Stanley, Leanne M.; Edwards, Michael C.
2016-01-01
The purpose of this article is to highlight the distinction between the reliability of test scores and the fit of psychometric measurement models, reminding readers why it is important to consider both when evaluating whether test scores are valid for a proposed interpretation and/or use. It is often the case that an investigator judges both the…
Classification rates: non‐parametric verses parametric models using ...
African Journals Online (AJOL)
This research sought to establish if non parametric modeling achieves a higher correct classification ratio than a parametric model. The local likelihood technique was used to model fit the data sets. The same sets of data were modeled using parametric logit and the abilities of the two models to correctly predict the binary ...
Induced subgraph searching for geometric model fitting
Xiao, Fan; Xiao, Guobao; Yan, Yan; Wang, Xing; Wang, Hanzi
2017-11-01
In this paper, we propose a novel model fitting method based on graphs to fit and segment multiple-structure data. In the graph constructed on data, each model instance is represented as an induced subgraph. Following the idea of pursuing the maximum consensus, the multiple geometric model fitting problem is formulated as searching for a set of induced subgraphs including the maximum union set of vertices. After the generation and refinement of the induced subgraphs that represent the model hypotheses, the searching process is conducted on the "qualified" subgraphs. Multiple model instances can be simultaneously estimated by solving a converted problem. Then, we introduce the energy evaluation function to determine the number of model instances in data. The proposed method is able to effectively estimate the number and the parameters of model instances in data severely corrupted by outliers and noises. Experimental results on synthetic data and real images validate the favorable performance of the proposed method compared with several state-of-the-art fitting methods.
Contrast Gain Control Model Fits Masking Data
Watson, Andrew B.; Solomon, Joshua A.; Null, Cynthia H. (Technical Monitor)
1994-01-01
We studied the fit of a contrast gain control model to data of Foley (JOSA 1994), consisting of thresholds for a Gabor patch masked by gratings of various orientations, or by compounds of two orientations. Our general model includes models of Foley and Teo & Heeger (IEEE 1994). Our specific model used a bank of Gabor filters with octave bandwidths at 8 orientations. Excitatory and inhibitory nonlinearities were power functions with exponents of 2.4 and 2. Inhibitory pooling was broad in orientation, but narrow in spatial frequency and space. Minkowski pooling used an exponent of 4. All of the data for observer KMF were well fit by the model. We have developed a contrast gain control model that fits masking data. Unlike Foley's, our model accepts images as inputs. Unlike Teo & Heeger's, our model did not require multiple channels for different dynamic ranges.
A Model Fit Statistic for Generalized Partial Credit Model
Liang, Tie; Wells, Craig S.
2009-01-01
Investigating the fit of a parametric model is an important part of the measurement process when implementing item response theory (IRT), but research examining it is limited. A general nonparametric approach for detecting model misfit, introduced by J. Douglas and A. S. Cohen (2001), has exhibited promising results for the two-parameter logistic…
Parametric and Non-Parametric System Modelling
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg
1999-01-01
the focus is on combinations of parametric and non-parametric methods of regression. This combination can be in terms of additive models where e.g. one or more non-parametric term is added to a linear regression model. It can also be in terms of conditional parametric models where the coefficients...... considered. It is shown that adaptive estimation in conditional parametric models can be performed by combining the well known methods of local polynomial regression and recursive least squares with exponential forgetting. The approach used for estimation in conditional parametric models also highlights how...... networks is included. In this paper, neural networks are used for predicting the electricity production of a wind farm. The results are compared with results obtained using an adaptively estimated ARX-model. Finally, two papers on stochastic differential equations are included. In the first paper, among...
The global electroweak Standard Model fit after the Higgs discovery
Baak, Max
2013-01-01
We present an update of the global Standard Model (SM) fit to electroweak precision data under the assumption that the new particle discovered at the LHC is the SM Higgs boson. In this scenario all parameters entering the calculations of electroweak precision observalbes are known, allowing, for the first time, to over-constrain the SM at the electroweak scale and assert its validity. Within the SM the W boson mass and the effective weak mixing angle can be accurately predicted from the global fit. The results are compatible with, and exceed in precision, the direct measurements. An updated determination of the S, T and U parameters, which parametrize the oblique vacuum corrections, is given. The obtained values show good consistency with the SM expectation and no direct signs of new physics are seen. We conclude with an outlook to the global electroweak fit for a future e+e- collider.
Correcting Model Fit Criteria for Small Sample Latent Growth Models with Incomplete Data
McNeish, Daniel; Harring, Jeffrey R.
2017-01-01
To date, small sample problems with latent growth models (LGMs) have not received the amount of attention in the literature as related mixed-effect models (MEMs). Although many models can be interchangeably framed as a LGM or a MEM, LGMs uniquely provide criteria to assess global data-model fit. However, previous studies have demonstrated poor…
Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite
International Nuclear Information System (INIS)
Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.
2007-01-01
The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5
Parametric Explosion Spectral Model
Energy Technology Data Exchange (ETDEWEB)
Ford, S R; Walter, W R
2012-01-19
Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. Explosion spectra can be fit with similar spectral models whose parameters are then correlated with near-source geology and containment conditions. We observe a correlation of high gas-porosity (low-strength) with increased spectral slope. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.
Automated Model Fit Method for Diesel Engine Control Development
Seykens, X.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.
2014-01-01
This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is
Automated model fit method for diesel engine control development
Seykens, X.L.J.; Willems, F.P.T.; Kuijpers, B.; Rietjens, C.J.H.
2014-01-01
This paper presents an automated fit for a control-oriented physics-based diesel engine combustion model. This method is based on the combination of a dedicated measurement procedure and structured approach to fit the required combustion model parameters. Only a data set is required that is
Design of spatial experiments: Model fitting and prediction
Energy Technology Data Exchange (ETDEWEB)
Fedorov, V.V.
1996-03-01
The main objective of the paper is to describe and develop model oriented methods and algorithms for the design of spatial experiments. Unlike many other publications in this area, the approach proposed here is essentially based on the ideas of convex design theory.
Rapid world modeling: Fitting range data to geometric primitives
International Nuclear Information System (INIS)
Feddema, J.; Little, C.
1996-01-01
For the past seven years, Sandia National Laboratories has been active in the development of robotic systems to help remediate DOE's waste sites and decommissioned facilities. Some of these facilities have high levels of radioactivity which prevent manual clean-up. Tele-operated and autonomous robotic systems have been envisioned as the only suitable means of removing the radioactive elements. World modeling is defined as the process of creating a numerical geometric model of a real world environment or workspace. This model is often used in robotics to plan robot motions which perform a task while avoiding obstacles. In many applications where the world model does not exist ahead of time, structured lighting, laser range finders, and even acoustical sensors have been used to create three dimensional maps of the environment. These maps consist of thousands of range points which are difficult to handle and interpret. This paper presents a least squares technique for fitting range data to planar and quadric surfaces, including cylinders and ellipsoids. Once fit to these primitive surfaces, the amount of data associated with a surface is greatly reduced up to three orders of magnitude, thus allowing for more rapid handling and analysis of world data
Reducing uncertainty based on model fitness: Application to a ...
African Journals Online (AJOL)
A weakness of global sensitivity and uncertainty analysis methodologies is the often subjective definition of prior parameter probability distributions, especially ... The reservoir representing the central part of the wetland, where flood waters separate into several independent distributaries, is a keystone area within the model.
Standard error propagation in R-matrix model fitting for light elements
International Nuclear Information System (INIS)
Chen Zhenpeng; Zhang Rui; Sun Yeying; Liu Tingjin
2003-01-01
The error propagation features with R-matrix model fitting 7 Li, 11 B and 17 O systems were researched systematically. Some laws of error propagation were revealed, an empirical formula P j = U j c / U j d = K j · S-bar · √m / √N for describing standard error propagation was established, the most likely error ranges for standard cross sections of 6 Li(n,t), 10 B(n,α0) and 10 B(n,α1) were estimated. The problem that the standard error of light nuclei standard cross sections may be too small results mainly from the R-matrix model fitting, which is not perfect. Yet R-matrix model fitting is the most reliable evaluation method for such data. The error propagation features of R-matrix model fitting for compound nucleus system of 7 Li, 11 B and 17 O has been studied systematically, some laws of error propagation are revealed, and these findings are important in solving the problem mentioned above. Furthermore, these conclusions are suitable for similar model fitting in other scientific fields. (author)
The issue of statistical power for overall model fit in evaluating structural equation models
Directory of Open Access Journals (Sweden)
Richard HERMIDA
2015-06-01
Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.
Efficient occupancy model-fitting for extensive citizen-science data
Morgan, Byron J. T.; Freeman, Stephen N.; Ridout, Martin S.; Brereton, Tom M.; Fox, Richard; Powney, Gary D.; Roy, David B.
2017-01-01
Appropriate large-scale citizen-science data present important new opportunities for biodiversity modelling, due in part to the wide spatial coverage of information. Recently proposed occupancy modelling approaches naturally incorporate random effects in order to account for annual variation in the composition of sites surveyed. In turn this leads to Bayesian analysis and model fitting, which are typically extremely time consuming. Motivated by presence-only records of occurrence from the UK Butterflies for the New Millennium data base, we present an alternative approach, in which site variation is described in a standard way through logistic regression on relevant environmental covariates. This allows efficient occupancy model-fitting using classical inference, which is easily achieved using standard computers. This is especially important when models need to be fitted each year, typically for many different species, as with British butterflies for example. Using both real and simulated data we demonstrate that the two approaches, with and without random effects, can result in similar conclusions regarding trends. There are many advantages to classical model-fitting, including the ability to compare a range of alternative models, identify appropriate covariates and assess model fit, using standard tools of maximum likelihood. In addition, modelling in terms of covariates provides opportunities for understanding the ecological processes that are in operation. We show that there is even greater potential; the classical approach allows us to construct regional indices simply, which indicate how changes in occupancy typically vary over a species’ range. In addition we are also able to construct dynamic occupancy maps, which provide a novel, modern tool for examining temporal changes in species distribution. These new developments may be applied to a wide range of taxa, and are valuable at a time of climate change. They also have the potential to motivate citizen
Shavit Grievink, Liat; Penny, David; Hendy, Michael D; Holland, Barbara R
2010-05-01
Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction.
Irvine, Michael A; Hollingsworth, T Déirdre
2018-05-26
Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Clark, D Angus; Bowles, Ryan P
2018-04-23
In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.
PARAMETRIC MODEL OF LUMBAR VERTEBRA
Directory of Open Access Journals (Sweden)
CAPPETTI Nicola
2010-11-01
Full Text Available The present work proposes the realization of a parametric/variational CAD model of a normotype lumbar vertebra, which could be used for improving the effectiveness of actual imaging techniques in informational augmentation of the orthopaedic and traumatological diagnosis. In addition it could be used for ergonomic static and dynamical analysis of the lumbar region and vertebral column.
Interactive Dimensioning of Parametric Models
Kelly, T.
2015-06-22
We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.
Development and design of a late-model fitness test instrument based on LabView
Xie, Ying; Wu, Feiqing
2010-12-01
Undergraduates are pioneers of China's modernization program and undertake the historic mission of rejuvenating our nation in the 21st century, whose physical fitness is vital. A smart fitness test system can well help them understand their fitness and health conditions, thus they can choose more suitable approaches and make practical plans for exercising according to their own situation. following the future trends, a Late-model fitness test Instrument based on LabView has been designed to remedy defects of today's instruments. The system hardware consists of fives types of sensors with their peripheral circuits, an acquisition card of NI USB-6251 and a computer, while the system software, on the basis of LabView, includes modules of user register, data acquisition, data process and display, and data storage. The system, featured by modularization and an open structure, is able to be revised according to actual needs. Tests results have verified the system's stability and reliability.
Levy flights and self-similar exploratory behaviour of termite workers: beyond model fitting.
Directory of Open Access Journals (Sweden)
Octavio Miramontes
Full Text Available Animal movements have been related to optimal foraging strategies where self-similar trajectories are central. Most of the experimental studies done so far have focused mainly on fitting statistical models to data in order to test for movement patterns described by power-laws. Here we show by analyzing over half a million movement displacements that isolated termite workers actually exhibit a range of very interesting dynamical properties--including Lévy flights--in their exploratory behaviour. Going beyond the current trend of statistical model fitting alone, our study analyses anomalous diffusion and structure functions to estimate values of the scaling exponents describing displacement statistics. We evince the fractal nature of the movement patterns and show how the scaling exponents describing termite space exploration intriguingly comply with mathematical relations found in the physics of transport phenomena. By doing this, we rescue a rich variety of physical and biological phenomenology that can be potentially important and meaningful for the study of complex animal behavior and, in particular, for the study of how patterns of exploratory behaviour of individual social insects may impact not only their feeding demands but also nestmate encounter patterns and, hence, their dynamics at the social scale.
Ranger, Jochen; Kuhn, Jörg-Tobias; Szardenings, Carsten
2017-05-01
Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey (Econometrica, 53, 1985, 1047) and Tauchen (J. Econometrics, 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica, 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q-diffusion model and the D-diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M 2 test (Molenaar et al., J. Stat. Softw., 66, 2015, 1), the moment test (Ranger et al., Br. J. Math. Stat. Psychol., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. , 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions. © 2017 The British Psychological Society.
A History of Regression and Related Model-Fitting in the Earth Sciences (1636?-2000)
International Nuclear Information System (INIS)
Howarth, Richard J.
2001-01-01
The (statistical) modeling of the behavior of a dependent variate as a function of one or more predictors provides examples of model-fitting which span the development of the earth sciences from the 17th Century to the present. The historical development of these methods and their subsequent application is reviewed. Bond's predictions (c. 1636 and 1668) of change in the magnetic declination at London may be the earliest attempt to fit such models to geophysical data. Following publication of Newton's theory of gravitation in 1726, analysis of data on the length of a 1 o meridian arc, and the length of a pendulum beating seconds, as a function of sin 2 (latitude), was used to determine the ellipticity of the oblate spheroid defining the Figure of the Earth. The pioneering computational methods of Mayer in 1750, Boscovich in 1755, and Lambert in 1765, and the subsequent independent discoveries of the principle of least squares by Gauss in 1799, Legendre in 1805, and Adrain in 1808, and its later substantiation on the basis of probability theory by Gauss in 1809 were all applied to the analysis of such geodetic and geophysical data. Notable later applications include: the geomagnetic survey of Ireland by Lloyd, Sabine, and Ross in 1836, Gauss's model of the terrestrial magnetic field in 1838, and Airy's 1845 analysis of the residuals from a fit to pendulum lengths, from which he recognized the anomalous character of measurements of gravitational force which had been made on islands. In the early 20th Century applications to geological topics proliferated, but the computational burden effectively held back applications of multivariate analysis. Following World War II, the arrival of digital computers in universities in the 1950s facilitated computation, and fitting linear or polynomial models as a function of geographic coordinates, trend surface analysis, became popular during the 1950-60s. The inception of geostatistics in France at this time by Matheron had its
Matthew P. Adams; Catherine J. Collier; Sven Uthicke; Yan X. Ow; Lucas Langlois; Katherine R. O’Brien
2017-01-01
When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluat...
Adams, Matthew P; Collier, Catherine J; Uthicke, Sven; Ow, Yan X; Langlois, Lucas; O'Brien, Katherine R
2017-01-04
When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (T opt ) for maximum photosynthetic rate (P max ). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.
Adams, Matthew P.; Collier, Catherine J.; Uthicke, Sven; Ow, Yan X.; Langlois, Lucas; O'Brien, Katherine R.
2017-01-01
When several models can describe a biological process, the equation that best fits the data is typically considered the best. However, models are most useful when they also possess biologically-meaningful parameters. In particular, model parameters should be stable, physically interpretable, and transferable to other contexts, e.g. for direct indication of system state, or usage in other model types. As an example of implementing these recommended requirements for model parameters, we evaluated twelve published empirical models for temperature-dependent tropical seagrass photosynthesis, based on two criteria: (1) goodness of fit, and (2) how easily biologically-meaningful parameters can be obtained. All models were formulated in terms of parameters characterising the thermal optimum (Topt) for maximum photosynthetic rate (Pmax). These parameters indicate the upper thermal limits of seagrass photosynthetic capacity, and hence can be used to assess the vulnerability of seagrass to temperature change. Our study exemplifies an approach to model selection which optimises the usefulness of empirical models for both modellers and ecologists alike.
Log-normal frailty models fitted as Poisson generalized linear mixed models.
Hirsch, Katharina; Wienke, Andreas; Kuss, Oliver
2016-12-01
The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known since decades. As shown in recent studies, this equivalence carries over to clustered survival data: A frailty model with a log-normal frailty term can be interpreted and estimated as a generalized linear mixed model with a binary response, a Poisson likelihood, and a specific offset. Proceeding this way, statistical theory and software for generalized linear mixed models are readily available for fitting frailty models. This gain in flexibility comes at the small price of (1) having to fix the number of pieces for the baseline hazard in advance and (2) having to "explode" the data set by the number of pieces. In this paper we extend the simulations of former studies by using a more realistic baseline hazard (Gompertz) and by comparing the model under consideration with competing models. Furthermore, the SAS macro %PCFrailty is introduced to apply the Poisson generalized linear mixed approach to frailty models. The simulations show good results for the shared frailty model. Our new %PCFrailty macro provides proper estimates, especially in case of 4 events per piece. The suggested Poisson generalized linear mixed approach for log-normal frailty models based on the %PCFrailty macro provides several advantages in the analysis of clustered survival data with respect to more flexible modelling of fixed and random effects, exact (in the sense of non-approximate) maximum likelihood estimation, and standard errors and different types of confidence intervals for all variance parameters. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Model Fitting for Predicted Precipitation in Darwin: Some Issues with Model Choice
Farmer, Jim
2010-01-01
In Volume 23(2) of the "Australian Senior Mathematics Journal," Boncek and Harden present an exercise in fitting a Markov chain model to rainfall data for Darwin Airport (Boncek & Harden, 2009). Days are subdivided into those with precipitation and precipitation-free days. The author abbreviates these labels to wet days and dry days.…
Optimal parametric modelling of measured short waves
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
the importance of selecting a suitable sampling interval for better estimates of parametric modelling and also for better statistical representation. Implementation of the above algorithms in a structural monitoring system has the potential advantage of storing...
McNeish, Daniel; Hancock, Gregory R
2018-03-01
Lance, Beck, Fan, and Carter (2016) recently advanced 6 new fit indices and associated cutoff values for assessing data-model fit in the structural portion of traditional latent variable path models. The authors appropriately argued that, although most researchers' theoretical interest rests with the latent structure, they still rely on indices of global model fit that simultaneously assess both the measurement and structural portions of the model. As such, Lance et al. proposed indices intended to assess the structural portion of the model in isolation of the measurement model. Unfortunately, although these strategies separate the assessment of the structure from the fit of the measurement model, they do not isolate the structure's assessment from the quality of the measurement model. That is, even with a perfectly fitting measurement model, poorer quality (i.e., less reliable) measurements will yield a more favorable verdict regarding structural fit, whereas better quality (i.e., more reliable) measurements will yield a less favorable structural assessment. This phenomenon, referred to by Hancock and Mueller (2011) as the reliability paradox, affects not only traditional global fit indices but also those structural indices proposed by Lance et al. as well. Fortunately, as this comment will clarify, indices proposed by Hancock and Mueller help to mitigate this problem and allow the structural portion of the model to be assessed independently of both the fit of the measurement model as well as the quality of indicator variables contained therein. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Linear Parametric Model Checking of Timed Automata
DEFF Research Database (Denmark)
Hune, Tohmas Seidelin; Romijn, Judi; Stoelinga, Mariëlle
2001-01-01
We present an extension of the model checker Uppaal capable of synthesize linear parameter constraints for the correctness of parametric timed automata. The symbolic representation of the (parametric) state-space is shown to be correct. A second contribution of this paper is the identication...... of a subclass of parametric timed automata (L/U automata), for which the emptiness problem is decidable, contrary to the full class where it is know to be undecidable. Also we present a number of lemmas enabling the verication eort to be reduced for L/U automata in some cases. We illustrate our approach...
Directory of Open Access Journals (Sweden)
Mónica A Silva
Full Text Available Argos recently implemented a new algorithm to calculate locations of satellite-tracked animals that uses a Kalman filter (KF. The KF algorithm is reported to increase the number and accuracy of estimated positions over the traditional Least Squares (LS algorithm, with potential advantages to the application of state-space methods to model animal movement data. We tested the performance of two Bayesian state-space models (SSMs fitted to satellite tracking data processed with KF algorithm. Tracks from 7 harbour seals (Phoca vitulina tagged with ARGOS satellite transmitters equipped with Fastloc GPS loggers were used to calculate the error of locations estimated from SSMs fitted to KF and LS data, by comparing those to "true" GPS locations. Data on 6 fin whales (Balaenoptera physalus were used to investigate consistency in movement parameters, location and behavioural states estimated by switching state-space models (SSSM fitted to data derived from KF and LS methods. The model fit to KF locations improved the accuracy of seal trips by 27% over the LS model. 82% of locations predicted from the KF model and 73% of locations from the LS model were <5 km from the corresponding interpolated GPS position. Uncertainty in KF model estimates (5.6 ± 5.6 km was nearly half that of LS estimates (11.6 ± 8.4 km. Accuracy of KF and LS modelled locations was sensitive to precision but not to observation frequency or temporal resolution of raw Argos data. On average, 88% of whale locations estimated by KF models fell within the 95% probability ellipse of paired locations from LS models. Precision of KF locations for whales was generally higher. Whales' behavioural mode inferred by KF models matched the classification from LS models in 94% of the cases. State-space models fit to KF data can improve spatial accuracy of location estimates over LS models and produce equally reliable behavioural estimates.
Parametric structural modeling of insect wings
International Nuclear Information System (INIS)
Mengesha, T E; Vallance, R R; Barraja, M; Mittal, R
2009-01-01
Insects produce thrust and lift forces via coupled fluid-structure interactions that bend and twist their compliant wings during flapping cycles. Insight into this fluid-structure interaction is achieved with numerical modeling techniques such as coupled finite element analysis and computational fluid dynamics, but these methods require accurate and validated structural models of insect wings. Structural models of insect wings depend principally on the shape, dimensions and material properties of the veins and membrane cells. This paper describes a method for parametric modeling of wing geometry using digital images and demonstrates the use of the geometric models in constructing three-dimensional finite element (FE) models and simple reduced-order models. The FE models are more complete and accurate than previously reported models since they accurately represent the topology of the vein network, as well as the shape and dimensions of the veins and membrane cells. The methods are demonstrated by developing a parametric structural model of a cicada forewing.
UK energy policy ambition and UK energy modelling-fit for purpose?
International Nuclear Information System (INIS)
Strachan, Neil
2011-01-01
Aiming to lead amongst other G20 countries, the UK government has classified the twin energy policy priorities of decarbonisation and security of supply as a 'centennial challenge'. This viewpoint discusses the UK's capacity for energy modelling and scenario building as a critical underpinning of iterative decision making to meet these policy ambitions. From a nadir, over the last decade UK modelling expertise has been steadily built up. However extreme challenges remain in the level and consistency of funding of core model teams - critical to ensure a full scope of energy model types and hence insights, and in developing new state-of-the-art models to address evolving uncertainties. Meeting this challenge will facilitate a broad scope of types and geographical scale of UK's analytical tools to responsively deliver the evidence base for a range of public and private sector decision makers, and ensure that the UK contributes to global efforts to advance the field of energy-economic modelling. - Research highlights: → Energy modelling capacity is a critical underpinning for iterative energy policy making. → Full scope of energy models and analytical approaches is required. → Extreme challenges remain in consistent and sustainable funding of energy modelling teams. → National governments that lead in global energy policy also need to invest in modelling capacity.
Assessing model fit in latent class analysis when asymptotics do not hold
van Kollenburg, Geert H.; Mulder, Joris; Vermunt, Jeroen K.
2015-01-01
The application of latent class (LC) analysis involves evaluating the LC model using goodness-of-fit statistics. To assess the misfit of a specified model, say with the Pearson chi-squared statistic, a p-value can be obtained using an asymptotic reference distribution. However, asymptotic p-values
Probabilistic Reachability for Parametric Markov Models
DEFF Research Database (Denmark)
Hahn, Ernst Moritz; Hermanns, Holger; Zhang, Lijun
2011-01-01
Given a parametric Markov model, we consider the problem of computing the rational function expressing the probability of reaching a given set of states. To attack this principal problem, Daws has suggested to first convert the Markov chain into a finite automaton, from which a regular expression...
Using geometry to improve model fitting and experiment design for glacial isostasy
Kachuck, S. B.; Cathles, L. M.
2017-12-01
As scientists we routinely deal with models, which are geometric objects at their core - the manifestation of a set of parameters as predictions for comparison with observations. When the number of observations exceeds the number of parameters, the model is a hypersurface (the model manifold) in the space of all possible predictions. The object of parameter fitting is to find the parameters corresponding to the point on the model manifold as close to the vector of observations as possible. But the geometry of the model manifold can make this difficult. By curving, ending abruptly (where, for instance, parameters go to zero or infinity), and by stretching and compressing the parameters together in unexpected directions, it can be difficult to design algorithms that efficiently adjust the parameters. Even at the optimal point on the model manifold, parameters might not be individually resolved well enough to be applied to new contexts. In our context of glacial isostatic adjustment, models of sparse surface observations have a broad spread of sensitivity to mixtures of the earth's viscous structure and the surface distribution of ice over the last glacial cycle. This impedes precise statements about crucial geophysical processes, such as the planet's thermal history or the climates that controlled the ice age. We employ geometric methods developed in the field of systems biology to improve the efficiency of fitting (geodesic accelerated Levenberg-Marquardt) and to identify the maximally informative sources of additional data to make better predictions of sea levels and ice configurations (optimal experiment design). We demonstrate this in particular in reconstructions of the Barents Sea Ice Sheet, where we show that only certain kinds of data from the central Barents have the power to distinguish between proposed models.
Multiple organ definition in CT using a Bayesian approach for 3D model fitting
Boes, Jennifer L.; Weymouth, Terry E.; Meyer, Charles R.
1995-08-01
Organ definition in computed tomography (CT) is of interest for treatment planning and response monitoring. We present a method for organ definition using a priori information about shape encoded in a set of biometric organ models--specifically for the liver and kidney-- that accurately represents patient population shape information. Each model is generated by averaging surfaces from a learning set of organ shapes previously registered into a standard space defined by a small set of landmarks. The model is placed in a specific patient's data set by identifying these landmarks and using them as the basis for model deformation; this preliminary representation is then iteratively fit to the patient's data based on a Bayesian formulation of the model's priors and CT edge information, yielding a complete organ surface. We demonstrate this technique using a set of fifteen abdominal CT data sets for liver surface definition both before and after the addition of a kidney model to the fitting; we demonstrate the effectiveness of this tool for organ surface definition in this low-contrast domain.
A turbulent mixing Reynolds stress model fitted to match linear interaction analysis predictions
International Nuclear Information System (INIS)
Griffond, J; Soulard, O; Souffland, D
2010-01-01
To predict the evolution of turbulent mixing zones developing in shock tube experiments with different gases, a turbulence model must be able to reliably evaluate the production due to the shock-turbulence interaction. In the limit of homogeneous weak turbulence, 'linear interaction analysis' (LIA) can be applied. This theory relies on Kovasznay's decomposition and allows the computation of waves transmitted or produced at the shock front. With assumptions about the composition of the upstream turbulent mixture, one can connect the second-order moments downstream from the shock front to those upstream through a transfer matrix, depending on shock strength. The purpose of this work is to provide a turbulence model that matches LIA results for the shock-turbulent mixture interaction. Reynolds stress models (RSMs) with additional equations for the density-velocity correlation and the density variance are considered here. The turbulent states upstream and downstream from the shock front calculated with these models can also be related through a transfer matrix, provided that the numerical implementation is based on a pseudo-pressure formulation. Then, the RSM should be modified in such a way that its transfer matrix matches the LIA one. Using the pseudo-pressure to introduce ad hoc production terms, we are able to obtain a close agreement between LIA and RSM matrices for any shock strength and thus improve the capabilities of the RSM.
