Energy Technology Data Exchange (ETDEWEB)
Hu, R. [Argonne National Lab. (ANL), Argonne, IL (United States)
2017-09-01
This report documents the initial progress on the reduced-order flow model developments in SAM for thermal stratification and mixing modeling. Two different modeling approaches are pursued. The first one is based on one-dimensional fluid equations with additional terms accounting for the thermal mixing from both flow circulations and turbulent mixing. The second approach is based on three-dimensional coarse-grid CFD approach, in which the full three-dimensional fluid conservation equations are modeled with closure models to account for the effects of turbulence.
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.
Fernandez, R.; Deveaux, V.
2010-01-01
We provide a formal definition and study the basic properties of partially ordered chains (POC). These systems were proposed to model textures in image processing and to represent independence relations between random variables in statistics (in the later case they are known as Bayesian networks).
On nonlinear reduced order modeling
International Nuclear Information System (INIS)
Abdel-Khalik, Hany S.
2011-01-01
When applied to a model that receives n input parameters and predicts m output responses, a reduced order model estimates the variations in the m outputs of the original model resulting from variations in its n inputs. While direct execution of the forward model could provide these variations, reduced order modeling plays an indispensable role for most real-world complex models. This follows because the solutions of complex models are expensive in terms of required computational overhead, thus rendering their repeated execution computationally infeasible. To overcome this problem, reduced order modeling determines a relationship (often referred to as a surrogate model) between the input and output variations that is much cheaper to evaluate than the original model. While it is desirable to seek highly accurate surrogates, the computational overhead becomes quickly intractable especially for high dimensional model, n ≫ 10. In this manuscript, we demonstrate a novel reduced order modeling method for building a surrogate model that employs only 'local first-order' derivatives and a new tensor-free expansion to efficiently identify all the important features of the original model to reach a predetermined level of accuracy. This is achieved via a hybrid approach in which local first-order derivatives (i.e., gradient) of a pseudo response (a pseudo response represents a random linear combination of original model’s responses) are randomly sampled utilizing a tensor-free expansion around some reference point, with the resulting gradient information aggregated in a subspace (denoted by the active subspace) of dimension much less than the dimension of the input parameters space. The active subspace is then sampled employing the state-of-the-art techniques for global sampling methods. The proposed method hybridizes the use of global sampling methods for uncertainty quantification and local variational methods for sensitivity analysis. In a similar manner to
Randomized Local Model Order Reduction
Buhr, Andreas; Smetana, Kathrin
2017-01-01
In this paper we propose local approximation spaces for localized model order reduction procedures such as domain decomposition and multiscale methods. Those spaces are constructed from local solutions of the partial differential equation (PDE) with random boundary conditions, yield an approximation
A multiscale approach for modeling atherosclerosis progression.
Exarchos, Konstantinos P; Carpegianni, Clara; Rigas, Georgios; Exarchos, Themis P; Vozzi, Federico; Sakellarios, Antonis; Marraccini, Paolo; Naka, Katerina; Michalis, Lambros; Parodi, Oberdan; Fotiadis, Dimitrios I
2015-03-01
Progression of atherosclerotic process constitutes a serious and quite common condition due to accumulation of fatty materials in the arterial wall, consequently posing serious cardiovascular complications. In this paper, we assemble and analyze a multitude of heterogeneous data in order to model the progression of atherosclerosis (ATS) in coronary vessels. The patient's medical record, biochemical analytes, monocyte information, adhesion molecules, and therapy-related data comprise the input for the subsequent analysis. As indicator of coronary lesion progression, two consecutive coronary computed tomography angiographies have been evaluated in the same patient. To this end, a set of 39 patients is studied using a twofold approach, namely, baseline analysis and temporal analysis. The former approach employs baseline information in order to predict the future state of the patient (in terms of progression of ATS). The latter is based on an approach encompassing dynamic Bayesian networks whereby snapshots of the patient's status over the follow-up are analyzed in order to model the evolvement of ATS, taking into account the temporal dimension of the disease. The quantitative assessment of our work has resulted in 93.3% accuracy for the case of baseline analysis, and 83% overall accuracy for the temporal analysis, in terms of modeling and predicting the evolvement of ATS. It should be noted that the application of the SMOTE algorithm for handling class imbalance and the subsequent evaluation procedure might have introduced an overestimation of the performance metrics, due to the employment of synthesized instances. The most prominent features found to play a substantial role in the progression of the disease are: diabetes, cholesterol and cholesterol/HDL. Among novel markers, the CD11b marker of leukocyte integrin complex is associated with coronary plaque progression.
Ordering of diagnostic information in encoded medical images. Accuracy progression
Przelaskowski, A.; Jóźwiak, R.; Krzyżewski, T.; Wróblewska, A.
2008-03-01
A concept of diagnostic accuracy progression for embedded coding of medical images was presented. Implementation of JPEG2000 encoder with a modified PCRD optimization algorithm was realized and initially verified as a tool for accurate medical image streaming. Mean square error as a distortion measure was replaced by other numerical measures to revise quality progression according to diagnostic importance of successively encoded image information. A faster increment of image diagnostic importance during reconstruction of initial packets of code stream was reached. Modified Jasper code was initially tested on a set of mammograms containing clusters of microcalcifications and malignant masses, and other radiograms. Teleradiologic applications were considered as the first area of interests.
Progress in all-order breakup reaction theories
Indian Academy of Sciences (India)
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 ... R Chatterjee1. Department of Physics, Indian Institute of Technology, Roorkee 247 667, India ...
Generalized Reduced Order Model Generation, Phase I
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...
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...
Progress in modeling asphaltene precipitation
Energy Technology Data Exchange (ETDEWEB)
Yarranton, H.W.; Satyro, M.A. [Department of Chemical and Petroleum Engineering, University of Calgary (Canada); Taylor, S.D. [DBR Technology Center, Schlumberger (Canada)
2011-07-01
In the oil industry, asphaltene precipitation may happen when heavy oils are in contact with a solvent, crude oils are blended or when light oils containing asphaltenes are depressurized. Asphaltene precipitation has proven challenging to predict and the aim of this paper is to evaluate 2 different approaches for asphaltene precipitation modeling: regular solution and equation of state. Two case were studied: an Athabasca bitumen diluted with n-alkane and a depressurized Gulf of Mexico crude oil and both models were applied to each case. Results showed that both thermodynamic models are, to a limited extend, suitable for asphaltene precipitation prediction but they do not offer a correct prediction at low asphaltene concentrations and the equation of state cannot predict asphaltene precipitation from depressurized crude oils. This study showed the limits of current models in predicting precipitation of asphaltene and provided a trick to overcome these deficiencies; further work should be undertaken to develop a consistent approach.
Recent progress in sorption mechanisms and models
International Nuclear Information System (INIS)
Fedoroff, M.; Lefevre, G.
2005-01-01
Full text of publication follows: Sorption-desorption phenomena play an important role in the migration of radioactive species in surface and underground waters. In order to predict the transport of these species, we need a good knowledge of sorption processes and data, together with reliable models able to be included in transport calculation. Traditional approaches based on experimentally determined distribution coefficients (Kd) and sorption isotherms have a limited predictive capability, since they are very sensitive to the numerous parameters characterizing the solution and the solid. Models based on thermodynamic equilibria were developed to account for the influence these parameters: the ion exchange model and the surface complexation models (2-pK mono-site, 1-pK multi-site, with several different electrostatic models: CCM, DLM, BSM, TLM,...). Although these models are very useful, studies performed in recent years showed that they have important theoretical and experimental limitations, which result in the fact that we must be very careful when we use them for extrapolating sorption data to long term and to large natural systems. Among all problems which can be found are: the possibility to fit a set of experimental data with different models, sometimes bad adequacy with the real sorption processes, some theoretical limitations such as a rigorous definition of reference and standard states in surface equilibria, slow kinetics which prevent from equilibrium achievement, irreversibility, solubility and evolution of solid phases... Through the increase of the number of sensitive spectroscopic methods, we are now able to know more about sorption processes at the atomic scale. Models such as the 1-pK CD-MUSIC model can account for the influence of orientation of the faces of the solid. More and more examples of the influence of this orientation on the sorption properties are known. Calculations performed by 'ab initio' modeling is also useful to predict the
Generalized linear model for partially ordered data.
Zhang, Qiang; Ip, Edward Haksing
2012-01-13
Within the rich literature on generalized linear models, substantial efforts have been devoted to models for categorical responses that are either completely ordered or completely unordered. Few studies have focused on the analysis of partially ordered outcomes, which arise in practically every area of study, including medicine, the social sciences, and education. To fill this gap, we propose a new class of generalized linear models--the partitioned conditional model--that includes models for both ordinal and unordered categorical data as special cases. We discuss the specification of the partitioned conditional model and its estimation. We use an application of the method to a sample of the National Longitudinal Study of Youth to illustrate how the new method is able to extract from partially ordered data useful information about smoking youths that is not possible using traditional methods. Copyright © 2011 John Wiley & Sons, Ltd.
Amyotrophic lateral sclerosis disease progression model.
Gomeni, Roberto; Fava, Maurizio
2014-03-01
Our objective was to develop: 1) a longitudinal model to describe amyotrophic lateral sclerosis (ALS) disease progression using the revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R); and 2) a probabilistic model to estimate the presence of clusters of trajectories in ALS progression over 12 months of treatment. Three hundred and thirty-eight patients treated with placebo from the PRO-ACT database were included in the analyses. A non-linear Weibull model best described the ALS disease progression, and a stepwise logistic regression approach was used to select the variables predicting a slow or fast disease progression. Results identified two clusters of trajectories: 1) slow disease progressors (46% of patients with a change from baseline of 13%); 2) fast disease progressors (54% of patients with a change from baseline of 49%). ROC curve analysis estimated the optimal cut-off for classifying patients as slow or fast disease progressors given ALSFRS-R measurements at 2-4 weeks. Results showed that the degree of ALS disease progression quantified by the ALSFRS-R symptomatic change on placebo is highly heterogeneous. In conclusion, this finding indicates the potential interest of disease progression models for implementing a population enrichment strategy to control the level of heterogeneity in the patients included in new trials.
XY model with higher-order exchange.
Žukovič, Milan; Kalagov, Georgii
2017-08-01
An XY model, generalized by inclusion of up to an infinite number of higher-order pairwise interactions with an exponentially decreasing strength, is studied by spin-wave theory and Monte Carlo simulations. At low temperatures the model displays a quasi-long-range-order phase characterized by an algebraically decaying correlation function with the exponent η=T/[2πJ(p,α)], nonlinearly dependent on the parameters p and α that control the number of the higher-order terms and the decay rate of their intensity, respectively. At higher temperatures the system shows a crossover from the continuous Berezinskii-Kosterlitz-Thouless to the first-order transition for the parameter values corresponding to a highly nonlinear shape of the potential well. The role of topological excitations (vortices) in changing the nature of the transition is discussed.
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.
Optimal inventory management and order book modeling
Baradel, Nicolas
2018-02-16
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.
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.
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.
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.
Are Quantum Models for Order Effects Quantum?
Moreira, Catarina; Wichert, Andreas
2017-12-01
The application of principles of Quantum Mechanics in areas outside of physics has been getting increasing attention in the scientific community in an emergent disciplined called Quantum Cognition. These principles have been applied to explain paradoxical situations that cannot be easily explained through classical theory. In quantum probability, events are characterised by a superposition state, which is represented by a state vector in a N-dimensional vector space. The probability of an event is given by the squared magnitude of the projection of this superposition state into the desired subspace. This geometric approach is very useful to explain paradoxical findings that involve order effects, but do we really need quantum principles for models that only involve projections? This work has two main goals. First, it is still not clear in the literature if a quantum projection model has any advantage towards a classical projection. We compared both models and concluded that the Quantum Projection model achieves the same results as its classical counterpart, because the quantum interference effects play no role in the computation of the probabilities. Second, it intends to propose an alternative relativistic interpretation for rotation parameters that are involved in both classical and quantum models. In the end, instead of interpreting these parameters as a similarity measure between questions, we propose that they emerge due to the lack of knowledge concerned with a personal basis state and also due to uncertainties towards the state of world and towards the context of the questions.
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,…
Decimative Spectral Estimation with Unconstrained Model Order
Directory of Open Access Journals (Sweden)
Stavroula-Evita Fotinea
2012-01-01
Full Text Available This paper presents a new state-space method for spectral estimation that performs decimation by any factor, it makes use of the full set of data and brings further apart the poles under consideration, while imposing almost no constraints to the size of the Hankel matrix (model order, as decimation increases. It is compared against two previously proposed techniques for spectral estimation (along with derived decimative versions, that lie among the most promising methods in the field of spectroscopy, where accuracy of parameter estimation is of utmost importance. Moreover, it is compared against a state-of-the-art purely decimative method proposed in literature. Experiments performed on simulated NMR signals prove the new method to be more robust, especially for low signal-to-noise ratio.
Modelling Progressive Failure in Rock-slopes
Pons, M. Güell I.; Jaboyedoff, M.
2009-04-01
Rock failures are common in Alpine mountain chains and pose a threat to life and infrastructures. In general, rock slope stability is an interplay between existing discontinuities and development of new ones in intact material. In this work, we study progressive failure by means of numerical methods at multiple scales and using distinct element methods (DEM). Distinct element methods are of advantage because they account for discontinuities and are able to simulate the development of failure in time. The use of micro-parameters instead of constitutive laws allows studying the influence of heterogeneities present in the rock mass. In the first case, the code PFC-2D is used at the slope scale to test the influence of the slope geometry, the joint sets distribution and the joint set persistence in the case of toppling failures under various triggering mechanisms. Heterogeneity properties (cohesion and friction angle) are distributed randomly to simulate natural rock variability. In the second case, a cellular automata model, which is based on concepts of progressive failure in disordered systems, is used to explain the role of heterogeneities in the fracture process at a small scale. The results provide a link to time-to-failure predictions observed in some field cases. This study aims to be a base for the development of a model which permits to understand why some rock masses accelerate until global failure while other are capable to stabilize under the same conditions.
Modelling amyotrophic lateral sclerosis: progress and possibilities
Directory of Open Access Journals (Sweden)
Philip Van Damme
2017-05-01
Full Text Available Amyotrophic lateral sclerosis (ALS is a neurodegenerative disorder that primarily affects the motor system and presents with progressive muscle weakness. Most patients survive for only 2-5 years after disease onset, often due to failure of the respiratory muscles. ALS is a familial disease in ∼10% of patients, with the remaining 90% developing sporadic ALS. Over the past decade, major advances have been made in our understanding of the genetics and neuropathology of ALS. To date, around 20 genes are associated with ALS, with the most common causes of typical ALS associated with mutations in SOD1, TARDBP, FUS and C9orf72. Advances in our understanding of the genetic basis of ALS have led to the creation of different models of this disease. The molecular pathways that have emerged from these systems are more heterogeneous than previously anticipated, ranging from protein aggregation and defects in multiple key cellular processes in neurons, to dysfunction of surrounding non-neuronal cells. Here, we review the different model systems used to study ALS and discuss how they have contributed to our current knowledge of ALS disease mechanisms. A better understanding of emerging disease pathways, the detrimental effects of the various gene mutations and the causes underlying motor neuron denegation in sporadic ALS will accelerate progress in the development of novel treatments.
MODELING THE SELF-ASSEMBLY OF ORDERED NANOPOROUS MATERIALS
Energy Technology Data Exchange (ETDEWEB)
Monson, Peter [University of Massachusetts; Auerbach, Scott [University of Massachusetts
2017-11-13
This report describes progress on a collaborative project on the multiscale modeling of the assembly processes in the synthesis of nanoporous materials. Such materials are of enormous importance in modern technology with application in the chemical process industries, biomedicine and biotechnology as well as microelectronics. The project focuses on two important classes of materials: i) microporous crystalline materials, such as zeolites, and ii) ordered mesoporous materials. In the first case the pores are part of the crystalline structure, while in the second the structures are amorphous on the atomistic length scale but where surfactant templating gives rise to order on the length scale of 2 - 20 nm. We have developed a modeling framework that encompasses both these kinds of materials. Our models focus on the assembly of corner sharing silica tetrahedra in the presence of structure directing agents. We emphasize a balance between sufficient realism in the models and computational tractibility given the complex many-body phenomena. We use both on-lattice and off-lattice models and the primary computational tools are Monte Carlo simulations with sampling techniques and ensembles appropriate to specific situations. Our modeling approach is the first to capture silica polymerization, nanopore crystallization, and mesopore formation through computer-simulated self assembly.
Advanced Fluid Reduced Order Models for Compressible Flow.
Energy Technology Data Exchange (ETDEWEB)
Tezaur, Irina Kalashnikova [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Fike, Jeffrey A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Carlberg, Kevin Thomas [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Maddix, Danielle [Stanford Univ., CA (United States); Mussoni, Erin E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Balajewicz, Maciej [Univ. of Illinois, Urbana-Champaign, IL (United States)
2017-09-01
This report summarizes fiscal year (FY) 2017 progress towards developing and implementing within the SPARC in-house finite volume flow solver advanced fluid reduced order models (ROMs) for compressible captive-carriage flow problems of interest to Sandia National Laboratories for the design and qualification of nuclear weapons components. The proposed projection-based model order reduction (MOR) approach, known as the Proper Orthogonal Decomposition (POD)/Least- Squares Petrov-Galerkin (LSPG) method, can substantially reduce the CPU-time requirement for these simulations, thereby enabling advanced analyses such as uncertainty quantification and de- sign optimization. Following a description of the project objectives and FY17 targets, we overview briefly the POD/LSPG approach to model reduction implemented within SPARC . We then study the viability of these ROMs for long-time predictive simulations in the context of a two-dimensional viscous laminar cavity problem, and describe some FY17 enhancements to the proposed model reduction methodology that led to ROMs with improved predictive capabilities. Also described in this report are some FY17 efforts pursued in parallel to the primary objective of determining whether the ROMs in SPARC are viable for the targeted application. These include the implemen- tation and verification of some higher-order finite volume discretization methods within SPARC (towards using the code to study the viability of ROMs on three-dimensional cavity problems) and a novel structure-preserving constrained POD/LSPG formulation that can improve the accuracy of projection-based reduced order models. We conclude the report by summarizing the key takeaways from our FY17 findings, and providing some perspectives for future work.
Reduced order model of draft tube flow
International Nuclear Information System (INIS)
Rudolf, P; Štefan, D
2014-01-01
Swirling flow with compact coherent structures is very good candidate for proper orthogonal decomposition (POD), i.e. for decomposition into eigenmodes, which are the cornerstones of the flow field. Present paper focuses on POD of steady flows, which correspond to different operating points of Francis turbine draft tube flow. Set of eigenmodes is built using a limited number of snapshots from computational simulations. Resulting reduced order model (ROM) describes whole operating range of the draft tube. ROM enables to interpolate in between the operating points exploiting the knowledge about significance of particular eigenmodes and thus reconstruct the velocity field in any operating point within the given range. Practical example, which employs axisymmetric simulations of the draft tube flow, illustrates accuracy of ROM in regions without vortex breakdown together with need for higher resolution of the snapshot database close to location of sudden flow changes (e.g. vortex breakdown). ROM based on POD interpolation is very suitable tool for insight into flow physics of the draft tube flows (especially energy transfers in between different operating points), for supply of data for subsequent stability analysis or as an initialization database for advanced flow simulations
Vishik, Inna
2018-03-29
In the course of seeking the microscopic mechanism of superconductivity in cuprate high temperature superconductors, the pseudogap phase\\textemdash the very abnormal 'normal' state on the hole-doped side\\textemdash has proven to be as big of a quandary as superconductivity itself. Angle-resolved photoemission spectroscopy (ARPES) is a powerful tool for assessing the momentum-dependent phenomenology of the pseudogap, and recent technological developments have permitted a more detailed understanding. This report reviews recent progress in understanding the relationship between superconductivity and the pseudogap, the Fermi arc phenomena, and the relationship between charge order and pseudogap from the perspective of ARPES measurements. © 2018 IOP Publishing Ltd.
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
Model Order Reduction of Aeroservoelastic Model of Flexible Aircraft
Wang, Yi; Song, Hongjun; Pant, Kapil; Brenner, Martin J.; Suh, Peter
2016-01-01
This paper presents a holistic model order reduction (MOR) methodology and framework that integrates key technological elements of sequential model reduction, consistent model representation, and model interpolation for constructing high-quality linear parameter-varying (LPV) aeroservoelastic (ASE) reduced order models (ROMs) of flexible aircraft. The sequential MOR encapsulates a suite of reduction techniques, such as truncation and residualization, modal reduction, and balanced realization and truncation to achieve optimal ROMs at grid points across the flight envelope. The consistence in state representation among local ROMs is obtained by the novel method of common subspace reprojection. Model interpolation is then exploited to stitch ROMs at grid points to build a global LPV ASE ROM feasible to arbitrary flight condition. The MOR method is applied to the X-56A MUTT vehicle with flexible wing being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies demonstrated that relative to the fullorder model, our X-56A ROM can accurately and reliably capture vehicles dynamics at various flight conditions in the target frequency regime while the number of states in ROM can be reduced by 10X (from 180 to 19), and hence, holds great promise for robust ASE controller synthesis and novel vehicle design.
Model order reduction using eigen algorithm
African Journals Online (AJOL)
DR OKE
to use either for design or analysis. Hence, it is ... directly from the Eigen algorithm while the zeros are determined through factor division algorithm to obtain the reduced order system. ..... V. Singh, Chandra and H. Kar, “Improved Routh Pade approximationss: A computer aided approach”, IEEE Transaction on. Automat ...
Order and disorder in product innovation models
Pina e Cunha, Miguel; Gomes, Jorge F.S.; Gomes, J.F.
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
Model Order Reduction: Application to Electromagnetic Problems
Paquay, Yannick
2017-01-01
With the increase in computational resources, numerical modeling has grown expo- nentially these last two decades. From structural analysis to combustion modeling and electromagnetics, discretization methods–in particular the finite element method–have had a tremendous impact. Their main advantage consists in a correct representation of dynamical and nonlinear behaviors by solving equations at local scale, however the spatial discretization inherent to such approaches is also its main drawbac...
Model selection criteria : how to evaluate order restrictions
Kuiper, R.M.
2012-01-01
Researchers often have ideas about the ordering of model parameters. They frequently have one or more theories about the ordering of the group means, in analysis of variance (ANOVA) models, or about the ordering of coefficients corresponding to the predictors, in regression models.A researcher might
Model Order Reduction for Non Linear Mechanics
Pinillo, Rubén
2017-01-01
Context: Automotive industry is moving towards a new generation of cars. Main idea: Cars are furnished with radars, cameras, sensors, etc… providing useful information about the environment surrounding the car. Goals: Provide an efficient model for the radar input/output. Reducing computational costs by means of big data techniques.
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
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...... crystals. For both models, which have a nonconserved order parameter, it is found that the linear scale, R(t), of the evolving order, following quenches to below the transition temperature, grows at late times in an effectively algebraic fashion, R(t)∼tn, with exponent values which are strongly temperature...
Chen, Jonathan H; Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B
2017-05-01
Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% ( P sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Ang, Daniel; Demille, David; Doyle, John; Gabrielse, Gerald; Haefner, Jonathan; Lasner, Zack; Meisenhelder, Cole; Panda, Cristian; West, Adam; West, Elizabeth
2017-04-01
The search for the electron electric dipole moment (eEDM) is a powerful probe of fundamental physics beyond the Standard Model. In 2014, the first generation of the ACME experiment set the most stringent upper limit on the eEDM of |de | < 1 ×10-28 e . cm by means of measuring spin precession in a beam of thorium monoxide. Since then, we have implemented various improvements, such as STIRAP preparation of the experimental H state, rotational cooling, optimized apparatus geometry, and enhanced detection efficency, boosting our signal by a factor of about 400. We have also devised means to reduce the leading systematics we found in the Generation I experiment. We describe the recent progress in taking data using our Generation II apparatus and our ongoing efforts to investigate various systematics. NSF Grant 1404146.
Multiscale Reduced Order Modeling of Complex Multi-Bay Structures
2013-07-01
modeled with 96,000 degrees of freedom within Nastran . Keywords: reduced order modeling, nonlinear geometric response, finite elements 2...deformations, i.e. exhibiting geometric nonlinearity, from finite element models generated using commercial codes (e.g. Nastran , Abaqus, DYNA3D), see...reduced order model of the 9-bay panel modeled within Nastran with 96,000 degrees of freedom. An excellent agreement between the nonlinear static
A reduced order model of a quadruped walking system
International Nuclear Information System (INIS)
Sano, Akihito; Furusho, Junji; Naganuma, Nobuyuki
1990-01-01
Trot walking has recently been studied by several groups because of its stability and realizability. In the trot, diagonally opposed legs form pairs. While one pair of legs provides support, the other pair of legs swings forward in preparation for the next step. In this paper, we propose a reduced order model for the trot walking. The reduced order model is derived by using two dominant modes of the closed loop system in which the local feedback at each joint is implemented. It is shown by numerical examples that the obtained reduced order model can well approximate the original higher order model. (author)
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.
Higher-order RANS turbulence models for separated flows
National Aeronautics and Space Administration — Higher-order Reynolds-averaged Navier-Stokes (RANS) models are developed to overcome the shortcomings of second-moment RANS models in predicting separated flows....
Recent Progress in Greenland Ice Sheet Modelling
Goelzer, Heiko; Robinson, Alexander; Seroussi, Helene; Van De Wal, Roderik S.w.
2017-01-01
Purpose of Review This paper reviews the recent literature on numerical modelling of the dynamics of the Greenland ice sheet with the goal of providing an overview of advancements and to highlight important directions of future research. In particular, the review is focused on large-scale modelling
Orbital Order in Two-Orbital Hubbard Model
Honkawa, Kojiro; Onari, Seiichiro
2018-03-01
In strongly correlated multiorbital systems, various ordered phases appear. In particular, the orbital order in iron-based superconductors attracts much attention since it is considered to be the origin of the nematic state. To clarify the essential conditions for realizing orbital orders, we study the simple two-orbital (dxz,dyz) Hubbard model. We find that the orbital order, which corresponds to the nematic order, appears due to the vertex corrections even in the two-orbital model. Thus, the dxy orbital is not essential to realize the nematic orbital order. The obtained orbital order is determined by the orbital dependence and the topology of Fermi surfaces. We also find that another type of orbital order, which is rotated 45°, appears in a heavily hole-doped case.
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)
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
Spiking and bursting patterns of fractional-order Izhikevich model
Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha
2018-03-01
Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.
Mouse models of metastasis: progress and prospects
Directory of Open Access Journals (Sweden)
Laura Gómez-Cuadrado
2017-09-01
Full Text Available Metastasis is the spread of cancer cells from a primary tumor to distant sites within the body to establish secondary tumors. Although this is an inefficient process, the consequences are devastating as metastatic disease accounts for >90% of cancer-related deaths. The formation of metastases is the result of a series of events that allow cancer cells to escape from the primary site, survive in the lymphatic system or blood vessels, extravasate and grow at distant sites. The metastatic capacity of a tumor is determined by genetic and epigenetic changes within the cancer cells as well as contributions from cells in the tumor microenvironment. Mouse models have proven to be an important tool for unraveling the complex interactions involved in the metastatic cascade and delineating its many stages. Here, we critically appraise the strengths and weaknesses of the current mouse models and highlight the recent advances that have been made using these models in our understanding of metastasis. We also discuss the use of these models for testing potential therapies and the challenges associated with the translation of these findings into the provision of new and effective treatments for cancer patients.
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.
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...
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.
Energy Technology Data Exchange (ETDEWEB)
1976-01-01
Progress is reviewed in these areas: nuclear spin-lattice relaxation in ortho-para mixtures of solid deuterium below T/sub lambda/; pulsed NMR experiments of matrix isolated HCl; stimulated Raman scattering in solid hydrogen and nitrogen; and infrared line broadening of matrix isolated molecules. (GHT)
International Nuclear Information System (INIS)
1976-01-01
Progress is reviewed in these areas: nuclear spin-lattice relaxation in ortho-para mixtures of solid deuterium below T/sub lambda/; pulsed NMR experiments of matrix isolated HCl; stimulated Raman scattering in solid hydrogen and nitrogen; and infrared line broadening of matrix isolated molecules
International Nuclear Information System (INIS)
Nagler, S.E.
1989-01-01
We report on the progress of our project entitled ''X-ray Scattering Studies of Non-Equilibrium Ordering Processes.'' In-house time-resolved x-ray scattering has been used to investigate ordering kinetics in single crystal thin films of Cu 3 Au. Scaling analysis of the results shows that two dimensional kinetic behavior is observed in 260 /angstrom/ thick films. Significant improvements have been made in the local capabilities for fast time resolved measurements and data analysis. Measurements of microphase separation and ordering kinetics have been made in block-co-polymers, and experiments on Au-Cd martensitic material are continuing. 15 refs., 7 figs
User-Defined Material Model for Progressive Failure Analysis
Knight, Norman F. Jr.; Reeder, James R. (Technical Monitor)
2006-01-01
An overview of different types of composite material system architectures and a brief review of progressive failure material modeling methods used for structural analysis including failure initiation and material degradation are presented. Different failure initiation criteria and material degradation models are described that define progressive failure formulations. These progressive failure formulations are implemented in a user-defined material model (or UMAT) for use with the ABAQUS/Standard1 nonlinear finite element analysis tool. The failure initiation criteria include the maximum stress criteria, maximum strain criteria, the Tsai-Wu failure polynomial, and the Hashin criteria. The material degradation model is based on the ply-discounting approach where the local material constitutive coefficients are degraded. Applications and extensions of the progressive failure analysis material model address two-dimensional plate and shell finite elements and three-dimensional solid finite elements. Implementation details and use of the UMAT subroutine are described in the present paper. Parametric studies for composite structures are discussed to illustrate the features of the progressive failure modeling methods that have been implemented.
Multi-Criteria Model for Determining Order Size
Directory of Open Access Journals (Sweden)
Katarzyna Jakowska-Suwalska
2013-01-01
Full Text Available A multi-criteria model for determining the order size for materials used in production has been presented. It was assumed that the consumption rate of each material is a random variable with a known probability distribution. Using such a model, in which the purchase cost of materials ordered is limited, three criteria were considered: order size, probability of a lack of materials in the production process, and deviations in the order size from the consumption rate in past periods. Based on an example, it has been shown how to use the model to determine the order sizes for polyurethane adhesive and wood in a hard-coal mine. (original abstract
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.
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.
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.
An improved second-order continuum traffic model
Marques, W., Jr.; Velasco, R. M.
2010-02-01
We construct a second-order continuum traffic model by using an iterative procedure in order to derive a constitutive relation for the traffic pressure which is similar to the Navier-Stokes equation for ordinary fluids. Our second-order traffic model represents an improvement on the traffic model suggested by Kerner and Konhäuser since the iterative procedure introduces, in the constitutive relation for the traffic pressure, a density-dependent viscosity coefficient. By using a finite-difference scheme based on the Steger-Warming flux splitting, we investigate the solution of our improved second-order traffic model for specific problems like shock fronts in traffic and freeway-lane drop.
An improved second-order continuum traffic model
International Nuclear Information System (INIS)
Marques, W Jr; Velasco, R M
2010-01-01
We construct a second-order continuum traffic model by using an iterative procedure in order to derive a constitutive relation for the traffic pressure which is similar to the Navier–Stokes equation for ordinary fluids. Our second-order traffic model represents an improvement on the traffic model suggested by Kerner and Konhäuser since the iterative procedure introduces, in the constitutive relation for the traffic pressure, a density-dependent viscosity coefficient. By using a finite-difference scheme based on the Steger–Warming flux splitting, we investigate the solution of our improved second-order traffic model for specific problems like shock fronts in traffic and freeway-lane drop
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.
Energy Technology Data Exchange (ETDEWEB)
Caskey, C.T.
1995-09-01
A reciprocal probing method is described which uses pooled cDNA probes to order chromosome specific libraries in order to identify cosmids containing sequences capable to hybridizing to the pool. In this pilot study, placental DNA clones were used to identify cosmids from both chromosomes X and 17. Sixty unique cDNA`s were identified of which 22 were novel.
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.
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. ...
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.
Testing static tradeoff theory against pecking order models of capital ...
African Journals Online (AJOL)
We test two models with the purpose of finding the best empirical explanation for corporate financing choice of a cross section of 27 Nigerian quoted companies. The models were developed to represent the Static tradeoff Theory and the Pecking order Theory of capital structure with a view to make comparison between ...
Bayesian variable order Markov models: Towards Bayesian predictive state representations
Dimitrakakis, C.
2009-01-01
We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more
Latent Partially Ordered Classification Models and Normal Mixtures
Tatsuoka, Curtis; Varadi, Ferenc; Jaeger, Judith
2013-01-01
Latent partially ordered sets (posets) can be employed in modeling cognitive functioning, such as in the analysis of neuropsychological (NP) and educational test data. Posets are cognitively diagnostic in the sense that classification states in these models are associated with detailed profiles of cognitive functioning. These profiles allow for…
Testing static tradeoff theiry against pecking order models of capital ...
African Journals Online (AJOL)
We test two models with the purpose of finding the best empirical explanation for corporate financing choice of a cross section of 27 Nigerian quoted companies. The models were developed to represent the Static tradeoff Theory and the Pecking order Theory of capital structure with a view to make comparison between ...
Partial-Order Reduction for GPU Model Checking
Neele, T.; Wijs, A.; Bosnacki, D.; van de Pol, Jan Cornelis; Artho, C; Legay, A.; Peled, D.
2016-01-01
Model checking using GPUs has seen increased popularity over the last years. Because GPUs have a limited amount of memory, only small to medium-sized systems can be verified. For on-the-fly explicit-state model checking, we improve memory efficiency by applying partial-order reduction. We propose
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.
Mathematical modelling of fractional order circuit elements and bioimpedance applications
Moreles, Miguel Angel; Lainez, Rafael
2017-05-01
In this work a classical derivation of fractional order circuits models is presented. Generalised constitutive equations in terms of fractional Riemann-Liouville derivatives are introduced in the Maxwell's equations for each circuit element. Next the Kirchhoff voltage law is applied in a RCL circuit configuration. It is shown that from basic properties of Fractional Calculus, a fractional differential equation model with Caputo derivatives is obtained. Thus standard initial conditions apply. Finally, models for bioimpedance are revisited.
Measurement Error in Designed Experiments for Second Order Models
McMahan, Angela Renee
1997-01-01
Measurement error (ME) in the factor levels of designed experiments is often overlooked in the planning and analysis of experimental designs. A familiar model for this type of ME, called the Berkson error model, is discussed at length. Previous research has examined the effect of Berkson error on two-level factorial and fractional factorial designs. This dissertation extends the examination to designs for second order models. The results are used to suggest ...
Modeling Human Behaviour with Higher Order Logic: Insider Threats
DEFF Research Database (Denmark)
Boender, Jaap; Ivanova, Marieta Georgieva; Kammuller, Florian
2014-01-01
it to the sociological process of logical explanation. As a case study on modeling human behaviour, we present the modeling and analysis of insider threats as a Higher Order Logic theory in Isabelle/HOL. We show how each of the three step process of sociological explanation can be seen in our modeling of insider’s state......, its context within an organisation and the effects on security as outcomes of a theorem proving analysis....
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...
Terminology Modeling for an Enterprise Laboratory Orders Catalog
Zhou, Li; Goldberg, Howard; Pabbathi, Deepika; Wright, Adam; Goldman, Debora S.; Van Putten, Cheryl; Barley, Amanda; Rocha, Roberto A.
2009-01-01
Laboratory test orders are used in a variety of clinical information systems at Partners HealthCare. At present, each site at Partners manages its own set of laboratory orders with locally defined codes. Our current plan is to implement an enterprise catalog, where laboratory test orders are mapped to reference terminologies and codes from different sites are mapped to each other. This paper describes the terminology modeling effort that preceded the implementation of the enterprise laboratory orders catalog. In particular, we present our experience in adapting HL7’s “Common Terminology Services 2 – Upper Level Class Model” as a terminology metamodel for guiding the development of fully specified laboratory orders and related services. PMID:20351950
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).
Reduced order modeling of some fluid flows of industrial interest
International Nuclear Information System (INIS)
Alonso, D; Terragni, F; Velazquez, A; Vega, J M
2012-01-01
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)
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)
In-Situ Residual Tracking in Reduced Order Modelling
Directory of Open Access Journals (Sweden)
Joseph C. Slater
2002-01-01
Full Text Available Proper orthogonal decomposition (POD based reduced-order modelling is demonstrated to be a weighted residual technique similar to Galerkin's method. Estimates of weighted residuals of neglected modes are used to determine relative importance of neglected modes to the model. The cumulative effects of neglected modes can be used to estimate error in the reduced order model. Thus, once the snapshots have been obtained under prescribed training conditions, the need to perform full-order simulations for comparison is eliminates. This has the potential to allow the analyst to initiate further training when the reduced modes are no longer sufficient to accurately represent the predominant phenomenon of interest. The response of a fluid moving at Mach 1.2 above a panel to a forced localized oscillation of the panel at and away from the training operating conditions is used to demonstrate the evaluation method.
Composite symmetry-protected topological order and effective models
Nietner, A.; Krumnow, C.; Bergholtz, E. J.; Eisert, J.
2017-12-01
Strongly correlated quantum many-body systems at low dimension exhibit a wealth of phenomena, ranging from features of geometric frustration to signatures of symmetry-protected topological order. In suitable descriptions of such systems, it can be helpful to resort to effective models, which focus on the essential degrees of freedom of the given model. In this work, we analyze how to determine the validity of an effective model by demanding it to be in the same phase as the original model. We focus our study on one-dimensional spin-1 /2 systems and explain how nontrivial symmetry-protected topologically ordered (SPT) phases of an effective spin-1 model can arise depending on the couplings in the original Hamiltonian. In this analysis, tensor network methods feature in two ways: on the one hand, we make use of recent techniques for the classification of SPT phases using matrix product states in order to identify the phases in the effective model with those in the underlying physical system, employing Künneth's theorem for cohomology. As an intuitive paradigmatic model we exemplify the developed methodology by investigating the bilayered Δ chain. For strong ferromagnetic interlayer couplings, we find the system to transit into exactly the same phase as an effective spin-1 model. However, for weak but finite coupling strength, we identify a symmetry broken phase differing from this effective spin-1 description. On the other hand, we underpin our argument with a numerical analysis making use of matrix product states.
College Students' Technology Arc: A Model for Understanding Progress
Langer, Arthur; Knefelkamp, L. Lee
2008-01-01
This article introduces the Student Technology Arc, a model that evaluates college students 'technology literacy, or how they operate within an education system influenced by new technologies. Student progress is monitored through the Arc's 5 interdependent stages, which reflect growing technological maturity through levels of increasing cognitive…
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.
