinesq theory for water waves covering the period from 1872 to date. Previous reviews have been given by Dingemans,1 Kirby,2,3 and Madsen & Schäffer.4 Next, we present our most recent high-order Boussinesq-type formulation valid...... for fully nonlinear and highly dispersive waves traveling over a rapidly varying bathymetry. Finally, we cover applications of this Boussinesq model, and we study a number of nonlinear wave phenomena in deep and shallow water. These include (1) Kinematics in highly nonlinear progressive deep-water waves; (2......) Kinematics in progressive solitary waves; (3) Reflection of solitary waves from a vertical wall; (4) Reflection and diffraction around a vertical plate; (5) Quartet and quintet interactions and class I and II instabilities; (6) Extreme events from focused directionally spread waveelds; (7) Bragg scattering...
Jiang, Chen; Liu, Xiaozhou; Liu, Jiehui; Mao, Yiwei; Marston, Philip L
2017-04-01
By means of series expansion theory, the incident quasi-Bessel-Gauss beam is expanded using spherical harmonic functions, and the beam coefficients of the quasi-Bessel-Gauss beam are calculated. According to the theory, the acoustic radiation force function, which is the radiation force per unit energy on a unit cross-sectional surface on a sphere made of diverse materials and immersed in an ideal fluid along the propagation axis of zero-order quasi-Bessel-Gauss progressive and standing beams, is investigated. The acoustic radiation force function is calculated as a function of the spherical radius parameter ka and the half-cone angle β with different beam widths in a progressive and standing zero-order Bessel-Gauss beam. Simulation results indicate that the acoustic radiation forces with different waist radii demonstrate remarkably different features from those found in previous studies. The results are expected to be useful in potential applications such as acoustic tweezers. Copyright Â© 2016 Elsevier B.V. All rights reserved.
A simple model of scientific progress - with examples
Scorzato, Luigi
2016-01-01
One of the main goals of scientific research is to provide a description of the empirical data which is as accurate and comprehensive as possible, while relying on as few and simple assumptions as possible. In this paper, I propose a definition of the notion of "few and simple assumptions" that is not affected by known problems. This leads to the introduction of a simple model of scientific progress that is based only on empirical accuracy and conciseness. An essential point in this task is the understanding of the role played by "measurability" in the formulation of a scientific theory. This is the key to prevent artificially concise formulations. The model is confronted here with many possible objections and with challenging cases of real progress. Although I cannot exclude that the model might have some limitations, it includes all the cases of genuine progress examined here, and no spurious one. In this model, I stress the role of the "state of the art", which is the collection of all the theories that ar...
Phase-field-crystal model for fcc ordering.
Wu, Kuo-An; Adland, Ari; Karma, Alain
2010-06-01
We develop and analyze a two-mode phase-field-crystal model to describe fcc ordering. The model is formulated by coupling two different sets of crystal density waves corresponding to and reciprocal lattice vectors, which are chosen to form triads so as to produce a simple free-energy landscape with coexistence of crystal and liquid phases. The feasibility of the approach is demonstrated with numerical examples of polycrystalline and (111) twin growth. We use a two-mode amplitude expansion to characterize analytically the free-energy landscape of the model, identifying parameter ranges where fcc is stable or metastable with respect to bcc. In addition, we derive analytical expressions for the elastic constants for both fcc and bcc. Those expressions show that a nonvanishing amplitude of [200] density waves is essential to obtain mechanically stable fcc crystals with a nonvanishing tetragonal shear modulus (C11-C12)/2. We determine the model parameters for specific materials by fitting the peak liquid structure factor properties and solid-density wave amplitudes following the approach developed for bcc [K.-A. Wu and A. Karma, Phys. Rev. B 76, 184107 (2007)]. This procedure yields reasonable predictions of elastic constants for both bcc Fe and fcc Ni using input parameters from molecular dynamics simulations. The application of the model to two-dimensional square lattices is also briefly examined.
Model Order Selection Rules for Covariance Structure Classification in Radar
Carotenuto, Vincenzo; De Maio, Antonio; Orlando, Danilo; Stoica, Petre
2017-10-01
The adaptive classification of the interference covariance matrix structure for radar signal processing applications is addressed in this paper. This represents a key issue because many detection architectures are synthesized assuming a specific covariance structure which may not necessarily coincide with the actual one due to the joint action of the system and environment uncertainties. The considered classification problem is cast in terms of a multiple hypotheses test with some nested alternatives and the theory of Model Order Selection (MOS) is exploited to devise suitable decision rules. Several MOS techniques, such as the Akaike, Takeuchi, and Bayesian information criteria are adopted and the corresponding merits and drawbacks are discussed. At the analysis stage, illustrating examples for the probability of correct model selection are presented showing the effectiveness of the proposed rules.
Ordered LOGIT Model approach for the determination of financial distress.
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.
Low-order modelling of droplets on hydrophobic surfaces
Matar, Omar; Wray, Alex; Kahouadji, Lyes; Davis, Stephen
2015-11-01
We consider the behaviour of a droplet deposited onto a hydrophobic substrate. This and associated problems have garnered a wide degree of attention due to their significance in industrial and experimental settings, such as the post-rupture dewetting problem. These problems have generally defied low-order analysis due to the multi-valued nature of the interface, but we show here how to overcome this in this instance. We first discuss the static problem: when the droplet is stationary, its shape is prescribed by an ordinary differential equation (ODE) given by balancing gravitational and capillary stresses at the interface. This is dependent on the contact angle, the Bond number and the volume of the drop. In the high Bond number limit, we derive several low-order models of varying complexity to predict the shape of such drops. These are compared against numerical calculations of the ODE. We then approach the dynamic problem: in this case, the full Stokes equations throughout the drop must be considered. A low-order approach is used by solving the biharmonic equation in a coordinate system naturally mapping to the droplet shape. The results are compared against direct numerical simulations. EPSRC Programme Grant, MEMPHIS, EP/K0039761/1, EPSRC Doctoral Prize Fellowship (AWW).
Computing supersonic non-premixed turbulent combustion by an SMLD flamelet progress variable model
Coclite, A; Gurtner, M; De Palma, P; Haidnd, O J; Pascazio, G
2015-01-01
This paper describes the numerical simulation of the NASA Langley Research Center supersonic H2 -Air combustion chamber performed using two approaches to model the presumed probability density function (PDF) in the flamelet progress variable (FPV) framework. The first one is a standard FPV model, built presuming the functional shape of the PDFs of the mixture fraction, Z, and of the progress parameter, {\\Lambda}. In order to enhance the prediction capabilities of such a model in high-speed reacting flows, a second approach is proposed employing the statistically most likely distribution (SMLD) techcnique to presume the joint PDF of Z and {\\Lambda}, without any assumption about their behaviour. The standard and FPV-SMLD models have been developed using the low Mach number assumption. In both cases, the temperature is evaluated by solving the total-energy conservation equation, providing a more suitable approach for the simulation of supersonic combustion. By comparison with experimental data, the proposed SMLD...
Policy Decisions for a Price Dependent Demand Rate Inventory Model with Progressive Payments Scheme
Rajat Kumar; Mukesh Kumar
2012-01-01
Problem statement: In this proposed research, we developed an inventory model to formulate an optimal ordering policies for supplier who offers progressive permissible delay periods to the retailer to settle his/her account. We assumed that the annual demand rate as a decreasing function of price with constant rate of deterioration and time-varying holding cost. Shortages in inventory are allowed which is completely backlogged. Approach: The main objective of this study to frame an inventory ...
Progress on Analytical Modeling of Coherent Electron Cooling
Energy Technology Data Exchange (ETDEWEB)
Wang, G.; Blaskiewicz, M.; Litvinenko, V.; Webb, S.
2010-05-23
We report recent progresses on analytical studies of Coherent Electron Cooling. The phase space electron beam distribution obtained from the 1D FEL amplifier is applied to an infinite electron plasma model and the electron density evolution inside the kicker is derived. We also investigate the velocity modulation in the modulator and obtain a closed form solution for the current density evolution for infinite homogeneous electron plasma.
Model-theoretical foundation of action and progression
Institute of Scientific and Technical Information of China (English)
田启家; 史忠植
1997-01-01
Action is one of the most important concepts in computer science, and situation calculus is the standard formalism for representing and reasoning about actions and their effects. Situation calculus essentially could be presented in a logic framework. Based on the framework LR, such a logic framework is given. Minimal action theory is proposed and studied from the point of view of model theory. By theorems of mathematical logic, some results about the definability about the progression in minimal action theory are obtained.
Falk, Richard A.
The monograph examines the relationship of nuclear power to world order. The major purpose of the document is to stimulate research, education, dialogue, and political action for a just and peaceful world order. The document is presented in five chapters. Chapter I stresses the need for a system of global security to counteract dangers brought…
Reduced order modeling in iTOUGH2
Pau, George Shu Heng; Zhang, Yingqi; Finsterle, Stefan; Wainwright, Haruko; Birkholzer, Jens
2014-04-01
The inverse modeling and uncertainty quantification capabilities of iTOUGH2 are augmented with reduced order models (ROMs) that act as efficient surrogates for computationally expensive high fidelity models (HFMs). The implementation of the ROM capabilities involves integration of three main computational components. The first component is the ROM itself. Two response surface approximations are currently implemented: Gaussian process regression (GPR) and radial basis function (RBF) interpolation. The second component is a multi-output adaptive sampling procedure that determines the sample points used to construct the ROMs. The third component involves defining appropriate error measures for the adaptive sampling procedure, allowing ROMs to be constructed efficiently with limited user intervention. Details in all three components must complement one another to obtain an accurate approximation. The new capability and its integration with other analysis tools within iTOUGH2 are demonstrated in two examples. The results from using the ROMs in an uncertainty quantification analysis and a global sensitivity analysis compare favorably with the results obtained using the HFMs. GPR is more accurate than RBF, but the difference can be small and similar conclusion can be deduced from the analyses. In the second example involving a realistic numerical model for a hypothetical industrial-scale carbon storage project in the Southern San Joaquin Basin, California, USA, significant reduction in computational effort can be achieved when ROMs are used to perform a rigorous global sensitivity analysis.
Using the Neumann series expansion for assembling Reduced Order Models
Directory of Open Access Journals (Sweden)
Nasisi S.
2014-06-01
Full Text Available An efficient method to remove the limitation in selecting the master degrees of freedom in a finite element model by means of a model order reduction is presented. A major difficulty of the Guyan reduction and IRS method (Improved Reduced System is represented by the need of appropriately select the master and slave degrees of freedom for the rate of convergence to be high. This study approaches the above limitation by using a particular arrangement of the rows and columns of the assembled matrices K and M and employing a combination between the IRS method and a variant of the analytical selection of masters presented in (Shah, V. N., Raymund, M., Analytical selection of masters for the reduced eigenvalue problem, International Journal for Numerical Methods in Engineering 18 (1 1982 in case first lowest frequencies had to be sought. One of the most significant characteristics of the approach is the use of the Neumann series expansion that motivates this particular arrangement of the matrices’ entries. The method shows a higher rate of convergence when compared to the standard IRS and very accurate results for the lowest reduced frequencies. To show the effectiveness of the proposed method two testing structures and the human vocal tract model employed in (Vampola, T., Horacek, J., Svec, J. G., FE modeling of human vocal tract acoustics. Part I: Prodution of Czech vowels, Acta Acustica United with Acustica 94 (3 2008 are presented.
Reliability-based design optimization with progressive surrogate models
Kanakasabai, Pugazhendhi; Dhingra, Anoop K.
2014-12-01
Reliability-based design optimization (RBDO) has traditionally been solved as a nested (bilevel) optimization problem, which is a computationally expensive approach. Unilevel and decoupled approaches for solving the RBDO problem have also been suggested in the past to improve the computational efficiency. However, these approaches also require a large number of response evaluations during optimization. To alleviate the computational burden, surrogate models have been used for reliability evaluation. These approaches involve construction of surrogate models for the reliability computation at each point visited by the optimizer in the design variable space. In this article, a novel approach to solving the RBDO problem is proposed based on a progressive sensitivity surrogate model. The sensitivity surrogate models are built in the design variable space outside the optimization loop using the kriging method or the moving least squares (MLS) method based on sample points generated from low-discrepancy sampling (LDS) to estimate the most probable point of failure (MPP). During the iterative deterministic optimization, the MPP is estimated from the surrogate model for each design point visited by the optimizer. The surrogate sensitivity model is also progressively updated for each new iteration of deterministic optimization by adding new points and their responses. Four example problems are presented showing the relative merits of the kriging and MLS approaches and the overall accuracy and improved efficiency of the proposed approach.
Modelling Hydrological Consequences of Climate Change-Progress and Challenges
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps: (1) use of general circulation models (GCMs) to provide future global climate scenarios under the effect of increasing greenhouse gases,(2) use of downscaling techniques (both nested regional climate models, RCMs, and statistical methods)for "downscaling" the GCM output to the scales compatible with hydrological models, and (3) use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales.Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.
Animal Models of Diabetic Neuropathy: Progress Since 1960s
Directory of Open Access Journals (Sweden)
Md. Shahidul Islam
2013-01-01
Full Text Available Diabetic or peripheral diabetic neuropathy (PDN is one of the major complications among some other diabetic complications such as diabetic nephropathy, diabetic retinopathy, and diabetic cardiomyopathy. The use of animal models in the research of diabetes and diabetic complications is very common when rats and mice are most commonly used for many reasons. A numbers of animal models of diabetic and PDN have been developed in the last several decades such as streptozotocin-induced diabetic rat models, conventional or genetically modified or high-fat diet-fed C57BL/Ks (db/db mice models, streptozotocin-induced C57BL6/J and ddY mice models, Chinese hamster neuropathic model, rhesus monkey PDN model, spontaneously diabetic WBN/Kob rat model, L-fucose-induced neropathic rat model, partial sciatic nerve ligated rat model, nonobese diabetic (NOD mice model, spontaneously induced Ins2 Akita mice model, leptin-deficient (ob/ob mice model, Otsuka Long-Evans Tokushima Fatty (OLETF rat model, surgically-induced neuropathic model, and genetically modified Spontaneously Diabetic Torii (SDT rat model, none of which are without limitations. An animal model of diabetic or PDN should mimic the all major pathogeneses of human diabetic neuropathy. Hence, this review comparatively evaluates the animal models of diabetic and PDN which are developed since 1960s with their advantages and disadvantages to help diabetic research groups in order to more accurately choose an appropriate model to meet their specific research objectives.
Capillary wave approach to order-order fluid interfaces in the 3D three-state Potts model
Provero, P
1994-01-01
The physics of fluid interfaces between domains of different magnetization in the ordered phase of the 3D three-state Potts model is studied by means of a Monte Carlo simulation. It is shown that finite--size effects in the interface free energy are well described by the capillary wave model at two loop order, supporting the idea of the universality of this description of fluid interfaces in 3D statistical models.
Stochastic reduced order models for inverse problems under uncertainty.
Warner, James E; Aquino, Wilkins; Grigoriu, Mircea D
2015-03-01
This work presents a novel methodology for solving inverse problems under uncertainty using stochastic reduced order models (SROMs). Given statistical information about an observed state variable in a system, unknown parameters are estimated probabilistically through the solution of a model-constrained, stochastic optimization problem. The point of departure and crux of the proposed framework is the representation of a random quantity using a SROM - a low dimensional, discrete approximation to a continuous random element that permits e cient and non-intrusive stochastic computations. Characterizing the uncertainties with SROMs transforms the stochastic optimization problem into a deterministic one. The non-intrusive nature of SROMs facilitates e cient gradient computations for random vector unknowns and relies entirely on calls to existing deterministic solvers. Furthermore, the method is naturally extended to handle multiple sources of uncertainty in cases where state variable data, system parameters, and boundary conditions are all considered random. The new and widely-applicable SROM framework is formulated for a general stochastic optimization problem in terms of an abstract objective function and constraining model. For demonstration purposes, however, we study its performance in the specific case of inverse identification of random material parameters in elastodynamics. We demonstrate the ability to efficiently recover random shear moduli given material displacement statistics as input data. We also show that the approach remains effective for the case where the loading in the problem is random as well.
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.
Accelerated gravitational wave parameter estimation with reduced order modeling.
Canizares, Priscilla; Field, Scott E; Gair, Jonathan; Raymond, Vivien; Smith, Rory; Tiglio, Manuel
2015-02-20
Inferring the astrophysical parameters of coalescing compact binaries is a key science goal of the upcoming advanced LIGO-Virgo gravitational-wave detector network and, more generally, gravitational-wave astronomy. However, current approaches to parameter estimation for these detectors require computationally expensive algorithms. Therefore, there is a pressing need for new, fast, and accurate Bayesian inference techniques. In this Letter, we demonstrate that a reduced order modeling approach enables rapid parameter estimation to be performed. By implementing a reduced order quadrature scheme within the LIGO Algorithm Library, we show that Bayesian inference on the 9-dimensional parameter space of nonspinning binary neutron star inspirals can be sped up by a factor of ∼30 for the early advanced detectors' configurations (with sensitivities down to around 40 Hz) and ∼70 for sensitivities down to around 20 Hz. This speedup will increase to about 150 as the detectors improve their low-frequency limit to 10 Hz, reducing to hours analyses which could otherwise take months to complete. Although these results focus on interferometric gravitational wave detectors, the techniques are broadly applicable to any experiment where fast Bayesian analysis is desirable.
High order discretization schemes for stochastic volatility models
Jourdain, Benjamin
2009-01-01
In usual stochastic volatility models, the process driving the volatility of the asset price evolves according to an autonomous one-dimensional stochastic differential equation. We assume that the coefficients of this equation are smooth. Using It\\^o's formula, we get rid, in the asset price dynamics, of the stochastic integral with respect to the Brownian motion driving this SDE. Taking advantage of this structure, we propose - a scheme, based on the Milstein discretization of this SDE, with order one of weak trajectorial convergence for the asset price, - a scheme, based on the Ninomiya-Victoir discretization of this SDE, with order two of weak convergence for the asset price. We also propose a specific scheme with improved convergence properties when the volatility of the asset price is driven by an Orstein-Uhlenbeck process. We confirm the theoretical rates of convergence by numerical experiments and show that our schemes are well adapted to the multilevel Monte Carlo method introduced by Giles [2008a,b].
Computational design of patterned interfaces using reduced order models
Vattré, A. J.; Abdolrahim, N.; Kolluri, K.; Demkowicz, M. J.
2014-01-01
Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids. Many interfaces have non-uniform internal structures comprised of misfit dislocations, which in turn govern interface properties. We develop and validate a computational strategy for designing interfaces with controlled misfit dislocation patterns by tailoring interface crystallography and composition. Our approach relies on a novel method for predicting the internal structure of interfaces: rather than obtaining it from resource-intensive atomistic simulations, we compute it using an efficient reduced order model based on anisotropic elasticity theory. Moreover, our strategy incorporates interface synthesis as a constraint on the design process. As an illustration, we apply our approach to the design of interfaces with rapid, 1-D point defect diffusion. Patterned interfaces may be integrated into the microstructure of composite materials, markedly improving performance. PMID:25169868
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.
Inflationary scenarios in Starobinsky model with higher order corrections
Energy Technology Data Exchange (ETDEWEB)
Artymowski, Michał [Institute of Physics, Jagiellonian University,Łojasiewicza 11, 30-348 Kraków (Poland); Lalak, Zygmunt [Institute of Theoretical Physics, Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Lewicki, Marek [Institute of Theoretical Physics, Faculty of Physics, University of Warsaw,ul. Pasteura 5, 02-093 Warsaw (Poland); Michigan Center for Theoretical Physics, University of Michigan,450 Church Street, Ann Arbor MI 48109 (United States)
2015-06-17
We consider the Starobinsky inflation with a set of higher order corrections parametrised by two real coefficients λ{sub 1} ,λ{sub 2}. In the Einstein frame we have found a potential with the Starobinsky plateau, steep slope and possibly with an additional minimum, local maximum or a saddle point. We have identified three types of inflationary behaviour that may be generated in this model: i) inflation on the plateau, ii) at the local maximum (topological inflation), iii) at the saddle point. We have found limits on parameters λ{sub i} and initial conditions at the Planck scale which enable successful inflation and disable eternal inflation at the plateau. We have checked that the local minimum away from the GR vacuum is stable and that the field cannot leave it neither via quantum tunnelling nor via thermal corrections.
Progress in Inertial Fusion Energy Modelling at DENIM
Energy Technology Data Exchange (ETDEWEB)
Velarde, G; Cabellos, O; Caturla, M J; Florido, R; Gil, J M; Leon, P T; Mancini, R; Marian, J; Martel, P; Martinez-Val, J M; Minguez, E; Mota, F; Ogando, F; Perlado, J M; Piera, M; Reyes, S; Rodriguez, R; Rubiano, J G; Salvador, M; Sanz, J; Sauvan, P; Velarde, M; Velarde, P
2004-11-17
New results of the jet driven ignition target are presented, both with direct and indirect drive. This target is based on the conical guided target used in fast ignition, but use only one laser pulse. The ignition of the target is started by the impact of a jet produced in the guiding cone, instead of using charged particles generated by a other high power laser. We have shown that a laser or X-ray pulse could be used to produce a high velocity jet of several hundred of km/s by an accumulative effect, and we use these ideas to design this new kind of targets. In order to increase the efficiency of the process, we scan in the simulations different materials, cone profiles and laser intensities. ANALOP is a code developed to calculate opacities for hot plasmas, using analytical potentials including density and temperature effects. It has been recently updated to include the radiative transport into the rate equations by mean of the escape factors, and in parallel a line transport code which solve self-consistently the rate equation and radiative transfer equation in 1D planar geometry has been also developed. We have developed a comprehensive methodology to compute uncertainties on activation calculations. First we developed a sensitivity-uncertainty analysis method, providing the uncertainties of the different inventory responses functions due to the uncertainty of each of the reaction cross sections separately. Lately, we have developed and proved the excellent behaviour of a Monte Carlo-based methodology in assessing the synergetic/global effect of the complete set of cross-sections uncertainties on calculated radiological quantities. The methods have been applied to the activation analysis of the National Ignition Facility (NIF) and different IFE concepts (HYLIFE and Sombrero). Research on multiscale modeling of radiation damage in metals will be presented in comparison with ''ad hoc'' experiments. Research on SiC composite is being pursued at
DEFF Research Database (Denmark)
De Vos, Cees B; Breithardt, Günter; Camm, A John;
2012-01-01
Paroxysmal atrial fibrillation (AF) may progress to persistent AF. We studied the clinical correlates and the effect of rhythm-control strategy on AF progression.......Paroxysmal atrial fibrillation (AF) may progress to persistent AF. We studied the clinical correlates and the effect of rhythm-control strategy on AF progression....
Establishing the colitis-associated cancer progression mouse models.
Zheng, Haiming; Lu, Zhanjun; Wang, Ruhua; Chen, Niwei; Zheng, Ping
2016-12-01
Inflammatory bowel disease (IBD) has been reported as an important inducer of colorectal cancer (CRC). The most malignant IBD-associated CRC type has been highlighted as colitis-associated cancer (CAC). However, lack of CAC cases and difficulties of the long follow-up research have challenged researchers in molecular mechanism probing. Here, we established pre-CAC mouse models (dextran sulfate sodium [DSS] group and azoxymethane [AOM] group) and CAC mouse model (DSS/AOM group) to mimic human CAC development through singly or combinational treatment with DSS and AOM followed by disease activity index analysis. We found that these CAC mice showed much more severe disease phenotype, including serious diarrhea, body weight loss, rectal prolapse and bleeding, bloody stool, tumor burden, and bad survival. By detecting expression patterns of several therapeutic targets-Apc, p53, Kras, and TNF-α-in these mouse models through western blot, histology analysis, qRT-PCR, and ELISA methods, we found that the oncogene Kras expression remained unchanged, while the tumor suppressors-Apc and p53 expression were both significantly downregulated with malignancy progression from pre-CAC to CAC, and TNF-α level was elevated the most in CAC mice blood which is of potential clinical use. These data indicated the successful establishment of CAC development mouse models, which mimics human CAC well both in disease phenotype and molecular level, and highlighted the promoting role of inflammation in CAC progression. This useful tool will facilitate the further study in CAC molecular mechanism.
Second-order closure PBL model with new third-order moments: Comparison with LES data
Canuto, V. M.; Minotti, F.; Ronchi, C.; Ypma, R. M.; Zeman, O.
1994-01-01
This paper contains two parts. In the first part, a new set of diagnostic equations is derived for the third-order moments for a buoyancy-driven flow, by exact inversion of the prognostic equations for the third-order moment equations in the stationary case. The third-order moments exhibit a universal structure: they all are a linear combination of the derivatives of all the second-order moments, bar-w(exp 2), bar-w theta, bar-theta(exp 2), and bar-q(exp 2). Each term of the sum contains a turbulent diffusivity D(sub t), which also exhibits a universal structure of the form D(sub t) = a nu(sub t) + b bar-w theta. Since the sign of the convective flux changes depending on stable or unstable stratification, D(sub t) varies according to the type of stratification. Here nu(sub t) approximately equal to wl (l is a mixing length and w is an rms velocity) represents the 'mechanical' part, while the 'buoyancy' part is represented by the convective flux bar-w theta. The quantities a and b are functions of the variable N(sub tau)(exp 2), where N(exp 2) = g alpha derivative of Theta with respect to z and tau is the turbulence time scale. The new expressions for the third-order moments generalize those of Zeman and Lumley, which were subsequently adopted by Sun and Ogura, Chen and Cotton, and Finger and Schmidt in their treatments of the convective boundary layer. In the second part, the new expressions for the third-order moments are used to solve the ensemble average equations describing a purely convective boundary laye r heated from below at a constant rate. The computed second- and third-order moments are then compared with the corresponding Large Eddy Simulation (LES) results, most of which are obtained by running a new LES code, and part of which are taken from published results. The ensemble average results compare favorably with the LES data.
Higher-order models versus direct hierarchical models: g as superordinate or breadth factor?
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GILLES E. GIGNAC
2008-03-01
Full Text Available Intelligence research appears to have overwhelmingly endorsed a superordinate (higher-order model conceptualization of g, in comparison to the relatively less well-known breadth conceptualization of g, as represented by the direct hierarchical model. In this paper, several similarities and distinctions between the indirect and direct hierarchical models are delineated. Based on the re-analysis of five correlation matrices, it was demonstrated via CFA that the conventional conception of g as a higher-order superordinate factor was likely not as plausible as a first-order breadth factor. The results are discussed in light of theoretical advantages of conceptualizing g as a first-order factor. Further, because the associations between group-factors and g are constrained to zero within a direct hierarchical model, previous observations of isomorphic associations between a lower-order group factor and g are questioned.
The complex model of risk and progression of AMD estimation
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V. S. Akopyan
2012-01-01
Full Text Available Purpose: to develop a method and a statistical model to estimate individual risk of AMD and the risk for progression to advanced AMD using clinical and genetic risk factors.Methods: A statistical risk assessment model was developed using stepwise binary logistic regression analysis. to estimate the population differences in the prevalence of allelic variants of genes and for the development of models adapted to the population of Moscow region genotyping and assessment of the influence of other risk factors was performed in two groups: patients with differ- ent stages of AMD (n = 74, and control group (n = 116. Genetic risk factors included in the study: polymorphisms in the complement system genes (C3 and CFH, genes at 10q26 locus (ARMS2 and HtRA1, polymorphism in the mitochondrial gene Mt-ND2. Clinical risk factors included in the study: age, gender, high body mass index, smoking history.Results: A comprehensive analysis of genetic and clinical risk factors for AMD in the study group was performed. Compiled statis- tical model assessment of individual risk of AMD, the sensitivity of the model — 66.7%, specificity — 78.5%, AUC = 0.76. Risk factors of late AMD, compiled a statistical model describing the probability of late AMD, the sensitivity of the model — 66.7%, specificity — 78.3%, AUC = 0.73. the developed system allows determining the most likely version of the current late AMD: dry or wet.Conclusion: the developed test system and the mathematical algorhythm for determining the risk of AMD, risk of progression to advanced AMD have fair diagnostic informative and promising for use in clinical practice.
The complex model of risk and progression of AMD estimation
Directory of Open Access Journals (Sweden)
V. S. Akopyan
2014-07-01
Full Text Available Purpose: to develop a method and a statistical model to estimate individual risk of AMD and the risk for progression to advanced AMD using clinical and genetic risk factors.Methods: A statistical risk assessment model was developed using stepwise binary logistic regression analysis. to estimate the population differences in the prevalence of allelic variants of genes and for the development of models adapted to the population of Moscow region genotyping and assessment of the influence of other risk factors was performed in two groups: patients with differ- ent stages of AMD (n = 74, and control group (n = 116. Genetic risk factors included in the study: polymorphisms in the complement system genes (C3 and CFH, genes at 10q26 locus (ARMS2 and HtRA1, polymorphism in the mitochondrial gene Mt-ND2. Clinical risk factors included in the study: age, gender, high body mass index, smoking history.Results: A comprehensive analysis of genetic and clinical risk factors for AMD in the study group was performed. Compiled statis- tical model assessment of individual risk of AMD, the sensitivity of the model — 66.7%, specificity — 78.5%, AUC = 0.76. Risk factors of late AMD, compiled a statistical model describing the probability of late AMD, the sensitivity of the model — 66.7%, specificity — 78.3%, AUC = 0.73. the developed system allows determining the most likely version of the current late AMD: dry or wet.Conclusion: the developed test system and the mathematical algorhythm for determining the risk of AMD, risk of progression to advanced AMD have fair diagnostic informative and promising for use in clinical practice.