Efficient parallel implementation of active appearance model fitting algorithm on GPU.
Wang, Jinwei; Ma, Xirong; Zhu, Yuanping; Sun, Jizhou
2014-01-01
The active appearance model (AAM) is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs) that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia's GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.
Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU
Directory of Open Access Journals (Sweden)
Jinwei Wang
2014-01-01
Full Text Available The active appearance model (AAM is one of the most powerful model-based object detecting and tracking methods which has been widely used in various situations. However, the high-dimensional texture representation causes very time-consuming computations, which makes the AAM difficult to apply to real-time systems. The emergence of modern graphics processing units (GPUs that feature a many-core, fine-grained parallel architecture provides new and promising solutions to overcome the computational challenge. In this paper, we propose an efficient parallel implementation of the AAM fitting algorithm on GPUs. Our design idea is fine grain parallelism in which we distribute the texture data of the AAM, in pixels, to thousands of parallel GPU threads for processing, which makes the algorithm fit better into the GPU architecture. We implement our algorithm using the compute unified device architecture (CUDA on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. To compare the performance of our algorithm with different data sizes, we built sixteen face AAM models of different dimensional textures. The experiment results show that our parallel AAM fitting algorithm can achieve real-time performance for videos even on very high-dimensional textures.
Does Vocational Education Model fit to Fulfil Prisoners’ Needs Based on Gender?
Hayzaki, S. H.; Nurhaeni, I. D. A.
2018-02-01
Men and women have different needs, based on their gender or the socio-cultural construction. The government has issued a policy about accelerating the equivalence of gender since 2012 through responsive planning and budgeting. With the policy, every institution (including the institutions under the ministry of law and human rights) must integrate its gender perspective on planning and budgeting, then it can fulfill the different needs between men and women. One of the programs developed in prisons for prisoners is vocational education and technology for preparing the prisoners’ life after being released from the prison cells. This article was made for evaluating the vocational education and training given to the prisoners. Gender perspective is employed as the analyzing tool. The result was then used as the basis of formulating vocational education model integrating gender perspective. The research was conducted at the Prison of Demak Regency, Indonesia. The method used in the research is qualitative descriptive with data collection techniques using by in-depth interviews, observation and documentation. The data analysis uses statistic description of Harvard’s checklist category model and combined with Moser category model. The result shows that vocational education and training given have not considered the differences between men and women. As a result, the prisoners were still not able to understand their different needs which can cause gender injustice when they come into job market. It is suggested that gender perspective must be included as a teaching material in the vocational education and training.
Temperature dependence of bulk respiration of crop stands. Measurement and model fitting
International Nuclear Information System (INIS)
Tani, Takashi; Arai, Ryuji; Tako, Yasuhiro
2007-01-01
The objective of the present study was to examine whether the temperature dependence of respiration at a crop-stand scale could be directly represented by an Arrhenius function that was widely used for representing the temperature dependence of leaf respiration. We determined temperature dependences of bulk respiration of monospecific stands of rice and soybean within a range of the air temperature from 15 to 30degC using large closed chambers. Measured responses of respiration rates of the two stands were well fitted by the Arrhenius function (R 2 =0.99). In the existing model to assess the local radiological impact of the anthropogenic carbon-14, effects of the physical environmental factors on photosynthesis and respiration of crop stands are not taken into account for the calculation of the net amount of carbon per cultivation area in crops at harvest which is the crucial parameter for the estimation of the activity concentration of carbon-14 in crops. Our result indicates that the Arrhenius function is useful for incorporating the effect of the temperature on respiration of crop stands into the model which is expected to contribute to a more realistic estimate of the activity concentration of carbon-14 in crops. (author)
Model reduction of parametrized systems
Ohlberger, Mario; Patera, Anthony; Rozza, Gianluigi; Urban, Karsten
2017-01-01
The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems. The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor t, carried out over the last 12 years, to build a growing research community in this field. Though not a textbook, some of the chapters ca...
Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting
Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.
2016-01-01
Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048
Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.
Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L
2017-02-01
Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.
The conceptual basis of mathematics in cardiology IV: statistics and model fitting.
Bates, Jason H T; Sobel, Burton E
2003-06-01
This is the fourth in a series of four articles developed for the readers of Coronary Artery Disease. Without language ideas cannot be articulated. What may not be so immediately obvious is that they cannot be formulated either. One of the essential languages of cardiology is mathematics. Unfortunately, medical education does not emphasize, and in fact, often neglects empowering physicians to think mathematically. Reference to statistics, conditional probability, multicompartmental modeling, algebra, calculus and transforms is common but often without provision of genuine conceptual understanding. At the University of Vermont College of Medicine, Professor Bates developed a course designed to address these deficiencies. The course covered mathematical principles pertinent to clinical cardiovascular and pulmonary medicine and research. It focused on fundamental concepts to facilitate formulation and grasp of ideas. This series of four articles was developed to make the material available for a wider audience. The articles will be published sequentially in Coronary Artery Disease. Beginning with fundamental axioms and basic algebraic manipulations they address algebra, function and graph theory, real and complex numbers, calculus and differential equations, mathematical modeling, linear system theory and integral transforms and statistical theory. The principles and concepts they address provide the foundation needed for in-depth study of any of these topics. Perhaps of even more importance, they should empower cardiologists and cardiovascular researchers to utilize the language of mathematics in assessing the phenomena of immediate pertinence to diagnosis, pathophysiology and therapeutics. The presentations are interposed with queries (by Coronary Artery Disease abbreviated as CAD) simulating the nature of interactions that occurred during the course itself. Each article concludes with one or more examples illustrating application of the concepts covered to
Efficient Constrained Local Model Fitting for Non-Rigid Face Alignment.
Lucey, Simon; Wang, Yang; Cox, Mark; Sridharan, Sridha; Cohn, Jeffery F
2009-11-01
Active appearance models (AAMs) have demonstrated great utility when being employed for non-rigid face alignment/tracking. The "simultaneous" algorithm for fitting an AAM achieves good non-rigid face registration performance, but has poor real time performance (2-3 fps). The "project-out" algorithm for fitting an AAM achieves faster than real time performance (> 200 fps) but suffers from poor generic alignment performance. In this paper we introduce an extension to a discriminative method for non-rigid face registration/tracking referred to as a constrained local model (CLM). Our proposed method is able to achieve superior performance to the "simultaneous" AAM algorithm along with real time fitting speeds (35 fps). We improve upon the canonical CLM formulation, to gain this performance, in a number of ways by employing: (i) linear SVMs as patch-experts, (ii) a simplified optimization criteria, and (iii) a composite rather than additive warp update step. Most notably, our simplified optimization criteria for fitting the CLM divides the problem of finding a single complex registration/warp displacement into that of finding N simple warp displacements. From these N simple warp displacements, a single complex warp displacement is estimated using a weighted least-squares constraint. Another major advantage of this simplified optimization lends from its ability to be parallelized, a step which we also theoretically explore in this paper. We refer to our approach for fitting the CLM as the "exhaustive local search" (ELS) algorithm. Experiments were conducted on the CMU Multi-PIE database.
Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting
Energy Technology Data Exchange (ETDEWEB)
Ross, James C., E-mail: jross@bwh.harvard.edu [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States); Kindlmann, Gordon L. [Computer Science Department and Computation Institute, University of Chicago, Chicago, Illinois 60637 (United States); Okajima, Yuka; Hatabu, Hiroto [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Díaz, Alejandro A. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 and Department of Pulmonary Diseases, Pontificia Universidad Católica de Chile, Santiago (Chile); Silverman, Edwin K. [Channing Laboratory, Brigham and Women' s Hospital, Boston, Massachusetts 02215 and Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Washko, George R. [Pulmonary and Critical Care Division, Brigham and Women' s Hospital and Harvard Medical School, Boston, Massachusetts 02215 (United States); Dy, Jennifer [ECE Department, Northeastern University, Boston, Massachusetts 02115 (United States); Estépar, Raúl San José [Department of Radiology, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Surgical Planning Lab, Brigham and Women' s Hospital, Boston, Massachusetts 02215 (United States); Laboratory of Mathematics in Imaging, Brigham and Women' s Hospital, Boston, Massachusetts 02126 (United States)
2013-12-15
Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The
Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting
International Nuclear Information System (INIS)
Ross, James C.; Kindlmann, Gordon L.; Okajima, Yuka; Hatabu, Hiroto; Díaz, Alejandro A.; Silverman, Edwin K.; Washko, George R.; Dy, Jennifer; Estépar, Raúl San José
2013-01-01
Purpose: Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. Methods: The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. Results: The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. Conclusions: The proposed
Energy Technology Data Exchange (ETDEWEB)
Kondratenko, I.; Jablonska, B. [ECN , Petten (Netherlands)
2009-11-15
There is growing justification and political commitment in Europe to tackle energy efficiency in new and existing buildings, both residential and non-residential. It requires shifting the construction sector towards large scale successful implementation of innovative energy efficient and sustainable building concepts. Nowadays, a number of innovative building concepts exist, to name a few: Very Low Energy, Passive House, Zero-Energy, Zero-Emission, Energy Producing, etc. However, the experience in the Netherlands has shown inflexibility in the behaviour within the traditional building process to allow the necessary changes for large scale introduction of innovative integral building concepts. This has led to examining the question: 'How well does the building process organisation model in the Netherlands allow the implementation of innovative housing building concepts?' Answering this question requires specific knowledge of the behaviour of the traditional building process, its characteristics, advantages and disadvantages, phases and actors involved. It also demanded to focus on the nature of barriers within, and on possibilities to overcome identified bottlenecks. Also, examined was the suitability of several selected novel concepts in their opportunities for adapting the building process organisation model and the behaviour of actors within, such as: The Life Cycle Analysis, (including the Whole Building Life Cycle Costing and the Least Life Cycle Costing), The Cradle to Cradle (C2C) Concept, The Living Building Concept and Private Initiatives. This also included recent experiences with building projects implementing these concepts in the Netherlands. In summary, there are a number of challenges. The traditional building process in the Netherlands is fragmented in nature into successive phases with a strict way of cooperation and division of tasks and responsibilities between actors. There is also a cost / risk approach preventing enabling long
Energy Technology Data Exchange (ETDEWEB)
Reed, S.L.; et al.
2017-01-17
We present the discovery and spectroscopic confirmation with the ESO NTT and Gemini South telescopes of eight new 6.0 < z < 6.5 quasars with z$_{AB}$ < 21.0. These quasars were photometrically selected without any star-galaxy morphological criteria from 1533 deg$^{2}$ using SED model fitting to photometric data from the Dark Energy Survey (g, r, i, z, Y), the VISTA Hemisphere Survey (J, H, K) and the Wide-Field Infrared Survey Explorer (W1, W2). The photometric data was fitted with a grid of quasar model SEDs with redshift dependent Lyman-{\\alpha} forest absorption and a range of intrinsic reddening as well as a series of low mass cool star models. Candidates were ranked using on a SED-model based $\\chi^{2}$-statistic, which is extendable to other future imaging surveys (e.g. LSST, Euclid). Our spectral confirmation success rate is 100% without the need for follow-up photometric observations as used in other studies of this type. Combined with automatic removal of the main types of non-astrophysical contaminants the method allows large data sets to be processed without human intervention and without being over run by spurious false candidates. We also present a robust parametric redshift estimating technique that gives comparable accuracy to MgII and CO based redshift estimators. We find two z $\\sim$ 6.2 quasars with HII near zone sizes < 3 proper Mpc which could indicate that these quasars may be young with ages < 10$^6$ - 10$^7$ years or lie in over dense regions of the IGM. The z = 6.5 quasar VDESJ0224-4711 has J$_{AB}$ = 19.75 is the second most luminous quasar known with z > 6.5.
International Nuclear Information System (INIS)
Reed, S. L.; McMahon, R. G.; Martini, P.; Banerji, M.; Auger, M.
2017-01-01
Here, we present the discovery and spectroscopic confirmation with the European Southern Observatory New Technology Telescope (NTT) and Gemini South telescopes of eight new, and the rediscovery of two previously known, 6.0 < z < 6.5 quasars with zAB < 21.0. These quasars were photometrically selected without any morphological criteria from 1533 deg2 using spectral energy distribution (SED) model fitting to photometric data from Dark Energy Survey (g, r, i, z, Y), VISTA Hemisphere Survey (J, H, K) and Wide-field Infrared Survey Explorer (W1, W2). The photometric data were fitted with a grid of quasar model SEDs with redshift-dependent Ly α forest absorption and a range of intrinsic reddening as well as a series of low-mass cool star models. Candidates were ranked using an SED-model-based χ2-statistic, which is extendable to other future imaging surveys (e.g. LSST and Euclid). Our spectral confirmation success rate is 100 per cent without the need for follow-up photometric observations as used in other studies of this type. Combined with automatic removal of the main types of non-astrophysical contaminants, the method allows large data sets to be processed without human intervention and without being overrun by spurious false candidates. We also present a robust parametric redshift estimator that gives comparable accuracy to Mg ii and CO-based redshift estimators. We find two z ~6.2 quasars with H ii near zone sizes ≤3 proper Mpc that could indicate that these quasars may be young with ages ≲ 10 6 -10 7 years or lie in over dense regions of the IGM. The z = 6.5 quasar VDES J0224–4711 has JAB = 19.75 and is the second most luminous quasar known with z ≥ 6.5.
Parametric Cost Models for Space Telescopes
Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtney
2010-01-01
Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.
Parametric cost models for space telescopes
Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtnay
2017-11-01
Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.
Ground-Based Telescope Parametric Cost Model
Stahl, H. Philip; Rowell, Ginger Holmes
2004-01-01
A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.
Hyperbolic and semi-parametric models in finance
Bingham, N. H.; Kiesel, Rüdiger
2001-02-01
The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.
International Nuclear Information System (INIS)
Hameeteman, K; Niessen, W J; Klein, S; Van 't Klooster, R; Selwaness, M; Van der Lugt, A; Witteman, J C M
2013-01-01
We present a method for carotid vessel wall volume quantification from magnetic resonance imaging (MRI). The method combines lumen and outer wall segmentation based on deformable model fitting with a learning-based segmentation correction step. After selecting two initialization points, the vessel wall volume in a region around the bifurcation is automatically determined. The method was trained on eight datasets (16 carotids) from a population-based study in the elderly for which one observer manually annotated both the lumen and outer wall. An evaluation was carried out on a separate set of 19 datasets (38 carotids) from the same study for which two observers made annotations. Wall volume and normalized wall index measurements resulting from the manual annotations were compared to the automatic measurements. Our experiments show that the automatic method performs comparably to the manual measurements. All image data and annotations used in this study together with the measurements are made available through the website http://ergocar.bigr.nl. (paper)
Semi-parametric estimation for ARCH models
Directory of Open Access Journals (Sweden)
Raed Alzghool
2018-03-01
Full Text Available In this paper, we conduct semi-parametric estimation for autoregressive conditional heteroscedasticity (ARCH model with Quasi likelihood (QL and Asymptotic Quasi-likelihood (AQL estimation methods. The QL approach relaxes the distributional assumptions of ARCH processes. The AQL technique is obtained from the QL method when the process conditional variance is unknown. We present an application of the methods to a daily exchange rate series. Keywords: ARCH model, Quasi likelihood (QL, Asymptotic Quasi-likelihood (AQL, Martingale difference, Kernel estimator
Parametric uncertainty in optical image modeling
Potzick, James; Marx, Egon; Davidson, Mark
2006-10-01
Optical photomask feature metrology and wafer exposure process simulation both rely on optical image modeling for accurate results. While it is fair to question the accuracies of the available models, model results also depend on several input parameters describing the object and imaging system. Errors in these parameter values can lead to significant errors in the modeled image. These parameters include wavelength, illumination and objective NA's, magnification, focus, etc. for the optical system, and topography, complex index of refraction n and k, etc. for the object. In this paper each input parameter is varied over a range about its nominal value and the corresponding images simulated. Second order parameter interactions are not explored. Using the scenario of the optical measurement of photomask features, these parametric sensitivities are quantified by calculating the apparent change of the measured linewidth for a small change in the relevant parameter. Then, using reasonable values for the estimated uncertainties of these parameters, the parametric linewidth uncertainties can be calculated and combined to give a lower limit to the linewidth measurement uncertainty for those parameter uncertainties.
Parametric uncertainty modeling for robust control
DEFF Research Database (Denmark)
Rasmussen, K.H.; Jørgensen, Sten Bay
1999-01-01
The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...... point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure...
Lepping, R. P.; Wu, C.-C.; Berdichevsky, D. B.; Szabo, A.
2018-04-01
We give the results of parameter fitting of the magnetic clouds (MCs) observed by the Wind spacecraft for the three-year period 2013 to the end of 2015 (called the "Present" period) using the MC model of Lepping, Jones, and Burlaga ( J. Geophys. Res. 95, 11957, 1990). The Present period is almost coincident with the solar maximum of the sunspot number, which has a broad peak starting in about 2012 and extending to almost 2015. There were 49 MCs identified in the Present period. The modeling gives MC quantities such as size, axial attitude, field handedness, axial magnetic-field strength, center time, and closest-approach vector. Derived quantities are also estimated, such as axial magnetic flux, axial current density, and total axial current. Quality estimates are assigned representing excellent, fair/good, and poor. We provide error estimates on the specific fit parameters for the individual MCs, where the poor cases are excluded. Model-fitting results that are based on the Present period are compared to the results of the full Wind mission from 1995 to the end of 2015 (Long-term period), and compared to the results of two other recent studies that encompassed the periods 2007 - 2009 and 2010 - 2012, inclusive. We see that during the Present period, the MCs are, on average, slightly slower, slightly weaker in axial magnetic field (by 8.7%), and larger in diameter (by 6.5%) than those in the Long-term period. However, in most respects, the MCs in the Present period are significantly closer in characteristics to those of the Long-term period than to those of the two recent three-year periods. However, the rate of occurrence of MCs for the Long-term period is 10.3 year^{-1}, whereas this rate for the Present period is 16.3 year^{-1}, similar to that of the period 2010 - 2012. Hence, the MC occurrence rate has increased appreciably in the last six years. MC Type (N-S, S-N, All N, All S, etc.) is assigned to each MC; there is an inordinately large percentage of All S
Nonscaling parametrization of hadronic spectra and dual parton model
International Nuclear Information System (INIS)
Gaponenko, O.N.
2001-01-01
Using the popular Wdowczyk-Wolfendale parametrization (WW-parametrization) as an example one studies restrictions imposed by a dual parton model for different nonscaling parametrizations of the pulsed hadron spectra in soft hadron-hadron and hadron-nuclear interactions. One derived a new parametrization free from basic drawback of the WW-formulae. In the central range the determined parametrization show agreement with the Wdowczyk-Wolfendale formula, but in contrast to the last-named one it does not result in contradiction with the experiment due to fast reduction of inelastic factor reduction with energy increase [ru
Parametric Cost and Schedule Modeling for Early Technology Development
2018-04-02
Research NoteNational Security Rep rt PARAMETRIC MODELING FOR EARLY TECHNOLOGY DEVELOPMENT COST AND SCHEDULE Chuck...Alexander NSR_11x17_Cover_CostModeling_v8.indd 1 11/20/17 3:15 PM PARAMETRIC COST AND SCHEDULE MODELING FOR EARLY TECHNOLOGY DEVELOPMENT Chuck...COST AND SCHEDULE MODELING FOR EARLY TECHNOLOGY DEVELOPMENT iii Contents Figures
Parametric Analysis of Flexible Logic Control Model
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Lihua Fu
2013-01-01
Full Text Available Based on deep analysis about the essential relation between two input variables of normal two-dimensional fuzzy controller, we used universal combinatorial operation model to describe the logic relationship and gave a flexible logic control method to realize the effective control for complex system. In practical control application, how to determine the general correlation coefficient of flexible logic control model is a problem for further studies. First, the conventional universal combinatorial operation model has been limited in the interval [0,1]. Consequently, this paper studies a kind of universal combinatorial operation model based on the interval [a,b]. And some important theorems are given and proved, which provide a foundation for the flexible logic control method. For dealing reasonably with the complex relations of every factor in complex system, a kind of universal combinatorial operation model with unequal weights is put forward. Then, this paper has carried out the parametric analysis of flexible logic control model. And some research results have been given, which have important directive to determine the values of the general correlation coefficients in practical control application.
Testing Parametric versus Semiparametric Modelling in Generalized Linear Models
Härdle, W.K.; Mammen, E.; Müller, M.D.
1996-01-01
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e.
International Nuclear Information System (INIS)
Pronyaev, V.G.
2003-01-01
The information entropy is taken as a measure of knowledge about the object and the reduced univariante variance as a common measure of uncertainty. Covariances in the model versus non-model least square fits are discussed
Mixing parametrizations for ocean climate modelling
Gusev, Anatoly; Moshonkin, Sergey; Diansky, Nikolay; Zalesny, Vladimir
2016-04-01
The algorithm is presented of splitting the total evolutionary equations for the turbulence kinetic energy (TKE) and turbulence dissipation frequency (TDF), which is used to parameterize the viscosity and diffusion coefficients in ocean circulation models. The turbulence model equations are split into the stages of transport-diffusion and generation-dissipation. For the generation-dissipation stage, the following schemes are implemented: the explicit-implicit numerical scheme, analytical solution and the asymptotic behavior of the analytical solutions. The experiments were performed with different mixing parameterizations for the modelling of Arctic and the Atlantic climate decadal variability with the eddy-permitting circulation model INMOM (Institute of Numerical Mathematics Ocean Model) using vertical grid refinement in the zone of fully developed turbulence. The proposed model with the split equations for turbulence characteristics is similar to the contemporary differential turbulence models, concerning the physical formulations. At the same time, its algorithm has high enough computational efficiency. Parameterizations with using the split turbulence model make it possible to obtain more adequate structure of temperature and salinity at decadal timescales, compared to the simpler Pacanowski-Philander (PP) turbulence parameterization. Parameterizations with using analytical solution or numerical scheme at the generation-dissipation step of the turbulence model leads to better representation of ocean climate than the faster parameterization using the asymptotic behavior of the analytical solution. At the same time, the computational efficiency left almost unchanged relative to the simple PP parameterization. Usage of PP parametrization in the circulation model leads to realistic simulation of density and circulation with violation of T,S-relationships. This error is majorly avoided with using the proposed parameterizations containing the split turbulence model
Reike, Dennis; Schwarz, Wolf
2016-01-01
The time required to determine the larger of 2 digits decreases with their numerical distance, and, for a given distance, increases with their magnitude (Moyer & Landauer, 1967). One detailed quantitative framework to account for these effects is provided by random walk models. These chronometric models describe how number-related noisy…
Fast, Sequence Adaptive Parcellation of Brain MR Using Parametric Models
DEFF Research Database (Denmark)
Puonti, Oula; Iglesias, Juan Eugenio; Van Leemput, Koen
2013-01-01
In this paper we propose a method for whole brain parcellation using the type of generative parametric models typically used in tissue classification. Compared to the non-parametric, multi-atlas segmentation techniques that have become popular in recent years, our method obtains state-of-the-art ...
Energy Technology Data Exchange (ETDEWEB)
Smith, D.L.; Guenther, P.T.
1983-11-01
We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references.
International Nuclear Information System (INIS)
Smith, D.L.; Guenther, P.T.
1983-11-01
We suggest a procedure for estimating uncertainties in neutron cross sections calculated with a nuclear model descriptive of a specific mass region. It applies standard error propagation techniques, using a model-parameter covariance matrix. Generally, available codes do not generate covariance information in conjunction with their fitting algorithms. Therefore, we resort to estimating a relative covariance matrix a posteriori from a statistical examination of the scatter of elemental parameter values about the regional representation. We numerically demonstrate our method by considering an optical-statistical model analysis of a body of total and elastic scattering data for the light fission-fragment mass region. In this example, strong uncertainty correlations emerge and they conspire to reduce estimated errors to some 50% of those obtained from a naive uncorrelated summation in quadrature. 37 references
Worthington, Thomas A.; Zhang, T.; Logue, Daniel R.; Mittelstet, Aaron R.; Brewer, Shannon K.
2016-01-01
Truncated distributions of pelagophilic fishes have been observed across the Great Plains of North America, with water use and landscape fragmentation implicated as contributing factors. Developing conservation strategies for these species is hindered by the existence of multiple competing flow regime hypotheses related to species persistence. Our primary study objective was to compare the predicted distributions of one pelagophil, the Arkansas River Shiner Notropis girardi, constructed using different flow regime metrics. Further, we investigated different approaches for improving temporal transferability of the species distribution model (SDM). We compared four hypotheses: mean annual flow (a baseline), the 75th percentile of daily flow, the number of zero-flow days, and the number of days above 55th percentile flows, to examine the relative importance of flows during the spawning period. Building on an earlier SDM, we added covariates that quantified wells in each catchment, point source discharges, and non-native species presence to a structured variable framework. We assessed the effects on model transferability and fit by reducing multicollinearity using Spearman’s rank correlations, variance inflation factors, and principal component analysis, as well as altering the regularization coefficient (β) within MaxEnt. The 75th percentile of daily flow was the most important flow metric related to structuring the species distribution. The number of wells and point source discharges were also highly ranked. At the default level of β, model transferability was improved using all methods to reduce collinearity; however, at higher levels of β, the correlation method performed best. Using β = 5 provided the best model transferability, while retaining the majority of variables that contributed 95% to the model. This study provides a workflow for improving model transferability and also presents water-management options that may be considered to improve the
Sakamoto, Toshihiro
2018-04-01
Crop phenological information is a critical variable in evaluating the influence of environmental stress on the final crop yield in spatio-temporal dimensions. Although the MODIS (Moderate Resolution Imaging Spectroradiometer) Land Cover Dynamics product (MCD12Q2) is widely used in place of crop phenological information, the definitions of MCD12Q2-derived phenological events (e.g. green-up date, dormancy date) were not completely consistent with those of crop development stages used in statistical surveys (e.g. emerged date, harvested date). It has been necessary to devise an alternative method focused on detecting continental-scale crop developmental stages using a different approach. Therefore, this study aimed to refine the Shape Model Fitting (SMF) method to improve its applicability to multiple major U.S. crops. The newly-refined SMF methods could estimate the timing of 36 crop-development stages of major U.S. crops, including corn, soybeans, winter wheat, spring wheat, barley, sorghum, rice, and cotton. The newly-developed calibration process did not require any long-term field observation data, and could calibrate crop-specific phenological parameters, which were used as coefficients in estimated equation, by using only freely accessible public data. The calibration of phenological parameters was conducted in two steps. In the first step, the national common phenological parameters, referred to as X0[base], were calibrated by using the statistical data of 2008. The SMF method coupled using X0[base] was named the rSMF[base] method. The second step was a further calibration to gain regionally-adjusted phenological parameters for each state, referred to as X0[local], by using additional statistical data of 2015 and 2016. The rSMF method using the X0[local] was named the rSMF[local] method. This second calibration process improved the estimation accuracy for all tested crops. When applying the rSMF[base] method to the validation data set (2009-2014), the root
Directory of Open Access Journals (Sweden)
Lemieux Sébastien
2006-08-01
Full Text Available Abstract Background The identification of differentially expressed genes (DEGs from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication. Results On a wholly defined dataset, the PL-LM method was able to identify 75% of the differentially expressed genes within 10% of false positives. This accuracy was achieved both using the three replicates per conditions available in the dataset and using only one replicate per condition. Conclusion The method achieves, on this dataset, a higher accuracy than the best set of tools identified by the authors of the dataset, and does so using only one replicate per condition.