The MPTP/probenecid model of progressive Parkinson's disease.
Carta, Anna R; Carboni, Ezio; Spiga, Saturnino
2013-01-01
Parkinson's disease (PD) is characterized by a progressive degeneration of dopamine (DA) neurons and a chronic loss of motor functions. The investigation of progressive degenerative mechanisms and possible neuroprotective approaches for PD depends upon the development of an experimental animal model that reproduces the neuropathology observed in humans. This chapter describes the generation of the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/probenecid (MPTPp) chronic mouse model of PD. This model displays key features of PD, including impairment of motor and olfactory functions associated with partial loss of tyrosine hydroxylase-positive neurons and DA levels in the brain. The MPTPp mouse model provides an important tool for the study of mechanisms contributing to the pathological dysfunction of PD at the cellular and whole animal level.
Reverse time migration by Krylov subspace reduced order modeling
Basir, Hadi Mahdavi; Javaherian, Abdolrahim; Shomali, Zaher Hossein; Firouz-Abadi, Roohollah Dehghani; Gholamy, Shaban Ali
2018-04-01
Imaging is a key step in seismic data processing. To date, a myriad of advanced pre-stack depth migration approaches have been developed; however, reverse time migration (RTM) is still considered as the high-end imaging algorithm. The main limitations associated with the performance cost of reverse time migration are the intensive computation of the forward and backward simulations, time consumption, and memory allocation related to imaging condition. Based on the reduced order modeling, we proposed an algorithm, which can be adapted to all the aforementioned factors. Our proposed method benefit from Krylov subspaces method to compute certain mode shapes of the velocity model computed by as an orthogonal base of reduced order modeling. Reverse time migration by reduced order modeling is helpful concerning the highly parallel computation and strongly reduces the memory requirement of reverse time migration. The synthetic model results showed that suggested method can decrease the computational costs of reverse time migration by several orders of magnitudes, compared with reverse time migration by finite element method.
Impact of Physics Parameterization Ordering in a Global Atmosphere Model
Donahue, Aaron S.; Caldwell, Peter M.
2018-02-01
Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid-scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k-means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.
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.
A MATHEMATICAL MODELLING APPROACH TO ONE-DAY CRICKET BATTING ORDERS
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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
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 results are related to experimental work on ordering processes in orientational glasses. It is suggested that the experimental observation of very slow ordering kinetics in, e.g., glassy crystals of cyanoadamantane may be a consequence of low-temperature activated processes which ultimately lead......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......, of the algebraic growth law, R(t)∼Atn, whereas the growth exponent, n, remains close to the value n=1/2 predicted by the classical Lifshitz-Allen-Cahn growth law for systems with nonconserved order parameter. At very low temperatures there is, however, an effective crossover to a much slower algebraic growth...
A fractional-order model for MINMOD Millennium.
Cho, Yongjin; Kim, Imbunm; Sheen, Dongwoo
2015-04-01
MINMOD Millennium has been widely used to estimate insulin sensitivity (SI) in glucose-insulin dynamics. In order to explain the rheological behavior of glucose-insulin we attempt to modify MINMOD Millennium with fractional-order differentiation of order α ∈ (0, 1]. We show that the new modified model has non-negative, bounded solutions and a stable equilibrium point. Quasi-optimal fractional orders and parameters are estimated by using a nonlinear weighted least-squares method, the Levenberg-Marquardt algorithm, and the fractional Adams-Bashforth-Moulton method for several subjects (normal subjects and type 2 diabetic patients). The numerical results confirm that SI is significantly lower in diabetics than in non-diabetics. In addition, we explain the new factor (τ(1 - α)) determining glucose tolerance and the relation between SI and τ(1 - α). Copyright © 2015 Elsevier Inc. All rights reserved.
Robust simulation of buckled structures using reduced order modeling
International Nuclear Information System (INIS)
Wiebe, R.; Perez, R.A.; Spottswood, S.M.
2016-01-01
Lightweight metallic structures are a mainstay in aerospace engineering. For these structures, stability, rather than strength, is often the critical limit state in design. For example, buckling of panels and stiffeners may occur during emergency high-g maneuvers, while in supersonic and hypersonic aircraft, it may be induced by thermal stresses. The longstanding solution to such challenges was to increase the sizing of the structural members, which is counter to the ever present need to minimize weight for reasons of efficiency and performance. In this work we present some recent results in the area of reduced order modeling of post- buckled thin beams. A thorough parametric study of the response of a beam to changing harmonic loading parameters, which is useful in exposing complex phenomena and exercising numerical models, is presented. Two error metrics that use but require no time stepping of a (computationally expensive) truth model are also introduced. The error metrics are applied to several interesting forcing parameter cases identified from the parametric study and are shown to yield useful information about the quality of a candidate reduced order model. Parametric studies, especially when considering forcing and structural geometry parameters, coupled environments, and uncertainties would be computationally intractable with finite element models. The goal is to make rapid simulation of complex nonlinear dynamic behavior possible for distributed systems via fast and accurate reduced order models. This ability is crucial in allowing designers to rigorously probe the robustness of their designs to account for variations in loading, structural imperfections, and other uncertainties. (paper)
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.
Time Ordering in Frontal Lobe Patients: A Stochastic Model Approach
Magherini, Anna; Saetti, Maria Cristina; Berta, Emilia; Botti, Claudio; Faglioni, Pietro
2005-01-01
Frontal lobe patients reproduced a sequence of capital letters or abstract shapes. Immediate and delayed reproduction trials allowed the analysis of short- and long-term memory for time order by means of suitable Markov chain stochastic models. Patients were as proficient as healthy subjects on the immediate reproduction trial, thus showing spared…
Reduced order modelling and predictive control of multivariable ...
Indian Academy of Sciences (India)
Anuj Abraham
2018-03-16
Mar 16, 2018 ... The performance of constraint generalized predictive control scheme is found to be superior to that of the conventional PID controller in terms of overshoot, settling time and performance indices, mainly ISE, IAE and MSE. Keywords. Predictive control; distillation column; reduced order model; dominant pole; ...
An Almost Integration-free Approach to Ordered Response Models
van Praag, B.M.S.; Ferrer-i-Carbonell, A.
2006-01-01
'In this paper we propose an alternative approach to the estimation of ordered response models. We show that the Probit-method may be replaced by a simple OLS-approach, called P(robit)OLS, without any loss of efficiency. This method can be generalized to the analysis of panel data. For large-scale
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.
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.
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.
Integrable higher order deformations of Heisenberg supermagnetic model
International Nuclear Information System (INIS)
Guo Jiafeng; Yan Zhaowen; Wang Shikun; Wu Ke; Zhao Weizhong
2009-01-01
The Heisenberg supermagnet model is an integrable supersymmetric system and has a close relationship with the strong electron correlated Hubbard model. In this paper, we investigate the integrable higher order deformations of Heisenberg supermagnet models with two different constraints: (i) S 2 =3S-2I for S is an element of USPL(2/1)/S(U(2)xU(1)) and (ii) S 2 =S for S is an element of USPL(2/1)/S(L(1/1)xU(1)). In terms of the gauge transformation, their corresponding gauge equivalent counterparts are derived.
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.
Aeroelastic simulation using CFD based reduced order models
International Nuclear Information System (INIS)
Zhang, W.; Ye, Z.; Li, H.; Yang, Q.
2005-01-01
This paper aims at providing an accurate and efficient method for aeroelastic simulation. System identification is used to get the reduced order models of unsteady aerodynamics. Unsteady Euler codes are used to compute the output signals while 3211 multistep input signals are utilized. LS(Least Squares) method is used to estimate the coefficients of the input-output difference model. The reduced order models are then used in place of the unsteady CFD code for aeroelastic simulation. The aeroelastic equations are marched by an improved 4th order Runge-Kutta method that only needs to compute the aerodynamic loads one time at every time step. The computed results agree well with that of the direct coupling CFD/CSD methods. The computational efficiency is improved 1∼2 orders while still retaining the high accuracy. A standard aeroelastic computing example (isogai wing) with S type flutter boundary is computed and analyzed. It is due to the system has more than one neutral points at the Mach range of 0.875∼0.9. (author)
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.
Computational Analysis of Complex Population Dynamical Model with Arbitrary Order
Directory of Open Access Journals (Sweden)
Fazal Haq
2018-01-01
Full Text Available This paper considers the approximation of solution for a fractional order biological population model. The fractional derivative is considered in the Caputo sense. By using Laplace Adomian decomposition method (LADM, we construct a base function and provide deformation equation of higher order in a simple equation. The considered scheme gives us a solution in the form of rapidly convergent infinite series. Some examples are used to show the efficiency of the method. The results show that LADM is efficient and accurate for solving such types of nonlinear problems.
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.
A Model of Gear Transmission: Fractional Order System Dynamics
Directory of Open Access Journals (Sweden)
Katica (Stevanović Hedrih
2010-01-01
Full Text Available A theoretical model of multistep gear transmission dynamics is presented. This model is based on the assumption that the connection between the teeth of the gears is with properties within the range from ideal clasic to viscoelastic so that a new model of connection between the teeth was expressed by means of derivative of fractional order. For this model a two-step gear transmision with three degrees of freedom of motion has been used. The obtained solutions are in the analytic form of the expansion according to time. As boundary cases this model gives results for the case of ideally elastic connection of the gear teeth and for the case of viscoelastic connection of the gear teeth, as well. Eigen fractional modes are obtained and a vizualization is done.
Empirical Reduced-Order Modeling for Boundary Feedback Flow Control
Directory of Open Access Journals (Sweden)
Seddik M. Djouadi
2008-01-01
Full Text Available This paper deals with the practical and theoretical implications of model reduction for aerodynamic flow-based control problems. Various aspects of model reduction are discussed that apply to partial differential equation- (PDE- based models in general. Specifically, the proper orthogonal decomposition (POD of a high dimension system as well as frequency domain identification methods are discussed for initial model construction. Projections on the POD basis give a nonlinear Galerkin model. Then, a model reduction method based on empirical balanced truncation is developed and applied to the Galerkin model. The rationale for doing so is that linear subspace approximations to exact submanifolds associated with nonlinear controllability and observability require only standard matrix manipulations utilizing simulation/experimental data. The proposed method uses a chirp signal as input to produce the output in the eigensystem realization algorithm (ERA. This method estimates the system's Markov parameters that accurately reproduce the output. Balanced truncation is used to show that model reduction is still effective on ERA produced approximated systems. The method is applied to a prototype convective flow on obstacle geometry. An H∞ feedback flow controller is designed based on the reduced model to achieve tracking and then applied to the full-order model with excellent performance.
Identification of the reduced order models of a BWR reactor
International Nuclear Information System (INIS)
Hernandez S, A.
2004-01-01
The present work has as objective to analyze the relative stability of a BWR type reactor. It is analyzed that so adaptive it turns out to identify the parameters of a model of reduced order so that this it reproduces a condition of given uncertainty. This will take of a real fact happened in the La Salle plant under certain operation conditions of power and flow of coolant. The parametric identification is carried out by means of an algorithm of recursive least square and an Output Error model (Output Error), measuring the output power of the reactor when the instability is present, and considering that it is produced by a change in the reactivity of the system in the same way that a sign of type step. Also it is carried out an analytic comparison of the relative stability, analyzing two types of answers: the original answer of the uncertainty of the reactor vs. the obtained response identifying the parameters of the model of reduced order, reaching the conclusion that it is very viable to adapt a model of reduced order to study the stability of a reactor, under the only condition to consider that the dynamics of the reactivity is of step type. (Author)
A MATHEMATICAL MODEL OF CHP 2000 TYPE PROGRESSIVE GEAR
Paweł Lonkwic
2016-01-01
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 th...
Progress in integrated energy-economy-environment model system development
International Nuclear Information System (INIS)
Yasukawa, Shigeru; Mankin, Shuichi; Sato, Osamu; Tadokoro, Yoshihiro; Nakano, Yasuyuki; Nagano, Takao
1987-11-01
The Integrated Energy-Economy-Environment Model System has been developed for providing analytical tools for the system analysis and technology assessments in the field of nuclear research and development. This model system consists of the following four model groups. The first model block installs 5 models and can serve to analyze and generate long-term scenarios on economy-energy-environment evolution. The second model block installs 2 models and can serve to analyze the structural transition phenomena in energy-economy-environment interactions. The third model block installs 2 models and can handle power reactor installation strategy problem and long-term fuel cycle analysis. The fourth model block installs 5 models and codes and can treats cost-benefit-risk analysis and assessments. This report describes mainly the progress and the outlines of application of the model system in these years after the first report on the research and development of the model system (JAERI-M 84 - 139). (author)
HOKF: High Order Kalman Filter for Epilepsy Forecasting Modeling.
Nguyen, Ngoc Anh Thi; Yang, Hyung-Jeong; Kim, Sunhee
2017-08-01
Epilepsy forecasting has been extensively studied using high-order time series obtained from scalp-recorded electroencephalography (EEG). An accurate seizure prediction system would not only help significantly improve patients' quality of life, but would also facilitate new therapeutic strategies to manage epilepsy. This paper thus proposes an improved Kalman Filter (KF) algorithm to mine seizure forecasts from neural activity by modeling three properties in the high-order EEG time series: noise, temporal smoothness, and tensor structure. The proposed High-Order Kalman Filter (HOKF) is an extension of the standard Kalman filter, for which higher-order modeling is limited. The efficient dynamic of HOKF system preserves the tensor structure of the observations and latent states. As such, the proposed method offers two main advantages: (i) effectiveness with HOKF results in hidden variables that capture major evolving trends suitable to predict neural activity, even in the presence of missing values; and (ii) scalability in that the wall clock time of the HOKF is linear with respect to the number of time-slices of the sequence. The HOKF algorithm is examined in terms of its effectiveness and scalability by conducting forecasting and scalability experiments with a real epilepsy EEG dataset. The results of the simulation demonstrate the superiority of the proposed method over the original Kalman Filter and other existing methods. Copyright © 2017 Elsevier B.V. All rights reserved.
Model predictive control based on reduced order models applied to belt conveyor system.
Chen, Wei; Li, Xin
2016-11-01
In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
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.
Modeling the assembly order of multimeric heteroprotein complexes.
Peterson, Lenna X; Togawa, Yoichiro; Esquivel-Rodriguez, Juan; Terashi, Genki; Christoffer, Charles; Roy, Amitava; Shin, Woong-Hee; Kihara, Daisuke
2018-01-01
Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure modeling and will be
Modeling the assembly order of multimeric heteroprotein complexes.
Directory of Open Access Journals (Sweden)
Lenna X Peterson
2018-01-01
Full Text Available Protein-protein interactions are the cornerstone of numerous biological processes. Although an increasing number of protein complex structures have been determined using experimental methods, relatively fewer studies have been performed to determine the assembly order of complexes. In addition to the insights into the molecular mechanisms of biological function provided by the structure of a complex, knowing the assembly order is important for understanding the process of complex formation. Assembly order is also practically useful for constructing subcomplexes as a step toward solving the entire complex experimentally, designing artificial protein complexes, and developing drugs that interrupt a critical step in the complex assembly. There are several experimental methods for determining the assembly order of complexes; however, these techniques are resource-intensive. Here, we present a computational method that predicts the assembly order of protein complexes by building the complex structure. The method, named Path-LzerD, uses a multimeric protein docking algorithm that assembles a protein complex structure from individual subunit structures and predicts assembly order by observing the simulated assembly process of the complex. Benchmarked on a dataset of complexes with experimental evidence of assembly order, Path-LZerD was successful in predicting the assembly pathway for the majority of the cases. Moreover, when compared with a simple approach that infers the assembly path from the buried surface area of subunits in the native complex, Path-LZerD has the strong advantage that it can be used for cases where the complex structure is not known. The path prediction accuracy decreased when starting from unbound monomers, particularly for larger complexes of five or more subunits, for which only a part of the assembly path was correctly identified. As the first method of its kind, Path-LZerD opens a new area of computational protein structure
Multivariable robust adaptive controller using reduced-order model
Directory of Open Access Journals (Sweden)
Wei Wang
1990-04-01
Full Text Available In this paper a multivariable robust adaptive controller is presented for a plant with bounded disturbances and unmodeled dynamics due to plant-model order mismatches. The robust stability of the closed-loop system is achieved by using the normalization technique and the least squares parameter estimation scheme with dead zones. The weighting polynomial matrices are incorporated into the control law, so that the open-loop unstable or/and nonminimum phase plants can be handled.
Long range ordering in model Ni-Cr-X alloys
International Nuclear Information System (INIS)
Young, G.A.; Eno, D.R.
2015-01-01
Nickel-chromium alloys are used throughout commercial nuclear power systems due to their desirable combination of corrosion resistance and mechanical properties. However, some Ni-Cr alloys can undergo long range ordering (LRO), forming the Ni 2 Cr phase when exposed to temperatures < 590 C. degrees. LRO results in lattice contraction, hardening, and a change in slip mode, which, in turn, can cause dimensional changes, internal stress, and appreciable embrittlement. Despite the technological importance of this alloy system, the variables that influence LRO are not well understood and the time-temperature-transformation kinetics poorly defined. In order to assess the risk of LRO in nuclear power systems, the present research uses model Ni-Cr alloys and ageing times up to 10000 hours to define the kinetics of LRO and to assess the effects of cold work, quench rate, and alloying additions. Results show that the hardening caused by ordering is well described by the Kolmogorov-Johnson-Mehl-Avrami (KJMA) equation with an Avrami exponent, n near 0.65 and an apparent activation energy that depends on the starting condition of the alloy. Furnace cooled samples displayed a Q ∼ 244 kJ/mol, which suggests bulk diffusional growth of the ordered phase, while water quenched samples exhibited a Q ∼ 147 kJ/mol, indicating that excess vacancies accelerate ordering. Cold work (10% or 20%) acts to disrupt any ordering that forms on furnace cooling but has no apparent effect on the apparent activation energy or Avrami exponent. Iron additions decrease the temperature below which the ordered phase is stable but do not appear to affect the rate of ordering. Investigation of other alloying suggest that molybdenum (∼ 2.47 wt.%) may accelerate ordering but other alloying elements studied (Si up to 0.28 wt.%, Mn up to 0.19 wt.%, and Nb up to 2.38 wt.%) have little influence. These findings, combined with a review of LRO in commercial alloys indicate that LRO can develop over a wide
Progress towards localization in the attractive Hubbard model
Morong, W.; Xu, W.; Demarco, B.
2017-04-01
The interplay between fermionic superfluidity and disorder is a topic of long-standing interest that has recently come within reach of ultracold gas experiments. Outstanding questions include the fate of Cooper pairs in a localized superfluid and the effect of disorder on the superfluid transition temperature. We report progress on tackling this problem using a realization of the Hubbard model with attractive interactions. Our system consists of two spin states of fermionic potassium-40 trapped in a cubic optical lattice. Disorder is introduced using an optical speckle potential, and interactions are controlled via a Feshbach resonance. We study the binding and unbinding of Cooper pairs in this system using rf spectroscopy, changes in Tc by measuring the condensate fraction, and transport properties by observing the response to an applied impulse. We will discuss progress towards these measurements.
An Ordered Regression Model to Predict Transit Passengers’ Behavioural Intentions
Energy Technology Data Exchange (ETDEWEB)
Oña, J. de; Oña, R. de; Eboli, L.; Forciniti, C.; Mazzulla, G.
2016-07-01
Passengers’ behavioural intentions after experiencing transit services can be viewed as signals that show if a customer continues to utilise a company’s service. Users’ behavioural intentions can depend on a series of aspects that are difficult to measure directly. More recently, transit passengers’ behavioural intentions have been just considered together with the concepts of service quality and customer satisfaction. Due to the characteristics of the ways for evaluating passengers’ behavioural intentions, service quality and customer satisfaction, we retain that this kind of issue could be analysed also by applying ordered regression models. This work aims to propose just an ordered probit model for analysing service quality factors that can influence passengers’ behavioural intentions towards the use of transit services. The case study is the LRT of Seville (Spain), where a survey was conducted in order to collect the opinions of the passengers about the existing transit service, and to have a measure of the aspects that can influence the intentions of the users to continue using the transit service in the future. (Author)
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...
Probabilistic Rotor Life Assessment Using Reduced Order Models
Directory of Open Access Journals (Sweden)
Brian K. Beachkofski
2009-01-01
Full Text Available Probabilistic failure assessments for integrally bladed disks are system reliability problems where a failure in at least one blade constitutes a rotor system failure. Turbine engine fan and compressor blade life is dominated by High Cycle Fatigue (HCF initiated either by pure HCF or Foreign Object Damage (FOD. To date performing an HCF life assessment for the entire rotor system has been too costly in analysis time to be practical. Although the substantial run-time has previously precluded a full-rotor probabilistic analysis, reduced order models make this process tractable as demonstrated in this work. The system model includes frequency prediction, modal stress variation, mistuning amplification, FOD effect, and random material capability. The model has many random variables which are most easily handled through simple random sampling.
Topological order in an exactly solvable 3D spin model
International Nuclear Information System (INIS)
Bravyi, Sergey; Leemhuis, Bernhard; Terhal, Barbara M.
2011-01-01
Research highlights: RHtriangle We study exactly solvable spin model with six-qubit nearest neighbor interactions on a 3D face centered cubic lattice. RHtriangle The ground space of the model exhibits topological quantum order. RHtriangle Elementary excitations can be geometrically described as the corners of rectangular-shaped membranes. RHtriangle The ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. RHtriangle Logical operators acting on the encoded qubits are described in terms of closed strings and closed membranes. - Abstract: We study a 3D generalization of the toric code model introduced recently by Chamon. This is an exactly solvable spin model with six-qubit nearest-neighbor interactions on an FCC lattice whose ground space exhibits topological quantum order. The elementary excitations of this model which we call monopoles can be geometrically described as the corners of rectangular-shaped membranes. We prove that the creation of an isolated monopole separated from other monopoles by a distance R requires an operator acting on Ω(R 2 ) qubits. Composite particles that consist of two monopoles (dipoles) and four monopoles (quadrupoles) can be described as end-points of strings. The peculiar feature of the model is that dipole-type strings are rigid, that is, such strings must be aligned with face-diagonals of the lattice. For periodic boundary conditions the ground space can encode 4g qubits where g is the greatest common divisor of the lattice dimensions. We describe a complete set of logical operators acting on the encoded qubits in terms of closed strings and closed membranes.
Progress in tritium retention and release modeling for ceramic breeders
International Nuclear Information System (INIS)
Raffray, A.R.; Federici, G.; Billone, M.C.; Tanaka, S.
1994-01-01
Tritium behavior in ceramic breeder blankets is a key design issue for this class of blanket because of its impact on safety and fuel self-sufficiency. Over the past 10-15 years, substantial theoretical and experimental efforts have been dedicated world-wide to develop a better understanding of tritium transport in ceramic breeders. Models that are available today seem to cover reasonably well all the key physical transport and trapping mechanisms. They have allowed for reasonable interpretation and reproduction of experimental data and have helped in pointing out deficiencies in material property data base, in providing guidance for future experiments, and in analyzing blanket tritium behavior. This paper highlights the progress in tritium modeling over the last decade. Key tritium transport mechanisms are briefly described along with the more recent and sophisticated models developed to help understand them. Recent experimental data are highlighted and model calibration and validation discussed. Finally, example applications to blanket cases are shown as illustration of progress in the prediction of ceramic breeder blanket tritium inventory
Towards a Wind Turbine Wake Reduced-Order Model
Hamilton, Nicholas; Viggiano, Bianca; Calaf, Marc; Tutkun, Murat; Cal, Raúl Bayoán
2017-11-01
A reduced-order model for a wind turbine wake is sought for prediction and control. Basis functions from the proper orthogonal decomposition (POD) represent the spatially coherent turbulence structures in the wake; eigenvalues delineate the turbulence kinetic energy associated with each mode. Back-projecting the POD modes onto the velocity snapshots produces coefficients that express the amplitude of each mode in time. A reduced-order model of the wind turbine wake (wakeROM) is defined through a series of polynomial parameters that quantify mode interaction and the evolution of each mode coefficient. Tikhonov regularization is employed to recalibrate the dynamical system, reducing error in the modeled mode coefficients and adding stability to the system. The wakeROM is periodically reinitialized by relating the incoming turbulent velocity to the POD mode coefficients. A high-level view of the wakeROM provides as a platform to discuss promising research direction, alternate processes that will enhance stability, and portability to control methods. NSF- ECCS-1032647, NSF-CBET-1034581, Research Council of Norway Project Number 231491.
The complex model of risk and progression of AMD estimation
Directory of Open Access Journals (Sweden)
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.
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...
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
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...... 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...... on a trumpet signal show the applicability on real signals....
Recent progress in human reliability models for nuclear power safety
International Nuclear Information System (INIS)
Bersini, U.; Devooght, J.; Smidts, C.
1988-01-01
The importance of a human factor in the safety of nuclear power plants hardly needs to be stressed after the Three Mile Island and Chernobyl accidents. Following TMI, such progress was made that Chernobyl did not reveal significant faults in the design or operation of Western nuclear power plants. Post-TMI progress concerns: design of control rooms, development of simulators for training operators, use of computer aided diagnostics, a better understanding of procedural safety, the collection of human error data, etc. We shall concentrate here on the specific point of modelling human errors for incorporation in the standard tools of reliability and safety engineering (e.g. fault trees). The Rasmussen report (WASH 1400) has already included human error in the analysis of fault and event trees and since then new models have been developed and tested. Human reliability methods, which first appeared in the early 1980s, model operator behavior during routine tasks and quantify his error probability. Here three of these methods are briefly described: THERP, SLIM and MAPPS. 17 refs
A MATHEMATICAL MODEL OF CHP 2000 TYPE PROGRESSIVE GEAR
Directory of Open Access Journals (Sweden)
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.
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....
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...
Antiferromagnetic order in the Hubbard model on the Penrose lattice
Koga, Akihisa; Tsunetsugu, Hirokazu
2017-12-01
We study an antiferromagnetic order in the ground state of the half-filled Hubbard model on the Penrose lattice and investigate the effects of quasiperiodic lattice structure. In the limit of infinitesimal Coulomb repulsion U →+0 , the staggered magnetizations persist to be finite, and their values are determined by confined states, which are strictly localized with thermodynamics degeneracy. The magnetizations exhibit an exotic spatial pattern, and have the same sign in each of cluster regions, the size of which ranges from 31 sites to infinity. With increasing U , they continuously evolve to those of the corresponding spin model in the U =∞ limit. In both limits of U , local magnetizations exhibit a fairly intricate spatial pattern that reflects the quasiperiodic structure, but the pattern differs between the two limits. We have analyzed this pattern change by a mode analysis by the singular value decomposition method for the fractal-like magnetization pattern projected into the perpendicular space.
Pairing of parafermions of order 2: seniority model
International Nuclear Information System (INIS)
Nelson, Charles A
2004-01-01
As generalizations of the fermion seniority model, four multi-mode Hamiltonians are considered to investigate some of the consequences of the pairing of parafermions of order 2. Two- and four-particle states are explicitly constructed for H A ≡ -GA†A with A† ≡ 1/2 Σ m>0 c† m c† -m and the distinct H C ≡ -GC†C with C† ≡ 1/2 Σ m>0 c† -m c† m , and for the time-reversal invariant H (-) ≡ -G(A† - C†)(A - C) and H (+) ≡ -G(A† + C†)(A + C), which has no analogue in the fermion case. The spectra and degeneracies are compared with those of the usual fermion seniority model
Quantifying and modeling birth order effects in autism.
Directory of Open Access Journals (Sweden)
Tychele Turner
Full Text Available Autism is a complex genetic disorder with multiple etiologies whose molecular genetic basis is not fully understood. Although a number of rare mutations and dosage abnormalities are specific to autism, these explain no more than 10% of all cases. The high heritability of autism and low recurrence risk suggests multifactorial inheritance from numerous loci but other factors also intervene to modulate risk. In this study, we examine the effect of birth rank on disease risk which is not expected for purely hereditary genetic models. We analyzed the data from three publicly available autism family collections in the USA for potential birth order effects and studied the statistical properties of three tests to show that adequate power to detect these effects exist. We detect statistically significant, yet varying, patterns of birth order effects across these collections. In multiplex families, we identify V-shaped effects where middle births are at high risk; in simplex families, we demonstrate linear effects where risk increases with each additional birth. Moreover, the birth order effect is gender-dependent in the simplex collection. It is currently unknown whether these patterns arise from ascertainment biases or biological factors. Nevertheless, further investigation of parental age-dependent risks yields patterns similar to those observed and could potentially explain part of the increased risk. A search for genes considering these patterns is likely to increase statistical power and uncover novel molecular etiologies.
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...
Roof planes detection via a second-order variational model
Benciolini, Battista; Ruggiero, Valeria; Vitti, Alfonso; Zanetti, Massimo
2018-04-01
The paper describes a unified automatic procedure for the detection of roof planes in gridded height data. The procedure exploits the Blake-Zisserman (BZ) model for segmentation in both 2D and 1D, and aims to detect, to model and to label roof planes. The BZ model relies on the minimization of a functional that depends on first- and second-order derivatives, free discontinuities and free gradient discontinuities. During the minimization, the relative strength of each competitor is controlled by a set of weight parameters. By finding the minimum of the approximated BZ functional, one obtains: (1) an approximation of the data that is smoothed solely within regions of homogeneous gradient, and (2) an explicit detection of the discontinuities and gradient discontinuities of the approximation. Firstly, input data is segmented using the 2D BZ. The maps of data and gradient discontinuities are used to isolate building candidates and planar patches (i.e. regions with homogeneous gradient) that correspond to roof planes. Connected regions that can not be considered as buildings are filtered according to both patch dimension and distribution of the directions of the normals to the boundary. The 1D BZ model is applied to the curvilinear coordinates of boundary points of building candidates in order to reduce the effect of data granularity when the normals are evaluated. In particular, corners are preserved and can be detected by means of gradient discontinuity. Lastly, a total least squares model is applied to estimate the parameters of the plane that best fits the points of each planar patch (orthogonal regression with planar model). Refinement of planar patches is performed by assigning those points that are close to the boundaries to the planar patch for which a given proximity measure assumes the smallest value. The proximity measure is defined to account for the variance of a fitting plane and a weighted distance of a point from the plane. The effectiveness of the
Wang, Shiyu; Yang, Yan; Culpepper, Steven Andrew; Douglas, Jeffrey A.
2018-01-01
A family of learning models that integrates a cognitive diagnostic model and a higher-order, hidden Markov model in one framework is proposed. This new framework includes covariates to model skill transition in the learning environment. A Bayesian formulation is adopted to estimate parameters from a learning model. The developed methods are…
Topological order in an exactly solvable 3D spin model
Bravyi, Sergey; Leemhuis, Bernhard; Terhal, Barbara M.
2011-04-01
We study a 3D generalization of the toric code model introduced recently by Chamon. This is an exactly solvable spin model with six-qubit nearest-neighbor interactions on an FCC lattice whose ground space exhibits topological quantum order. The elementary excitations of this model which we call monopoles can be geometrically described as the corners of rectangular-shaped membranes. We prove that the creation of an isolated monopole separated from other monopoles by a distance R requires an operator acting on Ω( R2) qubits. Composite particles that consist of two monopoles (dipoles) and four monopoles (quadrupoles) can be described as end-points of strings. The peculiar feature of the model is that dipole-type strings are rigid, that is, such strings must be aligned with face-diagonals of the lattice. For periodic boundary conditions the ground space can encode 4 g qubits where g is the greatest common divisor of the lattice dimensions. We describe a complete set of logical operators acting on the encoded qubits in terms of closed strings and closed membranes.
Evaluating Alzheimer's Disease Progression by Modeling Crosstalk Network Disruption
Liu, Haochen; Wei, Chunxiang; He, Hua; Liu, Xiaoquan
2016-01-01
Aβ, tau, and P-tau have been widely accepted as reliable markers for Alzheimer's disease (AD). The crosstalk between these markers forms a complex network. AD may induce the integral variation and disruption of the network. The aim of this study was to develop a novel mathematic model based on a simplified crosstalk network to evaluate the disease progression of AD. The integral variation of the network is measured by three integral disruption parameters. The robustness of network is evaluated by network disruption probability. Presented results show that network disruption probability has a good linear relationship with Mini Mental State Examination (MMSE). The proposed model combined with Support vector machine (SVM) achieves a relative high 10-fold cross-validated performance in classification of AD vs. normal and mild cognitive impairment (MCI) vs. normal (95% accuracy, 95% sensitivity, 95% specificity for AD vs. normal; 90% accuracy, 94% sensitivity, 83% specificity for MCI vs. normal). This research evaluates the progression of AD and facilitates AD early diagnosis. PMID:26834548
In silico ADME-Tox modeling: progress and prospects.
Alqahtani, Saeed
2017-11-01
Although significant progress has been made in high-throughput screening of absorption, distribution, metabolism and excretion, and toxicity (ADME-Tox) properties in drug discovery and development, in silico ADME-Tox prediction continues to play an important role in facilitating the appropriate selection of candidate drugs by pharmaceutical companies prior to expensive clinical trials. Areas covered: This review provides an overview of the available in silico models that have been used to predict the ADME-Tox properties of compounds. It also provides a comprehensive overview and summarization of the latest modeling methods and algorithms available for the prediction of physicochemical characteristics, ADME properties, and drug toxicity issues. Expert opinion: The in silico models currently available have greatly contributed to the knowledge of screening approaches in the early stages of drug discovery and the development process. As the definitive goal of in silico molding is to predict the pharmacokinetics and disposition of compounds in vivo by assembling all kinetic processes within one global model, PBPK models can serve this purpose. However, much work remains to be done in this area to generate more data and input parameters to build more reliable and accurate prediction models.
Theory and Low-Order Modeling of Unsteady Airfoil Flows
Ramesh, Kiran
Unsteady flow phenomena are prevalent in a wide range of problems in nature and engineering. These include, but are not limited to, aerodynamics of insect flight, dynamic stall in rotorcraft and wind turbines, leading-edge vortices in delta wings, micro-air vehicle (MAV) design, gust handling and flow control. The most significant characteristics of unsteady flows are rapid changes in the circulation of the airfoil, apparent-mass effects, flow separation and the leading-edge vortex (LEV) phenomenon. Although experimental techniques and computational fluid dynamics (CFD) methods have enabled the detailed study of unsteady flows and their underlying features, a reliable and inexpensive loworder method for fast prediction and for use in control and design is still required. In this research, a low-order methodology based on physical principles rather than empirical fitting is proposed. The objective of such an approach is to enable insights into unsteady phenomena while developing approaches to model them. The basis of the low-order model developed here is unsteady thin-airfoil theory. A time-stepping approach is used to solve for the vorticity on an airfoil camberline, allowing for large amplitudes and nonplanar wakes. On comparing lift coefficients from this method against data from CFD and experiments for some unsteady test cases, it is seen that the method predicts well so long as LEV formation does not occur and flow over the airfoil is attached. The formation of leading-edge vortices (LEVs) in unsteady flows is initiated by flow separation and the formation of a shear layer at the airfoil's leading edge. This phenomenon has been observed to have both detrimental (dynamic stall in helicopters) and beneficial (high-lift flight in insects) effects. To predict the formation of LEVs in unsteady flows, a Leading Edge Suction Parameter (LESP) is proposed. This parameter is calculated from inviscid theory and is a measure of the suction at the airfoil's leading edge. It
Modeling Diverse Pathways to Age Progressive Volcanism in Subduction Zones.
Kincaid, C. R.; Szwaja, S.; Sylvia, R. T.; Druken, K. A.
2015-12-01
One of the best, and most challenging clues to unraveling mantle circulation patterns in subduction zones comes in the form of age progressive volcanic and geochemical trends. Hard fought geological data from many subduction zones, like Tonga-Lau, the Cascades and Costa-Rica/Nicaragua, reveal striking temporal patterns used in defining mantle flow directions and rates. We summarize results from laboratory subduction models showing a range in circulation and thermal-chemical transport processes. These interaction styles are capable of producing such trends, often reflecting apparent instead of actual mantle velocities. Lab experiments use a glucose working fluid to represent Earth's upper mantle and kinematically driven plates to produce a range in slab sinking and related wedge transport patterns. Kinematic forcing assumes most of the super-adiabatic temperature gradient available to drive major downwellings is in the tabular slabs. Moreover, sinking styles for fully dynamic subduction depend on many complicating factors that are only poorly understood and which can vary widely even for repeated parameter combinations. Kinematic models have the benefit of precise, repeatable control of slab motions and wedge flow responses. Results generated with these techniques show the evolution of near-surface thermal-chemical-rheological heterogeneities leads to age progressive surface expressions in a variety of ways. One set of experiments shows that rollback and back-arc extension combine to produce distinct modes of linear, age progressive melt delivery to the surface through a) erosion of the rheological boundary layer beneath the overriding plate, and deformation and redistribution of both b) mantle residuum produced from decompression melting and c) formerly active, buoyant plumes. Additional experiments consider buoyant diapirs rising in a wedge under the influence of rollback, back-arc spreading and slab-gaps. Strongly deflected diapirs, experiencing variable rise
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.
Vortex network community based reduced-order force model
Gopalakrishnan Meena, Muralikrishnan; Nair, Aditya; Taira, Kunihiko
2017-11-01
We characterize the vortical wake interactions by utilizing network theory and cluster-based approaches, and develop a data-inspired unsteady force model. In the present work, the vortical interaction network is defined by nodes representing vortical elements and the edges quantified by induced velocity measures amongst the vortices. The full vorticity field is reduced to a finite number of vortical clusters based on network community detection algorithm, which serves as a basis for a skeleton network that captures the essence of the wake dynamics. We use this reduced representation of the wake to develop a data-inspired reduced-order force model that can predict unsteady fluid forces on the body. The overall formulation is demonstrated for laminar flows around canonical bluff body wake and stalled flow over an airfoil. We also show the robustness of the present network-based model against noisy data, which motivates applications towards turbulent flows and experimental measurements. Supported by the National Science Foundation (Grant 1632003).
McNeish, Daniel; Dumas, Denis
2017-01-01
Recent methodological work has highlighted the promise of nonlinear growth models for addressing substantive questions in the behavioral sciences. In this article, we outline a second-order nonlinear growth model in order to measure a critical notion in development and education: potential. Here, potential is conceptualized as having three components-ability, capacity, and availability-where ability is the amount of skill a student is estimated to have at a given timepoint, capacity is the maximum amount of ability a student is predicted to be able to develop asymptotically, and availability is the difference between capacity and ability at any particular timepoint. We argue that single timepoint measures are typically insufficient for discerning information about potential, and we therefore describe a general framework that incorporates a growth model into the measurement model to capture these three components. Then, we provide an illustrative example using the public-use Early Childhood Longitudinal Study-Kindergarten data set using a Michaelis-Menten growth function (reparameterized from its common application in biochemistry) to demonstrate our proposed model as applied to measuring potential within an educational context. The advantage of this approach compared to currently utilized methods is discussed as are future directions and limitations.