A novel homologous model for noninvasive monitoring of endometriosis progression.
Ferrero, Hortensia; Buigues, Anna; Martínez, Jessica; Simón, Carlos; Pellicer, Antonio; Gómez, Raúl
2017-02-01
To date, several groups have generated homologous models of endometriosis through the implantation of endometrial tissue fluorescently labeled by green fluorescent protein (GFP) or tissue from luciferase-expressing transgenic mice into recipient animals, enabling noninvasive monitoring of lesion signal. These models present an advantage over endpoint models, but some limitations persist; use of transgenic mice is laborious and expensive, and GFP presents poor tissue penetration due to the relatively short emission wavelength. For this reason, a homologous mouse model of endometriosis that allows in vivo monitoring of generated lesions over time and mimics human lesions in recipient mice would be most desirable. In this regard, using C57BL/6 and B6N-Tyrc-Brd/BrdCrCrl mice, we optimized a decidualization protocol to obtain large volumes of decidual endometrium and mimic human lesions. Subsequently, to obtain a more robust and reliable noninvasive monitoring of lesions, we used the fluorescent reporter mCherry, which presents deeper tissue penetration and higher photostability, showing that endometrial tissue was properly labeled with 1 × 108 PFU/mL mCherry adenoviral vectors. mCherry-labeled endometriotic tissue was implanted in recipient mice, generating lesions that displayed characteristics typical of human endometriotic lesions, such as epithelial cells forming glands, local inflammation, collagen deposits, and new vessel formation. In vivo monitoring demonstrated that subcutaneous implantation on ventral abdomen of recipient mice provided the most intense and reliable signal for noninvasive lesion monitoring over a period of at least 20 days. This homologous model improves upon previously reported models of endometriosis and provides opportunities to study mechanism underlying endometriotic lesion growth and progression. We created a cost-effective but accurate homologous mouse model of endometriosis that allows the study of growth and progression of
Monte Carlo autofluorescence modeling of cervical intraepithelial neoplasm progression
Chu, S. C.; Chiang, H. K.; Wu, C. E.; He, S. Y.; Wang, D. Y.
2006-02-01
Monte Carlo fluorescence model has been developed to estimate the autofluorescent spectra associated with the progression of the Exo-Cervical Intraepithelial Neoplasm (CIN). We used double integrating spheres system and a tunable light source system, 380 to 600 nm, to measure the reflection and transmission spectra of a 50 μm thick tissue, and used Inverse Adding-Doubling (IAD) method to estimate the absorption (μa) and scattering (μs) coefficients. Human cervical tissue samples were sliced vertically (longitudinal) by the frozen section method. The results show that the absorption and scattering coefficients of cervical neoplasia are 2~3 times higher than normal tissues. We applied Monte Carlo method to estimate photon distribution and fluorescence emission in the tissue. By combining the intrinsic fluorescence information (collagen, NADH, and FAD), the anatomical information of the epithelium, CIN, stroma layers, and the fluorescence escape function, the autofluorescence spectra of CIN at different development stages were obtained.We have observed that the progression of the CIN results in gradually decreasing of the autofluorescence intensity of collagen peak intensity. In addition, the existence of the CIN layer formeda barrier that blocks the autofluorescence escaping from the stroma layer due to the strong extinction(scattering and absorption) of the CIN layer. To our knowledge, this is the first study measuring the CIN optical properties in the visible range; it also successfully demonstrates the fluorescence model forestimating autofluorescence spectra of cervical tissue associated with the progression of the CIN tissue;this model is very important in assisting the CIN diagnosis and treatment in clinical medicine.
Modelling progressive autonomic failure in MSA: where are we now?
Stemberger, Sylvia; Wenning, Gregor K
2011-05-01
Multiple system atrophy (MSA) is a fatal late-onset α-synucleinopathy that presents with features of ataxia, Parkinsonism, and pyramidal dysfunction in any combination. Over the last decade, efforts have been made to develop preclinical MSA testbeds for novel interventional strategies. The main focus has been on murine analogues of MSA-linked motor features and their underlying brainstem, cerebellar and basal ganglia pathology. Although progressive autonomic failure (AF) is a prominent clinical feature of patients with MSA, reflecting a disruption of both central and peripheral autonomic networks controlling cardiovascular, respiratory, urogenital, gastrointestinal and sudomotor functions, attempts of modelling this aspect of the human disease have been limited. However, emerging evidence suggests that AF-like features may occur in transgenic MSA models reflecting α-synucleinopathy lesions in distributed autonomic networks. Further research is needed to fully characterize both autonomic and motor features in optimized preclinical MSA models.
Formal modeling and verification of fractional order linear systems.
Zhao, Chunna; Shi, Likun; Guan, Yong; Li, Xiaojuan; Shi, Zhiping
2016-05-01
This paper presents a formalization of a fractional order linear system in a higher-order logic (HOL) theorem proving system. Based on the formalization of the Grünwald-Letnikov (GL) definition, we formally specify and verify the linear and superposition properties of fractional order systems. The proof provides a rigor and solid underpinnings for verifying concrete fractional order linear control systems. Our implementation in HOL demonstrates the effectiveness of our approach in practical applications.
A MATHEMATICAL MODEL OF CHP 2000 TYPE PROGRESSIVE GEAR
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Paweł Lonkwic
2016-12-01
Full Text Available The project of CHP2000 type progressive gear has been presented in the article. The offered solution from its construction point of view differs from the existing solutions due to the application of Belleville springs packets supporting the braking roller cam and achieving a flexible range of the gear loading. The standard concept of the gear loading within a mathematical and a geometrical model has been presented in the article. The proposed solution can be used in the friction lifts with the loading capacity from 8500 up to 20000 N.
Progress toward the Determination of Complete Vertex Operators for The IIB Matrix Model
Kitazawa, Y; Saito, O; Kitazawa, Yoshihisa; Mizoguchi, Shun'ya; Saito, Osamu
2006-01-01
We report on progress in determining the complete form of vertex operators for the IIB matrix model. The exact expressions are obtained for those emitting massless IIB supergravity fields up to sixth order in the light-cone superfield, in which the conjugate gravitino and conjugate two-form vertex operators are newly determined. We also provide a consistency check by computing the kinematical factor of a four-point graviton amplitude in a D-instanton background. We conjecture that the low-energy effective action of the IIB matrix model at large N is given by tree-level supergravity coupled to the vertex operators.
Fourth order phase-field model for local max-ent approximants applied to crack propagation
Amiri, Fatemeh; Millán, Daniel; Arroyo Balaguer, Marino; Silani, Mohammad; Rabczuk, Timon
2016-01-01
We apply a fourth order phase-field model for fracture based on local maximum entropy (LME) approximants. The higher order continuity of the meshfree LME approximants allows to directly solve the fourth order phase-field equations without splitting the fourth order differential equation into two second order differential equations. We will first show that the crack surface can be captured more accurately in the fourth order model. Furthermore, less nodes are needed for the fourth order model ...
The Model of Optimum Economic Growth with the Induced Scientific-Technological Progress
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Dilenko Viktor A.
2017-07-01
Full Text Available On the basis of the economic dynamics of the Harrod – Domar model, a model of optimum economic growth in line with the induced scientific-technological progress (STP has been built. In order to reflect the induced scientific-technological progress, with this model is proposed to further allocate the income element that is specially used for the investment of innovation activity, implementation of which reduces the capital intensity in development of the discussed economy. For the simplest way of presenting an economic mechanism for the investment of induced STP, analytical solutions of an appropriate task in optimum management have been obtained. Studying these decisions allowed to reveal the characteristics of the impact of parameters of scientific-technological progress and the analyzed economic system on choosing the best trajectory for its evolution. Possible directions for further developing the results presented can be considered the tasks in building and analyzing models of optimum economic growth that implement different investment options for the induced STP, as well as the models in which this investment mechanism is not exogenouslyed, but rather the result of the corresponding economic-mathematical research.
Construction of energy-stable Galerkin reduced order models.
Energy Technology Data Exchange (ETDEWEB)
Kalashnikova, Irina; Barone, Matthew Franklin; Arunajatesan, Srinivasan; van Bloemen Waanders, Bart Gustaaf
2013-05-01
This report aims to unify several approaches for building stable projection-based reduced order models (ROMs). Attention is focused on linear time-invariant (LTI) systems. The model reduction procedure consists of two steps: the computation of a reduced basis, and the projection of the governing partial differential equations (PDEs) onto this reduced basis. Two kinds of reduced bases are considered: the proper orthogonal decomposition (POD) basis and the balanced truncation basis. The projection step of the model reduction can be done in two ways: via continuous projection or via discrete projection. First, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of PDEs using continuous projection is proposed. The idea is to apply to the set of PDEs a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. The resulting ROM will be energy-stable for any choice of reduced basis. It is shown that, for many PDE systems, the desired transformation is induced by a special weighted L2 inner product, termed the %E2%80%9Csymmetry inner product%E2%80%9D. Attention is then turned to building energy-stable ROMs via discrete projection. A discrete counterpart of the continuous symmetry inner product, a weighted L2 inner product termed the %E2%80%9CLyapunov inner product%E2%80%9D, is derived. The weighting matrix that defines the Lyapunov inner product can be computed in a black-box fashion for a stable LTI system arising from the discretization of a system of PDEs in space. It is shown that a ROM constructed via discrete projection using the Lyapunov inner product will be energy-stable for any choice of reduced basis. Connections between the Lyapunov inner product and the inner product induced by the balanced truncation algorithm are made. Comparisons are also made between the symmetry inner product and the Lyapunov inner product. The performance of ROMs constructed
SyntEyes KTC: higher order statistical eye model for developing keratoconus.
Rozema, Jos J; Rodriguez, Pablo; Ruiz Hidalgo, Irene; Navarro, Rafael; Tassignon, Marie-José; Koppen, Carina
2017-05-01
To present and validate a stochastic eye model for developing keratoconus to e.g. improve optical corrective strategies. This could be particularly useful for researchers that do not have access to original keratoconic data. The Scheimpflug tomography, ocular biometry and wavefront of 145 keratoconic right eyes were collected. These data were processed using principal component analysis for parameter reduction, followed by a multivariate Gaussian fit that produces a stochastic model for keratoconus (SyntEyes KTC). The output of this model is filtered to remove the occasional incorrect topography patterns by either an automatic or manual procedure. Finally, the output of this keratoconus model is matched to that of the original model for normal eyes using the non-corneal biometry to obtain a description of keratoconus development. The synthetic data generated by the model were found to be significantly equal to the original data (non-parametric Mann-Whitney equivalence test; 145/154 passed). The variability of the synthetic data, however, was often significantly less than that of the original data, especially for the higher order Zernike terms of corneal elevation (non-parametric Levene test; p keratoconus progression. The synthetic data provided by the proposed keratoconus model closely resembles actual clinical data and may be used for a range of research applications when (sufficient) real data is not available. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.
Numerical simulation for SI model with variable-order fractional
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mohamed mohamed
2016-04-01
Full Text Available In this paper numerical studies for the variable-order fractional delay differential equations are presented. Adams-Bashforth-Moulton algorithm has been extended to study this problem, where the derivative is defined in the Caputo variable-order fractional sense. Special attention is given to prove the error estimate of the proposed method. Numerical test examples are presented to demonstrate utility of the method. Chaotic behaviors are observed in variable-order one dimensional delayed systems.
Alzheimer's disease: a mathematical model for onset and progression
Bertsch, Michiel; Marcello, Norina; Tesi, Maria Carla; Tosin, Andrea
2015-01-01
In this paper we propose a mathematical model for the onset and progression of Alzheimer's disease based on transport and diffusion equations. We regard brain neurons as a continuous medium, and structure them by their degree of malfunctioning. Two different mechanisms are assumed to be relevant for the temporal evolution of the disease: i) diffusion and agglomeration of soluble polymers of amyloid, produced by damaged neurons; ii) neuron-to-neuron prion-like transmission. We model these two processes by a system of Smoluchowski equations for the amyloid concentration, coupled to a kinetic-type transport equation for the distribution function of the degree of malfunctioning of neurons. The second equation contains an integral term describing the random onset of the disease as a jump process localized in particularly sensitive areas of the brain. Even though we deliberately neglect many aspects of the complexity of the brain and the disease, numerical simulations are in good qualitative agreement with clinical...
Inferring Sequential Order of Somatic Mutations during Tumorgenesis based on Markov Chain Model.
Kang, Hao; Cho, Kwang-Hyun; Zhang, Xiaohua Douglas; Zeng, Tao; Chen, Luonan
2015-01-01
Tumors are developed and worsen with the accumulated mutations on DNA sequences during tumorigenesis. Identifying the temporal order of gene mutations in cancer initiation and development is a challenging topic. It not only provides a new insight into the study of tumorigenesis at the level of genome sequences but also is an effective tool for early diagnosis of tumors and preventive medicine. In this paper, we develop a novel method to accurately estimate the sequential order of gene mutations during tumorigenesis from genome sequencing data based on Markov chain model as TOMC (Temporal Order based on Markov Chain), and also provide a new criterion to further infer the order of samples or patients, which can characterize the severity or stage of the disease. We applied our method to the analysis of tumors based on several high-throughput datasets. Specifically, first, we revealed that tumor suppressor genes (TSG) tend to be mutated ahead of oncogenes, which are considered as important events for key functional loss and gain during tumorigenesis. Second, the comparisons of various methods demonstrated that our approach has clear advantages over the existing methods due to the consideration on the effect of mutation dependence among genes, such as co-mutation. Third and most important, our method is able to deduce the ordinal sequence of patients or samples to quantitatively characterize their severity of tumors. Therefore, our work provides a new way to quantitatively understand the development and progression of tumorigenesis based on high throughput sequencing data.
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)
Models and correlations of the DEBRIS Late-Phase Melt Progression Model
Energy Technology Data Exchange (ETDEWEB)
Schmidt, R.C.; Gasser, R.D. [Sandia National Labs., Albuquerque, NM (United States). Reactor Safety Experiments Dept.
1997-09-01
The DEBRIS Late Phase Melt Progression Model is an assembly of models, embodied in a computer code, which is designed to treat late-phase melt progression in dry rubble (or debris) regions that can form as a consequence of a severe core uncover accident in a commercial light water nuclear reactor. The approach is fully two-dimensional, and incorporates a porous medium modeling framework together with conservation and constitutive relationships to simulate the time-dependent evolution of such regions as various physical processes act upon the materials. The objective of the code is to accurately model these processes so that the late-phase melt progression that would occur in different hypothetical severe nuclear reactor accidents can be better understood and characterized. In this report the models and correlations incorporated and used within the current version of DEBRIS are described. These include the global conservation equations solved, heat transfer and fission heating models, melting and refreezing models (including material interactions), liquid and solid relocation models, gas flow and pressure field models, and the temperature and compositionally dependent material properties employed. The specific models described here have been used in the experiment design analysis of the Phebus FPT-4 debris-bed fission-product release experiment. An earlier DEBRIS code version was used to analyze the MP-1 and MP-2 late-phase melt progression experiments conducted at Sandia National Laboratories for the US Nuclear Regulatory Commission.
Wind Farm Flow Modeling using an Input-Output Reduced-Order Model
Energy Technology Data Exchange (ETDEWEB)
Annoni, Jennifer; Gebraad, Pieter; Seiler, Peter
2016-08-01
Wind turbines in a wind farm operate individually to maximize their own power regardless of the impact of aerodynamic interactions on neighboring turbines. There is the potential to increase power and reduce overall structural loads by properly coordinating turbines. To perform control design and analysis, a model needs to be of low computational cost, but retains the necessary dynamics seen in high-fidelity models. The objective of this work is to obtain a reduced-order model that represents the full-order flow computed using a high-fidelity model. A variety of methods, including proper orthogonal decomposition and dynamic mode decomposition, can be used to extract the dominant flow structures and obtain a reduced-order model. In this paper, we combine proper orthogonal decomposition with a system identification technique to produce an input-output reduced-order model. This technique is used to construct a reduced-order model of the flow within a two-turbine array computed using a large-eddy simulation.
Reduced Order Aeroservoelastic Models with Rigid Body Modes Project
National Aeronautics and Space Administration — Complex aeroelastic and aeroservoelastic phenomena can be modeled on complete aircraft configurations generating models with millions of degrees of freedom. Starting...
Modelling Trends in Ordered Correspondence Analysis Using Orthogonal Polynomials.
Lombardo, Rosaria; Beh, Eric J; Kroonenberg, Pieter M
2016-06-01
The core of the paper consists of the treatment of two special decompositions for correspondence analysis of two-way ordered contingency tables: the bivariate moment decomposition and the hybrid decomposition, both using orthogonal polynomials rather than the commonly used singular vectors. To this end, we will detail and explain the basic characteristics of a particular set of orthogonal polynomials, called Emerson polynomials. It is shown that such polynomials, when used as bases for the row and/or column spaces, can enhance the interpretations via linear, quadratic and higher-order moments of the ordered categories. To aid such interpretations, we propose a new type of graphical display-the polynomial biplot.
Model order reduction of linear time invariant systems
Directory of Open Access Journals (Sweden)
Lj. Radić-Weissenfeld
2008-05-01
Full Text Available This paper addresses issues related to the order reduction of systems with multiple input/output ports. The order reduction is divided up into two steps. The first step is the standard order reduction method based on the multipoint approximation of system matrices by applying Krylov subspace. The second step is based on the rejection of the weak part of a system. To recognise the weak system part, Lyapunov equations are used. Thus, this paper introduces efficient solutions of the Lyapunov equations for port to port subsystems.
Strategic Competence as a Fourth-Order Factor Model: A Structural Equation Modeling Approach
Phakiti, Aek
2008-01-01
This article reports on an empirical study that tests a fourth-order factor model of strategic competence through the use of structural equation modeling (SEM). The study examines the hierarchical relationship of strategic competence to (a) strategic knowledge of cognitive and metacognitive strategy use in general (i.e., trait) and (b) strategic…
Distributed-order diffusion equations and multifractality: Models and solutions
Sandev, Trifce; Chechkin, Aleksei V.; Korabel, Nickolay; Kantz, Holger; Sokolov, Igor M.; Metzler, Ralf
2015-10-01
We study distributed-order time fractional diffusion equations characterized by multifractal memory kernels, in contrast to the simple power-law kernel of common time fractional diffusion equations. Based on the physical approach to anomalous diffusion provided by the seminal Scher-Montroll-Weiss continuous time random walk, we analyze both natural and modified-form distributed-order time fractional diffusion equations and compare the two approaches. The mean squared displacement is obtained and its limiting behavior analyzed. We derive the connection between the Wiener process, described by the conventional Langevin equation and the dynamics encoded by the distributed-order time fractional diffusion equation in terms of a generalized subordination of time. A detailed analysis of the multifractal properties of distributed-order diffusion equations is provided.
NUMERICAL MODELLING OF PROGRESSIVE FAILURE IN PARTICULATE COMPOSITES LIKE SANDSTONE
Institute of Scientific and Technical Information of China (English)
无
1999-01-01
The beam-particle model is presented for analyzing the progressive failure of particulate composites such as sandstone and concrete. In the model, the medium is schematized as an assembly of particles which are linked through a network of brittle-breaking beam elements. The mechanical behaviour of particle elements is governed by the distinct element method and finite element method. The propagation of the cracking process in particulate composites is mimicked by removing the beam element from the mesh as soon as the stress in the beam exceeds the strength assigned to that particular beam. The new model can be utilized at a meso-scale and in different loading conditions. Two physical experiments are performed to verify the numerical results. The crack patterns and load-displacement response obtained with the proposed numerical model are in good agreement with the experimental results. Moreover, the influence of heterogeneity on crack patterns is also discussed and the correlation existing between the fracture evolution and the loads imposed on the specimen is characterized by fractal dimensions.
Policy Decisions for a Price Dependent Demand Rate Inventory Model with Progressive Payments Scheme
Directory of Open Access Journals (Sweden)
Rajat Kumar
2012-01-01
Full Text Available Problem statement: In this proposed research, we developed an inventory model to formulate an optimal ordering policies for supplier who offers progressive permissible delay periods to the retailer to settle his/her account. We assumed that the annual demand rate as a decreasing function of price with constant rate of deterioration and time-varying holding cost. Shortages in inventory are allowed which is completely backlogged. Approach: The main objective of this study to frame an inventory model in real life situations. In this study, we introduced a new idea of trade credits, namely, the supplier charges the retailer progressive interest rates if the retailer prolongs its unpaid balance. By offering progressive interest rates to the retailers, a supplier, can secure competitive market advantage over the competitors and possibly improve market share profit. This study has two main purposes, first the mathematical model of an inventory system are establish under the above conditions and second demonstrate that the optimal solution not only exists but also feasible. We developed theoretical results to obtain the optimal replenishment interval by examine the explicit condition. An algorithm is given to find the flow of optimal ordering policy. Results: The results is illustrated with the help of numerical example using Mathematica software and the optimal solution of the problem is Z (p, T1 = 76.8586 at (p, T1 = (0.952656, 0.128844. Conclusion: We proposed an algorithm to find the optimal ordering policy. A numerical study has been performed to observe the sensitivity of the effect of demand parameter changes.
Ito, Shin-Ichi; Nagao, Hiromichi; Yamanaka, Akinori; Tsukada, Yuhki; Koyama, Toshiyuki; Inoue, Junya
Phase field (PF) method, which phenomenologically describes dynamics of microstructure evolutions during solidification and phase transformation, has progressed in the fields of hydromechanics and materials engineering. How to determine, based on observation data, an initial state and model parameters involved in a PF model is one of important issues since previous estimation methods require too much computational cost. We propose data assimilation (DA), which enables us to estimate the parameters and states by integrating the PF model and observation data on the basis of the Bayesian statistics. The adjoint method implemented on DA not only finds an optimum solution by maximizing a posterior distribution but also evaluates the uncertainty in the estimations by utilizing the second order information of the posterior distribution. We carried out an estimation test using synthetic data generated by the two-dimensional Kobayashi's PF model. The proposed method is confirmed to reproduce the true initial state and model parameters we assume in advance, and simultaneously estimate their uncertainties due to quality and quantity of the data. This result indicates that the proposed method is capable of suggesting the experimental design to achieve the required accuracy.
2D model for melt progression through rods and debris
Energy Technology Data Exchange (ETDEWEB)
Fichot, F. [IPSN/DRS, CEA Cadarache, St. Paul-lez-Durance (France)
2001-07-01
During the degradation of a nuclear core in a severe accident scenario, the high temperatures reached lead to the melting of materials. The formation of liquid mixtures at various elevations is followed by the flow of molten materials through the core. Liquid mixture may flow under several configurations: axial relocation along the rods, horizontal motion over a plane surface such as the core support plate or a blockage of material, 2D relocation through a debris bed, etc.. The two-dimensional relocation of molten material through a porous debris bed, implemented for the simulation of late degradation phases, has opened a new way to the elaboration of the relocation model for the flow of liquid mixture along the rods. It is based on a volume averaging method, where wall friction and capillary effects are taken into account by introducing effective coefficients to characterize the solid matrix (rods, grids, debris, etc.). A local description of the liquid flow is necessary to derive the effective coefficients. Heat transfers are modelled in a similar way. The derivation of the conservation equations for the liquid mixture falling flow (momentum) in two directions (axial and radial-horizontal) and for the heat exchanges (energy) are the main points of this new model for simulating melt progression. In this presentation, the full model for the relocation and solidification of liquid materials through a rod bundle or a debris bed is described. It is implemented in the ICARE/CATHARE code, developed by IPSN in Cadarache. The main improvements and advantages of the new model are: A single formulation for liquid mixture relocation, in 2D, either through a rod bundle or a porous debris bed, Extensions to complex structures (grids, by-pass, etc..), The modeling of relocation of a liquid mixture over plane surfaces. (author)
Directory of Open Access Journals (Sweden)
Kotb A.E.H.M. Kotb
2011-01-01
Full Text Available Problem statement: In this study, we provide a simple method to determine the inventory policy of probabilistic single-item Economic Order Quantity (EOQ model, that has varying order cost and zero lead time. The model is restricted to the expected holding cost and the expected available limited storage space. Approach: The annual expected total cost is composed of three components (expected purchase cost, expected ordering cost and expected holding cost. The problem is then solved using a modified Geometric Programming method (GP. Results: Using the annual expected total cost to determine the optimal solutions, number of periods, maximum inventory level and minimum expected total cost per period. A classical model is derived and numerical example is solved to confirm the model. Conclusion/Recommendations: The results indicated the total cost decreased with changes in optimal solutions. Possible future extension of this model was include continuous decreasing ordering function of the number of periods and introducing expected annual demand rate as a decision variable.
Ordering in Two-Dimensional Ising Models with Competing Interactions
2004-01-01
We study the 2D Ising model on a square lattice with additional non-equal diagonal next-nearest neighbor interactions. The cases of classical and quantum (transverse) models are considered. Possible phases and their locations in the space of three Ising couplings are analyzed. In particular, incommensurate phases occurring only at non-equal diagonal couplings, are predicted. We also analyze a spin-pseudospin model comprised of the quantum Ising model coupled to XY spin chains in a particular ...
Modeling Human Behaviour with Higher Order Logic: Insider Threats
Boender, Jaap; Ivanova, Marieta Georgieva; Kammüller, Florian; Primierio, Giuseppe
2014-01-01
In this paper, we approach the problem of modeling the human component in technical systems with a view on the difference between the use of model and theory in sociology and computer science. One aim of this essay is to show that building of theories and models for sociology can be compared and imp
Modelling the Progression of Male Swimmers’ Performances through Adolescence
Directory of Open Access Journals (Sweden)
Shilo J. Dormehl
2016-01-01
Full Text Available Insufficient data on adolescent athletes is contributing to the challenges facing youth athletic development and accurate talent identification. The purpose of this study was to model the progression of male sub-elite swimmers’ performances during adolescence. The performances of 446 males (12–19 year olds competing in seven individual events (50, 100, 200 m freestyle, 100 m backstroke, breaststroke, butterfly, 200 m individual medley over an eight-year period at an annual international schools swimming championship, run under FINA regulations were collected. Quadratic functions for each event were determined using mixed linear models. Thresholds of peak performance were achieved between the ages of 18.5 ± 0.1 (50 m freestyle and 200 m individual medley and 19.8 ± 0.1 (100 m butterfly years. The slowest rate of improvement was observed in the 200 m individual medley (20.7% and the highest in the 100 m butterfly (26.2%. Butterfly does however appear to be one of the last strokes in which males specialise. The models may be useful as talent identification tools, as they predict the age at which an average sub-elite swimmer could potentially peak. The expected rate of improvement could serve as a tool in which to monitor and evaluate benchmarks.
Automatic Black-Box Model Order Reduction using Radial Basis Functions
Energy Technology Data Exchange (ETDEWEB)
Stephanson, M B; Lee, J F; White, D A
2011-07-15
Finite elements methods have long made use of model order reduction (MOR), particularly in the context of fast freqeucny sweeps. In this paper, we discuss a black-box MOR technique, applicable to a many solution methods and not restricted only to spectral responses. We also discuss automated methods for generating a reduced order model that meets a given error tolerance. Numerical examples demonstrate the effectiveness and wide applicability of the method. With the advent of improved computing hardware and numerous fast solution techniques, the field of computational electromagnetics are progressed rapidly in terms of the size and complexity of problems that can be solved. Numerous applications, however, require the solution of a problem for many different configurations, including optimization, parameter exploration, and uncertainly quantification, where the parameters that may be changed include frequency, material properties, geometric dimensions, etc. In such cases, thousands of solutions may be needed, so solve times of even a few minutes can be burdensome. Model order reduction (MOR) may alleviate this difficulty by creating a small model that can be evaluated quickly. Many MOR techniques have been applied to electromagnetic problems over the past few decades, particularly in the context of fast frequency sweeps. Recent works have extended these methods to allow more than one parameter and to allow the parameters to represent material and geometric properties. There are still limitations with these methods, however. First, they almost always assume that the finite element method is used to solve the problem, so that the system matrix is a known function of the parameters. Second, although some authors have presented adaptive methods (e.g., [2]), the order of the model is often determined before the MOR process begins, with little insight about what order is actually needed to reach the desired accuracy. Finally, it not clear how to efficiently extend most
Spin and quadrupolar orders in the spin-1 bilinear-biquadratic model for iron-based superconductors
Luo, Cheng; Datta, Trinanjan; Yao, Dao-Xin
2016-06-01
Motivated by the recent experimental and theoretical progress of the magnetic properties in iron-based superconductors, we provide a comprehensive analysis of the extended spin-1 bilinear-biquadratic (BBQ) model on the square lattice. Using a variational approach at the mean-field level, we identify the existence of various magnetic phases, including conventional spin dipolar orders (ferro- and antiferromagnet), novel quadrupolar orders (spin nematic), and mixed dipolar-quadrupolar orders. In contrast to the regular Heisenberg model, the elementary excitations of the spin-1 BBQ model are described by the SU(3) flavor-wave theory. By fitting the experimental spin-wave dispersion, we determine the refined exchange couplings corresponding to the collinear antiferromagnetic iron pnictides. We also present the dynamic structure factors of both spin dipolar and quadrupolar components with connections to the future experiments.