Elghafghuf, Adel; Dufour, Simon; Reyher, Kristen; Dohoo, Ian; Stryhn, Henrik
2014-12-01
Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format - leading to larger datasets - thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation
International Nuclear Information System (INIS)
Syrmalenios, Panayotis
1973-01-01
This research thesis addresses the issue of safety of fast neutron reactors, and more particularly is a contribution of the study of mechanisms of interaction between molten fuel and sodium. It aims at developing tools of prediction of consequences of three main types of accidents: local fusion of a fuel rod and contact of the fuel with the surrounding sodium, failure of an assembly due to the fusion of several rods and fuel-coolant interaction within the assembly, and fuel-coolant interaction at the level of the reactor core. The author first proposes a bibliographical analysis of experimental and theoretical studies related to this issue of interaction between a hot body and a cold liquid, and of its consequences. Then, he introduces a mathematical model and its resolution method, and reports the use of the associated code (Corfou) for the interpretation of experimental results: expulsion of cold sodium column by expansion of an overheated sodium mass, fusion of a rod by Joule effect, interaction between UO_2 molten by high frequency with liquid sodium. Finally, the author discusses a comparison between the Corfou code and other models which are being currently developed [fr
Model Adaptation in Parametric Space for POD-Galerkin Models
Gao, Haotian; Wei, Mingjun
2017-11-01
The development of low-order POD-Galerkin models is largely motivated by the expectation to use the model developed with a set of parameters at their native values to predict the dynamic behaviors of the same system under different parametric values, in other words, a successful model adaptation in parametric space. However, most of time, even small deviation of parameters from their original value may lead to large deviation or unstable results. It has been shown that adding more information (e.g. a steady state, mean value of a different unsteady state, or an entire different set of POD modes) may improve the prediction of flow with other parametric states. For a simple case of the flow passing a fixed cylinder, an orthogonal mean mode at a different Reynolds number may stabilize the POD-Galerkin model when Reynolds number is changed. For a more complicated case of the flow passing an oscillatory cylinder, a global POD-Galerkin model is first applied to handle the moving boundaries, then more information (e.g. more POD modes) is required to predicate the flow under different oscillatory frequencies. Supported by ARL.
Cai, Li
2015-06-01
Lord and Wingersky's (Appl Psychol Meas 8:453-461, 1984) recursive algorithm for creating summed score based likelihoods and posteriors has a proven track record in unidimensional item response theory (IRT) applications. Extending the recursive algorithm to handle multidimensionality is relatively simple, especially with fixed quadrature because the recursions can be defined on a grid formed by direct products of quadrature points. However, the increase in computational burden remains exponential in the number of dimensions, making the implementation of the recursive algorithm cumbersome for truly high-dimensional models. In this paper, a dimension reduction method that is specific to the Lord-Wingersky recursions is developed. This method can take advantage of the restrictions implied by hierarchical item factor models, e.g., the bifactor model, the testlet model, or the two-tier model, such that a version of the Lord-Wingersky recursive algorithm can operate on a dramatically reduced set of quadrature points. For instance, in a bifactor model, the dimension of integration is always equal to 2, regardless of the number of factors. The new algorithm not only provides an effective mechanism to produce summed score to IRT scaled score translation tables properly adjusted for residual dependence, but leads to new applications in test scoring, linking, and model fit checking as well. Simulated and empirical examples are used to illustrate the new applications.
Magnetorheological fluid dampers: a review of parametric modelling
International Nuclear Information System (INIS)
Wang, D H; Liao, W H
2011-01-01
Due to the inherent nonlinear nature of magnetorheological (MR) dampers, one of the challenging aspects for developing and utilizing these devices to achieve high performance is the development of models that can accurately describe their unique characteristics. In this review, the characteristics of MR dampers are summarized according to the measured responses under different conditions. On these bases, the considerations and methods of the parametric dynamic modelling for MR dampers are given and the state-of-the-art parametric dynamic modelling, identification and validation techniques for MR dampers are reviewed. In the past two decades, the models for MR dampers have been focused on how to improve the modelling accuracy. Although the force–displacement behaviour is well represented by most of the proposed dynamic models for MR dampers, no simple parametric models with high accuracy for MR dampers can be found. In addition, the parametric dynamic models for MR dampers with on-line updating ability and the inverse parametric models for MR dampers are scarcely explored. Moreover, whether one dynamic model for MR dampers can portray the force–displacement and force–velocity behaviour is not only determined by the dynamic model itself but also determined by the identification method. (topical review)
Incident Duration Modeling Using Flexible Parametric Hazard-Based Models
Directory of Open Access Journals (Sweden)
Ruimin Li
2014-01-01
Full Text Available Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers. This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model. Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008. Results show that different factors significantly affect different incident time phases, whose best distributions were diverse. Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents. The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time.
Incorporating parametric uncertainty into population viability analysis models
McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.
2011-01-01
Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.
Bosone, Lucia; Martinez, Frédéric; Kalampalikis, Nikos
2015-04-01
In health-promotional campaigns, positive and negative role models can be deployed to illustrate the benefits or costs of certain behaviors. The main purpose of this article is to investigate why, how, and when exposure to role models strengthens the persuasiveness of a message, according to regulatory fit theory. We argue that exposure to a positive versus a negative model activates individuals' goals toward promotion rather than prevention. By means of two experiments, we demonstrate that high levels of persuasion occur when a message advertising healthy dietary habits offers a regulatory fit between its framing and the described role model. Our data also establish that the effects of such internal regulatory fit by vicarious experience depend on individuals' perceptions of response-efficacy and self-efficacy. Our findings constitute a significant theoretical complement to previous research on regulatory fit and contain valuable practical implications for health-promotional campaigns. © 2015 by the Society for Personality and Social Psychology, Inc.
Sun, Xiangqing; Elston, Robert C; Barnholtz-Sloan, Jill S; Falk, Gary W; Grady, William M; Faulx, Ashley; Mittal, Sumeet K; Canto, Marcia; Shaheen, Nicholas J; Wang, Jean S; Iyer, Prasad G; Abrams, Julian A; Tian, Ye D; Willis, Joseph E; Guda, Kishore; Markowitz, Sanford D; Chandar, Apoorva; Warfe, James M; Brock, Wendy; Chak, Amitabh
2016-05-01
Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727-35. ©2016 AACR. ©2016 American Association for
Directory of Open Access Journals (Sweden)
Wakhid Slamet Ciptono
2011-02-01
Full Text Available This study purposively is to conduct an empirical analysis of the structural relations among critical factors of quality management practices (QMPs, world-class company practice (WCC, operational excellence practice (OE, and company performance (company non-financial performance or CNFP and company financial performance or CFP in the oil and gas companies operating in Indonesia. The current study additionally examines the relationships between QMPs and CFP through WCC, OE, and CNFP (as partial mediators simultaneously. The study uses data from a survey of 140 strategic business units (SBUs within 49 oil and gas contractor companies in Indonesia. The findings suggest that all six QMPs have positive and significant indirect relationships on CFP through WCC and CNFP. Only four of six QMPs have positive and significant indirect relationships on CFP through OE and CNFP. Hence, WCC, OE, and CNFP play as partial mediators between QMPs and CFP. CNFP has a significant influence on CFP. A major implication of this study is that oil and gas managers need to recognize the structural relations model fit by developing all of the research constructs simultaneously associated with a comprehensive TQM practice. Furthermore, the findings will assist oil and gas companies by improving CNFP, which is very critical to TQM, thereby contributing to a better achievement of CFP. The current study uses the Deming’s principles, Hayes and Wheelwright dimensions of world-class company practice, Chevron Texaco’s operational excellence practice, and the dimensions of company financial and non-financial performances. The paper also provides an insight into the sustainability of TQM implementation model and their effect on company financial performance in oil and gas companies in Indonesia.
Housing price prediction: parametric versus semi-parametric spatial hedonic models
Montero, José-María; Mínguez, Román; Fernández-Avilés, Gema
2018-01-01
House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.
Brian J. Clough; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Philip J. Radtke
2016-01-01
tEstimation of live tree biomass is an important task for both forest carbon accounting and studies of nutri-ent dynamics in forest ecosystems. In this study, we took advantage of an extensive felled-tree database(with 2885 foliage biomass observations) to compare different models and grouping schemes based onphylogenetic and geographic variation for predicting foliage...
Tay, Louis; Drasgow, Fritz
2012-01-01
Two Monte Carlo simulation studies investigated the effectiveness of the mean adjusted X[superscript 2]/df statistic proposed by Drasgow and colleagues and, because of problems with the method, a new approach for assessing the goodness of fit of an item response theory model was developed. It has been previously recommended that mean adjusted…
Green, Samuel B.; Thompson, Marilyn S.; Poirier, Jennifer
1999-01-01
The use of Lagrange multiplier (LM) tests in specification searches and the efforts that involve the addition of extraneous parameters to models are discussed. Presented are a rationale and strategy for conducting specification searches in two stages that involve adding parameters to LM tests to maximize fit and then deleting parameters not needed…
DEVELOPING PARAMETRIC BUILDING MODELS – THE GANDIS USE CASE
Directory of Open Access Journals (Sweden)
W. Thaller
2012-09-01
Full Text Available In the course of a project related to green building design, we have created a group of eight parametric building models that can be manipulated interactively with respect to dimensions, number of ﬂoors, and a few other parameters. We report on the commonalities and differences between the models and the abstractions that we were able to identify.
SEMIPARAMETRIC VERSUS PARAMETRIC CLASSIFICATION MODELS - AN APPLICATION TO DIRECT MARKETING
BULT, [No Value
In this paper we are concerned with estimation of a classification model using semiparametric and parametric methods. Benefits and limitations of semiparametric models in general, and of Manski's maximum score method in particular, are discussed. The maximum score method yields consistent estimates
Exchange of parametric bridge models using a neutral data format
Ji, Y.; Borrmann, André; Beetz, J.; Obergrießer, M.
2013-01-01
Parametric modeling is a well-established methodology in the field of mechanical engineering. It allows the creation of flexible geometric models using parameters for dimensions and makes it possible to define numeric relationships between these parameters by means of mathematical formulas and
Parametric, nonparametric and parametric modelling of a chaotic circuit time series
Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.
2000-09-01
The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.
Schipper, L. A.; Robinson, J.; O'Neill, T.; Ryburn, J.; Arcus, V. L.
2015-12-01
Developing robust models of the temperature response and sensitivity of soil respiration is critical for determining changes carbon cycling in response to climate change and at daily to annual time scales. Currently, approaches for measuring temperature dependence of soil respiration generally use long incubation times (days to weeks and months) at a limited number of incubation temperatures. Long incubation times likely allow thermal adaptation by the microbial population so that results are poorly representative of in situ soil responses. Additionally, too few incubation temperatures allows for the fit and justification of many different predictive equations, which can lead to inaccuracies when used for carbon budgeting purposes. We have developed a method to rapidly determine the response of soil respiration rate to wide range of temperatures. An aluminium block with 44 sample slots is heated at one end and cooled at the other to give a temperature gradient from 0 to 55°C at about one degree increments. Soil respiration is measured within 5 hours to minimise the possibility of thermal adaptation. We have used this method to demonstrate the similarity of temperature sensitivity of respiration for different soils from the same location across seasons. We are currently testing whether long-term (weeks to months) incubation alter temperature response and sensitivity that occurs in situ responses. This method is also well suited for determining the most appropriate models of temperature dependence and sensitivity of soil respiration (including macromolecular rate theory MMRT). With additional testing, this method is expected to be a more reliable method of measuring soil respiration rate for soil quality and modelling of soil carbon processes.
A CONTRASTIVE ANALYSIS OF THE FACTORIAL STRUCTURE OF THE PCL-R: WHICH MODEL FITS BEST THE DATA?
Directory of Open Access Journals (Sweden)
Beatriz Pérez
2015-01-01
Full Text Available The aim of this study was to determine which of the factorial solutions proposed for the Hare Psychopathy Checklist-Revised (PCL-R of two, three, four factors, and unidimensional fitted best the data. Two trained and experienced independent raters scored 197 prisoners from the Villabona Penitentiary (Asturias, Spain, age range 21 to 73 years (M = 36.0, SD = 9.7, of whom 60.12% were reoffenders and 73% had committed violent crimes. The results revealed that the two-factor correlational, three-factor hierarchical without testlets, four-factor correlational and hierarchical, and unidimensional models were a poor fit for the data (CFI ≤ .86, and the three-factor model with testlets was a reasonable fit for the data (CFI = .93. The scale resulting from the three-factor hierarchical model with testlets (13 items classified psychopathy significantly higher than the original 20-item scale. The results are discussed in terms of their implications for theoretical models of psychopathy, decision-making, prison classification and intervention, and prevention. Se diseñó un estudio con el objetivo de conocer cuál de las soluciones factoriales propuestas para la Hare Psychopathy Checklist-Revised (PCL-R de dos, tres y cuatro factores y unidimensional era la que presentaba mejor ajuste a los datos. Para ello, dos evaluadores entrenados y con experiencia evaluaron de forma independiente a 197 internos en la prisión Villabona (Asturias, España, con edades comprendidas entre los 21 y los 73 años (M = 36.0, DT = 9.7, de los cuales el 60.12% eran reincidentes y el 73% había cometido delitos violentos. Los resultados mostraron que los modelos unidimensional, correlacional de 2 factores, jerárquico de 3 factores sin testlest y correlacional y jerárquico de 4 factores, presentaban un pobre ajuste con los datos (CFI ≤ .86 y un ajuste razonable del modelo jerárquico de tres factores con testlets (CFI = .93. La escala resultante del modelo de tres factores
International Nuclear Information System (INIS)
Dorado Delgado, Jennifer; Burbano Criollo, Juan Carlos; Molina Tabares, Jose Manuel; Carvajal Escobar, Yesid; Aristizabal, Hector Fabio
2006-01-01
In this study, space and time variability of monthly and annual rainfall was analyzed for the downstream influence zone of a Colombian supply-regulation reservoir, Sara-Brut, located on the Cauca valley department. Monthly precipitation data from 18 gauge stations and for a 29-year record (1975-2003) were used. These data were processed by means of time series completion, consistency analyses and sample statistics computations. Theoretical probabilistic distribution models such as Gumbel, normal, lognormal and wake by, and other empirical distributions such as Weibull and Landwehr were applied in order to fit the historical precipitation data set. The fit standard error (FSE) was used to test the goodness of fit of the theoretical distribution models and to choose the best of this probabilistic function. The wake by approach showed the best goodness of fit in 89% of the total gauges taken into account. Time variability was analyzed by means of wake by estimated values of monthly and annual precipitation associated with return periods of 1,052, 1,25, 2, 10, 20 and 50 years. Precipitation space variability is presents by means of ArcGis v8.3 and using krigging as interpolation method. In general terms the results obtained from this study show significant distribution variability in precipitation over the whole area, and particularity, the formation of dry and humid nucleus over the northeastern strip and microclimates at the southwestern and central zone of the study area were observed, depending on the season of year. The mentioned distribution pattern is likely caused by the influence of pacific wind streams, which come from the Andean western mountain range. It is expected that the results from this work be helpful for future planning and hydrologic project design
Monitoring coastal marshes biomass with CASI: a comparison of parametric and non-parametric models
Mo, Y.; Kearney, M.
2017-12-01
Coastal marshes are important carbon sinks that face multiple natural and anthropogenic stresses. Optical remote sensing is a powerful tool for closely monitoring the biomass of coastal marshes. However, application of hyperspectral sensors on assessing the biomass of diverse coastal marsh ecosystems is limited. This study samples spectral and biophysical data from coastal freshwater, intermediate, brackish, and saline marshes in Louisiana, and develops parametric and non-parametric models for using the Compact Airborne Spectrographic Imager (CASI) to retrieve the marshes' biomass. Linear models and random forest models are developed from simulated CASI data (48 bands, 380-1050 nm, bandwidth 14 nm). Linear models are also developed using narrowband vegetation indices computed from all possible band combinations from the blue, red, and near infrared wavelengths. It is found that the linear models derived from the optimal narrowband vegetation indices provide strong predictions for the marshes' Leaf Area Index (LAI; R2 > 0.74 for ARVI), but not for their Aboveground Green Biomass (AGB; R2 > 0.25). The linear models derived from the simulated CASI data strongly predict the marshes' LAI (R2 = 0.93) and AGB (R2 = 0.71) and have 27 and 30 bands/variables in the final models through stepwise regression, respectively. The random forest models derived from the simulated CASI data also strongly predict the marshes' LAI and AGB (R2 = 0.91 and 0.84, respectively), where the most important variables for predicting LAI are near infrared bands at 784 and 756 nm and for predicting ABG are red bands at 684 and 670 nm. In sum, the random forest model is preferable for assessing coastal marsh biomass using CASI data as it offers high R2 for both LAI and AGB. The superior performance of the random forest model is likely to due to that it fully utilizes the full-spectrum data and makes no assumption of the approximate normality of the sampling population. This study offers solutions
Parametrization of contrails in a comprehensive climate model
Energy Technology Data Exchange (ETDEWEB)
Ponater, M; Brinkop, S; Sausen, R; Schumann, U [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere
1998-12-31
A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.
Parametrization of contrails in a comprehensive climate model
Energy Technology Data Exchange (ETDEWEB)
Ponater, M.; Brinkop, S.; Sausen, R.; Schumann, U. [Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt e.V., Oberpfaffenhofen (Germany). Inst. fuer Physik der Atmosphaere
1997-12-31
A contrail parametrization scheme for a general circulation model (GCM) is presented. Guidelines for its development were that it should be based on the thermodynamic theory of contrail formation and that it should be consistent with the cloud parametrization scheme of the GCM. Results of a six-year test integration indicate reasonable results concerning the spatial and temporal development of both contrail coverage and contrail optical properties. Hence, the scheme forms a promising basis for the quantitative estimation of the contrail climatic impact. (author) 9 refs.
Wind Farm parametrization in the mesoscale model WRF
DEFF Research Database (Denmark)
Volker, Patrick; Badger, Jake; Hahmann, Andrea N.
2012-01-01
, but are parametrized as another sub-grid scale process. In order to appropriately capture the wind farm wake recovery and its direction, two properties are important, among others, the total energy extracted by the wind farm and its velocity deficit distribution. In the considered parametrization the individual...... the extracted force is proportional to the turbine area interfacing a grid cell. The sub-grid scale wake expansion is achieved by adding turbulence kinetic energy (proportional to the extracted power) to the flow. The validity of both wind farm parametrizations has been verified against observational data. We...... turbines produce a thrust dependent on the background velocity. For the sub-grid scale velocity deficit, the entrainment from the free atmospheric flow into the wake region, which is responsible for the expansion, is taken into account. Furthermore, since the model horizontal distance is several times...
Two-parametric model of metals hardening during cold working
International Nuclear Information System (INIS)
Khajkin, B.E.
1985-01-01
Mathematical models of cold working metal resistance σ depending on deformation degree have been analyzed. Advantage of two-parametric formula combining simplicity with satisfactory accuracy of experimental data approximation is noted. The formula is convenient when determining value σ, which is average with respect of deformation location, as average geometric value
Bim and Gis: when Parametric Modeling Meets Geospatial Data
Barazzetti, L.; Banfi, F.
2017-12-01
Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building) scale to the infrastructure (where geospatial data cannot be neglected) has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by "pure" GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator) industry, as well as new solutions for parametric modelling with additional geoinformation.
BIM AND GIS: WHEN PARAMETRIC MODELING MEETS GEOSPATIAL DATA
Directory of Open Access Journals (Sweden)
L. Barazzetti
2017-12-01
Full Text Available Geospatial data have a crucial role in several projects related to infrastructures and land management. GIS software are able to perform advanced geospatial analyses, but they lack several instruments and tools for parametric modelling typically available in BIM. At the same time, BIM software designed for buildings have limited tools to handle geospatial data. As things stand at the moment, BIM and GIS could appear as complementary solutions, notwithstanding research work is currently under development to ensure a better level of interoperability, especially at the scale of the building. On the other hand, the transition from the local (building scale to the infrastructure (where geospatial data cannot be neglected has already demonstrated that parametric modelling integrated with geoinformation is a powerful tool to simplify and speed up some phases of the design workflow. This paper reviews such mixed approaches with both simulated and real examples, demonstrating that integration is already a reality at specific scales, which are not dominated by “pure” GIS or BIM. The paper will also demonstrate that some traditional operations carried out with GIS software are also available in parametric modelling software for BIM, such as transformation between reference systems, DEM generation, feature extraction, and geospatial queries. A real case study is illustrated and discussed to show the advantage of a combined use of both technologies. BIM and GIS integration can generate greater usage of geospatial data in the AECOO (Architecture, Engineering, Construction, Owner and Operator industry, as well as new solutions for parametric modelling with additional geoinformation.
Update on Parametric Cost Models for Space Telescopes
Stahl. H. Philip; Henrichs, Todd; Luedtke, Alexander; West, Miranda
2011-01-01
Since the June 2010 Astronomy Conference, an independent review of our cost data base discovered some inaccuracies and inconsistencies which can modify our previously reported results. This paper will review changes to the data base, our confidence in those changes and their effect on various parametric cost models
Parametric study of a thorium model
International Nuclear Information System (INIS)
Lourenco, M.C.; Lipztein, J.L.; Szwarcwald, C.L.
1997-01-01
Full text. Models for radionuclides distribution in the human body and dosimetry involve assumptions on the biokinetic behaviour of the material among compartments representing organs and tissues in the body. The lack of knowledge about the metabolic behaviour of a radionuclide represents a factor of uncertainty in estimates of committed dose equivalent. An important problem in biokinetic modeling is the correct assignment of transfer coefficients and biological half-lives to body compartments. The purpose of this study is to analyze the variability in the activities of the body compartments in relation to the variations in the transfer coefficients and compartments biological half-lives in a certain model. A thorium specific recycling model for continuous exposure was used. Multiple regression analysis methods were applied to analyze the results
Parametric modelling of nonstationary platform deck motions
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
with fast Fourier transform spectra and show good agreement. However, the higher order maximum entropy model can be used for better representation of nonstationary motions. This method also reduces long time series of nonstationary offshore data into a few...
Parametric study of a thorium model
International Nuclear Information System (INIS)
Lourenco, M.C.; Lipsztein, J.L.; Szwarcwald, C.L.
2002-01-01
Models for radionuclides distribution in the human body and dosimetry involve assumptions on the biokinetic behavior of the material among compartments representing organs and tissues in the body. One of the most important problem in biokinetic modeling is the assignment of transfer coefficients and biological half-lives to body compartments. In Brazil there are many areas of high natural radioactivity, where the population is chronically exposed to radionuclides of the thorium series. The uncertainties of the thorium biokinetic model are a major cause of uncertainty in the estimates of the committed dose equivalent of the population living in high background areas. The purpose of this study is to discuss the variability in the thorium activities accumulated in the body compartments in relation to the variations in the transfer coefficients and compartments biological half-lives of a thorium-recycling model for continuous exposure. Multiple regression analysis methods were applied to analyze the results. (author)
Parametric study for horizontal steam generator modelling
Energy Technology Data Exchange (ETDEWEB)
Ovtcharova, I. [Energoproekt, Sofia (Bulgaria)
1995-12-31
In the presentation some of the calculated results of horizontal steam generator PGV - 440 modelling with RELAP5/Mod3 are described. Two nodalization schemes have been used with different components in the steam dome. A study of parameters variation on the steam generator work and calculated results is made in cases with separator and branch.
Parametric study for horizontal steam generator modelling
Energy Technology Data Exchange (ETDEWEB)
Ovtcharova, I [Energoproekt, Sofia (Bulgaria)
1996-12-31
In the presentation some of the calculated results of horizontal steam generator PGV - 440 modelling with RELAP5/Mod3 are described. Two nodalization schemes have been used with different components in the steam dome. A study of parameters variation on the steam generator work and calculated results is made in cases with separator and branch.
Bayesian non parametric modelling of Higgs pair production
Directory of Open Access Journals (Sweden)
Scarpa Bruno
2017-01-01
Full Text Available Statistical classification models are commonly used to separate a signal from a background. In this talk we face the problem of isolating the signal of Higgs pair production using the decay channel in which each boson decays into a pair of b-quarks. Typically in this context non parametric methods are used, such as Random Forests or different types of boosting tools. We remain in the same non-parametric framework, but we propose to face the problem following a Bayesian approach. A Dirichlet process is used as prior for the random effects in a logit model which is fitted by leveraging the Polya-Gamma data augmentation. Refinements of the model include the insertion in the simple model of P-splines to relate explanatory variables with the response and the use of Bayesian trees (BART to describe the atoms in the Dirichlet process.
Non-Parametric Model Drift Detection
2016-07-01
framework on two tasks in NLP domain, topic modeling, and machine translation. Our main findings are summarized as follows: • We can measure important...thank,us,me,hope,today Group num: 4, TC(X;Y_j): 0.407 4:republic,palestinian,israel, arab ,israeli,democratic,congo,mr,president,occupied Group num: 5...support,change,lessons,partnerships,l earned Group num: 35, TC(X;Y_j): 0.094 35:russian,federation,spoke,you,french,spanish, arabic ,your,chinese,sir
Conformally parametrized surfaces associated with CPN-1 sigma models
International Nuclear Information System (INIS)
Grundland, A M; Hereman, W A; Yurdusen, I-dot
2008-01-01
Two-dimensional parametrized surfaces immersed in the su(N) algebra are investigated. The focus is on surfaces parametrized by solutions of the equations for the CP N-1 sigma model. The Lie-point symmetries of the CP N-1 model are computed for arbitrary N. The Weierstrass formula for immersion is determined and an explicit formula for a moving frame on a surface is constructed. This allows us to determine the structural equations and geometrical properties of surfaces in R N 2 -1 . The fundamental forms, Gaussian and mean curvatures, Willmore functional and topological charge of surfaces are given explicitly in terms of any holomorphic solution of the CP 2 model. The approach is illustrated through several examples, including surfaces immersed in low-dimensional su(N) algebras
Parametric analysis of fire model CFAST
International Nuclear Information System (INIS)
Lee, Y. H.; Yang, J. Y.; Kim, J. H.
2004-01-01
This paper describes the pump room fire of the nuclear power plant using CFAST fire modeling code developed by NIST. It is determined by the constrained or unconstrained fire, Lower Oxygen Limit (LOL), Radiative Fraction (RF), and the times to open doors, which are the input parameters of CAFST. According to the results, pump room fire is ventilation-controlled fire, so it is adequate that the value of LOL is 10% which is also the default value. It is appeared that the RF does not change the temperature of the upper gas layer. But the level of opening of the penetrating area and the times to opening it have an effect on the temperature of the upper layer, so it is determined that the results of it should be carefully analyzed
PARAMETRIC MODELING, CREATIVITY, AND DESIGN: TWO EXPERIENCES WITH ARCHITECTURE’ STUDENTS
Directory of Open Access Journals (Sweden)
Wilson Florio
2012-02-01
Full Text Available The aim of this article is to reflect on the use of the parametric modeling in two didactic experiences. The first experiment involved resources of the Paracloud program and its relation with the Rhinoceros program, that resulted in the production of physical models produced with the aid of the laser cutting. In the second experiment, the students had produced algorithms in the Grasshopper, resulting in families of structures and coverings. The study objects are both the physical models and digital algorithms resultants from this experimentation. For the analysis and synthesis of the results, we adopted four important assumptions: 1. the value of attitudes and environment of work; 2. the importance of experimentation and improvisation; 3. understanding of the design process as a situated act and as a ill-defined problem; 4. the inclusion of creative and critical thought in the disciplines. The results allow us to affirm that the parametric modeling stimulates creativity, therefore allowing combination of different parameters, that result in unexpected discoveries. Keywords: Teach-Learning, Parametric Modeling, Laser Cutter, Grasshopper, Design Process, Creativity.
A Novel Parametric Model For The Human Respiratory System
Directory of Open Access Journals (Sweden)
Clara Mihaela IONESCU
2003-12-01
Full Text Available The purpose of this work is to present some recent results in an ongoing research project between Ghent University and Chess Medical Technology Company Belgium. The overall aim of the project is to provide a fast method for identification of the human respiratory system in order to allow for an instantaneously diagnosis of the patient by the medical staff. A novel parametric model of the human respiratory system as well as the obtained experimental results is presented in this paper. A prototype apparatus developed by the company, based on the forced oscillation technique is used to record experimental data from 4 patients in this paper. Signal processing is based on spectral analysis and is followed by the parametric identification of a non-linear mechanistic model. The parametric model is equivalent to the structure of a simple electrical RLC-circuit, containing a non-linear capacitor. These parameters have a useful and easy-to-interpret physical meaning for the medical staff members.
Maydeu-Olivares, Albert
2005-01-01
Chernyshenko, Stark, Chan, Drasgow, and Williams (2001) investigated the fit of Samejima's logistic graded model and Levine's non-parametric MFS model to the scales of two personality questionnaires and found that the graded model did not fit well. We attribute the poor fit of the graded model to small amounts of multidimensionality present in…
Onset patterns in a simple model of localized parametric forcing.