Partially ordered mixed hidden Markov model for the disablement process of older adults.
Ip, Edward H; Zhang, Qiang; Rejeski, W Jack; Harris, Tamara B; Kritchevsky, Stephen
2013-06-01
At both the individual and societal levels, the health and economic burden of disability in older adults is enormous in developed countries, including the U.S. Recent studies have revealed that the disablement process in older adults often comprises episodic periods of impaired functioning and periods that are relatively free of disability, amid a secular and natural trend of decline in functioning. Rather than an irreversible, progressive event that is analogous to a chronic disease, disability is better conceptualized and mathematically modeled as states that do not necessarily follow a strict linear order of good-to-bad. Statistical tools, including Markov models, which allow bidirectional transition between states, and random effects models, which allow individual-specific rate of secular decline, are pertinent. In this paper, we propose a mixed effects, multivariate, hidden Markov model to handle partially ordered disability states. The model generalizes the continuation ratio model for ordinal data in the generalized linear model literature and provides a formal framework for testing the effects of risk factors and/or an intervention on the transitions between different disability states. Under a generalization of the proportional odds ratio assumption, the proposed model circumvents the problem of a potentially large number of parameters when the number of states and the number of covariates are substantial. We describe a maximum likelihood method for estimating the partially ordered, mixed effects model and show how the model can be applied to a longitudinal data set that consists of N = 2,903 older adults followed for 10 years in the Health Aging and Body Composition Study. We further statistically test the effects of various risk factors upon the probabilities of transition into various severe disability states. The result can be used to inform geriatric and public health science researchers who study the disablement process.
Reduced order modeling in topology optimization of vibroacoustic problems
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Brunskog, Jonas
2017-01-01
There is an interest in introducing topology optimization techniques in the design process of structural-acoustic systems. In topology optimization, the design space must be finely meshed in order to obtain an accurate design, which results in large numbers of degrees of freedom when designing...... or size optimization in large vibroacoustic models; however, new challenges are encountered when dealing with topology optimization. Since a design parameter per element is considered, the total number of design variables becomes very large; this poses a challenge to most existing pMOR techniques, which...... suffer from the curse of dimensionality. Moreover, the fact that the nature of the elements changes throughout the optimization (material to void or material to air) makes it more difficult to create a global basis that is accurate throughout the whole design space. In this work, these challenges...
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.
Dynamical analysis of fractional order model of immunogenic tumors
Directory of Open Access Journals (Sweden)
Sadia Arshad
2016-07-01
Full Text Available In this article, we examine the fractional order model of the cytotoxic T lymphocyte response to a growing tumor cell population. We investigate the long-term behavior of tumor growth and explore the conditions of tumor elimination analytically. We establish the conditions for the tumor-free equilibrium and tumor-infection equilibrium to be asymptotically stable and provide the expression of the basic reproduction number. Existence of physical significant tumor-infection equilibrium points is investigated analytically. We show that tumor growth rate, source rate of immune cells, and death rate of immune cells play vital role in tumor dynamics and system undergoes saddle-node and transcritical bifurcation based on these parameters. Furthermore, the effect of cancer treatment is discussed by varying the values of relevant parameters. Numerical simulations are presented to illustrate the analytical results.
Directory of Open Access Journals (Sweden)
Augusto Cabrera-Becerril
Full Text Available Computational modeling has been applied to simulate the heterogeneity of cancer behavior. The development of Cervical Cancer (CC is a process in which the cell acquires dynamic behavior from non-deleterious and deleterious mutations, exhibiting chromosomal alterations as a manifestation of this dynamic. To further determine the progression of chromosomal alterations in precursor lesions and CC, we introduce a computational model to study the dynamics of deleterious and non-deleterious mutations as an outcome of tumor progression. The analysis of chromosomal alterations mediated by our model reveals that multiple deleterious mutations are more frequent in precursor lesions than in CC. Cells with lethal deleterious mutations would be eliminated, which would mitigate cancer progression; on the other hand, cells with non-deleterious mutations would become dominant, which could predispose them to cancer progression. The study of somatic alterations through computer simulations of cancer progression provides a feasible pathway for insights into the transformation of cell mechanisms in humans. During cancer progression, tumors may acquire new phenotype traits, such as the ability to invade and metastasize or to become clinically important when they develop drug resistance. Non-deleterious chromosomal alterations contribute to this progression.
Pelagic functional group modeling: Progress, challenges and prospects
Hood, Raleigh R.; Laws, Edward A.; Armstrong, Robert A.; Bates, Nicholas R.; Brown, Christopher W.; Carlson, Craig A.; Chai, Fei; Doney, Scott C.; Falkowski, Paul G.; Feely, Richard A.; Friedrichs, Marjorie A. M.; Landry, Michael R.; Keith Moore, J.; Nelson, David M.; Richardson, Tammi L.; Salihoglu, Baris; Schartau, Markus; Toole, Dierdre A.; Wiggert, Jerry D.
2006-03-01
In this paper, we review the state of the art and major challenges in current efforts to incorporate biogeochemical functional groups into models that can be applied on basin-wide and global scales, with an emphasis on models that might ultimately be used to predict how biogeochemical cycles in the ocean will respond to global warming. We define the term "biogeochemical functional group" to refer to groups of organisms that mediate specific chemical reactions in the ocean. Thus, according to this definition, "functional groups" have no phylogenetic meaning—these are composed of many different species with common biogeochemical functions. Substantial progress has been made in the last decade toward quantifying the rates of these various functions and understanding the factors that control them. For some of these groups, we have developed fairly sophisticated models that incorporate this understanding, e.g. for diazotrophs (e.g. Trichodesmium), silica producers (diatoms) and calcifiers (e.g. coccolithophorids and specifically Emiliania huxleyi). However, current representations of nitrogen fixation and calcification are incomplete, i.e., based primarily upon models of Trichodesmium and E. huxleyi, respectively, and many important functional groups have not yet been considered in open-ocean biogeochemical models. Progress has been made over the last decade in efforts to simulate dimethylsulfide (DMS) production and cycling (i.e., by dinoflagellates and prymnesiophytes) and denitrification, but these efforts are still in their infancy, and many significant problems remain. One obvious gap is that virtually all functional group modeling efforts have focused on autotrophic microbes, while higher trophic levels have been completely ignored. It appears that in some cases (e.g., calcification), incorporating higher trophic levels may be essential not only for representing a particular biogeochemical reaction, but also for modeling export. Another serious problem is our
Sparsity enabled cluster reduced-order models for control
Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.
2018-01-01
Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.
Models and correlations of the DEBRIS Late-Phase Melt Progression Model
International Nuclear Information System (INIS)
Schmidt, R.C.; Gasser, R.D.
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
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.
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.
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.
Kopasakis, George
2014-01-01
The presentation covers a recently developed methodology to model atmospheric turbulence as disturbances for aero vehicle gust loads and for controls development like flutter and inlet shock position. The approach models atmospheric turbulence in their natural fractional order form, which provides for more accuracy compared to traditional methods like the Dryden model, especially for high speed vehicle. The presentation provides a historical background on atmospheric turbulence modeling and the approaches utilized for air vehicles. This is followed by the motivation and the methodology utilized to develop the atmospheric turbulence fractional order modeling approach. Some examples covering the application of this method are also provided, followed by concluding remarks.
Stabilization Approaches for Linear and Nonlinear Reduced Order Models
Rezaian, Elnaz; Wei, Mingjun
2017-11-01
It has been a major concern to establish reduced order models (ROMs) as reliable representatives of the dynamics inherent in high fidelity simulations, while fast computation is achieved. In practice it comes to stability and accuracy of ROMs. Given the inviscid nature of Euler equations it becomes more challenging to achieve stability, especially where moving discontinuities exist. Originally unstable linear and nonlinear ROMs are stabilized here by two approaches. First, a hybrid method is developed by integrating two different stabilization algorithms. At the same time, symmetry inner product is introduced in the generation of ROMs for its known robust behavior for compressible flows. Results have shown a notable improvement in computational efficiency and robustness compared to similar approaches. Second, a new stabilization algorithm is developed specifically for nonlinear ROMs. This method adopts Particle Swarm Optimization to enforce a bounded ROM response for minimum discrepancy between the high fidelity simulation and the ROM outputs. Promising results are obtained in its application on the nonlinear ROM of an inviscid fluid flow with discontinuities. Supported by ARL.
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
Alzheimer's disease: a mathematical model for onset and progression.
Bertsch, Michiel; Franchi, Bruno; Marcello, Norina; Tesi, Maria Carla; Tosin, Andrea
2017-06-01
In this article 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 and 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. Our numerical simulations are in good qualitative agreement with clinical images of the disease distribution in the brain which vary from early to advanced stages. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.
Effective low-order models for atmospheric dynamics and time series analysis.
Gluhovsky, Alexander; Grady, Kevin
2016-02-01
The paper focuses on two interrelated problems: developing physically sound low-order models (LOMs) for atmospheric dynamics and employing them as novel time-series models to overcome deficiencies in current atmospheric time series analysis. The first problem is warranted since arbitrary truncations in the Galerkin method (commonly used to derive LOMs) may result in LOMs that violate fundamental conservation properties of the original equations, causing unphysical behaviors such as unbounded solutions. In contrast, the LOMs we offer (G-models) are energy conserving, and some retain the Hamiltonian structure of the original equations. This work examines LOMs from recent publications to show that all of them that are physically sound can be converted to G-models, while those that cannot lack energy conservation. Further, motivated by recent progress in statistical properties of dynamical systems, we explore G-models for a new role of atmospheric time series models as their data generating mechanisms are well in line with atmospheric dynamics. Currently used time series models, however, do not specifically utilize the physics of the governing equations and involve strong statistical assumptions rarely met in real 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)
Permutation forests for modeling word order in machine translation
Stanojević, M.
2017-01-01
In natural language, there is only a limited space for variation in the word order of linguistic productions. From a linguistic perspective, word order is the result of multiple application of syntactic recursive functions. These syntactic operations produce hierarchical syntactic structures, as
A Novel Method for Decoding Any High-Order Hidden Markov Model
Directory of Open Access Journals (Sweden)
Fei Ye
2014-01-01
Full Text Available This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of the equivalent first-order hidden Markov model is recognized by the existing Viterbi algorithm of the first-order hidden Markov model. Finally, the optimal state sequence of the high-order hidden Markov model is inferred from the optimal state sequence of the equivalent first-order hidden Markov model. This method provides a unified algorithm framework for decoding hidden Markov models including the first-order hidden Markov model and any high-order hidden Markov model.
Reduced Order Aeroservoelastic Models with Rigid Body Modes, Phase II
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...
Towards predictive stochastic dynamical modeling of cancer genesis and progression.
Ao, P; Galas, D; Hood, L; Yin, L; Zhu, X M
2010-06-01
Based on an innovative endogenous network hypothesis on cancer genesis and progression we have been working towards a quantitative cancer theory along the systems biology perspective. Here we give a brief report on our progress and illustrate that combing ideas from evolutionary and molecular biology, mathematics, engineering, and physics, such quantitative approach is feasible.
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 using eigen algorithm | Singh | International ...
African Journals Online (AJOL)
-scale dynamic systems where denominator polynomial determined through Eigen algorithm and numerator polynomial via factor division algorithm. In Eigen algorithm, the most dominant Eigen value of both original and reduced order ...
Directory of Open Access Journals (Sweden)
Christer Dalen
2017-10-01
Full Text Available A model reduction technique based on optimization theory is presented, where a possible higher order system/model is approximated with an unstable DIPTD model by using only step response data. The DIPTD model is used to tune PD/PID controllers for the underlying possible higher order system. Numerous examples are used to illustrate the theory, i.e. both linear and nonlinear models. The Pareto Optimal controller is used as a reference controller.
Progress in Mathematical Modeling of Gastrointestinal Slow Wave Abnormalities.
Du, Peng; Calder, Stefan; Angeli, Timothy R; Sathar, Shameer; Paskaranandavadivel, Niranchan; O'Grady, Gregory; Cheng, Leo K
2017-01-01
Gastrointestinal (GI) motility is regulated in part by electrophysiological events called slow waves, which are generated by the interstitial cells of Cajal (ICC). Slow waves propagate by a process of "entrainment," which occurs over a decreasing gradient of intrinsic frequencies in the antegrade direction across much of the GI tract. Abnormal initiation and conduction of slow waves have been demonstrated in, and linked to, a number of GI motility disorders. A range of mathematical models have been developed to study abnormal slow waves and applied to propose novel methods for non-invasive detection and therapy. This review provides a general outline of GI slow wave abnormalities and their recent classification using multi-electrode (high-resolution) mapping methods, with a particular emphasis on the spatial patterns of these abnormal activities. The recently-developed mathematical models are introduced in order of their biophysical scale from cellular to whole-organ levels. The modeling techniques, main findings from the simulations, and potential future directions arising from notable studies are discussed.
DEFF Research Database (Denmark)
Azarang, Leyla; Scheike, Thomas; de Uña-Álvarez, Jacobo
2017-01-01
In this work, we present direct regression analysis for the transition probabilities in the possibly non-Markov progressive illness–death model. The method is based on binomial regression, where the response is the indicator of the occupancy for the given state along time. Randomly weighted score...
Comparing plasma fluid models of different order for 1D streamer ionization fronts
A. Markosyan (Aram); H.J. Teunissen (Jannis); S. Dujko (Sasa); U. M. Ebert (Ute)
2015-01-01
htmlabstractWe evaluate the performance of three plasma fluid models: the first order reaction-drift-diffusion model based on the local field approximation; the second order reaction-drift-diffusion model based on the local energy approximation and a recently developed high order fluid model by
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
Low-level laser therapy ameliorates disease progression in a mouse model of Alzheimer's disease.
Farfara, Dorit; Tuby, Hana; Trudler, Dorit; Doron-Mandel, Ella; Maltz, Lidya; Vassar, Robert J; Frenkel, Dan; Oron, Uri
2015-02-01
Low-level laser therapy (LLLT) has been used to treat inflammation, tissue healing, and repair processes. We recently reported that LLLT to the bone marrow (BM) led to proliferation of mesenchymal stem cells (MSCs) and their homing in the ischemic heart suggesting its role in regenerative medicine. The aim of the present study was to investigate the ability of LLLT to stimulate MSCs of autologous BM in order to affect neurological behavior and β-amyloid burden in progressive stages of Alzheimer's disease (AD) mouse model. MSCs from wild-type mice stimulated with LLLT showed to increase their ability to maturate towards a monocyte lineage and to increase phagocytosis activity towards soluble amyloid beta (Aβ). Furthermore, weekly LLLT to BM of AD mice for 2 months, starting at 4 months of age (progressive stage of AD), improved cognitive capacity and spatial learning, as compared to sham-treated AD mice. Histology revealed a significant reduction in Aβ brain burden. Our results suggest the use of LLLT as a therapeutic application in progressive stages of AD and imply its role in mediating MSC therapy in brain amyloidogenic diseases.
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...
Abnormal Waves Modelled as Second-order Conditional Waves
DEFF Research Database (Denmark)
Jensen, Jørgen Juncher
2005-01-01
, 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...
LQG controller designs from reduced order models for a launch ...
Indian Academy of Sciences (India)
This paper describes the effort of a multivariable control approach applied to the Geosynchronous Satellite Launch Vehicle (GSLV) of the Indian Space Research Organization (ISRO) during a certain stage of its launch. The fuel slosh dynamics are modelled using a pendulum model analogy. We describe two design ...
Higher-Order Hamiltonian Model for Unidirectional Water Waves
Bona, J. L.; Carvajal, X.; Panthee, M.; Scialom, M.
2018-04-01
Formally second-order correct, mathematical descriptions of long-crested water waves propagating mainly in one direction are derived. These equations are analogous to the first-order approximations of KdV- or BBM-type. The advantage of these more complex equations is that their solutions corresponding to physically relevant initial perturbations of the rest state may be accurate on a much longer timescale. The initial value problem for the class of equations that emerges from our derivation is then considered. A local well-posedness theory is straightforwardly established by a contraction mapping argument. A subclass of these equations possess a special Hamiltonian structure that implies the local theory can be continued indefinitely.
International Nuclear Information System (INIS)
Abdou, M.A.; Tillack, M.S.; Raffray, A.R.
1987-01-01
This document is a progress report on two technical studies carried out during 1986, both of which relate to the implementation phase of FNT. The first, which is a follow-up to FINESSE, focuses on specific key questions for: (1) very near-term (0 to 3 years) non-fusion experiments and facilities, and (2) FNT testing in a fusion facility. The second is the initial stage of a detailed effort to develop theory, models and computer codes for predicting the performance of nuclear components. Chapters are presented on (1) introduction and chapter summaries, (2) non-fusion experiments and facilities, (3) fusion testing issues, and (4) theory and modeling. Chapter 2 is an assessment of the relative advantages of many solid breeders, neutron multipliers and configurations. Various issues affecting design and cost of the blanket are examined in Chapter 3. Chapter 4 reports on the progress of the initial stage of an effort to develop theory and analytical and numerical models for nuclear components. A major part of the effort has focused on modeling of MHD effects for liquid metal blankets. Progress has also been made on modeling tritium transport and inventory in solid breeder blankets and the thermomechanical behavior of liquid-metal-cooled limiters
Order parameter model for unstable multilane traffic flow
Lubashevsky, Ihor A.; Mahnke, Reinhard
1999-01-01
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 phase transitions "free flow -> synchronized motion -> jam" as well as the hysteresis in the transition "free flow synchronized motion". We introduce a new variable called 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 ...
Neutrino masses and their ordering: global data, priors and models
Gariazzo, S.; Archidiacono, M.; de Salas, P. F.; Mena, O.; Ternes, C. A.; Tórtola, M.
2018-03-01
We present a full Bayesian analysis of the combination of current neutrino oscillation, neutrinoless double beta decay and Cosmic Microwave Background observations. Our major goal is to carefully investigate the possibility to single out one neutrino mass ordering, namely Normal Ordering or Inverted Ordering, with current data. Two possible parametrizations (three neutrino masses versus the lightest neutrino mass plus the two oscillation mass splittings) and priors (linear versus logarithmic) are exhaustively examined. We find that the preference for NO is only driven by neutrino oscillation data. Moreover, the values of the Bayes factor indicate that the evidence for NO is strong only when the scan is performed over the three neutrino masses with logarithmic priors; for every other combination of parameterization and prior, the preference for NO is only weak. As a by-product of our Bayesian analyses, we are able to (a) compare the Bayesian bounds on the neutrino mixing parameters to those obtained by means of frequentist approaches, finding a very good agreement; (b) determine that the lightest neutrino mass plus the two mass splittings parametrization, motivated by the physical observables, is strongly preferred over the three neutrino mass eigenstates scan and (c) find that logarithmic priors guarantee a weakly-to-moderately more efficient sampling of the parameter space. These results establish the optimal strategy to successfully explore the neutrino parameter space, based on the use of the oscillation mass splittings and a logarithmic prior on the lightest neutrino mass, when combining neutrino oscillation data with cosmology and neutrinoless double beta decay. We also show that the limits on the total neutrino mass ∑ mν can change dramatically when moving from one prior to the other. These results have profound implications for future studies on the neutrino mass ordering, as they crucially state the need for self-consistent analyses which explore the
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 eyes with incorrect topographies. Interpolation between matched pairs of normal and keratoconic SyntEyes appears to provide an adequate model for 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.
Differential geometry of viscoelastic models with fractional-order derivatives
International Nuclear Information System (INIS)
Yajima, Takahiro; Nagahama, Hiroyuki
2010-01-01
Viscoelastic materials with memory effect are studied based on the fractional rheonomic geometry. The geometric objects are regarded as basic quantities of fractional viscoelastic models, i.e. the metric tensor and torsion tensor are interpreted as the strain and the fractional strain rate, respectively. The generalized viscoelastic equations are expressed by the geometric objects. Especially, the basic constitutive equations such as Voigt and Maxwell models can be derived geometrically from the generalized equation. This leads to the fact that various viscoelastic models can be unified into one geometric expression.
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
Reduced Order Modeling of Combustion Instability in a Gas Turbine Model Combustor
Arnold-Medabalimi, Nicholas; Huang, Cheng; Duraisamy, Karthik
2017-11-01
Hydrocarbon fuel based propulsion systems are expected to remain relevant in aerospace vehicles for the foreseeable future. Design of these devices is complicated by combustion instabilities. The capability to model and predict these effects at reduced computational cost is a requirement for both design and control of these devices. This work focuses on computational studies on a dual swirl model gas turbine combustor in the context of reduced order model development. Full fidelity simulations are performed utilizing URANS and Hybrid RANS-LES with finite rate chemistry. Following this, data decomposition techniques are used to extract a reduced basis representation of the unsteady flow field. These bases are first used to identify sensor locations to guide experimental interrogations and controller feedback. Following this, initial results on developing a control-oriented reduced order model (ROM) will be presented. The capability of the ROM will be further assessed based on different operating conditions and geometric configurations.
Stripe order from the perspective of the Hubbard model
Energy Technology Data Exchange (ETDEWEB)
Devereaux, Thomas Peter
2018-03-01
A microscopic understanding of the strongly correlated physics of the cuprates must account for the translational and rotational symmetry breaking that is present across all cuprate families, commonly in the form of stripes. Here we investigate emergence of stripes in the Hubbard model, a minimal model believed to be relevant to the cuprate superconductors, using determinant quantum Monte Carlo (DQMC) simulations at finite temperatures and density matrix renormalization group (DMRG) ground state calculations. By varying temperature, doping, and model parameters, we characterize the extent of stripes throughout the phase diagram of the Hubbard model. Our results show that including the often neglected next-nearest-neighbor hopping leads to the absence of spin incommensurability upon electron-doping and nearly half-filled stripes upon hole-doping. The similarities of these findings to experimental results on both electron and hole-doped cuprate families support a unified description across a large portion of the cuprate phase diagram.
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.
The Complexity of Model Checking Higher-Order Fixpoint Logic
DEFF Research Database (Denmark)
Axelsson, Roland; Lange, Martin; Somla, Rafal
2007-01-01
Higher Order Fixpoint Logic (HFL) is a hybrid of the simply typed λ-calculus and the modal μ-calculus. This makes it a highly expressive temporal logic that is capable of expressing various interesting correctness properties of programs that are not expressible in the modal μ-calculus. This paper...... 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...
Modelling T4 cell count as a marker of HIV progression in the ...
African Journals Online (AJOL)
Modelling T4 cell count as a marker of HIV progression in the absence of any defense mechanism. VSM Yadavalli, MMO Labeodan, S Udayabaskaran, N Forche. Abstract. The T4 cell count, which is considered one of the markers of disease progression in an HIV infected individual, is modelled in this paper. The World ...
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…
Proposed higher order continuum-based models for an elastic ...
African Journals Online (AJOL)
Three new variants of continuum-based models for an elastic subgrade are proposed. The subgrade is idealized as a homogenous, isotropic elastic layer of thickness H overlying a firm stratum. All components of the stress tensor in the subgrade are taken into account. Reasonable assumptions are made regarding the ...
Next-to-leading order corrections to the valon model
Indian Academy of Sciences (India)
To obtain the proton structure function in valon model with respect to the Laguerre polynomials one needs to use an elegant and fast numerical method at LO up to NLO. Therefore, we concentrate on the Laguerre polynomials in our determinations. In the. Laguerre method [13,14], the Laguerre polynomials are defined as.
A generalized cellular automata approach to modeling first order ...
Indian Academy of Sciences (India)
Cellular automata; enzyme kinetics; extended von-Neumann neighborhood. 1. Introduction. Over the past two decades, there has been a significant growth in the use of computer-generated models to study dynamic phenomena in biochemical systems (Kier et al 2005). The need to include greater details about biochemical ...
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.
Optimization of power rationing order based on fuzzy evaluation model
Zhang, Siyuan; Liu, Li; Xie, Peiyuan; Tang, Jihong; Wang, Canlin
2018-04-01
With the development of production and economic growth, China's electricity load has experienced a significant increase. Over the years, in order to alleviate the contradiction of power shortage, a series of policies and measures to speed up electric power construction have been made in china, which promotes the rapid development of the power industry and the power construction has made great achievements. For China, after large-scale power facilities, power grid long-term power shortage situation has been improved to some extent, but in a certain period of time, the power development still exists uneven development. On the whole, it is still in the state of insufficient power, and the situation of power restriction is still severe in some areas, so it is necessary to study on the power rationing.
Han, Suyue; Chang, Gary Han; Schirmer, Clemens; Modarres-Sadeghi, Yahya
2016-11-01
We construct a reduced-order model (ROM) to study the Wall Shear Stress (WSS) distributions in image-based patient-specific aneurysms models. The magnitude of WSS has been shown to be a critical factor in growth and rupture of human aneurysms. We start the process by running a training case using Computational Fluid Dynamics (CFD) simulation with time-varying flow parameters, such that these parameters cover the range of parameters of interest. The method of snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases using the training CFD simulation. The resulting ROM enables us to study the flow patterns and the WSS distributions over a range of system parameters computationally very efficiently with a relatively small number of modes. This enables comprehensive analysis of the model system across a range of physiological conditions without the need to re-compute the simulation for small changes in the system parameters.
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.
Computer modeling: from sports to spaceflight ... from order to chaos.
Danby, J. M. A.
In this volume the problems of concern are those that can be modeled by systems of ordinary differential equations and cannot be solved by mathematical formulae. The subjects covered are diverse and include chaotic systems; population growth and ecology; sickness and health; competition and economics; sports; travel and reaction; space travel and astronomy; pendulums; springs; chemical and other reacting systems. Accompanying the book is software on a CD-ROM which includes over 50 projects from this book.
LQG controller designs from reduced order models for a launch ...
Indian Academy of Sciences (India)
Performing the indicated operations, assuming τpi and ˙τpi are small quantities and noting that .... Sensors in Rate path. GR = ω2. 2 s2 + 2ξ2ω2s + ω2. 2. , where ω2 = 12·5 Hz = 78·54 rad/sec and ξ2 = 0·7. 3. Formulation of the state space model. The vehicle dynamics including rigid body, slosh and actuators can be written ...
In vitro biological models in order to study BNCT
International Nuclear Information System (INIS)
Dagrosa, Maria A.; Kreimann, Erica L.; Schwint, Amanda E.; Juvenal, Guillermo J.; Pisarev, Mario A.; Farias, Silvia S.; Garavaglia, Ricardo N.; Batistoni, Daniel A.
1999-01-01
Undifferentiated thyroid carcinoma (UTC) lacks an effective treatment. Boron neutron capture therapy (BNCT) is based on the selective uptake of 10 B-boronated compounds by some tumours, followed by irradiation with an appropriate neutron beam. The radioactive boron originated ( 11 B) decays releasing 7 Li, gamma rays and alpha particles, and these latter will destroy the tumour. In order to explore the possibility of applying BNCT to UTC we have studied the biodistribution of BPA. In vitro studies: the uptake of p- 10 borophenylalanine (BPA) by the UTC cell line ARO, primary cultures of normal bovine thyroid cells (BT) and human follicular adenoma (FA) thyroid was studied. No difference in BPA uptake was observed between proliferating and quiescent ARO cells. The uptake by quiescent ARO, BT and FA showed that the ARO/BT and ARO/FA ratios were 4 and 5, respectively (p< 0.001). The present experimental results open the possibility of applying BNCT for the treatment of UTC. (author)
Oxygen Transport Characterization of a Human Model of Progressive Hemorrhage
2010-01-01
treatment of hemorrhaging patients . 2. Methods 2.1. Study design, setting, and population This was a prospective study performed at the USAISR in San...70mmHg, and/or the presence of pre- syncopal symptoms expressed by the subject such as gray-out, sweating, nausea, or dizziness. 2.3. Instrumentation...protocol was terminated.23 This approach avoids attrition of sample size as the individual absolute levels of LBNP progressed and considers the data
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...
Quantization of second-order Lagrangians: Model problem
Moore, R. A.; Scott, T. C.
1991-08-01
Many aspects of a model problem, the Lagrangian of which contains a term depending quadratically on the acceleration, are examined in the regime where the classical solution consists of two independent normal modes. It is shown that the techniques of conversion to a problem of Lagrange, generalized mechanics, and Dirac's method for constrained systems all yield the same canonical form for the Hamiltonian. It is also seen that the resultant canonical equations of motion are equivalent to the Euler-Lagrange equations. In canonical form, all of the standard results apply, quantization follows in the usual way, and the interpretation of the results is straightforward. It is also demonstrated that perturbative methods fail, both classically and quantum mechanically, indicating the need for the nonperturbative techniques applied herein. Finally, it is noted that this result may have fundamental implications for certain relativistic theories.
The Meaning of Higher-Order Factors in Reflective-Measurement Models
Eid, Michael; Koch, Tobias
2014-01-01
Higher-order factor analysis is a widely used approach for analyzing the structure of a multidimensional test. Whenever first-order factors are correlated researchers are tempted to apply a higher-order factor model. But is this reasonable? What do the higher-order factors measure? What is their meaning? Willoughby, Holochwost, Blanton, and Blair…
Spear, D J; Katz, J L
1991-01-01
Reinforcer magnitude and fixed-ratio requirement were varied under two second-order schedules. Under one, the first sequence of a fixed number of responses completed after the lapse of a 10-min fixed interval produced reinforcement. Under the second, a second-order progressive-ratio schedule, the fixed number of responses increased after each reinforcement. Either cocaine (0 to 300 micrograms/kg/inj) or food (0 to 5,700 mg/delivery) reinforcers were delivered. Under some conditions, a 2-s ill...
A parametric model order reduction technique for poroelastic finite element models.
Lappano, Ettore; Polanz, Markus; Desmet, Wim; Mundo, Domenico
2017-10-01
This research presents a parametric model order reduction approach for vibro-acoustic problems in the frequency domain of systems containing poroelastic materials (PEM). The method is applied to the Finite Element (FE) discretization of the weak u-p integral formulation based on the Biot-Allard theory and makes use of reduced basis (RB) methods typically employed for parametric problems. The parametric reduction is obtained rewriting the Biot-Allard FE equations for poroelastic materials using an affine representation of the frequency (therefore allowing for RB methods) and projecting the frequency-dependent PEM system on a global reduced order basis generated with the proper orthogonal decomposition instead of standard modal approaches. This has proven to be better suited to describe the nonlinear frequency dependence and the strong coupling introduced by damping. The methodology presented is tested on two three-dimensional systems: in the first experiment, the surface impedance of a PEM layer sample is calculated and compared with results of the literature; in the second, the reduced order model of a multilayer system coupled to an air cavity is assessed and the results are compared to those of the reference FE model.
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
Widlowski, J.-L.; Taberner, M.; Pinty, B.; Bruniquel-Pinel, V.; Disney, M.; Fernandes, R.; Gastellu-Etchegorry, J.-P.; Gobron, N.; Kuusk, A.; Lavergne, T.; Leblanc, S.; Lewis, P. E.; Martin, E.; Mõttus, M.; North, P. R. J.; Qin, W.; Robustelli, M.; Rochdi, N.; Ruiloba, R.; Soler, C.; Thompson, R.; Verhoef, W.; Verstraete, M. M.; Xie, D.
2007-05-01
The Radiation Transfer Model Intercomparison (RAMI) initiative benchmarks canopy reflectance models under well-controlled experimental conditions. Launched for the first time in 1999, this triennial community exercise encourages the systematic evaluation of canopy reflectance models on a voluntary basis. The first phase of RAMI focused on documenting the spread among radiative transfer (RT) simulations over a small set of primarily 1-D canopies. The second phase expanded the scope to include structurally complex 3-D plant architectures with and without background topography. Here sometimes significant discrepancies were noted which effectively prevented the definition of a reliable "surrogate truth," over heterogeneous vegetation canopies, against which other RT models could then be compared. The present paper documents the outcome of the third phase of RAMI, highlighting both the significant progress that has been made in terms of model agreement since RAMI-2 and the capability of/need for RT models to accurately reproduce local estimates of radiative quantities under conditions that are reminiscent of in situ measurements. Our assessment of the self-consistency and the relative and absolute performance of 3-D Monte Carlo models in RAMI-3 supports their usage in the generation of a "surrogate truth" for all RAMI test cases. This development then leads (1) to the presentation of the "RAMI Online Model Checker" (ROMC), an open-access web-based interface to evaluate RT models automatically, and (2) to a reassessment of the role, scope, and opportunities of the RAMI project in the future.
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...
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.
Zambrano, Andres
2012-01-01
In Venezuela, the name of “barrio” is given to the housing agglomeration set without any city-planning order on a land area that, most of the times, has been illegally occupied. In the barrio zones it is the family that undertakes, from the beginning, the gradual construction of its house, without any intermediary and with scarcely qualified construction workers. This dynamic occupation and following house construction is part of many Venezuelan cities’ growth. In this context, featured by th...
Progress and challenges in coupled hydrodynamic-ecological estuarine modeling.
Ganju, Neil K; Brush, Mark J; Rashleigh, Brenda; Aretxabaleta, Alfredo L; Del Barrio, Pilar; Grear, Jason S; Harris, Lora A; Lake, Samuel J; McCardell, Grant; O'Donnell, James; Ralston, David K; Signell, Richard P; Testa, Jeremy M; Vaudrey, Jamie M P
2016-03-01
Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.
Testing Static Trade-off Against Pecking Order Models of Capital Structure
Lakshmi Shyam-Sunder; Stewart C. Myers
1994-01-01
This paper tests traditional capital structure models against the alternative of a pecking order model of corporate financing. The basic pecking order model, which predicts external debt financing driven by the internal financial deficit, has much greater explanatory power than a static trade-off model which predicts that each firm adjusts toward an optimal debt ratio. We show that the power of some usual tests of the trade-off model is virtually nil. We question whether the available empiric...
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
Pile group program for full material modeling and progressive failure.
2008-12-01
Strain wedge (SW) model formulation has been used, in previous work, to evaluate the response of a single pile or a group of piles (including its : pile cap) in layered soils to lateral loading. The SW model approach provides appropriate prediction f...
International Nuclear Information System (INIS)
1995-01-01
During this reporting period, the authors group has been active in five areas of research: (1) improvements on their x-ray instrumentation at the SUNY Beamline, National Synchrotron Light Source (NSLS) so that they can perform new experiments which are not accessible otherwise; (2) characterization of functionalized hairy rod polymers designed for studying the macromolecular structures in molecular composites; (3) investigation of supramolecular ordered systems composed mainly of block copolymers from dilute to concentrated solutions, including the gel state; (4) evolution of crystalline structures in polymer blends and melts; and (5) multiphase structure of segment polyurethanes
Energy Technology Data Exchange (ETDEWEB)
1995-01-01
During this reporting period, the authors group has been active in five areas of research: (1) improvements on their x-ray instrumentation at the SUNY Beamline, National Synchrotron Light Source (NSLS) so that they can perform new experiments which are not accessible otherwise; (2) characterization of functionalized hairy rod polymers designed for studying the macromolecular structures in molecular composites; (3) investigation of supramolecular ordered systems composed mainly of block copolymers from dilute to concentrated solutions, including the gel state; (4) evolution of crystalline structures in polymer blends and melts; and (5) multiphase structure of segment polyurethanes.
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.
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
Ambrosini, Roberto; Borgoni, Riccardo; Rubolini, Diego; Sicurella, Beatrice; Fiedler, Wolfgang; Bairlein, Franz; Baillie, Stephen R; Robinson, Robert A; Clark, Jacquie A; Spina, Fernando; Saino, Nicola
2014-01-01
Migration is a fundamental stage in the life history of several taxa, including birds, and is under strong selective pressure. At present, the only data that may allow for both an assessment of patterns of bird migration and for retrospective analyses of changes in migration timing are the databases of ring recoveries. We used ring recoveries of the Barn Swallow Hirundo rustica collected from 1908-2008 in Europe to model the calendar date at which a given proportion of birds is expected to have reached a given geographical area ('progression of migration') and to investigate the change in timing of migration over the same areas between three time periods (1908-1969, 1970-1990, 1991-2008). The analyses were conducted using binomial conditional autoregressive (CAR) mixed models. We first concentrated on data from the British Isles and then expanded the models to western Europe and north Africa. We produced maps of the progression of migration that disclosed local patterns of migration consistent with those obtained from the analyses of the movements of ringed individuals. Timing of migration estimated from our model is consistent with data on migration phenology of the Barn Swallow available in the literature, but in some cases it is later than that estimated by data collected at ringing stations, which, however, may not be representative of migration phenology over large geographical areas. The comparison of median migration date estimated over the same geographical area among time periods showed no significant advancement of spring migration over the whole of Europe, but a significant advancement of autumn migration in southern Europe. Our modelling approach can be generalized to any records of ringing date and locality of individuals including those which have not been recovered subsequently, as well as to geo-referenced databases of sightings of migratory individuals.
Directory of Open Access Journals (Sweden)
Godefrooij DA
2017-10-01
Full Text Available Daniel A Godefrooij, Mustapha El Kandoussi, Nienke Soeters, Robert PL Wisse Utrecht Cornea Research Group, Department of Ophthalmology, University Medical Center Utrecht, Utrecht, the Netherlands Purpose: The purpose of this study was to compare the effects of transepithelial crosslinking (trans-CXL versus epithelium-off crosslinking (epi-off CXL for progressive keratoconus with respect to the development of higher order aberrations (HOAs and their effects on visual acuity.Materials and methods: A total of 61 patients were randomized and examined preoperatively and 1, 3, 6, and 12 months postoperatively in an academic referral center. Total corneal HOAs were compared between the two treatment groups using mixed linear modeling. Types of HOAs (coma, trefoil, and spherical aberration that differed between groups were entered in a multivariable analysis to test their effect on uncorrected distance visual acuity (UDVA and corrected distance visual acuity (CDVA.Results: The epi-off CXL group had more flattening in maximal keratometry compared to the trans-CXL group (P=0.02. UDVA did not differ significantly between the groups (P=0.59; however, CDVA was significantly more improved in the trans-CXL group (P=0.02. Horizontal trefoil improved more in the epi-off group compared to the trans-CXL group (P=0.04, whereas the other HOAs were virtually unchanged in both groups. Differences in changes in HOAs between the two groups had no effect on either UCVA (P=0.76 or CDVA (P=0.96.Conclusion: Although HOAs are clinically relevant determinants of vision quality in keratoconus patients, the change in total HOAs post treatment did not differ between the trans-CXL and epi-off CXL groups. Only horizontal trefoil differed significantly post treatment between the trans-CXL and epi-off CXL groups. However, this difference did not independently affect either UDVA or CDVA. Trans-CXL provides no benefit over epi-off CXL regarding visual relevant HOAs. Keywords
Model-order reduction of lumped parameter systems via fractional calculus
Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio
2018-04-01
This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.