Domain minimization and beyond: Modeling prepositional phrase ordering
Wiechmann, D.; Lohmann, A.
2013-01-01
An important account of linear ordering in syntax is John A. Hawkins' (2004) theory of cognitive efficiency and the principles of domain minimization formulated therein. In its latest formulation, the theory postulates syntactic and semantic minimization principles. With regard to the relative stren
Higher Order Hierarchical Legendre Basis Functions for Electromagnetic Modeling
DEFF Research Database (Denmark)
Jørgensen, Erik; Volakis, John L.; Meincke, Peter
2004-01-01
This paper presents a new hierarchical basis of arbitrary order for integral equations solved with the Method of Moments (MoM). The basis is derived from orthogonal Legendre polynomials which are modified to impose continuity of vector quantities between neighboring elements while maintaining mos...
Higher Order Hierarchical Legendre Basis Functions for Electromagnetic Modeling
DEFF Research Database (Denmark)
Jørgensen, Erik; Volakis, John L.; Meincke, Peter
2004-01-01
This paper presents a new hierarchical basis of arbitrary order for integral equations solved with the Method of Moments (MoM). The basis is derived from orthogonal Legendre polynomials which are modified to impose continuity of vector quantities between neighboring elements while maintaining mos...
High order fluid model for ionization fronts in streamer discharges
Markosyan, A.; Dujko, S.; Hundsdorfer, W.; Ebert, U.
2011-01-01
When non-ionized or lowly ionized matter is exposed to high electric fields, non-equilibrium ionization processes, streamer discharges, can develop. Streamers occur in nature and as well in many industrial applications such as the treatment of exhaust gasses, polluted water or biogas. A third order
A Framework Model for an Order Fulfillment System Based on Service Oriented Architecture
Institute of Scientific and Technical Information of China (English)
YANG Li-xi; LI Shi-qi
2008-01-01
To effectively implement order fulfillment, we present an integrated framework model focusing on the whole process of order fulfillment. Firstly, five aims of the OFS (order fulfillment system) are built. Then after discussing three major processes of order fulfillment, we summarize functional and quality attributes of the OFS. Subsequently, we investigate SOA (Service Oriented Architecture) and present a SOA meta-model to be an integrated framework and to fulfill quality requirements. Moreover, based on the SOA meta-model, we construct a conceptual framework model that aims to conveniently integrate other functions from different systems into the order fulfillment system. This model offers enterprises a new approach to implementing order fulfillment.
Methods for eigenvalue problems with applications in model order reduction
Rommes, J.
2007-01-01
Physical structures and processes are modeled by dynamical systems in a wide range of application areas. The increasing demand for complex components and large structures, together with an increasing demand for detail and accuracy, makes the models larger and more complicated. To be able to simulate
Calculus for cognitive scientists higher order models and their analysis
Peterson, James K
2016-01-01
This book offers a self-study program on how mathematics, computer science and science can be profitably and seamlessly intertwined. This book focuses on two variable ODE models, both linear and nonlinear, and highlights theoretical and computational tools using MATLAB to explain their solutions. It also shows how to solve cable models using separation of variables and the Fourier Series.
Temporal Aggregation in First Order Cointegrated Vector Autoregressive models
DEFF Research Database (Denmark)
Milhøj, Anders; la Cour, Lisbeth Funding
2011-01-01
with the frequency of the data. We also introduce a graphical representation that will prove useful as an additional informational tool for deciding the appropriate cointegration rank of a model. In two examples based on models of time series of different grades of gasoline, we demonstrate the usefulness of our...
A Processing Model for Free Word Order Languages
Rambow, O; Rambow, Owen; Joshi, Aravind K.
1995-01-01
Like many verb-final languages, Germn displays considerable word-order freedom: there is no syntactic constraint on the ordering of the nominal arguments of a verb, as long as the verb remains in final position. This effect is referred to as ``scrambling'', and is interpreted in transformational frameworks as leftward movement of the arguments. Furthermore, arguments from an embedded clause may move out of their clause; this effect is referred to as ``long-distance scrambling''. While scrambling has recently received considerable attention in the syntactic literature, the status of long-distance scrambling has only rarely been addressed. The reason for this is the problematic status of the data: not only is long-distance scrambling highly dependent on pragmatic context, it also is strongly subject to degradation due to processing constraints. As in the case of center-embedding, it is not immediately clear whether to assume that observed unacceptability of highly complex sentences is due to grammatical restric...
Modeling Pluto-Charon mutual eclipse events. I. First-order models
Energy Technology Data Exchange (ETDEWEB)
Dunbar, R.S.; Tedesco, E.F.
1986-11-01
The present first order analytical and numerical models of light curves due to mutual events between close planetary binaries, the effects of shadowing are included. Attention is given to the case of the Pluto-Charon system. The results of the analytical and numerical approaches agree to well within the expected light curve measurement error. The model predicts that the current mutual eclipse event series will end by November 1990. 12 references.
Heterogeneous traffic flow modelling using second-order macroscopic continuum model
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.
Reduced Order Models for Dynamic Behavior of Elastomer Damping Devices
Morin, B.; Legay, A.; Deü, J.-F.
2016-09-01
In the context of passive damping, various mechanical systems from the space industry use elastomer components (shock absorbers, silent blocks, flexible joints...). The material of these devices has frequency, temperature and amplitude dependent characteristics. The associated numerical models, using viscoelastic and hyperelastic constitutive behaviour, may become computationally too expensive during a design process. The aim of this work is to propose efficient reduced viscoelastic models of rubber devices. The first step is to choose an accurate material model that represent the viscoelasticity. The second step is to reduce the rubber device finite element model to a super-element that keeps the frequency dependence. This reduced model is first built by taking into account the fact that the device's interfaces are much more rigid than the rubber core. To make use of this difference, kinematical constraints enforce the rigid body motion of these interfaces reducing the rubber device model to twelve dofs only on the interfaces (three rotations and three translations per face). Then, the superelement is built by using a component mode synthesis method. As an application, the dynamic behavior of a structure supported by four hourglass shaped rubber devices under harmonic loads is analysed to show the efficiency of the proposed approach.
High order fluid model for streamer discharges: I. Derivation of model and transport data
Dujko, S; White, R D; Ebert, U
2013-01-01
Streamer discharges pose basic problems in plasma physics, as they are very transient, far from equilibrium and have high ionization density gradients; they appear in diverse areas of science and technology. The present paper focuses on the derivation of a high order fluid model for streamers. Using momentum transfer theory, the fluid equations are obtained as velocity moments of the Boltzmann equation; they are closed in the local mean energy approximation and coupled to the Poisson equation for the space charge generated electric field. The high order tensor in the energy flux equation is approximated by the product of two lower order moments to close the system. The average collision frequencies for momentum and energy transfer in elastic and inelastic collisions for electrons in molecular nitrogen are calculated from a multi term Boltzmann equation solution. We then discuss, in particular, (1) the correct implementation of transport data in streamer models; (2) the accuracy of the two term approximation f...
Living ordered neural networks as model systems for signal processing
Villard, C.; Amblard, P. O.; Becq, G.; Gory-Fauré, S.; Brocard, J.; Roth, S.
2007-06-01
Neural circuit architecture is a fundamental characteristic of the brain, and how architecture is bound to biological functions is still an open question. Some neuronal geometries seen in the retina or the cochlea are intriguing: information is processed in parallel by several entities like in "pooling" networks which have recently drawn the attention of signal processing scientists. These systems indeed exhibit the noise-enhanced processing effect, which is also actively discussed in the neuroscience community at the neuron scale. The aim of our project is to use in-vitro ordered neuron networks as living paradigms to test ideas coming from the computational science. The different technological bolts that have to be solved are enumerated and the first results are presented. A neuron is a polarised cell, with an excitatory axon and a receiving dendritic tree. We present how soma confinement and axon differentiation can be induced by surface functionalization techniques. The recording of large neuron networks, ordered or not, is also detailed and biological signals shown. The main difficulty to access neural noise in the case of weakly connected networks grown on micro electrode arrays is explained. This open the door to a new detection technology suitable for sub-cellular analysis and stimulation, whose development will constitute the next step of this project.
Multilevel Higher-Order Item Response Theory Models
Huang, Hung-Yu; Wang, Wen-Chung
2014-01-01
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Passivity Preserving Model Order Reduction For the SMIB
Ionescu, Tudor C.; Scherpen, Jacquelien M. A.
2008-01-01
We apply (linear) positive real balancing to the model of a single machine connected to an infinite bus. For that we compute the available storage and the required supply using Taylor approximation and define axis positive real singular value functions. Furthermore, we apply linear positive real bal
Comparative modelling of chemical ordering in palladium-iridium nanoalloys
Energy Technology Data Exchange (ETDEWEB)
Davis, Jack B. A.; Johnston, Roy L., E-mail: r.l.johnston@bham.ac.uk [School of Chemistry, University of Birmingham, Birmingham B15 2TT (United Kingdom); Rubinovich, Leonid; Polak, Micha, E-mail: mpolak@bgu.ac.il [Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 84105 (Israel)
2014-12-14
Chemical ordering in “magic-number” palladium-iridium nanoalloys has been studied by means of density functional theory (DFT) computations, and compared to those obtained by the Free Energy Concentration Expansion Method (FCEM) using derived coordination dependent bond energy variations (CBEV), and by the Birmingham Cluster Genetic Algorithm using the Gupta potential. Several compositions have been studied for 38- and 79-atom particles as well as the site preference for a single Ir dopant atom in the 201-atom truncated octahedron (TO). The 79- and 38-atom nanoalloy homotops predicted for the TO by the FCEM/CBEV are shown to be, respectively, the global minima and competitive low energy minima. Significant reordering of minima predicted by the Gupta potential is seen after reoptimisation at the DFT level.
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.
Higher-Order Approximation of Cubic-Quintic Duffing Model
DEFF Research Database (Denmark)
Ganji, S. S.; Barari, Amin; Babazadeh, H.
2011-01-01
We apply an Artificial Parameter Lindstedt-Poincaré Method (APL-PM) to find improved approximate solutions for strongly nonlinear Duffing oscillations with cubic-quintic nonlinear restoring force. This approach yields simple linear algebraic equations instead of nonlinear algebraic equations...... without analytical solution which makes it a unique solution. It is demonstrated that this method works very well for the whole range of parameters in the case of the cubic-quintic oscillator, and excellent agreement of the approximate frequencies with the exact one has been observed and discussed....... Moreover, it is not limited to the small parameter such as in the classical perturbation method. Interestingly, this study revealed that the relative error percentage in the second-order approximate analytical period is less than 0.042% for the whole parameter values. In addition, we compared...
Progress and Current Challenges in Modeling Large RNAs.
Somarowthu, Srinivas
2016-02-27
Recent breakthroughs in next-generation sequencing technologies have led to the discovery of several classes of non-coding RNAs (ncRNAs). It is now apparent that RNA molecules are not only just carriers of genetic information but also key players in many cellular processes. While there has been a rapid increase in the number of ncRNA sequences deposited in various databases over the past decade, the biological functions of these ncRNAs are largely not well understood. Similar to proteins, RNA molecules carry out a function by forming specific three-dimensional structures. Understanding the function of a particular RNA therefore requires a detailed knowledge of its structure. However, determining experimental structures of RNA is extremely challenging. In fact, RNA-only structures represent just 1% of the total structures deposited in the PDB. Thus, computational methods that predict three-dimensional RNA structures are in high demand. Computational models can provide valuable insights into structure-function relationships in ncRNAs and can aid in the development of functional hypotheses and experimental designs. In recent years, a set of diverse RNA structure prediction tools have become available, which differ in computational time, input data and accuracy. This review discusses the recent progress and challenges in RNA structure prediction methods.
Finite element modeling of a progressively expanding shape memory stent.
Thériault, Philippe; Terriault, Patrick; Brailovski, Vladimir; Gallo, Richard
2006-01-01
Cardiovascular stents are small cylindrical devices introduced in stenosed arteries to reopen the lumen and restore blood flow. However, this treatment presents complications, including restenosis, which is the reclosing of the artery's diameter after the insertion of a stent. The structure of the prosthesis penetrates into and injures the walls of the patient's artery. There then follows a proliferation of cells and the formation of scar tissue around the injury, similar to the scarring of other organic tissues. This reaction to the trauma subjects the artery to close. The proposed solution is to develop a Nitinol stent with a progressive expansion device made of polyethylene, allowing smooth and gradual contact between the stent and the artery's wall by creep effect. The purpose of this paper is to describe the technology and methodology for the numerical study of this kind of stent through the finite element method. ANSYS 8.0 software is used to perform the analysis. The Nitinol is modeled with a superelastic law and the polyethylene with a yield hardening law. A first simulation determines the final geometry of the stent laser cut from a small tube. A second simulation examines the behavior of the prosthesis during surgery and over the 4 weeks following the operation. The results demonstrate that a compromise can be reached between a limited expansion prior the inflation of the expandable balloon and a significant expansion by creep of the polymer rings.
Using Rasch models to develop and validate an environmental thinking learning progression
Hashimoto-Martell, Erin A.
Environmental understanding is highly relevant in today's global society. Social, economic, and political structures are connected to the state of environmental degradation and exploitation, and disproportionately affect those in poor or urban communities (Brulle & Pellow, 2006; Executive Order No. 12898, 1994). Environmental education must challenge the way we live, and our social and ecological quality of life, with the goal of responsible action. The development of a learning progression in environmental thinking, along with a corresponding assessment, could provide a tool that could be used across environmental education programs to help evaluate and guide programmatic decisions. This study sought to determine if a scale could be constructed that allowed individuals to be ordered along a continuum of environmental thinking. First, I developed the Environmental Thinking Learning Progression, a scale of environmental thinking from novice to advanced, based on the current available research and literature. The scale consisted of four subscales, each measuring a different aspect of environmental thinking: place consciousness, human connection, agency, and science concepts. Second, a measurement instrument was developed, so that the data appropriately fit the model using Rasch analysis. A Rasch analysis of the data placed respondents along a continuum, given the range of item difficulty for each subscale. Across three iterations of instrument revision and data collection, findings indicated that the items were ordered in a hierarchical way that corresponded to the construct of environmental thinking. Comparisons between groups showed that the average score of respondents who had participated in environmental education programs was significantly higher than those who had not. A comparison between males and females showed no significant difference in average measure, however, there were varied significant differences between how racial/ethnic groups performed. Overall
Validating and optimizing the effects of model progression in simulation-based inquiry learning
Mulder, Y.G.; Lazonder, A.W.; Jong, de T.; Anjewierden, A.A.; Bollen, L.
2012-01-01
Model progression denotes the organization of the inquiry learning process in successive phases of increasing complexity. This study investigated the effectiveness of model progression in general, and explored the added value of either broadening or narrowing students’ possibilities to change model
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.
A Refinement of the Classical Order Point Model
Farhad Moeeni; Stephen Replogle; Zariff Chaudhury; Ahmad Syamil
2012-01-01
Factors such as demand volume and replenishment lead time that influence production and inventory control systems are random variables. Existing inventory models incorporate the parameters (e.g., mean and standard deviation) of these statistical quantities to formulate inventory policies. In practice, only sample estimates of these parameters are available. The estimates are subject to sampling variation and hence are random variables. Whereas the effect of sampling variability on estimates o...
A first-order dynamical model of hierarchical triple stars and its application
Xu, Xingbo; Fu, Yanning
2015-01-01
For most hierarchical triple stars, the classical double two-body model of zeroth-order cannot describe the motions of the components under the current observational accuracy. In this paper, Marchal's first-order analytical solution is implemented and a more efficient simplified version is applied to real triple stars. The results show that, for most triple stars, the proposed first-order model is preferable to the zeroth-order model either in fitting observational data or in predicting component positions.
Order and chaos in hydrodynamic BL Her models
Smolec, R
2013-01-01
Many dynamical systems of different complexity, e.g. 1D logistic map, the Lorentz equations, or real phenomena, like turbulent convection, show chaotic behaviour. Despite huge differences, the dynamical scenarios for these systems are strikingly similar: chaotic bands are born through the series of period doubling bifurcations and merge through interior crises. Within chaotic bands periodic windows are born through the tangent bifurcations, preceded by the intermittent behaviour. This is a universal behaviour of dynamical systems (Feigenbaum 1983). We demonstrate such behaviour in models of pulsating stars.
On the use of fractional order PK-PD models
Ionescu, Clara; Copot, Dana
2017-01-01
Quantifying and controlling depth of anesthesia is a challenging process due to lack of measurement technology for direct effects of drug supply into the body. Efforts are being made to develop new sensor techniques and new horizons are explored for modeling this intricate process. This paper introduces emerging tools available on the ‘engineering market’ imported from the area of fractional calculus. A novel interpretation of the classical drug-effect curve is given, enabling linear control. This enables broadening the horizon of signal processing and control techniques and suggests future research lines.
REVEAL: An Extensible Reduced Order Model Builder for Simulation and Modeling
Energy Technology Data Exchange (ETDEWEB)
Agarwal, Khushbu; Sharma, Poorva; Ma, Jinliang; Lo, Chaomei; Gorton, Ian; Liu, Yan
2013-04-30
Many science domains need to build computationally efficient and accurate representations of high fidelity, computationally expensive simulations. These computationally efficient versions are known as reduced-order models. This paper presents the design and implementation of a novel reduced-order model (ROM) builder, the REVEAL toolset. This toolset generates ROMs based on science- and engineering-domain specific simulations executed on high performance computing (HPC) platforms. The toolset encompasses a range of sampling and regression methods that can be used to generate a ROM, automatically quantifies the ROM accuracy, and provides support for an iterative approach to improve ROM accuracy. REVEAL is designed to be extensible in order to utilize the core functionality with any simulator that has published input and output formats. It also defines programmatic interfaces to include new sampling and regression techniques so that users can ‘mix and match’ mathematical techniques to best suit the characteristics of their model. In this paper, we describe the architecture of REVEAL and demonstrate its usage with a computational fluid dynamics model used in carbon capture.
A proposed fractional-order Gompertz model and its application to tumour growth data.
Bolton, Larisse; Cloot, Alain H J J; Schoombie, Schalk W; Slabbert, Jacobus P
2015-06-01
A fractional-order Gompertz model of orders between 0 and 2 is proposed. The main purpose of this investigation is to determine whether the ordinary or proposed fractional Gompertz model would best fit our experimental dataset. The solutions for the proposed model are obtained using fundamental concepts from fractional calculus. The closed-form equations of both the proposed model and the ordinary Gompertz model are calibrated using an experimental dataset containing tumour growth volumes of a Rhabdomyosarcoma tumour in a mouse. With regard to the proposed model, the order, within the interval mentioned, that resulted in the best fit to the data was used in a further investigation into the prediction capability of the model. This was compared to the prediction capability of the ordinary Gompertz model. The result of the investigation was that a fractional-order Gompertz model of order 0.68 produced a better fit to our experimental dataset than the well-known ordinary Gompertz model.
POD/DEIM Nonlinear model order reduction of an ADI implicit shallow water equations model
Stefanescu, Razvan
2012-01-01
In the present paper we consider a 2-D shallow-water equations (SWE) model on a $\\beta$-plane solved using an alternating direction fully implicit (ADI) finite-difference scheme on a rectangular domain. The scheme was shown to be unconditionally stable for the linearized equations. The discretization yields a number of nonlinear systems of algebraic equations. We then use a proper orthogonal decomposition (POD) to reduce the dimension of the SWE model. Due to the model nonlinearities, the computational complexity of the reduced model still depends on the number of variables of the full shallow - water equations model. By employing the discrete empirical interpolation method (DEIM) we reduce the computational complexity of the reduced order model due to its depending on the nonlinear full dimension model and regain the full model reduction expected from the POD model. To emphasize the CPU gain in performance due to use of POD/DEIM, we also propose testing an explicit Euler finite difference scheme (EE) as an a...
Energy Technology Data Exchange (ETDEWEB)
Hong, J.H. [Kyungwon University, Songnam (Korea, Republic of)
1995-07-01
This paper describes a method of obtaining transmission network equivalents from the network`s response to a impulse excitation signal. Proposed method is based on the modal decomposition representation for the large-scale interconnected system. For this framework we use Prony analysis to identify the network function of the system and to decompose the large system into a parallel combination of simple first-order systems. As a result, rational network function of optimal low order can be obtained in a direct and simple way. And Thevenin-type of discrete-time filter model can be generated. It can reproduce the driving-point impedance characteristic of the network. Furthermore proposed model can be implemented into the EMTP in a direct manner. The simulation results with the full system representation and the developed equivalent system showed a good agreement. (author). 14 refs., 11 figs.
Applicability of the capability maturity model for engineer-to-order firms
Veldman, J.; Klingenberg, W.
2009-01-01
Most of the well-known management and improvement systems and techniques, Such as Lean Production (e.g. Just-In-Time (JIT) Pull production, one piece flow) and Six Sigma (reduction in variation) were developed in high Volume industries. In order to measure the progress of the implementation of Such
Applicability of the capability maturity model for engineer-to-order firms
Veldman, Jasper; Klingenberg, Warse
2009-01-01
Most of the well-known management and improvement systems and techniques, such as Lean Production (e.g. Just-In-Time (JIT) pull production, one piece flow) and Six Sigma (reduction in variation) were developed in high volume industries. In order to measure the progress of the implementation of such
Applicability of the capability maturity model for engineer-to-order firms
Veldman, Jasper; Klingenberg, Warse
2009-01-01
Most of the well-known management and improvement systems and techniques, such as Lean Production (e.g. Just-In-Time (JIT) pull production, one piece flow) and Six Sigma (reduction in variation) were developed in high volume industries. In order to measure the progress of the implementation of such
Applicability of the capability maturity model for engineer-to-order firms
Veldman, J.; Klingenberg, W.
2009-01-01
Most of the well-known management and improvement systems and techniques, Such as Lean Production (e.g. Just-In-Time (JIT) Pull production, one piece flow) and Six Sigma (reduction in variation) were developed in high Volume industries. In order to measure the progress of the implementation of Such
An epidemic model for the future progression of the current Haiti cholera epidemic
Bertuzzo, E.; Mari, L.; Righetto, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.
2012-04-01
As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to December 2011, climb to 522,000 cases and 7,000 deaths, the development of general models to track and predict the evolution of the outbreak, so as to guide the allocation of medical supplies and staff, is gaining notable urgency. We propose here a spatially explicit epidemic model that accounts for the dynamics of susceptible and infected individuals as well as the redistribution of Vibrio cholera, the causative agent of the disease, among different human communities. In particular, we model two spreading pathways: the advection of pathogens through hydrologic connections and the dissemination due to human mobility described by means of a gravity-like model. To this end the country has been divided into hydrologic units based on drainage directions derived from a digital terrain model. Moreover the population of each unit has been estimated from census data downscaled to 1 km x 1 km resolution via remotely sensed geomorphological information (LandScan project). The model directly accounts for the role of rainfall patterns in driving the seasonality of cholera outbreaks. The two main outbreaks in fact occurred during the rainy seasons (October and May) when extensive floodings severely worsened the sanitation conditions and, in turn, raised the risk of infection. The model capability to reproduce the spatiotemporal features of the epidemic up to date grants robustness to the foreseen future development. To this end, we generate realistic scenario of future precipitation in order to forecast possible epidemic paths up to the end of the 2013. In this context, the duration of acquired immunity, a hotly debated topic in the scientific community, emerges as a controlling factor for progression of the epidemic in the near future. The framework presented here can straightforwardly be used to evaluate the effectiveness of alternative intervention strategies like mass vaccinations
Model Order Selection in Multi-baseline Interferometric Radar Systems
Directory of Open Access Journals (Sweden)
Fulvio Gini
2005-12-01
Full Text Available Synthetic aperture radar interferometry (InSAR is a powerful technique to derive three-dimensional terrain images. Interest is growing in exploiting the advanced multi-baseline mode of InSAR to solve layover effects from complex orography, which generate reception of unexpected multicomponent signals that degrade imagery of both terrain radar reflectivity and height. This work addresses a few problems related to the implementation into interferometric processing of nonlinear algorithms for estimating the number of signal components, including a system trade-off analysis. Performance of various eigenvalues-based information-theoretic criteria (ITC algorithms is numerically investigated under some realistic conditions. In particular, speckle effects from surface and volume scattering are taken into account as multiplicative noise in the signal model. Robustness to leakage of signal power into the noise eigenvalues and operation with a small number of looks are investigated. The issue of baseline optimization for detection is also addressed. The use of diagonally loaded ITC methods is then proposed as a tool for robust operation in the presence of speckle decorrelation. Finally, case studies of a nonuniform array are studied and recommendations for a proper combination of ITC methods and system configuration are given.
Markosyan, A H; Ebert, U
2013-01-01
The high order fluid model developed in the preceding paper is employed here to study the propagation of negative planar streamer fronts in pure nitrogen. The model consists of the balance equations for electron density, average electron velocity, average electron energy and average electron energy flux. These balance equations have been obtained as velocity moments of Boltzmann's equation and are here coupled to the Poisson equation for the space charge electric field. Here the results of simulations with the high order model, with a PIC/MC (Particle in cell/Monte Carlo) model and with the first order fluid model based on the hydrodynamic drift-diffusion approximation are presented and compared. The comparison with the MC model clearly validates our high order fluid model, thus supporting its correct theoretical derivation and numerical implementation. The results of the first order fluid model with local field approximation, as usually used for streamer discharges, show considerable deviations. Furthermore,...
Ability, Breadth, and Parsimony in Computational Models of Higher-Order Cognition
Cassimatis, Nicholas L.; Bello, Paul; Langley, Pat
2008-01-01
Computational models will play an important role in our understanding of human higher-order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher-order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do;…
Higher-Order Process Modeling: Product-Lining, Variability Modeling and Beyond
Directory of Open Access Journals (Sweden)
Johannes Neubauer
2013-09-01
Full Text Available We present a graphical and dynamic framework for binding and execution of business process models. It is tailored to integrate 1 ad hoc processes modeled graphically, 2 third party services discovered in the (Internet, and 3 (dynamically synthesized process chains that solve situation-specific tasks, with the synthesis taking place not only at design time, but also at runtime. Key to our approach is the introduction of type-safe stacked second-order execution contexts that allow for higher-order process modeling. Tamed by our underlying strict service-oriented notion of abstraction, this approach is tailored also to be used by application experts with little technical knowledge: users can select, modify, construct and then pass (component processes during process execution as if they were data. We illustrate the impact and essence of our framework along a concrete, realistic (business process modeling scenario: the development of Springer's browser-based Online Conference Service (OCS. The most advanced feature of our new framework allows one to combine online synthesis with the integration of the synthesized process into the running application. This ability leads to a particularly flexible way of implementing self-adaption, and to a particularly concise and powerful way of achieving variability not only at design time, but also at runtime.
Stochastic modelling and predictability: analysis of a low-order coupled ocean-atmosphere model.
Vannitsem, Stéphane
2014-06-28
There is a growing interest in developing stochastic schemes for the description of processes that are poorly represented in atmospheric and climate models, in order to increase their variability and reduce the impact of model errors. The use of such noise could however have adverse effects by modifying in undesired ways a certain number of moments of their probability distributions. In this work, the impact of developing a stochastic scheme (based on stochastic averaging) for the ocean is explored in the context of a low-order coupled (deterministic) ocean-atmosphere system. After briefly analysing its variability, its ability in predicting the oceanic flow generated by the coupled system is investigated. Different phases in the error dynamics are found: for short lead times, an initial overdispersion of the ensemble forecast is present while the ensemble mean follows a dynamics reminiscent of the combined amplification of initial condition and model errors for deterministic systems; for longer lead times, a reliable diffusive ensemble spread is observed. These different phases are also found for ensemble-oriented skill measures like the Brier score and the rank histogram. The implications of these features on building stochastic models are then briefly discussed.
Validation of a RANS transition model using a high-order weighted compact nonlinear scheme
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.
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.
Regression model for tuning the PID controller with fractional order time delay system
S.P. Agnihotri; Laxman Madhavrao Waghmare
2014-01-01
In this paper a regression model based for tuning proportional integral derivative (PID) controller with fractional order time delay system is proposed. The novelty of this paper is that tuning parameters of the fractional order time delay system are optimally predicted using the regression model. In the proposed method, the output parameters of the fractional order system are used to derive the regression function. Here, the regression model depends on the weights of the exponential function...
Energy Technology Data Exchange (ETDEWEB)
Napier, Bruce A.; Krupka, Kenneth M.; Fellows, Robert J.; Cataldo, Dominic A.; Valenta, Michelle M.; Gilmore, Tyler J.
2004-12-02
This Annual Progress Report describes the work performed and summarizes some of the key observations to date on the U.S. Nuclear Regulatory Commission’s project Assessment of Food Chain Pathway Parameters in Biosphere Models, which was established to assess and evaluate a number of key parameters used in the food-chain models used in performance assessments of radioactive waste disposal facilities. Section 2 of this report describes activities undertaken to collect samples of soils from three regions of the United States, the Southeast, Northwest, and Southwest, and perform analyses to characterize their physical and chemical properties. Section 3 summarizes information gathered regarding agricultural practices and common and unusual crops grown in each of these three areas. Section 4 describes progress in studying radionuclide uptake in several representative crops from the three soil types in controlled laboratory conditions. Section 5 describes a range of international coordination activities undertaken by Project staff in order to support the underlying data needs of the Project. Section 6 provides a very brief summary of the status of the GENII Version 2 computer program, which is a “client” of the types of data being generated by the Project, and for which the Project will be providing training to the US NRC staff in the coming Fiscal Year. Several appendices provide additional supporting information.