Porter, J; Tinao, I; Laverón-Simavilla, A; Rodríguez, J
2013-10-01
We investigate pattern selection at onset in a parametrically and inhomogeneously forced partial differential equation obtained by generalizing Mathieu's equation to include spatial interactions. No separation of scales is assumed. The proposed model is directly relevant to the case of parametrically forced surface waves, such as cross-waves, excited by the horizontal vibration of a fluid, where the forcing is localized to a finite region near the endwall or wavemaker. The availability of analytical solutions in the limit of piecewise constant forcing allows us investigate in detail the dependence of selected eigenfunctions on spatial detuning, forcing width, damping, boundary conditions, and container size. A wide range of onset patterns are located and described, many of which are rotated, modulated, or both, and deviate far from simple crosswise oriented standing waves. The linear selection mechanisms governing this multiplicity of potential onset patterns are discussed.
A parametric costing model for wave energy technology
International Nuclear Information System (INIS)
1992-01-01
This document describes the philosophy and technical approach to a parametric cost model for offshore wave energy systems. Consideration is given both to existing known devices and other devices yet to be conceptualised. The report is complementary to a spreadsheet based cost estimating model. The latter permits users to derive capital cost estimates using either inherent default data or user provided data, if a particular scheme provides sufficient design definition for more accurate estimation. The model relies on design default data obtained from wave energy device designs and a set of specifically collected cost data. (author)
Multivariable Parametric Cost Model for Ground Optical Telescope Assembly
Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia
2005-01-01
A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.
Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly
Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia
2004-01-01
A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.
Rodenacker, Klaas; Hautmann, Christopher; Görtz-Dorten, Anja; Döpfner, Manfred
2016-01-01
Various studies have demonstrated that bifactor models yield better solutions than models with correlated factors. However, the kind of bifactor model that is most appropriate is yet to be examined. The current study is the first to test bifactor models across the full age range (11-18 years) of adolescents using self-reports, and the first to test bifactor models with German subjects and German questionnaires. The study sample included children and adolescents aged between 6 and 18 years recruited from a German clinical sample (n = 1,081) and a German community sample (n = 642). To examine the factorial validity, we compared unidimensional, correlated factors and higher-order and bifactor models and further tested a modified incomplete bifactor model for measurement invariance. Bifactor models displayed superior model fit statistics compared to correlated factor models or second-order models. However, a more parsimonious incomplete bifactor model with only 2 specific factors (inattention and impulsivity) showed a good model fit and a better factor structure than the other bifactor models. Scalar measurement invariance was given in most group comparisons. An incomplete bifactor model would suggest that the specific inattention and impulsivity factors represent entities separable from the general attention-deficit/hyperactivity disorder construct and might, therefore, give way to a new approach to subtyping of children beyond and above attention-deficit/hyperactivity disorder. © 2016 S. Karger AG, Basel.
Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.
2011-01-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques
Spatial variability and parametric uncertainty in performance assessment models
International Nuclear Information System (INIS)
Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo
2011-01-01
The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)
Parametric modeling for damped sinusoids from multiple channels
DEFF Research Database (Denmark)
Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll
2013-01-01
frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....
Process simulation and parametric modeling for strategic project management
Morales, Peter J
2013-01-01
Process Simulation and Parametric Modeling for Strategic Project Management will offer CIOs, CTOs and Software Development Managers, IT Graduate Students an introduction to a set of technologies that will help them understand how to better plan software development projects, manage risk and have better insight into the complexities of the software development process.A novel methodology will be introduced that allows a software development manager to better plan and access risks in the early planning of a project. By providing a better model for early software development estimation and softw
Facial Performance Transfer via Deformable Models and Parametric Correspondence.
Asthana, Akshay; de la Hunty, Miles; Dhall, Abhinav; Goecke, Roland
2012-09-01
The issue of transferring facial performance from one person's face to another's has been an area of interest for the movie industry and the computer graphics community for quite some time. In recent years, deformable face models, such as the Active Appearance Model (AAM), have made it possible to track and synthesize faces in real time. Not surprisingly, deformable face model-based approaches for facial performance transfer have gained tremendous interest in the computer vision and graphics community. In this paper, we focus on the problem of real-time facial performance transfer using the AAM framework. We propose a novel approach of learning the mapping between the parameters of two completely independent AAMs, using them to facilitate the facial performance transfer in a more realistic manner than previous approaches. The main advantage of modeling this parametric correspondence is that it allows a "meaningful" transfer of both the nonrigid shape and texture across faces irrespective of the speakers' gender, shape, and size of the faces, and illumination conditions. We explore linear and nonlinear methods for modeling the parametric correspondence between the AAMs and show that the sparse linear regression method performs the best. Moreover, we show the utility of the proposed framework for a cross-language facial performance transfer that is an area of interest for the movie dubbing industry.
Mace, Andy; Rudolph, David L.; Kachanoski , R. Gary
1998-01-01
The performance of parametric models used to describe soil water retention (SWR) properties and predict unsaturated hydraulic conductivity (K) as a function of volumetric water content (θ) is examined using SWR and K(θ) data for coarse sand and gravel sediments. Six 70 cm long, 10 cm diameter cores of glacial outwash were instrumented at eight depths with porous cup ten-siometers and time domain reflectometry probes to measure soil water pressure head (h) and θ, respectively, for seven unsaturated and one saturated steady-state flow conditions. Forty-two θ(h) and K(θ) relationships were measured from the infiltration tests on the cores. Of the four SWR models compared in the analysis, the van Genuchten (1980) equation with parameters m and n restricted according to the Mualem (m = 1 - 1/n) criterion is best suited to describe the θ(h) relationships. The accuracy of two models that predict K(θ) using parameter values derived from the SWR models was also evaluated. The model developed by van Genuchten (1980) based on the theoretical expression of Mualem (1976) predicted K(θ) more accurately than the van Genuchten (1980) model based on the theory of Burdine (1953). A sensitivity analysis shows that more accurate predictions of K(θ) are achieved using SWR model parameters derived with residual water content (θr) specified according to independent measurements of θ at values of h where θ/h ∼ 0 rather than model-fit θr values. The accuracy of the model K(θ) function improves markedly when at least one value of unsaturated K is used to scale the K(θ) function predicted using the saturated K. The results of this investigation indicate that the hydraulic properties of coarse-grained sediments can be accurately described using the parametric models. In addition, data collection efforts should focus on measuring at least one value of unsaturated hydraulic conductivity and as complete a set of SWR data as possible, particularly in the dry range.
Parametric packet-based audiovisual quality model for IPTV services
Garcia, Marie-Neige
2014-01-01
This volume presents a parametric packet-based audiovisual quality model for Internet Protocol TeleVision (IPTV) services. The model is composed of three quality modules for the respective audio, video and audiovisual components. The audio and video quality modules take as input a parametric description of the audiovisual processing path, and deliver an estimate of the audio and video quality. These outputs are sent to the audiovisual quality module which provides an estimate of the audiovisual quality. Estimates of perceived quality are typically used both in the network planning phase and as part of the quality monitoring. The same audio quality model is used for both these phases, while two variants of the video quality model have been developed for addressing the two application scenarios. The addressed packetization scheme is MPEG2 Transport Stream over Real-time Transport Protocol over Internet Protocol. In the case of quality monitoring, that is the case for which the network is already set-up, the aud...
Parametric design and analysis framework with integrated dynamic models
DEFF Research Database (Denmark)
Negendahl, Kristoffer
2014-01-01
of building energy and indoor environment, are generally confined to late in the design process. Consequence based design is a framework intended for the early design stage. It involves interdisciplinary expertise that secures validity and quality assurance with a simulationist while sustaining autonomous...... control with the building designer. Consequence based design is defined by the specific use of integrated dynamic modeling, which includes the parametric capabilities of a scripting tool and building simulation features of a building performance simulation tool. The framework can lead to enhanced...
Parametric System Model for a Stirling Radioisotope Generator
Schmitz, Paul C.
2015-01-01
A Parametric System Model (PSM) was created in order to explore conceptual designs, the impact of component changes and power level on the performance of the Stirling Radioisotope Generator (SRG). Using the General Purpose Heat Source (GPHS approximately 250 Wth) modules as the thermal building block from which a SRG is conceptualized, trade studies are performed to understand the importance of individual component scaling on isotope usage. Mathematical relationships based on heat and power throughput, temperature, mass, and volume were developed for each of the required subsystems. The PSM uses these relationships to perform component- and system-level trades.
Parametrization of Seesaw Models and Light Sterile Neutrinos
Blennow, Mattias
2011-01-01
The recent recomputation of the neutrino fluxes from nuclear reactors relaxes the tension between the LSND and MiniBooNE anomalies and disappearance data when interpreted in terms of sterile neutrino oscillations. The simplest extension of the Standard Model with such fermion singlets is the addition of right-handed sterile neutrinos with small Majorana masses. Even when introducing three right-handed neutrinos, this scenario has less free parameters than the 3+2 scenarios studied in the literature. This begs the question whether the best fit regions obtained can be reproduced by this simplest extension of the Standard Model. In order to address this question, we devise an exact parametrization of Standard Model extensions with right-handed neutrinos. Apart from the usual 3x3 neutrino mixing matrix and the 3 masses of the lightest neutrinos, the extra degrees of freedom are encoded in another 3x3 unitary matrix and 3 additional mixing angles. The parametrization includes all the correlations among masses and ...
Thermodynamic model and parametric analysis of a tubular SOFC module
Campanari, Stefano
Solid oxide fuel cells (SOFCs) have been considered in the last years as one of the most promising technologies for very high-efficiency electric energy generation from natural gas, both with simple fuel cell plants and with integrated gas turbine-fuel cell systems. Among the SOFC technologies, tubular SOFC stacks with internal reforming have emerged as one of the most mature technology, with a serious potential for a future commercialization. In this paper, a thermodynamic model of a tubular SOFC stack, with natural gas feeding, internal reforming of hydrocarbons and internal air preheating is proposed. In the first section of the paper, the model is discussed in detail, analyzing its calculating equations and tracing its logical steps; the model is then calibrated on the available data for a recently demonstrated tubular SOFC prototype plant. In the second section of the paper, it is carried out a detailed parametric analysis of the stack working conditions, as a function of the main operating parameters. The discussion of the results of the thermodynamic and parametric analysis yields interesting considerations about partial load SOFC operation and load regulation, and about system design and integration with gas turbine cycles.
Reed, S. L.; McMahon, R. G.; Martini, P.; Banerji, M.; Auger, M.; Hewett, P. C.; Koposov, S. E.; Gibbons, S. L. J.; Gonzalez-Solares, E.; Ostrovski, F.; Tie, S. S.; Abdalla, F. B.; Allam, S.; Benoit-Lévy, A.; Bertin, E.; Brooks, D.; Buckley-Geer, E.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; da Costa, L. N.; DePoy, D. L.; Desai, S.; Diehl, H. T.; Doel, P.; Evrard, A. E.; Finley, D. A.; Flaugher, B.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gaztanaga, E.; Goldstein, D. A.; Gruen, D.; Gruendl, R. A.; Gutierrez, G.; James, D. J.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Lima, M.; Maia, M. A. G.; Marshall, J. L.; Melchior, P.; Miller, C. J.; Miquel, R.; Nord, B.; Ogando, R.; Plazas, A. A.; Romer, A. K.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, R. C.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Tucker, D. L.; Walker, A. R.; Wester, W.
2017-07-01
We present the discovery and spectroscopic confirmation with the European Southern Observatory New Technology Telescope (NTT) and Gemini South telescopes of eight new, and the rediscovery of two previously known, 6.0 VISTA Hemisphere Survey (J, H, K) and Wide-field Infrared Survey Explorer (W1, W2). The photometric data were fitted with a grid of quasar model SEDs with redshift-dependent Ly α forest absorption and a range of intrinsic reddening as well as a series of low-mass cool star models. Candidates were ranked using an SED-model-based χ2-statistic, which is extendable to other future imaging surveys (e.g. LSST and Euclid). Our spectral confirmation success rate is 100 per cent without the need for follow-up photometric observations as used in other studies of this type. Combined with automatic removal of the main types of non-astrophysical contaminants, the method allows large data sets to be processed without human intervention and without being overrun by spurious false candidates. We also present a robust parametric redshift estimator that gives comparable accuracy to Mg II and CO-based redshift estimators. We find two z ˜ 6.2 quasars with H II near zone sizes ≤3 proper Mpc that could indicate that these quasars may be young with ages ≲ 106-107 years or lie in over dense regions of the IGM. The z = 6.5 quasar VDES J0224-4711 has JAB = 19.75 and is the second most luminous quasar known with z ≥ 6.5.
Toward an Empirically-based Parametric Explosion Spectral Model
Ford, S. R.; Walter, W. R.; Ruppert, S.; Matzel, E.; Hauk, T. F.; Gok, R.
2010-12-01
Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases (Pn, Pg, and Lg) that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. These parameters are then correlated with near-source geology and containment conditions. There is a correlation of high gas-porosity (low strength) with increased spectral slope. However, there are trade-offs between the slope and corner-frequency, which we try to independently constrain using Mueller-Murphy relations and coda-ratio techniques. The relationship between the parametric equation and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source, and aid in the prediction of observed local and regional distance seismic amplitudes for event identification and yield determination in regions with incomplete or no prior history of underground nuclear testing.
Environmental Parametric Cost Model in Oil and Gas EPC Contracts
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Madjid Abbaspour
2018-01-01
Full Text Available This study aims at identifying the parameters that govern the environmental costs in oil and gas projects. An initial conceptual model was proposed. Next, the costs of environmental management work packages were estimated, separately and were applied in project control tools (WBS/CBS. Then, an environmental parametric cost model was designed to determine the environmental costs and relevant weighting factors. The suggested model can be considered as an innovative approach to designate the environmental indicators in oil and gas projects. The validity of variables was investigated based on Delphi method. The results indicated that the project environmental management’s weighting factor is 0.87% of total project’s weighting factor.
An Evaluation of Parametric and Nonparametric Models of Fish Population Response.
Energy Technology Data Exchange (ETDEWEB)
Haas, Timothy C.; Peterson, James T.; Lee, Danny C.
1999-11-01
Predicting the distribution or status of animal populations at large scales often requires the use of broad-scale information describing landforms, climate, vegetation, etc. These data, however, often consist of mixtures of continuous and categorical covariates and nonmultiplicative interactions among covariates, complicating statistical analyses. Using data from the interior Columbia River Basin, USA, we compared four methods for predicting the distribution of seven salmonid taxa using landscape information. Subwatersheds (mean size, 7800 ha) were characterized using a set of 12 covariates describing physiography, vegetation, and current land-use. The techniques included generalized logit modeling, classification trees, a nearest neighbor technique, and a modular neural network. We evaluated model performance using out-of-sample prediction accuracy via leave-one-out cross-validation and introduce a computer-intensive Monte Carlo hypothesis testing approach for examining the statistical significance of landscape covariates with the non-parametric methods. We found the modular neural network and the nearest-neighbor techniques to be the most accurate, but were difficult to summarize in ways that provided ecological insight. The modular neural network also required the most extensive computer resources for model fitting and hypothesis testing. The generalized logit models were readily interpretable, but were the least accurate, possibly due to nonlinear relationships and nonmultiplicative interactions among covariates. Substantial overlap among the statistically significant (P<0.05) covariates for each method suggested that each is capable of detecting similar relationships between responses and covariates. Consequently, we believe that employing one or more methods may provide greater biological insight without sacrificing prediction accuracy.
MTL-Model Checking of One-Clock Parametric Timed Automata is Undecidable
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Karin Quaas
2014-03-01
Full Text Available Parametric timed automata extend timed automata (Alur and Dill, 1991 in that they allow the specification of parametric bounds on the clock values. Since their introduction in 1993 by Alur, Henzinger, and Vardi, it is known that the emptiness problem for parametric timed automata with one clock is decidable, whereas it is undecidable if the automaton uses three or more parametric clocks. The problem is open for parametric timed automata with two parametric clocks. Metric temporal logic, MTL for short, is a widely used specification language for real-time systems. MTL-model checking of timed automata is decidable, no matter how many clocks are used in the timed automaton. In this paper, we prove that MTL-model checking for parametric timed automata is undecidable, even if the automaton uses only one clock and one parameter and is deterministic.
Salameh , Farah; Picot , Antoine; Chabert , Marie; Maussion , Pascal
2017-01-01
International audience; This paper describes an original statistical approach for the lifespan modeling of electric machine insulation materials. The presented models aim to study the effect of three main stress factors (voltage, frequency and temperature) and their interactions on the insulation lifespan. The proposed methodology is applied to two different insulation materials tested in partial discharge regime. Accelerated ageing tests are organized according to experimental optimization m...
Study on Semi-Parametric Statistical Model of Safety Monitoring of Cracks in Concrete Dams
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Chongshi Gu
2013-01-01
Full Text Available Cracks are one of the hidden dangers in concrete dams. The study on safety monitoring models of concrete dam cracks has always been difficult. Using the parametric statistical model of safety monitoring of cracks in concrete dams, with the help of the semi-parametric statistical theory, and considering the abnormal behaviors of these cracks, the semi-parametric statistical model of safety monitoring of concrete dam cracks is established to overcome the limitation of the parametric model in expressing the objective model. Previous projects show that the semi-parametric statistical model has a stronger fitting effect and has a better explanation for cracks in concrete dams than the parametric statistical model. However, when used for forecast, the forecast capability of the semi-parametric statistical model is equivalent to that of the parametric statistical model. The modeling of the semi-parametric statistical model is simple, has a reasonable principle, and has a strong practicality, with a good application prospect in the actual project.
Lumped parametric model of the human ear for sound transmission.
Feng, Bin; Gan, Rong Z
2004-09-01
A lumped parametric model of the human auditoria peripherals consisting of six masses suspended with six springs and ten dashpots was proposed. This model will provide the quantitative basis for the construction of a physical model of the human middle ear. The lumped model parameters were first identified using published anatomical data, and then determined through a parameter optimization process. The transfer function of the middle ear obtained from human temporal bone experiments with laser Doppler interferometers was used for creating the target function during the optimization process. It was found that, among 14 spring and dashpot parameters, there were five parameters which had pronounced effects on the dynamic behaviors of the model. The detailed discussion on the sensitivity of those parameters was provided with appropriate applications for sound transmission in the ear. We expect that the methods for characterizing the lumped model of the human ear and the model parameters will be useful for theoretical modeling of the ear function and construction of the ear physical model.
Parametric overdispersed frailty models for current status data.
Abrams, Steven; Aerts, Marc; Molenberghs, Geert; Hens, Niel
2017-12-01
Frailty models have a prominent place in survival analysis to model univariate and multivariate time-to-event data, often complicated by the presence of different types of censoring. In recent years, frailty modeling gained popularity in infectious disease epidemiology to quantify unobserved heterogeneity using Type I interval-censored serological data or current status data. In a multivariate setting, frailty models prove useful to assess the association between infection times related to multiple distinct infections acquired by the same individual. In addition to dependence among individual infection times, overdispersion can arise when the observed variability in the data exceeds the one implied by the model. In this article, we discuss parametric overdispersed frailty models for time-to-event data under Type I interval-censoring, building upon the work by Molenberghs et al. (2010) and Hens et al. (2009). The proposed methodology is illustrated using bivariate serological data on hepatitis A and B from Flanders, Belgium anno 1993-1994. Furthermore, the relationship between individual heterogeneity and overdispersion at a stratum-specific level is studied through simulations. Although it is important to account for overdispersion, one should be cautious when modeling both individual heterogeneity and overdispersion based on current status data as model selection is hampered by the loss of information due to censoring. © 2017, The International Biometric Society.
Parametric Thermal Models of the Transient Reactor Test Facility (TREAT)
Energy Technology Data Exchange (ETDEWEB)
Bradley K. Heath
2014-03-01
This work supports the restart of transient testing in the United States using the Department of Energy’s Transient Reactor Test Facility at the Idaho National Laboratory. It also supports the Global Threat Reduction Initiative by reducing proliferation risk of high enriched uranium fuel. The work involves the creation of a nuclear fuel assembly model using the fuel performance code known as BISON. The model simulates the thermal behavior of a nuclear fuel assembly during steady state and transient operational modes. Additional models of the same geometry but differing material properties are created to perform parametric studies. The results show that fuel and cladding thermal conductivity have the greatest effect on fuel temperature under the steady state operational mode. Fuel density and fuel specific heat have the greatest effect for transient operational model. When considering a new fuel type it is recommended to use materials that decrease the specific heat of the fuel and the thermal conductivity of the fuel’s cladding in order to deal with higher density fuels that accompany the LEU conversion process. Data on the latest operating conditions of TREAT need to be attained in order to validate BISON’s results. BISON’s models for TREAT (material models, boundary convection models) are modest and need additional work to ensure accuracy and confidence in results.
Validation of statistical models for creep rupture by parametric analysis
Energy Technology Data Exchange (ETDEWEB)
Bolton, J., E-mail: john.bolton@uwclub.net [65, Fisher Ave., Rugby, Warks CV22 5HW (United Kingdom)
2012-01-15
Statistical analysis is an efficient method for the optimisation of any candidate mathematical model of creep rupture data, and for the comparative ranking of competing models. However, when a series of candidate models has been examined and the best of the series has been identified, there is no statistical criterion to determine whether a yet more accurate model might be devised. Hence there remains some uncertainty that the best of any series examined is sufficiently accurate to be considered reliable as a basis for extrapolation. This paper proposes that models should be validated primarily by parametric graphical comparison to rupture data and rupture gradient data. It proposes that no mathematical model should be considered reliable for extrapolation unless the visible divergence between model and data is so small as to leave no apparent scope for further reduction. This study is based on the data for a 12% Cr alloy steel used in BS PD6605:1998 to exemplify its recommended statistical analysis procedure. The models considered in this paper include a) a relatively simple model, b) the PD6605 recommended model and c) a more accurate model of somewhat greater complexity. - Highlights: Black-Right-Pointing-Pointer The paper discusses the validation of creep rupture models derived from statistical analysis. Black-Right-Pointing-Pointer It demonstrates that models can be satisfactorily validated by a visual-graphic comparison of models to data. Black-Right-Pointing-Pointer The method proposed utilises test data both as conventional rupture stress and as rupture stress gradient. Black-Right-Pointing-Pointer The approach is shown to be more reliable than a well-established and widely used method (BS PD6605).
Motion Imitation and Recognition using Parametric Hidden Markov Models
DEFF Research Database (Denmark)
Herzog, Dennis; Ude, Ales; Krüger, Volker
2008-01-01
) are important. Only together they convey the whole meaning of an action. Similarly, to imitate a movement, the robot needs to select the proper action and parameterize it, e.g., by the relative position of the object that needs to be grasped. We propose to utilize parametric hidden Markov models (PHMMs), which...... extend the classical HMMs by introducing a joint parameterization of the observation densities, to simultaneously solve the problems of action recognition, parameterization of the observed actions, and action synthesis. The proposed approach was fully implemented on a humanoid robot HOAP-3. To evaluate...... the approach, we focused on reaching and pointing actions. Even though the movements are very similar in appearance, our approach is able to distinguish the two movement types and discover the parameterization, and is thus enabling both, action recognition and action synthesis. Through parameterization we...
Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models
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Marius Pesavento
2004-08-01
Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.
Parametric study of the Incompletely Stirred Reactor modeling
Energy Technology Data Exchange (ETDEWEB)
Mobini, K. [Department of Mechanical Engineering, Shahid Rajaee University, Lavizan, Tehran (Iran); Bilger, R.W. [School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney, Sydney (Australia)
2009-09-15
The Incompletely Stirred Reactor (ISR) is a generalization of the widely-used Perfectly Stirred Reactor (PSR) model and allows for incomplete mixing within the reactor. Its formulation is based on the Conditional Moment Closure (CMC) method. This model is applicable to nonpremixed combustion with strong recirculation such as in a gas turbine combustor primary zone. The model uses the simplifying assumptions that the conditionally-averaged reactive-scalar concentrations are independent of position in the reactor: this results in ordinary differential equations in mixture fraction space. The simplicity of the model permits the use of very complex chemical mechanisms. The effects of the detailed chemistry can be found while still including the effects of micromixing. A parametric study is performed here on an ISR for combustion of methane at overall stoichiometric conditions to investigate the sensitivity of the model to different parameters. The focus here is on emissions of nitric oxide and carbon monoxide. It is shown that the most important parameters in the ISR model are reactor residence time, the chemical mechanism and the core-averaged Probability Density Function (PDF). Using several different shapes for the core-averaged PDF, it is shown that use of a bimodal PDF with a low minimum at stoichiometric mixture fraction and a large variance leads to lower nitric oxide formation. The 'rich-plus-lean' mixing or staged combustion strategy for combustion is thus supported. (author)
Directory of Open Access Journals (Sweden)
Renata Pires Gonçalves
2012-02-01
. The experiments of type dosage x response are very common in the determination of levels of nutrients in optimal food balance and include the use of regression models to achieve this objective. Nevertheless, the regression analysis routine, generally, uses a priori information about a possible relationship between the response variable. The isotonic regression is a method of estimation by least squares that generates estimates which preserves data ordering. In the theory of isotonic regression this information is essential and it is expected to increase fitting efficiency. The objective of this work was to use an isotonic regression methodology, as an alternative way of analyzing data of Zn deposition in tibia of male birds of Hubbard lineage. We considered the models of plateau response of polynomial quadratic and linear exponential forms. In addition to these models, we also proposed the fitting of a logarithmic model to the data and the efficiency of the methodology was evaluated by Monte Carlo simulations, considering different scenarios for the parametric values. The isotonization of the data yielded an improvement in all the fitting quality parameters evaluated. Among the models used, the logarithmic presented estimates of the parameters more consistent with the values reported in literature.
Parametric Model for Astrophysical Proton-Proton Interactions and Applications
Energy Technology Data Exchange (ETDEWEB)
Karlsson, Niklas [KTH Royal Institute of Technology, Stockholm (Sweden)
2007-01-01
Observations of gamma-rays have been made from celestial sources such as active galaxies, gamma-ray bursts and supernova remnants as well as the Galactic ridge. The study of gamma rays can provide information about production mechanisms and cosmic-ray acceleration. In the high-energy regime, one of the dominant mechanisms for gamma-ray production is the decay of neutral pions produced in interactions of ultra-relativistic cosmic-ray nuclei and interstellar matter. Presented here is a parametric model for calculations of inclusive cross sections and transverse momentum distributions for secondary particles--gamma rays, e^{±}, v_{e}, $\\bar{v}$_{e}, v_{μ} and $\\bar{μ}$_{e}--produced in proton-proton interactions. This parametric model is derived on the proton-proton interaction model proposed by Kamae et al.; it includes the diffraction dissociation process, Feynman-scaling violation and the logarithmically rising inelastic proton-proton cross section. To improve fidelity to experimental data for lower energies, two baryon resonance excitation processes were added; one representing the Δ(1232) and the other multiple resonances with masses around 1600 MeV/c^{2}. The model predicts the power-law spectral index for all secondary particle to be about 0.05 lower in absolute value than that of the incident proton and their inclusive cross sections to be larger than those predicted by previous models based on the Feynman-scaling hypothesis. The applications of the presented model in astrophysics are plentiful. It has been implemented into the Galprop code to calculate the contribution due to pion decays in the Galactic plane. The model has also been used to estimate the cosmic-ray flux in the Large Magellanic Cloud based on HI, CO and gamma-ray observations. The transverse momentum distributions enable calculations when the proton distribution is anisotropic. It is shown that the gamma-ray spectrum and flux due to a
Directory of Open Access Journals (Sweden)
Junyi eDai
2015-03-01
Full Text Available The Iowa Gambling Task (IGT and the Soochow Gambling Task (SGT are two experience-based risky decision-making tasks for examining decision-making deficits in clinical populations. Several cognitive models, including the expectancy-valence learning model (EVL and the prospect valence learning model (PVL, have been developed to disentangle the motivational, cognitive, and response processes underlying the explicit choices in these tasks. The purpose of the current study was to develop an improved model that can fit empirical data better than the EVL and PVL models and, in addition, produce more consistent parameter estimates across the IGT and SGT. Twenty-six opiate users (mean age 34.23; SD 8.79 and 27 control participants (mean age 35; SD 10.44 completed both tasks. Eighteen cognitive models varying in evaluation, updating, and choice rules were fit to individual data and their performances were compared to that of a statistical baseline model to find a best fitting model. The results showed that the model combining the prospect utility function treating gains and losses separately, the decay-reinforcement updating rule, and the trial-independent choice rule performed the best in both tasks. Furthermore, the winning model produced more consistent individual parameter estimates across the two tasks than any of the other models.