Measurements and models for hazardous chemical and mixed wastes. 1998 annual progress report
International Nuclear Information System (INIS)
Holcomb, C.; Louie, B.; Mullins, M.E.; Outcalt, S.L.; Rogers, T.N.; Watts, L.
1998-01-01
'Aqueous waste of various chemical compositions constitutes a significant fraction of the total waste produced by industry in the US. A large quantity of the waste generated by the US chemical process industry is waste water. In addition, the majority of the waste inventory at DoE sites previously used for nuclear weapons production is aqueous waste. Large quantities of additional aqueous waste are expected to be generated during the clean-up of those sites. In order to effectively treat, safely handle, and properly dispose of these wastes, accurate and comprehensive knowledge of basic thermophysical property information is paramount. This knowledge will lead to huge savings by aiding in the design and optimization of treatment and disposal processes. The main objectives of this project are: Develop and validate models that accurately predict the phase equilibria and thermodynamic properties of hazardous aqueous systems necessary for the safe handling and successful design of separation and treatment processes for hazardous chemical and mixed wastes. Accurately measure the phase equilibria and thermodynamic properties of a representative system (water + acetone + isopropyl alcohol + sodium nitrate) over the applicable ranges of temperature, pressure, and composition to provide the pure component, binary, ternary, and quaternary experimental data required for model development. As of May, 1998, nine months into the first year of a three year project, the authors have made significant progress in the database development, have begun testing the models, and have been performance testing the apparatus on the pure components.'
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.
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.
Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.
El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher
2018-01-01
Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.
Shao, C G; Liu, Z Z; Wang, J F; Luo, J
2003-07-01
The L-state Potts model for rumor is the N-spin chain describing how a simple rumor transmitted by N recreant rumormongers is aggrandized. The studied rumor is represented mathematically by a simple proposition with the universal quantifier, which again is represented geometrically by a point in a proposition space. During the transmission, such a proposition is changed with the change of the rumor, which has individual number N0 at the beginning of the transmission. Correspondingly, the point expressing the proposition may start from an arbitrary site at the proposition space, and then it shifts in the space. Thus, a spin sum of the Potts model corresponds to a walk of a point in the proposition space and spin configuration's numbers is given by enumerating the corresponding walks. The concept of the lattice path in combinatorial mathematics is introduced and the exact series representation of the configuration's numbers is given. The partition function exhibits the transition of the chain and critical equivalent inverse temperature beta(c) is determined. Moreover, there is a crossover value of the individual number, N00. The model has a first-order transition when N0N00.
Dynamics of a Fractional Order HIV Infection Model with Specific Functional Response and Cure Rate
Directory of Open Access Journals (Sweden)
Adnane Boukhouima
2017-01-01
Full Text Available We propose a fractional order model in this paper to describe the dynamics of human immunodeficiency virus (HIV infection. In the model, the infection transmission process is modeled by a specific functional response. First, we show that the model is mathematically and biologically well posed. Second, the local and global stabilities of the equilibria are investigated. Finally, some numerical simulations are presented in order to illustrate our theoretical results.
Progress in modeling solidification in molten salt coolants
Tano, Mauricio; Rubiolo, Pablo; Doche, Olivier
2017-10-01
Molten salts have been proposed as heat carrier media in the nuclear and concentrating solar power plants. Due to their high melting temperature, solidification of the salts is expected to occur during routine and accidental scenarios. Furthermore, passive safety systems based on the solidification of these salts are being studied. The following article presents new developments in the modeling of eutectic molten salts by means of a multiphase, multicomponent, phase-field model. Besides, an application of this methodology for the eutectic solidification process of the ternary system LiF-KF-NaF is presented. The model predictions are compared with a newly developed semi-analytical solution for directional eutectic solidification at stable growth rate. A good qualitative agreement is obtained between the two approaches. The results obtained with the phase-field model are then used for calculating the homogenized properties of the solid phase distribution. These properties can then be included in a mixture macroscale model, more suitable for industrial applications.
Wang, Xinsheng; Wang, Chenxu; Yu, Mingyan
2016-07-01
In this paper, we propose a generalised sub-block structure preservation interconnect model order reduction (MOR) technique based on the swarm intelligence method, that is, particle swarm optimisation (PSO). The swarm intelligence-based structure preservation MOR can be used for a standard model as a criterion for different structure preservation interconnect MOR methods. In the proposed technique, the PSO method is used for predicting the unknown elements of structure-preserving reduced-order modelling of interconnect circuits. The prediction is based on minimising the difference of transform function between the original full-order and desired reduced-order systems maintaining the full-order structure in the reduced-order model. The proposed swarm-intelligence-based structure-preserving MOR method is compared with published work on structure preservation MOR SPRIM techniques. Simulation and synthesis results verify the accuracy and validity of the new structure-preserving MOR technique.
Qi, D.; Majda, A.
2017-12-01
A low-dimensional reduced-order statistical closure model is developed for quantifying the uncertainty in statistical sensitivity and intermittency in principal model directions with largest variability in high-dimensional turbulent system and turbulent transport models. Imperfect model sensitivity is improved through a recent mathematical strategy for calibrating model errors in a training phase, where information theory and linear statistical response theory are combined in a systematic fashion to achieve the optimal model performance. The idea in the reduced-order method is from a self-consistent mathematical framework for general systems with quadratic nonlinearity, where crucial high-order statistics are approximated by a systematic model calibration procedure. Model efficiency is improved through additional damping and noise corrections to replace the expensive energy-conserving nonlinear interactions. Model errors due to the imperfect nonlinear approximation are corrected by tuning the model parameters using linear response theory with an information metric in a training phase before prediction. A statistical energy principle is adopted to introduce a global scaling factor in characterizing the higher-order moments in a consistent way to improve model sensitivity. Stringent models of barotropic and baroclinic turbulence are used to display the feasibility of the reduced-order methods. Principal statistical responses in mean and variance can be captured by the reduced-order models with accuracy and efficiency. Besides, the reduced-order models are also used to capture crucial passive tracer field that is advected by the baroclinic turbulent flow. It is demonstrated that crucial principal statistical quantities like the tracer spectrum and fat-tails in the tracer probability density functions in the most important large scales can be captured efficiently with accuracy using the reduced-order tracer model in various dynamical regimes of the flow field with
An isotonic partial credit model for ordering subjects on the basis of their sum scores
Ligtvoet, R.
2012-01-01
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable.
Comparing higher order models for the EORTC QLQ-C30
DEFF Research Database (Denmark)
Gundy, Chad M; Fayers, Peter M; Grønvold, Mogens
2012-01-01
To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire.......To investigate the statistical fit of alternative higher order models for summarizing the health-related quality of life profile generated by the EORTC QLQ-C30 questionnaire....
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.
Qualitative modelling macroeconomics indicators for prediction of progress branch
Directory of Open Access Journals (Sweden)
Jiří Luňáček
2010-01-01
Full Text Available A qualitative modelling philosophy has been developed in an effort to produce a general and reasonably unified common sense approach to the modelling of unique, complex and unsteady state systems. Economics, Ecology, Sociology and Politics are sciences, which study such systems. An integration of sub models from those sciences into supermodels is inevitable if realistic decision making tasks are analysed. Therefore conventional formal tools (e.g. statistics cannot be correctly applied because of lack of information. Qualitative variables are quantified using three values only – positive (increasing, zero (constant and negative (decreasing. Knowledge items of qualitative nature (e.g. if productivity goes up then profit does not decrease are often the only available information. The classical quantitative tools cannot deal with such information items. However, qualitative models can absorb shallow qualitative knowledge and generate all possible scenarios i.e. qualitative solutions. The complete list of scenarios guarantees that any analysis (decision making based on it does not ignore any promising solution. The case study of oil related macro economical risks is presented in details (15 variables e.g. Inflation, Corruption, 14 qualitative relations among the variables. No a priory knowledge of qualitative analysis is required.
Recent progress in the modelling of thermal plasma systems
International Nuclear Information System (INIS)
Xi Chen
2002-01-01
Plasma flow and heat transfer in thermal plasma systems are often of three-dimensional (3-D) features and cannot be well studied by use of a two-dimensional modelling approach. 3-D modelling studies are recently performed in our group. It is found that appreciable 3-D effects exist within non-transferred DC arc plasma torches even for the case with axisymmetrical external conditions. The key for the successful 3-D modelling of the non-transferred arc plasma torch is that the anode-nozzle wall is included in the computational domain. The predicted results are favorably compared with experimental observation. 3-D modelling of the plasma jets with lateral injection of particulate matter and its carrier gas also reveals distinct 3-D effects with the injection velocity and the distance between the carrier-gas injection-tube tip and the jet edge as critical parameters. The 3-D effects appreciably influence the trajectories and heating histories of particles injected into the plasma jet. (author)
The Choice of a Progressive Bilingual Education Model
Zelin, Li
2017-01-01
Bilingual education has unique and complex features. In the course of language study, with the mother tongue as a foundation, acquiring a second language depends on the features of student's learning and age. Based on the construction of J. Cummins's (1984) dual iceberg theory dual-language model, students' bilingual education is founded on the…
Progress towards a lightning ignition model for the Northern Rockies
Paul Sopko; Don Latham
2010-01-01
We are in the process of constructing a lightning ignition model specific to the Northern Rockies using fire occurrence, lightning strike, ecoregion, and historical weather, NFDRS (National Fire Danger Rating System), lightning efficiency and lightning "possibility" data. Daily grids for each of these categories were reconstructed for the 2003 fire season (...
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.
Modelling of Lime Kiln Using Subspace Method with New Order Selection Criterion
Directory of Open Access Journals (Sweden)
Li Zhang
2014-01-01
Full Text Available This paper is taking actual control demand of rotary kiln as background and builds a calcining belt state space model using PO-Moesp subspace method. A novel order-delay double parameters error criterion (ODC is presented to reduce the modeling order. The proposed subspace order identification method takes into account the influence of order and delay on model error criterion simultaneously. For the introduction of the delay factors, the order is reduced dramatically in the system modeling. Also, in the data processing part sliding-window method is adopted for stripping delay factor from historical data. For this, the parameters can be changed flexibly. Some practical problems in industrial kiln process modeling are also solved. Finally, it is applied to an industrial kiln case.
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.
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.
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
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.
Recent progress in modelling 3D lithospheric deformation
Kaus, B. J. P.; Popov, A.; May, D. A.
2012-04-01
Modelling 3D lithospheric deformation remains a challenging task, predominantly because the variations in rock types, as well as nonlinearities due to for example plastic deformation result in sharp and very large jumps in effective viscosity contrast. As a result, there are only a limited number of 3D codes available, most of which are using direct solvers which are computationally and memory-wise very demanding. As a result, the resolutions for typical model runs are quite modest, despite the use of hundreds of processors (and using much larger computers is unlikely to bring much improvement in this situation). For this reason we recently developed a new 3D deformation code,called LaMEM: Lithosphere and Mantle Evolution Model. LaMEM is written on top of PETSc, and as a result it runs on massive parallel machines and we have a large number of iterative solvers available (including geometric and algebraic multigrid methods). As it remains unclear which solver combinations work best under which conditions, we have implemented most currently suggested methods (such as schur complement reduction or Fully coupled iterations). In addition, we can use either a finite element discretization (with Q1P0, stabilized Q1Q1 or Q2P-1 elements) or a staggered finite difference discretization for the same input geometry, which is based on a marker and cell technique). This gives us he flexibility to test various solver methodologies on the same model setup, in terms of accuracy, speed, memory usage etc. Here, we will report on some features of LaMEM, on recent code additions, as well as on some lessons we learned which are important for modelling 3D lithospheric deformation. Specifically we will discuss: 1) How we combine a particle-and-cell method to make it work with both a finite difference and a (lagrangian, eulerian or ALE) finite element formulation, with only minor code modifications code 2) How finite difference and finite element discretizations compare in terms of
Zheng, Guo; Wang, Jue; Wang, Lin; Zhou, Muchun; Xin, Yu; Song, Minmin
2017-11-15
The general formulae for second-order moments of Schell-model beams with various correlation functions in atmospheric turbulence are derived and validated by the Bessel-Gaussian Schell-model beams and cosine-Gaussian-correlated Schell-model beams. Our finding shows that the second-order moments of partially coherent Schell-model beams are related to the second-order partial derivatives of source spectral degree of coherence at the origin. The formulae we provide are much more convenient to analyze and research propagation problems in turbulence.
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
Progress towards quantum simulating the classical O(2) Model
2014-12-01
by L3, the third component of the angular momentum in the SU(2) Lie algebra . Pursuing the analogy, we replace e±iθ̂ by an operator proportional to the...becomes diagonal because In(0) = 0 except for n = 0 [I0(0) = 1], and by the conservation law the same index nx characterizes the interaction along the time...Understanding how the symmetries of this initial tensor affect the universality class is under study. The O(2) model has an exact conservation law
Fast Simulating High Order Models Application to Micro Electro-Mechanical Systems (MEMS)
International Nuclear Information System (INIS)
Yacine, Z.; Benfdila, A.; Djennoune, S.
2009-01-01
The approximation of high order systems by low order models is one of the important problems in system theory. The use of a reduced order model makes it easier to implement analysis, simulations and control system designs. Numerous methods are available in the literature for order reduction of linear continuous systems in time domain as well as in frequency domain. But, this is not the case for non linear systems. The well known Trajectory Piece-Wise Linear approach (TPWL) elaborated to nonlinear model order reduction guarantees a simplification and an accurate representation of the behaviour of strongly non linear systems handling local and global approximation. The present attempt is towards evolving an improvement for the TPWL order reduction technique, which ensures a good quality of approximation combining the advantages of the Krylov subspaces method and the local linearization. We illustrate the technique on a MEMS circuit (Micro Electro-Mechanical System).
Progress in lung modelling by the ICRP Task Group
International Nuclear Information System (INIS)
James, A.C.; Birchall, A.
1989-01-01
The Task Group has reviewed the data on: (a) morphology and physiology of the human respiratory tract; (b) inspirability of aerosols and their deposition in anatomical regions as functions of respiratory parameters; (c) clearance of particles within and from the respiratory tract; (d) absorption of different materials into the blood in humans and in animals. The Task Group proposes a new model which predicts the deposition, retention and systemic uptake of materials, enabling doses absorbed by different respiratory tissues and other body organs to be evaluated. In the proposed model, clearance is described in terms of competition between the processes moving particles to the oropharynx or to lymph nodes and that of absorption into the blood. From studies with human subjects, characteristic rates and pathways are defined to represent mechanical clearance of particles from each region, which do not depend on the material. Conversely, the absorption rate is determined solely by the material: it is assumed to be the same in all parts of the respiratory tract and in other animal species. For several of the radiologically important forms of actinides, absorption rates can be derived from animal experiments, or, in some cases, directly from human data. Otherwise, default values are used, based on the current D, W and Y classification system. (author)
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.
Reprogramming of human cancer cells to pluripotency for models of cancer progression.
Kim, Jungsun; Zaret, Kenneth S
2015-03-12
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. © 2015 The Authors.
A seventh-order model for dynamic response of an electro-hydraulic servo valve
Directory of Open Access Journals (Sweden)
Liu Changhai
2014-12-01
Full Text Available 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.
Empirical analyses of a choice model that captures ordering among attribute values
DEFF Research Database (Denmark)
Mabit, Stefan Lindhard
2017-01-01
an alternative additionally because it has the highest price. In this paper, we specify a discrete choice model that takes into account the ordering of attribute values across alternatives. This model is used to investigate the effect of attribute value ordering in three case studies related to alternative-fuel...... vehicles, mode choice, and route choice. In our application to choices among alternative-fuel vehicles, we see that especially the price coefficient is sensitive to changes in ordering. The ordering effect is also found in the applications to mode and route choice data where both travel time and cost...
A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression
International Nuclear Information System (INIS)
Dutta-Moscato, Joyeeta; Solovyev, Alexey; Mi, Qi; Nishikawa, Taichiro; Soto-Gutierrez, Alejandro; Fox, Ira J.; Vodovotz, Yoram
2014-01-01
Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl 4 ). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl 4 -treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl 4 -injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into
A Multiscale Agent-Based in silico Model of Liver Fibrosis Progression
Energy Technology Data Exchange (ETDEWEB)
Dutta-Moscato, Joyeeta [Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Solovyev, Alexey [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Mathematics, University of Pittsburgh, Pittsburgh, PA (United States); Mi, Qi [Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA (United States); Nishikawa, Taichiro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Soto-Gutierrez, Alejandro [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Pathology, University of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Fox, Ira J. [McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States); Department of Surgery, Children’s Hospital of Pittsburgh, Pittsburgh, PA (United States); Thomas E. Starzl Transplantation Institute, University of Pittsburgh, Pittsburgh, PA (United States); Vodovotz, Yoram, E-mail: vodovotzy@upmc.edu [Department of Surgery, University of Pittsburgh, Pittsburgh, PA (United States); Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA (United States)
2014-05-30
Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM) of liver tissue in order to computationally examine the consequence of liver inflammation. Our liver fibrosis ABM (LFABM) is comprised of literature-derived rules describing molecular and histopathological aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathological features observed in liver sections from rats treated with carbon tetrachloride (CCl{sub 4}). An in silico “tension test” for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl{sub 4}-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing tumor necrosis factor alpha vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathological and macroscopic properties of CCl{sub 4}-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant
A multiscale agent-based in silico model of liver fibrosis progression
Directory of Open Access Journals (Sweden)
Joyeeta eDutta-Moscato
2014-05-01
Full Text Available Chronic hepatic inflammation involves a complex interplay of inflammatory and mechanical influences, ultimately manifesting in a characteristic histopathology of liver fibrosis. We created an agent-based model (ABM of liver tissue in order to computationally examine the consequence of liver inflammation. Our Liver Fibrosis ABM (LFABM is comprised of literature-derived rules describing molecular and histopathologic aspects of inflammation and fibrosis in a section of chemically injured liver. Hepatocytes are modeled as agents within hexagonal lobules. Injury triggers an inflammatory reaction, which leads to activation of local Kupffer cells and recruitment of monocytes from circulation. Portal fibroblasts and hepatic stellate cells are activated locally by the products of inflammation. The various agents in the simulation are regulated by above-threshold concentrations of pro- and anti-inflammatory cytokines and damage-associated molecular pattern (DAMP molecules. The simulation progresses from chronic inflammation to collagen deposition, exhibiting periportal fibrosis followed by bridging fibrosis, and culminating in disruption of the regular lobular structure. The ABM exhibited key histopathologic features observed in liver sections from rats treated with carbon tetrachloride (CCl4. An in silico tension test for the hepatic lobules predicted an overall increase in tissue stiffness, in line with clinical elastography literature and published studies in CCl4-treated rats. Therapy simulations suggested differential anti-fibrotic effects of neutralizing TNF-a vs. enhancing M2 Kupffer cells. We conclude that a computational model of liver inflammation on a structural skeleton of physical forces can recapitulate key histopathologic and macroscopic properties of CCl4-injured liver. This multiscale approach linking molecular and chemomechanical stimuli enables a model that could be used to gain translationally relevant insights into live fibrosis.
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.
Giotopoulos, George; van der Weyden, Louise; Osaki, Hikari; Rust, Alistair G.; Gallipoli, Paolo; Meduri, Eshwar; Horton, Sarah J.; Chan, Wai-In; Foster, Donna; Prinjha, Rab K.; Pimanda, John E.; Tenen, Daniel G.; Vassiliou, George S.; Koschmieder, Steffen; Adams, David J.
2015-01-01
The introduction of highly selective ABL-tyrosine kinase inhibitors (TKIs) has revolutionized therapy for chronic myeloid leukemia (CML). However, TKIs are only efficacious in the chronic phase of the disease and effective therapies for TKI-refractory CML, or after progression to blast crisis (BC), are lacking. Whereas the chronic phase of CML is dependent on BCR-ABL, additional mutations are required for progression to BC. However, the identity of these mutations and the pathways they affect are poorly understood, hampering our ability to identify therapeutic targets and improve outcomes. Here, we describe a novel mouse model that allows identification of mechanisms of BC progression in an unbiased and tractable manner, using transposon-based insertional mutagenesis on the background of chronic phase CML. Our BC model is the first to faithfully recapitulate the phenotype, cellular and molecular biology of human CML progression. We report a heterogeneous and unique pattern of insertions identifying known and novel candidate genes and demonstrate that these pathways drive disease progression and provide potential targets for novel therapeutic strategies. Our model greatly informs the biology of CML progression and provides a potent resource for the development of candidate therapies to improve the dismal outcomes in this highly aggressive disease. PMID:26304963
Reduced-order LPV model of flexible wind turbines from high fidelity aeroelastic codes
DEFF Research Database (Denmark)
Adegas, Fabiano Daher; Sønderby, Ivan Bergquist; Hansen, Morten Hartvig
2013-01-01
of high-order linear time invariant (LTI) models. Firstly, the high-order LTI models are locally approximated using modal and balanced truncation and residualization. Then, an appropriate coordinate transformation is applied to allow interpolation of the model matrices between points on the parameter...... space. The obtained LPV model is of suitable size for designing modern gain-scheduling controllers based on recently developed LPV control design techniques. Results are thoroughly assessed on a set of industrial wind turbine models generated by the recently developed aeroelastic code HAWCStab2....
Snodgrass, Michael; Kalaida, Natasha; Winer, E Samuel
2009-06-01
Access can either be first-order or second-order. First order access concerns whether contents achieve representation in phenomenal consciousness at all; second-order access concerns whether phenomenally conscious contents are selected for metacognitive, higher order processing by reflective consciousness. When the optional and flexible nature of second-order access is kept in mind, there remain strong reasons to believe that exclusion failure can indeed isolate phenomenally conscious stimuli that are not so accessed. Irvine's [Irvine, E. (2009). Signal detection theory, the exclusion failure paradigm and weak consciousness-Evidence for the access/phenomenal distinction? Consciousness and Cognition.] partial access argument fails because exclusion failure is indeed due to lack of second-order access, not insufficient phenomenally conscious information. Further, the enable account conforms with both qualitative differences and subjective report, and is simpler than the endow account. Finally, although first-order access may be a distinct and important process, second-order access arguably reflects the core meaning of access generally.
Applications of computer modeling to fusion research. Progress report, 1988--1989
Energy Technology Data Exchange (ETDEWEB)
Dawson, J.M.
1989-12-31
Progress achieved during this report period is presented on the following topics: Development and application of gyrokinetic particle codes to tokamak transport, development of techniques to take advantage of parallel computers; model dynamo and bootstrap current drive; and in general maintain our broad-based program in basic plasma physics and computer modeling.
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.
Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments
Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh
2018-03-01
Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.
A Low Order Model for Analyzing effects of Blade Fatigue Load Control
DEFF Research Database (Denmark)
Kallesøe, Bjarne Skovmose
2006-01-01
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, and tor......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......, 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...
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.
Directory of Open Access Journals (Sweden)
Yang Xiao-Jun
2017-01-01
Full Text Available In this paper, we address a class of the fractional derivatives of constant and variable orders for the first time. Fractional-order relaxation equations of constants and variable orders in the sense of Caputo type are modeled from mathematical view of point. The comparative results of the anomalous relaxation among the various fractional derivatives are also given. They are very efficient in description of the complex phenomenon arising in heat transfer.
Xiang, Hong-Jun; Zhang, Zhi-Wei; Shi, Zhi-Fei; Li, Hong
2018-04-01
A fully coupled modeling approach is developed for piezoelectric energy harvesters in this work based on the use of available robust finite element packages and efficient reducing order modeling techniques. At first, the harvester is modeled using finite element packages. The dynamic equilibrium equations of harvesters are rebuilt by extracting system matrices from the finite element model using built-in commands without any additional tools. A Krylov subspace-based scheme is then applied to obtain a reduced-order model for improving simulation efficiency but preserving the key features of harvesters. Co-simulation of the reduced-order model with nonlinear energy harvesting circuits is achieved in a system level. Several examples in both cases of harmonic response and transient response analysis are conducted to validate the present approach. The proposed approach allows to improve the simulation efficiency by several orders of magnitude. Moreover, the parameters used in the equivalent circuit model can be conveniently obtained by the proposed eigenvector-based model order reduction technique. More importantly, this work establishes a methodology for modeling of piezoelectric energy harvesters with any complicated mechanical geometries and nonlinear circuits. The input load may be more complex also. The method can be employed by harvester designers to optimal mechanical structures or by circuit designers to develop novel energy harvesting circuits.
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.
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...... stall using only few states. A set of reduced-order models obtained at various operating points are shown to be easily connected by interpolation and are thereby suited for gain-scheduling control design. A new method is proposed to reduce separately the number of structural and aerodynamic states...
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…
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…
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
Reardon, Sean F.; Shear, Benjamin R.; Castellano, Katherine E.; Ho, Andrew D.
2017-01-01
Test score distributions of schools or demographic groups are often summarized by frequencies of students scoring in a small number of ordered proficiency categories. We show that heteroskedastic ordered probit (HETOP) models can be used to estimate means and standard deviations of multiple groups' test score distributions from such data. Because…
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
Large-order behavior of nondecoupling effects in the standard model and triviality
International Nuclear Information System (INIS)
Aoki, K.
1994-01-01
We compute some nondecoupling effects in the standard model, such as the ρ parameter, to all orders in the coupling constant expansion. We analyze their large order behavior and explicitly show how they are related to the nonperturbative cutoff dependence of these nondecoupling effects due to the triviality of the theory
Recent progress of an integrated implosion code and modeling of element physics
International Nuclear Information System (INIS)
Nagatomo, H.; Takabe, H.; Mima, K.; Ohnishi, N.; Sunahara, A.; Takeda, T.; Nishihara, K.; Nishiguchu, A.; Sawada, K.
2001-01-01
Physics of the inertial fusion is based on a variety of elements such as compressible hydrodynamics, radiation transport, non-ideal equation of state, non-LTE atomic process, and relativistic laser plasma interaction. In addition, implosion process is not in stationary state and fluid dynamics, energy transport and instabilities should be solved simultaneously. In order to study such complex physics, an integrated implosion code including all physics important in the implosion process should be developed. The details of physics elements should be studied and the resultant numerical modeling should be installed in the integrated code so that the implosion can be simulated with available computer within realistic CPU time. Therefore, this task can be basically separated into two parts. One is to integrate all physics elements into a code, which is strongly related to the development of hydrodynamic equation solver. We have developed 2-D integrated implosion code which solves mass, momentum, electron energy, ion energy, equation of states, laser ray-trace, laser absorption radiation, surface tracing and so on. The reasonable results in simulating Rayleigh-Taylor instability and cylindrical implosion are obtained using this code. The other is code development on each element physics and verification of these codes. We had progress in developing a nonlocal electron transport code and 2 and 3 dimension radiation hydrodynamic code. (author)
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,...
The formulation and estimation of a spatial skew-normal generalized ordered-response model.
2016-06-01
This paper proposes a new spatial generalized ordered response model with skew-normal kernel error terms and an : associated estimation method. It contributes to the spatial analysis field by allowing a flexible and parametric skew-normal : distribut...
Novel Reduced Order in Time Models for Problems in Nonlinear Aeroelasticity, Phase I
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...
Universal block diagram based modeling and simulation schemes for fractional-order control systems.
Bai, Lu; Xue, Dingyü
2017-05-08
Universal block diagram based schemes are proposed for modeling and simulating the fractional-order control systems in this paper. A fractional operator block in Simulink is designed to evaluate the fractional-order derivative and integral. Based on the block, the fractional-order control systems with zero initial conditions can be modeled conveniently. For modeling the system with nonzero initial conditions, the auxiliary signal is constructed in the compensation scheme. Since the compensation scheme is very complicated, therefore the integrator chain scheme is further proposed to simplify the modeling procedures. The accuracy and effectiveness of the schemes are assessed in the examples, the computation results testify the block diagram scheme is efficient for all Caputo fractional-order ordinary differential equations (FODEs) of any complexity, including the implicit Caputo FODEs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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.
Tabberer, Maggie; Gonzalez-McQuire, Sebastian; Muellerova, Hana; Briggs, Andrew H; Rutten-van Mölken, Maureen P M H; Chambers, Mike; Lomas, David A
2017-05-01
To develop and validate a new conceptual model (CM) of chronic obstructive pulmonary disease (COPD) for use in disease progression and economic modeling. The CM identifies and describes qualitative associations between disease attributes, progression and outcomes. A literature review was performed to identify any published CMs or literature reporting the impact and association of COPD disease attributes with outcomes. After critical analysis of the literature, a Steering Group of experts from the disciplines of health economics, epidemiology and clinical medicine was convened to develop a draft CM, which was refined using a Delphi process. The refined CM was validated by testing for associations between attributes using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). Disease progression attributes included in the final CM were history and occurrence of exacerbations, lung function, exercise capacity, signs and symptoms (cough, sputum, dyspnea), cardiovascular disease comorbidities, 'other' comorbidities (including depression), body composition (body mass index), fibrinogen as a biomarker, smoking and demographic characteristics (age, gender). Mortality and health-related quality of life were determined to be the most relevant final outcome measures for this model, intended to be the foundation of an economic model of COPD. The CM is being used as the foundation for developing a new COPD model of disease progression and to provide a framework for the analysis of patient-level data. The CM is available as a reference for the implementation of further disease progression and economic models.
Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States
Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter M.; Brenner, Martin J.
2017-01-01
This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12× reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design.
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.
A seventh-order model for dynamic response of an electro-hydraulic servo valve
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 resu...
A fourth order spline collocation approach for a business cycle model
Sayfy, A.; Khoury, S.; Ibdah, H.
2013-10-01
A collocation approach, based on a fourth order cubic B-splines is presented for the numerical solution of a Kaleckian business cycle model formulated by a nonlinear delay differential equation. The equation is approximated and the nonlinearity is handled by employing an iterative scheme arising from Newton's method. It is shown that the model exhibits a conditionally dynamical stable cycle. The fourth-order rate of convergence of the scheme is verified numerically for different special cases.
Generalized Gramian Framework for Model/Controller Order Reduction of Switched Systems
DEFF Research Database (Denmark)
Shaker, Hamid Reza; Wisniewski, Rafal
2011-01-01
In this article, a general method for model/controller order reduction of switched linear dynamical systems is presented. The proposed technique is based on the generalised gramian framework for model reduction. It is shown that different classical reduction methods can be developed into a genera......In this article, a general method for model/controller order reduction of switched linear dynamical systems is presented. The proposed technique is based on the generalised gramian framework for model reduction. It is shown that different classical reduction methods can be developed...
Maguire, Sarah L.; Peck, Barrie; Wai, Patty T.; Campbell, James; Barker, Holly; Gulati, Aditi; Daley, Frances; Vyse, Simon; Huang, Paul; Lord, Christopher J.; Farnie, Gillian; Brennan, Keith; Natrajan, Rachael
2016-01-01
Abstract The initiation and progression of breast cancer from the transformation of the normal epithelium to ductal carcinoma in situ (DCIS) and invasive disease is a complex process involving the acquisition of genetic alterations and changes in gene expression, alongside microenvironmental and recognized histological alterations. Here, we sought to comprehensively characterise the genomic and transcriptomic features of the MCF10 isogenic model of breast cancer progression, and to functional...
Sanchez, Christopher M.
2011-01-01
NASA White Sands Test Facility (WSTF) is leading an evaluation effort in advanced destructive and nondestructive testing of composite pressure vessels and structures. WSTF is using progressive finite element analysis methods for test design and for confirmation of composite pressure vessel performance. Using composite finite element analysis models and failure theories tested in the World-Wide Failure Exercise, WSTF is able to estimate the static strength of composite pressure vessels. Additionally, test and evaluation on composites that have been impact damaged is in progress so that models can be developed to estimate damage tolerance and the degradation in static strength.
Flexible implementation of the Ensemble Model with arbitrary order of moments
Energy Technology Data Exchange (ETDEWEB)
Ackermann, W. [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder (TEMF), Schlossgartenstrasse 8, D 64289 Darmstadt (Germany)]. E-mail: ackermann@temf.tu-darmstadt.de; Weiland, T. [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder (TEMF), Schlossgartenstrasse 8, D 64289 Darmstadt (Germany)]. E-mail: thomas.weiland@temf.tu-darmstadt.de
2006-03-01
The Ensemble Model takes advantage of an approach to express the phase space particle distribution function in terms of the first, second and higher order moments instead of considering individual particles. Based on a new flexible implementation, an arbitrary number of orders can be processed and automatically converted into proper update equations for the simulation program V-Code. In this paper the influence of the introduction of higher order moments on the beam dynamics simulation is investigated. The achievable accuracy and the numerical efforts are compared with the ones obtained from the lower order calculations.
Modeling 3D PCMI using the Extended Finite Element Method with higher order elements
Energy Technology Data Exchange (ETDEWEB)
Jiang, W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Spencer, Benjamin W. [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2017-03-31
This report documents the recent development to enable XFEM to work with higher order elements. It also demonstrates the application of higher order (quadratic) elements to both 2D and 3D models of PCMI problems, where discrete fractures in the fuel are represented using XFEM. The modeling results demonstrate the ability of the higher order XFEM to accurately capture the effects of a crack on the response in the vicinity of the intersecting surfaces of cracked fuel and cladding, as well as represent smooth responses in the regions away from the crack.
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.
Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts
Hamid, R.; Pabunga, D. B.
2017-09-01
The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.
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).
[Research on high-order Windkessel model for assessing vascular compliance].
Ren, Yinzi; Xu, Jing; Gong, Shijin; Li, Li; Hu, Qijun; Yan, Jing; Ning, Gangmin
2011-04-01
In this paper, we propose the construction of a fifth-order Windkessel model, and give complete mathematical solutions for this model. Utilizing the diastolic pulse wave analytical methods, we derived the parameters of the mathematical model. The parameters were further applied to estimate arterial compliance, blood flow inertia, peripheral resistance and other indices. With simulation tools we assess the validity of the model, and built a simulation circuit with the model parameters R, C and L. The model parameters were obtained from the high-order Windkessel model. The stroke volume of left ventricle is employed as the input of the simulation circuit. At the end of the circuit, the responding signal was gained. And it in turn was compared with the measured pulse waveform. The results show that the fifth-order Windkessel model is superior to the third-order Windkessel model in the pulse wave fitting and stability, and thus better reflects the role of microvessles in the circulatory system.
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
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.
Directory of Open Access Journals (Sweden)
C.G. Ozoegwu
2016-01-01
Full Text Available The general least squares model for milling process state term is presented. A discrete map for milling stability analysis that is based on the third-order case of the presented general least squares milling state term model is first studied and compared with its third-order counterpart that is based on the interpolation theory. Both numerical rate of convergence and chatter stability results of the two maps are compared using the single degree of freedom (1DOF milling model. The numerical rate of convergence of the presented third-order model is also studied using the two degree of freedom (2DOF milling process model. Comparison gave that stability results from the two maps agree closely but the presented map demonstrated reduction in number of needed calculations leading to about 30% savings in computational time (CT. It is seen in earlier works that accuracy of milling stability analysis using the full-discretization method rises from first-order theory to second-order theory and continues to rise to the third-order theory. The present work confirms this trend. In conclusion, the method presented in this work will enable fast and accurate computation of stability diagrams for use by machinists.
Shi, Jinfei; Zhu, Songqing; Chen, Ruwen
2017-12-01
An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.
Qi, Di
Turbulent dynamical systems are ubiquitous in science and engineering. Uncertainty quantification (UQ) in turbulent dynamical systems is a grand challenge where the goal is to obtain statistical estimates for key physical quantities. In the development of a proper UQ scheme for systems characterized by both a high-dimensional phase space and a large number of instabilities, significant model errors compared with the true natural signal are always unavoidable due to both the imperfect understanding of the underlying physical processes and the limited computational resources available. One central issue in contemporary research is the development of a systematic methodology for reduced order models that can recover the crucial features both with model fidelity in statistical equilibrium and with model sensitivity in response to perturbations. In the first part, we discuss a general mathematical framework to construct statistically accurate reduced-order models that have skill in capturing the statistical variability in the principal directions of a general class of complex systems with quadratic nonlinearity. A systematic hierarchy of simple statistical closure schemes, which are built through new global statistical energy conservation principles combined with statistical equilibrium fidelity, are designed and tested for UQ of these problems. Second, the capacity of imperfect low-order stochastic approximations to model extreme events in a passive scalar field advected by turbulent flows is investigated. The effects in complicated flow systems are considered including strong nonlinear and non-Gaussian interactions, and much simpler and cheaper imperfect models with model error are constructed to capture the crucial statistical features in the stationary tracer field. Several mathematical ideas are introduced to improve the prediction skill of the imperfect reduced-order models. Most importantly, empirical information theory and statistical linear response theory are
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.
Time-Frequency Analysis Using Warped-Based High-Order Phase Modeling
Directory of Open Access Journals (Sweden)
Ioana Cornel
2005-01-01
Full Text Available The high-order ambiguity function (HAF was introduced for the estimation of polynomial-phase signals (PPS embedded in noise. Since the HAF is a nonlinear operator, it suffers from noise-masking effects and from the appearance of undesired cross-terms when multicomponents PPS are analyzed. In order to improve the performances of the HAF, the multi-lag HAF concept was proposed. Based on this approach, several advanced methods (e.g., product high-order ambiguity function (PHAF have been recently proposed. Nevertheless, performances of these new methods are affected by the error propagation effect which drastically limits the order of the polynomial approximation. This phenomenon acts especially when a high-order polynomial modeling is needed: representation of the digital modulation signals or the acoustic transient signals. This effect is caused by the technique used for polynomial order reduction, common for existing approaches: signal multiplication with the complex conjugated exponentials formed with the estimated coefficients. In this paper, we introduce an alternative method to reduce the polynomial order, based on the successive unitary signal transformation, according to each polynomial order. We will prove that this method reduces considerably the effect of error propagation. Namely, with this order reduction method, the estimation error at a given order will depend only on the performances of the estimation method.
Higher Order Moments Generation by Mellin Transform for Compound Models of Clutter
Bhattacharya, C
2008-01-01
The compound models of clutter statistics are found suitable to describe the nonstationary nature of radar backscattering from high-resolution observations. In this letter, we show that the properties of Mellin transform can be utilized to generate higher order moments of simple and compound models of clutter statistics in a compact manner.