Ma, Lu; Wang, Guan; Yan, Xuedong; Weng, Jinxian
2016-04-01
Debates on the ordering patterns of crash injury severity are ongoing in the literature. Models without proper econometrical structures for accommodating the complex ordering patterns of injury severity could result in biased estimations and misinterpretations of factors. This study proposes a hybrid finite mixture (HFM) model aiming to capture heterogeneous ordering patterns of driver injury severity while enhancing modeling flexibility. It attempts to probabilistically partition samples into two groups in which one group represents an unordered/nominal data-generating process while the other represents an ordered data-generating process. Conceptually, the newly developed model offers flexible coefficient settings for mining additional information from crash data, and more importantly it allows the coexistence of multiple ordering patterns for the dependent variable. A thorough modeling performance comparison is conducted between the HFM model, and the multinomial logit (MNL), ordered logit (OL), finite mixture multinomial logit (FMMNL) and finite mixture ordered logit (FMOL) models. According to the empirical results, the HFM model presents a strong ability to extract information from the data, and more importantly to uncover heterogeneous ordering relationships between factors and driver injury severity. In addition, the estimated weight parameter associated with the MNL component in the HFM model is greater than the one associated with the OL component, which indicates a larger likelihood of the unordered pattern than the ordered pattern for driver injury severity.
Bayesian Modeling of ChIP-chip Data Through a High-Order Ising Model
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.
Van Enter, A C D
2003-01-01
We consider various sufficiently nonlinear sigma models for nematic ordering of RP^{N-1} type and of lattice gauge type with continous symmetries. We rigorously show that they exhibit a first-order transition in the temperature. The result holds in dimension 2 or more for the RP{N-1} models and in dimension 3 or more for the lattice gauge models. In the two-dimensional case our results clarify and solve a recent controversy about the possibilty of such transitions. For lattice gauge models our methods provide the first prof of a first-order transition in a model with a continous gauge symmetry.
Directory of Open Access Journals (Sweden)
Yi Xu
2013-01-01
Full Text Available We propose a fourth-order total bounded variation regularization model which could reduce undesirable effects effectively. Based on this model, we introduce an improved split Bregman iteration algorithm to obtain the optimum solution. The convergence property of our algorithm is provided. Numerical experiments show the more excellent visual quality of the proposed model compared with the second-order total bounded variation model which is proposed by Liu and Huang (2010.
A Bit Progress on Word—Based Language Model
Institute of Scientific and Technical Information of China (English)
陈勇; 陈国评
2003-01-01
A good language model is essential to a postprocessing algorithm for recognition systems. In the past, researchers have pre-sented various language models, such as character based language models, word based language model, syntactical rules :language mod-el, hybrid models, etc. The word N-gram model is by far an effective and efficient model, but one has to address the problem of data sparseness in establishing the model. Katz and Kneser et al. respectively presented effective remedies to solve this challenging prob-lem. In this study, we proposed an improvement to their methods by incorporating Chinese language-specific information or Chinese word class information into the system.
Advances of Model Order Reduction Research in Large-scale System Simulation
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Model Order Reduction (MOR) plays more and more imp or tant role in complex system simulation, design and control recently. For example , for the large-size space structures, VLSI and MEMS (Micro-ElectroMechanical Systems) etc., in order to shorten the development cost, increase the system co ntrolling accuracy and reduce the complexity of controllers, the reduced order model must be constructed. Even in Virtual Reality (VR), the simulation and d isplay must be in real-time, the model order must be red...
Basic principles and aims of model order reduction in compliant mechanisms
Directory of Open Access Journals (Sweden)
M. Rösner
2011-10-01
Full Text Available Model order reduction appears to be beneficial for the synthesis and simulation of compliant mechanisms due to computational costs. Model order reduction is an established method in many technical fields for the approximation of large-scale linear time-invariant dynamical systems described by ordinary differential equations. Based on system theory, underlying representations of the dynamical system are introduced from which the general reduced order model is derived by projection. During the last years, numerous new procedures were published and investigated appropriate to simulation, optimization and control. Singular value decomposition, condensation-based and Krylov subspace methods representing three order reduction methods are reviewed and their advantages and disadvantages are outlined in this paper. The convenience of applying model order reduction in compliant mechanisms is quoted. Moreover, the requested attributes for order reduction as a future research direction meeting the characteristics of compliant mechanisms are commented.
Ranatunga, Vipul; Bednarcyk, Brett A.; Arnold, Steven M.
2010-01-01
A method for performing progressive damage modeling in composite materials and structures based on continuum level interfacial displacement discontinuities is presented. The proposed method enables the exponential evolution of the interfacial compliance, resulting in unloading of the tractions at the interface after delamination or failure occurs. In this paper, the proposed continuum displacement discontinuity model has been used to simulate failure within both isotropic and orthotropic materials efficiently and to explore the possibility of predicting the crack path, therein. Simulation results obtained from Mode-I and Mode-II fracture compare the proposed approach with the cohesive element approach and Virtual Crack Closure Techniques (VCCT) available within the ABAQUS (ABAQUS, Inc.) finite element software. Furthermore, an eccentrically loaded 3-point bend test has been simulated with the displacement discontinuity model, and the resulting crack path prediction has been compared with a prediction based on the extended finite element model (XFEM) approach.
Higgs boson mass in the Standard Model at two-loop order and beyond
Energy Technology Data Exchange (ETDEWEB)
Martin, Stephen P. [Northern Illinois U.; Robertson, David G. [Otterbein Coll.
2014-10-23
We calculate the mass of the Higgs boson in the standard model in terms of the underlying Lagrangian parameters at complete 2-loop order with leading 3-loop corrections. A computer program implementing the results is provided. The program also computes and minimizes the standard model effective potential in Landau gauge at 2-loop order with leading 3-loop corrections.
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.
BAYESIAN PARAMETER ESTIMATION IN A MIXED-ORDER MODEL OF BOD DECAY. (U915590)
We describe a generalized version of the BOD decay model in which the reaction is allowed to assume an order other than one. This is accomplished by making the exponent on BOD concentration a free parameter to be determined by the data. This "mixed-order" model may be ...
Advanced Modeling, Simulation and Analysis (AMSA) Capability Roadmap Progress Review
Antonsson, Erik; Gombosi, Tamas
2005-01-01
Contents include the following: NASA capability roadmap activity. Advanced modeling, simulation, and analysis overview. Scientific modeling and simulation. Operations modeling. Multi-special sensing (UV-gamma). System integration. M and S Environments and Infrastructure.
Model-based Prognostics with Concurrent Damage Progression Processes
National Aeronautics and Space Administration — Model-based prognostics approaches rely on physics-based models that describe the behavior of systems and their components. These models must account for the several...
Necessary and Sufficient Conditions on Partial Orders for Modeling Concurrent Computations
Chauhan, Himanshu; Vijay K Garg
2014-01-01
Partial orders are used extensively for modeling and analyzing concurrent computations. In this paper, we define two properties of partially ordered sets: width-extensibility and interleaving-consistency, and show that a partial order can be a valid state based model: (1) of some synchronous concurrent computation iff it is width-extensible, and (2) of some asynchronous concurrent computation iff it is width-extensible and interleaving-consistent. We also show a duality between the event base...
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......-frequency non-minimum phase zeros. To correctly predict the non-minimum phase zeros, it is shown to be essential to include lateral tower and blade flap degrees of freedom. The thesis describes and analyzes various methods to design low-order aeroelastic models of wind turbines. Low-order models are designed...
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.
Discrete Methods Based on First Order Reversal Curves to Identify Preisach Model of Smart Materials
Institute of Scientific and Technical Information of China (English)
LI Fan; ZHAO Jian-hui
2007-01-01
Preisach model is widely used in modeling of smart materials. Although first order reversal curves (FORCs) have often found applications in the fields of physics and geology, they are able to serve to identify Preisach model. In order to clarify the relationship between the Preisach model and the first order reversal curves, this paper is directed towards: (1) giving the reason a first order reversal curve is introduced; (2) presenting, for identifying Preisach model, two discrete methods, which are analytically based on first order reversal curves. Herein also is indicated the solution's uniqueness of these two identifying methods. At last, the validity of these two methods is verified by simulating a real smart actuator both methods have been applied to.
Mean-value second-order uncertainty analysis method: application to water quality modelling
Mailhot, Alain; Villeneuve, Jean-Pierre
Uncertainty analysis in hydrology and water quality modelling is an important issue. Various methods have been proposed to estimate uncertainties on model results based on given uncertainties on model parameters. Among these methods, the mean-value first-order second-moment (MFOSM) method and the advanced mean-value first-order second-moment (AFOSM) method are the most common ones. This paper presents a method based on a second-order approximation of a model output function. The application of this method requires the estimation of first- and second-order derivatives at a mean-value point in the parameter space. Application to a Streeter-Phelps prototype model is presented. Uncertainties on two and six parameters are considered. Exceedance probabilities (EP) of dissolved oxygen concentrations are obtained and compared with EP computed using Monte Carlo, AFOSM and MFOSM methods. These results show that the mean-value second-order method leads to better estimates of EP.
Ramesh, K; Nirmalkumar, A; Gurusamy, G
2010-01-01
In this paper, design of current controller for a two quadrant DC motor drive was proposed with the help of model order reduction technique. The calculation of current controller gain with some approximations in the conventional design process is replaced by proposed model order reduction method. The model order reduction technique proposed in this paper gives the better controller gain value for the DC motor drive. The proposed model order reduction method is a mixed method, where the numerator polynomial of reduced order model is obtained by using stability equation method and the denominator polynomial is obtained by using some approximation technique preceded in this paper. The designed controllers responses were simulated with the help of MATLAB to show the validity of the proposed method.
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.
Steady progression of osteoarthritic features in the canine groove model
Marijnissen, A.C.A.; Roermund, P.M. van; Verzijl, N.; Tekoppele, J.M.; Bijlsma, J.W.J.; Lafeber, F.P.J.G.
2002-01-01
Objective: Recently we described a canine model of osteoarthritis (OA), the groove model with features of OA at 10 weeks after induction, identical to those seen in the canine anterior cruciate ligament transection (ACLT) model. This new model depends on cartilage damage accompanied by transient int
Steady progression of osteoarthritic features in the canine groove model
Marijnissen, A.C.A.; Roermund, P.M. van; Verzijl, N.; Tekoppele, J.M.; Bijlsma, J.W.J.; Lafeber, F.P.J.G.
2002-01-01
Objective: Recently we described a canine model of osteoarthritis (OA), the groove model with features of OA at 10 weeks after induction, identical to those seen in the canine anterior cruciate ligament transection (ACLT) model. This new model depends on cartilage damage accompanied by transient int
West, Patti; Rutstein, Daisy Wise; Mislevy, Robert J.; Liu, Junhui; Choi, Younyoung; Levy, Roy; Crawford, Aaron; DiCerbo, Kristen E.; Chappel, Kristina; Behrens, John T.
2010-01-01
A major issue in the study of learning progressions (LPs) is linking student performance on assessment tasks to the progressions. This report describes the challenges faced in making this linkage using Bayesian networks to model LPs in the field of computer networking. The ideas are illustrated with exemplar Bayesian networks built on Cisco…
Progress in Hadronic Physics Modelling in Geant4
Energy Technology Data Exchange (ETDEWEB)
Apostolakis, John; /CERN; Folger, Gunter; /CERN; Grichine, Vladimir; /CERN; Heikkinen, Aatos; /Helsinki Inst. of Phys.; Howard, Alexander; /CERN; Ivanchenko, Vladimir; /CERN; Kaitaniemi, Pekka; /Helsinki Inst. of Phys.; Koi, Tatsumi; /SLAC; Kosov, Mikhail; /CERN /Moscow, ITEP; Quesada, Jose Manuel; /Seville U.; Ribon, Alberto; /CERN; Uzhinsky, Vladimir; /CERN; Wright, Dennis; /SLAC
2011-11-28
Geant4 offers a set of models to simulate hadronic showers in calorimeters. Recent improvements to several models relevant to the modelling of hadronic showers are discussed. These include improved cross sections, a revision of the FTF model, the addition of quasi-elastic scattering to the QGS model, and enhancements in the nuclear precompound and de-excitation models. The validation of physics models against thin target experiments has been extended especially in the energy region 10 GeV and below. Examples of new validation results are shown.
Index-aware model order reduction methods applications to differential-algebraic equations
Banagaaya, N; Schilders, W H A
2016-01-01
The main aim of this book is to discuss model order reduction (MOR) methods for differential-algebraic equations (DAEs) with linear coefficients that make use of splitting techniques before applying model order reduction. The splitting produces a system of ordinary differential equations (ODE) and a system of algebraic equations, which are then reduced separately. For the reduction of the ODE system, conventional MOR methods can be used, whereas for the reduction of the algebraic systems new methods are discussed. The discussion focuses on the index-aware model order reduction method (IMOR) and its variations, methods for which the so-called index of the original model is automatically preserved after reduction.
Innovation in Academic Progression: Progress of the New Mexico Nursing Education Consortium Model.
Landen, Jenny; Evans-Prior, Diane; Dakin, Becky; Liesveld, Judy
The Institute of Medicine (IOM) challenged nursing education programs to increase the proportion of nurses with a baccalaureate degree in nursing to 80 percent by 2020. All 18 state-funded prelicensure nursing programs in New Mexico joined forces to create the New Mexico Nursing Education Consortium (NMNEC). NMNEC is a model of collaboration with a statewide common curriculum that provides seamless transferability for students between schools while offering the BSN on community college campuses. Over three years, university partnerships with community colleges increased prelicensure BSN seats by 77 percent. This article describes the NMNEC model, challenges and opportunities associated with implementation, current program outcomes, and factors that have contributed to NMNEC's success. Also discussed are future steps for sustainability and growth as NMNEC continues in its commitment to meeting the IOM challenge.
Developing a Learning Progression for Number Sense Based on the Rule Space Model in China
Chen, Fu; Yan, Yue; Xin, Tao
2017-01-01
The current study focuses on developing the learning progression of number sense for primary school students, and it applies a cognitive diagnostic model, the rule space model, to data analysis. The rule space model analysis firstly extracted nine cognitive attributes and their hierarchy model from the analysis of previous research and the…
Generating dynamic higher-order Markov models in web usage mining
Borges, J; Levene, Mark
2005-01-01
Markov models have been widely used for modelling users’ web navigation behaviour. In previous work we have presented a dynamic clustering-based Markov model that accurately represents second-order transition probabilities given by a collection of navigation sessions. Herein, we propose a generalisation of the method that takes into account higher-order conditional probabilities. The method makes use of the state cloning concept together with a clustering technique to separate the navigation ...
Improved Nonlinear Model of a Second-Order Charge-Pump Pll
Gillespie, Diarmaid; Kennedy, Michael Peter; Kolumbán, Géza
An improved model of a second-order Charge-Pump Phase-Locked Loop (CP-PLL) is proposed. An event-driven second-order CP-PLL o-model is further developed from that described by Hedayat [1]. This model is made practical by taking account of VCO overload. Transient simulations are shown which illustrate the nature of phase-locking.
First Versus Second Order Latent Growth Curve Models: Some Insights From Latent State-Trait Theory
Geiser, Christian; Keller, Brian; Lockhart, Ginger
2013-01-01
First order latent growth curve models (FGMs) estimate change based on a single observed variable and are widely used in longitudinal research. Despite significant advantages, second order latent growth curve models (SGMs), which use multiple indicators, are rarely used in practice, and not all aspects of these models are widely understood. In this article, our goal is to contribute to a deeper understanding of theoretical and practical differences between FGMs and SGMs. We define the latent ...
Comments on the present state of second-order closure models for incompressible flows
Speziale, Charles G.
1992-01-01
Second-order closure models account for history and nonlocal effects of the mean velocity gradients on the Reynolds stress tensor. Turbulent flows involving body forces or curvature, Reynolds stress relaxational effects, and counter-gradient transport are usually better described. The topics are presented in viewgraph form and include: (1) the Reynolds stress transport equation; (2) issues in second-order closure modeling; and (3) near wall models.
Glesener, G. B.; Vican, L.
2015-12-01
Physical analog models and demonstrations can be effective educational tools for helping instructors teach abstract concepts in the Earth, planetary, and space sciences. Reducing the learning challenges for students using physical analog models and demonstrations, however, can often increase instructors' workload and budget because the cost and time needed to produce and maintain such curriculum materials is substantial. First, this presentation describes a working model for the Modeling and Educational Demonstrations Laboratory Curriculum Materials Center (MEDL-CMC) to support instructors' use of physical analog models and demonstrations in the science classroom. The working model is based on a combination of instructional resource models developed by the Association of College & Research Libraries and by the Physics Instructional Resource Association. The MEDL-CMC aims to make the curriculum materials available for all science courses and outreach programs within the institution where the MEDL-CMC resides. The sustainability and value of the MEDL-CMC comes from its ability to provide and maintain a variety of physical analog models and demonstrations in a wide range of science disciplines. Second, the presentation then reports on the development, progress, and future of the MEDL-CMC at the University of California Los Angeles (UCLA). Development of the UCLA MEDL-CMC was funded by a grant from UCLA's Office of Instructional Development and is supported by the Department of Earth, Planetary, and Space Sciences. Other UCLA science departments have recently shown interest in the UCLA MEDL-CMC services, and therefore, preparations are currently underway to increase our capacity for providing interdepartmental service. The presentation concludes with recommendations and suggestions for other institutions that wish to start their own MEDL-CMC in order to increase educational effectiveness and decrease instructor workload. We welcome an interuniversity collaboration to
The confluence model: birth order as a within-family or between-family dynamic?
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.
Energy Technology Data Exchange (ETDEWEB)
Zheng Yongai, E-mail: zhengyongai@163.co [Department of Computer, Yangzhou University, Yangzhou, 225009 (China); Nian Yibei [School of Energy and Power Engineering, Yangzhou University, Yangzhou, 225009 (China); Wang Dejin [Department of Computer, Yangzhou University, Yangzhou, 225009 (China)
2010-12-01
In this Letter, a kind of novel model, called the generalized Takagi-Sugeno (T-S) fuzzy model, is first developed by extending the conventional T-S fuzzy model. Then, a simple but efficient method to control fractional order chaotic systems is proposed using the generalized T-S fuzzy model and adaptive adjustment mechanism (AAM). Sufficient conditions are derived to guarantee chaos control from the stability criterion of linear fractional order systems. The proposed approach offers a systematic design procedure for stabilizing a large class of fractional order chaotic systems from the literature about chaos research. The effectiveness of the approach is tested on fractional order Roessler system and fractional order Lorenz system.
Multiple Damage Progression Paths in Model-based Prognostics
National Aeronautics and Space Administration — Model-based prognostics approaches employ do- main knowledge about a system, its components, and how they fail through the use of physics-based models. Compo- nent...
A seventh-order model for dynamic response of an electro-hydraulic servo valve
Institute of Scientific and Technical Information of China (English)
Liu Changhai; Jiang Hongzhou
2014-01-01
In this paper, taking two degrees of freedom on the armature–flapper assembly into account, a seventh-order model is deduced and proposed for the dynamic response of a two-stage electro-hydraulic servo valve from nonlinear equations. These deductions are based on fundamental laws of electromagnetism, fluid, and general mechanics. The coefficients of the proposed seventh-order model are derived in terms of servo valve physical parameters and fluid properties explicitly. For validating the results of the proposed model, an AMESim simulation model based on physical laws and the existing low-order models validated by other researchers through experiments are used to compare with the seventh-order model. The results show that the seventh-order model can reflect the physical behavior of the servo valve more explicitly than the existing low-order models and it could provide guidance more easily for a linear control design approach and sensitivity analysis than the AMESim simulation model.
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.
Reduced density matrices and topological order in a quantum dimer model
Energy Technology Data Exchange (ETDEWEB)
Furukawa, Shunsuke [Laboratoire de Physique Theorique de la Matiere Condensee, UMR 7600 of CNRS, Universite P et M Curie, case 121, 4 Place Jussieu, 75252 Paris Cedex (France); Misguich, Gregoire [Service de Physique Theorique, CEA Saclay, 91191 Gif-sur-Yvette Cedex (France); Oshikawa, Masaki [Institute for Solid State Physics, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa 277-8581 (Japan)
2007-04-11
Resonating valence bond (RVB) liquids in two dimensions are believed to exhibit topological order and to admit no local order parameter of any kind. This is a defining property of 'liquids', but it has been confirmed explicitly only in a few exactly solvable models. In this paper, we investigate the quantum dimer model on the triangular lattice. This possesses an RVB-type liquid phase, however, for which the absence of a local order parameter has not been proved. We examine the question numerically with a measure based on reduced density matrices. We find a scaling of the measure which strongly supports the absence of any local order parameter.
Multidisciplinary model-based-engineering for laser weapon systems: recent progress
Coy, Steve; Panthaki, Malcolm
2013-09-01
We are working to develop a comprehensive, integrated software framework and toolset to support model-based engineering (MBE) of laser weapons systems. MBE has been identified by the Office of the Director, Defense Science and Engineering as one of four potentially "game-changing" technologies that could bring about revolutionary advances across the entire DoD research and development and procurement cycle. To be effective, however, MBE requires robust underlying modeling and simulation technologies capable of modeling all the pertinent systems, subsystems, components, effects, and interactions at any level of fidelity that may be required in order to support crucial design decisions at any point in the system development lifecycle. Very often the greatest technical challenges are posed by systems involving interactions that cut across two or more distinct scientific or engineering domains; even in cases where there are excellent tools available for modeling each individual domain, generally none of these domain-specific tools can be used to model the cross-domain interactions. In the case of laser weapons systems R&D these tools need to be able to support modeling of systems involving combined interactions among structures, thermal, and optical effects, including both ray optics and wave optics, controls, atmospheric effects, target interaction, computational fluid dynamics, and spatiotemporal interactions between lasing light and the laser gain medium. To address this problem we are working to extend Comet™, to add the addition modeling and simulation capabilities required for this particular application area. In this paper we will describe our progress to date.
Progress in modeling of fluid flows in crystal growth processes
Institute of Scientific and Technical Information of China (English)
Qisheng Chen; Yanni Jiang; Junyi Yan; Ming Qin
2008-01-01
Modeling of fluid flows in crystal growth processes has become an important research area in theoretical and applied mechanics.Most crystal growth processes involve fluid flows,such as flows in the melt,solution or vapor.Theoretical modeling has played an important role in developing technologies used for growing semiconductor crystals for high performance electronic and optoelectronic devices.The application of devices requires large diameter crystals with a high degree of crystallographic perfection,low defect density and uniform dopant distribution.In this article,the flow models developed in modeling of the crystal growth processes such as Czochralski,ammono-thermal and physical vapor transport methods are reviewed.In the Czochralski growth modeling,the flow models for thermocapillary flow,turbulent flow and MHD flow have been developed.In the ammonothermal growth modeling,the buoyancy and porous media flow models have been developed based on a single-domain and continuum approach for the composite fluid-porous layer systems.In the physical vapor transport growth modeling,the Stefan flow model has been proposed based on the flow-kinetics theory for the vapor growth.In addition,perspectives for future studies on crystal growth modeling are proposed.
Order Reduction of the Radiative Heat Transfer Model for the Simulation of Plasma Arcs
Fagiano, Lorenzo
2015-01-01
An approach to derive low-complexity models describing thermal radiation for the sake of simulating the behavior of electric arcs in switchgear systems is presented. The idea is to approximate the (high dimensional) full-order equations, modeling the propagation of the radiated intensity in space, with a model of much lower dimension, whose parameters are identified by means of nonlinear system identification techniques. The low-order model preserves the main structural aspects of the full-order one, and its parameters can be straightforwardly used in arc simulation tools based on computational fluid dynamics. In particular, the model parameters can be used together with the common approaches to resolve radiation in magnetohydrodynamic simulations, including the discrete-ordinate method, the P-N methods and photohydrodynamics. The proposed order reduction approach is able to systematically compute the partitioning of the electromagnetic spectrum in frequency bands, and the related absorption coefficients, tha...
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.
On the relation between hydrogen bonds, tetrahedral order and molecular mobility in model water
Pereyra, R G; Malaspina, D C; Carignano, M A
2013-01-01
We studied by molecular dynamics simulations the relation existing between the lifetime of hydrogen bonds, the tetrahedral order and the diffusion coefficient of model water. We tested four different models: SPC/E, TIP4P-Ew, TIP5P-Ew and Six-site, these last two having sites explicitly resembling the water lone pairs. While all the models perform reasonably well at ambient conditions, their behavior is significantly different for temperatures below 270 K. The models with explicit lone-pairs have a longer hydrogen bond lifetime, a better tetrahedral order and a smaller diffusion coefficient than the models without them.
On the equivalence between standard and sequentially ordered hidden Markov models
Chopin, Nicolas
2012-01-01
Chopin (2007) introduced a sequentially ordered hidden Markov model, for which states are ordered according to their order of appearance, and claimed that such a model is a re-parametrisation of a standard Markov model. This note gives a formal proof that this equivalence holds in Bayesian terms, as both formulations generate equivalent posterior distributions, but does not hold in Frequentist terms, as both formulations generate incompatible likelihood functions. Perhaps surprisingly, this shows that Bayesian re-parametrisation and Frequentist re-parametrisation are not identical concepts.
Beethoven, a mouse model for dominant, progressive hearing loss DFNA36.
Vreugde, Sarah; Erven, Alexandra; Kros, Corné J; Marcotti, Walter; Fuchs, Helmut; Kurima, Kiyoto; Wilcox, Edward R; Friedman, Thomas B; Griffith, Andrew J; Balling, Rudi; Hrabé De Angelis, Martin; Avraham, Karen B; Steel, Karen P
2002-03-01
Despite recent progress in identifying genes underlying deafness, there are still relatively few mouse models of specific forms of human deafness. Here we describe the phenotype of the Beethoven (Bth) mouse mutant and a missense mutation in Tmc1 (transmembrane cochlear-expressed gene 1). Progressive hearing loss (DFNA36) and profound congenital deafness (DFNB7/B11) are caused by dominant and recessive mutations of the human ortholog, TMC1 (ref. 1), for which Bth and deafness (dn) are mouse models, respectively.
Price, Derek A; Swanson, William H; Horner, Douglas G
2017-07-01
different approaches for testing the hypothesis both gave a negative result. For all seven ganglion cell models, rates of ganglion cell loss were highly affected by fluctuations in height of the hill of vision. Methods for reducing effects of between-visit variability are needed in order to assess progression by relating perimetric sensitivities and ganglion cell numbers. © 2017 The Authors. Ophthalmic and Physiological Optics published by John Wiley & Sons Ltd on behalf of College of Optometrists.
Tuning algorithms for fractional order internal model controllers for time delay processes
Muresan, Cristina I.; Dutta, Abhishek; Dulf, Eva H.; Pinar, Zehra; Maxim, Anca; Ionescu, Clara M.
2016-03-01
This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.
Economic Order Quantity Model with Two Levels of Delayed Payment and Bad Debt
Directory of Open Access Journals (Sweden)
Qin Juanjuan
2012-08-01
Full Text Available The purpose of this study is to determine the optimal retailer’s replenishment policies considering the customers’ bad debt and delayed payment in the three-stage supply chain with the dominant retailer. The effect of bad debt is analyzed on the interest earned and interest charged to build the models of the retailer’s decision in two cases. By analyzing the model, the retailer’s optimal replenishment time and the optimal order quantity are obtained. Furthermore, analyze the effect of parameters on the retailer’s optimal order policies. Finally, the numerical analysis is presented to demonstrate the conclusions. The results show that the delayed payment offered by the manufacturer becomes large, the retailer's optimal order cycle and the optimal order quantity increases or remains the same; When the delayed payment time offered by the retailer decreases, the retailer's optimal order cycle and the optimal order quantity increases or remains the same. When the fixed ordering cost is reduced, the retailer's optimal order cycle and the optimal order quantity decreases or remains the same. When the charged interest is greater than the earned interest, with the bad debt rate increasing, the retailer's optimal order cycle and optimal order quantity is converged to a certain value.
Research progress on animal models of Alzheimer's disease
Directory of Open Access Journals (Sweden)
Wen DONG
2015-08-01
Full Text Available Alzheimer's disease (AD is a degenerative disease of the central nervous system, and its pathogenesis is complex. Animal models play an important role in study on pathogenesis and treatment of AD. This paper summarized methods of building models, observation on animal models and evaluation index in recent years, so as to provide related evidence for basic and clinical research in future. DOI: 10.3969/j.issn.1672-6731.2015.08.003
Subsymmetry and asymmetry models for multiway square contingency tables with ordered categories
Directory of Open Access Journals (Sweden)
Aktaş Serpil
2016-01-01
Full Text Available This paper suggests several models that describe the symmetry and asymmetry structure of each subdimension for the multiway square contingency table with ordered categories. A classical three-way categorical example is examined to illustrate the model results. These models analyze the subsymmetric and asymetric structure of the table.