Fox, William
2012-01-01
The purpose of our modeling effort is to predict future outcomes. We assume the data collected are both accurate and relatively precise. For our oscillating data, we examined several mathematical modeling forms for predictions. We also examined both ignoring the oscillations as an important feature and including the oscillations as an important…
Parametric Linear Hybrid Automata for Complex Environmental Systems Modeling
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Samar Hayat Khan Tareen
2015-07-01
Full Text Available Environmental systems, whether they be weather patterns or predator-prey relationships, are dependent on a number of different variables, each directly or indirectly affecting the system at large. Since not all of these factors are known, these systems take on non-linear dynamics, making it difficult to accurately predict meaningful behavioral trends far into the future. However, such dynamics do not warrant complete ignorance of different efforts to understand and model close approximations of these systems. Towards this end, we have applied a logical modeling approach to model and analyze the behavioral trends and systematic trajectories that these systems exhibit without delving into their quantification. This approach, formalized by René Thomas for discrete logical modeling of Biological Regulatory Networks (BRNs and further extended in our previous studies as parametric biological linear hybrid automata (Bio-LHA, has been previously employed for the analyses of different molecular regulatory interactions occurring across various cells and microbial species. As relationships between different interacting components of a system can be simplified as positive or negative influences, we can employ the Bio-LHA framework to represent different components of the environmental system as positive or negative feedbacks. In the present study, we highlight the benefits of hybrid (discrete/continuous modeling which lead to refinements among the fore-casted behaviors in order to find out which ones are actually possible. We have taken two case studies: an interaction of three microbial species in a freshwater pond, and a more complex atmospheric system, to show the applications of the Bio-LHA methodology for the timed hybrid modeling of environmental systems. Results show that the approach using the Bio-LHA is a viable method for behavioral modeling of complex environmental systems by finding timing constraints while keeping the complexity of the model
A local non-parametric model for trade sign inference
Blazejewski, Adam; Coggins, Richard
2005-03-01
We investigate a regularity in market order submission strategies for 12 stocks with large market capitalization on the Australian Stock Exchange. The regularity is evidenced by a predictable relationship between the trade sign (trade initiator), size of the trade, and the contents of the limit order book before the trade. We demonstrate this predictability by developing an empirical inference model to classify trades into buyer-initiated and seller-initiated. The model employs a local non-parametric method, k-nearest neighbor, which in the past was used successfully for chaotic time series prediction. The k-nearest neighbor with three predictor variables achieves an average out-of-sample classification accuracy of 71.40%, compared to 63.32% for the linear logistic regression with seven predictor variables. The result suggests that a non-linear approach may produce a more parsimonious trade sign inference model with a higher out-of-sample classification accuracy. Furthermore, for most of our stocks the observed regularity in market order submissions seems to have a memory of at least 30 trading days.
Rabin, Sam S.; Ward, Daniel S.; Malyshev, Sergey L.; Magi, Brian I.; Shevliakova, Elena; Pacala, Stephen W.
2018-03-01
This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001-2009 (global totals: 0.434×106 and 2.02×106 km2 yr-1 modeled, 0.454×106 and 2.04×106 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgC yr-1 modeled, 0.194 and 0.538 PgC yr-1 observed). The non-agricultural fire module underestimates global burned area (1.91×106 km2 yr-1 modeled, 2.44×106 km2 yr-1 observed) and carbon emissions (1.14 PgC yr-1 modeled, 1.84 PgC yr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg-Marquardt algorithm in an interactive optimization for a dynamic global vegetation model.
de Villiers, Marelize; Kriticos, Darren J; Veldtman, Ruan
2017-01-01
The European wasp, Vespula germanica (Fabricius) (Hymenoptera: Vespidae), is of Palaearctic origin, being native to Europe, northern Africa and Asia, and introduced into North America, Chile, Argentina, Iceland, Ascension Island, South Africa, Australia and New Zealand. Due to its polyphagous nature and scavenging behaviour, V. germanica threatens agriculture and silviculture, and negatively affects biodiversity, while its aggressive nature and venomous sting pose a health risk to humans. In areas with warmer winters and longer summers, queens and workers can survive the winter months, leading to the build-up of large nests during the following season; thereby increasing the risk posed by this species. To prevent or prepare for such unwanted impacts it is important to know where the wasp may be able to establish, either through natural spread or through introduction as a result of human transport. Distribution data from Argentina and Australia, and seasonal phenology data from Argentina were used to determine the potential distribution of V. germanica using CLIMEX modelling. In contrast to previous models, the influence of irrigation on its distribution was also investigated. Under a natural rainfall scenario, the model showed similarities to previous models. When irrigation is applied, dry stress is alleviated, leading to larger areas modelled climatically suitable compared with previous models, which provided a better fit with the actual distribution of the species. The main areas at risk of invasion by V. germanica include western USA, Mexico, small areas in Central America and in the north-western region of South America, eastern Brazil, western Russia, north-western China, Japan, the Mediterranean coastal regions of North Africa, and parts of southern and eastern Africa.
Directory of Open Access Journals (Sweden)
Marelize de Villiers
Full Text Available The European wasp, Vespula germanica (Fabricius (Hymenoptera: Vespidae, is of Palaearctic origin, being native to Europe, northern Africa and Asia, and introduced into North America, Chile, Argentina, Iceland, Ascension Island, South Africa, Australia and New Zealand. Due to its polyphagous nature and scavenging behaviour, V. germanica threatens agriculture and silviculture, and negatively affects biodiversity, while its aggressive nature and venomous sting pose a health risk to humans. In areas with warmer winters and longer summers, queens and workers can survive the winter months, leading to the build-up of large nests during the following season; thereby increasing the risk posed by this species. To prevent or prepare for such unwanted impacts it is important to know where the wasp may be able to establish, either through natural spread or through introduction as a result of human transport. Distribution data from Argentina and Australia, and seasonal phenology data from Argentina were used to determine the potential distribution of V. germanica using CLIMEX modelling. In contrast to previous models, the influence of irrigation on its distribution was also investigated. Under a natural rainfall scenario, the model showed similarities to previous models. When irrigation is applied, dry stress is alleviated, leading to larger areas modelled climatically suitable compared with previous models, which provided a better fit with the actual distribution of the species. The main areas at risk of invasion by V. germanica include western USA, Mexico, small areas in Central America and in the north-western region of South America, eastern Brazil, western Russia, north-western China, Japan, the Mediterranean coastal regions of North Africa, and parts of southern and eastern Africa.
Image sequence analysis in nuclear medicine: (1) Parametric imaging using statistical modelling
International Nuclear Information System (INIS)
Liehn, J.C.; Hannequin, P.; Valeyre, J.
1989-01-01
This is a review of parametric imaging methods on Nuclear Medicine. A Parametric Image is an image in which each pixel value is a function of the value of the same pixel of an image sequence. The Local Model Method is the fitting of each pixel time activity curve by a model which parameter values form the Parametric Images. The Global Model Method is the modelling of the changes between two images. It is applied to image comparison. For both methods, the different models, the identification criterion, the optimization methods and the statistical properties of the images are discussed. The analysis of one or more Parametric Images is performed using 1D or 2D histograms. The statistically significant Parametric Images, (Images of significant Variances, Amplitudes and Differences) are also proposed [fr
Comparison of parametric methods for modeling corneal surfaces
Bouazizi, Hala; Brunette, Isabelle; Meunier, Jean
2017-02-01
Corneal topography is a medical imaging technique to get the 3D shape of the cornea as a set of 3D points of its anterior and posterior surfaces. From these data, topographic maps can be derived to assist the ophthalmologist in the diagnosis of disorders. In this paper, we compare three different mathematical parametric representations of the corneal surfaces leastsquares fitted to the data provided by corneal topography. The parameters obtained from these models reduce the dimensionality of the data from several thousand 3D points to only a few parameters and could eventually be useful for diagnosis, biometry, implant design etc. The first representation is based on Zernike polynomials that are commonly used in optics. A variant of these polynomials, named Bhatia-Wolf will also be investigated. These two sets of polynomials are defined over a circular domain which is convenient to model the elevation (height) of the corneal surface. The third representation uses Spherical Harmonics that are particularly well suited for nearly-spherical object modeling, which is the case for cornea. We compared the three methods using the following three criteria: the root-mean-square error (RMSE), the number of parameters and the visual accuracy of the reconstructed topographic maps. A large dataset of more than 2000 corneal topographies was used. Our results showed that Spherical Harmonics were superior with a RMSE mean lower than 2.5 microns with 36 coefficients (order 5) for normal corneas and lower than 5 microns for two diseases affecting the corneal shapes: keratoconus and Fuchs' dystrophy.
Teeling, M.V.M.T.; Turrin, M.; de Ruiter, P.; Turrin, Michela; Peters, Brady; O'Brien, William; Stouffs, Rudi; Dogan, Timur
2017-01-01
This paper presents a parametric approach to an integrated and performance-oriented design, from the conceptual design phase towards materialization. The novelty occurs in the use of parametric models as a way of integrating multidisciplinary design constraints, from daylight optimization to the
Comparison of Parametrization Techniques for an Electrical Circuit Model of Lithium-Sulfur Batteries
DEFF Research Database (Denmark)
Knap, Vaclav; Stroe, Daniel Loan; Teodorescu, Remus
2015-01-01
on the comparison of different parametrization methods of electrical circuit models (ECMs) for Li-S batteries. These methods are used to parametrize an ECM based on laboratory measurements performed on a Li-S pouch cell. Simulation results of ECMs are presented and compared against measurement values...
Variance in parametric images: direct estimation from parametric projections
International Nuclear Information System (INIS)
Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.
2000-01-01
Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)
Reinforcement Toolbox, a Parametric Reinforcement Modelling Tool for Curved Surface Structures
Lauppe, J.; Rolvink, A.; Coenders, J.L.
2013-01-01
This paper presents a computational strategy and parametric modelling toolbox which aim at enhancing the design- and production process of reinforcement in freeform curved surface structures. The computational strategy encompasses the necessary steps of raising an architectural curved surface model
Parametric Hidden Markov Models for Recognition and Synthesis of Movements
DEFF Research Database (Denmark)
Herzog, Dennis; Krüger, Volker; Grest, Daniel
2008-01-01
In humanoid robotics, the recognition and synthesis of parametric movements plays an extraordinary role for robot human interaction. Such a parametric movement is a movement of a particular type (semantic), for example, similar pointing movements performed at different table-top positions....... For understanding the whole meaning of a movement of a human, the recognition of its type, likewise its parameterization are important. Only both together convey the whole meaning. Vice versa, for mimicry, the synthesis of movements for the motor control of a robot needs to be parameterized, e.g., by the relative...... the applicability for online recognition based on very noisy 3D tracking data. The use of a parametric representation of movements is shown in a robot demo, where a robot removes objects from a table as demonstrated by an advisor. The synthesis for motor control is performed for arbitrary table-top positions....
Numerical Modelling of Spontaneous Emission in Optical Parametric Amplifiers
DEFF Research Database (Denmark)
Friis, Søren Michael Mørk; Andersen, Ulrik Lund; Rottwitt, Karsten
2013-01-01
Fiber optical parametric processes offer a wide range of applications including phase sensitive as well as phase insensitive amplification, wavelength conversion and signal regeneration. One of the difficult challenges is any of these applications is to predict their associated noise performance....
Four-parametric two-layer algebraic model of transition boundary layer at a planar plate
International Nuclear Information System (INIS)
Labusov, A.N.; Lapin, Yu.V.
1996-01-01
Consideration is given to four-parametric two-layer algebraic model of transition boundary layer on a plane plate, based on generalization of one-parametric algebraic Prandtl-Loitsjansky-Klauzer-3 model. The algebraic model uses Prandtl formulas for mixing path with Loitsjansky damping multiplier in the internal region and the relation for turbulent viscosity, based on universal scales of external region and named the Klauzer-3 formula. 12 refs., 10 figs
Kouramas, K.I.
2011-08-01
This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.
A parametric model for the global thermodynamic behavior of fluids in the critical region
International Nuclear Information System (INIS)
Luettmer-Strathmann, J.; Tang, S.; Sengers, J.V.
1992-01-01
The asymptotic thermodynamic behavior of fluids near the critical point is described by scaling laws with universal scaling functions that can be represented by parametric equations. In this paper, we derive a more general parametric model that incorporates the crossover from singular thermodynamic behavior near the critical point to regular classical thermodynamic behavior far away from the critical point. Using ethane as an example, we show that such a parametric crossover model yields an accurate representation of the thermodynamic properties of fluids in a large region around the critical point
APT cost scaling: Preliminary indications from a Parametric Costing Model (PCM)
International Nuclear Information System (INIS)
Krakowski, R.A.
1995-01-01
A Parametric Costing Model has been created and evaluate as a first step in quantitatively understanding important design options for the Accelerator Production of Tritium (APT) concept. This model couples key economic and technical elements of APT in a two-parameter search of beam energy and beam power that minimizes costs within a range of operating constraints. The costing and engineering depth of the Parametric Costing Model is minimal at the present open-quotes entry levelclose quotes, and is intended only to demonstrate a potential for a more-detailed, cost-based integrating design tool. After describing the present basis of the Parametric Costing Model and giving an example of a single parametric scaling run derived therefrom, the impacts of choices related to resistive versus superconducting accelerator structures and cost of electricity versus plant availability (open-quotes load curveclose quotes) are reported. Areas of further development and application are suggested
Fast and Sequence-Adaptive Whole-Brain Segmentation Using Parametric Bayesian Modeling
DEFF Research Database (Denmark)
Puonti, Oula; Iglesias, Juan Eugenio; Van Leemput, Koen
2016-01-01
the performance of a segmentation algorithm designed to meet these requirements, building upon generative parametric models previously used in tissue classification. The method is tested on four different datasets acquired with different scanners, field strengths and pulse sequences, demonstrating comparable...
Parametric Modelling of As-Built Beam Framed Structure in Bim Environment
Yang, X.; Koehl, M.; Grussenmeyer, P.
2017-02-01
A complete documentation and conservation of a historic timber roof requires the integration of geometry modelling, attributional and dynamic information management and results of structural analysis. Recently developed as-built Building Information Modelling (BIM) technique has the potential to provide a uniform platform, which provides possibility to integrate the traditional geometry modelling, parametric elements management and structural analysis together. The main objective of the project presented in this paper is to develop a parametric modelling tool for a timber roof structure whose elements are leaning and crossing beam frame. Since Autodesk Revit, as the typical BIM software, provides the platform for parametric modelling and information management, an API plugin, able to automatically create the parametric beam elements and link them together with strict relationship, was developed. The plugin under development is introduced in the paper, which can obtain the parametric beam model via Autodesk Revit API from total station points and terrestrial laser scanning data. The results show the potential of automatizing the parametric modelling by interactive API development in BIM environment. It also integrates the separate data processing and different platforms into the uniform Revit software.
Parametric model to estimate containment loads following an ex-vessel steam spike
International Nuclear Information System (INIS)
Lopez, R.; Hernandez, J.; Huerta, A.
1998-01-01
This paper describes the use of a relatively simple parametric model to estimate containment loads following an ex-vessel steam spike. The study was motivated because several PSAs have identified containment loads accompanying reactor vessel failures as a major contributor to early containment failure. The paper includes a detailed description of the simple but physically sound parametric model which was adopted to estimate containment loads following a steam spike into the reactor cavity. (author)
Parametric level correlations in random-matrix models
International Nuclear Information System (INIS)
Weidenmueller, Hans A
2005-01-01
We show that parametric level correlations in random-matrix theories are closely related to a breaking of the symmetry between the advanced and the retarded Green functions. The form of the parametric level correlation function is the same as for the disordered case considered earlier by Simons and Altshuler and is given by the graded trace of the commutator of the saddle-point solution with the particular matrix that describes the symmetry breaking in the actual case of interest. The strength factor differs from the case of disorder. It is determined solely by the Goldstone mode. It is essentially given by the number of levels that are strongly mixed as the external parameter changes. The factor can easily be estimated in applications
Parametric Covariance Model for Horizon-Based Optical Navigation
Hikes, Jacob; Liounis, Andrew J.; Christian, John A.
2016-01-01
This Note presents an entirely parametric version of the covariance for horizon-based optical navigation measurements. The covariance can be written as a function of only the spacecraft position, two sensor design parameters, the illumination direction, the size of the observed planet, the size of the lit arc to be used, and the total number of observed horizon points. As a result, one may now more clearly understand the sensitivity of horizon-based optical navigation performance as a function of these key design parameters, which is insight that was obscured in previous (and nonparametric) versions of the covariance. Finally, the new parametric covariance is shown to agree with both the nonparametric analytic covariance and results from a Monte Carlo analysis.
Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory
Dees, Patrick D.; Zwack, Matthew R.; Edwards, Stephen; Steffens, Michael
2016-01-01
into Conceptual and Pre-Conceptual design, knowledge of the effects originating from changes to the vehicle must be calculated. In order to do this, a model capable of quantitatively describing any vehicle within the entire design space under consideration must be constructed. This model must be based upon analysis of acceptable fidelity, which in this work comes from POST. Design space interrogation can be achieved with surrogate modeling, a parametric, polynomial equation representing a tool. A surrogate model must be informed by data from the tool with enough points to represent the solution space for the chosen number of variables with an acceptable level of error. Therefore, Design Of Experiments (DOE) is used to select points within the design space to maximize information gained on the design space while minimizing number of data points required. To represent a design space with a non-trivial number of variable parameters the number of points required still represent an amount of work which would take an inordinate amount of time via the current paradigm of manual analysis, and so an automated method was developed. The best practices of expert trajectory analysts working within NASA Marshall's Advanced Concepts Office (ACO) were implemented within a tool called multiPOST. These practices include how to use the output data from a previous run of POST to inform the next, determining whether a trajectory solution is feasible from a real-world perspective, and how to handle program execution errors. The tool was then augmented with multiprocessing capability to enable analysis on multiple trajectories simultaneously, allowing throughput to scale with available computational resources. In this update to the previous work the authors discuss issues with the method and solutions.
Parametric amplification of metric fluctuations during reheating in two field models
International Nuclear Information System (INIS)
Finelli, F.; Brandenberger, R.
2000-01-01
We study the parametric amplification of super-Hubble-scale scalar metric fluctuations at the end of inflation in some specific two-field models of inflation, a class of which is motivated by hybrid inflation. We demonstrate that there can indeed be a large growth of fluctuations due to parametric resonance and that this effect is not taken into account by the conventional theory of isocurvature perturbations. Scalar field interactions play a crucial role in this analysis. We discuss the conditions under which there can be nontrivial parametric resonance effects on large scales
Theory of fluctuations and parametric noise in a point nuclear reactor model
International Nuclear Information System (INIS)
Rodriguez, M.A.; San Miguel, M.; Sancho, J.M.
1984-01-01
We present a joint description of internal fluctuations and parametric noise in a point nuclear reactor model in which delayed neutrons and a detector are considered. We obtain kinetic equations for the first moments and define effective kinetic parameters which take into account the effect of parametric Gaussian white noise. We comment on the validity of Langevin approximations for this problem. We propose a general method to deal with weak but otherwise arbitrary non-white parametric noise. Exact kinetic equations are derived for Gaussian non-white noise. (author)
International Nuclear Information System (INIS)
Gorecki, Paul K.
2013-01-01
The all-island wholesale electricity market, SEM, has to comply with the Target Model by 2016. SEM has worked well for consumers through mitigating market power, facilitating entry and ensuring adequate generation capacity, problems that will persist. But the SEM is a mandatory pool with central dispatch, the Target Model is a self dispatch with bilateral contracts. Minimal change to the SEM in complying with the Target Model is preferable to reinvention of SEM. The latter option might be appropriate when the EU internal electricity market is complete and the all-island market has sufficient interconnection to participate fully in that market. - Highlights: ► The Single Electricity Market (SEM) has worked well for consumers in Ireland. ► The SEM has to conform to the Target Model (TM) by 2016. ► The SEM is mandatory pool/central dispatch; the TM is bilateral contracts/self dispatch. ► Ensuring compliance with TM is best achieved through minimal change to SEM. ► Far reaching change is more appropriate once SEM is fully integrated in the EU electricity market.
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.
Research on Mixer Parametric Modeling System Based on Redevelopment of ANSYS
Directory of Open Access Journals (Sweden)
Bin Zheng
2015-01-01
Full Text Available In this paper, the mixer parametric modeling system software was developed by using VB which was taken as the foreground development program, and the paper combined with ANSYS software to create the finite element model of mixer blade and cylinder for the following numerical simulation of the flow field and parameter optimization of mixer. The software user interface was developed by VB and the pre-process model was created by invoking APDL of ANSYS in background. Therefore, the operation of modeling, meshing, component-building of mixer blade and cylinder were completed by using APDL and the graphic and text were outputted and displayed on the mixer parametric modeling system user interface which was developed by VB. Practice proved that it is convenient to modify the mixer solid model created by the parametric design language of ANSYS due to the similar structure.
Simulation of parametric model towards the fixed covariate of right censored lung cancer data
Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Ridwan Olaniran, Oyebayo; Enera Amran, Syahila
2017-09-01
In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.
Modeling of Acoustic Field for a Parametric Focusing Source Using the Spheroidal Beam Equation
Directory of Open Access Journals (Sweden)
Yu Lili
2015-09-01
Full Text Available A theoretical model of acoustic field for a parametric focusing source on concave spherical surface is proposed. In this model, the source boundary conditions of the Spheroidal Beam Equation (SBE for difference frequency wave excitation were studied. Propagation curves and beam patterns for difference frequency component of the acoustic field are compared with those obtained for Khokhlov-Zabolotskaya-Kuznetsov (KZK model. The results demonstrate that the focused parametric model of SBE is good valid for a large aperture angle in the strongly focused acoustic field. It is also investigated that high directivity and good focal ability with the decreasing of downshift ratio and the increasing of half-aperture angle for the focused parametric model of SBE.
Whitening of Background Brain Activity via Parametric Modeling
Directory of Open Access Journals (Sweden)
Nidal Kamel
2007-01-01
Full Text Available Several signal subspace techniques have been recently suggested for the extraction of the visual evoked potential signals from brain background colored noise. The majority of these techniques assume the background noise as white, and for colored noise, it is suggested to be whitened, without further elaboration on how this might be done. In this paper, we investigate the whitening capabilities of two parametric techniques: a direct one based on Levinson solution of Yule-Walker equations, called AR Yule-Walker, and an indirect one based on the least-squares solution of forward-backward linear prediction (FBLP equations, called AR-FBLP. The whitening effect of the two algorithms is investigated with real background electroencephalogram (EEG colored noise and compared in time and frequency domains.
International Nuclear Information System (INIS)
Valdés, José R.; Rodríguez, José M.; Saumell, Javier; Pütz, Thomas
2014-01-01
Highlights: • We develop a methodology for the parametric modelling of flow in hydraulic valves. • We characterize the flow coefficients with a generic function with two parameters. • The parameters are derived from CFD simulations of the generic geometry. • We apply the methodology to two cases from the automotive brake industry. • We validate by comparing with CFD results varying the original dimensions. - Abstract: The main objective of this work is to develop a methodology for the parametric modelling of the flow rate in hydraulic valve systems. This methodology is based on the derivation, from CFD simulations, of the flow coefficient of the critical restrictions as a function of the Reynolds number, using a generalized square root function with two parameters. The methodology is then demonstrated by applying it to two completely different hydraulic systems: a brake master cylinder and an ABS valve. This type of parametric valve models facilitates their implementation in dynamic simulation models of complex hydraulic systems
PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems
Liu, Haopeng; Zhu, Yunpeng; Luo, Zhong; Han, Qingkai
2017-09-01
In response to the identification problem concerning multi-degree of freedom (MDOF) nonlinear systems, this study presents the extended forward orthogonal regression (EFOR) based on predicted residual sums of squares (PRESS) to construct a nonlinear dynamic parametrical model. The proposed parametrical model is based on the non-linear autoregressive with exogenous inputs (NARX) model and aims to explicitly reveal the physical design parameters of the system. The PRESS-based EFOR algorithm is proposed to identify such a model for MDOF systems. By using the algorithm, we built a common-structured model based on the fundamental concept of evaluating its generalization capability through cross-validation. The resulting model aims to prevent over-fitting with poor generalization performance caused by the average error reduction ratio (AERR)-based EFOR algorithm. Then, a functional relationship is established between the coefficients of the terms and the design parameters of the unified model. Moreover, a 5-DOF nonlinear system is taken as a case to illustrate the modeling of the proposed algorithm. Finally, a dynamic parametrical model of a cantilever beam is constructed from experimental data. Results indicate that the dynamic parametrical model of nonlinear systems, which depends on the PRESS-based EFOR, can accurately predict the output response, thus providing a theoretical basis for the optimal design of modeling methods for MDOF nonlinear systems.
Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data.
Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao
2013-01-01
Generalized nonparametric additive models present a flexible way to evaluate the effects of several covariates on a general outcome of interest via a link function. In this modeling framework, one assumes that the effect of each of the covariates is nonparametric and additive. However, in practice, often there is prior information available about the shape of the regression functions, possibly from pilot studies or exploratory analysis. In this paper, we consider such situations and propose an estimation procedure where the prior information is used as a parametric guide to fit the additive model. Specifically, we first posit a parametric family for each of the regression functions using the prior information (parametric guides). After removing these parametric trends, we then estimate the remainder of the nonparametric functions using a nonparametric generalized additive model, and form the final estimates by adding back the parametric trend. We investigate the asymptotic properties of the estimates and show that when a good guide is chosen, the asymptotic variance of the estimates can be reduced significantly while keeping the asymptotic variance same as the unguided estimator. We observe the performance of our method via a simulation study and demonstrate our method by applying to a real data set on mergers and acquisitions.
Parametrizing coarse grained models for molecular systems at equilibrium
Kalligiannaki, Evangelia; Chazirakis, A.; Tsourtis, A.; Katsoulakis, M. A.; Plechá č, P.; Harmandaris, V.
2016-01-01
Hierarchical coarse graining of atomistic molecular systems at equilibrium has been an intensive research topic over the last few decades. In this work we (a) review theoretical and numerical aspects of different parametrization methods (structural-based, force matching and relative entropy) to derive the effective interaction potential between coarse-grained particles. All methods approximate the many body potential of mean force; resulting, however, in different optimization problems. (b) We also use a reformulation of the force matching method by introducing a generalized force matching condition for the local mean force in the sense that allows the approximation of the potential of mean force under both linear and non-linear coarse graining mappings (E. Kalligiannaki, et al., J. Chem. Phys. 2015). We apply and compare these methods to: (a) a benchmark system of two isolated methane molecules; (b) methane liquid; (c) water; and (d) an alkane fluid. Differences between the effective interactions, derived from the various methods, are found that depend on the actual system under study. The results further reveal the relation of the various methods and the sensitivities that may arise in the implementation of numerical methods used in each case.
Parametrizing coarse grained models for molecular systems at equilibrium
Kalligiannaki, Evangelia
2016-10-18
Hierarchical coarse graining of atomistic molecular systems at equilibrium has been an intensive research topic over the last few decades. In this work we (a) review theoretical and numerical aspects of different parametrization methods (structural-based, force matching and relative entropy) to derive the effective interaction potential between coarse-grained particles. All methods approximate the many body potential of mean force; resulting, however, in different optimization problems. (b) We also use a reformulation of the force matching method by introducing a generalized force matching condition for the local mean force in the sense that allows the approximation of the potential of mean force under both linear and non-linear coarse graining mappings (E. Kalligiannaki, et al., J. Chem. Phys. 2015). We apply and compare these methods to: (a) a benchmark system of two isolated methane molecules; (b) methane liquid; (c) water; and (d) an alkane fluid. Differences between the effective interactions, derived from the various methods, are found that depend on the actual system under study. The results further reveal the relation of the various methods and the sensitivities that may arise in the implementation of numerical methods used in each case.