Estimation of Higher Order Moments for Compound Models of Clutter by Mellin Transform
Bhattacharya, C
2008-01-01
The compound models of clutter statistics are found suitable to describe the nonstationary nature of radar backscattering from high-resolution observations. In this letter, we show that the properties of Mellin transform can be utilized to generate higher order moments of simple and compound models of clutter statistics in a compact manner
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…
A Fuel-Sensitive Reduced-Order Model (ROM) for Piston Engine Scaling Analysis
2017-09-29
computational fluid dynamics simulations resolving the transient 3-D spray behavior have been performed to validate the model... computational fluid dynamics , fuels 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF PAGES 56...from the work of Naber and Siebers (Naber and Siebers 1996; Siebers 1999) and a full-order model (FOM) based on 3-D– computational fluid dynamics
An efficient flexible-order model for coastal and ocean water waves
DEFF Research Database (Denmark)
Engsig-Karup, Allan Peter; Bingham, Harry B.; Lindberg, Ole
Current work are directed toward the development of an improved numerical 3D model for fully nonlinear potential water waves over arbitrary depths. The model is high-order accurate, robust and efficient for large-scale problems, and support will be included for flexibility in the description of s...
First Order Fire Effects Model: FOFEM 4.0, user's guide
Elizabeth D. Reinhardt; Robert E. Keane; James K. Brown
1997-01-01
A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.
Guirguis, A A; Slape, C I; Failla, L M; Saw, J; Tremblay, C S; Powell, D R; Rossello, F; Wei, A; Strasser, A; Curtis, D J
2016-06-01
Myelodysplastic syndrome (MDS) is characterized by ineffective hematopoiesis with resultant cytopenias. Increased apoptosis and aberrantly functioning progenitors are thought to contribute to this phenotype. As is the case for other malignancies, overcoming apoptosis is believed to be important in progression toward acute myeloid leukemia (AML). Using the NUP98-HOXD13 (NHD13) transgenic mouse model of MDS, we previously reported that overexpression of the anti-apoptotic protein BCL2, blocked apoptosis and improved cytopenias, paradoxically, delaying leukemic progression. To further understand this surprising result, we examined the role of p53 and its pro-apoptotic effectors, PUMA and NOXA in NHD13 mice. The absence of p53 or PUMA but not NOXA reduced apoptosis and expanded the numbers of MDS-repopulating cells. Despite a similar effect on apoptosis and cell numbers, the absence of p53 and PUMA had diametrically opposed effects on progression to AML: absence of p53 accelerated leukemic progression, while absence of PUMA significantly delayed progression. This may be explained in part by differences in cellular responses to DNA damage. The absence of p53 led to higher levels of γ-H2AX (indicative of persistent DNA lesions) while PUMA-deficient NHD13 progenitors resolved DNA lesions in a manner comparable to wild-type cells. These results suggest that targeting PUMA may improve the cytopenias of MDS without a detrimental effect on leukemic progression thus warranting further investigation.
Directory of Open Access Journals (Sweden)
Bin Wang
2016-01-01
Full Text Available This paper studies the application of frequency distributed model for finite time control of a fractional order nonlinear hydroturbine governing system (HGS. Firstly, the mathematical model of HGS with external random disturbances is introduced. Secondly, a novel terminal sliding surface is proposed and its stability to origin is proved based on the frequency distributed model and Lyapunov stability theory. Furthermore, based on finite time stability and sliding mode control theory, a robust control law to ensure the occurrence of the sliding motion in a finite time is designed for stabilization of the fractional order HGS. Finally, simulation results show the effectiveness and robustness of the proposed scheme.
Directory of Open Access Journals (Sweden)
Thanoon Y. Thanoon
2016-03-01
Full Text Available In this paper, ordered categorical variables are used to compare between linear and nonlinear interactions of fixed covariate and latent variables Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution is used to handle the problem of ordered categorical data. Statistical inferences, which involve estimation of parameters and their standard deviations, and residuals analyses for testing the selected model, are discussed. The proposed procedure is illustrated by a simulation data obtained from R program. Analysis are done by using OpenBUGS program.
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
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.
Effective high-order solver with thermally perfect gas model for hypersonic heating prediction
International Nuclear Information System (INIS)
Jiang, Zhenhua; Yan, Chao; Yu, Jian; Qu, Feng; Ma, Libin
2016-01-01
Highlights: • Design proper numerical flux for thermally perfect gas. • Line-implicit LUSGS enhances efficiency without extra memory consumption. • Develop unified framework for both second-order MUSCL and fifth-order WENO. • The designed gas model can be applied to much wider temperature range. - Abstract: Effective high-order solver based on the model of thermally perfect gas has been developed for hypersonic heat transfer computation. The technique of polynomial curve fit coupling to thermodynamics equation is suggested to establish the current model and particular attention has been paid to the design of proper numerical flux for thermally perfect gas. We present procedures that unify five-order WENO (Weighted Essentially Non-Oscillatory) scheme in the existing second-order finite volume framework and a line-implicit method that improves the computational efficiency without increasing memory consumption. A variety of hypersonic viscous flows are performed to examine the capability of the resulted high order thermally perfect gas solver. Numerical results demonstrate its superior performance compared to low-order calorically perfect gas method and indicate its potential application to hypersonic heating predictions for real-life problem.
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.
Ordering Cost Reduction in Inventory Model with Defective Items and Backorder Price Discount
Directory of Open Access Journals (Sweden)
Karuppuchamy Annadurai
2014-01-01
Full Text Available In the real market, as unsatisfied demands occur, the longer the length of lead time is, the smaller the proportion of backorder would be. In order to make up for the inconvenience and even the losses of royal and patient customers, the supplier may offer a backorder price discount to secure orders during the shortage period. Also, ordering policies determined by conventional inventory models may be inappropriate for the situation in which an arrival lot contains some defective items. To compensate for the inconvenience of backordering and to secure orders, the supplier may offer a price discount on the stockout item. The purpose of this study is to explore a coordinated inventory model including defective arrivals by allowing the backorder price discount and ordering cost as decision variables. There are two inventory models proposed in this paper, one with normally distributed demand and another with distribution free demand. A computer code using the software Matlab 7.0 is developed to find the optimal solution and present numerical examples to illustrate the models. The results in the numerical examples indicate that the savings of the total cost are realized through ordering cost reduction and backorder price discount.
Vermeer, Koen A.; Vos, Frans M.; Lo, Barrick; Zhou, Qienyuan; Lemij, Hans G.; Vossepoel, Albert M.; van Vliet, Lucas J.
2006-01-01
The development of methods to detect slowly progressing diseases is often hampered by the time-consuming acquisition of a sufficiently large data set. In this paper, a method is presented to model the change in images acquired by scanning laser polarimetry, for the detection of glaucomatous
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.
Dynamical building simulation: A low order model for thermal bridges losses
Energy Technology Data Exchange (ETDEWEB)
Gao, Y. [School of Environment and Energy, Beijing University of Civil Engineering and Architecture, Beijing 100044 (China); Roux, J.J. [Centre de thermique de Lyon, CNRS-UMR 5008 - UCBL - INSA de LYON, Domaine scientifique de la Doua, Bat. Reyssinet, 40 rue des arts, Villeurbanne 69100 (France); Zhao, L.H. [Department of Architecture, South China University of Technology, GuangZhou 510640 (China); Jiang, Y. [School of Architecture, Tsinghua University, Beijing 100084 (China)
2008-07-01
Thermal bridges losses represent an increasing part of heat losses owing to significant three-dimensional heat transfer characteristics in modern buildings, but one-dimensional models are used in most simulation software for thermal analyses to simplify the calculations. State model reduction techniques were used to develop low-order three-dimensional heat transfer model for additional losses of thermal bridges, which is efficient and accuracy. Coupling this technique with traditional one-dimensional model for walls losses, it is possible to reduce a large amount of time simulations. Low-order model was validated from frequency response and time-domain output. And the effect of this model was shown with its implementation in software ''TRNSYS''. (author)
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
the stability properties of the original closed loop model. The analysis shows that the currents dynamics influence the stability of the microgrid particularly for high values of the frequency droop control parameters. It is also shown that a further reduction of the model order leads to the typical oscillator......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...
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.
Energy Technology Data Exchange (ETDEWEB)
Emmert, G.A.
1983-08-01
The research performed under Task II of this contract has focused on (1) the coupling of an ECRH ray tracing and absorption code to a tandem mirror transport code in order to self-consistently model the temporal and spatial evolution of the plasma, and (2) the further development of a semi-analytical kinetic model for plasma flow in divertors and pumped limiters. Work on these topics is briefly summarized in this progress report.
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.
Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis F
2013-10-01
Vehicle operating speed measured on roadways is a critical component for a host of analysis in the transportation field including transportation safety, traffic flow modeling, roadway geometric design, vehicle emissions modeling, and road user route decisions. The current research effort contributes to the literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model in the literature. The proposed formulation allows us to model the proportion of vehicles traveling in each speed interval for the entire segment of roadway. We extend the model to allow the influence of exogenous variables to vary across the population. Further, we develop a panel mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the speed distribution. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate
Accuracy Analysis of the Zero-Order Hold Model for Digital Pulsewidth Modulation
DEFF Research Database (Denmark)
Ma, Junpeng; Wang, Xiongfei; Blaabjerg, Frede
2018-01-01
This paper analyzes the accuracy of the zero-order hold (ZOH) model for the digital pulsewidth modulator (DPWM) in the s-domain. The s-domain model and the exact z-domain model for the control loop of the single-phase inverter with L-type filter is elaborated for quantifying the deviation...... of the ZOH model for DPWM. The influence of the different computational delay and duty-cycle update modes on this deviation is analyzed in detail. The compensation method for this deviation of the ZOH model is proposed for accurately predicting the stability region of the control system in the s...
Computer modeling of point defects and diffusion in ordered intermetallic compounds
Mishin, Y.
2003-03-01
This paper gives an overview of the recent progress in the understanding of diffusion mechanisms in ordered intermetallic compounds, particularly the structural aluminides TiAl and NiAl. The long-range order of the crystal structure imposes selection rules on possible diffusion mechanisms. It favors mechanisms that either do not affect the order or destroy it only locally and temporarily but recover it once the diffusion cycle is complete. Atomistic simulation tools for studying point defects and diffusion in ordered structures are discussed and their applications are demonstrated. The compositional disorder in TiAl is accommodated by antisite defects on both sides of the stoichiometry. Diffusion in TiAl involves sublattice vacancy jumps, inter-sublattice jumps, and three-jump vacancy cycles. NiAl contains antisites on the Al sublattice in Ni-rich compositions and constitutional vacancies on the Ni sublattice in Al-rich compositions. Diffusion in NiAl is governed by several mechanisms operating concurrently, including sublattice diffusion of Ni vacancies, six-jump vacancy cycles, and other processes. Many of the vacancy jumps are collective transitions involving two atoms. The dominant diffusion mechanism depends on the temperature and the degree of off-stoichiometry. The diffusion coefficients obtained by atomistic calculations compare well with experimental data.
National Research Council Canada - National Science Library
Gertig, Dorota M; Erbas, Bircan; Bymes, Gram; Dowty, James
2005-01-01
... IS. Similar results were found for histological grade. We have developed a computer simulation for mammographic screening data which models progression and detection of Ductal carcinoma in situ...
Cherry, Benjamin M; Korde, Neha; Kwok, Mary; Manasanch, Elisabet E; Bhutani, Manisha; Mulquin, Marcia; Zuchlinski, Diamond; Yancey, Mary Ann; Maric, Irina; Calvo, Katherine R; Braylan, Raul; Stetler-Stevenson, Maryalice; Yuan, Constance; Tembhare, Prashant; Zingone, Adriana; Costello, Rene; Roschewski, Mark J; Landgren, Ola
2013-10-01
The risk of progression to multiple myeloma (MM) from the precursor condition smoldering MM (SMM) varies considerably among individual patients. Reliable markers for progression to MM are vital to advance the understanding of myeloma precursor disease and for the development of intervention trials designed to delay/prevent MM. The Mayo Clinic and Spanish PETHEMA have proposed models to stratify patient risk based on clinical parameters. The aim of our study was to define the degree of concordance between these two models by comparing the distribution of patients with SMM classified as low, medium and high risk for progression. A total of 77 patients with SMM were enrolled in our prospective natural history study. Per study protocol, each patient was assigned risk scores based on both the Mayo and the Spanish models. The Mayo Clinic model identified 38, 35 and four patients as low, medium and high risk, respectively. The Spanish PETHEMA model classified 17, 22 and 38 patients as low, medium and high risk, respectively. There was significant discordance in overall patient risk classification (28.6% concordance) and in classifying patients as low versus high (p < 0.0001), low versus non-low (p = 0.0007) and high versus non-high (p < 0.0001) risk. There is a need for prospectively validated models to characterize individual patient risk of transformation to MM.
Applying the Rule Space Model to Develop a Learning Progression for Thermochemistry
Chen, Fu; Zhang, Shanshan; Guo, Yanfang; Xin, Tao
2017-12-01
We used the Rule Space Model, a cognitive diagnostic model, to measure the learning progression for thermochemistry for senior high school students. We extracted five attributes and proposed their hierarchical relationships to model the construct of thermochemistry at four levels using a hypothesized learning progression. For this study, we developed 24 test items addressing the attributes of exothermic and endothermic reactions, chemical bonds and heat quantity change, reaction heat and enthalpy, thermochemical equations, and Hess's law. The test was administered to a sample base of 694 senior high school students taught in 3 schools across 2 cities. Results based on the Rule Space Model analysis indicated that (1) the test items developed by the Rule Space Model were of high psychometric quality for good analysis of difficulties, discriminations, reliabilities, and validities; (2) the Rule Space Model analysis classified the students into seven different attribute mastery patterns; and (3) the initial hypothesized learning progression was modified by the attribute mastery patterns and the learning paths to be more precise and detailed.
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
A High Order Filter with Galerkin Finite Element Method for the Spherical Local domain Model
Lee, C. H.; Cheong, H. B.; Kang, H. G.
2017-12-01
A High Order Filter with Galerkin Finite Element Method for the Spherical Local domain ModelChung-Hui Lee1 and Hyeong-Bin Cheong and Hyun-Gyu KangDepartment of Environmental Atmospheric Sciences, Pukyong National University, Busan, Korea (1 chlee@pukyong.ac.kr) A high-order filter with Galerkin finite element method is constructed by applying a two dimensional finite element method with quadrilateral basis functions to the spherical limited area domain. The quadrilateral basis function is defined as four shape-functions on separate four grid-boxes which share the same gridpoint. A first-order derivative is represented with an algebraic equation consisting of nine point stencil. Helmholtz equation on a sphere is the basic component of the high order filter and the filtering is performed by solving this equation with two dimensional finite element method. As the theory describes, for spherical Laplacian operator and first-order derivative, the convergence rates of the error were revealed to be second-order and fourth-order, respectively. In addition, since the convergence rate of errors for the filter in this study was the same as the filter with Fourier finite element method, the accuracy of the filter is comparable to the filter based on the Fourier finite element method. The high-order filter was applied to the WRF (Weather Research and Forecasting) as hyper-viscosity and its performance was compared with those of the built-in viscosity scheme of the WRF model. As a result of the tropical cyclone simulation, the forecast error for the high-order filter and the built-in viscosity were similar for the minimum pressure and track prediction. However, for the precipitation and rainfall distribution, the prediction with high-order filter appeared closer to observations than those with built-in viscosity.
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.
Ferroquadrupolar Order in the Spin-1 Bilinear-Biquadratic Model up to the Second Nearest Neighbor
Pires, A. S. T.
2017-10-01
We have studied some ferroquadrupolar phases of the S = 1 Heisenberg model with bilinear and biquadratic exchange interactions on the square lattice up to the second nearest neighbor, using the SU(3) Schwinger bosons formalism in a mean field approximation. This technique is very convenient to treat nematic order. This technique has the advantage of using the fundamental representation of the SU(N) group instead of SU(2), designed to capture spin-quadrupolar order in addition to the dipolar magnetic order. We also present quadrupole structure factors that can be measured in future experiments. Our calculations can have implications in the study of iron-based superconductors.
Study on the Business Cycle Model with Fractional-Order Time Delay under Random Excitation
Directory of Open Access Journals (Sweden)
Zifei Lin
2017-07-01
Full Text Available Time delay of economic policy and memory property in a real economy system is omnipresent and inevitable. In this paper, a business cycle model with fractional-order time delay which describes the delay and memory property of economic control is investigated. Stochastic averaging method is applied to obtain the approximate analytical solution. Numerical simulations are done to verify the method. The effects of the fractional order, time delay, economic control and random excitation on the amplitude of the economy system are investigated. The results show that time delay, fractional order and intensity of random excitation can all magnify the amplitude and increase the volatility of the economy system.
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.
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
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.
Gómez-Aguilar, J. F.
2018-03-01
In this paper, we analyze an alcoholism model which involves the impact of Twitter via Liouville-Caputo and Atangana-Baleanu-Caputo fractional derivatives with constant- and variable-order. Two fractional mathematical models are considered, with and without delay. Special solutions using an iterative scheme via Laplace and Sumudu transform were obtained. We studied the uniqueness and existence of the solutions employing the fixed point postulate. The generalized model with variable-order was solved numerically via the Adams method and the Adams-Bashforth-Moulton scheme. Stability and convergence of the numerical solutions were presented in details. Numerical examples of the approximate solutions are provided to show that the numerical methods are computationally efficient. Therefore, by including both the fractional derivatives and finite time delays in the alcoholism model studied, we believe that we have established a more complete and more realistic indicator of alcoholism model and affect the spread of the drinking.
Viable inflationary models ending with a first-order phase transition
International Nuclear Information System (INIS)
Cortes, Marina; Liddle, Andrew R.
2009-01-01
We investigate the parameter space of two-field inflation models where inflation terminates via a first-order phase transition causing nucleation of bubbles. Such models experience a tension from the need to ensure nearly scale-invariant density perturbations, while avoiding a near scale-invariant bubble size distribution which would conflict observations. We perform an exact analysis of the different regimes of the models, where the energy density of the inflaton field ranges from being negligible as compared to the vacuum energy to providing most of the energy for inflation. Despite recent microwave anisotropy results favoring a spectral index less than 1, we find that there are still viable models that end with bubble production and can match all available observations. As a by-product of our analysis, we also provide an up-to-date assessment of the viable parameter space of Linde's original second-order hybrid model across its full parameter range.
Enhanced regime predictability in atmospheric low-order models due to stochastic forcing.
Kwasniok, Frank
2014-06-28
Regime predictability in atmospheric low-order models augmented with stochastic forcing is studied. Atmospheric regimes are identified as persistent or metastable states using a hidden Markov model analysis. A somewhat counterintuitive, coherence resonance-like effect is observed: regime predictability increases with increasing noise level up to an intermediate optimal value, before decreasing when further increasing the noise level. The enhanced regime predictability is due to increased persistence of the regimes. The effect is found in the Lorenz '63 model and a low-order model of barotropic flow over topography. The increased predictability is only present in the regime dynamics, that is, in a coarse-grained view of the system; predictability of individual trajectories decreases monotonically with increasing noise level. A possible explanation for the phenomenon is given and implications of the finding for weather and climate modelling and prediction are discussed. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Determination of Economic Order Quantity in a fuzzy EOQ Model using of GMIR Deffuzification
Directory of Open Access Journals (Sweden)
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.
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.
[Biomass dynamics of tree branches of higher order. A model analysis].
Galitskiĭ, V V
2012-01-01
The sectional model of biomass dynamics of freely growing tree brahcnes of all orders is presented. The model is an extension of the sectional tree biomass model proposed earlier. The branches model showed bell-shaped dynamics of a branches biomass and, accordingly, boundedness of branch orders number. The important element of the model of branches system is the inter-verticil green biomass. The model is parameterized on the basis of published data on lifespan of branches of different orders and age in which the biomass of skeletal branches of spruce, Picea abies (L.) Karst, reaches the maximum. When adding known peculiarities of spruce growth (such as the initial growth inhibiton and presence of the inter-verticil branches) to the model of biomass dynamics of regular branches system, good appproximation of all natural data by model values is obtained. The possible mechanism of inter-verticil branches appearance in response to improvement of a tree growth conditions, and also their function in a tree growth process, namely replacement of regular branches incapable of appropriate response, is described. Initiation of appearing and/or waking of the sleeping (adventive) buds which give rise to inter-verticil branches is probably caused by rise of pressure of photosynthates in a tree phloem what the published results of experiments on a decapitaion of branches of Wollemia nobilis (Araucariaceae) also testify.
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.
A POD reduced order unstructured mesh ocean modelling method for moderate Reynolds number flows
Fang, F.; Pain, C. C.; Navon, I. M.; Gorman, G. J.; Piggott, M. D.; Allison, P. A.; Farrell, P. E.; Goddard, A. J. H.
Herein a new approach to enhance the accuracy of a novel Proper Orthogonal Decomposition (POD) model applied to moderate Reynolds number flows (of the type typically encountered in ocean models) is presented. This approach develops the POD model of Fang et al. [Fang, F., Pain, C.C., Navon, I.M., Piggott, M.D., Gorman, G.J., Allison, P., Goddard, A.J.H., 2008. Reduced-order modelling of an adaptive mesh ocean model. International Journal for Numerical Methods in Fluids. doi:10.1002/fld.1841] used in conjunction with the Imperial College Ocean Model (ICOM), an adaptive, non-hydrostatic finite element model. Both the velocity and vorticity results of the POD reduced order model (ROM) exhibit an overall good agreement with those obtained from the full model. The accuracy of the POD-Galerkin model with the use of adaptive meshes is first evaluated using the Munk gyre flow test case with Reynolds numbers ranging between 400 and 2000. POD models using the L2 norm become oscillatory when the Reynolds number exceeds Re=400. This is because the low-order truncation of the POD basis inhibits generally all the transfers between the large and the small (unresolved) scales of the fluid flow. Accuracy is improved by using the H1 POD projector in preference to the L2 POD projector. The POD bases are constructed by incorporating gradients as well as function values in the H1 Sobolev norm. The accuracy of numerical results is further enhanced by increasing the number of snapshots and POD bases. Error estimation was used to assess the effect of truncation (involved in the POD-Galerkin approach) when adaptive meshes are used in conjunction with POD/ROM. The RMSE of velocity results between the full model and POD-Galerkin model is reduced by as much as 50% by using the H1 norm and increasing the number of snapshots and POD bases.
Directory of Open Access Journals (Sweden)
Jackalina M Van Kampen
Full Text Available 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
Energy Technology Data Exchange (ETDEWEB)
Honerkamp, Carsten [Institute for Theoretical Solid State Physics, RWTH Aachen University (Germany); JARA - Fundamentals of Future Information Technology, Aachen (Germany)
2017-11-15
We investigate the impact of electron self-energy corrections on potential antiferromagnetic ordering instabilities in mono- and bilayer graphene, modeled by a Hubbard-type lattice model with onsite interactions among the electrons, using a self-consistent random phase approximation (RPA). In qualitative agreement with earlier studies we find that the electronic interactions cause non-Fermi liquid behavior at low energies. In self-consistent RPA, the transition scales for antiferromagnetic ordering are renormalized significantly by these self-energy effects, both for interaction-driven and temperature-driven cases. (copyright 2017 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
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
Arana-Guajardo, Ana; Pérez-Barbosa, Lorena; Vega-Morales, David; Riega-Torres, Janett; Esquivel-Valerio, Jorge; Garza-Elizondo, Mario
2014-01-01
Different prediction rules have been applied to patients with undifferentiated arthritis (UA) to identify those that progress to rheumatoid arthritis (RA). The Leiden Prediction Rule (LPR) has proven useful in different UA cohorts. To apply the LPR to a cohort of patients with UA of northeastern Mexico. We included 47 patients with UA, LPR was applied at baseline. They were evaluated and then classified after one year of follow-up into two groups: those who progressed to RA (according to ACR 1987) and those who did not. 43% of the AI patients developed RA. In the RA group, 56% of patients obtained a score ≤ 6 and only 15% ≥ 8. 70% who did not progress to RA had a score between 6 and ≤ 8. There was no difference in median score of LPR between groups, p=0.940. Most patients who progressed to RA scored less than 6 points in the LPR. Unlike what was observed in other cohorts, the model in our population did not allow us to predict the progression of the disease. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.
Progression of renal cell carcinoma is inhibited by genistein and radiation in an orthotopic model
International Nuclear Information System (INIS)
Hillman, Gilda G; Wang, Yu; Che, Mingxin; Raffoul, Julian J; Yudelev, Mark; Kucuk, Omer; Sarkar, Fazlul H
2007-01-01
We have previously reported the potentiation of radiotherapy by the soy isoflavone genistein for prostate cancer using prostate tumor cells in vitro and orthotopic prostate tumor models in vivo. However, when genistein was used as single therapy in animal models, it promoted metastasis to regional para-aortic lymph nodes. To clarify whether these intriguing adverse effects of genistein are intrinsic to the orthotopic prostate tumor model, or these results could also be recapitulated in another model, we used the orthotopic metastatic KCI-18 renal cell carcinoma (RCC) model established in our laboratory. The KCI-18 RCC cell line was generated from a patient with papillary renal cell carcinoma. Following orthotopic renal implantation of KCI-18 RCC cells and serial in vivo kidney passages in nude mice, we have established a reliable and predictable metastatic RCC tumor model. Mice bearing established kidney tumors were treated with genistein combined with kidney tumor irradiation. The effect of the therapy was assessed on the primary tumor and metastases to various organs. In this experimental model, the karyotype and histological characteristics of the human primary tumor are preserved. Tumor cells metastasize from the primary renal tumor to the lungs, liver and mesentery mimicking the progression of RCC in humans. Treatment of established kidney tumors with genistein demonstrated a tendency to stimulate the growth of the primary kidney tumor and increase the incidence of metastasis to the mesentery lining the bowel. In contrast, when given in conjunction with kidney tumor irradiation, genistein significantly inhibited the growth and progression of established kidney tumors. These findings confirm the potentiation of radiotherapy by genistein in the orthotopic RCC model as previously shown in orthotopic models of prostate cancer. Our studies in both RCC and prostate tumor models demonstrate that the combination of genistein with primary tumor irradiation is a more
Joint modelling of longitudinal CEA tumour marker progression and survival data on breast cancer
Borges, Ana; Sousa, Inês; Castro, Luis
2017-06-01
This work proposes the use of Biostatistics methods to study breast cancer in patients of Braga's Hospital Senology Unit, located in Portugal. The primary motivation is to contribute to the understanding of the progression of breast cancer, within the Portuguese population, using a more complex statistical model assumptions than the traditional analysis that take into account a possible existence of a serial correlation structure within a same subject observations. We aim to infer which risk factors aect the survival of Braga's Hospital patients, diagnosed with breast tumour. Whilst analysing risk factors that aect a tumour markers used on the surveillance of disease progression the Carcinoembryonic antigen (CEA). As survival and longitudinal processes may be associated, it is important to model these two processes together. Hence, a joint modelling of these two processes to infer on the association of these was conducted. A data set of 540 patients, along with 50 variables, was collected from medical records of the Hospital. A joint model approach was used to analyse these data. Two dierent joint models were applied to the same data set, with dierent parameterizations which give dierent interpretations to model parameters. These were used by convenience as the ones implemented in R software. Results from the two models were compared. Results from joint models, showed that the longitudinal CEA values were signicantly associated with the survival probability of these patients. A comparison between parameter estimates obtained in this analysis and previous independent survival[4] and longitudinal analysis[5][6], lead us to conclude that independent analysis brings up bias parameter estimates. Hence, an assumption of association between the two processes in a joint model of breast cancer data is necessary. Results indicate that the longitudinal progression of CEA is signicantly associated with the probability of survival of these patients. Hence, an assumption of
Mahachie John, Jestinah M; Cattaert, Tom; Lishout, François Van; Gusareva, Elena S; Steen, Kristel Van
2012-01-01
Identifying gene-gene interactions or gene-environment interactions in studies of human complex diseases remains a big challenge in genetic epidemiology. An additional challenge, often forgotten, is to account for important lower-order genetic effects. These may hamper the identification of genuine epistasis. If lower-order genetic effects contribute to the genetic variance of a trait, identified statistical interactions may simply be due to a signal boost of these effects. In this study, we restrict attention to quantitative traits and bi-allelic SNPs as genetic markers. Moreover, our interaction study focuses on 2-way SNP-SNP interactions. Via simulations, we assess the performance of different corrective measures for lower-order genetic effects in Model-Based Multifactor Dimensionality Reduction epistasis detection, using additive and co-dominant coding schemes. Performance is evaluated in terms of power and familywise error rate. Our simulations indicate that empirical power estimates are reduced with correction of lower-order effects, likewise familywise error rates. Easy-to-use automatic SNP selection procedures, SNP selection based on "top" findings, or SNP selection based on p-value criterion for interesting main effects result in reduced power but also almost zero false positive rates. Always accounting for main effects in the SNP-SNP pair under investigation during Model-Based Multifactor Dimensionality Reduction analysis adequately controls false positive epistasis findings. This is particularly true when adopting a co-dominant corrective coding scheme. In conclusion, automatic search procedures to identify lower-order effects to correct for during epistasis screening should be avoided. The same is true for procedures that adjust for lower-order effects prior to Model-Based Multifactor Dimensionality Reduction and involve using residuals as the new trait. We advocate using "on-the-fly" lower-order effects adjusting when screening for SNP-SNP interactions
Dyjas, Oliver; Ulrich, Rolf
2014-01-01
In typical discrimination experiments, participants are presented with a constant standard and a variable comparison stimulus and their task is to judge which of these two stimuli is larger (comparative judgement). In these experiments, discrimination sensitivity depends on the temporal order of these stimuli (Type B effect) and is usually higher when the standard precedes rather than follows the comparison. Here, we outline how two models of stimulus discrimination can account for the Type B effect, namely the weighted difference model (or basic Sensation Weighting model) and the Internal Reference Model. For both models, the predicted psychometric functions for comparative judgements as well as for equality judgements, in which participants indicate whether they perceived the two stimuli to be equal or not equal, are derived and it is shown that the models also predict a Type B effect for equality judgements. In the empirical part, the models' predictions are evaluated. To this end, participants performed a duration discrimination task with comparative judgements and with equality judgements. In line with the models' predictions, a Type B effect was observed for both judgement types. In addition, a time-order error, as indicated by shifts of the psychometric functions, and differences in response times were observed only for the equality judgement. Since both models entail distinct additional predictions, it seems worthwhile for future research to unite the two models into one conceptual framework.
A model of the nerve impulse using two first-order differential equations
Hindmarsh, J. L.; Rose, R. M.
1982-03-01
The Hodgkin-Huxley model1 of the nerve impulse consists of four coupled nonlinear differential equations, six functions and seven constants. Because of the complexity of these equations and the necessity for numerical solution, it is difficult to use them in simulations of interactions in small neural networks. Thus, it would be useful to have a second-order differential equation which predicted correctly properties such as the frequency-current relationship. Fitzhugh2 introduced a second-order model of the nerve impulse, but his equations predict an action potential duration which is similar to the inter-spike interval3 and they do not give a reasonable frequency-current relationship. To develop a second-order model having few parameters but which does not have these disadvantages, we have generalized the second-order Fitzhugh equations2, and based the form of the functions in the new equations on voltage-clamp data obtained from a snail neurone. We report here an unexpected property of the resulting equations-the x and y null clines in the phase plane lie close together when the phase point is on the recovery side of the phase plane. The resulting slow movement along the phase path gives a long inter-spike interval, a property not shown clearly by previous models2,4. The model also predicts the linearity of the frequency-current relationship, and may be useful for studying detailed interactions in networks containing small numbers of neurones.
Directory of Open Access Journals (Sweden)
Philipp Singer
Full Text Available One of the most frequently used models for understanding human navigation on the Web is the Markov chain model, where Web pages are represented as states and hyperlinks as probabilities of navigating from one page to another. Predominantly, human navigation on the Web has been thought to satisfy the memoryless Markov property stating that the next page a user visits only depends on her current page and not on previously visited ones. This idea has found its way in numerous applications such as Google's PageRank algorithm and others. Recently, new studies suggested that human navigation may better be modeled using higher order Markov chain models, i.e., the next page depends on a longer history of past clicks. Yet, this finding is preliminary and does not account for the higher complexity of higher order Markov chain models which is why the memoryless model is still widely used. In this work we thoroughly present a diverse array of advanced inference methods for determining the appropriate Markov chain order. We highlight strengths and weaknesses of each method and apply them for investigating memory and structure of human navigation on the Web. Our experiments reveal that the complexity of higher order models grows faster than their utility, and thus we confirm that the memoryless model represents a quite practical model for human navigation on a page level. However, when we expand our analysis to a topical level, where we abstract away from specific page transitions to transitions between topics, we find that the memoryless assumption is violated and specific regularities can be observed. We report results from experiments with two types of navigational datasets (goal-oriented vs. free form and observe interesting structural differences that make a strong argument for more contextual studies of human navigation in future work.
DEFF Research Database (Denmark)
Brodin, Nils Patrik; Vogelius, Ivan R.; Bjørk-Eriksson, Thomas
2013-01-01
As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published...
Maguire, Sarah L; Peck, Barrie; Wai, Patty T; Campbell, James; Barker, Holly; Gulati, Aditi; Daley, Frances; Vyse, Simon; Huang, Paul; Lord, Christopher J; Farnie, Gillian; Brennan, Keith; Natrajan, Rachael
2016-11-01
The initiation and progression of breast cancer from the transformation of the normal epithelium to ductal carcinoma in situ (DCIS) and invasive disease is a complex process involving the acquisition of genetic alterations and changes in gene expression, alongside microenvironmental and recognized histological alterations. Here, we sought to comprehensively characterise the genomic and transcriptomic features of the MCF10 isogenic model of breast cancer progression, and to functionally validate potential driver alterations in three-dimensional (3D) spheroids that may provide insights into breast cancer progression, and identify targetable alterations in conditions more similar to those encountered in vivo. We performed whole genome, exome and RNA sequencing of the MCF10 progression series to catalogue the copy number and mutational and transcriptomic landscapes associated with progression. We identified a number of predicted driver mutations (including PIK3CA and TP53) that were acquired during transformation of non-malignant MCF10A cells to their malignant counterparts that are also present in analysed primary breast cancers from The Cancer Genome Atlas (TCGA). Acquisition of genomic alterations identified MYC amplification and previously undescribed RAB3GAP1-HRAS and UBA2-PDCD2L expressed in-frame fusion genes in malignant cells. Comparison of pathway aberrations associated with progression showed that, when cells are grown as 3D spheroids, they show perturbations of cancer-relevant pathways. Functional interrogation of the dependency on predicted driver events identified alterations in HRAS, PIK3CA and TP53 that selectively decreased cell growth and were associated with progression from preinvasive to invasive disease only when cells were grown as spheroids. Our results have identified changes in the genomic repertoire in cell lines representative of the stages of breast cancer progression, and demonstrate that genetic dependencies can be uncovered when cells
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.
Lie Symmetry Analysis of a First-Order Feedback Model of Option Pricing
Directory of Open Access Journals (Sweden)
Winter Sinkala
2015-01-01
Full Text Available A first-order feedback model of option pricing consisting of a coupled system of two PDEs, a nonliner generalised Black-Scholes equation and the classical Black-Scholes equation, is studied using Lie symmetry analysis. This model arises as an extension of the classical Black-Scholes model when liquidity is incorporated into the market. We compute the admitted Lie point symmetries of the system and construct an optimal system of the associated one-dimensional subalgebras. We also construct some invariant solutions of the 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
A Study of Enhanced, Higher Order Boussinesq-Type Equations and Their Numerical Modelling
DEFF Research Database (Denmark)
Banijamali, Babak
model is designated for the solution of higher-order Boussinesq-type equations, formulated in terms of the horizontal velocity at an arbitrary depth vector. Various discretisation techniques and grid definitions have been considered in this endeavour, undertaking a detailed analysis of the selected......This project has encompassed efforts in two separate veins: on the one hand, the acquiring of highly accurate model equations of the Boussinesq-type, and on the other hand, the theoretical and practical work in implementing such equations in the form of conventional numerical models, with obvious...... potential for applications to the realm of numerical modelling in coastal engineering. The derivation and analysis of several forms of higher-order in dispersion and non-linearity Boussinesq-type equations have been undertaken, obtaining and investigating the properties of a new and generalised class...
Mixed Lp Estimators Variety for Model Order Reduction in Control Oriented System Identification
Directory of Open Access Journals (Sweden)
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 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 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.
Hastatic order in the two-channel Kondo-Heisenberg model
Zhang, Guanghua; Flint, Rebecca
Understanding Kondo physics in materials with non-Kramers doublets requires understanding the two channel Kondo effect, as valence fluctuations are from a non-Kramers doublet ground state to an excited Kramers doublet. Here, the development of a heavy Fermi liquid requires a channel symmetry breaking hybridization. This order, which breaks both single and double time-reversal symmetry was recently introduced as hastatic order. Here we employ an SU(N) fermionic mean-field treatment of the two-channel Kondo-Heisenberg model on a square lattice to explore properties of hastatic order and particularly the competition between the hastatic order and magnetism, as embodied by a spin liquid phase in our model. For simplicity, only a momentum independent hybrization between the non-Kramers f2 states and conduction electrons is considered. Upon varying the RKKY coupling and conduction electron density, we find both uniform and staggered [ Q = (π , π) ] hastatic order, in addition to the spin liquid phase, with metal-insulator transitions, including Lifshitz transitions inside the staggered phase. As the band degeneracy of the conduction electron bands is broken, the uniform hastatic order is partially suppressed compared to the staggered phase.
Comparisons of model simulations of climate variability with data, Task 2. [Progress report
Energy Technology Data Exchange (ETDEWEB)
1990-12-31
Significant progress has been made in our investigations aimed at diagnosing low frequency variations of climate in General Circulation Models. We have analyzed three versions of the Oregon State University General Circulation Model (OSU GCM). These are: (1) the Slab Model in which the ocean is treated as a static heat reservoir of fixed depth, (2) the coupled upper ocean-atmosphere model in which the ocean dynamics are calculated in two layers of variable depths representing the mixed layers and the thermocline; this model is referred to OSU2 in the following discussion, and (3) the coupled full ocean-atmosphere model in which the ocean is represented by six layers of variable depth; this model is referred to as OSU6 GCM in the discussion.