Recent progress in battery models for hybrid wind power systems
Energy Technology Data Exchange (ETDEWEB)
Manwell, J.F.; McGowan, J.G.; Baring-Gould, I.; Stein, W. [Univ. of Massachusetts, Amherst, MA (United States)
1995-12-31
This paper summarizes the latest University of Massachusetts work on the analytical modeling and experimental testing of battery component models for hybrid power systems. An extension of the Kinetic Battery Model (KiBaM), developed at the University of Massachusetts is presented. The original model was based on a combination of phenomenological and physical considerations. As described in this paper, the modified KiBaM can now model the sharp increase in voltage near the end of charging, and the sharp drop in voltage when the battery is nearly empty. This model may readily be coupled with a DC load or charging source (such as a DC wind turbine or photovoltaic panels) to determine the corresponding DC bus voltage. For example, it is now an integral part of the DC bus section of the University of Massachusetts HYBRID simulation models. The paper describes the development of the extensions to the KiBaM model and the method of determining the constants from test data. On the experimental/applications side, it includes an illustration of how the constants are obtained from representative data (using a specially developed testing apparatus), and an example of how the model can be used.
The fractional-order modeling and synchronization of electrically coupled neuron systems
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.
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.
Numerical Models of Higher-Order Boussinesq Equations and Comparisons with Laboratory Measurement
Institute of Scientific and Technical Information of China (English)
邹志利; 张晓莉
2001-01-01
Nonlinear water wave propagation passing a submerged shelf is studied experimentally and numerically. The applicability of two different wave propagation models has been investigated. One is higher-order Boussinesq equationsderived by Zou (1999) and the other is the classic Boussinesq equations. Physical experiments are conducted, three differ-ent front slopes (1:10, 1:5 and 1:2) of the shelf are set up in the experiment and their effects on wave propagation are in-vestigated. Comparisons of numerical results with test data are made, the model of higher-order Boussinesq equationsagrees much better with the measurements than the model of the classical Boussinesq equations. The results show thatthe higher-order Boussinesq equations can also be applied to the steeper slope case although the mild slope assumption isemployed in the derivation of the higher order terms of higher order Boussinesq equations.
Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments
Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh
2017-05-01
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.
New second order Mumford-Shah model based on Γ-convergence approximation for image processing
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.
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.
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.
First-order phase transition in $1d$ Potts model with long-range interactions
Uzelac, K.; Glumac, Z.
1998-01-01
The first-order phase transition in the one-dimensional $q$-state Potts model with long-range interactions decaying with distance as $1/r^{1+\\sigma}$ has been studied by Monte Carlo numerical simulations for $0 2$. On the basis of finite-size scaling analysis of interface free energy $\\Delta F_L$, specific heat and Binder's fourth order cumulant, we obtain the first-order transition which occurs for $\\sigma$ below a threshold value $\\sigma_c(q)$.
A Reduced-Order Model for Evaluating the Dynamic Response of Multilayer Plates to Impulsive Loads
2016-04-12
distribution is unlimited SAE INTERNATIONAL • Motivation • Technical Approach • Reduced Order Model (ROM) • Validation – by Spectrum Finite Element ...also be paramount factors for Army vehicles in order for faster transport, greater fuel conservation, higher payload and higher mobility. • Develop...Matrix • The departure wave vectors ?̃?∗ and ?̃? contain same elements but in different order. It can be expressed in equivalence through a global
Images as drivers of progress in cardiac computational modelling.
Lamata, Pablo; Casero, Ramón; Carapella, Valentina; Niederer, Steve A; Bishop, Martin J; Schneider, Jürgen E; Kohl, Peter; Grau, Vicente
2014-08-01
Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.
Damage progression from impact in layered glass modeled with peridynamics
Bobaru, Florin; Ha, Youn; Hu, Wenke
2012-12-01
Dynamic fracture in brittle materials has been difficult to model and predict. Interfaces, such as those present in multi-layered glass systems, further complicate this problem. In this paper we use a simplified peridynamic model of a multi-layer glass system to simulate damage evolution under impact with a high-velocity projectile. The simulation results are compared with results from recently published experiments. Many of the damage morphologies reported in the experiments are captured by the peridynamic results. Some finer details seen in experiments and not replicated by the computational model due to limitations in available computational resources that limited the spatial resolution of the model, and to the simple contact conditions between the layers instead of the polyurethane bonding used in the experiments. The peridynamic model uncovers a fascinating time-evolution of damage and the dynamic interaction between the stress waves, propagating cracks, interfaces, and bending deformations, in three-dimensions.
A new fuzzy multi-objective higher order moment portfolio selection model for diversified portfolios
Yue, Wei; Wang, Yuping
2017-01-01
Due to the important effect of the higher order moments to portfolio returns, the aim of this paper is to make use of the third and fourth moments for fuzzy multi-objective portfolio selection model. Firstly, in order to overcome the low diversity of the obtained solution set and lead to corner solutions for the conventional higher moment portfolio selection models, a new entropy function based on Minkowski measure is proposed as a new objective function and a novel fuzzy multi-objective weighted possibilistic higher order moment portfolio model is presented. Secondly, to solve the proposed model efficiently, a new multi-objective evolutionary algorithm is designed. Thirdly, several portfolio performance evaluation techniques are used to evaluate the performance of the portfolio models. Finally, some experiments are conducted by using the data of Shanghai Stock Exchange and the results indicate the efficiency and effectiveness of the proposed model and algorithm.
Constructing set-valued fundamental diagrams from jamiton solutions in second order traffic models
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.
Teaching Higher Order Thinking in the Introductory MIS Course: A Model-Directed Approach
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…
Exact Sampling and Decoding in High-Order Hidden Markov Models
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 mod
A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means
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…
Teaching Higher Order Thinking in the Introductory MIS Course: A Model-Directed Approach
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…
van der Linden, Willem J.
1995-01-01
Dichotomous item response theory (IRT) models can be viewed as families of stochastically ordered distributions of responses to test items. This paper explores several properties of such distributiom. The focus is on the conditions under which stochastic order in families of conditional distribution
Novel Reduced Order in Time Models for Problems in Nonlinear Aeroelasticity Project
National Aeronautics and Space Administration — Research is proposed for the development and implementation of state of the art, reduced order models for problems in nonlinear aeroelasticity. Highly efficient and...
Fractional order Buck-Boost converter in CCM: modelling, analysis and simulations
Wang, Faqiang; Ma, Xikui
2014-12-01
In this paper, the modelling, analysis and the power electronics simulator (PSIM) simulations of the fractional order Buck-Boost converter operating in continuous conduction mode (CCM) operation are investigated. Based on the three-terminal switch device method, the average circuit model of the fractional order Buck-Boost converter is established, and the corresponding DC equivalent circuit model and AC small signal equivalent circuit model are presented. And then, the equilibrium point and the transfer functions are derived. It is found that the equilibrium point is not influenced by the inductor's or the capacitor's order, but both these orders are included in the derived transfer functions. Finally, the comparisons between the theoretical analysis and the PSIM simulations are given for confirmation.
Neel order in the two-dimensional S=1/2 Heisenberg Model
Löw, Ute
2007-01-01
The existence of Neel order in the S=1/2 Heisenberg model on the square lattice at T=0 is shown using inequalities set up by Kennedy, Lieb and Shastry in combination with high precision Quantum Monte Carlo data.
Equilibrium pricing in an order book environment: Case study for a spin model
Meudt, Frederik; Schmitt, Thilo A.; Schäfer, Rudi; Guhr, Thomas
2016-07-01
When modeling stock market dynamics, the price formation is often based on an equilibrium mechanism. In real stock exchanges, however, the price formation is governed by the order book. It is thus interesting to check if the resulting stylized facts of a model with equilibrium pricing change, remain the same or, more generally, are compatible with the order book environment. We tackle this issue in the framework of a case study by embedding the Bornholdt-Kaizoji-Fujiwara spin model into the order book dynamics. To this end, we use a recently developed agent based model that realistically incorporates the order book. We find realistic stylized facts. We conclude for the studied case that equilibrium pricing is not needed and that the corresponding assumption of a "fundamental" price may be abandoned.
Modeling Delays of Microwave Transistors and Transmission Lines by the 2nd Order Bessel Function
Directory of Open Access Journals (Sweden)
K. Ulovec
2007-04-01
Full Text Available At present, most of simulation programs can characterize gate delays of microwave transistors. However, the delay is mostly approximated by means of first-order differential equations. In the paper, a more accurate way is suggested which is based on an appropriate second-order differential equation. Concerning the transmission line delay, majority of the simulation programs use both Branin (for lossless lines and LCRG (for lossy lines models. However, the first causes extreme simulation times, and the second causes well-known spurious oscillations in the simulation results. In the paper, an unusual way for modeling the transmission line delay is defined, which is also based on the second-order Bessel function. The proposed model does not create the spurious oscillations and the simulation times are comparable with those obtained with the classical models. Properties of the implementation of the second-order Bessel function are demonstrated by analyses of both digital and analog microwave circuits.
Nonlinear AeroServoElastic Reduced Order Model for Active Structural Control Project
National Aeronautics and Space Administration — The overall goal of the proposed effort is to develop and demonstrate rigorous model order reduction (MOR) technologies to automatically generate fully coupled,...
Model Order and Identifiability of Non-Linear Biological Systems in Stable Oscillation.
Wigren, Torbjörn
2015-01-01
The paper presents a theoretical result that clarifies when it is at all possible to determine the nonlinear dynamic equations of a biological system in stable oscillation, from measured data. As it turns out the minimal order needed for this is dependent on the minimal dimension in which the stable orbit of the system does not intersect itself. This is illustrated with a simulated fourth order Hodgkin-Huxley spiking neuron model, which is identified using a non-linear second order differential equation model. The simulated result illustrates that the underlying higher order model of the spiking neuron cannot be uniquely determined given only the periodic measured data. The result of the paper is of general validity when the dynamics of biological systems in stable oscillation is identified, and illustrates the need to carefully address non-linear identifiability aspects when validating models based on periodic data.
The East model: recent results and new progresses
Faggionato, Alessandra; Roberto, Cyril; Toninelli, Cristina
2012-01-01
The East model is a particular one dimensional interacting particle system in which certain transitions are forbidden according to some constraints depending on the configuration of the system. As such it has received particular attention in the physics literature as a special case of a more general class of systems referred to as kinetically constrained models, which play a key role in explaining some features of the dynamics of glasses. In this paper we give an extensive overview of recent rigorous results concerning the equilibrium and non-equilibrium dynamics of the East model together with some new improvements.
Geant4 and beyond: recent progress in precision physics modeling
Batic, Matej; Han, Min Cheol; Hauf, Steffen; Hoff, Gabriela; Kim, Chan Hyeong; Kim, Han Sung; Kim, Sung Hun; Kuster, Markus; Pia, Maria Grazia; Saracco, Paolo; Weidenspointner, Georg
2014-01-01
This extended abstract briefly summarizes ongoing research activity on the evaluation and experimental validation of physics methods for photon and electron transport. The analysis includes physics models currently implemented in Geant4 as well as modeling methods used in other Monte Carlo codes, or not yet considered in general purpose Monte Carlo simulation systems. The validation of simulation models is performed with the support of rigorous statistical methods, which involve goodness-of-fit tests followed by categorical analysis. All results are quantitative, and are fully documented.
Simplification of high order polynomial calibration model for fringe projection profilometry
Yu, Liandong; Zhang, Wei; Li, Weishi; Pan, Chengliang; Xia, Haojie
2016-10-01
In fringe projection profilometry systems, high order polynomial calibration models can be employed to improve the accuracy. However, it is not stable to fit a high order polynomial model with least-squares algorithms. In this paper, a novel method is presented to analyze the significance of each polynomial term and simplify the high order polynomial calibration model. Term significance is evaluated by comparing the loading vector elements of the first few principal components which are obtained with the principal component analysis, and trivial terms are identified and neglected from the high order polynomial calibration model. As a result, the high order model is simplified with significant improvement of computation stability and little loss of reconstruction accuracy. An interesting finding is that some terms of 0 and 1st order, as well as some high order terms related to the image direction that is vertical to the phase change direction, are trivial terms for this specific problem. Experimental results are shown to validate of the proposed method.
Global gene expression profile progression in Gaucher disease mouse models
Directory of Open Access Journals (Sweden)
Zhang Wujuan
2011-01-01
Full Text Available Abstract Background Gaucher disease is caused by defective glucocerebrosidase activity and the consequent accumulation of glucosylceramide. The pathogenic pathways resulting from lipid laden macrophages (Gaucher cells in visceral organs and their abnormal functions are obscure. Results To elucidate this pathogenic pathway, developmental global gene expression analyses were conducted in distinct Gba1 point-mutated mice (V394L/V394L and D409 V/null. About 0.9 to 3% of genes had altered expression patterns (≥ ± 1.8 fold change, representing several categories, but particularly macrophage activation and immune response genes. Time course analyses (12 to 28 wk of INFγ-regulated pro-inflammatory (13 and IL-4-regulated anti-inflammatory (11 cytokine/mediator networks showed tissue differential profiles in the lung and liver of the Gba1 mutant mice, implying that the lipid-storage macrophages were not functionally inert. The time course alterations of the INFγ and IL-4 pathways were similar, but varied in degree in these tissues and with the Gba1 mutation. Conclusions Biochemical and pathological analyses demonstrated direct relationships between the degree of tissue glucosylceramides and the gene expression profile alterations. These analyses implicate IFNγ-regulated pro-inflammatory and IL-4-regulated anti-inflammatory networks in differential disease progression with implications for understanding the Gaucher disease course and pathophysiology.
Long range order in gauge theories. Deformed QCD as a toy model
Thomas, Evan
2012-01-01
We study a number of different ingredients, related to long range order observed in lattice QCD simulations, using a simple "deformed QCD" model. This model is a weakly coupled gauge theory, which however has all the relevant crucial elements allowing us to study difficult and nontrivial questions which are known to be present in real strongly coupled QCD. Essentially, we want to understand the physics of long range order in form of coherent low dimensional vacuum configurations observed in Monte Carlo lattice simulations.
Investigation of the Stability of POD-Galerkin Techniques for Reduced Order Model Development
2016-01-09
CFD solutions comparison of Case A at x/L = 0.5 for cases in Table 4. 12 The remaining three cases with multiple frequencies in the forcing function...Techniques for Reduced Order Model Development 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Huang, C...mitigate the stability issues encountered in developing a reduced order model (ROM) for combustion response to specified excitations using the Euler
Reduced-order modeling for cardiac electrophysiology. Application to parameter identification
Boulakia, Muriel; Gerbeau, Jean-Frédéric
2011-01-01
A reduced-order model based on Proper Orthogonal Decomposition (POD) is proposed for the bidomain equations of cardiac electrophysiology. Its accuracy is assessed through electrocardiograms in various configurations, including myocardium infarctions and long-time simulations. We show in particular that a restitution curve can efficiently be approximated by this approach. The reduced-order model is then used in an inverse problem solved by an evolutionary algorithm. Some attempts are presented to identify ionic parameters and infarction locations from synthetic ECGs.
Progress in Finite Element Modeling of the Lower Extremities
2015-06-01
as well as have a vision for the future. Modeling the human body is a challenging endeavor due to its geometric complexity, numerous interacting ...efforts and documents some major improvements to the lower leg model with a vision of the future in mind . We also introduce significant details regarding...variability matters in the context of predicting injury is an open research question. These challenges and the unknowns introduce numerous practical
Animal Models of Diabetic Neuropathy: Progress Since 1960s
Md. Shahidul Islam
2013-01-01
Diabetic or peripheral diabetic neuropathy (PDN) is one of the major complications among some other diabetic complications such as diabetic nephropathy, diabetic retinopathy, and diabetic cardiomyopathy. The use of animal models in the research of diabetes and diabetic complications is very common when rats and mice are most commonly used for many reasons. A numbers of animal models of diabetic and PDN have been developed in the last several decades such as streptozotocin-induced diabetic rat...
Dose-Response Modeling Under Simple Order Restrictions Using Bayesian Variable Selection Methods
Otava, Martin; Shkedy, Ziv; Lin, Dan; Goehlmann, Hinrich W. H.; Bijnens, Luc; Talloen, Willem; Kasim, Adetayo
2014-01-01
Bayesian modeling of dose–response data offers the possibility to establish the relationship between a clinical or a genomic response and increasing doses of a therapeutic compound and to determine the nature of the relationship wherever it exists. In this article, we focus on an order-restricted one-way ANOVA model which can be used to test the null hypothesis of no dose effect against an ordered alternative. Within the framework of the dose–response modeling, a model uncertainty can be addr...
Low order p-modes in a bipolytropic model of the Sun
Pinzon, G A
2001-01-01
Based on the Solar Standard Model we developed a solar model in hydrostatic equilibrium using two polytropes that describes both the "radiative" and "convective" zones of the solar interior. Then we apply small periodic and adiabatic perturbations on this bipolytropic model in order to obtain proper frequencies and proper functions. The frequencies obtained are in the "p-modes" range of low order l<20 which agrees with the observational data, particularly with the so called five minutes solar oscillations. Key Words: Solar Standard Model, Lane-Emden, Non Radial Oscillations, p-modes.
Performance of a reduced-order FSI model for flow-induced vocal fold vibration
Chang, Siyuan; Luo, Haoxiang; Luo's lab Team
2016-11-01
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 is often needed in procedures such as optimization and parameter estimation. In this work, we study the 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. 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. Supported by the NSF.
A model of serial order problems in fluent, stuttered and agrammatic speech
Howell, Peter
2007-01-01
Many models of speech production have attempted to explain dysfluent speech. Most models assume that the disruptions that occur when speech is dysfluent arise because the speakers make errors while planning an utterance. In this contribution, a model of the serial order of speech is described that does not make this assumption. It involves the coordination or ‘interlocking’ of linguistic planning and execution stages at the language–speech interface. The model is examined to determine whether...
A model of serial order problems in fluent, stuttered and agrammatic speech
Howell, P.
2007-01-01
Many models of speech production have attempted to explain dysfluent speech. Most models assume that the disruptions that occur when speech is dysfluent arise because the speakers make errors while planning an utterance. In this contribution, a model of the serial order of speech is described that does not make this assumption. It involves the coordination or 'interlocking' of linguistic planning and execution stages at the language-speech interface. The model is examined to determine whether...
Eighth-order phase-field-crystal model for two-dimensional crystallization
Jaatinen, A.; Ala-Nissila, T.
2010-01-01
We present a derivation of the recently proposed eighth order phase field crystal model [Jaatinen et al., Phys. Rev. E 80, 031602 (2009)] for the crystallization of a solid from an undercooled melt. The model is used to study the planar growth of a two dimensional hexagonal crystal, and the results are compared against similar results from dynamical density functional theory of Marconi and Tarazona, as well as other phase field crystal models. We find that among the phase field crystal models...
First-order formalism for twinlike models with several real scalar fields
Bazeia, D; Losano, L; Menezes, R
2014-01-01
We investigate the presence of twinlike models in theories described by several real scalar fields. We focus on the first-order formalism, and we show how to build distinct scalar field theories that support the same extended solution, with the same energy density and the very same linear stability. The results are valid for two distinct classes of generalized models, that include the standard model and cover a diversity of generalized models of current interest in high energy physics.
Progress in and prospects for fluvial flood modelling.
Wheater, H S
2002-07-15
Recent floods in the UK have raised public and political awareness of flood risk. There is an increasing recognition that flood management and land-use planning are linked, and that decision-support modelling tools are required to address issues of climate and land-use change for integrated catchment management. In this paper, the scientific context for fluvial flood modelling is discussed, current modelling capability is considered and research challenges are identified. Priorities include (i) appropriate representation of spatial precipitation, including scenarios of climate change; (ii) development of a national capability for continuous hydrological simulation of ungauged catchments; (iii) improved scientific understanding of impacts of agricultural land-use and land-management change, and the development of new modelling approaches to represent those impacts; (iv) improved representation of urban flooding, at both local and catchment scale; (v) appropriate parametrizations for hydraulic simulation of in-channel and flood-plain flows, assimilating available ground observations and remotely sensed data; and (vi) a flexible decision-support modelling framework, incorporating developments in computing, data availability, data assimilation and uncertainty analysis.
Role of Compaction Ratio in the Mathematical Model of Progressive Collapse
Beck, Charles M
2008-01-01
We derive a mathematical model of progressive collapse and examine role of compaction. Contrary to a previous result by Ba\\v{z}ant and Verdure, J. Engr. Mech. ASCE 133 (2006) 308, we find that compaction slows down the avalanche by effectively increasing the resistive force. We compare currently available estimates of the resistive force, that of Ba\\v{z}ant and Verdure (2006) corrected for compaction for World Trade Center (WTC) 2, and of Beck, www.arxiv.org:physics/0609105, for WTC 1 and 2. We concentrate on a damage wave propagating through the building before the avalanche that figures in both models: an implicit heat wave that reduces the resistive force of the building by 60% in Ba\\v{z}ant and Verdure (2006), or a wave of massive destruction that reduces the resistive force by 75% in Beck (2006). We show that the avalanche cannot supply the energy to the heat wave as this increases the resistive force by two orders of magnitude. We thus reaffirm the conclusion of Beck (2006) that the avalanche is initiat...
Algebraic Specifications, Higher-order Types and Set-theoretic Models
DEFF Research Database (Denmark)
Kirchner, Hélène; Mosses, Peter David
2001-01-01
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......, 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...
Doping driven metal-insulator transitions and charge orderings in the extended Hubbard model
Kapcia, K J; Capone, M; Amaricci, A
2016-01-01
We perform a thorough study of an extended Hubbard model featuring local and nearest-neighbor Coulomb repulsion. Using dynamical mean-field theory we investigated the zero temperature phase-diagram of this model as a function of the chemical doping. The interplay between local and non-local interaction drives a variety of phase-transitions connecting two distinct charge-ordered insulators, i.e., half-filled and quarter-filled, a charge-ordered metal and a Mott insulating phase. We characterize these transitions and the relative stability of the solutions and we show that the two interactions conspire to stabilize the quarter-filled charge ordered phase.
Towards a double-scaling limit for tensor models: probing sub-dominant orders
Kaminski, Wojciech; Ryan, James P
2013-01-01
The definition of a double-scaling limit represents an important goal in the development of tensor models. We take the first steps towards this goal by extracting and analysing the next-to-leading order contributions, in the 1/N expansion, for the IID tensor models. We show that the radius of convergence of the NLO series coincides with that of the leading order melonic sector. Meanwhile, the value of the susceptibility exponent at NLO is 3/2, signaling a departure from the leading order behaviour. Both pieces of information provide clues for a non-trivial double-scaling limit, for which we put forward some precise conjecture.
Progress in microscopic direct reaction modeling of nucleon induced reactions
Energy Technology Data Exchange (ETDEWEB)
Dupuis, M.; Bauge, E.; Hilaire, S.; Lechaftois, F.; Peru, S.; Pillet, N.; Robin, C. [CEA, DAM, DIF, Arpajon (France)
2015-12-15
A microscopic nuclear reaction model is applied to neutron elastic and direct inelastic scatterings, and pre-equilibrium reaction. The JLM folding model is used with nuclear structure information calculated within the quasi-particle random phase approximation implemented with the Gogny D1S interaction. The folding model for direct inelastic scattering is extended to include rearrangement corrections stemming from both isoscalar and isovector density variations occurring during a transition. The quality of the predicted (n,n), (n,n{sup '}), (n,xn) and (n,n{sup '}γ) cross sections, as well as the generality of the present microscopic approach, shows that it is a powerful tool that can help improving nuclear reactions data quality. Short- and long-term perspectives are drawn to extend the present approach to more systems, to include missing reactions mechanisms, and to consistently treat both structure and reaction problems. (orig.)
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.
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. PMID:25276851
Second-order model for free surface convection and interface reconstruction
Energy Technology Data Exchange (ETDEWEB)
Kim, Seong O.; Hwang, Young Dong; Kim, Young In; Chang, Moon Hee
1997-03-01
To improve the numerical analysis of free surface convection and its reconstruction, both first- and second-order algorithms are developed based on the volume of fraction method. Through the rearrangement of the surface cell and resetting of volume fraction, 16 possible cases of distribution of volume fraction in a cell block can be reduced to a single case. The methodology applied to the second-order model is to define the second-order linear curve having both face slopes as near to horizontal as possible while satisfying the cell`s defined volume fraction. The second-order method is compared with the FLAIR method and the first-order method through the simulation of the convection for various sizes of circular liquid shapes and solitary waves. For the small curvature of a free surface, e.g. circles with a large diameter, the linear method such as the FLAIR method and the first-order method shows relatively good predictions. However, for large curvature configurations, e.g. circles with a relatively small diameter or solitary waves, the linear approach shows large distortion of free surface. On the contrary, the second-order model always shows powerful prediction capabilities of free surface convection. Therefore, it is recommended that for the reconstruction and convection of free surface geometry with a large curvature, the second-order model should be used. (author). 21 refs., 1 tab., 21 figs.
Modeling NSCLC Progression: Recent Advances and Opportunities Available
Suleiman, Ahmed Abbas; Nogova, Lucia; Fuhr, Uwe, 1960-
2013-01-01
Non-small cell lung cancer (NSCLC) is one of the leading causes of death around the world with an estimated 5-year relative survival rate of 16% at diagnosis. Development of drugs treating NSCLC is not easy, and the success rate for an anticancer treatment to pass through the whole clinical development process is as low as 5%. Modeling and simulation lend themselves as tools which can potentially streamline drug development. A critical component of the models developed is a description of how...
Modelling stock order flows with non-homogeneous intensities from high-frequency data
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).
Reprogramming of human cancer cells to pluripotency for models of cancer progression
Kim, Jungsun; Zaret, Kenneth S
2015-01-01
The ability to study live cells as they progress through the stages of cancer provides the opportunity to discover dynamic networks underlying pathology, markers of early stages, and ways to assess therapeutics. Genetically engineered animal models of cancer, where it is possible to study the consequences of temporal-specific induction of oncogenes or deletion of tumor suppressors, have yielded major insights into cancer progression. Yet differences exist between animal and human cancers, such as in markers of progression and response to therapeutics. Thus, there is a need for human cell models of cancer progression. Most human cell models of cancer are based on tumor cell lines and xenografts of primary tumor cells that resemble the advanced tumor state, from which the cells were derived, and thus do not recapitulate disease progression. Yet a subset of cancer types have been reprogrammed to pluripotency or near-pluripotency by blastocyst injection, by somatic cell nuclear transfer and by induced pluripotent stem cell (iPS) technology. The reprogrammed cancer cells show that pluripotency can transiently dominate over the cancer phenotype. Diverse studies show that reprogrammed cancer cells can, in some cases, exhibit early-stage phenotypes reflective of only partial expression of the cancer genome. In one case, reprogrammed human pancreatic cancer cells have been shown to recapitulate stages of cancer progression, from early to late stages, thus providing a model for studying pancreatic cancer development in human cells where previously such could only be discerned from mouse models. We discuss these findings, the challenges in developing such models and their current limitations, and ways that iPS reprogramming may be enhanced to develop human cell models of cancer progression. PMID:25712212
The Naval Ocean Vertical Aerosol Model : Progress Report
Leeuw, G. de; Gathman, S.G.; Davidson, K.L.; Jensen, D.R.
1990-01-01
The Naval Oceanic Vertical Aerosol Model (NOVAM) has been formulated to estimate the vertical structure of the optical and infrared extinction coefficients in the marine atmospheric boundary layer (MABL). NOVAM was designed to predict the non-uniform and non-logarithmic extinction profiles which are
Modeling sheet-flow sand transport under progressive surface waves
Kranenburg, W.M.
2013-01-01
In the near-shore zone, energetic sea waves generate sheet-flow sand transport. In present day coastal models, wave-induced sheet-flow sand transport rates are usually predicted with semi-empirical transport formulas, based on extensive research on this phenomenon in oscillatory flow tunnels. Howeve
The production-distribution problem with order acceptance and package delivery: models and algorithm
Directory of Open Access Journals (Sweden)
Khalili Majid
2016-01-01
Full Text Available The production planning and distribution are among the most important decisions in the supply chain. Classically, in this problem, it is assumed that all orders have to produced and separately delivered; while, in practice, an order may be rejected if the cost that it brings to the supply chain exceeds its revenue. Moreover, orders can be delivered in a batch to reduce the related costs. This paper considers the production planning and distribution problem with order acceptance and package delivery to maximize the profit. At first, a new mathematical model based on mixed integer linear programming is developed. Using commercial optimization software, the model can optimally solve small or even medium sized instances. For large instances, a solution method, based on imperialist competitive algorithms, is also proposed. Using numerical experiments, the proposed model and algorithm are evaluated.
Sullivan, D L; Schommer, J C
1993-01-01
The purpose of this study was to investigate empirically the potential cost savings to a pharmaceutical wholesaler using the Economic Order Quantity (EOQ) model. This model allows for calculating the order quantity that minimizes both ordering and holding costs. A regional pharmaceutical wholesaler was selected for a case analysis study using the EOQ model. Eleven brand name products were randomly selected for the analysis. The average yearly cost savings using EOQ was $31.92 per product. The potential yearly cost savings based on 8500 brand name stock-keeping units was $271,320. Using EOQ can therefore assist pharmaceutical wholesalers in minimizing holding and ordering costs and improve efficiency for pharmaceutical distribution channels.
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.