Modeling and Validation across Scales: Parametrizing the effect of the forested landscape
DEFF Research Database (Denmark)
Dellwik, Ebba; Badger, Merete; Angelou, Nikolas
be transferred into a parametrization of forests in wind models. The presentation covers three scales: the single tree, the forest edges and clearings, and the large-scale forested landscape in which the forest effects are parameterized with a roughness length. Flow modeling results and validation against...
Evaluating Portfolio Value-At-Risk Using Semi-Parametric GARCH Models
J.V.K. Rombouts; M.J.C.M. Verbeek (Marno)
2009-01-01
textabstractIn this paper we examine the usefulness of multivariate semi-parametric GARCH models for evaluating the Value-at-Risk (VaR) of a portfolio with arbitrary weights. We specify and estimate several alternative multivariate GARCH models for daily returns on the S&P 500 and Nasdaq indexes.
A non-parametric hierarchical model to discover behavior dynamics from tracks
Kooij, J.F.P.; Englebienne, G.; Gavrila, D.M.
2012-01-01
We present a novel non-parametric Bayesian model to jointly discover the dynamics of low-level actions and high-level behaviors of tracked people in open environments. Our model represents behaviors as Markov chains of actions which capture high-level temporal dynamics. Actions may be shared by
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
Directory of Open Access Journals (Sweden)
Jinchao Feng
2018-03-01
Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
International Nuclear Information System (INIS)
Kim, Su Jin; Lee, Jae Sung; Kim, Yu Kyeong; Lee, Dong Soo
2007-01-01
Parametric imaging allows us analysis of the entire brain or body image. Graphical approaches are commonly employed to generate parametric imaging through linear or multilinear regression. However, this linear regression method has limited accuracy due to bias in high level of noise data. Several methods have been proposed to reduce bias for linear regression estimation especially in reversible model. In this study, we focus on generating a net accumulation rate (K i ), which is related to binding parameter in brain receptor study, parametric imaging in an irreversible compartment model using multiple linear analysis. The reliability of a newly developed multiple linear analysis method (MLAIR) was assessed through the Monte Carlo simulation, and we applied it to a [ 11 C]MeNTI PET for opioid receptor
Han, Feng; Zheng, Yi
2018-06-01
Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.
Nonlinear Container Ship Model for the Study of Parametric Roll Resonance
Directory of Open Access Journals (Sweden)
Christian Holden
2007-10-01
Full Text Available Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to +-40 degrees, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head seas. A Matlab/Simulink parametric roll benchmark model for a large container ship has been implemented and validated against a wide set of experimental data. The model is a part of a Matlab/Simulink Toolbox (MSS, 2007. The benchmark implements a 3rd-order nonlinear model where the dynamics of roll is strongly coupled with the heave and pitch dynamics. The implemented model has shown good accuracy in predicting the container ship motions, both in the vertical plane and in the transversal one. Parametric roll has been reproduced for all the data sets in which it happened, and the model provides realistic results which are in good agreement with the model tank experiments.
International Nuclear Information System (INIS)
Shafieloo, Arman
2012-01-01
By introducing Crossing functions and hyper-parameters I show that the Bayesian interpretation of the Crossing Statistics [1] can be used trivially for the purpose of model selection among cosmological models. In this approach to falsify a cosmological model there is no need to compare it with other models or assume any particular form of parametrization for the cosmological quantities like luminosity distance, Hubble parameter or equation of state of dark energy. Instead, hyper-parameters of Crossing functions perform as discriminators between correct and wrong models. Using this approach one can falsify any assumed cosmological model without putting priors on the underlying actual model of the universe and its parameters, hence the issue of dark energy parametrization is resolved. It will be also shown that the sensitivity of the method to the intrinsic dispersion of the data is small that is another important characteristic of the method in testing cosmological models dealing with data with high uncertainties
A Parametric Computational Model of the Action Potential of Pacemaker Cells.
Ai, Weiwei; Patel, Nitish D; Roop, Partha S; Malik, Avinash; Andalam, Sidharta; Yip, Eugene; Allen, Nathan; Trew, Mark L
2018-01-01
A flexible, efficient, and verifiable pacemaker cell model is essential to the design of real-time virtual hearts that can be used for closed-loop validation of cardiac devices. A new parametric model of pacemaker action potential is developed to address this need. The action potential phases are modeled using hybrid automaton with one piecewise-linear continuous variable. The model can capture rate-dependent dynamics, such as action potential duration restitution, conduction velocity restitution, and overdrive suppression by incorporating nonlinear update functions. Simulated dynamics of the model compared well with previous models and clinical data. The results show that the parametric model can reproduce the electrophysiological dynamics of a variety of pacemaker cells, such as sinoatrial node, atrioventricular node, and the His-Purkinje system, under varying cardiac conditions. This is an important contribution toward closed-loop validation of cardiac devices using real-time heart models.
Preliminary Multi-Variable Parametric Cost Model for Space Telescopes
Stahl, H. Philip; Hendrichs, Todd
2010-01-01
This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.
The numerical model for parametric studies of forest haul roads pavements
Directory of Open Access Journals (Sweden)
Lenka Ševelová
2010-01-01
Full Text Available Forest roads pavement structures are considered to be low volume roads. These roads serve as a mean of transport of wood and people. Besides they are currently often used for recreational purpose. The construction of the pavements should be suitable for forest transportation irrespective of their low bearing capacity. These pavement structures are very specific for special unbound materials that are used in their construction. To meet the requirements of the pavement designs and simulation analysis the FEM model in the software ANSYS was created.This paper compares two material models used for the description of the behaviour of unbound materials. The first is linear elastic according to Hook theory (H model and the second one is nonlinear plastic model Drucker-Prager (D–P model. ANSYS software has been used to create flexible model based on the parametrers of variable principle. The flexible model is parametric to realize repeated calculations useful for optimization analysis.
Galindo-Garre, Francisca; Hidalgo, María Dolores; Guilera, Georgina; Pino, Oscar; Rojo, J Emilio; Gómez-Benito, Juana
2015-03-01
The World Health Organization Disability Assessment Schedule II (WHO-DAS II) is a multidimensional instrument developed for measuring disability. It comprises six domains (getting around, self-care, getting along with others, life activities and participation in society). The main purpose of this paper is the evaluation of the psychometric properties for each domain of the WHO-DAS II with parametric and non-parametric Item Response Theory (IRT) models. A secondary objective is to assess whether the WHO-DAS II items within each domain form a hierarchy of invariantly ordered severity indicators of disability. A sample of 352 patients with a schizophrenia spectrum disorder is used in this study. The 36 items WHO-DAS II was administered during the consultation. Partial Credit and Mokken scale models are used to study the psychometric properties of the questionnaire. The psychometric properties of the WHO-DAS II scale are satisfactory for all the domains. However, we identify a few items that do not discriminate satisfactorily between different levels of disability and cannot be invariantly ordered in the scale. In conclusion the WHO-DAS II can be used to assess overall disability in patients with schizophrenia, but some domains are too general to assess functionality in these patients because they contain items that are not applicable to this pathology. Copyright © 2014 John Wiley & Sons, Ltd.
Oude Lansink, A.G.J.M.; Pietola, K.
2005-01-01
This paper applies a semi-parametric approach to estimating a generalised model of investments in heating installations. The results suggest that marginal costs of investments in heating installations increase quickly at small investment levels, whereas the increase slows down at higher investment
Exploring location influences on firm survival rates using parametric duration models
Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.; Timmermans, H.J.P.; Vries, de B.
2010-01-01
Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and
Exploring location influences on firm survival rates using parametric duration models
Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.
2011-01-01
Using parametric duration models applied to an office firm dataset, we carried out an exploratory study about the location influences on firm survival rates. Amongst the variables included, we found that accessibility to infrastructure supply, regional effects, demographic and economic aspects, and
Exploration of location influences on firm survival rates using parametric duration models
Manzato, G.G.; Arentze, T.A.; Timmermans, H.J.P.; Ettema, D.F.
2011-01-01
This study explored the influences of location on business firm survival rates with the use of parametric duration models applied to a data set. Of the variables included, those found to be the most significant were accessibility to infrastructure supply, regional effects, demographic and economic
The Support Reduction Algorithm for Computing Non-Parametric Function Estimates in Mixture Models
GROENEBOOM, PIET; JONGBLOED, GEURT; WELLNER, JON A.
2008-01-01
In this paper, we study an algorithm (which we call the support reduction algorithm) that can be used to compute non-parametric M-estimators in mixture models. The algorithm is compared with natural competitors in the context of convex regression and the ‘Aspect problem’ in quantum physics.
A comparative study of non-parametric models for identification of ...
African Journals Online (AJOL)
However, the frequency response method using random binary signals was good for unpredicted white noise characteristics and considered the best method for non-parametric system identifica-tion. The autoregressive external input (ARX) model was very useful for system identification, but on applicati-on, few input ...
Brown, Gregory G; Thomas, Michael L; Patt, Virginie
Neuropsychology is an applied measurement field with its psychometric work primarily built upon classical test theory (CTT). We describe a series of psychometric models to supplement the use of CTT in neuropsychological research and test development. We introduce increasingly complex psychometric models as measurement algebras, which include model parameters that represent abilities and item properties. Within this framework of parametric model measurement (PMM), neuropsychological assessment involves the estimation of model parameters with ability parameter values assuming the role of test 'scores'. Moreover, the traditional notion of measurement error is replaced by the notion of parameter estimation error, and the definition of reliability becomes linked to notions of item and test information. The more complex PMM approaches incorporate into the assessment of neuropsychological performance formal parametric models of behavior validated in the experimental psychology literature, along with item parameters. These PMM approaches endorse the use of experimental manipulations of model parameters to assess a test's construct representation. Strengths and weaknesses of these models are evaluated by their implications for measurement error conditional upon ability level, sensitivity to sample characteristics, computational challenges to parameter estimation, and construct validity. A family of parametric psychometric models can be used to assess latent processes of interest to neuropsychologists. By modeling latent abilities at the item level, psychometric studies in neuropsychology can investigate construct validity and measurement precision within a single framework and contribute to a unification of statistical methods within the framework of generalized latent variable modeling.
A Parametric Factor Model of the Term Structure of Mortality
DEFF Research Database (Denmark)
Haldrup, Niels; Rosenskjold, Carsten Paysen T.
The prototypical Lee-Carter mortality model is characterized by a single common time factor that loads differently across age groups. In this paper we propose a factor model for the term structure of mortality where multiple factors are designed to influence the age groups differently via...... on the loading functions, the factors are not designed to be orthogonal but can be dependent and can possibly cointegrate when the factors have unit roots. We suggest two estimation procedures similar to the estimation of the dynamic Nelson-Siegel term structure model. First, a two-step nonlinear least squares...... procedure based on cross-section regressions together with a separate model to estimate the dynamics of the factors. Second, we suggest a fully specified model estimated by maximum likelihood via the Kalman filter recursions after the model is put on state space form. We demonstrate the methodology for US...
Cardiovascular oscillations: in search of a nonlinear parametric model
Bandrivskyy, Andriy; Luchinsky, Dmitry; McClintock, Peter V.; Smelyanskiy, Vadim; Stefanovska, Aneta; Timucin, Dogan
2003-05-01
We suggest a fresh approach to the modeling of the human cardiovascular system. Taking advantage of a new Bayesian inference technique, able to deal with stochastic nonlinear systems, we show that one can estimate parameters for models of the cardiovascular system directly from measured time series. We present preliminary results of inference of parameters of a model of coupled oscillators from measured cardiovascular data addressing cardiorespiratory interaction. We argue that the inference technique offers a very promising tool for the modeling, able to contribute significantly towards the solution of a long standing challenge -- development of new diagnostic techniques based on noninvasive measurements.
Directory of Open Access Journals (Sweden)
Ibsen Chivatá Cárdenas
2008-05-01
Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions
A generalized Jaynes-Cummings model: The relativistic parametric amplifier and a single trapped ion
Energy Technology Data Exchange (ETDEWEB)
Ojeda-Guillén, D., E-mail: dojedag@ipn.mx [Escuela Superior de Cómputo, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz esq. Av. Miguel Othón de Mendizábal, Col. Lindavista, Delegación Gustavo A. Madero, C.P. 07738 Ciudad de México (Mexico); Mota, R. D. [Escuela Superior de Ingeniería Mecánica y Eléctrica, Unidad Culhuacán, Instituto Politécnico Nacional, Av. Santa Ana No. 1000, Col. San Francisco Culhuacán, Delegación Coyoacán, C.P. 04430 Ciudad de México (Mexico); Granados, V. D. [Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, Ed. 9, Unidad Profesional Adolfo López Mateos, Delegación Gustavo A. Madero, C.P. 07738 Ciudad de México (Mexico)
2016-06-15
We introduce a generalization of the Jaynes-Cummings model and study some of its properties. We obtain the energy spectrum and eigenfunctions of this model by using the tilting transformation and the squeezed number states of the one-dimensional harmonic oscillator. As physical applications, we connect this new model to two important and novelty problems: the relativistic parametric amplifier and the quantum simulation of a single trapped ion.
Integrating acoustic analysis in the architectural design process using parametric modelling
DEFF Research Database (Denmark)
Peters, Brady
2011-01-01
This paper discusses how parametric modeling techniques can be used to provide architectural designers with a better understanding of the acoustic performance of their designs and provide acoustic engineers with models that can be analyzed using computational acoustic analysis software. Architects......, acoustic performance can inform the geometry and material logic of the design. In this way, the architectural design and the acoustic analysis model become linked....
Assessing scenario and parametric uncertainties in risk analysis: a model uncertainty audit
International Nuclear Information System (INIS)
Tarantola, S.; Saltelli, A.; Draper, D.
1999-01-01
In the present study a process of model audit is addressed on a computational model used for predicting maximum radiological doses to humans in the field of nuclear waste disposal. Global uncertainty and sensitivity analyses are employed to assess output uncertainty and to quantify the contribution of parametric and scenario uncertainties to the model output. These tools are of fundamental importance for risk analysis and decision making purposes
Moore, Julia L; Remais, Justin V
2014-03-01
Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.
Parametric Sensitivity Analysis of the WAVEWATCH III Model
Directory of Open Access Journals (Sweden)
Beng-Chun Lee
2009-01-01
Full Text Available The parameters in numerical wave models need to be calibrated be fore a model can be applied to a specific region. In this study, we selected the 8 most important parameters from the source term of the WAVEWATCH III model and subjected them to sensitivity analysis to evaluate the sensitivity of the WAVEWATCH III model to the selected parameters to determine how many of these parameters should be considered for further discussion, and to justify the significance priority of each parameter. After ranking each parameter by sensitivity and assessing their cumulative impact, we adopted the ARS method to search for the optimal values of those parameters to which the WAVEWATCH III model is most sensitive by comparing modeling results with ob served data at two data buoys off the coast of north eastern Taiwan; the goal being to find optimal parameter values for improved modeling of wave development. The procedure adopting optimal parameters in wave simulations did improve the accuracy of the WAVEWATCH III model in comparison to default runs based on field observations at two buoys.
Evaluation of wave runup predictions from numerical and parametric models
Stockdon, Hilary F.; Thompson, David M.; Plant, Nathaniel G.; Long, Joseph W.
2014-01-01
Wave runup during storms is a primary driver of coastal evolution, including shoreline and dune erosion and barrier island overwash. Runup and its components, setup and swash, can be predicted from a parameterized model that was developed by comparing runup observations to offshore wave height, wave period, and local beach slope. Because observations during extreme storms are often unavailable, a numerical model is used to simulate the storm-driven runup to compare to the parameterized model and then develop an approach to improve the accuracy of the parameterization. Numerically simulated and parameterized runup were compared to observations to evaluate model accuracies. The analysis demonstrated that setup was accurately predicted by both the parameterized model and numerical simulations. Infragravity swash heights were most accurately predicted by the parameterized model. The numerical model suffered from bias and gain errors that depended on whether a one-dimensional or two-dimensional spatial domain was used. Nonetheless, all of the predictions were significantly correlated to the observations, implying that the systematic errors can be corrected. The numerical simulations did not resolve the incident-band swash motions, as expected, and the parameterized model performed best at predicting incident-band swash heights. An assimilated prediction using a weighted average of the parameterized model and the numerical simulations resulted in a reduction in prediction error variance. Finally, the numerical simulations were extended to include storm conditions that have not been previously observed. These results indicated that the parameterized predictions of setup may need modification for extreme conditions; numerical simulations can be used to extend the validity of the parameterized predictions of infragravity swash; and numerical simulations systematically underpredict incident swash, which is relatively unimportant under extreme conditions.
Numerical model of solar dynamic radiator for parametric analysis
Rhatigan, Jennifer L.
1989-01-01
Growth power requirements for Space Station Freedom will be met through addition of 25 kW solar dynamic (SD) power modules. Extensive thermal and power cycle modeling capabilities have been developed which are powerful tools in Station design and analysis, but which prove cumbersome and costly for simple component preliminary design studies. In order to aid in refining the SD radiator to the mature design stage, a simple and flexible numerical model was developed. The model simulates heat transfer and fluid flow performance of the radiator and calculates area mass and impact survivability for many combinations of flow tube and panel configurations, fluid and material properties, and environmental and cycle variations.
Analysis of survival in breast cancer patients by using different parametric models
Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti
2017-09-01
In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.
A parametric framework for modelling of bioelectrical signals
Mughal, Yar Muhammad
2016-01-01
This book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move...
Bifurcation analysis of parametrically excited bipolar disorder model
Nana, Laurent
2009-02-01
Bipolar II disorder is characterized by alternating hypomanic and major depressive episode. We model the periodic mood variations of a bipolar II patient with a negatively damped harmonic oscillator. The medications administrated to the patient are modeled via a forcing function that is capable of stabilizing the mood variations and of varying their amplitude. We analyze analytically, using perturbation method, the amplitude and stability of limit cycles and check this analysis with numerical simulations.
Principles of parametric estimation in modeling language competition.
Zhang, Menghan; Gong, Tao
2013-06-11
It is generally difficult to define reasonable parameters and interpret their values in mathematical models of social phenomena. Rather than directly fitting abstract parameters against empirical data, we should define some concrete parameters to denote the sociocultural factors relevant for particular phenomena, and compute the values of these parameters based upon the corresponding empirical data. Taking the example of modeling studies of language competition, we propose a language diffusion principle and two language inheritance principles to compute two critical parameters, namely the impacts and inheritance rates of competing languages, in our language competition model derived from the Lotka-Volterra competition model in evolutionary biology. These principles assign explicit sociolinguistic meanings to those parameters and calculate their values from the relevant data of population censuses and language surveys. Using four examples of language competition, we illustrate that our language competition model with thus-estimated parameter values can reliably replicate and predict the dynamics of language competition, and it is especially useful in cases lacking direct competition data.
Parametric modelling of temporal variations in radon concentrations in homes
International Nuclear Information System (INIS)
Revzan, K.L.; Turk, B.H.; Harrison, J.; Nero, A.V.; Sextro, R.G.
1988-01-01
The 222 Rn concentrations in the living area, the basement, and the undelying soil of a New Jersey home have been measured at half-hour intervals over the course of a year, as have indoor and outdoor temperatures, wind speed and direction, and indoor-outdoor and basement-subslab pressures; in addition, periods of furnace opration have been logged. We generalize and extend an existing radon entry model in order to demonstrate the dependence of the radon concentration on the environmental variales and the extent of furnace use. The model contains parameters which are dependent on geological and structural factors which have not been measured or otherwise determined; statistical methods are used to find the best values of the parameters. The non-linear regression of the model predictions (over time) on the measured living area radon concentrations yields an R/aup 2/ of 0.88. 9 refs., 2 figs
A parametric model for analyzing anticipation in genetically predisposed families
DEFF Research Database (Denmark)
Larsen, Klaus; Petersen, Janne; Bernstein, Inge
2009-01-01
and are sensitive to right truncation of the data. We propose a normal random effects model that allows for right-censored observations and includes covariates, and draw statistical inference based on the likelihood function. We applied the model to the hereditary nonpolyposis colorectal cancer (HNPCC)/Lynch...... syndrome family cohort from the national Danish HNPCC register. Age-at-onset was analyzed in 824 individuals from 2-4 generations in 125 families with proved disease-predisposing mutations. A significant effect from anticipation was identified with a mean of 3 years earlier age-at-onset per generation...
Determining input values for a simple parametric model to estimate ...
African Journals Online (AJOL)
Estimating soil evaporation (Es) is an important part of modelling vineyard evapotranspiration for irrigation purposes. Furthermore, quantification of possible soil texture and trellis effects is essential. Daily Es from six topsoils packed into lysimeters was measured under grapevines on slanting and vertical trellises, ...
Latest astronomical constraints on some non-linear parametric dark energy models
Yang, Weiqiang; Pan, Supriya; Paliathanasis, Andronikos
2018-04-01
We consider non-linear redshift-dependent equation of state parameters as dark energy models in a spatially flat Friedmann-Lemaître-Robertson-Walker universe. To depict the expansion history of the universe in such cosmological scenarios, we take into account the large-scale behaviour of such parametric models and fit them using a set of latest observational data with distinct origin that includes cosmic microwave background radiation, Supernove Type Ia, baryon acoustic oscillations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and finally the local Hubble constant from Hubble space telescope. The fitting technique avails the publicly available code Cosmological Monte Carlo (COSMOMC), to extract the cosmological information out of these parametric dark energy models. From our analysis, it follows that those models could describe the late time accelerating phase of the universe, while they are distinguished from the Λ-cosmology.
Comparison of radiation parametrizations within the HARMONIE-AROME NWP model
Rontu, Laura; Lindfors, Anders V.
2018-05-01
Downwelling shortwave radiation at the surface (SWDS, global solar radiation flux), given by three different parametrization schemes, was compared to observations in the HARMONIE-AROME numerical weather prediction (NWP) model experiments over Finland in spring 2017. Simulated fluxes agreed well with each other and with the observations in the clear-sky cases. In the cloudy-sky conditions, all schemes tended to underestimate SWDS at the daily level, as compared to the measurements. Large local and temporal differences between the model results and observations were seen, related to the variations and uncertainty of the predicted cloud properties. The results suggest a possibility to benefit from the use of different radiative transfer parametrizations in a NWP model to obtain perturbations for the fine-resolution ensemble prediction systems. In addition, we recommend usage of the global radiation observations for the standard validation of the NWP models.
Study of the long-term values and prices of plutonium; a simplified parametrized model
International Nuclear Information System (INIS)
Gaussens, J.; Paillot, H.
1965-01-01
The authors define the notions of use values and price of plutonium. They give a 'simplified parametrized model' simulating the equilibrium of the offer and the demand in time, concerning the plutonium and the price deriving from the relative scarcity of this metal, taking into account the technical and economic operating parameters of the various reactors confronted. This model is simple enough to allow direct computations and establish clear relations between the various parameters. The use of the linear programmes method allows on the other hand a wide extension of the model. This report includes three main parts: I - General description of the study (without detailed calculations) II - Mathematical development of the simplified parametrized model and application (the basic data and the results of the calculations are given) III - Appendices (giving the detailed computations of part II). (authors) [fr
A Neural Parametric Singing Synthesizer Modeling Timbre and Expression from Natural Songs
Directory of Open Access Journals (Sweden)
Merlijn Blaauw
2017-12-01
Full Text Available We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This allows conveniently modifying pitch to match any target melody, facilitates training on more modest dataset sizes, and significantly reduces training and generation times. Nonetheless, compared to modeling waveform directly, ways of effectively handling higher-dimensional outputs, multiple feature streams and regularization become more important with our approach. In this work, we extend our proposed system to include additional components for predicting F0 and phonetic timings from a musical score with lyrics. These expression-related features are learned together with timbrical features from a single set of natural songs. We compare our method to existing statistical parametric, concatenative, and neural network-based approaches using quantitative metrics as well as listening tests.
Scalability of the muscular action in a parametric 3D model of the index finger.
Sancho-Bru, Joaquín L; Vergara, Margarita; Rodríguez-Cervantes, Pablo-Jesús; Giurintano, David J; Pérez-González, Antonio
2008-01-01
A method for scaling the muscle action is proposed and used to achieve a 3D inverse dynamic model of the human finger with all its components scalable. This method is based on scaling the physiological cross-sectional area (PCSA) in a Hill muscle model. Different anthropometric parameters and maximal grip force data have been measured and their correlations have been analyzed and used for scaling the PCSA of each muscle. A linear relationship between the normalized PCSA and the product of the length and breadth of the hand has been finally used for scaling, with a slope of 0.01315 cm(-2), with the length and breadth of the hand expressed in centimeters. The parametric muscle model has been included in a parametric finger model previously developed by the authors, and it has been validated reproducing the results of an experiment in which subjects from different population groups exerted maximal voluntary forces with their index finger in a controlled posture.
Parametric reduced models for the nonlinear Schrödinger equation.
Harlim, John; Li, Xiantao
2015-05-01
Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-12-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.
Modelling and Simulation for Energy Production Parametric Dependence in Greenhouses
Directory of Open Access Journals (Sweden)
Maurizio Carlini
2010-01-01
Full Text Available Greenhouses crops in Italy are made by using prefabricated structures, leaving out the preliminary study of optical and thermal exchanges between the external environment and the greenhouse, dealing with heating and cooling and the effects of air conditioning needed for plant growth. This involves rather significant costs that directs the interest of designers, builders, and farmers in order to seek constructive solutions to optimize the system of such emissions. This work was done by building a model of gases using TRNSYS software, and these gases then have been checked for compliance. The model was constructed considering an example of a prefabricated greenhouse, located in central of Italy. Aspects of the structural components, and thermal and optical properties are analyzed in order to achieve a representation of reality.
Parametric modelling of correlation in a dense plasma
International Nuclear Information System (INIS)
Krikorian V, R.; Daveloza de K, S.
1982-01-01
A two-component-symmetric quantum plasma is analyzed. The collective repulsive effects are considered by means of models for the local structures, in their coordination shell, using partial distribution functions. The generalized expressions for the internal energy and equation of state of the system are presented, which reflect the local structure effects and guarantee the thermodynamic stability of the system. The only limit on the density is that due to the impenetrability of the particles. (L.C.) [pt
Nikulin, M; Mesbah, M; Limnios, N
2004-01-01
Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.
International Nuclear Information System (INIS)
Vu, H.X.; Bezzerides, B.; DuBois, D.F.
1999-01-01
A fully kinetic, reduced-description particle-in-cell (RPIC) model is presented in which deviations from quasineutrality, electron and ion kinetic effects, and nonlinear interactions between low-frequency and high-frequency parametric instabilities are modeled correctly. The model is based on a reduced description where the electromagnetic field is represented by three separate temporal envelopes in order to model parametric instabilities with low-frequency and high-frequency daughter waves. Because temporal envelope approximations are invoked, the simulation can be performed on the electron time scale instead of the time scale of the light waves. The electrons and ions are represented by discrete finite-size particles, permitting electron and ion kinetic effects to be modeled properly. The Poisson equation is utilized to ensure that space-charge effects are included. The RPIC model is fully three dimensional and has been implemented in two dimensions on the Accelerated Strategic Computing Initiative (ASCI) parallel computer at Los Alamos National Laboratory, and the resulting simulation code has been named ASPEN. The authors believe this code is the first particle-in-cell code capable of simulating the interaction between low-frequency and high-frequency parametric instabilities in multiple dimensions. Test simulations of stimulated Raman scattering, stimulated Brillouin scattering, and Langmuir decay instability are presented
Voorhoeve, R.J.; van der Maas, A.; Oomen, T.A.J.
2018-01-01
Frequency response function (FRF) identification is often used as a basis for control systems design and as a starting point for subsequent parametric system identification. The aim of this paper is to develop a multiple-input multiple-output (MIMO) local parametric modeling approach for FRF
Gan, Y.; Liang, X. Z.; Duan, Q.; Xu, J.; Zhao, P.; Hong, Y.