Directory of Open Access Journals (Sweden)
Francesca Colciaghi
Full Text Available Whether severe epilepsy could be a progressive disorder remains as yet unresolved. We previously demonstrated in a rat model of acquired focal cortical dysplasia, the methylazoxymethanol/pilocarpine - MAM/pilocarpine - rats, that the occurrence of status epilepticus (SE and subsequent seizures fostered a pathologic process capable of modifying the morphology of cortical pyramidal neurons and NMDA receptor expression/localization. We have here extended our analysis by evaluating neocortical and hippocampal changes in MAM/pilocarpine rats at different epilepsy stages, from few days after onset up to six months of chronic epilepsy. Our findings indicate that the process triggered by SE and subsequent seizures in the malformed brain i is steadily progressive, deeply altering neocortical and hippocampal morphology, with atrophy of neocortex and CA regions and progressive increase of granule cell layer dispersion; ii changes dramatically the fine morphology of neurons in neocortex and hippocampus, by increasing cell size and decreasing both dendrite arborization and spine density; iii induces reorganization of glutamatergic and GABAergic networks in both neocortex and hippocampus, favoring excitatory vs inhibitory input; iv activates NMDA regulatory subunits. Taken together, our data indicate that, at least in experimental models of brain malformations, severe seizure activity, i.e., SE plus recurrent seizures, may lead to a widespread, steadily progressive architectural, neuronal and synaptic reorganization in the brain. They also suggest the mechanistic relevance of glutamate/NMDA hyper-activation in the seizure-related brain pathologic plasticity.
Colciaghi, Francesca; Finardi, Adele; Nobili, Paola; Locatelli, Denise; Spigolon, Giada; Battaglia, Giorgio Stefano
2014-01-01
Whether severe epilepsy could be a progressive disorder remains as yet unresolved. We previously demonstrated in a rat model of acquired focal cortical dysplasia, the methylazoxymethanol/pilocarpine - MAM/pilocarpine - rats, that the occurrence of status epilepticus (SE) and subsequent seizures fostered a pathologic process capable of modifying the morphology of cortical pyramidal neurons and NMDA receptor expression/localization. We have here extended our analysis by evaluating neocortical and hippocampal changes in MAM/pilocarpine rats at different epilepsy stages, from few days after onset up to six months of chronic epilepsy. Our findings indicate that the process triggered by SE and subsequent seizures in the malformed brain i) is steadily progressive, deeply altering neocortical and hippocampal morphology, with atrophy of neocortex and CA regions and progressive increase of granule cell layer dispersion; ii) changes dramatically the fine morphology of neurons in neocortex and hippocampus, by increasing cell size and decreasing both dendrite arborization and spine density; iii) induces reorganization of glutamatergic and GABAergic networks in both neocortex and hippocampus, favoring excitatory vs inhibitory input; iv) activates NMDA regulatory subunits. Taken together, our data indicate that, at least in experimental models of brain malformations, severe seizure activity, i.e., SE plus recurrent seizures, may lead to a widespread, steadily progressive architectural, neuronal and synaptic reorganization in the brain. They also suggest the mechanistic relevance of glutamate/NMDA hyper-activation in the seizure-related brain pathologic plasticity.
Directory of Open Access Journals (Sweden)
Hosseini F.
2017-09-01
Full Text Available Background: Angiogenesis initiated by cancerous cells is the process by which new blood vessels are formed to enhance oxygenation and growth of tumor. Objective: In this paper, we present a new multiscale mathematical model for the formation of a vascular network in tumor angiogenesis process. Methods: Our model couples an improved sprout spacing model as a stochastic mathematical model of sprouting along an existing parent blood vessel, with a mathematical model of sprout progression in the extracellular matrix (ECM in response to some tumor angiogenic factors (TAFs. We perform simulations of the siting of capillary sprouts on an existing blood vessel using finite difference approximation of the dynamic equations of some angiogenesis activators and inhibitors. Angiogenesis activators are chemicals secreted by hypoxic tumor cells for initiating angiogenesis, and inhibitors of the angiogenesis are chemicals that are produced around every new sprout during tumor angiogenesis to inhibit the formation of further sprouts as a feedback of sprouting in angiogenesis. Moreover, for modelling sprout progression in ECM, we use three equations for the motility of endothelial cells at the tip of the activated sprouts, the consumption of TAF and the production and uptake of Fibronectin by endothelial cells. Results: Coupling these two basic models not only does provide a better time estimation of angiogenesis process, but also it is more compatible with reality. Conclusion: This model can be used to provide basic information for angiogenesis in the related studies. Related simulations can estimate the position and number of sprouts along parent blood vessel during the initial steps of angiogenesis and models the process of sprout progression in ECM until they vascularize a tumor.
Manzanares, Miguel Á; Campbell, Deanna J W; Maldonado, Gabrielle T; Sirica, Alphonse E
2018-02-01
Periostin and mesothelin have each been suggested to be predictors of poor survival for patients with intrahepatic cholangiocarcinoma, although the clinical prognostic value of both of these biomarkers remains uncertain. The aim of the current study was to investigate these biomarkers for their potential to act as tumor progression factors when assessed in orthotopic tumor and three-dimensional culture models of rat cholangiocarcinoma progression. Using our orthotopic model, we demonstrated a strong positive correlation between tumor and serum periostin and mesothelin and increasing liver tumor mass and associated peritoneal metastases that also reflected differences in cholangiocarcinoma cell aggressiveness and malignant grade. Periostin immunostaining was most prominent in the desmoplastic stroma of larger sized more aggressive liver tumors and peritoneal metastases. In comparison, mesothelin was more highly expressed in the cholangiocarcinoma cells; the slower growing more highly differentiated liver tumors exhibited a luminal cancer cell surface immunostaining for this biomarker, and the rapidly growing less differentiated liver and metastatic tumor masses largely showed cytoplasmic mesothelin immunoreactivity. Two molecular weight forms of mesothelin were identified, one at ∼40 kDa and the other, a more heavily glycosylated form, at ∼50 kDa. Increased expression of the 40-kDa mesothelin over that of the 50 kDa form predicted increased malignant progression in both the orthotopic liver tumors and in cholangiocarcinoma cells of different malignant potential in three-dimensional culture. Moreover, coculturing of cancer-associated myofibroblasts with cholangiocarcinoma cells promoted overexpression of the 40-kDa mesothelin, which correlated with enhanced malignant progression in vitro . Conclusion : Periostin and mesothelin are useful predictors of tumor progression in our rat desmoplastic cholangiocarcinoma models. This supports their relevance to human
2015-03-16
with logical rules to simulate an archetype biochemical network, the human coagulation cascade. The model consisted of five differential equations...coagulation system. Coagulation is an archetype proteolytic cascade involving both positive and negative feedback [10–12]. Coagulation is mediated by a...purely ODE models in the literature . We estimated the model parameters from in vitro extrinsic coagulation data sets, in the presence of ATIII, with and
Liu, Qun; Jiang, Daqing; Hayat, Tasawar; Ahmad, Bashir
2017-09-01
In this paper, we investigate two stochastic SIR epidemic models with higher order perturbation. For the nonautonomous periodic case of the model, by using Has'minskii's theory of periodic solution, we show that the system has at least one nontrivial positive T-periodic solution. For the system disturbed by both the white noise and telephone noise, we establish sufficient conditions for positive recurrence and the existence of ergodic stationary distribution of the positive solution.
Response errors explain the failure of independent-channels models of perception of temporal order
Directory of Open Access Journals (Sweden)
Miguel A García-Pérez
2012-04-01
Full Text Available Independent-channels models of perception of temporal order (also referred to as threshold models or perceptual latency models have been ruled out because two formal properties of these models (monotonicity and parallelism are not borne out by data from ternary tasks in which observers must judge whether stimulus A was presented before, after, or simultaneously with stimulus B. These models generally assume that observed responses are authentic indicators of unobservable judgments, but blinks, lapses of attention, or errors in pressing the response keys (maybe, but not only, motivated by time pressure when reaction times are being recorded may make observers misreport their judgments or simply guess a response. We present an extension of independent-channels models that considers response errors and we show that the model produces psychometric functions that do not satisfy monotonicity and parallelism. The model is illustrated by fitting it to data from a published study in which the ternary task was used. The fitted functions describe very accurately the absence of monotonicity and parallelism shown by the data. These characteristics of empirical data are thus consistent with independent-channels models when response errors are taken into consideration. The implications of these results for the analysis and interpretation of temporal-order judgment data are discussed.
Response errors explain the failure of independent-channels models of perception of temporal order.
García-Pérez, Miguel A; Alcalá-Quintana, Rocío
2012-01-01
Independent-channels models of perception of temporal order (also referred to as threshold models or perceptual latency models) have been ruled out because two formal properties of these models (monotonicity and parallelism) are not borne out by data from ternary tasks in which observers must judge whether stimulus A was presented before, after, or simultaneously with stimulus B. These models generally assume that observed responses are authentic indicators of unobservable judgments, but blinks, lapses of attention, or errors in pressing the response keys (maybe, but not only, motivated by time pressure when reaction times are being recorded) may make observers misreport their judgments or simply guess a response. We present an extension of independent-channels models that considers response errors and we show that the model produces psychometric functions that do not satisfy monotonicity and parallelism. The model is illustrated by fitting it to data from a published study in which the ternary task was used. The fitted functions describe very accurately the absence of monotonicity and parallelism shown by the data. These characteristics of empirical data are thus consistent with independent-channels models when response errors are taken into consideration. The implications of these results for the analysis and interpretation of temporal order judgment data are discussed.
Linear stability analysis of first-order delayed car-following models on a ring
Lassarre, Sylvain; Roussignol, Michel; Tordeux, Antoine
2012-09-01
The evolution of a line of vehicles on a ring is modeled by means of first-order car-following models. Three generic models describe the speed of a vehicle as a function of the spacing ahead and the speed of the predecessor. The first model is a basic one with no delay. The second is a delayed car-following model with a strictly positive parameter for the driver and vehicle reaction time. The last model includes a reaction time parameter with an anticipation process by which the delayed position of the predecessor is estimated. Explicit conditions for the linear stability of homogeneous configurations are calculated for each model. Two methods of calculus are compared: an exact one via Hopf bifurcations and an approximation by second-order models. The conditions describe stable areas for the parameters of the models that we interpret. The results notably show that the impact of the reaction time on the stability can be palliated by the anticipation process.
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).
Spin model for nontrivial types of magnetic order in inverse-perovskite antiferromagnets
Mochizuki, Masahito; Kobayashi, Masaya; Okabe, Reoya; Yamamoto, Daisuke
2018-02-01
Nontrivial magnetic orders in the inverse-perovskite manganese nitrides are theoretically studied by constructing a classical spin model describing the magnetic anisotropy and frustrated exchange interactions inherent in specific crystal and electronic structures of these materials. With a replica-exchange Monte Carlo technique, a theoretical analysis of this model reproduces the experimentally observed triangular Γ5 g and Γ4 g spin-ordered patterns and the systematic evolution of magnetic orders. Our Rapid Communication solves a 40-year-old problem of nontrivial magnetism for the inverse-perovskite manganese nitrides and provides a firm basis for clarifying the magnetism-driven negative thermal expansion phenomenon discovered in this class of materials.
Ordering in the quenched two-dimensional axial next-nearest-neighbor Ising model
International Nuclear Information System (INIS)
Hassold, G.N.; Srolovitz, D.J.
1988-01-01
Monte Carlo simulations of ordering in the two-dimensional axial next-nearest-neighbor Ising model following a quench were performed using nonconserved dynamics for a wide range of frustration parameters, κ, and temperatures. It was found that in quenches from T>>T/sub c/ to T 1 2 kinetics. Similar results are found for quenches at κ≥1, where the ordered structure is striped. However, for 0 phase (i.e., striped phase). Quenches to higher temperatures show the presence of a finite glass-transition temperature. Discontinuous changes in the value of the frustration parameter from the ferromagnetic to the -phase region of the phase diagram at low temperature yields a phase change which occurs via classical nucleation and growth. A simple energetic or growth model is proposed which accounts for all of the temperatures at which the ordering kinetics undergoes transitions
Vascular stents: Coupling full 3-D with reduced-order structural models
International Nuclear Information System (INIS)
Avdeev, I; Shams, M
2010-01-01
Self-expanding nitinol stents are used to treat peripheral arterial disease. The peripheral arteries are subjected to a combination of mechanical forces such as compression, torsion, bending, and contraction. Most commercially available peripheral self-expanding stents are composed of a series of sub-millimeter V-shaped struts, which are laser-cut from a nitinol tube and surface-treated for better fatigue performance. The numerical stent models must accurately predict location and distribution of local stresses and strains caused by large arterial deformations. Full 3-D finite element non-linear analysis of an entire stent is computationally expensive to the point of being prohibitive, especially for longer stents. Reduced-order models based on beam or shell elements are fairly accurate in capturing global deformations, but are not very helpful in predicting stent failure. We propose a mixed approach that combines the full 3-D model and reduced-order models. Several global-local, full 3-D/reduced-order finite element models of a peripheral self-expanding stent were validated and compared with experimental data. The kinematic constraint method used to couple various elements together was found to be very efficient and easily applicable to commercial FEA codes. The proposed mixed models can be used to accurately predict stent failure based on realistic (patient-specific), non-linear kinematic behavior of peripheral arteries.
Vascular stents: Coupling full 3-D with reduced-order structural models
Avdeev, I.; Shams, M.
2010-06-01
Self-expanding nitinol stents are used to treat peripheral arterial disease. The peripheral arteries are subjected to a combination of mechanical forces such as compression, torsion, bending, and contraction. Most commercially available peripheral self-expanding stents are composed of a series of sub-millimeter V-shaped struts, which are laser-cut from a nitinol tube and surface-treated for better fatigue performance. The numerical stent models must accurately predict location and distribution of local stresses and strains caused by large arterial deformations. Full 3-D finite element non-linear analysis of an entire stent is computationally expensive to the point of being prohibitive, especially for longer stents. Reduced-order models based on beam or shell elements are fairly accurate in capturing global deformations, but are not very helpful in predicting stent failure. We propose a mixed approach that combines the full 3-D model and reduced-order models. Several global-local, full 3-D/reduced-order finite element models of a peripheral self-expanding stent were validated and compared with experimental data. The kinematic constraint method used to couple various elements together was found to be very efficient and easily applicable to commercial FEA codes. The proposed mixed models can be used to accurately predict stent failure based on realistic (patient-specific), non-linear kinematic behavior of peripheral arteries.
Using Count Data and Ordered Models in National Forest Recreation Demand Analysis
Simões, Paula; Barata, Eduardo; Cruz, Luis
2013-11-01
This research addresses the need to improve our knowledge on the demand for national forests for recreation and offers an in-depth data analysis supported by the complementary use of count data and ordered models. From a policy-making perspective, while count data models enable the estimation of monetary welfare measures, ordered models allow for the wider use of the database and provide a more flexible analysis of data. The main purpose of this article is to analyse the individual forest recreation demand and to derive a measure of its current use value. To allow a more complete analysis of the forest recreation demand structure the econometric approach supplements the use of count data models with ordered category models using data obtained by means of an on-site survey in the Bussaco National Forest (Portugal). Overall, both models reveal that travel cost and substitute prices are important explanatory variables, visits are a normal good and demographic variables seem to have no influence on demand. In particular, estimated price and income elasticities of demand are quite low. Accordingly, it is possible to argue that travel cost (price) in isolation may be expected to have a low impact on visitation levels.
Trimming a hazard logic tree with a new model-order-reduction technique
Porter, Keith; Field, Edward; Milner, Kevin R
2017-01-01
The size of the logic tree within the Uniform California Earthquake Rupture Forecast Version 3, Time-Dependent (UCERF3-TD) model can challenge risk analyses of large portfolios. An insurer or catastrophe risk modeler concerned with losses to a California portfolio might have to evaluate a portfolio 57,600 times to estimate risk in light of the hazard possibility space. Which branches of the logic tree matter most, and which can one ignore? We employed two model-order-reduction techniques to simplify the model. We sought a subset of parameters that must vary, and the specific fixed values for the remaining parameters, to produce approximately the same loss distribution as the original model. The techniques are (1) a tornado-diagram approach we employed previously for UCERF2, and (2) an apparently novel probabilistic sensitivity approach that seems better suited to functions of nominal random variables. The new approach produces a reduced-order model with only 60 of the original 57,600 leaves. One can use the results to reduce computational effort in loss analyses by orders of magnitude.
Is organizational progress in the EFQM model related to employee satisfaction?
Matthies-Baraibar, Carmen; Arcelay-Salazar, Andoni; Cantero-González, David; Colina-Alonso, Alberto; García-Urbaneja, Marbella; González-Llinares, Rosa María; Letona-Aranburu, Jon; Martínez-Carazo, Catalina; Mateos-Del Pino, Maider; Nuño-Solinís, Roberto; Olaetxea-Urizar, Esther; de la Rica-Giménez, José Antonio; Rodríguez-González, María Angeles; Dabouza-Acebal, Silvia
2014-10-24
To determine whether there is greater employee satisfaction in organisations that have made more progress in implementation of the European Foundation for Quality Management (EFQM) model. A series of cross-sectional studies (one for each assessment cycle) comparing staff satisfaction survey results between groups of healthcare organisations by degree of implementation of the EFQM model (assessed in terms of external recognition of management quality in each organisation). 30 healthcare organisations including hospitals, primary care and mental health providers in Osakidetza, the Basque public health service. Employees of 30 Osakidetza organisations. Progress in implementation of EFQM model. Scores in 9 dimensions of employee satisfaction from questionnaires administered in healthcare organisations in 4 assessment cycles between 2001 and 2010. Comparing satisfaction results in organisations granted Gold or Silver Q Awards and those without this type of external recognition, we found statistically significant differences in the dimensions of training and internal communication. Then, comparing recipients of Gold Q Awards with those with no Q Certification, differences in leadership style and in policy and strategy also emerged as significant. Progress of healthcare organisations in the implementation of the EFQM Excellence Model is associated with increases in their employee satisfaction in dimensions that can be managed at the level of each organisation, while dimensions in which no statistically significant differences were found represent common organisational elements with little scope for self-management.
Vague Sets Security Measure for Steganographic System Based on High-Order Markov Model
Directory of Open Access Journals (Sweden)
Chun-Juan Ouyang
2017-01-01
Full Text Available Security measure is of great importance in both steganography and steganalysis. Considering that statistical feature perturbations caused by steganography in an image are always nondeterministic and that an image is considered nonstationary, in this paper, the steganography is regarded as a fuzzy process. Here a steganographic security measure is proposed. This security measure evaluates the similarity between two vague sets of cover images and stego images in terms of n-order Markov chain to capture the interpixel correlation. The new security measure has proven to have the properties of boundedness, commutativity, and unity. Furthermore, the security measures of zero order, first order, second order, third order, and so forth are obtained by adjusting the order value of n-order Markov chain. Experimental results indicate that the larger n is, the better the measuring ability of the proposed security measure will be. The proposed security measure is more sensitive than other security measures defined under a deterministic distribution model, when the embedding is low. It is expected to provide a helpful guidance for designing secure steganographic algorithms or reliable steganalytic methods.
Interacting gaps model, dynamics of order book, and stock-market fluctuations
Czech Academy of Sciences Publication Activity Database
Svorenčík, A.; Slanina, František
2007-01-01
Roč. 57, - (2007), s. 453-462 ISSN 1434-6028 R&D Projects: GA MŠk 1P04OCP10.001 Institutional research plan: CEZ:AV0Z10100520 Keywords : interacting gaps model * dynamics of order book * stock - market fluctuations Subject RIV: BE - Theoretical Physics Impact factor: 1.356, year: 2007
Compound waves in a higher order nonlinear model of thermoviscous fluids
DEFF Research Database (Denmark)
Rønne Rasmussen, Anders; Sørensen, Mads Peter; Gaididei, Yuri B.
2016-01-01
A generalized traveling wave ansatz is used to investigate compound shock waves in a higher order nonlinear model of a thermoviscous fluid. The fluid velocity potential is written as a traveling wave plus a linear function of space and time. The latter offers the possibility of predicting...
Algebraic Specifications, Higher-order Types and Set-theoretic Models
DEFF Research Database (Denmark)
Kirchner, Hélène; Mosses, Peter David
2001-01-01
, and power-sets. This paper presents a simple framework for algebraic specifications with higher-order types and set-theoretic models. It may be regarded as the basis for a Horn-clause approximation to the Z framework, and has the advantage of being amenable to prototyping and automated reasoning. Standard...
Effect of random field disorder on the first order transition in p-spin interaction model
Sumedha; Singh, Sushant K.
2016-01-01
We study the random field p-spin model with Ising spins on a fully connected graph using the theory of large deviations in this paper. This is a good model to study the effect of quenched random field on systems which have a sharp first order transition in the pure state. For p = 2, the phase-diagram of the model, for bimodal distribution of the random field, has been well studied and is known to undergo a continuous transition for lower values of the random field (h) and a first order transition beyond a threshold, htp(≈ 0.439) . We find the phase diagram of the model, for all p ≥ 2, with bimodal random field distribution, using large deviation techniques. We also look at the fluctuations in the system by calculating the magnetic susceptibility. For p = 2, beyond the tricritical point in the regime of first order transition, we find that for htp ho = 1 / p!), the system does not show ferromagnetic order even at zero temperature. We find that the magnetic susceptibility for p ≥ 3 is discontinuous at the transition point for h
Probabilistic modelling of combined sewer overflow using the First Order Reliability Method
DEFF Research Database (Denmark)
Thorndahl, Søren; Schaarup-Jensen, Kjeld; Jensen, Jacob Birk
2007-01-01
uncertainties on an application of the commercial urban drainage model MOUSE combined with the probabilistic First Order Reliability Method (FORM). Applying statistical characteristics on several years of rainfall, it is possible to derive a parameterization of the rainfall input and the failure probability...
Numerical computation of the optimal control model of higher-order ...
African Journals Online (AJOL)
The paper implemented the optimal control problem of higher-order nondispersive wave. The Extended Conjugate Gradient Method [1], was used to compute the optimal values of the control and state variables of the model while the analytical expressions of the state and control variables generated the analytical values.
Saragih, Sahat; Napitupulu, E. Elvis; Fauzi, Amin
2017-01-01
This research aims to develop a student-centered learning model based on local culture and instrument of mathematical higher order thinking of junior high school students in the frame of the 2013-Curriculum in North Sumatra, Indonesia. The subjects of the research are seventh graders which are taken proportionally random consisted of three public…
CSIR Research Space (South Africa)
Bogaers, Alfred EJ
2010-01-01
Full Text Available In this paper, we implement the method of Proper Orthogonal Decomposition (POD) to generate a reduced order model (ROM) of an optimization based mesh movement technique. In the study it is shown that POD can be used effectively to generate a ROM...
Reduction of static field equation of Faddeev model to first order PDE
International Nuclear Information System (INIS)
Hirayama, Minoru; Shi Changguang
2007-01-01
A method to solve the static field equation of the Faddeev model is presented. For a special combination of the concerned field, we adopt a form which is compatible with the field equation and involves two arbitrary complex functions. As a result, the static field equation is reduced to a set of first order partial differential equations
Weak first-order orientational transition in the Lebwohl-Lasher model for liquid crystals
DEFF Research Database (Denmark)
Zhang, Zhengping; Mouritsen, Ole G.; Zuckermann, Martin J.
1992-01-01
The nature of the orientational phase transition in the three-dimensional Lebwohl-Lasher model of liquid crystals has been studied by computer simulation using reweighting techniques and finite-size scaling analysis. Unambiguous numerical evidence is found in favor of a weak first-order transition...
Developing Student-Centered Learning Model to Improve High Order Mathematical Thinking Ability
Saragih, Sahat; Napitupulu, Elvis
2015-01-01
The purpose of this research was to develop student-centered learning model aiming to improve high order mathematical thinking ability of junior high school students of based on curriculum 2013 in North Sumatera, Indonesia. The special purpose of this research was to analyze and to formulate the purpose of mathematics lesson in high order…
Advancing investigation and physical modeling of first-order fire effects on soils
William J. Massman; John M. Frank; Sacha J. Mooney
2010-01-01
Heating soil during intense wildland fires or slash-pile burns can alter the soil irreversibly, resulting in many significant long-term biological, chemical, physical, and hydrological effects. To better understand these long-term effects, it is necessary to improve modeling capability and prediction of the more immediate, or first-order, effects that fire can have on...
Brady, Timothy F.; Tenenbaum, Joshua B.
2013-01-01
When remembering a real-world scene, people encode both detailed information about specific objects and higher order information like the overall gist of the scene. However, formal models of change detection, like those used to estimate visual working memory capacity, assume observers encode only a simple memory representation that includes no…
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
International Nuclear Information System (INIS)
Mandelli, Diego; Smith, Curtis L.; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua J.; Talbot, Paul W.; Rinaldi, Ivan; Maljovec, Dan; Wang, Bei; Pascucci, Valerio; Zhao, Haihua
2015-01-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.
Lattice Boltzmann model for high-order nonlinear partial differential equations
Chai, Zhenhua; He, Nanzhong; Guo, Zhaoli; Shi, Baochang
2018-01-01
In this paper, a general lattice Boltzmann (LB) model is proposed for the high-order nonlinear partial differential equation with the form ∂tϕ +∑k=1mαk∂xkΠk(ϕ ) =0 (1 ≤k ≤m ≤6 ), αk are constant coefficients, Πk(ϕ ) are some known differential functions of ϕ . As some special cases of the high-order nonlinear partial differential equation, the classical (m)KdV equation, KdV-Burgers equation, K (n ,n ) -Burgers equation, Kuramoto-Sivashinsky equation, and Kawahara equation can be solved by the present LB model. Compared to the available LB models, the most distinct characteristic of the present model is to introduce some suitable auxiliary moments such that the correct moments of equilibrium distribution function can be achieved. In addition, we also conducted a detailed Chapman-Enskog analysis, and found that the high-order nonlinear partial differential equation can be correctly recovered from the proposed LB model. Finally, a large number of simulations are performed, and it is found that the numerical results agree with the analytical solutions, and usually the present model is also more accurate than the existing LB models [H. Lai and C. Ma, Sci. China Ser. G 52, 1053 (2009), 10.1007/s11433-009-0149-3; H. Lai and C. Ma, Phys. A (Amsterdam) 388, 1405 (2009), 10.1016/j.physa.2009.01.005] for high-order nonlinear partial differential equations.
Reduced Order Model Implementation in the Risk-Informed Safety Margin Characterization Toolkit
Energy Technology Data Exchange (ETDEWEB)
Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Alfonsi, Andrea [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rabiti, Cristian [Idaho National Lab. (INL), Idaho Falls, ID (United States); Cogliati, Joshua J. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Talbot, Paul W. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rinaldi, Ivan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Maljovec, Dan [Idaho National Lab. (INL), Idaho Falls, ID (United States); Wang, Bei [Idaho National Lab. (INL), Idaho Falls, ID (United States); Pascucci, Valerio [Idaho National Lab. (INL), Idaho Falls, ID (United States); Zhao, Haihua [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2015-09-01
The RISMC project aims to develop new advanced simulation-based tools to perform Probabilistic Risk Analysis (PRA) for the existing fleet of U.S. nuclear power plants (NPPs). These tools numerically model not only the thermo-hydraulic behavior of the reactor primary and secondary systems but also external events temporal evolution and components/system ageing. Thus, this is not only a multi-physics problem but also a multi-scale problem (both spatial, µm-mm-m, and temporal, ms-s-minutes-years). As part of the RISMC PRA approach, a large amount of computationally expensive simulation runs are required. An important aspect is that even though computational power is regularly growing, the overall computational cost of a RISMC analysis may be not viable for certain cases. A solution that is being evaluated is the use of reduce order modeling techniques. During the FY2015, we investigated and applied reduced order modeling techniques to decrease the RICM analysis computational cost by decreasing the number of simulations runs to perform and employ surrogate models instead of the actual simulation codes. This report focuses on the use of reduced order modeling techniques that can be applied to any RISMC analysis to generate, analyze and visualize data. In particular, we focus on surrogate models that approximate the simulation results but in a much faster time (µs instead of hours/days). We apply reduced order and surrogate modeling techniques to several RISMC types of analyses using RAVEN and RELAP-7 and show the advantages that can be gained.
Quo natas, Danio?—Recent Progress in Modeling Cancer in Zebrafish
Directory of Open Access Journals (Sweden)
Stefanie Kirchberger
2017-08-01
Full Text Available Over the last decade, zebrafish has proven to be a powerful model in cancer research. Zebrafish form tumors that histologically and genetically resemble human cancers. The live imaging and cost-effective compound screening possible with zebrafish especially complement classic mouse cancer models. Here, we report recent progress in the field, including genetically engineered zebrafish cancer models, xenotransplantation of human cancer cells into zebrafish, promising approaches toward live investigation of the tumor microenvironment, and identification of therapeutic strategies by performing compound screens on zebrafish cancer models. Given the recent advances in genome editing, personalized zebrafish cancer models are now a realistic possibility. In addition, ongoing automation will soon allow high-throughput compound screening using zebrafish cancer models to be part of preclinical precision medicine approaches.
[RESEARCH PROGRESS OF EXPERIMENTAL ANIMAL MODELS OF AVASCULAR NECROSIS OF FEMORAL HEAD].
Yu, Kaifu; Tan, Hongbo; Xu, Yongqing
2015-12-01
To summarize the current researches and progress on experimental animal models of avascular necrosis of the femoral head. Domestic and internation literature concerning experimental animal models of avascular necrosis of the femoral head was reviewed and analyzed. The methods to prepare the experimental animal models of avascular necrosis of the femoral head can be mainly concluded as traumatic methods (including surgical, physical, and chemical insult), and non-traumatic methods (including steroid, lipopolysaccharide, steroid combined with lipopolysaccharide, steroid combined with horse serum, etc). Each method has both merits and demerits, yet no ideal methods have been developed. There are many methods to prepare the experimental animal models of avascular necrosis of the femoral head, but proper model should be selected based on the aim of research. The establishment of ideal experimental animal models needs further research in future.
Energy Technology Data Exchange (ETDEWEB)
Bernard, Véronique [Groupe de Physique Théorique, Institut de Physique Nucléaire, UMR 8608, CNRS,University Paris-Sud, Université Paris-Saclay, 91406 Orsay Cedex (France); Descotes-Genon, Sébastien [Laboratoire de Physique Théorique, UMR 8627, CNRS, University Paris-Sud, Université Paris-Saclay,91405 Orsay Cedex (France); Silva, Luiz Vale [Groupe de Physique Théorique, Institut de Physique Nucléaire, UMR 8608, CNRS,University Paris-Sud, Université Paris-Saclay, 91406 Orsay Cedex (France); Laboratoire de Physique Théorique, UMR 8627, CNRS, University Paris-Sud, Université Paris-Saclay,91405 Orsay Cedex (France)
2016-08-23
Left-Right (LR) models are extensions of the Standard Model where left-right symmetry is restored at high energies, and which are strongly constrained by kaon mixing described in the framework of the |ΔS|=2 effective Hamiltonian. We consider the short-distance QCD corrections to this Hamiltonian both in the Standard Model (SM) and in LR models. The leading logarithms occurring in these short-distance corrections can be resummed within a rigourous Effective Field Theory (EFT) approach integrating out heavy degrees of freedom progressively, or using an approximate simpler method of regions identifying the ranges of loop momentum generating large logarithms in the relevant two-loop diagrams. We compare the two approaches in the SM at next-to-leading order, finding a very good agreement when one scale dominates the problem, but only a fair agreement in the presence of a large logarithm at leading order. We compute the short-distance QCD corrections for LR models at next-to-leading order using the method of regions, and we compare the results with the EFT approach for the WW{sup ′} box with two charm quarks (together with additional diagrams forming a gauge-invariant combination), where a large logarithm occurs already at leading order. We conclude by providing next-to-leading-order estimates for cc, ct and tt boxes in LR models.
Rijmen, Frank; Jeon, Minjeong; von Davier, Matthias; Rabe-Hesketh, Sophia
2014-01-01
Second-order item response theory models have been used for assessments consisting of several domains, such as content areas. We extend the second-order model to a third-order model for assessments that include subdomains nested in domains. Using a graphical model framework, it is shown how the model does not suffer from the curse of…
Directory of Open Access Journals (Sweden)
Herzog Sereina A
2012-08-01
Full Text Available Abstract Background Pelvic inflammatory disease (PID results from the ascending spread of microorganisms from the vagina and endocervix to the upper genital tract. PID can lead to infertility, ectopic pregnancy and chronic pelvic pain. The timing of development of PID after the sexually transmitted bacterial infection Chlamydia trachomatis (chlamydia might affect the impact of screening interventions, but is currently unknown. This study investigates three hypothetical processes for the timing of progression: at the start, at the end, or throughout the duration of chlamydia infection. Methods We develop a compartmental model that describes the trial structure of a published randomised controlled trial (RCT and allows each of the three processes to be examined using the same model structure. The RCT estimated the effect of a single chlamydia screening test on the cumulative incidence of PID up to one year later. The fraction of chlamydia infected women who progress to PID is obtained for each hypothetical process by the maximum likelihood method using the results of the RCT. Results The predicted cumulative incidence of PID cases from all causes after one year depends on the fraction of chlamydia infected women that progresses to PID and on the type of progression. Progression at a constant rate from a chlamydia infection to PID or at the end of the infection was compatible with the findings of the RCT. The corresponding estimated fraction of chlamydia infected women that develops PID is 10% (95% confidence interval 7-13% in both processes. Conclusions The findings of this study suggest that clinical PID can occur throughout the course of a chlamydia infection, which will leave a window of opportunity for screening to prevent PID.
Guerrini, Luca; Sodini, Mauro
2014-01-01
We introduce a time-to-build technology in a Solow model with bounded technological progress. Our analysis shows that the system may be asymptotically stable, or it can produce stability switches and Hopf bifurcations when time delay varies. The direction and the stability criteria of the bifurcating periodic solutions are obtained by the normal form theory and the center manifold theorem. Numerical simulations confirms the theoretical results.
International Nuclear Information System (INIS)
Blin, J.; Baron, J.C.; Cambon, H.
1988-01-01
In 41 patients with clinically determined Progressive Supranuclear Palsy, a model of degenerative subcortical dementia, alterations in regional brain energy metabolism with respect to control subjects have been investigated using positron computed tomography and correlated to clinical and neuropsychological scores. A generalized significant reduction in brain metabolism was found, which predominated in the prefrontal cortex in accordance with, and statistically correlated to, the frontal neuropsychological score
International Nuclear Information System (INIS)
Sutheerawatthana, Pitch; Minato, Takayuki
2010-01-01
The response of a social group is a missing element in the formal impact assessment model. Previous discussion of the involvement of social groups in an intervention has mainly focused on the formation of the intervention. This article discusses the involvement of social groups in a different way. A descriptive model is proposed by incorporating a social group's response into the concept of second- and higher-order effects. The model is developed based on a cause-effect relationship through the observation of phenomena in case studies. The model clarifies the process by which social groups interact with a lower-order effect and then generate a higher-order effect in an iterative manner. This study classifies social groups' responses into three forms-opposing, modifying, and advantage-taking action-and places them in six pathways. The model is expected to be used as an analytical tool for investigating and identifying impacts in the planning stage and as a framework for monitoring social groups' responses during the implementation stage of a policy, plan, program, or project (PPPPs).
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Naets, Frank
2018-01-01
performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during...... the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis......-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system....
Toward a scalable flexible-order model for 3D nonlinear water waves
DEFF Research Database (Denmark)
Engsig-Karup, Allan Peter; Ducrozet, Guillaume; Bingham, Harry B.
For marine and coastal applications, current work are directed toward the development of a scalable 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...... strategy on a time-invariant mesh. The 3D numerical model is based on a finite difference method as in the original works \\cite{LiFleming1997,BinghamZhang2007}. Full details and other aspects of an improved 3D solution can be found in \\cite{EBL08}. The new and improved approach for three...
Formulation and validation of high-order linearized models of helicopter flight mechanics
Kim, Frederick D.; Celi, Roberto; Tischler, Mark B.
1990-01-01
A high-order linearized model of helicopter flight dynamics is extracted from a nonlinear time domain simulation. The model has 29 states that describe the fuselage rigid body degrees of freedom, the flap and lag dynamics in a nonrotating coordinate system, the inflow dynamics, the delayed entry of the horizontal tail into the main rotor wake, and, approximately, the blade torsion dynamics. The nonlinear simulation is obtained by extensively modifying the GENHEL computer program. The results indicate that the agreement between the linearized and the nonlinear model is good for small perturbations, and deteriorates for large amplitude maneuvers.
Energy Technology Data Exchange (ETDEWEB)
Silveira, L.M.; Kamon, M.; Elfadel, I.; White, J. [Massachusetts Inst. of Technology, Cambridge, MA (United States)
1996-12-31
Model order reduction based on Krylov subspace iterative methods has recently emerged as a major tool for compressing the number of states in linear models used for simulating very large physical systems (VLSI circuits, electromagnetic interactions). There are currently two main methods for accomplishing such a compression: one is based on the nonsymmetric look-ahead Lanczos algorithm that gives a numerically stable procedure for finding Pade approximations, while the other is based on a less well characterized Arnoldi algorithm. In this paper, we show that for certain classes of generalized state-space systems, the reduced-order models produced by a coordinate-transformed Arnoldi algorithm inherit the stability of the original system. Complete Proofs of our results will be given in the final paper.
Geometrical aspects of operator ordering terms in gauge invariant quantum models
International Nuclear Information System (INIS)
Houston, P.J.
1990-01-01
Finite-dimensional quantum models with both boson and fermion degrees of freedom, and which have a gauge invariance, are studied here as simple versions of gauge invariant quantum field theories. The configuration space of these finite-dimensional models has the structure of a principal fibre bundle and has defined on it a metric which is invariant under the action of the bundle or gauge group. When the gauge-dependent degrees of freedom are removed, thereby defining the quantum models on the base of the principal fibre bundle, extra operator ordering terms arise. By making use of dimensional reduction methods in removing the gauge dependence, expressions are obtained here for the operator ordering terms which show clearly their dependence on the geometry of the principal fibre bundle structure. (author)
International Nuclear Information System (INIS)
Suarez Antola, R.
2009-01-01
In the framework of an analytic or numerical model of a BWR power plant, this could imply first to find an suitable approximation to the solution manifold of the differential equations describing the stability behaviour of this nonlinear system, and then a classification of the different solution types concerning their relation with the operational safety of the power plant, by distributing the different solution types in relation with the exclusion region of the power-flow map. Then the goal is to obtain the best attainable qualitative and quantitative global picture of plant dynamics. To do this, the construction and the analysis of the so called reduced order models (Rom) seems a necessary step. A reduced order model results after the full system of coupled nonlinear partial differential equations of the plant is reduced to a system of coupled nonlinear ordinary differential equations
Fourth-Order Method for Numerical Integration of Age- and Size-Structured Population Models
Energy Technology Data Exchange (ETDEWEB)
Iannelli, M; Kostova, T; Milner, F A
2008-01-08
In many applications of age- and size-structured population models, there is an interest in obtaining good approximations of total population numbers rather than of their densities. Therefore, it is reasonable in such cases to solve numerically not the PDE model equations themselves, but rather their integral equivalents. For this purpose quadrature formulae are used in place of the integrals. Because quadratures can be designed with any order of accuracy, one can obtain numerical approximations of the solutions with very fast convergence. In this article, we present a general framework and a specific example of a fourth-order method based on composite Newton-Cotes quadratures for a size-structured population model.