Progress in Geant4 Electromagnetic Physics Modelling and Validation
Apostolakis, J.; Asai, M.; Bagulya, A.; Brown, J. M. C.; Burkhardt, H.; Chikuma, N.; Cortes-Giraldo, M. A.; Elles, S.; Grichine, V.; Guatelli, S.; Incerti, S.; Ivanchenko, V. N.; Jacquemier, J.; Kadri, O.; Maire, M.; Pandola, L.; Sawkey, D.; Toshito, T.; Urban, L.; Yamashita, T.
2015-12-01
In this work we report on recent improvements in the electromagnetic (EM) physics models of Geant4 and new validations of EM physics. Improvements have been made in models of the photoelectric effect, Compton scattering, gamma conversion to electron and muon pairs, fluctuations of energy loss, multiple scattering, synchrotron radiation, and high energy positron annihilation. The results of these developments are included in the new Geant4 version 10.1 and in patches to previous versions 9.6 and 10.0 that are planned to be used for production for run-2 at LHC. The Geant4 validation suite for EM physics has been extended and new validation results are shown in this work. In particular, the effect of gamma-nuclear interactions on EM shower shape at LHC energies is discussed.
Progress in Geant4 Electromagnetic Physics Modelling and Validation
Apostolakis, J; Bagulya, A; Brown, J M C; Burkhardt, H; Chikuma, N; Cortes-Giraldo, M A; Elles, S; Grichine, V; Guatelli, S; Incerti, S; Ivanchenko, V N; Jacquemier, J; Kadri, O; Maire, M; Pandola, L; Sawkey, D; Toshito, T; Urban, L; Yamashita, T
2015-01-01
In this work we report on recent improvements in the electromagnetic (EM) physics models of Geant4 and new validations of EM physics. Improvements have been made in models of the photoelectric effect, Compton scattering, gamma conversion to electron and muon pairs, fluctuations of energy loss, multiple scattering, synchrotron radiation, and high energy positron annihilation. The results of these developments are included in the new Geant4 version 10.1 and in patches to previous versions 9.6 and 10.0 that are planned to be used for production for run-2 at LHC. The Geant4 validation suite for EM physics has been extended and new validation results are shown in this work. In particular, the effect of gamma-nuclear interactions on EM shower shape at LHC energies is discussed.
Progress in Geant4 Electromagnetic Physics Modelling and Validation
Apostolakis, J; Bagulya, A; Brown, J M C; Burkhardt, H; Chikuma, N; Cortes-Giraldo, M A; Elles, S; Grichine, V; Guatelli, S; Incerti, S; Ivanchenko, V N; Jacquemier, J; Kadri, O; Maire, M; Pandola, L; Sawkey, D; Toshito, T; Urban, L; Yamashita, T
2015-01-01
In this work we report on recent improvements in the electromagnetic (EM) physics models of Geant4 and new validations of EM physics. Improvements have been made in models of the photoelectric effect, Compton scattering, gamma conversion to electron and muon pairs, fluctuations of energy loss, multiple scattering, synchrotron radiation, and high energy positron annihilation. The results of these developments are included in the new Geant4 version 10.1 and in patches to previous versions 9.6 and 10.0 that are planned to be used for production for run-2 at LHC. The Geant4 validation suite for EM physics has been extended and new validation results are shown in this work. In particular, the effect of gamma-nuclear interactions on EM shower shape at LHC energies is discussed.
Wilson, B.; Henseler, J.
2007-01-01
Many studies in the social sciences are increasingly modeling higher-order constructs. PLS can be used to investigate models at a higher level of abstraction (Lohmöller, 1989). It is often chosen due to its’ ability to estimate complex models (Chin, 1998). The primary goal of this paper is to demons
Classen, Laura; Xing, Rui-Qi; Khodas, Maxim; Chubukov, Andrey V
2017-01-20
We report the results of the parquet renormalization group (RG) analysis of the phase diagram of the most general 5-pocket model for Fe-based superconductors. We use as an input the orbital structure of excitations near the five pockets made out of d_{xz}, d_{yz}, and d_{xy} orbitals and argue that there are 40 different interactions between low-energy fermions in the orbital basis. All interactions flow under the RG, as one progressively integrates out fermions with higher energies. We find that the low-energy behavior is amazingly simple, despite the large number of interactions. Namely, at low energies the full 5-pocket model effectively reduces either to a 3-pocket model made of one d_{xy} hole pocket and two electron pockets or a 4-pocket model made of two d_{xz}/d_{yz} hole pockets and two electron pockets. The leading instability in the effective 4-pocket model is a spontaneous orbital (nematic) order, followed by s^{+-} superconductivity. In the effective 3-pocket model, orbital fluctuations are weaker, and the system develops either s^{+-} superconductivity or a stripe spin-density wave. In the latter case, nematicity is induced by composite spin fluctuations.
Preface: International Reference Ionosphere - Progress in Ionospheric Modelling
Bilitza Dieter; Reinisch, Bodo
2010-01-01
The international reference ionosphere (lRI) is the internationally recommended empirical model for the specification of ionospheric parameters supported by the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) and recognized by the International Standardization Organization (ISO). IRI is being continually improved by a team of international experts as new data become available and better models are being developed. This issue chronicles the latest phase of model updates as reported during two IRI-related meetings. The first was a special session during the Scientific Assembly of the Committee of Space Research (COSPAR) in Montreal, Canada in July 2008 and the second was an IRI Task Force Activity at the US Air Force Academy in Colorado Springs in May 2009. This work led to several improvements and additions of the model which will be included in the next version, IRI-201O. The issue is divided into three sections focusing on the improvements made in the topside ionosphere, the F-peak, and the lower ionosphere, respectively. This issue would not have been possible without the reviewing efforts of many individuals. Each paper was reviewed by two referees. We thankfully acknowledge the contribution to this issue made by the following reviewers: Jacob Adeniyi, David Altadill, Eduardo Araujo, Feza Arikan, Dieter Bilitza, Jilijana Cander, Bela Fejer, Tamara Gulyaeva, Manuel Hermindez-Pajares, Ivan Kutiev, John MacDougal, Leo McNamara, Bruno Nava, Olivier Obrou, Elijah Oyeyemi, Vadym Paznukhov, Bodo Reinisch, John Retterer, Phil Richards, Gary Sales, J.H. Sastri, Ludger Scherliess, Iwona Stanislavska, Stamir Stankov, Shin-Yi Su, Manlian Zhang, Y ongliang Zhang, and Irina Zakharenkova. We are grateful to Peggy Ann Shea for her final review and guidance as the editor-in-chief for special issues of Advances in Space Research. We thank the authors for their timely submission and their quick response to the reviewer comments and humbly
Progress towards quantum simulating the classical O(2) Model
2014-12-01
Hilbert space spanned by the eigenstates |n〉 of the “angular momentum” operator L = −i∂/∂θ with all positive and negative integer eigenvalues n. The...Ua = Ub = W are very large and positive , the on-site Hilbert space can then be restricted to the states satisfying nx = 2 at each site. All the other...gauge theory, to physical models potentially implementable on optical lattices and evolving at physical time. Using the tensor renormalization -group
A proposed Fast algorithm to construct the system matrices for a reduced-order groundwater model
Ushijima, Timothy T.; Yeh, William W.-G.
2017-04-01
Past research has demonstrated that a reduced-order model (ROM) can be two-to-three orders of magnitude smaller than the original model and run considerably faster with acceptable error. A standard method to construct the system matrices for a ROM is Proper Orthogonal Decomposition (POD), which projects the system matrices from the full model space onto a subspace whose range spans the full model space but has a much smaller dimension than the full model space. This projection can be prohibitively expensive to compute if it must be done repeatedly, as with a Monte Carlo simulation. We propose a Fast Algorithm to reduce the computational burden of constructing the system matrices for a parameterized, reduced-order groundwater model (i.e. one whose parameters are represented by zones or interpolation functions). The proposed algorithm decomposes the expensive system matrix projection into a set of simple scalar-matrix multiplications. This allows the algorithm to efficiently construct the system matrices of a POD reduced-order model at a significantly reduced computational cost compared with the standard projection-based method. The developed algorithm is applied to three test cases for demonstration purposes. The first test case is a small, two-dimensional, zoned-parameter, finite-difference model; the second test case is a small, two-dimensional, interpolated-parameter, finite-difference model; and the third test case is a realistically-scaled, two-dimensional, zoned-parameter, finite-element model. In each case, the algorithm is able to accurately and efficiently construct the system matrices of the reduced-order model.
Order reduction and efficient implementation of nonlinear nonlocal cochlear response models.
Filo, Maurice; Karameh, Fadi; Awad, Mariette
2016-12-01
The cochlea is an indispensable preliminary processing stage in auditory perception that employs mechanical frequency-tuning and electrical transduction of incoming sound waves. Cochlear mechanical responses are shown to exhibit active nonlinear spatiotemporal response dynamics (e.g., otoacoustic emission). To model such phenomena, it is often necessary to incorporate cochlear fluid-membrane interactions. This results in both excessively high-order model formulations and computationally intensive solutions that limit their practical use in simulating the model and analyzing its response even for simple single-tone inputs. In order to address these limitations, the current work employs a control-theoretic framework to reformulate a nonlinear two-dimensional cochlear model into discrete state space models that are of considerably lower order (factor of 8) and are computationally much simpler (factor of 25). It is shown that the reformulated models enjoy sparse matrix structures which permit efficient numerical manipulations. Furthermore, the spatially discretized models are linearized and simplified using balanced transformation techniques to result in lower-order (nonlinear) realizations derived from the dominant Hankel singular values of the system dynamics. Accuracy and efficiency of the reduced-order reformulations are demonstrated under the response to two fixed tones, sweeping tones and, more generally, a brief speech signal. The corresponding responses are compared to those produced by the original model in both frequency and spatiotemporal domains. Although carried out on a specific instance of cochlear models, the introduced framework of control-theoretic model reduction could be applied to a wide class of models that address the micro- and macro-mechanical properties of the cochlea.
Theory, Modeling and Simulation: Research progress report 1994--1995
Energy Technology Data Exchange (ETDEWEB)
Garrett, B.C.; Dixon, D.A.; Dunning, T.H.
1997-01-01
The Pacific Northwest National Laboratory (PNNL) has established the Environmental Molecular Sciences Laboratory (EMSL). In April 1994, construction began on the new EMSL, a collaborative research facility devoted to advancing the understanding of environmental molecular science. Research in the Theory, Modeling, and Simulation (TM and S) program will play a critical role in understanding molecular processes important in restoring DOE`s research, development, and production sites, including understanding the migration and reactions of contaminants in soils and ground water, developing processes for isolation and processing of pollutants, developing improved materials for waste storage, understanding the enzymatic reactions involved in the biodegradation of contaminants, and understanding the interaction of hazardous chemicals with living organisms. The research objectives of the TM and S program are fivefold: to apply available electronic structure and dynamics techniques to study fundamental molecular processes involved in the chemistry of natural and contaminated systems; to extend current electronic structure and dynamics techniques to treat molecular systems of future importance and to develop new techniques for addressing problems that are computationally intractable at present; to apply available molecular modeling techniques to simulate molecular processes occurring in the multi-species, multi-phase systems characteristic of natural and polluted environments; to extend current molecular modeling techniques to treat ever more complex molecular systems and to improve the reliability and accuracy of such simulations; and to develop technologies for advanced parallel architectural computer systems. Research highlights of 82 projects are given.
Progress Towards an LES Wall Model Including Unresolved Roughness
Craft, Kyle; Redman, Andrew; Aikens, Kurt
2015-11-01
Wall models used in large eddy simulations (LES) are often based on theories for hydraulically smooth walls. While this is reasonable for many applications, there are also many where the impact of surface roughness is important. A previously developed wall model has been used primarily for jet engine aeroacoustics. However, jet simulations have not accurately captured thick initial shear layers found in some experimental data. This may partly be due to nozzle wall roughness used in the experiments to promote turbulent boundary layers. As a result, the wall model is extended to include the effects of unresolved wall roughness through appropriate alterations to the log-law. The methodology is tested for incompressible flat plate boundary layers with different surface roughness. Correct trends are noted for the impact of surface roughness on the velocity profile. However, velocity deficit profiles and the Reynolds stresses do not collapse as well as expected. Possible reasons for the discrepancies as well as future work will be presented. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1053575. Computational resources on TACC Stampede were provided under XSEDE allocation ENG150001.
Theoretical models for coronary vascular biomechanics: Progress & challenges
Waters, Sarah L.; Alastruey, Jordi; Beard, Daniel A.; Bovendeerd, Peter H.M.; Davies, Peter F.; Jayaraman, Girija; Jensen, Oliver E.; Lee, Jack; Parker, Kim H.; Popel, Aleksander S.; Secomb, Timothy W.; Siebes, Maria; Sherwin, Spencer J.; Shipley, Rebecca J.; Smith, Nicolas P.; van de Vosse, Frans N.
2013-01-01
A key aim of the cardiac Physiome Project is to develop theoretical models to simulate the functional behaviour of the heart under physiological and pathophysiological conditions. Heart function is critically dependent on the delivery of an adequate blood supply to the myocardium via the coronary vasculature. Key to this critical function of the coronary vasculature is system dynamics that emerge via the interactions of the numerous constituent components at a range of spatial and temporal scales. Here, we focus on several components for which theoretical approaches can be applied, including vascular structure and mechanics, blood flow and mass transport, flow regulation, angiogenesis and vascular remodelling, and vascular cellular mechanics. For each component, we summarise the current state of the art in model development, and discuss areas requiring further research. We highlight the major challenges associated with integrating the component models to develop a computational tool that can ultimately be used to simulate the responses of the coronary vascular system to changing demands and to diseases and therapies. PMID:21040741
Modelling Distributed Shape Priors by Gibbs Random Fields of Second Order
Flach, Boris
2011-01-01
We analyse the potential of Gibbs Random Fields for shape prior modelling. We show that the expressive power of second order GRFs is already sufficient to express simple shapes and spatial relations between them simultaneously. This allows to model and recognise complex shapes as spatial compositions of simpler parts.
Optimized Second-Order Dynamical Systems and Their RLC Circuit Models with PWL Controlled Sources
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J. Brzobohaty
2004-09-01
Full Text Available Complementary active RLC circuit models with a voltage-controlledvoltage source (VCVS and a current-controlled current source (CCCSfor the second-order autonomous dynamical system realization areproposed. The main advantage of these equivalent circuits is the simplerelation between the state model parameters and their correspondingcircuit parameters, which leads also to simple design formulas.
Short-Term Memory for Serial Order: A Recurrent Neural Network Model
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…
First-order fire effects models for land Management: Overview and issues
Elizabeth D. Reinhardt; Matthew B. Dickinson
2010-01-01
We give an overview of the science application process at work in supporting fire management. First-order fire effects models, such as those discussed in accompanying papers, are the building blocks of software systems designed for application to landscapes over time scales from days to centuries. Fire effects may be modeled using empirical, rule based, or process...
Time-Frequency Analysis Using Warped-Based High-Order Phase Modeling
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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.
Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models
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Yi Hu
2014-01-01
Full Text Available Generalized method of moments (GMM has been widely applied for estimation of nonlinear models in economics and finance. Although generalized method of moments has good asymptotic properties under fairly moderate regularity conditions, its finite sample performance is not very well. In order to improve the finite sample performance of generalized method of moments estimators, this paper studies higher-order mean squared error of two-step efficient generalized method of moments estimators for nonlinear models. Specially, we consider a general nonlinear regression model with endogeneity and derive the higher-order asymptotic mean square error for two-step efficient generalized method of moments estimator for this model using iterative techniques and higher-order asymptotic theories. Our theoretical results allow the number of moments to grow with sample size, and are suitable for general moment restriction models, which contains conditional moment restriction models as special cases. The higher-order mean square error can be used to compare different estimators and to construct the selection criteria for improving estimator’s finite sample performance.
Zimmerling, Jörn; Wei, Lei; Urbach, Paul; Remis, Rob
2016-06-01
In this paper we present a Krylov subspace model-order reduction technique for time- and frequency-domain electromagnetic wave fields in linear dispersive media. Starting point is a self-consistent first-order form of Maxwell's equations and the constitutive relation. This form is discretized on a standard staggered Yee grid, while the extension to infinity is modeled via a recently developed global complex scaling method. By applying this scaling method, the time- or frequency-domain electromagnetic wave field can be computed via a so-called stability-corrected wave function. Since this function cannot be computed directly due to the large order of the discretized Maxwell system matrix, Krylov subspace reduced-order models are constructed that approximate this wave function. We show that the system matrix exhibits a particular physics-based symmetry relation that allows us to efficiently construct the time- and frequency-domain reduced-order models via a Lanczos-type reduction algorithm. The frequency-domain models allow for frequency sweeps meaning that a single model provides field approximations for all frequencies of interest and dominant field modes can easily be determined as well. Numerical experiments for two- and three-dimensional configurations illustrate the performance of the proposed reduction method.
Modeling Methodology of Progressive Collapse by the Example of Real High-Rise Buildings
Mariya Barabash
2014-01-01
The purpose of the research was to find out several ways to design real buildings with protective measures against progressive collapse. There are no uniform guidelines for choosing the type of finite element able to provide the necessary accuracy of the calculation model taking into account all the main factors affecting the strength and stability of the building. Therefore it is required to develop numerical methods for calculation on progressive collapse of buildings bearing structural ele...
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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.
Symmetries of 2-lattices and second order accuracy of the Cauchy--Born Model
Van Koten, Brian
2012-01-01
We show that the Cauchy--Born model of a single-species 2-lattice is second order if the atomistic and continuum kinematics are connected in a novel way. Our proof uses a generalization to 2-lattices of the point symmetry of Bravais lattices. Moreover, by identifying similar symmetries in multi-species pair interaction models, we construct a new stored energy density, using shift-gradients but not strain gradients, that is also second order accurate. These results can be used to develop highly accurate continuum models and atomistic/continuum coupling methods for materials such as graphene, hcp metals, and shape memory alloys.
Parallel Computation of Air Pollution Using a Second-Order Closure Model
Pai, Prasad Prabhakar
1991-02-01
Rational analysis, prediction and policy making of air pollution problems depend on our understanding of the individual processes that govern the atmospheric system. In the past, computational constraints have prohibited the incorporation of detailed physics of many individual processes in air pollution models. This has resulted in poor model performance for realistic situations. Recent advances in computing capabilities make it possible to develop air pollution models which capture the essential physics of the individual processes. The present study uses a three -dimensional second-order closure diffusion model to simulate dispersion from ground level and elevated point sources in convective (daytime) boundary layers. The model uses mean and turbulence variables simulated with a one-dimensional second-order closure fluid dynamic model. The calculated mean profiles of wind and temperature are found to be in good agreement with the observed Day 33 Wangara data, whereas the calculated vertical profiles of turbulence variables agree well with those estimated from other numerical models and laboratory experiments. The three-dimensional second -order closure diffusion model can capture the plume behavior in daytime atmospheric boundary layer remarkably well in comparison with laboratory data. We also compare the second -order closure diffusion model with the commonly used K -diffusion model for the same meteorological conditions. In order to reduce the computational requirements for second -order closure models, we propose a parallel algorithm of a time-splitting finite element method for the numerical solution of the governing equations. The parallel time -splitting finite element method substantially reduces the model wallclock or turnaround time by exploiting the vector and parallel capabilities of modern supercomputers. The plethora of supercomputers in the market today made it important for us to study the key issue of algorithm "portability". In view of this, we
Lattice solution model for order-disorder transitions in membranes and Langmuir monolayers
Guidi, Henrique S
2013-01-01
Lipid monolayers and bilayers have been used as experimental models for the investigation of membrane thermal transitions. The main transition takes place near ambient temperatures for several lipids and reflects the order-disorder transition of lipid hydrocarbonic chains, which is accompanied by a small density gap. Equivalence between the transitions in the two systems has been argued by several authors. The two-state statistical model adopted by numerous authors for different properties of the membrane, such as permeability, diffusion, mixture or insertion of cholesterol or protein, is inadequate for the description of charged membranes, since it lacks a proper description of surface density. We propose a lattice solution model which adds interactions with water molecules to lipid-lipid interactions and obtain its thermal properties under a mean-field approach. Density variations, although concomitant with chain order variations, are independent of the latter. The model presents both chain order and gas-li...
Analysis of credit linked demand in an inventory model with varying ordering cost.
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.
Higher-Order Markov Tag-Topic Models for Tagged Documents and Images
Zeng, Jia; Cheung, William K; Li, Chun-Hung
2011-01-01
This paper studies the topic modeling problem of tagged documents and images. Higher-order relations among tagged documents and images are major and ubiquitous characteristics, and play positive roles in extracting reliable and interpretable topics. In this paper, we propose the tag-topic models (TTM) to depict such higher-order topic structural dependencies within the Markov random field (MRF) framework. First, we use the novel factor graph representation of latent Dirichlet allocation (LDA)-based topic models from the MRF perspective, and present an efficient loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Second, we propose the factor hypergraph representation of TTM, and focus on both pairwise and higher-order relation modeling among tagged documents and images. Efficient loopy BP algorithm is developed to learn TTM, which encourages the topic labeling smoothness among tagged documents and images. Extensive experimental results confirm the incorporation of highe...
BLIND AND COMPLETE MODELING OF LINEAR SYSTEMS USING THIRD ORDER CUMULANTS
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper presents a novel approach to structure determination of linear systems along with the choice of system orders and parameters. AutoRegressive (AR), Moving Average (MA) or AutoRegressive-Moving Average (ARMA) model structure can be extracted blindly from the Third Order Cumulants (TOC) of the system output measurements, where the unknown system is driven by an unobservable stationary independent identically distributed (i.i.d.) non-Gaussian signal. By means of the system order recursion, whether the system has an AR structure or has AR part of an ARMA structure is firstly investigated. MA features in the TOC domain is then applied as a threshold to decide if the system is an MA model or has MA part of an ARMA model. Numerical simulations illustrate the generality of the proposed blind structure identification methodology that may serve as a guideline for blind linear system modeling.
Directory of Open Access Journals (Sweden)
Weihua Liu
2014-01-01
Full Text Available Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC, which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order’s volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.
A posteriori model validation for the temporal order of directed functional connectivity maps
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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.
Sexual Recruitment in Zostera marina: Progress toward a Predictive Model.
Furman, Bradley T; Peterson, Bradley J
2015-01-01
Ecophysiological stress and physical disturbance are capable of structuring meadows through a combination of direct biomass removal and recruitment limitation; however, predicting these effects at landscape scales has rarely been successful. To model environmental influence on sexual recruitment in perennial Zostera marina, we selected a sub-tidal, light-replete study site with seasonal extremes in temperature and wave energy. During an 8-year observation period, areal coverage increased from 4.8 to 42.7%. Gains were stepwise in pattern, attributable to annual recruitment of patches followed by centrifugal growth and coalescence. Recruitment varied from 13 to 4,894 patches per year. Using a multiple linear regression approach, we examined the association between patch appearance and relative wave energy, atmospheric condition and water temperature. Two models were developed, one appropriate for the dispersal of naked seeds, and another for rafted flowers. Results indicated that both modes of sexual recruitment varied as functions of wind, temperature, rainfall and wave energy, with a regime shift in wind-wave energy corresponding to periods of rapid colonization within our site. Temporal correlations between sexual recruitment and time-lagged climatic summaries highlighted floral induction, seed bank and small patch development as periods of vulnerability. Given global losses in seagrass coverage, regions of recovery and re-colonization will become increasingly important. Lacking landscape-scale process models for seagrass recruitment, temporally explicit statistical approaches presented here could be used to forecast colonization trajectories and to provide managers with real-time estimates of future meadow performance; i.e., when to expect a good year in terms of seagrass expansion. To facilitate use as forecasting tools, we did not use statistical composites or normalized variables as our predictors. This study, therefore, represents a first step toward linking
Sexual Recruitment in Zostera marina: Progress toward a Predictive Model.
Directory of Open Access Journals (Sweden)
Bradley T Furman
Full Text Available Ecophysiological stress and physical disturbance are capable of structuring meadows through a combination of direct biomass removal and recruitment limitation; however, predicting these effects at landscape scales has rarely been successful. To model environmental influence on sexual recruitment in perennial Zostera marina, we selected a sub-tidal, light-replete study site with seasonal extremes in temperature and wave energy. During an 8-year observation period, areal coverage increased from 4.8 to 42.7%. Gains were stepwise in pattern, attributable to annual recruitment of patches followed by centrifugal growth and coalescence. Recruitment varied from 13 to 4,894 patches per year. Using a multiple linear regression approach, we examined the association between patch appearance and relative wave energy, atmospheric condition and water temperature. Two models were developed, one appropriate for the dispersal of naked seeds, and another for rafted flowers. Results indicated that both modes of sexual recruitment varied as functions of wind, temperature, rainfall and wave energy, with a regime shift in wind-wave energy corresponding to periods of rapid colonization within our site. Temporal correlations between sexual recruitment and time-lagged climatic summaries highlighted floral induction, seed bank and small patch development as periods of vulnerability. Given global losses in seagrass coverage, regions of recovery and re-colonization will become increasingly important. Lacking landscape-scale process models for seagrass recruitment, temporally explicit statistical approaches presented here could be used to forecast colonization trajectories and to provide managers with real-time estimates of future meadow performance; i.e., when to expect a good year in terms of seagrass expansion. To facilitate use as forecasting tools, we did not use statistical composites or normalized variables as our predictors. This study, therefore, represents a first
Underpotential deposition of metals - Progress and prospects in modelling
Indian Academy of Sciences (India)
V Sudha; M V Sangaranarayanan
2005-05-01
Underpotential deposition (UPD) of metals is analysed from the perspective of phenomenological and statistical thermodynamic considerations; the parameters influencing the UPD shift have been quantitatively indicated using a general formalism. The manner in which the macroscopic properties pertaining to the depositing ions and solvent dipoles and the nature of the metallic substrate influence the UPD process are highlighted; earlier correlations of the UPD shift with the work function differences are rationalised. Anion-induced phase transitions which manifest as sharp peaks in experimental cyclic voltammograms are discussed using statistical thermodynamic models.
Ordering Cost Reduction in Inventory Model with Defective Items and Backorder Price Discount
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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.
Improved first-order uncertainty method for water-quality modeling
Melching, C.S.; Anmangandla, S.
1992-01-01
Uncertainties are unavoidable in water-quality modeling and subsequent management decisions. Monte Carlo simulation and first-order uncertainty analysis (involving linearization at central values of the uncertain variables) have been frequently used to estimate probability distributions for water-quality model output due to their simplicity. Each method has its drawbacks: Monte Carlo simulation's is mainly computational time; and first-order analysis are mainly questions of accuracy and representativeness, especially for nonlinear systems and extreme conditions. An improved (advanced) first-order method is presented, where the linearization point varies to match the output level whose exceedance probability is sought. The advanced first-order method is tested on the Streeter-Phelps equation to estimate the probability distribution of critical dissolved-oxygen deficit and critical dissolved oxygen using two hypothetical examples from the literature. The advanced first-order method provides a close approximation of the exceedance probability for the Streeter-Phelps model output estimated by Monte Carlo simulation using less computer time - by two orders of magnitude - regardless of the probability distributions assumed for the uncertain model parameters.
High-order state space simulation models of helicopter flight mechanics
Kim, Frederick D.; Celi, Roberto; Tischler, Mark B.
1993-01-01
This paper describes the formulation and validation of a high-order linearized mathematical model of helicopter flight mechanics, which includes rotor flap and lag degrees of freedom as well as inflow dynamics. The model is extracted numerically from an existing nonlinear, blade element, real-time simulation model. Extensive modifications in the formulation and solution process of the nonlinear model, required for a theoetically rigorous linearization, are described in detail. The validation results show that the linearized model successfully captures the coupled rotor-fuselage dynamics in the frequency band most critical for the design of advanced flight control systems. Additional results quantify the extent to which the order of the model can be reduced without loss of fidelity.
A Modular Arbitrary-Order Ocean-Atmosphere Model: MAOOAM v1.0
De Cruz, L; Vannitsem, S
2016-01-01
This paper describes a reduced-order quasi-geostrophic coupled ocean-atmosphere model that allows for an arbitrary number of atmospheric and oceanic modes to be retained in the spectral decomposition. The modularity of this new model allows one to easily modify the model physics. Using this new model, coined "Modular Arbitrary-Order Ocean-Atmosphere Model" (maooam), we analyse the dependence of the model dynamics on the truncation level of the spectral expansion, and unveil spurious behaviour that may exist at low resolution by a comparison with the higher resolution versions. In particular, we assess the robustness of the coupled low-frequency variability when the number of modes is increased. An "optimal" version is proposed for which the ocean resolution is sufficiently high while the total number of modes is small enough to allow for a tractable and extensive analysis of the dynamics.
Benchmark experiments for higher-order and full-Stokes ice sheet models (ISMIP–HOM
Directory of Open Access Journals (Sweden)
F. Pattyn
2008-08-01
Full Text Available We present the results of the first ice sheet model intercomparison project for higher-order and full-Stokes ice sheet models. These models are compared and verified in a series of six experiments of which one has an analytical solution obtained from a perturbation analysis. The experiments are applied to both 2-D and 3-D geometries; five experiments are steady-state diagnostic, and one has a time-dependent prognostic solution. All participating models give results that are in close agreement. A clear distinction can be made between higher-order models and those that solve the full system of equations. The full-Stokes models show a much smaller spread, hence are in better agreement with one another and with the analytical solution.