2017-12-01
The uncertainties associated with the parameters of a hydrological model need to be quantified and reduced for it to be useful for operational hydrological forecasting and decision support. An uncertainty quantification framework is presented to facilitate practical assessment and reduction of model parametric uncertainties. A case study, using the distributed hydrological model CREST for daily streamflow simulation during the period 2008-2010 over ten watershed, was used to demonstrate the performance of this new framework. Model behaviors across watersheds were analyzed by a two-stage stepwise sensitivity analysis procedure, using LH-OAT method for screening out insensitive parameters, followed by MARS-based Sobol' sensitivity indices for quantifying each parameter's contribution to the response variance due to its first-order and higher-order effects. Pareto optimal sets of the influential parameters were then found by the adaptive surrogate-based multi-objective optimization procedure, using MARS model for approximating the parameter-response relationship and SCE-UA algorithm for searching the optimal parameter sets of the adaptively updated surrogate model. The final optimal parameter sets were validated against the daily streamflow simulation of the same watersheds during the period 2011-2012. The stepwise sensitivity analysis procedure efficiently reduced the number of parameters that need to be calibrated from twelve to seven, which helps to limit the dimensionality of calibration problem and serves to enhance the efficiency of parameter calibration. The adaptive MARS-based multi-objective calibration exercise provided satisfactory solutions to the reproduction of the observed streamflow for all watersheds. The final optimal solutions showed significant improvement when compared to the default solutions, with about 65-90% reduction in 1-NSE and 60-95% reduction in |RB|. The validation exercise indicated a large improvement in model performance with about 40
FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES
Directory of Open Access Journals (Sweden)
U. S. Panday
2012-09-01
Full Text Available In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS data. This leads to inconsistent building outlines, which has a negative inﬂuence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of – 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for
Modeling and parametric analysis of a piezoelectric flexoelectric nanoactuator
Directory of Open Access Journals (Sweden)
Baroudi Sourour
2016-01-01
Full Text Available With the development of nanotechnology, nanoactuators have recently re-stimulated a surge of scientific interests in research communities. One of the interesting transduction mechanisms that showed high efficiency at the nanoscale was flexoelectricity. In fact, the flexoelectric effect in dielectric solids couples polarization and strain gradient, rather than polarization and strain for piezoelectricity, to convert mechanical stimulus into electricity and vice cersa. The objective of the current work is to develop a complete comprehensive electromechanical model of a nanobeam whose for piezoelectrically-actuated nanocantilever sensor in which both the flexoelectricity and piezoelectricity effects will be tzken into consideration. Starting from the enthalpy density function, the Hamilton’s principle is applied to drive the governing coupled equations with appropriate boundary conditions. Then, we investigate the free vibration of the mechanism by formulating the eigenvalue problem associated with the coupled partial differential equations. Using the Galerkin procedure we develop both the static and dynamic of our structure. The results show that a certain aspect ratio flexoelectric effect significantly increases the performance of the nanoactuator.
Oracle estimation of parametric models under boundary constraints.
Wong, Kin Yau; Goldberg, Yair; Fine, Jason P
2016-12-01
In many classical estimation problems, the parameter space has a boundary. In most cases, the standard asymptotic properties of the estimator do not hold when some of the underlying true parameters lie on the boundary. However, without knowledge of the true parameter values, confidence intervals constructed assuming that the parameters lie in the interior are generally over-conservative. A penalized estimation method is proposed in this article to address this issue. An adaptive lasso procedure is employed to shrink the parameters to the boundary, yielding oracle inference which adapt to whether or not the true parameters are on the boundary. When the true parameters are on the boundary, the inference is equivalent to that which would be achieved with a priori knowledge of the boundary, while if the converse is true, the inference is equivalent to that which is obtained in the interior of the parameter space. The method is demonstrated under two practical scenarios, namely the frailty survival model and linear regression with order-restricted parameters. Simulation studies and real data analyses show that the method performs well with realistic sample sizes and exhibits certain advantages over standard methods. © 2016, The International Biometric Society.
Two-parametric model of electron beam in computational dosimetry for radiation processing
International Nuclear Information System (INIS)
Lazurik, V.M.; Lazurik, V.T.; Popov, G.; Zimek, Z.
2016-01-01
Computer simulation of irradiation process of various materials with electron beam (EB) can be applied to correct and control the performances of radiation processing installations. Electron beam energy measurements methods are described in the international standards. The obtained results of measurements can be extended by implementation computational dosimetry. Authors have developed the computational method for determination of EB energy on the base of two-parametric fitting of semi-empirical model for the depth dose distribution initiated by mono-energetic electron beam. The analysis of number experiments show that described method can effectively consider random displacements arising from the use of aluminum wedge with a continuous strip of dosimetric film and minimize the magnitude uncertainty value of the electron energy evaluation, calculated from the experimental data. Two-parametric fitting method is proposed for determination of the electron beam model parameters. These model parameters are as follow: E 0 – energy mono-energetic and mono-directional electron source, X 0 – the thickness of the aluminum layer, located in front of irradiated object. That allows obtain baseline data related to the characteristic of the electron beam, which can be later on applied for computer modeling of the irradiation process. Model parameters which are defined in the international standards (like E p – the most probably energy and R p – practical range) can be linked with characteristics of two-parametric model (E 0 , X 0 ), which allows to simulate the electron irradiation process. The obtained data from semi-empirical model were checked together with the set of experimental results. The proposed two-parametric model for electron beam energy evaluation and estimation of accuracy for computational dosimetry methods on the base of developed model are discussed. - Highlights: • Experimental and computational methods of electron energy evaluation. • Development
A Hybrid Wind-Farm Parametrization for Mesoscale and Climate Models
Pan, Yang; Archer, Cristina L.
2018-04-01
To better understand the potential impact of wind farms on weather and climate at the regional to global scales, a new hybrid wind-farm parametrization is proposed for mesoscale and climate models. The proposed parametrization is a hybrid model because it is not based on physical processes or conservation laws, but on the multiple linear regression of the results of large-eddy simulations (LES) with the geometric properties of the wind-farm layout (e.g., the blockage ratio and blockage distance). The innovative aspect is that each wind turbine is treated individually based on its position in the farm and on the wind direction by predicting the velocity upstream of each turbine. The turbine-induced forces and added turbulence kinetic energy (TKE) are first derived analytically and then implemented in the Weather Research and Forecasting model. Idealized simulations of the offshore Lillgrund wind farm are conducted. The wind-speed deficit and TKE predicted with the hybrid model are in excellent agreement with those from the LES results, while the wind-power production estimated with the hybrid model is within 10% of that observed. Three additional wind farms with larger inter-turbine spacing than at Lillgrund are also considered, and a similar agreement with LES results is found, proving that the hybrid parametrization works well with any wind farm regardless of the spacing between turbines. These results indicate the wind-turbine position, wind direction, and added TKE are essential in accounting for the wind-farm effects on the surroundings, for which the hybrid wind-farm parametrization is a promising tool.
International Nuclear Information System (INIS)
Lefieux, V.
2007-10-01
Reseau de Transport d'Electricite (RTE), in charge of operating the French electric transportation grid, needs an accurate forecast of the power consumption in order to operate it correctly. The forecasts used everyday result from a model combining a nonlinear parametric regression and a SARIMA model. In order to obtain an adaptive forecasting model, nonparametric forecasting methods have already been tested without real success. In particular, it is known that a nonparametric predictor behaves badly with a great number of explanatory variables, what is commonly called the curse of dimensionality. Recently, semi parametric methods which improve the pure nonparametric approach have been proposed to estimate a regression function. Based on the concept of 'dimension reduction', one those methods (called MAVE : Moving Average -conditional- Variance Estimate) can apply to time series. We study empirically its effectiveness to predict the future values of an autoregressive time series. We then adapt this method, from a practical point of view, to forecast power consumption. We propose a partially linear semi parametric model, based on the MAVE method, which allows to take into account simultaneously the autoregressive aspect of the problem and the exogenous variables. The proposed estimation procedure is practically efficient. (author)
Towards the generation of a parametric foot model using principal component analysis: A pilot study.
Scarton, Alessandra; Sawacha, Zimi; Cobelli, Claudio; Li, Xinshan
2016-06-01
There have been many recent developments in patient-specific models with their potential to provide more information on the human pathophysiology and the increase in computational power. However they are not yet successfully applied in a clinical setting. One of the main challenges is the time required for mesh creation, which is difficult to automate. The development of parametric models by means of the Principle Component Analysis (PCA) represents an appealing solution. In this study PCA has been applied to the feet of a small cohort of diabetic and healthy subjects, in order to evaluate the possibility of developing parametric foot models, and to use them to identify variations and similarities between the two populations. Both the skin and the first metatarsal bones have been examined. Besides the reduced sample of subjects considered in the analysis, results demonstrated that the method adopted herein constitutes a first step towards the realization of a parametric foot models for biomechanical analysis. Furthermore the study showed that the methodology can successfully describe features in the foot, and evaluate differences in the shape of healthy and diabetic subjects. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.
Bioprocess iterative batch-to-batch optimization based on hybrid parametric/nonparametric models.
Teixeira, Ana P; Clemente, João J; Cunha, António E; Carrondo, Manuel J T; Oliveira, Rui
2006-01-01
This paper presents a novel method for iterative batch-to-batch dynamic optimization of bioprocesses. The relationship between process performance and control inputs is established by means of hybrid grey-box models combining parametric and nonparametric structures. The bioreactor dynamics are defined by material balance equations, whereas the cell population subsystem is represented by an adjustable mixture of nonparametric and parametric models. Thus optimizations are possible without detailed mechanistic knowledge concerning the biological system. A clustering technique is used to supervise the reliability of the nonparametric subsystem during the optimization. Whenever the nonparametric outputs are unreliable, the objective function is penalized. The technique was evaluated with three simulation case studies. The overall results suggest that the convergence to the optimal process performance may be achieved after a small number of batches. The model unreliability risk constraint along with sampling scheduling are crucial to minimize the experimental effort required to attain a given process performance. In general terms, it may be concluded that the proposed method broadens the application of the hybrid parametric/nonparametric modeling technique to "newer" processes with higher potential for optimization.
Rate-dependent extensions of the parametric magneto-dynamic model with magnetic hysteresis
Directory of Open Access Journals (Sweden)
S. Steentjes
2017-05-01
Full Text Available This paper extends the parametric magneto-dynamic model of soft magnetic steel sheets to account for the phase shift between local magnetic flux density and magnetic field strength. This phase shift originates from the damped motion of domain walls and is strongly dependent on the microstructure of the material. In this regard, two different approaches to include the rate-dependent effects are investigated: a purely phenomenological, mathematical approach and a physical-based one.
Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes
2012-11-01
2012 4. TITLE AND SUBTITLE Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes 5a. CONTRACT NUMBER 5b. GRANT ...may be used to construct spatially varying wind fields for the GOM region (e.g., Thompson and Cardone [12]), but this requires using a complicated...Storm Damage Reduc- tion, and Dredging Operations and Environmental Research (DOER). The USACE Headquarters granted permission to publish this paper
Neugebauer, Romain; Fireman, Bruce; Roy, Jason A; Raebel, Marsha A; Nichols, Gregory A; O'Connor, Patrick J
2013-08-01
Clinical trials are unlikely to ever be launched for many comparative effectiveness research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data, but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called super learning (SL) to avoid reliance on arbitrary parametric assumptions in CER. Using the electronic health records data from adults with new-onset type 2 diabetes, we implemented MSM with inverse probability weighting (IPW) estimation to evaluate the effect of three oral antidiabetic therapies on the worsening of glomerular filtration rate. Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, that is, time-dependent measurements of hemoglobin A1c. SL was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms. Erroneous IPW inference about clinical effectiveness because of arbitrary and incorrect modeling decisions may be avoided with SL. Copyright © 2013 Elsevier Inc. All rights reserved.
Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.
2018-01-01
This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.
Using an Autonomous Scale Ship Model for Resistance and Parametric Roll Tests
Directory of Open Access Journals (Sweden)
Fernando LOPEZ PEŇA
2015-04-01
Full Text Available This work presents the developing of a self-propelled scale ship model aimed to perform resistance and parametric roll tests in towing tanks. The main characteristic of the proposed system is that it doesn’t have any material link to a towing device to carry out the tests. This ship model has been fully instrumented in order to acquire all the significant raw data, process them onboard and communicate with an inshore station. This works presents a description of the proposed model as well as some results obtained by its use during a towing tank testing campaign.
Oliveira, N. P.; Maciel, L.; Catarino, A. P.; Rocha, A. M.
2017-10-01
This work proposes the creation of models of surfaces using a parametric computer modelling software to obtain three-dimensional structures in weft knitted fabrics produced on single needle system machines. Digital prototyping, another feature of digital modelling software, was also explored in three-dimensional drawings generated using the Rhinoceros software. With this approach, different 3D structures were developed and produced. Physical characterization tests were then performed on the resulting 3D weft knitted structures to assess their ability to promote comfort. From the obtained results, it is apparent that the developed structures have potential for application in different market segments, such as clothing and interior textiles.
Parametric model of the scala tympani for haptic-rendered cochlear implantation.
Todd, Catherine; Naghdy, Fazel
2005-01-01
A parametric model of the human scala tympani has been designed for use in a haptic-rendered computer simulation of cochlear implant surgery. It will be the first surgical simulator of this kind. A geometric model of the Scala Tympani has been derived from measured data for this purpose. The model is compared with two existing descriptions of the cochlear spiral. A first approximation of the basilar membrane is also produced. The structures are imported into a force-rendering software application for system development.
International Nuclear Information System (INIS)
Gabriel, S.; Lau, R.W.; Gabriel, C.
1996-01-01
A parametric model was developed to describe the variation of dielectric properties of tissues as a function of frequency. The experimental spectrum from 10 Hz to 100 GHz was modelled with four dispersion regions. The development of the model was based on recently acquired data, complemented by data surveyed from the literature. The purpose is to enable the prediction of dielectric data that are in line with those contained in the vast body of literature on the subject. The analysis was carried out on a Microsoft Excel spreadsheet. Parameters are given for 17 tissue types. (author)
Dynamic modeling and explicit/multi-parametric MPC control of pressure swing adsorption systems
Khajuria, Harish
2011-01-01
Pressure swing adsorption (PSA) is a flexible, albeit complex gas separation system. Due to its inherent nonlinear nature and discontinuous operation, the design of a model based PSA controller, especially with varying operating conditions, is a challenging task. This work focuses on the design of an explicit/multi-parametric model predictive controller for a PSA system. Based on a system involving four adsorbent beds separating 70% H2, 30% CH4 mixture into high purity hydrogen, the key controller objective is to fast track H2 purity to a set point value of 99.99%. To perform this task, a rigorous and systematic framework is employed. First, a high fidelity detailed dynamic model is built to represent the system\\'s real operation, and understand its dynamic behavior. The model is then used to derive appropriate linear models by applying suitable system identification techniques. For the reduced models, a model predictive control (MPC) step is formulated, where latest developments in multi-parametric programming and control are applied to derive a novel explicit MPC controller. To test the performance of the designed controller, closed loop simulations are performed where the dynamic model is used as the virtual plant. Comparison studies of the derived explicit MPC controller are also performed with conventional PID controllers. © 2010 Elsevier Ltd. All rights reserved.
Parametric analysis of the statistical model of the stick-slip process
Lima, Roberta; Sampaio, Rubens
2017-06-01
In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.
A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns
Dao, Ngocanh; Genton, Marc G.
2014-01-01
Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte
Häggström, Ida; Beattie, Bradley J; Schmidtlein, C Ross
2016-06-01
To develop and evaluate a fast and simple tool called dpetstep (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. The tool was developed in matlab using both new and previously reported modules of petstep (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). dpetstep was 8000 times faster than MC. Dynamic images from dpetstep had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dpetstep and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dpetstep images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dpetstep to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dpetstep can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.
A simple parametric model observer for quality assurance in computer tomography
Anton, M.; Khanin, A.; Kretz, T.; Reginatto, M.; Elster, C.
2018-04-01
Model observers are mathematical classifiers that are used for the quality assessment of imaging systems such as computer tomography. The quality of the imaging system is quantified by means of the performance of a selected model observer. For binary classification tasks, the performance of the model observer is defined by the area under its ROC curve (AUC). Typically, the AUC is estimated by applying the model observer to a large set of training and test data. However, the recording of these large data sets is not always practical for routine quality assurance. In this paper we propose as an alternative a parametric model observer that is based on a simple phantom, and we provide a Bayesian estimation of its AUC. It is shown that a limited number of repeatedly recorded images (10–15) is already sufficient to obtain results suitable for the quality assessment of an imaging system. A MATLAB® function is provided for the calculation of the results. The performance of the proposed model observer is compared to that of the established channelized Hotelling observer and the nonprewhitening matched filter for simulated images as well as for images obtained from a low-contrast phantom on an x-ray tomography scanner. The results suggest that the proposed parametric model observer, along with its Bayesian treatment, can provide an efficient, practical alternative for the quality assessment of CT imaging systems.
Identification of parametric models with a priori knowledge of process properties
Directory of Open Access Journals (Sweden)
Janiszowski Krzysztof B.
2016-12-01
Full Text Available An approach to estimation of a parametric discrete-time model of a process in the case of some a priori knowledge of the investigated process properties is presented. The knowledge of plant properties is introduced in the form of linear bounds, which can be determined for the coefficient vector of the parametric model studied. The approach yields special biased estimation of model coefficients that preserves demanded properties. A formula for estimation of the model coefficients is derived and combined with a recursive scheme determined for minimization of the sum of absolute model errors. The estimation problem of a model with known static gains of inputs is discussed and proper formulas are derived. This approach can overcome the non-identifiability problem which has been observed during estimation based on measurements recorded in industrial closed-loop control systems. The application of the proposed approach to estimation of a model for an industrial plant (a water injector into the steam flow in a power plant is presented and discussed.
Parametric sensitivity analysis of an agro-economic model of management of irrigation water
El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse
2015-04-01
The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.
Economic modeling and parametric studies for SOMBRERO - a laser-driven IFE power plant
International Nuclear Information System (INIS)
Meier, W.R.; Rosenberg, C.W. Jr. von
1992-01-01
Economic modeling and parametric studies for the SOMBRERO laser-driven inertial fusion energy (IFE) electric power plant have been conducted to determine the most attractive operating point. Cost scaling relationships have been developed and integrated into a cost-performance model of the plant. The figure-of-merit for determining the most attractive design point is the constant-dollar cost of electricity. Results are presented as a function of the driver energy. The sensitivity of the results to variations in the assumed net electric output and target performance is also examined
Economic modeling and parametric studies for OSIRIS - a HIB-driven IFE power plant
International Nuclear Information System (INIS)
Meier, W.R.; Bieri, R.L.
1992-01-01
Economic modeling and parametric studies for the Osiris HIB-driven inertial fusion energy (IFE) electric power plant have been conducted to determine the most attractive operating point. Cost scaling relationships have been developed and integrated into a cost-performance model of the plant. The figure-of-merit for determining the most attractive design point is the constant-dollar cost of electricity. Results are presented as a function of the driver energy. The sensitivity of the results to variations in the assumed net electric output and target performance is also examined
X-1 to X-Wings: Developing a Parametric Cost Model
Sterk, Steve; McAtee, Aaron
2015-01-01
In todays cost-constrained environment, NASA needs an X-Plane database and parametric cost model that can quickly provide rough order of magnitude predictions of cost from initial concept to first fight of potential X-Plane aircraft. This paper takes a look at the steps taken in developing such a model and reports the results. The challenges encountered in the collection of historical data and recommendations for future database management are discussed. A step-by-step discussion of the development of Cost Estimating Relationships (CERs) is then covered.
Parametric laws to model urban pollutant dispersion with a street network approach
Soulhac, L.; Salizzoni, P.; Mejean, P.; Perkins, R. J.
2013-03-01
This study discusses the reliability of the street network approach for pollutant dispersion modelling in urban areas. This is essentially based on a box model, with parametric relations that explicitly model the main phenomena that contribute to the street canyon ventilation: the mass exchanges between the street and the atmosphere, the pollutant advection along the street axes and the pollutant transfer at street intersections. In the first part of the paper the focus is on the development of a model for the bulk transfer street/atmosphere, which represents the main ventilation mechanisms for wind direction that are almost perpendicular to the axis of the street. We then discuss the role of the advective transfer along the street axis on its ventilation, depending on the length of the street and the direction of the external wind. Finally we evaluate the performances of a box model integrating parametric exchange laws for these transfer phenomena. To that purpose we compare the prediction of the model to wind tunnel experiments of pollutant dispersion within a street canyon placed in an idealised urban district.
Wang, S.; Jun, Z.
2017-12-01
Climatic characteristics of tropical stratospheric methane have been well researched using various satellite data, and numerical simulations have furtherly conducted using chemical climatic models, while the impact of stratospheric methane oxidation on distribution of water vapor is not paid enough attention in general circulation models. Simulated values of water vapour in the tropical upper stratosphere, and throughout much of the extratropical stratosphere, were too low. Something must be done to remedy this deficiency in order to producing realistic stratospheric water vapor using a general circulation model including the whole stratosphere. Introduction of a simple parametrization of the upper-stratospheric moisture source due to methane oxidation and a sink due to photolysis in the mesosphere was conducted. Numerical simulations and analysis of the influence of stratospheric methane on the prediction of tropical stratospheric moisture and temperature fields were carried out. This study presents the advantages of methane oxidation parametrization in producing a realistic distribution of water vapour in the tropical stratosphere and analyzes the impact of methane chemical process on the general circulation model using two storm cases including a heavy rain in South China and a typhoon caused tropical storm.It is obvious that general circulation model with methane oxidation parametrization succeeds in simulating the water vapor and temperature in stratosphere. The simulating rain center value of contrast experiment is increased up to 10% than that of the control experiment. Introduction of methane oxidation parametrization has modified the distribution of water vapour and then producing a broadly realistic distribution of temperature. Objective weather forecast verifications have been performed using simulating results of one month, which demonstrate somewhat positive effects on the model skill. There is a certain extent impact of methane oxidation
Parametric study of a turbocompound diesel engine based on an analytical model
International Nuclear Information System (INIS)
Zhao, Rongchao; Zhuge, Weilin; Zhang, Yangjun; Yin, Yong; Zhao, Yanting; Chen, Zhen
2016-01-01
Turbocompounding is an important technique to recover waste heat from engine exhaust and reduce CO_2 emission. This paper presents a parametric study of turbocompound diesel engine based on analytical model. An analytical model was developed to investigate the influence of system parameters on the engine fuel consumption. The model is based on thermodynamics knowledge and empirical models, which can consider the impacts of each parameter independently. The effects of turbine efficiency, back pressure, exhaust temperature, pressure ratio and engine speed on the recovery energy, pumping loss and engine fuel reductions were studied. Results show that turbine efficiency, exhaust temperature and back pressure has great influence on the fuel reduction and optimal power turbine (PT) expansion ratio. However, engine operation speed has little impact on the fuel savings obtained by turbocompounding. The interaction mechanism between the PT recovery power and engine pumping loss is presented in the paper. Due to the nonlinear characteristic of turbine power, there is an optimum value of PT expansion ratio to achieve largest power gain. At the end, the fuel saving potential of high performance turbocompound engine and the requirements for it are proposed in the paper. - Highlights: • An analytical model for turbocompound engine is developed and validated. • Parametric study is performed to obtain lowest BSFC and optimal expansion ratio. • The influences of each parameter on the fuel saving potentials are presented. • The impact mechanisms of each parameter on the energy tradeoff are disclosed. • It provides an effective tool to guide the preliminary design of turbocompounding.
Comparison of Parametric and Nonparametric Methods for Analyzing the Bias of a Numerical Model
Directory of Open Access Journals (Sweden)
Isaac Mugume
2016-01-01
Full Text Available Numerical models are presently applied in many fields for simulation and prediction, operation, or research. The output from these models normally has both systematic and random errors. The study compared January 2015 temperature data for Uganda as simulated using the Weather Research and Forecast model with actual observed station temperature data to analyze the bias using parametric (the root mean square error (RMSE, the mean absolute error (MAE, mean error (ME, skewness, and the bias easy estimate (BES and nonparametric (the sign test, STM methods. The RMSE normally overestimates the error compared to MAE. The RMSE and MAE are not sensitive to direction of bias. The ME gives both direction and magnitude of bias but can be distorted by extreme values while the BES is insensitive to extreme values. The STM is robust for giving the direction of bias; it is not sensitive to extreme values but it does not give the magnitude of bias. The graphical tools (such as time series and cumulative curves show the performance of the model with time. It is recommended to integrate parametric and nonparametric methods along with graphical methods for a comprehensive analysis of bias of a numerical model.
International Nuclear Information System (INIS)
Battaglia, N.; Trac, H.; Cen, R.; Loeb, A.
2013-01-01
We present a new method for modeling inhomogeneous cosmic reionization on large scales. Utilizing high-resolution radiation-hydrodynamic simulations with 2048 3 dark matter particles, 2048 3 gas cells, and 17 billion adaptive rays in a L = 100 Mpc h –1 box, we show that the density and reionization redshift fields are highly correlated on large scales (∼> 1 Mpc h –1 ). This correlation can be statistically represented by a scale-dependent linear bias. We construct a parametric function for the bias, which is then used to filter any large-scale density field to derive the corresponding spatially varying reionization redshift field. The parametric model has three free parameters that can be reduced to one free parameter when we fit the two bias parameters to simulation results. We can differentiate degenerate combinations of the bias parameters by combining results for the global ionization histories and correlation length between ionized regions. Unlike previous semi-analytic models, the evolution of the reionization redshift field in our model is directly compared cell by cell against simulations and performs well in all tests. Our model maps the high-resolution, intermediate-volume radiation-hydrodynamic simulations onto lower-resolution, larger-volume N-body simulations (∼> 2 Gpc h –1 ) in order to make mock observations and theoretical predictions
Economic policy optimization based on both one stochastic model and the parametric control theory
Ashimov, Abdykappar; Borovskiy, Yuriy; Onalbekov, Mukhit
2016-06-01
A nonlinear dynamic stochastic general equilibrium model with financial frictions is developed to describe two interacting national economies in the environment of the rest of the world. Parameters of nonlinear model are estimated based on its log-linearization by the Bayesian approach. The nonlinear model is verified by retroprognosis, estimation of stability indicators of mappings specified by the model, and estimation the degree of coincidence for results of internal and external shocks' effects on macroeconomic indicators on the basis of the estimated nonlinear model and its log-linearization. On the base of the nonlinear model, the parametric control problems of economic growth and volatility of macroeconomic indicators of Kazakhstan are formulated and solved for two exchange rate regimes (free floating and managed floating exchange rates)
Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies
Ofman, L.
2010-01-01
Observations of the solar wind plasma at 0.3 AU and beyond show that a turbulent spectrum of magnetic fluctuations is present. Remote sensing observations of the corona indicate that heavy ions are hotter than protons and their temperature is anisotropic (T(sub perpindicular / T(sub parallel) >> 1). We study the heating and the acceleration of multi-ion plasma in the solar wind by a turbulent spectrum of Alfvenic fluctuations using a 2-D hybrid numerical model. In the hybrid model the protons and heavy ions are treated kinetically as particles, while the electrons are included as neutralizing background fluid. This is the first two-dimensional hybrid parametric study of the solar wind plasma that includes an input turbulent wave spectrum guided by observation with inhomogeneous background density. We also investigate the effects of He++ ion beams in the inhomogeneous background plasma density on the heating of the solar wind plasma. The 2-D hybrid model treats parallel and oblique waves, together with cross-field inhomogeneity, self-consistently. We investigate the parametric dependence of the perpendicular heating, and the temperature anisotropy in the H+-He++ solar wind plasma. It was found that the scaling of the magnetic fluctuations power spectrum steepens in the higher-density regions, and the heating is channeled to these regions from the surrounding lower-density plasma due to wave refraction. The model parameters are applicable to the expected solar wind conditions at about 10 solar radii.