The Schwinger Dyson equations and the algebra of constraints of random tensor models at all orders
International Nuclear Information System (INIS)
Gurau, Razvan
2012-01-01
Random tensor models for a generic complex tensor generalize matrix models in arbitrary dimensions and yield a theory of random geometries. They support a 1/N expansion dominated by graphs of spherical topology. Their Schwinger Dyson equations, generalizing the loop equations of matrix models, translate into constraints satisfied by the partition function. The constraints have been shown, in the large N limit, to close a Lie algebra indexed by colored rooted D-ary trees yielding a first generalization of the Virasoro algebra in arbitrary dimensions. In this paper we complete the Schwinger Dyson equations and the associated algebra at all orders in 1/N. The full algebra of constraints is indexed by D-colored graphs, and the leading order D-ary tree algebra is a Lie subalgebra of the full constraints algebra.
Modal-based reduced-order model of BWR out-of phase instabilities
International Nuclear Information System (INIS)
Turso, J.A.; Edwards, R.M.; March-Leuba, J.
1995-01-01
For the past 40 yr, reduced-order modeling of boiling water reactor (BWR) dynamic behavior has been accomplished by several researchers. These models have been primarily concerned with providing insight into the so-called corewide neutron flux oscillation, where the power at each radial location in the core oscillates in unison. This is generally considered to be an illustration of the fundamental neutronic mode excited by the core thermal hydraulics. The time dependence of the fundamental mode is typically described by the point-kinetics equations, with one or more delayed-neutron groups. Thermal-hydraulic excitation of the first azimuthal harmonic mode, the so-called out-of-phase (OOP) instability, has been observed in operating BWRs. The temporal behavior of a low-order model of this phenomenon can be characterized using the modal point-kinetics formulation developed in this paper
MODELLING THE PROGRESSION OF COMPETITIVE PERFORMANCE OF AN ACADEMY'S SOCCER TEAMS
Directory of Open Access Journals (Sweden)
Rita M. Malcata
2012-09-01
Full Text Available Progression of a team's performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%. Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%. Aspire experienced a small home-ground advantage of 16% (-5 to 41%, whereas opposition teams experienced 31% (7 to 60% on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents' scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%, small over two years (15%, -8 to 44%, but unclear over >2 years. In conclusion, the generalized
Najhan Mohd Nagib, Ahmad; Naufal Adnan, Ahmad; Ismail, Azianti; Halim, Nurul Hayati Abdul; Syuhadah Khusaini, Nurul
2016-11-01
The inventory model had been utilized since the early 1900s. The implementation of the inventory management model is generally to ensure that an organisation is able to fulfil customer's demand at the lowest possible cost to improve profitability. This paper focuses on reviewing previous published papers regarding inventory control model mainly in the food and beverage processing industry. The author discusses four inventory models, which are the make-to-stock (MTS), make-to-order (MTO), economic order quantity (EOQ), and hybrid of MTS-MTO models. The issues raised by the researchers on the above techniques as well as the elements need to be considered upon selection have been discussed in this paper. The main objective of the study is to highlight the important role played by these inventory control models in the food and beverage processing industry.
Serial recall of colors: Two models of memory for serial order applied to continuous visual stimuli.
Peteranderl, Sonja; Oberauer, Klaus
2018-01-01
This study investigated the effects of serial position and temporal distinctiveness on serial recall of simple visual stimuli. Participants observed lists of five colors presented at varying, unpredictably ordered interitem intervals, and their task was to reproduce the colors in their order of presentation by selecting colors on a continuous-response scale. To control for the possibility of verbal labeling, articulatory suppression was required in one of two experimental sessions. The predictions were derived through simulation from two computational models of serial recall: SIMPLE represents the class of temporal-distinctiveness models, whereas SOB-CS represents event-based models. According to temporal-distinctiveness models, items that are temporally isolated within a list are recalled more accurately than items that are temporally crowded. In contrast, event-based models assume that the time intervals between items do not affect recall performance per se, although free time following an item can improve memory for that item because of extended time for the encoding. The experimental and the simulated data were fit to an interference measurement model to measure the tendency to confuse items with other items nearby on the list-the locality constraint-in people as well as in the models. The continuous-reproduction performance showed a pronounced primacy effect with no recency, as well as some evidence for transpositions obeying the locality constraint. Though not entirely conclusive, this evidence favors event-based models over a role for temporal distinctiveness. There was also a strong detrimental effect of articulatory suppression, suggesting that verbal codes can be used to support serial-order memory of simple visual stimuli.
Simulation of local instabilities with the use of reduced order models
International Nuclear Information System (INIS)
Dykin, V.; Demaziere, C.; Lange, C.; Hennig, D.
2011-01-01
The development of an advanced reduced order model (ROM) with four heated channels, taking into account local, regional and core-wide oscillations, is described. The ROM contains three sub-models: a neutron-kinetic model (describing neutron transport), a thermal- hydraulic model (describing the coolant flow) and a heat transfer model (describing heat transfer between the fuel and the coolant). All these three models are coupled to each other, using two feedback mechanisms: void feedback and doppler feedback. Each of the sub-models is described by a set of reduced ordinary differential equations, derived from the corresponding time space-dependent partial differential equations by using different types of approximations and mathematical techniques. All three models were developed from past ROMs and, subsequently, were modified in order to fit the purpose of our investigations. One of the novelties of the present ROM is that it takes into account the effect of the first three neutronic modes, namely the fundamental, the first and the second azimuthal modes, as well as the effect of local oscillations on these modes. In order to have a proper representation of both azimuthal modes, a four heated channel ROM was developed. Another modification, compared to earlier work, is the determination of the coupling reactivity coefficients for both void fraction and fuel temperature, which were calculated explicitly by evaluating cross-section perturbations with the help of the SIMULATE-3 and the CORESIM codes. The ROM was thereafter applied to a channel instability event that occurred at the Swedish Forsmark-1 BWR in 1996/1997. The time signals for each of the modes were generated from the ROM and compared with the measurements, performed at the plant. Some qualitative comparison between the ROM and the measurements was made. The results could bear some significance in understanding the instability event and its coupling mechanism to core-wide oscillations. (author)
An Artificial Neural Network Model for the Wholesale Company Order's Cycle Management
Directory of Open Access Journals (Sweden)
Tereza Sustrova
2016-06-01
Full Text Available The purpose of this article is to verify the possibility of using artificial neural networks (ANN in business management processes, primarily in the area of supply chain management. The author has designed several neural network models featuring different architectures to optimize the level of the company’s inventory. The results of the research show that ANN can be used for managing a company’s order cycle and lead to reduced levels of goods purchased and storage costs. Optimal neural networks show suitable results for subsequent prediction of the amount of items to be ordered and for achieving reduced inventory purchase and keeping costs down.
DEFF Research Database (Denmark)
Tahavori, Maryamsadat; Shaker, Hamid Reza
gramians within the time interval to build the appropriate Petrov-Galerkin projection for dynamical systems within the time interval of interest. The bound on approximation error is also derived. The numerical results are compared with the counterparts from other techniques. The results confirm......A method for model reduction of dynamical systems with the second order structure is proposed in this paper. The proposed technique preserves the second order structure of the system, and also preserves the stability of the original systems. The method uses the controllability and observability...
Directory of Open Access Journals (Sweden)
Clara ePrats
2016-02-01
Full Text Available The evolution of a tuberculosis (TB infection towards active disease is driven by a combination of factors mostly related to the host response. The equilibrium between control of the bacillary load and the pathology generated is crucial as regards preventing the growth and proliferation of TB lesions. In addition, some experimental evidence suggests an important role of both local endogenous reinfection and the coalescence of neighboring lesions.Herein we propose a mathematical model that captures the essence of these factors by defining three hypotheses: (i lesions grow logistically due to the inflammatory reaction; (ii new lesions can appear as a result of extracellular bacilli or infected macrophages that escape from older lesions; and (iii lesions can merge when they are close enough. This model was implemented in Matlab to simulate the dynamics of several lesions in a 3D space. It was also fitted to available microscopy data from infected C3HeB/FeJ mice, an animal model of active TB that reacts against Mycobacterium tuberculosis with an exaggerated inflammatory response.The results of the simulations show the dynamics observed experimentally, namely an initial increase in the number of lesions followed by oscillations, and an exponential increase in the mean area of the lesions. In addition, further analysis of experimental and simulation results show a strong coincidence of the area distributions of lesions at day 21, thereby highlighting the consistency of the model. Three simulation series removing each one of the hypothesis corroborate their essential role in the dynamics observed.These results demonstrate that three local factors, namely an exaggerated inflammatory response, an endogenous reinfection and a coalescence of lesions, are needed in order to progress towards active TB. The failure of one of these factors stops induction of the disease. This mathematical model may be used as a basis for developing strategies to stop the
Lee, Lee-Min; Jean, Fu-Rong
2016-08-01
The hidden Markov models have been widely applied to systems with sequential data. However, the conditional independence of the state outputs will limit the output of a hidden Markov model to be a piecewise constant random sequence, which is not a good approximation for many real processes. In this paper, a high-order hidden Markov model for piecewise linear processes is proposed to better approximate the behavior of a real process. A parameter estimation method based on the expectation-maximization algorithm was derived for the proposed model. Experiments on speech recognition of noisy Mandarin digits were conducted to examine the effectiveness of the proposed method. Experimental results show that the proposed method can reduce the recognition error rate compared to a baseline hidden Markov model.
A mathematical model for order splitting in a multiple supplier single-item inventory system
DEFF Research Database (Denmark)
Abginehchi, Soheil; Farahani, Reza Zanjirani; Rezapour, Shabnam
2013-01-01
The policy of simultaneously splitting replenishment orders among several suppliers has received considerable attention in the last few years and continues to attract the attention of researchers. In this paper, we develop a mathematical model which considers multiple-supplier single-item inventory...... systems. The item acquisition lead times of suppliers are random variables. Backorder is allowed and shortage cost is charged based on not only per unit in shortage but also per time unit. Continuous review (s,Q) policy has been assumed. When the inventory level depletes to a reorder level, the total......, procurement cost, inventory holding cost, and shortage cost, is minimized. We also conduct extensive numerical experiments to show the advantages of our model compared with the models in the literature. According to our extensive experiments, the model developed in this paper is the best model...
Basic problems solving for two-dimensional discrete 3 × 4 order hidden markov model
International Nuclear Information System (INIS)
Wang, Guo-gang; Gan, Zong-liang; Tang, Gui-jin; Cui, Zi-guan; Zhu, Xiu-chang
2016-01-01
A novel model is proposed to overcome the shortages of the classical hypothesis of the two-dimensional discrete hidden Markov model. In the proposed model, the state transition probability depends on not only immediate horizontal and vertical states but also on immediate diagonal state, and the observation symbol probability depends on not only current state but also on immediate horizontal, vertical and diagonal states. This paper defines the structure of the model, and studies the three basic problems of the model, including probability calculation, path backtracking and parameters estimation. By exploiting the idea that the sequences of states on rows or columns of the model can be seen as states of a one-dimensional discrete 1 × 2 order hidden Markov model, several algorithms solving the three questions are theoretically derived. Simulation results further demonstrate the performance of the algorithms. Compared with the two-dimensional discrete hidden Markov model, there are more statistical characteristics in the structure of the proposed model, therefore the proposed model theoretically can more accurately describe some practical problems.
Cattaneo, Lauren Bennett; Grossmann, Jessica; Chapman, Aliya R
2016-10-01
Protection orders (POs) are a widely recommended and commonly used intervention for intimate partner violence (IPV), but evidence for their effectiveness is mixed. This mixed methods study used the framework of empowerment to explore the goals of petitioners who seek POs, and the extent to which one group of experts considers these goals to be a good fit with the court's intent. We collected data in three phases: (a) We conducted a qualitative study to generate a list of goals (n = 10); (b) we administered the list to a sample of IPV survivors (n = 157); and (c) we surveyed a group of attorneys (n = 10). Results showed that petitioners endorse many goals for seeking POs and that while their highest priority goals relate to safety, other nearly universally endorsed goals are more psychological in nature, such as moving on with one's life. Petitioners also use the orders to navigate complex relationships, helping themselves to set boundaries in addition to sending a clear message to respondents. Our group of lawyers viewed petitioners' highest priority goals as a relatively good fit with the system, but was fairly pessimistic about the likelihood of success. Petitioners' ratings of progress toward their goals, at the time of the PO hearing, differed markedly from lawyers' perceptions. Implications for research and practice are discussed. © The Author(s) 2015.
Reduced-Order Modeling for Flutter/LCO Using Recurrent Artificial Neural Network
Yao, Weigang; Liou, Meng-Sing
2012-01-01
The present study demonstrates the efficacy of a recurrent artificial neural network to provide a high fidelity time-dependent nonlinear reduced-order model (ROM) for flutter/limit-cycle oscillation (LCO) modeling. An artificial neural network is a relatively straightforward nonlinear method for modeling an input-output relationship from a set of known data, for which we use the radial basis function (RBF) with its parameters determined through a training process. The resulting RBF neural network, however, is only static and is not yet adequate for an application to problems of dynamic nature. The recurrent neural network method [1] is applied to construct a reduced order model resulting from a series of high-fidelity time-dependent data of aero-elastic simulations. Once the RBF neural network ROM is constructed properly, an accurate approximate solution can be obtained at a fraction of the cost of a full-order computation. The method derived during the study has been validated for predicting nonlinear aerodynamic forces in transonic flow and is capable of accurate flutter/LCO simulations. The obtained results indicate that the present recurrent RBF neural network is accurate and efficient for nonlinear aero-elastic system analysis
Freed, Alan D.; Diethelm, Kai; Gray, Hugh R. (Technical Monitor)
2002-01-01
Fraction-order viscoelastic (FOV) material models have been proposed and studied in 1D since the 1930's, and were extended into three dimensions in the 1970's under the assumption of infinitesimal straining. It was not until 1997 that Drozdov introduced the first finite-strain FOV constitutive equations. In our presentation, we shall continue in this tradition by extending the standard, FOV, fluid and solid, material models introduced in 1971 by Caputo and Mainardi into 3D constitutive formula applicable for finite-strain analyses. To achieve this, we generalize both the convected and co-rotational derivatives of tensor fields to fractional order. This is accomplished by defining them first as body tensor fields and then mapping them into space as objective Cartesian tensor fields. Constitutive equations are constructed using both variants for fractional rate, and their responses are contrasted in simple shear. After five years of research and development, we now possess a basic suite of numerical tools necessary to study finite-strain FOV constitutive equations and their iterative refinement into a mature collection of material models. Numerical methods still need to be developed for efficiently solving fraction al-order integrals, derivatives, and differential equations in a finite element setting where such constitutive formulae would need to be solved at each Gauss point in each element of a finite model, which can number into the millions in today's analysis.
Beaulieu, Alexandre; Bossé, Dominick; Micheau, Philippe; Avoine, Olivier; Praud, Jean-Paul; Walti, Hervé
2012-02-01
This study presents a methodology for applying the forced-oscillation technique in total liquid ventilation. It mainly consists of applying sinusoidal volumetric excitation to the respiratory system, and determining the transfer function between the delivered flow rate and resulting airway pressure. The investigated frequency range was f ∈ [0.05, 4] Hz at a constant flow amplitude of 7.5 mL/s. The five parameters of a fractional order lung model, the existing "5-parameter constant-phase model," were identified based on measured impedance spectra. The identification method was validated in silico on computer-generated datasets and the overall process was validated in vitro on a simplified single-compartment mechanical lung model. In vivo data on ten newborn lambs suggested the appropriateness of a fractional-order compliance term to the mechanical impedance to describe the low-frequency behavior of the lung, but did not demonstrate the relevance of a fractional-order inertance term. Typical respiratory system frequency response is presented together with statistical data of the measured in vivo impedance model parameters. This information will be useful for both the design of a robust pressure controller for total liquid ventilators and the monitoring of the patient's respiratory parameters during total liquid ventilation treatment. © 2011 IEEE
User-defined Material Model for Thermo-mechanical Progressive Failure Analysis
Knight, Norman F., Jr.
2008-01-01
Previously a user-defined material model for orthotropic bimodulus materials was developed for linear and nonlinear stress analysis of composite structures using either shell or solid finite elements within a nonlinear finite element analysis tool. Extensions of this user-defined material model to thermo-mechanical progressive failure analysis are described, and the required input data are documented. The extensions include providing for temperature-dependent material properties, archival of the elastic strains, and a thermal strain calculation for materials exhibiting a stress-free temperature.
Widlowski, J.L.; Taberner, M.; Pinty, B.; Bruniquel-Pinel, V.; Disney, M.I.; Fernandes, R.; Gastellu-Etchegorry, J.P.; Gobron, N.; Kuusk, A.; Lavergne, T.; LeBlanc, S.; Lewis, P.E.; Martin, E.; Mõttus, M.; North, P.R.J.; Qin, W.; Robustelli, M.; Rochdi, N.; Ruiloba, R.; Thompson, R.; Verhoef, W.; Verstraete, M.M.; Xie, D.
2007-01-01
[1] The Radiation Transfer Model Intercomparison ( RAMI) initiative benchmarks canopy reflectance models under well-controlled experimental conditions. Launched for the first time in 1999, this triennial community exercise encourages the systematic evaluation of canopy reflectance models on a
Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach
Aguilo, Miguel A.; Warner, James E.
2017-01-01
This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.
3D Higher Order Modeling in the BEM/FEM Hybrid Formulation
Fink, P. W.; Wilton, D. R.
2000-01-01
Higher order divergence- and curl-conforming bases have been shown to provide significant benefits, in both convergence rate and accuracy, in the 2D hybrid finite element/boundary element formulation (P. Fink and D. Wilton, National Radio Science Meeting, Boulder, CO, Jan. 2000). A critical issue in achieving the potential for accuracy of the approach is the accurate evaluation of all matrix elements. These involve products of high order polynomials and, in some instances, singular Green's functions. In the 2D formulation, the use of a generalized Gaussian quadrature method was found to greatly facilitate the computation and to improve the accuracy of the boundary integral equation self-terms. In this paper, a 3D, hybrid electric field formulation employing higher order bases and higher order elements is presented. The improvements in convergence rate and accuracy, compared to those resulting from lower order modeling, are established. Techniques developed to facilitate the computation of the boundary integral self-terms are also shown to improve the accuracy of these terms. Finally, simple preconditioning techniques are used in conjunction with iterative solution procedures to solve the resulting linear system efficiently. In order to handle the boundary integral singularities in the 3D formulation, the parent element- either a triangle or rectangle-is subdivided into a set of sub-triangles with a common vertex at the singularity. The contribution to the integral from each of the sub-triangles is computed using the Duffy transformation to remove the singularity. This method is shown to greatly facilitate t'pe self-term computation when the bases are of higher order. In addition, the sub-triangles can be further divided to achieve near arbitrary accuracy in the self-term computation. An efficient method for subdividing the parent element is presented. The accuracy obtained using higher order bases is compared to that obtained using lower order bases when the number
An Online Method for Interpolating Linear Parametric Reduced-Order Models
Amsallem, David
2011-01-01
A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.
DEFF Research Database (Denmark)
Eriksen, Janus Juul; Solanko, Lukasz Michal; Nåbo, Lina J.
2014-01-01
We present an implementation of the Polarizable Continuum Model (PCM) in combination with the Second–Order Polarization Propagator Approximation (SOPPA) electronic structure method. In analogy with the most common way of designing ground state calculations based on a Second–Order Møller-Plesset (MP......2) wave function coupled to PCM, we introduce dynamical PCM solvent effects only in the Random Phase Approximation (RPA) part of the SOPPA response equations while the static solvent contribution is kept in both the RPA terms as well as in the higher order correlation matrix components of the SOPPA...... response equations. By dynamic terms, we refer to contributions that describe a change in environmental polarization which, in turn, reflects a change in the core molecular charge distribution upon an electronic excitation. This new combination of methods is termed PCM-SOPPA/RPA. We apply this newly...
First and second order semi-Markov chains for wind speed modeling
Prattico, F.; Petroni, F.; D'Amico, G.
2012-04-01
The increasing interest in renewable energy leads scientific research to find a better way to recover most of the available energy. Particularly, the maximum energy recoverable from wind is equal to 59.3% of that available (Betz law) at a specific pitch angle and when the ratio between the wind speed in output and in input is equal to 1/3. The pitch angle is the angle formed between the airfoil of the blade of the wind turbine and the wind direction. Old turbine and a lot of that actually marketed, in fact, have always the same invariant geometry of the airfoil. This causes that wind turbines will work with an efficiency that is lower than 59.3%. New generation wind turbines, instead, have a system to variate the pitch angle by rotating the blades. This system able the wind turbines to recover, at different wind speed, always the maximum energy, working in Betz limit at different speed ratios. A powerful system control of the pitch angle allows the wind turbine to recover better the energy in transient regime. A good stochastic model for wind speed is then needed to help both the optimization of turbine design and to assist the system control to predict the value of the wind speed to positioning the blades quickly and correctly. The possibility to have synthetic data of wind speed is a powerful instrument to assist designer to verify the structures of the wind turbines or to estimate the energy recoverable from a specific site. To generate synthetic data, Markov chains of first or higher order are often used [1,2,3]. In particular in [3] is presented a comparison between a first-order Markov chain and a second-order Markov chain. A similar work, but only for the first-order Markov chain, is conduced by [2], presenting the probability transition matrix and comparing the energy spectral density and autocorrelation of real and synthetic wind speed data. A tentative to modeling and to join speed and direction of wind is presented in [1], by using two models, first-order
Low-order dynamical system model of a fully developed turbulent channel flow
Hamilton, Nicholas; Tutkun, Murat; Cal, Raúl Bayoán
2017-06-01
A reduced order model of a turbulent channel flow is composed from a direct numerical simulation database hosted at the Johns Hopkins University. Snapshot proper orthogonal decomposition (POD) is used to identify the Hilbert space from which the reduced order model is obtained, as the POD basis is defined to capture the optimal energy content by mode. The reduced order model is defined by coupling the evolution of the dynamic POD mode coefficients through their respective time derivative with a least-squares polynomial fit of terms up to third order. Parameters coupling the dynamics of the POD basis are defined in analog to those produced in the classical Galerkin projection. The resulting low-order dynamical system is tested for a range of basis modes demonstrating that the non-linear mode interactions do not lead to a monotonic decrease in error propagation. A basis of five POD modes accounts for 50% of the integrated turbulence kinetic energy but captures only the largest features of the turbulence in the channel flow and is not able to reflect the anticipated flow dynamics. Using five modes, the low-order model is unable to accurately reproduce Reynolds stresses, and the root-mean-square error of the predicted stresses is as great as 30%. Increasing the basis to 28 modes accounts for 90% of the kinetic energy and adds intermediate scales to the dynamical system. The difference between the time derivatives of the random coefficients associated with individual modes and their least-squares fit is amplified in the numerical integration leading to unstable long-time solutions. Periodic recalibration of the dynamical system is undertaken by limiting the integration time to the range of the sampled data and offering the dynamical system new initial conditions. Renewed initial conditions are found by pushing the mode coefficients in the end of the integration time toward a known point along the original trajectories identified through a least-squares projection. Under
Effects of fluoride on caries development and progression using intra-oral models.
Wefel, J S
1990-02-01
This paper reviews the use of intra-oral model systems to help elucidate the role of fluoride and its mechanism of action in caries prevention. The intra-oral models currently in use were found to be of three general types. The most widely used system has consisted of a removable appliance that relies on the use of dacron gauze or a recessed sample to enhance plaque formation. Similarly, the banding model of Ogaard requires the presence of orthodontic band material to produce a plaque accumulation niche for demineralization, while the crown single-section technique relies mainly on placement of the sections in plaque-retentive areas (below contact points). In general, the models may be used for the assessment of food cariogenicity, an evaluation of de- and re-mineralization, and measurement of fluoride incorporation into enamel or root substrates. On evaluation of lesion initiation and progression in vivo, it is apparent that few non-destructive in vivo techniques are available that offer the sensitivity of laboratory-based analysis. Thus, the use of intra-oral models that allow lesion formation and progression to occur in the oral environment, but can be measured with the sensitivity of in vitro techniques, has been extremely important. Although the magnitude of the fluoride dose, the longevity of fluoride in the oral environment, and the time required for remineralization are different from those found in vitro, it is apparent that the presence of fluoride in the aqueous phase is now thought to be of primary importance. Mechanistically, the presence of fluoride will both inhibit demineralization by acid and promote remineralization under more neutral conditions. Thus, one of fluoride's major contributions is to affect the rates of lesion formation and progression. It was concluded that low-concentration fluoride agents with a high frequency of application would best fulfill the above needs.
Low-Order Modeling of Dynamic Stall on Airfoils in Incompressible Flow
Narsipur, Shreyas
Unsteady aerodynamics has been a topic of research since the late 1930's and has increased in popularity among researchers studying dynamic stall in helicopters, insect/bird flight, micro air vehicles, wind-turbine aerodynamics, and ow-energy harvesting devices. Several experimental and computational studies have helped researchers gain a good understanding of the unsteady ow phenomena, but have proved to be expensive and time-intensive for rapid design and analysis purposes. Since the early 1970's, the push to develop low-order models to solve unsteady ow problems has resulted in several semi-empirical models capable of effectively analyzing unsteady aerodynamics in a fraction of the time required by high-order methods. However, due to the various complexities associated with time-dependent flows, several empirical constants and curve fits derived from existing experimental and computational results are required by the semi-empirical models to be an effective analysis tool. The aim of the current work is to develop a low-order model capable of simulating incompressible dynamic-stall type ow problems with a focus on accurately modeling the unsteady ow physics with the aim of reducing empirical dependencies. The lumped-vortex-element (LVE) algorithm is used as the baseline unsteady inviscid model to which augmentations are applied to model unsteady viscous effects. The current research is divided into two phases. The first phase focused on augmentations aimed at modeling pure unsteady trailing-edge boundary-layer separation and stall without leading-edge vortex (LEV) formation. The second phase is targeted at including LEV shedding capabilities to the LVE algorithm and combining with the trailing-edge separation model from phase one to realize a holistic, optimized, and robust low-order dynamic stall model. In phase one, initial augmentations to theory were focused on modeling the effects of steady trailing-edge separation by implementing a non-linear decambering
A Basin-Scale Modeling of Land Use and Population Distributions Using the Horton- Strahler Ordering
Miyamoto, H.; Michioku, K.; Hashimoto, T.
2008-12-01
From a basin-scale viewpoint, impact factors of human activities on river environment, such as land use changes and human population distributed within the river basin, may affect the balance of water resources and the river ecology. In this study, we develop a mathematical model using the well-known Horton-Strahler's stream order to describe the basin-scale distributions of the human impact factors as well as to compare their distribution characteristics among many river basins with different geomorphological features. In the model, we assume that the mean areas or numbers of each human impact factor, such as the paddy field, forest, urban areas or human population, of each stream order form a geometric sequence with order number, which is the same representation as the conventional Horton-Strahler laws of river geomorphology. We use GIS dataset of the land uses and human populations in the 109 large river basins in allover Japan and verify the model applicability for all of the human impact factors. Then, we examine relationships between the Horton-Strahler's ratios, i.e., the bifurcation, length, area, and slope ratios, and the ratios of the human impact factors. The result shows that the ratios of the human impact factors can be represented with high accuracy by the only two Horton-Strahler's ratios, i.e., the bifurcation and area ratios. This implies that the human activities distributed within a river basin are strongly influenced by the basin topologic features generated over a very long span of time. Consequently, when we have information of the overall basin characteristics, i.e., the maximum stream order, basin area, land use areas and human population as well as the two Horton-Strahler's ratios, the present geometric model can provide the mean values of the human impact factors in each stream order. Furthermore, we evaluate the average and deviation of the human impact factors among the 109 river basins by using the present model with randomness of the
Pin-wheel hexagons: a model for anthraquinone ordering on Cu(111).
Simenas, M; Tornau, E E
2013-10-21
The 4-state model of anthraquinone molecules ordering in a pin-wheel large-pore honeycomb phase on Cu(111) is proposed and solved by Monte Carlo simulation. The model is defined on a rescaled triangular lattice with the lattice constant a being equal to intermolecular distance in the honeycomb phase. The pin-wheel triangle formations are obtained taking into account the elongated shape of the molecules and anisotropic interactions for main two attractive short range (double and single dimeric) H-bond interactions. The long-range intermolecular interactions, corresponding to repulsive dipole-dipole forces, are assumed to be isotropic. Also, a very small (compared to short-range forces) isotropic attractive long-range interaction at the "characteristic" distance of a pore diameter is employed, and its effect carefully studied. This interaction is crucial for a formation of closed porous ordered systems, pin-wheel hexagons in particular. If each side of a pin-wheel hexagon is formed of n parallel molecules, the distance of this characteristic interaction is a√(3n(2)+1). The phase diagrams including different pin-wheel hexagon phases and a variety of other ordered structures are obtained. By changing the distance of characteristic interaction, different ordering routes into the experimental pin-wheel honeycomb phase are explored. The results obtained imply that classical explanation of the origin of the pin-wheel honeycomb phase in terms of some balance of attractive and repulsive forces cannot be totally discounted yet.
Luo, Gang
2017-01-01
For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022
Luo, Gang
2017-12-01
For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic.
Coexistence of two vector order parameters: a holographic model for ferromagnetic superconductivity
Energy Technology Data Exchange (ETDEWEB)
Amoretti, Andrea [Dipartimento di Fisica, Università di Genova, and I.N.F.N. - Sezione di Genova, via Dodecaneso 33, 16146, Genova (Italy); Braggio, Alessandro [CNR-SPIN, via Dodecaneso 33, 16146, Genova (Italy); Maggiore, Nicola; Magnoli, Nicodemo [Dipartimento di Fisica, Università di Genova, and I.N.F.N. - Sezione di Genova, via Dodecaneso 33, 16146, Genova (Italy); Musso, Daniele [Physique Théorique et Mathématique, Université Libre de Bruxelles, C.P. 231, 1050 Bruxelles (Belgium)
2014-01-13
We study a generalization of the standard holographic p-wave superconductor featuring two interacting vector order parameters. Basing our argument on the symmetry and linear response properties of the model, we propose it as a holographic effective theory describing a strongly coupled ferromagnetic superconductor. We show that the two order parameters undergo concomitant condensations as a manifestation of an intrinsically interlaced charge/spin dynamics. Such intertwined dynamics is confirmed by the study of the transport properties. We characterize thoroughly the equilibrium and the linear response (i.e. optical conductivity and spin susceptibility) of the model at hand by means of a probe approximation analysis. Some insight about the effects of backreaction in the normal phase can be gained by analogy with the s-wave unbalanced holographic superconductor.
Directory of Open Access Journals (Sweden)
Wolfgang Witteveen
2014-01-01
Full Text Available The mechanical response of multilayer sheet structures, such as leaf springs or car bodies, is largely determined by the nonlinear contact and friction forces between the sheets involved. Conventional computational approaches based on classical reduction techniques or the direct finite element approach have an inefficient balance between computational time and accuracy. In the present contribution, the method of trial vector derivatives is applied and extended in order to obtain a-priori trial vectors for the model reduction which are suitable for determining the nonlinearities in the joints of the reduced system. Findings show that the result quality in terms of displacements and contact forces is comparable to the direct finite element method but the computational effort is extremely low due to the model order reduction. Two numerical studies are presented to underline the method’s accuracy and efficiency. In conclusion, this approach is discussed with respect to the existing body of literature.
Long-range order and symmetry breaking in projected entangled-pair state models
Rispler, Manuel; Duivenvoorden, Kasper; Schuch, Norbert
2015-10-01
Projected entangled-pair states (PEPS) provide a framework for the construction of models where a single tensor gives rise to both Hamiltonian and ground state wave function on the same footing. A key problem is to characterize the behavior which emerges in the system in terms of the properties of the tensor, and thus of the Hamiltonian. In this paper, we consider PEPS models with Z2 on-site symmetry and study the occurrence of long-range order and spontaneous symmetry breaking. We show how long-range order is connected to a degeneracy in the spectrum of the PEPS transfer operator, and how the latter gives rise to spontaneous symmetry breaking under perturbations. We provide a succinct characterization of the symmetry-broken states in terms of the PEPS tensor, and find that using the symmetry-broken states we can derive a local entanglement Hamiltonian, thereby restoring locality of the entanglement Hamiltonian for all gapped phases.
A Hybrid PO - Higher-Order Hierarchical MoM Formulation using Curvilinear Geometry Modeling
DEFF Research Database (Denmark)
Jørgensen, E.; Meincke, Peter; Breinbjerg, Olav
2003-01-01
which implies a very modest memory requirement. Nevertheless, the hierarchical feature of the basis functions maintains the ability to treat small geometrical details efficiently. In addition, the scatterer is modelled with higher-order curved patches which allows accurate modelling of curved surfaces......A very efficient hybrid PO-MoM method has been presented. In contrast to existing methods, the present solution employs higher-order hierarchical basis functions to discretize the MoM and PO currents. This allows to reduce the number of basis functions in both the PO and MoM regions considerably...... with a low number of patches. A numerical result for an offset shaped reflector antenna illustrated the accuracy of the method....
The Nordic Model in a Global Company Situated in Norway. Challenging Institutional Orders?
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Elin Kvande
2012-11-01
Full Text Available In this article, we explore the impact of internationalization as organizational processes where institutional actors meet in local contexts and negotiate the institutional order. The internationalization of working life implies that different traditions and practices meet and challenge each other. The focus is on how important elements of the Nordic micro model like cooperation between employees and employers and regulation of working hours are implemented in a global company situated in Norway. In general, it seems that employees and employers cooperate in line with this tradition in the Nordic micro model. Norwegian manager’s practices are described to be in accordance with Scandinavian management traditions, while managers from the United States appear to practice management consistent with the liberal working life model. The findings show a tension-filled clash between two different management practices, which indicates that the Nordic micro model in this field might be under pressure. Manager’s recommendation to the employees was not to become members of the trade union. The absence of trade unions in the organization implies that employees and employers are not cooperating on a collective level. This means that only parts of the regulatory arrangement related to participation and cooperation are implemented. Findings concerning working time and the relation to the institutional order represented by the Norwegian Work Environment Act indicate a clear tension between different institutional traditions in the organization. The company does not respect the Norwegian in working time regulations. These regulations are seen as counterproductive for a company that competes in the international market. This devaluation of the regulations in the Nordic model implies that the institutional order represented in the Nordic micro model is challenged.
Modeling shear-induced particle ordering and deformation in a dense soft particle suspension.
Liao, Chih-Tang; Wu, Yi-Fan; Chien, Wei; Huang, Jung-Ren; Chen, Yeng-Long
2017-11-01
We apply the lattice Boltzmann method and the bead-spring network model of deformable particles (DPs) to study shear-induced particle ordering and deformation and the corresponding rheological behavior for dense DP suspensions confined in a narrow gap under steady external shear. The particle configuration is characterized with small-angle scattering intensity, the real-space 2D local order parameter, and the particle shape factors including deformation, stretching and tilt angles. We investigate how particle ordering and deformation vary with the particle volume fraction ϕ (=0.45-0.65) and the external shear rate characterized with the capillary number Ca (=0.003-0.191). The degree of particle deformation increases mildly with ϕ but significantly with Ca. Under moderate shear rate (Ca = 0.105), the inter-particle structure evolves from string-like ordering to layered hexagonal close packing (HCP) as ϕ increases. A long wavelength particle slithering motion emerges for sufficiently large ϕ. For ϕ = 0.61, the structure maintains layered HCP for Ca = 0.031-0.143 but gradually becomes disordered for larger and smaller Ca. The correlation in particle zigzag movements depends sensitively on ϕ and particle ordering. Layer-by-layer analysis reveals how the non-slippery hard walls affect particle ordering and deformation. The shear-induced reconfiguration of DPs observed in the simulation agrees qualitatively with experimental results of sheared uniform emulsions. The apparent suspension viscosity increases with ϕ but exhibits much weaker dependence compared to hard-sphere suspensions, indicating that particle deformation and unjamming under shear can significantly reduce the viscous stress. Furthermore, the suspension shear-thins, corresponding to increased inter-DP ordering and particle deformation with Ca. This work provides useful insights into the microstructure-rheology relationship of concentrated deformable particle suspensions.
Directory of Open Access Journals (Sweden)
Xiaolin Shi
2016-01-01
Full Text Available This paper deals with the Bayesian inference on step-stress partially accelerated life tests using Type II progressive censored data in the presence of competing failure causes. Suppose that the occurrence time of the failure cause follows Pareto distribution under use stress levels. Based on the tampered failure rate model, the objective Bayesian estimates, Bayesian estimates, and E-Bayesian estimates of the unknown parameters and acceleration factor are obtained under the squared loss function. To evaluate the performance of the obtained estimates, the average relative errors (AREs and mean squared errors (MSEs are calculated. In addition, the comparisons of the three estimates of unknown parameters and acceleration factor for different sample sizes and different progressive censoring schemes are conducted through Monte Carlo simulations.
A Reduced-Order Model for Evaluating the Dynamic Response of Multilayer Plates to Impulsive Loads
2016-04-12
Analysis (SFEA) – by Numerical Analysis in Nastran • Dynamic Response Index (DRI) and the Screening Metric • Design Optimization Outline 2016-01-0307...elements method (SFEM) and numerical analysis in Nastran in the following examples. Reduced Order Model (ROM) 2016-01-0307 16UNCLASSIFIED: Distribution...Analysis (SFEA) 2. Validation by Numerical Analysis in Nastran • Applying an impulsive load • Comparing the forced response in frequency domain
Analysis of Internet Usage Intensity in Iraq: An Ordered Logit Model
Almas Heshmati; Firas H. Al-Hammadany; Ashraf Bany-Mohammed
2013-01-01
Intensity of Internet use is significantly influenced by government policies, people’s levels of income, education, employment and general development and economic conditions. Iraq has very low Internet usage levels compared to the region and the world. This study uses an ordered logit model to analyse the intensity of Internet use in Iraq. The results showed that economic reasons (internet cost and income level) were key cause for low level usage intensity rates. About 68% of the population ...
Directory of Open Access Journals (Sweden)
Xin Liang
2018-01-01
Full Text Available In this paper, an anomalous advection-dispersion model involving a new general Liouville–Caputo fractional-order derivative is addressed for the first time. The series solutions of the general fractional advection-dispersion equations are obtained with the aid of the Laplace transform. The results are given to demonstrate the efficiency of the proposed formulations to describe the anomalous advection dispersion processes.