Frequency Weighted Model Order Reduction Technique and Error Bounds for Discrete Time Systems
Directory of Open Access Journals (Sweden)
Muhammad Imran
2014-01-01
for whole frequency range. However, certain applications (like controller reduction require frequency weighted approximation, which introduce the concept of using frequency weights in model reduction techniques. Limitations of some existing frequency weighted model reduction techniques include lack of stability of reduced order models (for two sided weighting case and frequency response error bounds. A new frequency weighted technique for balanced model reduction for discrete time systems is proposed. The proposed technique guarantees stable reduced order models even for the case when two sided weightings are present. Efficient technique for frequency weighted Gramians is also proposed. Results are compared with other existing frequency weighted model reduction techniques for discrete time systems. Moreover, the proposed technique yields frequency response error bounds.
Fisher, Helen
2012-01-01
This article explores a Special Educational Needs Coordinator's experience of progressing from a "mainstream + SEN" approach to inclusion, defined as an extrinsically inclusive model, and perhaps more closely aligned to integration, towards a model of intrinsic inclusiveness. A three-tiered reading/spelling programme was implemented, using a…
Recent progress in plasma modelling at INFN-LNS
Energy Technology Data Exchange (ETDEWEB)
Neri, L., E-mail: neri@lns.infn.it; Castro, G.; Mascali, D.; Celona, L.; Gammino, S. [INFN-Laboratori Nazionali del Sud, Via S. Sofia 62, 95125 Catania (Italy); Torrisi, G. [INFN-Laboratori Nazionali del Sud, Via S. Sofia 62, 95125 Catania (Italy); Università Mediterranea di Reggio Calabria, Via Graziella, 89100 Reggio Calabria (Italy); Galatà, A. [INFN-Laboratori Nazionali di Legnaro, Viale dell’Università 2, 35020 Legnaro, Padova (Italy)
2016-02-15
At Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali del Sud (INFN-LNS), the development of intense ion and proton sources has been supported by a great deal of work on the modelling of microwave generated plasmas for many years. First, a stationary version of the particle-in-cell code was developed for plasma modelling starting from an iterative strategy adopted for the space charge dominated beam transport simulations. Electromagnetic properties of the plasma and full-waves simulations are now affordable for non-homogenous and non-isotropic magnetized plasma via “cold” approximation. The effects of Coulomb collisions on plasma particles dynamics was implemented with the Langevin formalism, instead of simply applying the Spitzer 90° collisions through a Monte Carlo technique. A wide database of different cross sections related to reactions occurring in a hydrogen plasma was implemented. The next step consists of merging such a variety of approaches for retrieving an “as-a-whole” picture of plasma dynamics in ion sources. The preliminary results will be summarized in the paper for a microwave discharge ion source designed for intense and high quality proton beams production, proton source for European Spallation Source project. Even if the realization of a predictive software including the complete processes involved in plasma formation is still rather far, a better comprehension of the source behavior is possible and so the simulations may support the optimization phase.
Recent progress in plasma modelling at INFN-LNS
Neri, L.; Castro, G.; Torrisi, G.; Galatà, A.; Mascali, D.; Celona, L.; Gammino, S.
2016-02-01
At Istituto Nazionale di Fisica Nucleare - Laboratori Nazionali del Sud (INFN-LNS), the development of intense ion and proton sources has been supported by a great deal of work on the modelling of microwave generated plasmas for many years. First, a stationary version of the particle-in-cell code was developed for plasma modelling starting from an iterative strategy adopted for the space charge dominated beam transport simulations. Electromagnetic properties of the plasma and full-waves simulations are now affordable for non-homogenous and non-isotropic magnetized plasma via "cold" approximation. The effects of Coulomb collisions on plasma particles dynamics was implemented with the Langevin formalism, instead of simply applying the Spitzer 90° collisions through a Monte Carlo technique. A wide database of different cross sections related to reactions occurring in a hydrogen plasma was implemented. The next step consists of merging such a variety of approaches for retrieving an "as-a-whole" picture of plasma dynamics in ion sources. The preliminary results will be summarized in the paper for a microwave discharge ion source designed for intense and high quality proton beams production, proton source for European Spallation Source project. Even if the realization of a predictive software including the complete processes involved in plasma formation is still rather far, a better comprehension of the source behavior is possible and so the simulations may support the optimization phase.
Classical Cepheid pulsation models --- VI. The Hertzsprung progression
Bono, G.; Marconi, M.; Stellingwerf, R. F.
2000-08-01
We present the results of an extensive theoretical investigation on the pulsation behavior of Bump Cepheids. We constructed several sequences of full amplitude, nonlinear, convective models by adopting a chemical composition typical of Large Magellanic Cloud (LMC) Cepheids (Y=0.25, Z=0.008) and stellar masses ranging from M/M⊙ =6.55 to 7.45. We find that theoretical light and velocity curves reproduce the HP, and indeed close to the blue edge the bump is located along the descending branch, toward longer periods it crosses at first the luminosity/velocity maximum and then it appears along the rising branch. In particular, we find that the predicted period at the HP center is PHP = 11.24∓0.46 d and that such a value is in very good agreement with the empirical value estimated by adopting the Fourier parameters of LMC Cepheid light curves i.e. PHP = 11.2 ∓ 0.8 d (Welch et al. 1997). Moreover, light and velocity amplitudes present a "double-peaked" distribution which is in good qualitative agreement with observational evidence on Bump Cepheids. It turns out that both the skewness and the acuteness typically show a well-defined minimum at the HP center and the periods range from PHP = 10.73 ∓ 0.97 d to PHP = 11.29 ∓ 0.53 d which are in good agreement with empirical estimates. We also find that the models at the HP center are located within the resonance region but not on the 2:1 resonance line (P2/P0 = 0.5), and indeed the P2/P0 ratios roughly range from 0.51 (cool models) to 0.52 (hot models). Interestingly enough, the predicted Bump Cepheid masses, based on a Mass-Luminosity (ML) relation which neglects the convective core overshooting, are in good agreement with the empirical masses of Galactic Cepheids estimated by adopting the Baade-Wesselink method (Gieren 1989). As a matter of fact, the observed mass at the HP center -P ≍ 11.2 d- is 6.9 ∓ 0.9 M⊙, while the predicted mass is 7.0 ∓ 0.45 M⊙. Even by accounting for the metallicity difference
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.
Van Kampen, Jackalina M; Baranowski, David C; Robertson, Harold A; Shaw, Christopher A; Kay, Denis G
2015-01-01
The development of effective neuroprotective therapies for Parkinson's disease (PD) has been severely hindered by the notable lack of an appropriate animal model for preclinical screening. Indeed, most models currently available are either acute in nature or fail to recapitulate all characteristic features of the disease. Here, we present a novel progressive model of PD, with behavioural and cellular features that closely approximate those observed in patients. Chronic exposure to dietary phytosterol glucosides has been found to be neurotoxic. When fed to rats, β-sitosterol β-d-glucoside (BSSG) triggers the progressive development of parkinsonism, with clinical signs and histopathology beginning to appear following cessation of exposure to the neurotoxic insult and continuing to develop over several months. Here, we characterize the progressive nature of this model, its non-motor features, the anatomical spread of synucleinopathy, and response to levodopa administration. In Sprague Dawley rats, chronic BSSG feeding for 4 months triggered the progressive development of a parkinsonian phenotype and pathological events that evolved slowly over time, with neuronal loss beginning only after toxin exposure was terminated. At approximately 3 months following initiation of BSSG exposure, animals displayed the early emergence of an olfactory deficit, in the absence of significant dopaminergic nigral cell loss or locomotor deficits. Locomotor deficits developed gradually over time, initially appearing as locomotor asymmetry and developing into akinesia/bradykinesia, which was reversed by levodopa treatment. Late-stage cognitive impairment was observed in the form of spatial working memory deficits, as assessed by the radial arm maze. In addition to the progressive loss of TH+ cells in the substantia nigra, the appearance of proteinase K-resistant intracellular α-synuclein aggregates was also observed to develop progressively, appearing first in the olfactory bulb, then
Proofreading of DNA polymerase: a new kinetic model with higher-order terminal effects
Song, Yong-Shun; Shu, Yao-Gen; Zhou, Xin; Ou-Yang, Zhong-Can; Li, Ming
2017-01-01
The fidelity of DNA replication by DNA polymerase (DNAP) has long been an important issue in biology. While numerous experiments have revealed details of the molecular structure and working mechanism of DNAP which consists of both a polymerase site and an exonuclease (proofreading) site, there were quite a few theoretical studies on the fidelity issue. The first model which explicitly considered both sites was proposed in the 1970s and the basic idea was widely accepted by later models. However, all these models did not systematically investigate the dominant factor on DNAP fidelity, i.e. the higher-order terminal effects through which the polymerization pathway and the proofreading pathway coordinate to achieve high fidelity. In this paper, we propose a new and comprehensive kinetic model of DNAP based on some recent experimental observations, which includes previous models as special cases. We present a rigorous and unified treatment of the corresponding steady-state kinetic equations of any-order terminal effects, and derive analytical expressions for fidelity in terms of kinetic parameters under bio-relevant conditions. These expressions offer new insights on how the higher-order terminal effects contribute substantially to the fidelity in an order-by-order way, and also show that the polymerization-and-proofreading mechanism is dominated only by very few key parameters. We then apply these results to calculate the fidelity of some real DNAPs, which are in good agreements with previous intuitive estimates given by experimentalists.
Dijk, van, Nico M.; Breedveld, P.C.
1991-01-01
The existence of zero-order causal paths in bond graphs of physical systems implies the set of state equations to be an implicit mixed set of Differential and Algebraic Equations (DAEs). In the block diagram expansion of such a bond graph, this type of causal path corresponds with a zero-order loop. In this paper the numerical solution of the DAEs by methods commonly used for solving stiff systems of Ordinary Differential Equations (ODEs) is discussed. Apart from a description of the numerica...
Institute of Scientific and Technical Information of China (English)
Yun Li; Hiroshi Kashiwagi
2005-01-01
Model Predictive Control (MPC) has recently found wide acceptance in the process industry, but existing design and implementation methods are restricted to linear process models. A chemical process, however, involves severe nonlinearity which cannot be ignored in practice. This paper aims to solve this nonlinear control problem by extending MPC to accommodate nonlinear models. It develops an analytical framework for nonlinear model predictive control (NMPC). It also offers a third-order Volterra series based nonparametric nonlinear modelling technique for NMPC design, which relieves practising engineers from the need for deriving a physical-principles based model first. An on-line realisation technique for implementing NMPC is then developed and applied to a Mitsubishi Chemicals polymerisation reaction process. Results show that this nonlinear MPC technique is feasible and very effective. It considerably outperforms linear and low-order Volterra model based methods. The advantages of the developed approach lie not only in control performance superior to existing NMPC methods, but also in eliminating the need for converting an analytical model and then convert it to a Volterra model obtainable only up to the second order.
DEFF Research Database (Denmark)
Kushch, V.I.; Shmegera, S.V.; Mishnaevsky, Leon
2011-01-01
Two micromechanical, representative unit cell type models of fiber reinforced composite (FRC) are applied to simulate explicitly onset and accumulation of scattered local damage in the form of interface debonding. The first model is based on the analytical, multipole expansion type solution...... of the multiple inclusion problem by means of complex potentials. The second, finite element model of FRC is based on the cohesive zone model of interface. Simulation of progressive debonding in FRC using the many-fiber models of composite has been performed. The advantageous features and applicability areas...... of both models are discussed. It has been shown that the developed models provide detailed analysis of the progressive debonding phenomena including the interface crack cluster formation, overall stiffness reduction and induced anisotropy of the effective elastic moduli of composite....
Reina, Borja
2014-01-01
Hartle's model describes the equilibrium configuration of a rotating isolated compact body in perturbation theory up to second order in General Relativity. The interior of the body is a perfect fluid with a barotropic equation of state, no convective motions and rigid rotation. That interior is matched across its surface to an asymptotically flat vacuum exterior. Perturbations are taken to second order around a static and spherically symmetric background configuration. Apart from the explicit assumptions, the perturbed configuration is constructed upon some implicit premises, in particular the continuity of the functions describing the perturbation in terms of some background radial coordinate. In this work we revisit the model within a modern general and consistent theory of perturbative matchings to second order, which is independent of the coordinates and gauges used to describe the two regions to be joined. We explore the matching conditions up to second order in full. The main particular result we presen...
Dynamo onset as a first-order transition: lessons from a shell model for magnetohydrodynamics.
Sahoo, Ganapati; Mitra, Dhrubaditya; Pandit, Rahul
2010-03-01
We carry out systematic and high-resolution studies of dynamo action in a shell model for magnetohydrodynamic (MHD) turbulence over wide ranges of the magnetic Prandtl number PrM and the magnetic Reynolds number ReM. Our study suggests that it is natural to think of dynamo onset as a nonequilibrium first-order phase transition between two different turbulent, but statistically steady, states. The ratio of the magnetic and kinetic energies is a convenient order parameter for this transition. By using this order parameter, we obtain the stability diagram (or nonequilibrium phase diagram) for dynamo formation in our MHD shell model in the (PrM-1,ReM) plane. The dynamo boundary, which separates dynamo and no-dynamo regions, appears to have a fractal character. We obtain a hysteretic behavior of the order parameter across this boundary and suggestions of nucleation-type phenomena.
Indian Academy of Sciences (India)
Jai Prakash
2013-01-01
Ionic thermocurrent (ITC) spectrum is much similar to a thermoluminescence (TL) glow curve involving monomolecular kinetics. It has already been reported that different orders of kinetics are involved in TL processes, which depend specifically on the extent of recombination and simultaneous retrapping. It is found that the involvement of different orders of kinetics in ITC spectrum depends on the experimental conditions of polarization and rate of rapid cooling. Consequently, order of kinetics involved in the ITC spectrum does not represent any specific feature of the system under investigation. An equation is developed which explains the occurrence of ITC spectrum involving any order of kinetics. Dielectric relaxation parameters, order of kinetics and approximate number of dipoles per unit volume are evaluated conveniently and easily following the proposed model.
Directory of Open Access Journals (Sweden)
Maneesha Gupta
2013-01-01
Full Text Available Second and third order digital integrators (DIs have been optimized first using Particle Swarm Optimization (PSO with minimized error fitness function obtained by registering mean, median, and standard deviation values in different random iterations. Later indirect discretization using Continued Fraction Expansion (CFE has been used to ascertain a better fitting of proposed integer order optimized DIs into their corresponding fractional counterparts by utilizing their refined properties, now restored in them due to PSO algorithm. Simulation results for the comparisons of the frequency responses of proposed 2nd and 3rd order optimized DIs and proposed discretized mathematical models of half integrators based on them, with their respective existing operators, have been presented. Proposed integer order PSO optimized integrators as well as fractional order integrators (FOIs have been observed to outperform the existing recently published operators in their respective domains reasonably well in complete range of Nyquist frequency.
Haussaire, Jean-Matthieu; Bocquet, Marc
2016-04-01
Atmospheric chemistry models are becoming increasingly complex, with multiphasic chemistry, size-resolved particulate matter, and possibly coupled to numerical weather prediction models. In the meantime, data assimilation methods have also become more sophisticated. Hence, it will become increasingly difficult to disentangle the merits of data assimilation schemes, of models, and of their numerical implementation in a successful high-dimensional data assimilation study. That is why we believe that the increasing variety of problems encountered in the field of atmospheric chemistry data assimilation puts forward the need for simple low-order models, albeit complex enough to capture the relevant dynamics, physics and chemistry that could impact the performance of data assimilation schemes. Following this analysis, we developped a low-order coupled chemistry meteorology model named L95-GRS [1]. The advective wind is simulated by the Lorenz-95 model, while the chemistry is made of 6 reactive species and simulates ozone concentrations. With this model, we carried out data assimilation experiments to estimate the state of the system as well as the forcing parameter of the wind and the emissions of chemical compounds. This model proved to be a powerful playground giving insights on the hardships of online and offline estimation of atmospheric pollution. Building on the results on this low-order model, we test advanced data assimilation methods on a state-of-the-art chemical transport model to check if the conclusions obtained with our low-order model still stand. References [1] Haussaire, J.-M. and Bocquet, M.: A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes, Geosci. Model Dev. Discuss., 8, 7347-7394, doi:10.5194/gmdd-8-7347-2015, 2015.
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
Directory of Open Access Journals (Sweden)
Paul C. Roberts
2005-10-01
Full Text Available Studies performed to identify early events of ovarian cancer and to establish molecular markers to support early detection and development of chemopreventive regimens have been hindered by a lack of adequate cell models. Taking advantage of the spontaneous transformation of mouse ovarian surface epithelial (MDSE cells in culture, we isolated and characterized distinct transitional stages of ovarian cancer as the cells progressed from a premalignant nontumorigenic phenotype to a highly aggressive malignant phenotype. Transitional stages were concurrent with progressive increases in proliferation, anchorage-independent growth capacity, in vivo tumor formation, and aneuploidy. During neoplastic progression, our ovarian cancer model underwent distinct remodeling of the actin cytoskeleton and focal adhesion complexes, concomitant with downregulation and/or aberrant subcellular localization of two tumor-suppressor proteins Ecadherin and connexin-43. In addition, we demonstrate that epigenetic silencing of E-cadherin through promoter methylation is associated with neoplastic progression of our ovarian cancer model. These results establish critical interactions between cellular cytoskeletal remodeling and epigenetic silencing events in the progression of ovarian cancer. Thus, our MDSE model provides an excellent tool to identify both cellularand molecular changes in the early and late stages of ovarian cancer, to evaluate their regulation, and to determine their significance in an immunocompetent in vivo environment.
Cifuentes, Diana; Poittevin, Marine; Dere, Ekrem; Broquères-You, Dong; Bonnin, Philippe; Benessiano, Joëlle; Pocard, Marc; Mariani, Jean; Kubis, Nathalie; Merkulova-Rainon, Tatyana; Lévy, Bernard I
2015-01-01
Cerebrovascular impairment is frequent in patients with Alzheimer disease and is believed to influence clinical manifestation and severity of the disease. Cardiovascular risk factors, especially hypertension, have been associated with higher risk of developing Alzheimer disease. To investigate the mechanisms underlying the hypertension, Alzheimer disease cross talk, we established a mouse model of dual pathology by infusing hypertensive doses of angiotensin II into transgenic APPPS1 mice overexpressing mutated human amyloid precursor and presenilin 1 proteins. At 4.5 months, at the early stage of disease progression, only hypertensive APPPS1 mice presented impairment of temporal order memory performance in the episodic-like memory task. This cognitive deficit was associated with an increased number of cortical amyloid deposits (223±5 versus 207±5 plaques/mm(2); PHypertensive APPPS1 mice presented several cerebrovascular alterations, including a 25% reduction in cerebral microvessel density and a 30% to 40% increase in cerebral vascular amyloid deposits, as well as a decrease in vascular endothelial growth factor A expression in the brain, compared with normotensive APPPS1 mice. Moreover, the brain levels of nitric oxide synthase 1 and 3 and the nitrite/nitrate levels were reduced in hypertensive APPPS1 mice (by 49%, 34%, and 33%, respectively, compared with wild-type mice; Phypertension accelerates the development of Alzheimer disease-related structural and functional alterations, partially through cerebral vasculature impairment and reduced nitric oxide production.
Fourth-order strain-gradient phase mixture model for nanocrystalline fcc materials
Klusemann, Benjamin; Bargmann, Swantje; Estrin, Yuri
2016-12-01
The proposed modeling approach for nanocrystalline materials is an extension of the local phase mixture model introduced by Kim et al (2000 Acta Mater. 48 493-504). Local models cannot account for any non-uniformities or strain patterns, i.e. such models describe the behavior correctly only as long as it is homogeneous. In order to capture heterogeneities, the phase mixture model is augmented with gradient terms of higher order, namely second and fourth order. Different deformation mechanisms are assumed to operate in grain interior and grain boundaries concurrently. The deformation mechanism in grain boundaries is associated with diffusional mass transport along the boundaries, while in the grain interior dislocation glide as well as diffusion controlled mechanisms are considered. In particular, the mechanical response of nanostructured polycrystals is investigated. The model is capable of correctly predicting the transition of flow stress from Hall-Petch behavior in conventional grain size range to an inverse Hall-Petch relation in the nanocrystalline grain size range. The consideration of second- and fourth-order strain gradients allows non-uniformities within the strain field to represent strain patterns in combination with a regularization effect. Details of the numerical implementation are provided.
First order coupled dynamic model of flexible space structures with time-varying configurations
Wang, Jie; Li, Dongxu; Jiang, Jianping
2017-03-01
This paper proposes a first order coupled dynamic modeling method for flexible space structures with time-varying configurations for the purpose of deriving the characteristics of the system. The model considers the first time derivative of the coordinate transformation matrix between the platform's body frame and the appendage's floating frame. As a result it can accurately predict characteristics of the system even if flexible appendages rotate with complex trajectory relative to the rigid part. In general, flexible appendages are fixed on the rigid platform or forced to rotate with a slow angular velocity. So only the zero order of the transformation matrix is considered in conventional models. However, due to neglecting of time-varying terms of the transformation matrix, these models introduce severe error when appendages, like antennas, for example, rotate with a fast speed relative to the platform. The first order coupled dynamic model for flexible space structures proposed in this paper resolve this problem by introducing the first time derivative of the transformation matrix. As a numerical example, a central core with a rotating solar panel is considered and the results are compared with those given by the conventional model. It has been shown that the first order terms are of great importance on the attitude of the rigid body and dynamic response of the flexible appendage.
Approaches for Reduced Order Modeling of Electrically Actuated von Karman Microplates
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
Computational algebraic geometry for statistical modeling FY09Q2 progress.
Energy Technology Data Exchange (ETDEWEB)
Thompson, David C.; Rojas, Joseph Maurice; Pebay, Philippe Pierre
2009-03-01
This is a progress report on polynomial system solving for statistical modeling. This is a progress report on polynomial system solving for statistical modeling. This quarter we have developed our first model of shock response data and an algorithm for identifying the chamber cone containing a polynomial system in n variables with n+k terms within polynomial time - a significant improvement over previous algorithms, all having exponential worst-case complexity. We have implemented and verified the chamber cone algorithm for n+3 and are working to extend the implementation to handle arbitrary k. Later sections of this report explain chamber cones in more detail; the next section provides an overview of the project and how the current progress fits into it.
Directory of Open Access Journals (Sweden)
Alok Dhaundiyal
2016-10-01
Full Text Available This article focuses on the influence of relevant parameters of biomass pyrolysis on the numerical solution of the isothermal nth-order distributed activation energy model (DAEM using the Rayleigh distribution as the initial distribution function F(E of the activation energies. In this study, the integral upper limit, the frequency factor, the reaction order and the scale parameters are investigated. This paper also derived the asymptotic approximation for the DAEM. The influence of these parameters is used to calculate the kinetic parameters of the isothermal nth-order DAEM with the help of thermo-analytical results of TGA/DTG analysis.
Yang, Xiaofeng; Han, Daozhi
2017-02-01
In this paper, we develop a series of linear, unconditionally energy stable numerical schemes for solving the classical phase field crystal model. The temporal discretizations are based on the first order Euler method, the second order backward differentiation formulas (BDF2) and the second order Crank-Nicolson method, respectively. The schemes lead to linear elliptic equations to be solved at each time step, and the induced linear systems are symmetric positive definite. We prove that all three schemes are unconditionally energy stable rigorously. Various classical numerical experiments in 2D and 3D are performed to validate the accuracy and efficiency of the proposed schemes.
Finite size scaling and first-order phase transition in a modified XY model
Sinha, Suman; Roy, Soumen Kumar
2010-02-01
Monte Carlo simulation has been performed in a two-dimensional modified XY -model first proposed by Domany [Phys. Rev. Lett. 52, 1535 (1984)] The cluster algorithm of Wolff has been used and multiple histogram reweighting is performed. The first-order scaling behavior of the quantities such as specific heat and free-energy barrier are found to be obeyed accurately. While the lowest-order correlation function was found to decay to zero at long distance just above the transition, the next-higher-order correlation function shows a nonzero plateau.
Protein Folding under Mediation of Ordering Water: an Off-Lattice Gō-Like Model Study
Institute of Scientific and Technical Information of China (English)
ZUO Guang-Hong; HU Jun; FANG Hai-Ping
2007-01-01
@@ Water plays an important role in the structure and function of biomolecules. Water confined at the nanoscale usually exhibits phenomena not seen in bulk water, including the ice-like ordering structure on the surfaces of many substrates. We investigate the behaviour of protein folding in which the proteins are asssumed in an environment with ordering water by using of an off-lattice Gō-like model. It is found that in the physiological temperature, both the folding rate and the thermodynamic stability of the protein are greatly promoted by the existence of ordering of water.
Evaluation of the Component Chemical Potentials in Analytical Models for Ordered Alloy Phases
Directory of Open Access Journals (Sweden)
W. A. Oates
2011-01-01
Full Text Available The component chemical potentials in models of solution phases with a fixed number of sites can be evaluated easily when the Helmholtz energy is known as an analytical function of composition. In the case of ordered phases, however, the situation is less straightforward, because the Helmholtz energy is a functional involving internal order parameters. Because of this, the chemical potentials are usually obtained numerically from the calculated integral Helmholtz energy. In this paper, we show how the component chemical potentials can be obtained analytically in ordered phases via the use of virtual cluster chemical potentials. Some examples are given which illustrate the simplicity of the method.
Benchmark experiments for higher-order and full Stokes ice sheet models (ISMIP-HOM
Directory of Open Access Journals (Sweden)
F. Pattyn
2008-02-01
Full Text Available We present the results of the first ice sheet model intercomparison project for higher-order and full Stokes ice sheet models. These models are validated in a series of six benchmark experiments of which one has an analytical solution under simplifying assumptions. Five of the tests are diagnostic and one experiment is prognostic or time dependent, for both 2-D and 3-D geometries. The results show a good convergence of the different models even for high aspect ratios. A clear distinction can be made between higher-order models and those that solve the full system of equations. The latter show a significantly better agreement with each other as well as with analytical solutions, which demonstrates that they are hardly influenced by the used numerics.
Bhattacharjee, Satyaki; Matouš, Karel
2016-05-01
A new manifold-based reduced order model for nonlinear problems in multiscale modeling of heterogeneous hyperelastic materials is presented. The model relies on a global geometric framework for nonlinear dimensionality reduction (Isomap), and the macroscopic loading parameters are linked to the reduced space using a Neural Network. The proposed model provides both homogenization and localization of the multiscale solution in the context of computational homogenization. To construct the manifold, we perform a number of large three-dimensional simulations of a statistically representative unit cell using a parallel finite strain finite element solver. The manifold-based reduced order model is verified using common principles from the machine-learning community. Both homogenization and localization of the multiscale solution are demonstrated on a large three-dimensional example and the local microscopic fields as well as the homogenized macroscopic potential are obtained with acceptable engineering accuracy.
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.
Limit order book and its modeling in terms of Gibbs Grand-Canonical Ensemble
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.
Directory of Open Access Journals (Sweden)
Lin Wen Feng
2016-01-01
Full Text Available In this article, we study inventory models to determine the optimal special order and maximum saving cost of imperfective items when the supplier offers a temporary discount. The received items are not all perfect and the defectives can be screened out by the end of 100% screening process. Three models are considered according to the special order occurs at regular replenishment time, non-regular replenishment time, and screening time of economic order quantity cycle. Each model has two sub-cases to be discussed. In temporary discount problems, in general, there are integer operators in objective functions. We suggest theorems to find the closed-form solutions to these kinds of problems. Furthermore, numerical examples and sensitivity analysis are given to illustrate the results of the proposed properties and theorems.
Jalas, S.; Dornmair, I.; Lehe, R.; Vincenti, H.; Vay, J.-L.; Kirchen, M.; Maier, A. R.
2017-03-01
Particle in Cell (PIC) simulations are a widely used tool for the investigation of both laser- and beam-driven plasma acceleration. It is a known issue that the beam quality can be artificially degraded by numerical Cherenkov radiation (NCR) resulting primarily from an incorrectly modeled dispersion relation. Pseudo-spectral solvers featuring infinite order stencils can strongly reduce NCR—or even suppress it—and are therefore well suited to correctly model the beam properties. For efficient parallelization of the PIC algorithm, however, localized solvers are inevitable. Arbitrary order pseudo-spectral methods provide this needed locality. Yet, these methods can again be prone to NCR. Here, we show that acceptably low solver orders are sufficient to correctly model the physics of interest, while allowing for parallel computation by domain decomposition.
Jalas, Sören; Lehe, Rémi; Vincenti, Henri; Vay, Jean-Luc; Kirchen, Manuel; Maier, Andreas R
2016-01-01
Particle in Cell (PIC) simulations are a widely used tool for the investigation of both laser- and beam-driven plasma acceleration. It is a known issue that the beam quality can be artificially degraded by numerical Cherenkov radiation (NCR) resulting primarily from an incorrectly modeled dispersion relation. Pseudo-spectral solvers featuring infinite order stencils can strongly reduce NCR -- or even suppress it -- and are therefore well suited to correctly model the beam properties. For efficient parallelization of the PIC algorithm, however, localized solvers are inevitable. Arbitrary order pseudo-spectral methods provide this needed locality. Yet, these methods can again be prone to NCR. Here, we show that acceptably low solver orders are sufficient to correctly model the physics of interest, while allowing for efficient parallelization.
Model on medium range order in liquid Al-Fe alloys
Institute of Scientific and Technical Information of China (English)
秦敬玉; 秦绪波; 王伟民; 边秀房
2004-01-01
Numerical analysis confirms that in some cases the prepeak in the structure factor causes obvious change in the coordination number, but change in the interatomic distance can be neglected for the study of the medium range order(MRO). In order to model the MRO, it is not possible to get enough information based on the pair correlation function; however the quasi-Bragg equation can be employed to characterize the quasi-period of MRO corresponding to the prepeak position. By assuming that the interatomic distance between Fe and Al atoms hardly varies with composition, structural models were constructed based on the B2-type structure units of ordered FeAl alloy.The quasi-periods for different alloys obtained from the model structures are in reasonable agreement with the experimental ones.
Determination of Economic Order Quantity in a fuzzy EOQ Model using of GMIR Deffuzification
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Hamidreza Salmani Mojaveri
2017-03-01
Full Text Available Inappropriate inventory control policies and its incorrect implementation can cause improper operation and uncompetitive advantage of organization logistic operation in the market. Therefore, analysis inventory control policies are important to be understood, including carrying cost, ordering cost, warehouse renting cost, and buying cost. In this research, Economic Order Quantity (EOQ problem in fuzzy condition is reviewed in two different situations. The first model concerned to costs (carrying cost, ordering cost, warehouse renting cost and buying cost, which is considered as triangular fuzzy numbers. The second model was in addition to inventory the cost system, in which annual demand is also reviewed as fuzzy numbers. In each model, graded mean integration representation (GMIR deffuzification was used for parameters deffuzification. Then, the final objective from this analysis was to obtain economic quantity formula through derivation.
Yang, Qingxia; Xu, Jun; Cao, Binggang; Li, Xiuqing
2017-01-01
Identification of internal parameters of lithium-ion batteries is a useful tool to evaluate battery performance, and requires an effective model and algorithm. Based on the least square genetic algorithm, a simplified fractional order impedance model for lithium-ion batteries and the corresponding parameter identification method were developed. The simplified model was derived from the analysis of the electrochemical impedance spectroscopy data and the transient response of lithium-ion batteries with different states of charge. In order to identify the parameters of the model, an equivalent tracking system was established, and the method of least square genetic algorithm was applied using the time-domain test data. Experiments and computer simulations were carried out to verify the effectiveness and accuracy of the proposed model and parameter identification method. Compared with a second-order resistance-capacitance (2-RC) model and recursive least squares method, small tracing voltage fluctuations were observed. The maximum battery voltage tracing error for the proposed model and parameter identification method is within 0.5%; this demonstrates the good performance of the model and the efficiency of the least square genetic algorithm to estimate the internal parameters of lithium-ion batteries. PMID:28212405
Yang, Qingxia; Xu, Jun; Cao, Binggang; Li, Xiuqing
2017-01-01
Identification of internal parameters of lithium-ion batteries is a useful tool to evaluate battery performance, and requires an effective model and algorithm. Based on the least square genetic algorithm, a simplified fractional order impedance model for lithium-ion batteries and the corresponding parameter identification method were developed. The simplified model was derived from the analysis of the electrochemical impedance spectroscopy data and the transient response of lithium-ion batteries with different states of charge. In order to identify the parameters of the model, an equivalent tracking system was established, and the method of least square genetic algorithm was applied using the time-domain test data. Experiments and computer simulations were carried out to verify the effectiveness and accuracy of the proposed model and parameter identification method. Compared with a second-order resistance-capacitance (2-RC) model and recursive least squares method, small tracing voltage fluctuations were observed. The maximum battery voltage tracing error for the proposed model and parameter identification method is within 0.5%; this demonstrates the good performance of the model and the efficiency of the least square genetic algorithm to estimate the internal parameters of lithium-ion batteries.
Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data
Xie, Qing
2016-02-23
Alzheimer\\'s Disease (AD) is currently attracting much attention in elders\\' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD\\'s progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients\\' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer\\'s Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.
Order Matters: Sequencing Scale-Realistic Versus Simplified Models to Improve Science Learning
Chen, Chen; Schneps, Matthew H.; Sonnert, Gerhard
2016-10-01
Teachers choosing between different models to facilitate students' understanding of an abstract system must decide whether to adopt a model that is simplified and striking or one that is realistic and complex. Only recently have instructional technologies enabled teachers and learners to change presentations swiftly and to provide for learning based on multiple models, thus giving rise to questions about the order of presentation. Using disjoint individual growth modeling to examine the learning of astronomical concepts using a simulation of the solar system on tablets for 152 high school students (age 15), the authors detect both a model effect and an order effect in the use of the Orrery, a simplified model that exaggerates the scale relationships, and the True-to-scale, a proportional model that more accurately represents the realistic scale relationships. Specifically, earlier exposure to the simplified model resulted in diminution of the conceptual gain from the subsequent realistic model, but the realistic model did not impede learning from the following simplified model.
Reduced-Order Modeling of Parametrically Excited Micro-Electro-Mechanical Systems (MEMS
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Sangram Redkar
2010-01-01
Full Text Available Reduced-order modeling is a systematic way of constructing models with smaller number of states that can capture the “essential dynamics” of the large-scale systems, accurately. In this paper, reduced-order modeling and control techniques for parametrically excited MEMS are presented. The techniques proposed here use the Lyapunov-Floquet (L-F transformation that makes the linear part of transformed equations time invariant. In this work, three model reduction techniques for MEMS are suggested. First method is simply an application of the well-known Guyan-like reduction method to nonlinear systems. The second technique is based on singular perturbation, where the transformed system dynamics is partitioned as fast and slow dynamics and the system of differential equations is converted into a differential algebraic (DAE system. In the third technique, the concept of invariant manifold for time-periodic systems is used. The “time periodic invariant manifold” based technique yields “reducibility conditions”. This is an important result because it helps us to understand the various types of resonances present in the system. These resonances indicate a tight coupling between the system states, and in order to retain the dynamic characteristics, one has to preserve all these “resonant” states in the reduced-order model. Thus, if the “reducibility conditions” are satisfied, only then a nonlinear order reduction based on invariant manifold approach is possible. It is found that the invariant manifold approach yields the most accurate results followed by the nonlinear projection and linear technique. These methodologies are general, free from small parameter assumptions, and can be applied to a variety of MEM systems like resonators, sensors and filters. The reduced-order models can be used for parametric study, sensitivity analysis and/or controller design. The controller design is based on the reduced-order system. Thus, first the
Identification of reduced-order model for an aeroelastic system from flutter test data
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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.
Energy Technology Data Exchange (ETDEWEB)
Leng, Wei [Chinese Academy of Sciences; Ju, Lili [University of South Carolina; Gunzburger, Max [Florida State University; Price, Stephen [Los Alamos National Laboratory; Ringler, Todd [Los Alamos National Laboratory,
2012-01-01
The numerical modeling of glacier and ice sheet evolution is a subject of growing interest, in part because of the potential for models to inform estimates of global sea level change. This paper focuses on the development of a numerical model that determines the velocity and pressure fields within an ice sheet. Our numerical model features a high-fidelity mathematical model involving the nonlinear Stokes system and combinations of no-sliding and sliding basal boundary conditions, high-order accurate finite element discretizations based on variable resolution grids, and highly scalable parallel solution strategies, all of which contribute to a numerical model that can achieve accurate velocity and pressure approximations in a highly efficient manner. We demonstrate the accuracy and efficiency of our model by analytical solution tests, established ice sheet benchmark experiments, and comparisons with other well-established ice sheet models.
Phase structure of the $O(2)$ ghost model with higher-order gradient term
Péli, Z; Sailer, K
2016-01-01
The phase structure and the infrared behaviour of the Euclidean 3-dimensional $O(2)$ symmetric ghost scalar field model with higher-order derivative term has been investigated in Wegner and Houghton's renormalization group framework. The symmetric phase in which no ghost condensation occurs and the phase with restored symmetry but with a transient presence of a ghost condensate have been identified. Finiteness of the correlation length at the phase boundary hints to a phase transition of first order. The results are compared with those for the ordinary $O(2)$ symmetric scalar field model.
Reduced-order models for dynamic control of power plants based on controllability and observability
Energy Technology Data Exchange (ETDEWEB)
Ahmed, G.S.; Abdel-Magid, Y.L.
1987-07-01
A new technique for constructing dynamic equivalents of power systems is developed. The method identifies the important modes of the system utilizing a performance index based on the notions of controllability and observability. The system state variables corresponding to the retained modes are identified by inspection of the elements of the sensitivity matrix relating the eigenvalues to the state variables. The suitability of the method for obtaining reduced-order models of power systems for dynamic-control purposes is demonstrated on a single-machine infinite-bus system. Several reduced-order models are produced and their accuracy discussed. 11 refs.
Effect of assortative mixing in the second-order Kuramoto model
Peron, Thomas K DM; Rodrigues, Francisco A; Kurths, Jürgen
2015-01-01
In this paper we analyze the second-order Kuramoto model presenting a positive correlation between the heterogeneity of the connections and the natural frequencies in scale-free networks. We numerically show that discontinuous transitions emerge not just in disassortative but also in assortative networks, in contrast with the first-order model. We also find that the effect of assortativity on network synchronization can be compensated by adjusting the phase damping. Our results show that it is possible to control collective behavior of damped Kuramoto oscillators by tuning the network structure or by adjusting the dissipation related to the phases movement.
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
Second-order stochastic differential equation model as an alternative for the ALT and CALT models
Oud, J.H.L.
2010-01-01
The paper first discusses the autoregressive latent trajectory (ALT) model and presents in detail its improved version, the continuous-time autoregressive latent trajectory (CALT) model. Next, serious problems related to the linear components in the ALT and CALT models are dealt with. As an alternat
Comlekoglu, T.; Weinberg, S. H.
2017-09-01
Cardiac memory is the dependence of electrical activity on the prior history of one or more system state variables, including transmembrane potential (Vm), ionic current gating, and ion concentrations. While prior work has represented memory either phenomenologically or with biophysical detail, in this study, we consider an intermediate approach of a minimal three-variable cardiomyocyte model, modified with fractional-order dynamics, i.e., a differential equation of order between 0 and 1, to account for history-dependence. Memory is represented via both capacitive memory, due to fractional-order Vm dynamics, that arises due to non-ideal behavior of membrane capacitance; and ionic current gating memory, due to fractional-order gating variable dynamics, that arises due to gating history-dependence. We perform simulations for varying Vm and gating variable fractional-orders and pacing cycle length and measure action potential duration (APD) and incidence of alternans, loss of capture, and spontaneous activity. In the absence of ionic current gating memory, we find that capacitive memory, i.e., decreased Vm fractional-order, typically shortens APD, suppresses alternans, and decreases the minimum cycle length (MCL) for loss of capture. However, in the presence of ionic current gating memory, capacitive memory can prolong APD, promote alternans, and increase MCL. Further, we find that reduced Vm fractional order (typically less than 0.75) can drive phase 4 depolarizations that promote spontaneous activity. Collectively, our results demonstrate that memory reproduced by a fractional-order model can play a role in alternans formation and pacemaking, and in general, can greatly increase the range of electrophysiological characteristics exhibited by a minimal model.
Collar Option Model for Managing the Cost Overrun Caused by Change Orders
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Sanghyo Lee
2015-08-01
Full Text Available Effective change order management is very important in maintaining the financial sustainability of various stakeholders related to construction projects by minimizing cost overruns. In this study, we propose a zero-cost risk management approach based on the collar option model in order to control for the loss caused by change orders, the main cause of cost overruns in construction projects. We apply this model to actual projects for empirical analysis. The analysis, based on 237 projects, indicates that insurance buyers benefit from the collar option model in 46% of the cases, while insurance sellers do so in 53% of the cases. In most cases, the insurance buyer is the owner. According to the model, the owner experiences a loss when the cost overrun caused by change orders is lower than what was expected. In such cases, it is appropriate to conclude that the loss is not caused by the collar option model, but by the absence of additional revenue. However, the insurance seller suffers a loss if the cost overrun is higher than the strike price of the call option. Thus, the insurance seller needs to have expertise in construction management.
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.
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.
Selection of higher order regression models in the analysis of multi-factorial transcription data.
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Olivia Prazeres da Costa
Full Text Available INTRODUCTION: Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control, and treatment/non-treatment with interferon-γ. RESULTS: We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction, alleviating (co-occurring effects are weaker than expected from the single effects, or aggravating (stronger than expected. We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. CONCLUSIONS: We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.
The Effect of Units Lost Due to Deterioration in Fuzzy Economic Order Quantity (FEOQ Model
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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.
An efficient flexible-order model for coastal and ocean water waves
DEFF Research Database (Denmark)
Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole
of structures. The mathemathical equations for potential waves in the physical domain is transformed through $\\sigma$-mapping(s) to a time-invariant boundary-fitted domain which then becomes a basis for an efficient solution strategy. The improved 3D numerical model is based on a finite difference method......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...... properties of the numerical model together with the latests achievements....
Model Order Reductions for Stability Analysis of Islanded Microgrids With Droop Control
DEFF Research Database (Denmark)
Mariani, Valerio; Vasca, Francesco; Vásquez, Juan C.;
2015-01-01
Three-phase inverters subject to droop control are widely used in islanded microgrids to interface distributed energy resources to the network and to properly share the loads among different units. In this paper, a mathematical model for islanded microgrids with linear loads and inverters under...... frequency and voltage droop control is proposed. The model is constructed by introducing a suitable state space transformation which allows to write the closed loop model in an explicit state space form. Then, the singular perturbations technique is used to obtain reduced order models which reproduce...
Higher-order factors of the big five model of personality: a reanalysis of Digman (1997).
Mutch, Christopher
2005-02-01
Based on the results from factor analyses conducted on 14 different data sets, Digman proposed a model of two higher-order factors, or metatraits, that subsumed the Big Five personality traits. In the current article, problems in Digman's analyses were explicated, and more appropriate analyses were then conducted using the same 14 correlation matrices from Digman's study. The resultant two-factor model produced improper solutions, poor model fit indices, or both, in almost all of the 14 data sets and thus raised serious doubts about the veracity of Digman's proposed model.
A Stable Clock Error Model Using Coupled First and Second Order Gauss-Markov Processes
Carpenter, Russell; Lee, Taesul
2008-01-01
Long data outages may occur in applications of global navigation satellite system technology to orbit determination for missions that spend significant fractions of their orbits above the navigation satellite constellation(s). Current clock error models based on the random walk idealization may not be suitable in these circumstances, since the covariance of the clock errors may become large enough to overflow flight computer arithmetic. A model that is stable, but which approximates the existing models over short time horizons is desirable. A coupled first- and second-order Gauss-Markov process is such a model.
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
Directory of Open Access Journals (Sweden)
Mao Yu
2009-07-01
Full Text Available Abstract Background The identification of gene differential co-expression patterns between cancer stages is a newly developing method to reveal the underlying molecular mechanisms of carcinogenesis. Most researches of this subject lack an algorithm useful for performing a statistical significance assessment involving cancer progression. Lacking this specific algorithm is apparently absent in identifying precise gene pairs correlating to cancer progression. Results In this investigation we studied gene pair co-expression change by using a stochastic process model for approximating the underlying dynamic procedure of the co-expression change during cancer progression. Also, we presented a novel analytical method named 'Stochastic process model for Identifying differentially co-expressed Gene pair' (SIG method. This method has been applied to two well known prostate cancer data sets: hormone sensitive versus hormone resistant, and healthy versus cancerous. From these data sets, 428,582 gene pairs and 303,992 gene pairs were identified respectively. Afterwards, we used two different current statistical methods to the same data sets, which were developed to identify gene pair differential co-expression and did not consider cancer progression in algorithm. We then compared these results from three different perspectives: progression analysis, gene pair identification effectiveness analysis, and pathway enrichment analysis. Statistical methods were used to quantify the quality and performance of these different perspectives. They included: Re-identification Scale (RS and Progression Score (PS in progression analysis, True Positive Rate (TPR in gene pair analysis, and Pathway Enrichment Score (PES in pathway analysis. Our results show small values of RS and large values of PS, TPR, and PES; thus, suggesting that gene pairs identified by the SIG method are highly correlated with cancer progression, and highly enriched in disease-specific pathways. From
Using higher-order Markov models to reveal flow-based communities in networks
Salnikov, Vsevolod; Lambiotte, Renaud
2016-01-01
Complex systems made of interacting elements are commonly abstracted as networks, in which nodes are associated with dynamic state variables, whose evolution is driven by interactions mediated by the edges. Markov processes have been the prevailing paradigm to model such a network-based dynamics, for instance in the form of random walks or other types of diffusions. Despite the success of this modelling perspective for numerous applications, it represents an over-simplification of several real-world systems. Importantly, simple Markov models lack memory in their dynamics, an assumption often not realistic in practice. Here, we explore possibilities to enrich the system description by means of second-order Markov models, exploiting empirical pathway information. We focus on the problem of community detection and show that standard network algorithms can be generalized in order to extract novel temporal information about the system under investigation. We also apply our methodology to temporal networks, where w...
Eighth-order phase-field-crystal model for two-dimensional crystallization
Jaatinen, A.; Ala-Nissila, T.
2010-12-01
We present a derivation of the recently proposed eighth-order phase-field crystal model [A. Jaatinen , Phys. Rev. E 80, 031602 (2009)10.1103/PhysRevE.80.031602] for the crystallization of a solid from an undercooled melt. The model is used to study the planar growth of a two-dimensional hexagonal crystal, and the results are compared against similar results from dynamical density functional theory of Marconi and Tarazona, as well as other phase-field crystal models. We find that among the phase-field crystal models studied, the eighth-order fitting scheme gives results in good agreement with the density functional theory for both static and dynamic properties, suggesting it is an accurate and computationally efficient approximation to the density functional theory.
Mixed Lp Estimators Variety for Model Order Reduction in Control Oriented System Identification
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Christophe Corbier
2015-01-01
Full Text Available A new family of MLE type Lp estimators for model order reduction in dynamical systems identification is presented in this paper. A family of Lp distributions proposed in this work combines Lp2 (1
A HIGHER-ORDER NON-HYDROSTATIC MODEL FOR SIMULATING WAVE PROPAGATION OVER IRREGULAR BOTTOMS
Institute of Scientific and Technical Information of China (English)
AI Cong-fang; XING Yah; JIN Sheng
2011-01-01
A higher-order non-hydrostatic model is developed to simulate the wave propagation over irregular bottoms based on a vertical boundary-fitted coordinate system.In the model,an explicit projection method is adopted to solve the unsteady Euler equations.Advection terms are integrated explicitly with the MacCormack's scheme,with a second-order accuracy in both space and time.Two classical examples of surface wave propagation are used to demonstrate the capability of the model.It is found that the model with only two vertical layers could accurately simulate the motion of waves,including wave shoaling,nonlinearity,dispersion,refraction,and diffraction phenomena.
A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring [PowerPoint
Energy Technology Data Exchange (ETDEWEB)
Roettgen, Dan [Wisc; Seeger, Benjamin [Stuttgart; Tai, Wei Che [Washington; Baek, Seunghun [Michigan; Dossogne, Tilan [Liege; Allen, Matthew S [Wisc; Kuether, Robert J.; Brake, Matthew Robert; Mayes, Randall L.
2016-01-01
Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.
A Low Order Model for Analyzing effects of Blade Fatigue Load Control
DEFF Research Database (Denmark)
Kallesøe, Bjarne Skovmose
2006-01-01
, and torsional blade oscillations, and rotor speed). The aerodynamics is described by a model of unsteady aerodynamic. The equations of motion are derived in nonlinear and linear form. The linear equations of motion are used for stability analysis and control design. The nonlinear equations of motion are used...... for time simulations to evaluate control performance. The stability analysis shows that the model is capable of predicting classical flutter, and stall-induced vibrations. The results from the stability analysis are compared with known results, showing good agreement. The model is used to compare......A new low order mathematical model is introduced to analyse blade dynamics and blade load reducing control strategies for wind turbines. The model consists of a typical wing section model combined with a rotor speed model, leading to four structural degrees of freedom (flapwise, edgewise...
A Comparison of Reduced Order Modeling Techniques Used in Dynamic Substructuring.
Energy Technology Data Exchange (ETDEWEB)
Roettgen, Dan; Seegar, Ben; Tai, Wei Che; Baek, Seunghun; Dossogne, Tilan; Allen, Matthew; Kuether, Robert J.; Brake, Matthew Robert; Mayes, Randall L.
2015-10-01
Experimental dynamic substructuring is a means whereby a mathematical model for a substructure can be obtained experimentally and then coupled to a model for the rest of the assembly to predict the response. Recently, various methods have been proposed that use a transmission simulator to overcome sensitivity to measurement errors and to exercise the interface between the substructures; including the Craig-Bampton, Dual Craig-Bampton, and Craig-Mayes methods. This work compares the advantages and disadvantages of these reduced order modeling strategies for two dynamic substructuring problems. The methods are first used on an analytical beam model to validate the methodologies. Then they are used to obtain an experimental model for structure consisting of a cylinder with several components inside connected to the outside case by foam with uncertain properties. This represents an exceedingly difficult structure to model and so experimental substructuring could be an attractive way to obtain a model of the system.
Third-order analysis of pseudopotential lattice Boltzmann model for multiphase flow
Huang, Rongzong
2016-01-01
In this work, a third-order Chapman-Enskog analysis of the multiple-relaxation-time (MRT) pseudopotential lattice Boltzmann (LB) model for multiphase flow is performed for the first time. The leading terms on the interaction force, consisting of an anisotropic and an isotropic term, are successfully identified in the third-order macroscopic equation recovered by the lattice Boltzmann equation (LBE), and then new mathematical insights into the pseudopotential LB model are provided. For the third-order anisotropic term, numerical tests show that it can cause the stationary droplet to become out-of-round, which suggests the isotropic property of the LBE needs to be seriously considered in the pseudopotential LB model. By adopting the classical equilibrium moment or setting the so-called "magic" parameter to 1/12, the anisotropic term can be eliminated, which is found from the present third-order analysis and also validated numerically. As for the third-order isotropic term, when and only when it is considered, a...
Directory of Open Access Journals (Sweden)
Peter Bacchetti
Full Text Available BACKGROUND: Fibrosis stages from liver biopsies reflect liver damage from hepatitis C infection, but analysis is challenging due to their ordered but non-numeric nature, infrequent measurement, misclassification, and unknown infection times. METHODS: We used a non-Markov multistate model, accounting for misclassification, with multiple imputation of unknown infection times, applied to 1062 participants of whom 159 had multiple biopsies. Odds ratios (OR quantified the estimated effects of covariates on progression risk at any given time. RESULTS: Models estimated that progression risk decreased the more time participants had already spent in the current stage, African American race was protective (OR 0.75, 95% confidence interval 0.60 to 0.95, p = 0.018, and older current age increased risk (OR 1.33 per decade, 95% confidence interval 1.15 to 1.54, p = 0.0002. When controlled for current age, older age at infection did not appear to increase risk (OR 0.92 per decade, 95% confidence interval 0.47 to 1.79, p = 0.80. There was a suggestion that co-infection with human immunodeficiency virus increased risk of progression in the era of highly active antiretroviral treatment beginning in 1996 (OR 2.1, 95% confidence interval 0.97 to 4.4, p = 0.059. Other examined risk factors may influence progression risk, but evidence for or against this was weak due to wide confidence intervals. The main results were essentially unchanged using different assumed misclassification rates or imputation of age of infection. DISCUSSION: The analysis avoided problems inherent in simpler methods, supported the previously suspected protective effect of African American race, and suggested that current age rather than age of infection increases risk. Decreasing risk of progression with longer time already spent in a stage was also previously found for post-transplant progression. This could reflect varying disease activity, with recent progression indicating
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...
Modelling the Formation of Liver Zones within the Scope of Fractional Order Derivative
Directory of Open Access Journals (Sweden)
Abdon Atangana
2014-01-01
Full Text Available We develop and extend earlier results related to mathematical modelling of the liver formation zone by the adoption of noninteger order derivative. The hidden uncertainties in the model are captured and controlled thanks to the Caputo derivative. The stationary states are investigated and the time-dependent solution is approximated using two recent iteration methods. In particular, we discuss the convergence of these methods by constructing a suitable Hilbert space.
Modelling the Formation of Liver Zones within the Scope of Fractional Order Derivative
Atangana, Abdon; Oukouomi Noutchie, Suares Clovis
2014-01-01
We develop and extend earlier results related to mathematical modelling of the liver formation zone by the adoption of noninteger order derivative. The hidden uncertainties in the model are captured and controlled thanks to the Caputo derivative. The stationary states are investigated and the time-dependent solution is approximated using two recent iteration methods. In particular, we discuss the convergence of these methods by constructing a suitable Hilbert space. PMID:25276791
1991-04-29
22217-5000 1 1 1 11. TITLE (incde Securiy Clasicaton) A MODEL FOR SEQUENTIAL FIRST ORDER PHAGE TRANSITIONS OCCURRING IN THE UNDERPOTENTIAL DEPOSITION ...block number) FIELD GROUP SUB-GROUP 3 RACT (Continue on reverse if necessary and identify by block number) A model for the underpotential deposition of...this application we study the underpotential deposition of Cu on a Au(III) surface in the presence of sulfate ions. The voltammogram of the
Energy Technology Data Exchange (ETDEWEB)
Wagner, M.
2010-10-01
The inherent variability of the solar resource presents a unique challenge for CSP systems. Incident solar irradiation can fluctuate widely over a short time scale, but plant performance must be assessed for long time periods. As a result, annual simulations with hourly (or sub-hourly) timesteps are the norm in CSP analysis. A highly detailed power cycle model provides accuracy but tends to suffer from prohibitively long run-times; alternatively, simplified empirical models can run quickly but don?t always provide enough information, accuracy, or flexibility for the modeler. The ideal model for feasibility-level analysis incorporates both the detail and accuracy of a first-principle model with the low computational load of a regression model. The work presented in this paper proposes a methodology for organizing and extracting information from the performance output of a detailed model, then using it to develop a flexible reduced-order regression model in a systematic and structured way. A similar but less generalized approach for characterizing power cycle performance and a reduced-order modeling methodology for CFD analysis of heat transfer from electronic devices have been presented. This paper builds on these publications and the non-dimensional approach originally described.
A microstructure- and surface energy-dependent third-order shear deformation beam model
Gao, X.-L.; Zhang, G. Y.
2015-08-01
A new non-classical third-order shear deformation model is developed for Reddy-Levinson beams using a variational formulation based on Hamilton's principle. A modified couple stress theory and a surface elasticity theory are employed. The equations of motion and complete boundary conditions for the beam are obtained simultaneously. The new model contains a material length scale parameter to account for the microstructure effect and three surface elastic constants to describe the surface energy effect. Also, Poisson's effect is incorporated in the new beam model. The current non-classical model recovers the classical elasticity-based third-order shear deformation beam model as a special case when the microstructure, surface energy and Poisson's effects are all suppressed. In addition, the newly developed beam model includes the models considering the microstructure dependence or the surface energy effect alone as limiting cases and reduces to two existing models for Bernoulli-Euler and Timoshenko beams incorporating the microstructure and surface energy effects. To illustrate the new model, the static bending and free vibration problems of a simply supported beam loaded by a concentrated force are analytically solved by directly applying the general formulas derived. For the static bending problem, the numerical results reveal that both the deflection and rotation of the simply supported beam predicted by the current model are smaller than those predicted by the classical model. Also, it is observed that the differences in the deflection and rotation predicted by the two beam models are very large when the beam thickness is sufficiently small, but they are diminishing with the increase in the beam thickness. For the free vibration problem, it is found that the natural frequency predicted by the new model is higher than that predicted by the classical beam model, and the difference is significant for very thin beams. These predicted trends of the size effect at the
Averaging principle for second-order approximation of heterogeneous models with homogeneous models.
Fibich, Gadi; Gavious, Arieh; Solan, Eilon
2012-11-27
Typically, models with a heterogeneous property are considerably harder to analyze than the corresponding homogeneous models, in which the heterogeneous property is replaced by its average value. In this study we show that any outcome of a heterogeneous model that satisfies the two properties of differentiability and symmetry is O(ε(2)) equivalent to the outcome of the corresponding homogeneous model, where ε is the level of heterogeneity. We then use this averaging principle to obtain new results in queuing theory, game theory (auctions), and social networks (marketing).
The dual quark condensate in local and nonlocal NJL models: An order parameter for deconfinement?
Directory of Open Access Journals (Sweden)
Federico Marquez
2015-07-01
Full Text Available We study the behavior of the dual quark condensate Σ1 in the Nambu–Jona-Lasinio (NJL model and its nonlocal variant. In quantum chromodynamics Σ1 can be related to the breaking of the center symmetry and is therefore an (approximate order parameter of confinement. The deconfinement transition is then signaled by a strong rise of Σ1 as a function of temperature. However, a similar behavior is also seen in the NJL model, which is known to have no confinement. Indeed, it was shown that in this model the rise of Σ1 is triggered by the chiral phase transition. In order to shed more light on this issue, we calculate Σ1 for several variants of the NJL model, some of which have been suggested to be confining. Switching between “confining” and “non-confining” models and parametrizations we find no qualitative difference in the behavior of Σ1, namely, it always rises in the region of the chiral phase transition. We conclude that without having established a relation to the center symmetry in a given model, Σ1 should not blindly be regarded as an order parameter of confinement.