BAYESIAN ANALYSIS FOR THE PAIRED COMPARISON MODEL WITH ORDER EFFECTS (USING NON-INFORMATIVE PRIORS
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Ghausia Masood Gilani
2008-07-01
Full Text Available Sometimes it may be difficult for a panelist to rank or compare more than two objects or treatments at the same time. For this reason, paired comparison method is used. In this study, the Davidson and Beaver (1977 model for paired comparisons with order effects is analyzed through the Bayesian Approach. For this purpose, the posterior means and the posterior modes are compared using the noninformative priors.
First-order transition and tricritical behavior of the transverse crystal field spin-1 Ising model
Costabile, Emanuel; Viana, J. Roberto; de Sousa, J. Ricardo; de Arruda, Alberto S.
2015-06-01
The phase diagram of the spin-1 Ising model in the presence of a transverse crystal-field anisotropy (Dx) is studied within the framework of an effective-field theory with correlation. The effect of the coordination number (z) on the phase diagram in the T -Dx plane is investigated. We observe only second-order transitions for coordination number z Ricardo de Sousa and Branco, Phys. Rev. E 77 (2008) 012104] with a single tricritical point in the phase diagram.
Team Resilience as a Second-Order Emergent State: A Theoretical Model and Research Directions
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Clint Bowers
2017-08-01
Full Text Available Resilience has been recognized as an important phenomenon for understanding how individuals overcome difficult situations. However, it is not only individuals who face difficulties; it is not uncommon for teams to experience adversity. When they do, they must be able to overcome these challenges without performance decrements.This manuscript represents a theoretical model that might be helpful in conceptualizing this important construct. Specifically, it describes team resilience as a second-order emergent state. We also include research propositions that follow from the model.
Ordering phenomena and non-equilibrium properties of lattice gas models
International Nuclear Information System (INIS)
Fiig, T.
1994-03-01
This report falls within the general field of ordering processes and non-equilibrium properties of lattice gas models. The theory of diffuse scattering of lattice gas models originating from a random distribution of clusters is considered. We obtain relations between the diffuse part of the structure factor S dif (q), the correlation function C(r), and the size distribution of clusters D(n). For a number of distributions we calculate S dif (q) exactly in one dimension, and discuss the possibility for a Lorentzian and a Lorentzian square lineshape to arise. We discuss the two- and three-dimensional oxygen ordering processes in the high T c superconductor YBa 2 Cu 3 O 6+x based on a simple anisotropic lattice gas model. We calculate the structural phase diagram by Monte Carlo simulation and compared the results with experimental data. The structure factor of the oxygen ordering properties has been calculated in both two and three dimensions by Monte Carlo simulation. We report on results obtained from large scale computations on the Connection Machine, which are in excellent agreement with recent neutron diffraction data. In addition we consider the effect of the diffusive motion of metal-ion dopants on the oxygen ordering properties on YBa 2 Cu 3 O 6+x . The stationary properties of metastability in long-range interaction models are studied by application of a constrained transfer matrix (CTM) formalism. The model considered, which exhibits several metastable states, is an extension of the Blume Capel model to include weak long-range interactions. We show, that the decay rate of the metastable states is closely related to the imaginary part of the equilibrium free-energy density obtained from the CTM formalism. We discuss a class of lattice gas model for dissipative transport in the framework of a Langevin description, which is capable of producing power law spectra for the density fluctuations. We compare with numerical results obtained from simulations of a
Economic Order Quantity Model with Two Levels of Delayed Payment and Bad Debt
Qin Juanjuan
2012-01-01
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 paramet...
Preisser, J. S.; Phillips, C.; Perin, J.; Schwartz, T. A.
2011-01-01
Objectives The article reviews proportional and partial proportional odds regression for ordered categorical outcomes, such as patient-reported measures, that are frequently used in clinical research in dentistry. Methods The proportional odds regression model for ordinal data is a generalization of ordinary logistic regression for dichotomous responses. When the proportional odds assumption holds for some but not all of the covariates, the lesser known partial proportional odds model is shown to provide a useful extension. Results The ordinal data models are illustrated for the analysis of repeated ordinal outcomes to determine whether the burden associated with sensory alteration following a bilateral sagittal split osteotomy procedure differed for those patients who were given opening exercises only following surgery and those who received sensory retraining exercises in conjunction with standard opening exercises. Conclusions Proportional and partial proportional odds models are broadly applicable to the analysis of cross-sectional and longitudinal ordinal data in dental research. PMID:21070317
A New MEMS Stochastic Model Order Reduction Method: Research and Application
Directory of Open Access Journals (Sweden)
Bian Xiangjuan
2015-01-01
Full Text Available Modeling and simulation of MEMS devices is a very complex tasks which involve the electrical, mechanical, fluidic, and thermal domains, and there are still some uncertainties that need to be accounted for during the robust design of MEMS actuators caused by uncertain material and/or geometric parameters. According to these problems, we put forward stochastic model order reduction method under random input conditions to facilitate fast time and frequency domain analyses; the method makes use of polynomial chaos expansions in terms of the random input variables for the matrices of a finite element model of the system and then uses its transformation matrix to reduce the model; the method is independent of the MOR algorithm, so it is seamlessly compatible with MOR method used in popular finite element solvers. The simulation results verify the method is effective in large scale MEMS design process.
A Progress Review on Soot Experiments and Modeling in the Engine Combustion Network (ECN)
Skeen, Scott A.
2016-04-05
The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.
Genetic Algorithm-Guided, Adaptive Model Order Reduction of Flexible Aircrafts
Zhu, Jin; Wang, Yi; Pant, Kapil; Suh, Peter; Brenner, Martin J.
2017-01-01
This paper presents a methodology for automated model order reduction (MOR) of flexible aircrafts to construct linear parameter-varying (LPV) reduced order models (ROM) for aeroservoelasticity (ASE) analysis and control synthesis in broad flight parameter space. The novelty includes utilization of genetic algorithms (GAs) to automatically determine the states for reduction while minimizing the trial-and-error process and heuristics requirement to perform MOR; balanced truncation for unstable systems to achieve locally optimal realization of the full model; congruence transformation for "weak" fulfillment of state consistency across the entire flight parameter space; and ROM interpolation based on adaptive grid refinement to generate a globally functional LPV ASE ROM. The methodology is applied to the X-56A MUTT model currently being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies indicate that X-56A ROM with less than one-seventh the number of states relative to the original model is able to accurately predict system response among all input-output channels for pitch, roll, and ASE control at various flight conditions. The GA-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The adaptive refinement allows selective addition of the grid points in the parameter space where flight dynamics varies dramatically to enhance interpolation accuracy without over-burdening controller synthesis and onboard memory efforts downstream. The present MOR framework can be used by control engineers for robust ASE controller synthesis and novel vehicle design.
International Nuclear Information System (INIS)
Rojas T, J.; Instituto Peruano de Energia Nuclear, Lima; Manrique C, E.; Torres T, E.
2002-01-01
Using monte Carlo simulation have been carried out an atomistic description of the structure and ordering processes in the system Cu-Au in a two-dimensional model. The ABV model of the alloy is a system of N atoms A and B, located in rigid lattice with some vacant sites. In the model we assume pair wise interactions between nearest neighbors with constant ordering energy J = 0,03 eV. The dynamics was introduced by means of a vacancy that exchanges of place with any atom of its neighbors. The simulations were carried out in a square lattice with 1024 and 4096 particles, using periodic boundary conditions to avoid border effects. We calculate the first two parameters of short range order of Warren-Cowley as function of the concentration and temperature. It was also studied the probabilities of formation of different atomic clusters that consist of 9 atoms as function of the concentration of the alloy and temperatures in a wide range of values. In some regions of temperature and concentration it was observed compositional and thermal polymorphism
Energy Technology Data Exchange (ETDEWEB)
Huang, M.; Supek, S.; Aine, C.
1996-06-01
Empirical neuromagnetic studies have reported that multiple brain regions are active at single instants in time as well as across time intervals of interest. Determining the number of active regions, however, required a systematic search across increasing model orders using reduced chi-square measure of goodness-of-fit and multiple starting points within each model order assumed. Simulated annealing was recently proposed for noiseless biomagnetic data as an effective global minimizer. A modified cost function was also proposed to effectively deal with an unknown number of dipoles for noiseless, multi-source biomagnetic data. Numerical simulation studies were conducted using simulated annealing to examine effects of a systematic increase in model order using both reduced chi-square as a cost function as well as a modified cost function, and effects of overmodeling on parameter estimation accuracy. Effects of different choices of weighting factors are also discussed. Simulated annealing was also applied to visually evoked neuromagnetic data and the effectiveness of both cost functions in determining the number of active regions was demonstrated.
Coarse-graining for fast dynamics of order parameters in the phase-field model
Jou, D.; Galenko, P. K.
2018-01-01
In standard descriptions, the master equation can be obtained by coarse-graining with the application of the hypothesis of full local thermalization that is equivalent to the local thermodynamic equilibrium. By contrast, fast transformations proceed in the absence of local equilibrium and the master equation must be obtained with the absence of thermalization. In the present work, a non-Markovian master equation leading, in specific cases of relaxation to local thermodynamic equilibrium, to hyperbolic evolution equations for a binary alloy, is derived for a system with two order parameters. One of them is a conserved order parameter related to the atomistic composition, and the other one is a non-conserved order parameter, which is related to phase field. A microscopic basis for phenomenological phase-field models of fast phase transitions, when the transition is so fast that there is not sufficient time to achieve local thermalization between two successive elementary processes in the system, is provided. In a particular case, when the relaxation to local thermalization proceeds by the exponential law, the obtained coarse-grained equations are related to the hyperbolic phase-field model. The solution of the model equations is obtained to demonstrate non-equilibrium phenomenon of solute trapping which appears in rapid growth of dendritic crystals. This article is part of the theme issue `From atomistic interfaces to dendritic patterns'.
On the Entropy Based Associative Memory Model with Higher-Order Correlations
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Masahiro Nakagawa
2010-01-01
Full Text Available In this paper, an entropy based associative memory model will be proposed and applied to memory retrievals with an orthogonal learning model so as to compare with the conventional model based on the quadratic Lyapunov functional to be minimized during the retrieval process. In the present approach, the updating dynamics will be constructed on the basis of the entropy minimization strategy which may be reduced asymptotically to the above-mentioned conventional dynamics as a special case ignoring the higher-order correlations. According to the introduction of the entropy functional, one may involve higer-order correlation effects between neurons in a self-contained manner without any heuristic coupling coefficients as in the conventional manner. In fact we shall show such higher order coupling tensors are to be uniquely determined in the framework of the entropy based approach. From numerical results, it will be found that the presently proposed novel approach realizes much larger memory capacity than that of the quadratic Lyapunov functional approach, e.g., associatron.
Jacobian projection reduced-order models for dynamic systems with contact nonlinearities
Gastaldi, Chiara; Zucca, Stefano; Epureanu, Bogdan I.
2018-02-01
In structural dynamics, the prediction of the response of systems with localized nonlinearities, such as friction dampers, is of particular interest. This task becomes especially cumbersome when high-resolution finite element models are used. While state-of-the-art techniques such as Craig-Bampton component mode synthesis are employed to generate reduced order models, the interface (nonlinear) degrees of freedom must still be solved in-full. For this reason, a new generation of specialized techniques capable of reducing linear and nonlinear degrees of freedom alike is emerging. This paper proposes a new technique that exploits spatial correlations in the dynamics to compute a reduction basis. The basis is composed of a set of vectors obtained using the Jacobian of partial derivatives of the contact forces with respect to nodal displacements. These basis vectors correspond to specifically chosen boundary conditions at the contacts over one cycle of vibration. The technique is shown to be effective in the reduction of several models studied using multiple harmonics with a coupled static solution. In addition, this paper addresses another challenge common to all reduction techniques: it presents and validates a novel a posteriori error estimate capable of evaluating the quality of the reduced-order solution without involving a comparison with the full-order solution.
Modelling the Progression of Competitive Performance of an Academy’s Soccer Teams
Malcata, Rita M.; Hopkins, Will G; Richardson, Scott
2012-01-01
Progression of a team’s performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents’ scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed
Modelling the Progression of Competitive Performance of an Academy's Soccer Teams.
Malcata, Rita M; Hopkins, Will G; Richardson, Scott
2012-01-01
Progression of a team's performance is a key issue in competitive sport, but there appears to have been no published research on team progression for periods longer than a season. In this study we report the game-score progression of three teams of a youth talent-development academy over five seasons using a novel analytic approach based on generalised mixed modelling. The teams consisted of players born in 1991, 1992 and 1993; they played totals of 115, 107 and 122 games in Asia and Europe between 2005 and 2010 against teams differing in age by up to 3 years. Game scores predicted by the mixed model were assumed to have an over-dispersed Poisson distribution. The fixed effects in the model estimated an annual linear pro-gression for Aspire and for the other teams (grouped as a single opponent) with adjustment for home-ground advantage and for a linear effect of age difference between competing teams. A random effect allowed for different mean scores for Aspire and opposition teams. All effects were estimated as factors via log-transformation and presented as percent differences in scores. Inferences were based on the span of 90% confidence intervals in relation to thresholds for small factor effects of x/÷1.10 (+10%/-9%). Most effects were clear only when data for the three teams were combined. Older teams showed a small 27% increase in goals scored per year of age difference (90% confidence interval 13 to 42%). Aspire experienced a small home-ground advantage of 16% (-5 to 41%), whereas opposition teams experienced 31% (7 to 60%) on their own ground. After adjustment for these effects, the Aspire teams scored on average 1.5 goals per match, with little change in the five years of their existence, whereas their opponents' scores fell from 1.4 in their first year to 1.0 in their last. The difference in progression was trivial over one year (7%, -4 to 20%), small over two years (15%, -8 to 44%), but unclear over >2 years. In conclusion, the generalized mixed model
A semi-implicit, second-order-accurate numerical model for multiphase underexpanded volcanic jets
Directory of Open Access Journals (Sweden)
S. Carcano
2013-11-01
Full Text Available An improved version of the PDAC (Pyroclastic Dispersal Analysis Code, Esposti Ongaro et al., 2007 numerical model for the simulation of multiphase volcanic flows is presented and validated for the simulation of multiphase volcanic jets in supersonic regimes. The present version of PDAC includes second-order time- and space discretizations and fully multidimensional advection discretizations in order to reduce numerical diffusion and enhance the accuracy of the original model. The model is tested on the problem of jet decompression in both two and three dimensions. For homogeneous jets, numerical results are consistent with experimental results at the laboratory scale (Lewis and Carlson, 1964. For nonequilibrium gas–particle jets, we consider monodisperse and bidisperse mixtures, and we quantify nonequilibrium effects in terms of the ratio between the particle relaxation time and a characteristic jet timescale. For coarse particles and low particle load, numerical simulations well reproduce laboratory experiments and numerical simulations carried out with an Eulerian–Lagrangian model (Sommerfeld, 1993. At the volcanic scale, we consider steady-state conditions associated with the development of Vulcanian and sub-Plinian eruptions. For the finest particles produced in these regimes, we demonstrate that the solid phase is in mechanical and thermal equilibrium with the gas phase and that the jet decompression structure is well described by a pseudogas model (Ogden et al., 2008. Coarse particles, on the other hand, display significant nonequilibrium effects, which associated with their larger relaxation time. Deviations from the equilibrium regime, with maximum velocity and temperature differences on the order of 150 m s−1 and 80 K across shock waves, occur especially during the rapid acceleration phases, and are able to modify substantially the jet dynamics with respect to the homogeneous case.
A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence
Directory of Open Access Journals (Sweden)
Simon Zwieback
2015-06-01
Full Text Available Changes in soil moisture between two radar acquisitions can impact the observed coherence in differential interferometry: both coherence magnitude |Υ| and phase Φ are affected. The influence on the latter potentially biases the estimation of deformations. These effects have been found to be variable in magnitude and sign, as well as dependent on polarization, as opposed to predictions by existing models. Such diversity can be explained when the soil is modelled as a half-space with spatially varying dielectric properties and a rough interface. The first-order perturbative solution achieves–upon calibration with airborne L band data–median correlations ρ at HH polarization of 0.77 for the phase Φ, of 0.50 for |Υ|, and for the phase triplets ≡ of 0.56. The predictions are sensitive to the choice of dielectric mixing model, in particular the absorptive properties; the differences between the mixing models are found to be partially compensatable by varying the relative importance of surface and volume scattering. However, for half of the agricultural fields the Hallikainen mixing model cannot reproduce the observed sensitivities of the phase to soil moisture. In addition, the first-order expansion does not predict any impact on the HV coherence, which is however empirically found to display similar sensitivities to soil moisture as the co-pol channels HH and VV. These results indicate that the first-order solution, while not able to reproduce all observed phenomena, can capture some of the more salient patterns of the effect of soil moisture changes on the HH and VV DInSAR signals. Hence it may prove useful in separating the deformations from the moisture signals, thus yielding improved displacement estimates or new ways for inferring soil moisture.
Do-not-attempt-resuscitation orders and prognostic models for intraparenchymal hemorrhage.
Creutzfeldt, Claire J; Becker, Kyra J; Weinstein, Jonathan R; Khot, Sandeep P; McPharlin, Thomas O; Ton, Thanh G; Longstreth, W T; Tirschwell, David L
2011-01-01
Statistical models predicting outcome after intraparenchymal hemorrhage include patients irrespective of do-not-attempt-resuscitation orders. We built a model to explore how the inclusion of patients with do-not-attempt-resuscitation orders affects intraparenchymal hemorrhage prognostic models. Retrospective, observational cohort study from May 2001 until September 2003. University-affiliated tertiary referral hospital in Seattle, WA. Four hundred twenty-four consecutive patients with spontaneous intraparenchymal hemorrhage. We retrospectively abstracted information from medical records of intraparenchymal hemorrhage patients admitted to a single hospital. Using multivariate logistic regression of presenting clinical characteristics, but not do-not-attempt-resuscitation status, we generated a prognostic score for favorable outcome (defined as moderate disability or better at discharge). We compared observed probability of favorable outcome with that predicted, stratified by do-not-attempt-resuscitation status. We then generated a modified prognostic score using only non-do-not-attempt-resuscitation patients. Records of 424 patients were reviewed: 44% had favorable outcome, 43% had a do-not-attempt-resuscitation order, and 38% died in hospital. The observed and predicted probability of favorable outcome agreed well with all patients taken together. The observed probability of favorable outcome was significantly higher than predicted in non-do-not-attempt-resuscitation patients and significantly lower in do-not-attempt-resuscitation patients. Results were similar when applying a previously published and validated prognostic score. Our modified prognostic score was no longer pessimistic in non-do-not-attempt-resuscitation patients but remained overly optimistic in do-not-attempt-resuscitation patients. Although our prognostic model was well-calibrated when assessing all intraparenchymal hemorrhage patients, predictions were significantly pessimistic in patients
International Nuclear Information System (INIS)
Brodin, N. Patrik; Vogelius, Ivan R.; Björk-Eriksson, Thomas; Munck af Rosenschöld, Per; Bentzen, Søren M.
2013-01-01
Purpose: As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published pattern of failure data. Methods and Materials: Outcome data for standard-risk MB published after 1990 with pattern of relapse information were used to fit a tumor control dose-response model addressing failures in both the high-dose boost volume and the elective craniospinal volume. Estimates of 5-year event-free survival from 2 large randomized MB trials were used to model the time-to-progression distribution. Uncertainty in freedom from progression (FFP) was estimated by Monte Carlo sampling over the statistical uncertainty in input data. Results: The estimated 5-year FFP (95% confidence intervals [CI]) for craniospinal doses of 15, 18, 24, and 36 Gy while maintaining 54 Gy to the posterior fossa was 77% (95% CI, 70%-81%), 78% (95% CI, 73%-81%), 79% (95% CI, 76%-82%), and 80% (95% CI, 77%-84%) respectively. The uncertainty in FFP was considerably larger for craniospinal doses below 18 Gy, reflecting the lack of data in the lower dose range. Conclusions: Estimates of tumor control and time-to-progression for standard-risk MB provides a data-driven setting for hypothesis generation or power calculations for prospective trials, taking the uncertainties into account. The presented methods can also be applied to incorporate further risk-stratification for example based on molecular biomarkers, when the necessary data become available
A spatially explicit model for the future progression of the current Haiti cholera epidemic
Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.
2011-12-01
As a major cholera epidemic progresses in Haiti, and the figures of the infection, up to July 2011, climb to 385,000 cases and 5,800 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 textit{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 texttrademark project). The model directly account 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. 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, clean water supply and educational campaigns, thus emerging as an essential component of the control of future cholera
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Adele eDiederich
2014-09-01
Full Text Available A sequential sampling model for multiattribute binary choice options, called Multiattribute attention switching (MAAS model, assumes a separate sampling process for each attribute. During the deliberation process attention switches from one attribute consideration to the next. The order in which attributes are considered as well for how long each attribute is considered - the attention time - influences the predicted choice probabilities and choice response times. Several probability distributions for the attention time including deterministic, Poisson, binomial, geometric, and uniform with different variances are investigated. Depending on the time and order schedule the model predicts a rich choice probability/choice response time pattern including preference reversals and fast errors. Furthermore, the difference between a finite and infinite decision horizons for the attribute considered last is investigated. For the former case the model predicts a probability $p_0> 0$ of not deciding within the available time. The underlying stochastic process for each attribute is an Ornstein-Uhlenbeck process approximated by a discrete birth-death process. All predictions are also true for the widely applied Wiener process.
He, Zhangyi; Beaumont, Mark; Yu, Feng
2017-07-05
We explore the effect of different mechanisms of natural selection on the evolution of populations for one- and two-locus systems. We compare the effect of viability and fecundity selection in the context of the Wright-Fisher model with selection under the assumption of multiplicative fitness. We show that these two modes of natural selection correspond to different orderings of the processes of population regulation and natural selection in the Wright-Fisher model. We find that under the Wright-Fisher model these two different orderings can affect the distribution of trajectories of haplotype frequencies evolving with genetic recombination. However, the difference in the distribution of trajectories is only appreciable when the population is in significant linkage disequilibrium. We find that as linkage disequilibrium decays the trajectories for the two different models rapidly become indistinguishable. We discuss the significance of these findings in terms of biological examples of viability and fecundity selection, and speculate that the effect may be significant when factors such as gene migration maintain a degree of linkage disequilibrium. Copyright © 2017 He et al.
A note on inventory model for ameliorating items with time dependent second order demand rate
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Gobinda Chandra Panda
2013-03-01
Full Text Available Background: This paper is concerned with the development of ameliorating inventory models. The ameliorating inventory is the inventory of goods whose utility increases over the time by ameliorating activation. Material and Methods: This study is performed according to two areas: one is an economic order quantity (EOQ model for the items whose utility is ameliorating in accordance with Weibull distribution, and the other is a partial selling quantity (PSQ model developed for selling the surplus inventory accumulated by ameliorating activation with linear demand. The aim of this paper was to develop a mathematical model for inventory type concerned in the paper. Numerical examples were presented show the effect of ameliorating rate on inventory polices. Results and Conclusions: The inventory model for items with Weibull ameliorating is developed. For the case of small ameliorating rate (less than linear demand rate, EOQ model is developed, and for the case where ameliorating rate is greater than linear demand rate, PSQ model is developed. .
Hall, A.; Munoz-Ruiz, M.; Mattila, J.; Koikkalainen, J.; Tsolaki, M.; Mecocci, P.; Kloszewska, I.; Vellas, B.; Lovestone, S.; Visser, P.J.; Lotjonen, J.; Soininen, H.
2015-01-01
Background: The Disease State Index (DSI) prediction model measures the similarity of patient data to diagnosed stable and progressive mild cognitive impairment (MCI) cases to identify patients who are progressing to Alzheimer's disease. Objectives: We evaluated how well the DSI generalizes across
Modeling Geometry and Progressive Failure of Material Interfaces in Plain Weave Composites
Hsu, Su-Yuen; Cheng, Ron-Bin
2010-01-01
A procedure combining a geometrically nonlinear, explicit-dynamics contact analysis, computer aided design techniques, and elasticity-based mesh adjustment is proposed to efficiently generate realistic finite element models for meso-mechanical analysis of progressive failure in textile composites. In the procedure, the geometry of fiber tows is obtained by imposing a fictitious expansion on the tows. Meshes resulting from the procedure are conformal with the computed tow-tow and tow-matrix interfaces but are incongruent at the interfaces. The mesh interfaces are treated as cohesive contact surfaces not only to resolve the incongruence but also to simulate progressive failure. The method is employed to simulate debonding at the material interfaces in a ceramic-matrix plain weave composite with matrix porosity and in a polymeric matrix plain weave composite without matrix porosity, both subject to uniaxial cyclic loading. The numerical results indicate progression of the interfacial damage during every loading and reverse loading event in a constant strain amplitude cyclic process. However, the composites show different patterns of damage advancement.
Dietary folate deficiency blocks prostate cancer progression in the TRAMP model.
Bistulfi, Gaia; Foster, Barbara A; Karasik, Ellen; Gillard, Bryan; Miecznikowski, Jeff; Dhiman, Vineet K; Smiraglia, Dominic J
2011-11-01
Dietary folate is essential in all tissues to maintain several metabolite pools and cellular proliferation. Prostate cells, due to specific metabolic characteristics, have increased folate demand to support proliferation and prevent genetic and epigenetic damage. Although several studies have found that dietary folate interventions can affect colon cancer biology in rodent models, its impact on prostate is unknown. The purpose of this study was to determine whether dietary folate manipulation, possibly being of primary importance for prostate epithelial cell metabolism, could significantly affect prostate cancer progression. Strikingly, mild dietary folate depletion arrested prostate cancer progression in 25 of 26 transgenic adenoma of the mouse prostate (TRAMP) mice, in which tumorigenesis is prostate-specific and characteristically aggressive. The significant effect on prostate cancer growth was characterized by size, grade, proliferation, and apoptosis analyses. Folate supplementation had a mild, nonsignificant, beneficial effect on grade. In addition, characterization of folate pools (correlated with serum), metabolite pools (polyamines and nucleotides), genetic and epigenetic damage, and expression of key biosynthetic enzymes in prostate tissue revealed interesting correlations with tumor progression. These findings indicate that prostate cancer is highly sensitive to folate manipulation and suggest that antifolates, paired with current therapeutic strategies, might significantly improve treatment of prostate cancer, the most commonly diagnosed cancer in American men.
Compositional modeling of three-phase flow with gravity using higher-order finite element methods
Moortgat, Joachim
2011-05-11
A wide range of applications in subsurface flow involve water, a nonaqueous phase liquid (NAPL) or oil, and a gas phase, such as air or CO2. The numerical simulation of such processes is computationally challenging and requires accurate compositional modeling of three-phase flow in porous media. In this work, we simulate for the first time three-phase compositional flow using higher-order finite element methods. Gravity poses complications in modeling multiphase processes because it drives countercurrent flow among phases. To resolve this issue, we propose a new method for the upwinding of three-phase mobilities. Numerical examples, related to enhanced oil recovery and carbon sequestration, are presented to illustrate the capabilities of the proposed algorithm. We pay special attention to challenges associated with gravitational instabilities and take into account compressibility and various phase behavior effects, including swelling, viscosity changes, and vaporization. We find that the proposed higher-order method can capture sharp solution discontinuities, yielding accurate predictions of phase boundaries arising in computational three-phase flow. This work sets the stage for a broad extension of the higher-order methods for numerical simulation of three-phase flow for complex geometries and processes.
Rotaru, Ionela Magdalena
2015-09-01
Knowledge management is a powerful instrument. Areas where knowledge - based modelling can be applied are different from business, industry, government to education area. Companies engage in efforts to restructure the database held based on knowledge management principles as they recognize in it a guarantee of models characterized by the fact that they consist only from relevant and sustainable knowledge that can bring value to the companies. The proposed paper presents a theoretical model of what it means optimizing polyethylene pipes, thus bringing to attention two important engineering fields, the one of the metal cutting process and gas industry, who meet in order to optimize the butt fusion welding process - the polyethylene cutting part - of the polyethylene pipes. All approach is shaped on the principles of knowledge management. The study was made in collaboration with companies operating in the field.
In Vitro Co-Culture Models of Breast Cancer Metastatic Progression towards Bone
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Chiara Arrigoni
2016-08-01
Full Text Available Advanced breast cancer frequently metastasizes to bone through a multistep process involving the detachment of cells from the primary tumor, their intravasation into the bloodstream, adhesion to the endothelium and extravasation into the bone, culminating with the establishment of a vicious cycle causing extensive bone lysis. In recent years, the crosstalk between tumor cells and secondary organs microenvironment is gaining much attention, being indicated as a crucial aspect in all metastatic steps. To investigate the complex interrelation between the tumor and the microenvironment, both in vitro and in vivo models have been exploited. In vitro models have some advantages over in vivo, mainly the possibility to thoroughly dissect in controlled conditions and with only human cells the cellular and molecular mechanisms underlying the metastatic progression. In this article we will review the main results deriving from in vitro co-culture models, describing mechanisms activated in the crosstalk between breast cancer and bone cells which drive the different metastatic steps.
Recent progress and modern challenges in applied mathematics, modeling and computational science
Makarov, Roman; Belair, Jacques
2017-01-01
This volume is an excellent resource for professionals in various areas of applications of mathematics, modeling, and computational science. It focuses on recent progress and modern challenges in these areas. The volume provides a balance between fundamental theoretical and applied developments, emphasizing the interdisciplinary nature of modern trends and detailing state-of-the-art achievements in Applied Mathematics, Modeling, and Computational Science. The chapters have been authored by international experts in their respective fields, making this book ideal for researchers in academia, practitioners, and graduate students. It can also serve as a reference in the diverse selected areas of applied mathematics, modelling, and computational sciences, and is ideal for interdisciplinary collaborations.
Progressive Conversion from B-rep to BSP for Streaming Geometric Modeling.
Bajaj, Chandrajit; Paoluzzi, Alberto; Scorzelli, Giorgio
2006-01-01
We introduce a novel progressive approach to generate a Binary Space Partition (BSP) tree and a convex cell decomposition for any input triangles boundary representation (B-rep), by utilizing a fast calculation of the surface inertia. We also generate a solid model at progressive levels of detail. This approach relies on a variation of standard BSP tree generation, allowing for labeling cells as in, out and fuzzy, and which permits a comprehensive representation of a solid as the Hasse diagram of a cell complex. Our new algorithm is embedded in a streaming computational framework, using four types of dataflow processes that continuously produce, transform, combine or consume subsets of cells depending on their number or input/output stream. A varied collection of geometric modeling techniques are integrated in this streaming framework, including polygonal, spline, solid and heterogeneous modeling with boundary and decompositive representations, Boolean set operations, Cartesian products and adaptive refinement. The real-time B-rep to BSP streaming results we report in this paper are a large step forward in the ultimate unification of rapid conceptual and detailed shape design methodologies.
Linear and nonlinear stability analysis in BWRs applying a reduced order model
Energy Technology Data Exchange (ETDEWEB)
Olvera G, O. A.; Espinosa P, G.; Prieto G, A., E-mail: omar_olverag@hotmail.com [Universidad Autonoma Metropolitana, Unidad Iztapalapa, San Rafael Atlixco No. 186, Col. Vicentina, 09340 Ciudad de Mexico (Mexico)
2016-09-15
Boiling Water Reactor (BWR) stability studies are generally conducted through nonlinear reduced order models (Rom) employing various techniques such as bifurcation analysis and time domain numerical integration. One of those models used for these studies is the March-Leuba Rom. Such model represents qualitatively the dynamic behavior of a BWR through a one-point reactor kinetics, a one node representation of the heat transfer process in fuel, and a two node representation of the channel Thermal hydraulics to account for the void reactivity feedback. Here, we study the effect of this higher order model on the overall stability of the BWR. The change in the stability boundaries is determined by evaluating the eigenvalues of the Jacobian matrix. The nonlinear model is also integrated numerically to show that in the nonlinear region, the system evolves to stable limit cycles when operating close to the stability boundary. We also applied a new technique based on the Empirical Mode Decomposition (Emd) to estimate a parameter linked with stability in a BWR. This instability parameter is not exactly the classical Decay Ratio (Dr), but it will be linked with it. The proposed method allows decomposing the analyzed signal in different levels or mono-component functions known as intrinsic mode functions (Imf). One or more of these different modes can be associated to the instability problem in BWRs. By tracking the instantaneous frequencies (calculated through Hilbert Huang Transform (HHT) and the autocorrelation function (Acf) of the Imf linked to instability. The estimation of the proposed parameter can be achieved. The current methodology was validated with simulated signals of the studied model. (Author)
Fear Extinction as a Model for Translational Neuroscience: Ten Years of Progress
Milad, Mohammed R.; Quirk, Gregory J.
2016-01-01
The psychology of extinction has been studied for decades. Approximately 10 years ago, however, there began a concerted effort to understand the neural circuits of extinction of fear conditioning, in both animals and humans. Progress during this period has been facilitated by an unusual degree of coordination between rodent and human researchers examining fear extinction. This successful research program could serve as a model for translational research in other areas of behavioral neuroscience. Here we review the major advances and highlight new approaches to understanding and exploiting fear extinction. PMID:22129456
Greenwald, Holly S; Friedman, Erica B; Osman, Iman
2012-02-01
The classification of melanoma subtypes into prognostically relevant and therapeutically insightful categories has been a challenge since the first description of melanoma in the 1800s. One limitation has been the assumption that the two most common histological subtypes of melanoma, superficial spreading and nodular, evolve according to a linear model of progression, as malignant melanocytes spread radially and then invade vertically. However, recent clinical, pathological, and molecular data indicate that these two histological subtypes might evolve as distinct entities. Here, we review the published data that support distinct molecular characterization of superficial spreading and nodular melanoma, the clinical significance of this distinction including prognostic relevance and the therapeutic implications.
A comparative study of two prediction models for brain tumor progression
Zhou, Deqi; Tran, Loc; Wang, Jihong; Li, Jiang
2015-03-01
MR diffusion tensor imaging (DTI) technique together with traditional T1 or T2 weighted MRI scans supplies rich information sources for brain cancer diagnoses. These images form large-scale, high-dimensional data sets. Due to the fact that significant correlations exist among these images, we assume low-dimensional geometry data structures (manifolds) are embedded in the high-dimensional space. Those manifolds might be hidden from radiologists because it is challenging for human experts to interpret high-dimensional data. Identification of the manifold is a critical step for successfully analyzing multimodal MR images. We have developed various manifold learning algorithms (Tran et al. 2011; Tran et al. 2013) for medical image analysis. This paper presents a comparative study of an incremental manifold learning scheme (Tran. et al. 2013) versus the deep learning model (Hinton et al. 2006) in the application of brain tumor progression prediction. The incremental manifold learning is a variant of manifold learning algorithm to handle large-scale datasets in which a representative subset of original data is sampled first to construct a manifold skeleton and remaining data points are then inserted into the skeleton by following their local geometry. The incremental manifold learning algorithm aims at mitigating the computational burden associated with traditional manifold learning methods for large-scale datasets. Deep learning is a recently developed multilayer perceptron model that has achieved start-of-the-art performances in many applications. A recent technique named "Dropout" can further boost the deep model by preventing weight coadaptation to avoid over-fitting (Hinton et al. 2012). We applied the two models on multiple MRI scans from four brain tumor patients to predict tumor progression and compared the performances of the two models in terms of average prediction accuracy, sensitivity, specificity and precision. The quantitative performance metrics were
International Nuclear Information System (INIS)
Lee, R.R.; Ketelle, R.H.; Bownds, J.M.; Rizk, T.A.
1989-09-01
A groundwater flow and contaminant transport model calibration was performed to evaluate the ability of a typical, verified computer code to simulate groundwater tracer migration in the shallow aquifer of the Conasauga Group. Previously, standard practice site data interpretation and groundwater modeling resulted in inaccurate simulations of contaminant transport direction and rate compared with tracer migration behavior. The site's complex geology, the presence of flow in both fractured and weathered zones, and the transient character of flow in the shallow aquifer combined to render inaccurate assumptions of steady-state, homogeneous groundwater flow. The improvement of previous modeling results required iterative phases of conceptual model development, hypothesis testing, site field investigations, and modeling. The activities focused on generating a model grid that was compatible with site hydrogeologic conditions and on establishing boundary conditions based on site data. An annual average water table configuration derived from site data and fixed head boundary conditions was used as input for flow modeling. The contaminant transport model was combined with the data-driven flow model to obtain a preliminary contaminant plume. Calibration of the transport code was achieved by comparison with site tracer migration and concentration data. This study documents the influence of fractures and the transient character of flow and transport in the shallow aquifer. Although compatible with porous medium theory, site data demonstrate that the tracer migration pathway would not be anticipated using conventional porous medium analysis. 126 figs., 22 refs., 5 tabs
Relaxation approximations to second-order traffic flow models by high-resolution schemes
International Nuclear Information System (INIS)
Nikolos, I.K.; Delis, A.I.; Papageorgiou, M.
2015-01-01
A relaxation-type approximation of second-order non-equilibrium traffic models, written in conservation or balance law form, is considered. Using the relaxation approximation, the nonlinear equations are transformed to a semi-linear diagonilizable problem with linear characteristic variables and stiff source terms with the attractive feature that neither Riemann solvers nor characteristic decompositions are in need. In particular, it is only necessary to provide the flux and source term functions and an estimate of the characteristic speeds. To discretize the resulting relaxation system, high-resolution reconstructions in space are considered. Emphasis is given on a fifth-order WENO scheme and its performance. The computations reported demonstrate the simplicity and versatility of relaxation schemes as numerical solvers
Relaxation approximations to second-order traffic flow models by high-resolution schemes
Energy Technology Data Exchange (ETDEWEB)
Nikolos, I.K.; Delis, A.I.; Papageorgiou, M. [School of Production Engineering and Management, Technical University of Crete, University Campus, Chania 73100, Crete (Greece)
2015-03-10
A relaxation-type approximation of second-order non-equilibrium traffic models, written in conservation or balance law form, is considered. Using the relaxation approximation, the nonlinear equations are transformed to a semi-linear diagonilizable problem with linear characteristic variables and stiff source terms with the attractive feature that neither Riemann solvers nor characteristic decompositions are in need. In particular, it is only necessary to provide the flux and source term functions and an estimate of the characteristic speeds. To discretize the resulting relaxation system, high-resolution reconstructions in space are considered. Emphasis is given on a fifth-order WENO scheme and its performance. The computations reported demonstrate the simplicity and versatility of relaxation schemes as numerical solvers.