Moment stability for a predator–prey model with parametric dichotomous noises
International Nuclear Information System (INIS)
Jin Yan-Fei
2015-01-01
In this paper, we investigate the solution moment stability for a Harrison-type predator–prey model with parametric dichotomous noises. Using the Shapiro–Loginov formula, the equations for the first-order and second-order moments are obtained and the corresponding stable conditions are given. It is found that the solution moment stability depends on the noise intensity and correlation time of noise. The first-order and second-order moments become unstable with the decrease of correlation time. That is, the dichotomous noise can improve the solution moment stability with respect to Gaussian white noise. Finally, some numerical results are presented to verify the theoretical analyses. (paper)
A non-parametric consistency test of the ΛCDM model with Planck CMB data
Energy Technology Data Exchange (ETDEWEB)
Aghamousa, Amir; Shafieloo, Arman [Korea Astronomy and Space Science Institute, Daejeon 305-348 (Korea, Republic of); Hamann, Jan, E-mail: amir@aghamousa.com, E-mail: jan.hamann@unsw.edu.au, E-mail: shafieloo@kasi.re.kr [School of Physics, The University of New South Wales, Sydney NSW 2052 (Australia)
2017-09-01
Non-parametric reconstruction methods, such as Gaussian process (GP) regression, provide a model-independent way of estimating an underlying function and its uncertainty from noisy data. We demonstrate how GP-reconstruction can be used as a consistency test between a given data set and a specific model by looking for structures in the residuals of the data with respect to the model's best-fit. Applying this formalism to the Planck temperature and polarisation power spectrum measurements, we test their global consistency with the predictions of the base ΛCDM model. Our results do not show any serious inconsistencies, lending further support to the interpretation of the base ΛCDM model as cosmology's gold standard.
Parametric modeling of energy filtering by energy barriers in thermoelectric nanocomposites
Energy Technology Data Exchange (ETDEWEB)
Zianni, Xanthippi, E-mail: xzianni@teiste.gr, E-mail: xzianni@gmail.com [Department of Aircraft Technology, Technological Educational Institution of Sterea Ellada, 34400 Psachna (Greece); Department of Microelectronics, INN, NCSR “Demokritos,” 15310 Athens (Greece); Narducci, Dario [Department of Materials Science, University of Milano Bicocca, 20125 Milano (Italy)
2015-01-21
We present a parametric modeling of the thermoelectric transport coefficients based on a model previously used to interpret experimental measurements on the conductivity, σ, and Seebeck coefficient, S, in highly Boron-doped polycrystalline Si, where a very significant thermoelectric power factor (TPF) enhancement was observed. We have derived analytical formalism for the transport coefficients in the presence of an energy barrier assuming thermionic emission over the barrier for (i) non-degenerate and (ii) degenerate one-band semiconductor. Simple generic parametric equations are found that are in agreement with the exact Boltzmann transport formalism in a wide range of parameters. Moreover, we explore the effect of energy barriers in 1-d composite semiconductors in the presence of two phases: (a) the bulk-like phase and (b) the barrier phase. It is pointed out that significant TPF enhancement can be achieved in the composite structure of two phases with different thermal conductivities. The TPF enhancement is estimated as a function of temperature, the Fermi energy position, the type of scattering, and the barrier height. The derived modeling provides guidance for experiments and device design.
Parametric models to relate spike train and LFP dynamics with neural information processing.
Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan
2012-01-01
Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial
truncSP: An R Package for Estimation of Semi-Parametric Truncated Linear Regression Models
Directory of Open Access Journals (Sweden)
Maria Karlsson
2014-05-01
Full Text Available Problems with truncated data occur in many areas, complicating estimation and inference. Regarding linear regression models, the ordinary least squares estimator is inconsistent and biased for these types of data and is therefore unsuitable for use. Alternative estimators, designed for the estimation of truncated regression models, have been developed. This paper presents the R package truncSP. The package contains functions for the estimation of semi-parametric truncated linear regression models using three different estimators: the symmetrically trimmed least squares, quadratic mode, and left truncated estimators, all of which have been shown to have good asymptotic and ?nite sample properties. The package also provides functions for the analysis of the estimated models. Data from the environmental sciences are used to illustrate the functions in the package.
Wang, Zhen-yu; Yu, Jian-cheng; Zhang, Ai-qun; Wang, Ya-xing; Zhao, Wen-tao
2017-12-01
Combining high precision numerical analysis methods with optimization algorithms to make a systematic exploration of a design space has become an important topic in the modern design methods. During the design process of an underwater glider's flying-wing structure, a surrogate model is introduced to decrease the computation time for a high precision analysis. By these means, the contradiction between precision and efficiency is solved effectively. Based on the parametric geometry modeling, mesh generation and computational fluid dynamics analysis, a surrogate model is constructed by adopting the design of experiment (DOE) theory to solve the multi-objects design optimization problem of the underwater glider. The procedure of a surrogate model construction is presented, and the Gaussian kernel function is specifically discussed. The Particle Swarm Optimization (PSO) algorithm is applied to hydrodynamic design optimization. The hydrodynamic performance of the optimized flying-wing structure underwater glider increases by 9.1%.
Parametric City Scale Energy Modeling Perspectives on using Termite in city scaled models
DEFF Research Database (Denmark)
Negendahl, Kristoffer; Nielsen, Toke Rammer
Termite is a parametric tool using the Danish building performance simulation engine Be10 written for the Grasshopper3D/Rhino3D environment. The tool Be10 is originally intended for building energy frame calculations and is required by Danish law when constructing new buildings. Termite opens up...... requirements, placing solar energy production facilities etc....
Energy Technology Data Exchange (ETDEWEB)
Marques, T.C.; Cruz Junior, G.; Vinhal, C. [Universidade Federal de Goias (UFG), Goiania, GO (Brazil). Escola de Engenharia Eletrica e de Computacao], Emails: thyago@eeec.ufg.br, gcruz@eeec.ufg.br, vinhal@eeec.ufg.br
2009-07-01
The goal of this paper is to present a methodology to carry out the seasonal stream flow forecasting using database of average monthly inflows of one Brazilian hydroelectric plant located at Grande, Tocantins, Paranaiba, Sao Francisco and Iguacu river's. The model is based on the Adaptive Network Based Fuzzy Inference System (ANFIS), the non-parametric model. The performance of this model was compared with a periodic autoregressive model, the parametric model. The results show that the forecasting errors of the non-parametric model considered are significantly lower than the parametric model. (author)
Thermal modeling and parametric studies of a greenhouse fish pond in the Central Himalayan Region
International Nuclear Information System (INIS)
Sarkar, Bikash; Tiwari, G.N.
2006-01-01
This study describes the thermal modeling and its validation of greenhouse fish pond systems. Numerical computations have been performed for a typical day in the month of June, 2005, for the climatic condition of Champawat in the Central Himalayan Region. The energy balance equations have been written considering the effects of conduction, convection, radiation, evaporation and ventilation. The governing equations are numerically solved with Matlab 7.0 software to predict the water temperature. A parametric study has also been performed to find the effects of various parameters, namely the number of air changes per hour, the transmissivity (τ) and the isothermal mass and height of the greenhouse. It is observed that there is no significant effect in the parametric studies on water temperature due to the larger isothermal mass. The model has been validated with experimental data. On an average, the even span passive greenhouse fish pond can increase the inside temperature 4.14 deg. C higher than the temperature of an outdoor pond. Statistical analysis shows that the predicted and experimental values of water temperature exhibited fair agreement with a coefficient of correlation r = 0.90 and root mean square percent deviation e = 1.67%
Developing integrated parametric planning models for budgeting and managing complex projects
Etnyre, Vance A.; Black, Ken U.
1988-01-01
The applicability of integrated parametric models for the budgeting and management of complex projects is investigated. Methods for building a very flexible, interactive prototype for a project planning system, and software resources available for this purpose, are discussed and evaluated. The prototype is required to be sensitive to changing objectives, changing target dates, changing costs relationships, and changing budget constraints. To achieve the integration of costs and project and task durations, parametric cost functions are defined by a process of trapezoidal segmentation, where the total cost for the project is the sum of the various project cost segments, and each project cost segment is the integral of a linearly segmented cost loading function over a specific interval. The cost can thus be expressed algebraically. The prototype was designed using Lotus-123 as the primary software tool. This prototype implements a methodology for interactive project scheduling that provides a model of a system that meets most of the goals for the first phase of the study and some of the goals for the second phase.
Power-law neuronal fluctuations in a recurrent network model of parametric working memory.
Miller, Paul; Wang, Xiao-Jing
2006-02-01
In a working memory system, persistent activity maintains information in the absence of external stimulation, therefore the time scale and structure of correlated neural fluctuations reflect the intrinsic microcircuit dynamics rather than direct responses to sensory inputs. Here we show that a parametric working memory model capable of graded persistent activity is characterized by arbitrarily long correlation times, with Fano factors and power spectra of neural activity described by the power laws of a random walk. Collective drifts of the mnemonic firing pattern induce long-term noise correlations between pairs of cells, with the sign (positive or negative) and amplitude proportional to the product of the gradients of their tuning curves. None of the power-law behavior was observed in a variant of the model endowed with discrete bistable neural groups, where noise fluctuations were unable to cause long-term changes in rate. Therefore such behavior can serve as a probe for a quasi-continuous attractor. We propose that the unusual correlated fluctuations have important implications for neural coding in parametric working memory circuits.
Parametric model of ventilators simulated in OpenFOAM and Elmer
Čibera, Václav; Matas, Richard; Sedláček, Jan
2016-03-01
The main goal of presented work was to develop parametric model of a ventilator for CFD and structural analysis. The whole model was designed and scripted in freely available open source programmes in particular in OpenFOAM and Elmer. The main script, which runs or generates other scripts and further control the course of simulation, was written in bash scripting language in Linux environment. Further, the scripts needed for a mesh generation and running of a simulation were prepared using m4 word pre-processor. The use of m4 allowed comfortable set up of the higher amount of scripts. Consequently, the mesh was generated for fluid and solid part of the ventilator within OpenFOAM. Although OpenFOAM offers also a few tools for structural analysis, the mesh of solid parts was transferred into Elmer mesh format with the aim to perform structural analysis in this software. This submitted paper deals namely with part concerning fluid flow through parametrized geometry with different initial conditions. As an example, two simulations were conducted for the same geometric parameters and mesh but for different angular velocity of ventilator rotation.
A model of parametric X-ray radiation for application to diagnostic radiology
International Nuclear Information System (INIS)
Di Domenico, G.; Cardarelli, P.; Gambaccini, M.; Marziani, M.; Taibi, A.; Comandini, A.
2011-01-01
Parametric X-ray Radiation (PXR) is well known as an intense, tunable and quasi-monochromatic X-ray source. From the very first work of Ter-Mikaelian, who proposed the interaction phenomenon for Parametric X-rays many theoretical and experimental studies have investigated the characteristics of such a novel X-ray source. Within the framework of classical electrodynamics, we have thoroughly studied the physical implications of electrons moving through a medium at relativistic speed and then developed an analytical model of X-ray diffraction based on the PXR phenomenon. The model has been used to obtain information on the characteristics of PXR diffracted beam in terms of X-ray intensity, energy spectrum and angular distribution. Several crystals have been studied both in Bragg and Laue geometry and their relative yield has been compared. Preliminary results on the diagnostic potential of PXR have shown that, at a distance from the crystal which produces a size of the X-ray field useful for an imaging application, the photon yield of PXR is higher than that produced by a conventional X-ray tube, provided that a similar electron current is available.
Parametric model of ventilators simulated in OpenFOAM and Elmer
Directory of Open Access Journals (Sweden)
Čibera Václav
2016-01-01
Full Text Available The main goal of presented work was to develop parametric model of a ventilator for CFD and structural analysis. The whole model was designed and scripted in freely available open source programmes in particular in OpenFOAM and Elmer. The main script, which runs or generates other scripts and further control the course of simulation, was written in bash scripting language in Linux environment. Further, the scripts needed for a mesh generation and running of a simulation were prepared using m4 word pre-processor. The use of m4 allowed comfortable set up of the higher amount of scripts. Consequently, the mesh was generated for fluid and solid part of the ventilator within OpenFOAM. Although OpenFOAM offers also a few tools for structural analysis, the mesh of solid parts was transferred into Elmer mesh format with the aim to perform structural analysis in this software. This submitted paper deals namely with part concerning fluid flow through parametrized geometry with different initial conditions. As an example, two simulations were conducted for the same geometric parameters and mesh but for different angular velocity of ventilator rotation.
The relevance of parametric U-uptake models in ESR age calculations
International Nuclear Information System (INIS)
Gruen, Rainer
2009-01-01
In the ESR dating three basic parametric U-uptake models have been applied for dating teeth: early U-uptake (EU: closed system), linear U-uptake (LU) and recent U-uptake (RU, it is assumed that the dose rate contribution of U in the dental tissues is zero). In many ESR dating publications it is still assumed that samples comply with one or the other parametric U-uptake model calculation or that their correct age lies somewhere between EU and LU. Observations of the spatial distribution of uranium in dental tissues show that it is difficult to predict any relationships between the relative uptake in the dental tissues. Combined U-series/ESR age estimates can give insights into the actual U-uptake. An evaluation of published data shows that for cave sites, a significant number of results fall outside the EU and LU bracket, while for open air sites, the majority of data are outside this bracket, particularly showing greatly delayed U-uptake. This may be due to changes in the hydrological system, leading to erosion which exposes the open air site. U-leaching has also been observed on samples from open air sites, in which case any reasonable age calculation is impossible.
Garagnani, S.; Manferdini, A. M.
2013-02-01
Since their introduction, modeling tools aimed to architectural design evolved in today's "digital multi-purpose drawing boards" based on enhanced parametric elements able to originate whole buildings within virtual environments. Semantic splitting and elements topology are features that allow objects to be "intelligent" (i.e. self-aware of what kind of element they are and with whom they can interact), representing this way basics of Building Information Modeling (BIM), a coordinated, consistent and always up to date workflow improved in order to reach higher quality, reliability and cost reductions all over the design process. Even if BIM was originally intended for new architectures, its attitude to store semantic inter-related information can be successfully applied to existing buildings as well, especially if they deserve particular care such as Cultural Heritage sites. BIM engines can easily manage simple parametric geometries, collapsing them to standard primitives connected through hierarchical relationships: however, when components are generated by existing morphologies, for example acquiring point clouds by digital photogrammetry or laser scanning equipment, complex abstractions have to be introduced while remodeling elements by hand, since automatic feature extraction in available software is still not effective. In order to introduce a methodology destined to process point cloud data in a BIM environment with high accuracy, this paper describes some experiences on monumental sites documentation, generated through a plug-in written for Autodesk Revit and codenamed GreenSpider after its capability to layout points in space as if they were nodes of an ideal cobweb.
International Nuclear Information System (INIS)
Luo, Yongqiang; Zhang, Ling; Liu, Zhongbing; Wang, Yingzi; Wu, Jing; Wang, Xiliang
2016-01-01
Highlights: • Dynamic model of thermoelectric radiant panel system is established. • The internal parameters of thermoelectric module are dynamically calculated in simulation. • Both artificial neural networks model and system model are verified through experiment data. • Optimized system structure is obtained through parametric study. - Abstract: Radiant panel system can optimize indoor thermal comfort with lower energy consumption. The thermoelectric radiant panel (TERP) system is a new and effective prototype of radiant system using thermoelectric module (TEM) instead of conventional water pipes, as heat source. The TERP can realize more stable and easier system control as well as lower initial and operative cost. In this study, an improved system dynamic model was established by combining analytical system model and artificial neural networks (ANN) as well as the dynamic calculation functions of internal parameters of TEM. The double integral was used for the calculation of surface average temperature of TERP. The ANN model and system model were in good agreement with experiment data in both cooling and heating mode. In order to optimize the system design structure, parametric study was conducted in terms of the thickness of aluminum panel and insulation, as well as the arrangement of TEMs on the surface of radiant panel. It was found through simulation results that the optimum thickness of aluminum panel and insulation are respectively around 1–2 mm and 40–50 mm. In addition, TEMs should be uniformly installed on the surface of radiant panel and each TEM should stand at the central position of a square-shaped typical region with length around 0.387–0.548 m.
The Borromini's helicoidal staircase in Barberini Palace: scan laser survey and parametric modeling.
Directory of Open Access Journals (Sweden)
Leonardo Paris
2015-07-01
model, first of all measurable, but also able to disclosing shapes and geometries otherwise hardly perceptible, selecting parts or showing details.A first reading level of the models, obtained according to consolidated procedures of the points-cloud management, has highlighted the formal matrix of the oval with the identification of the centers of the polycentric line, the resulting three-dimensional development of the various helices belonging to cylindrical surface portions adjacent to each other and different radius, the relationship with the slope. Within this formal matrix of the first level it enters the formal matrix of the architectural order into the rhythm of the six pairs of alternate columns and of the balustrades, and in the entablature that develops as a tape into the central space illuminated by a skylight.The modular structure of the scale has also suggested a experimentation by means of parametric modeling techniques to try to trace the ideal model of the Borromini’s helical staircase. The digital parametric model tested here is a new mode of representation than the models already consolidated, either analog or digital. Through a critical selection of some remarkable points belonging to the geometries present, through a statistical and normalized observation of the recurring measures, we have identified a generative algorithm able to be representative of the design intentions of the author. The entire search path followed to reach the definition of parametric generative model – from analysis of the real model to the design of the virtual parametric model; from the development of the algorithm generative until to his check made by comparing the generated model and the model survey - it was found to be a constraint rigorous methodological for a more complete and appropriate knowledge of the work.
Development of a parametric containment event tree model for a severe BWR accident
Energy Technology Data Exchange (ETDEWEB)
Okkonen, T [OTO-Consulting Ay, Helsinki (Finland)
1995-04-01
A containment event tree (CET) is built for analysis of severe accidents at the TVO boiling water reactor (BWR) units. Parametric models of severe accident progression and fission product behaviour are developed and integrated in order to construct a compact and self-contained Level 2 PSA model. The model can be easily updated to correspond to new research results. The analyses of the study are limited to severe accidents starting from full-power operation and leading to core melting, and are focused mainly on the use and effects of the dedicated severe accident management (SAM) systems. Severe accident progression from eight plant damage states (PDS), involving different pre-core-damage accident evolution, is examined, but the inclusion of their relative or absolute probabilities, by integration with Level 1, is deferred to integral safety assessments. (33 refs., 5 figs., 7 tabs.).
Parametric Study of Synthetic-Jet-Based Flow Control on a Vertical Tail Model
Monastero, Marianne; Lindstrom, Annika; Beyar, Michael; Amitay, Michael
2015-11-01
Separation control over the rudder of the vertical tail of a commercial airplane using synthetic-jet-based flow control can lead to a reduction in tail size, with an associated decrease in drag and increase in fuel savings. A parametric, experimental study was undertaken using an array of finite span synthetic jets to investigate the sensitivity of the enhanced vertical tail side force to jet parameters, such as jet spanwise spacing and jet momentum coefficient. A generic wind tunnel model was designed and fabricated to fundamentally study the effects of the jet parameters at varying rudder deflection and model sideslip angles. Wind tunnel results obtained from pressure measurements and tuft flow visualization in the Rensselaer Polytechnic Subsonic Wind Tunnel show a decrease in separation severity and increase in model performance in comparison to the baseline, non-actuated case. The sensitivity to various parameters will be presented.
Energy Technology Data Exchange (ETDEWEB)
Gaussens, J; Paillot, H [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1965-07-01
The authors define the notions of use values and price of plutonium. They give a 'simplified parametrized model' simulating the equilibrium of the offer and the demand in time, concerning the plutonium and the price deriving from the relative scarcity of this metal, taking into account the technical and economic operating parameters of the various reactors confronted. This model is simple enough to allow direct computations and establish clear relations between the various parameters. The use of the linear programmes method allows on the other hand a wide extension of the model. This report includes three main parts: I - General description of the study (without detailed calculations) II - Mathematical development of the simplified parametrized model and application (the basic data and the results of the calculations are given) III - Appendices (giving the detailed computations of part II). (authors) [French] Les auteurs definissent les notions de valeurs d'usage et de prix du plutonium. Ils donnent un 'modele parametre simplifie' simulant l'equilibre de l'office et de la demande dans le temps concernant le plutonium et le prix qui decoule de la rarete relative de ce metal, compte tenu des parametres techniques et economiques de fonctionnement des divers reacteurs en presence. Ce modele est suffisamment simple pour permettre des calculs manuels et etablir des liaisons claires entre les divers parametres. L'utilisation de la technique des programmes lineaires permet par ailleurs une extension considerable du modele. Cette note comprend trois parties: I - Expose general de l'etude (sans expose du detail des calculs) II - Developpement mathematique du modele parametre simplifie et application (on precise les donnees de base et le resultat des calculs) III - Annexes (donnant le detail des calculs de la partie II). (auteurs)
Energy Technology Data Exchange (ETDEWEB)
Häggström, Ida, E-mail: haeggsti@mskcc.org [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 and Department of Radiation Sciences, Umeå University, Umeå 90187 (Sweden); Beattie, Bradley J.; Schmidtlein, C. Ross [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States)
2016-06-15
Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for
International Nuclear Information System (INIS)
Häggström, Ida; Beattie, Bradley J.; Schmidtlein, C. Ross
2016-01-01
Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for
Bayesian spatial semi-parametric modeling of HIV variation in Kenya.
Directory of Open Access Journals (Sweden)
Oscar Ngesa
Full Text Available Spatial statistics has seen rapid application in many fields, especially epidemiology and public health. Many studies, nonetheless, make limited use of the geographical location information and also usually assume that the covariates, which are related to the response variable, have linear effects. We develop a Bayesian semi-parametric regression model for HIV prevalence data. Model estimation and inference is based on fully Bayesian approach via Markov Chain Monte Carlo (McMC. The model is applied to HIV prevalence data among men in Kenya, derived from the Kenya AIDS indicator survey, with n = 3,662. Past studies have concluded that HIV infection has a nonlinear association with age. In this study a smooth function based on penalized regression splines is used to estimate this nonlinear effect. Other covariates were assumed to have a linear effect. Spatial references to the counties were modeled as both structured and unstructured spatial effects. We observe that circumcision reduces the risk of HIV infection. The results also indicate that men in the urban areas were more likely to be infected by HIV as compared to their rural counterpart. Men with higher education had the lowest risk of HIV infection. A nonlinear relationship between HIV infection and age was established. Risk of HIV infection increases with age up to the age of 40 then declines with increase in age. Men who had STI in the last 12 months were more likely to be infected with HIV. Also men who had ever used a condom were found to have higher likelihood to be infected by HIV. A significant spatial variation of HIV infection in Kenya was also established. The study shows the practicality and flexibility of Bayesian semi-parametric regression model in analyzing epidemiological data.
A Model for Straight and Helical Solar Jets: II. Parametric Study of the Plasma Beta
Pariat, E.; Dalmasse, K.; DeVore, C. R.; Antiochos, S. K.; Karpen, J. T.
2016-01-01
Context. Jets are dynamic, impulsive, well-collimated plasma events that develop at many different scales and in different layers of the solar atmosphere. Aims. Jets are believed to be induced by magnetic reconnection, a process central to many astrophysical phenomena. Within the solar atmosphere, jet-like events develop in many different environments, e.g. in the vicinity of active regions as well as in coronal holes, and at various scales, from small photospheric spicules to large coronal jets. In all these events, signatures of helical structure and/or twisting/rotating motions are regularly observed. The present study aims to establish that a single model can generally reproduce the observed properties of these jet-like events. Methods. In this study, using our state-of-the-art numerical solver ARMS, we present a parametric study of a numerical tridimensional magnetohydrodynamic (MHD) model of solar jet-like events. Within the MHD paradigm, we study the impact of varying the atmospheric plasma beta on the generation and properties of solar-like jets. Results. The parametric study validates our model of jets for plasma beta ranging from 10(sup 3) to 1, typical of the different layers and magnetic environments of the solar atmosphere. Our model of jets can robustly explain the generation of helical solar jet-like events at various beta less than or equal to 1. We show that the plasma beta modifies the morphology of the helical jet, explaining the different observed shapes of jets at different scales and in different layers of the solar atmosphere. Conclusions. Our results allow us to understand the energisation, triggering, and driving processes of jet-like events. Our model allows us to make predictions of the impulsiveness and energetics of jets as determined by the surrounding environment, as well as the morphological properties of the resulting jets.
Parametrization in models of subcritical glass fracture: Activation offset and concerted activation
Rodrigues, Bruno Poletto; Hühn, Carolin; Erlebach, Andreas; Mey, Dorothea; Sierka, Marek; Wondraczek, Lothar
2017-08-01
There are two established but fundamentally different empirical approaches to parametrize the rate of subcritical fracture in brittle materials. While both are relying on a thermally activated reaction of bond rupture, the difference lies in the way as to how the externally applied stresses affect the local energy landscape. In the consideration of inorganic glasses, the strain energy is typically taken as an off-set on the activation barrier. As an alternative interpretation, the system’s volumetric strain-energy is added to its thermal energy. Such an interpretation is consistent with the democratic fiber bundle model. Here, we test this approach of concerted activation against macroscopic data of bond cleavage activation energy, and also against ab initio quantum chemical simulation of the energy barrier for cracking in silica. The fact that both models are able to reproduce experimental observation to a remarkable degree highlights the importance of a holistic consideration towards non-empirical understanding.
Directory of Open Access Journals (Sweden)
Sandra Teodorescu
2013-11-01
Full Text Available The present paper describes a series of parametric distributions used for modeling non-life insurance payments data.Of those listed, special attention is paid to the transformed Beta distribution family.This distribution as well as those which are obtained from it(special cases of four-parameter transformed Beta distribution are used in the modeling of high costs, or even extreme ones.In the literature it follows the tail behaviour of distributions depending on the parameters, because the insurance payments data are tipically highly positively skewed and distributed with large upper tails.In the paper is described the tail behavior of the distribution in the left and right side respectively, and deduced from it, a general case.There are also some graphs of probability density function for one of the transformed Beta family members, which comes to reinforce the comments made.
Paul, Sarbajit; Chang, Junghwan
2017-07-01
This paper presents a design approach for a magnetic sensor module to detect mover position using the proper orthogonal decomposition-dynamic mode decomposition (POD-DMD)-based nonlinear parametric model order reduction (PMOR). The parameterization of the sensor module is achieved by using the multipolar moment matching method. Several geometric variables of the sensor module are considered while developing the parametric study. The operation of the sensor module is based on the principle of the airgap flux density distribution detection by the Hall Effect IC. Therefore, the design objective is to achieve a peak flux density (PFD) greater than 0.1 T and total harmonic distortion (THD) less than 3%. To fulfill the constraint conditions, the specifications for the sensor module is achieved by using POD-DMD based reduced model. The POD-DMD based reduced model provides a platform to analyze the high number of design models very fast, with less computational burden. Finally, with the final specifications, the experimental prototype is designed and tested. Two different modes, 90° and 120° modes respectively are used to obtain the position information of the linear motor mover. The position information thus obtained are compared with that of the linear scale data, used as a reference signal. The position information obtained using the 120° mode has a standard deviation of 0.10 mm from the reference linear scale signal, whereas the 90° mode position signal shows a deviation of 0.23 mm from the reference. The deviation in the output arises due to the mechanical tolerances introduced into the specification during the manufacturing process. This provides a scope for coupling the reliability based design optimization in the design process as a future extension.
Semiparametric modeling: Correcting low-dimensional model error in parametric models
International Nuclear Information System (INIS)
Berry, Tyrus; Harlim, John
2016-01-01
In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consists of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.
Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach
Directory of Open Access Journals (Sweden)
Oliveira Rui
2010-09-01
Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.
Moment stability for a predator-prey model with parametric dichotomous noises
Jin, Yan-Fei
2015-06-01
In this paper, we investigate the solution moment stability for a Harrison-type predator-prey model with parametric dichotomous noises. Using the Shapiro-Loginov formula, the equations for the first-order and second-order moments are obtained and the corresponding stable conditions are given. It is found that the solution moment stability depends on the noise intensity and correlation time of noise. The first-order and second-order moments become unstable with the decrease of correlation time. That is, the dichotomous noise can improve the solution moment stability with respect to Gaussian white noise. Finally, some numerical results are presented to verify the theoretical analyses. Project supported by the National Natural Science Foundation of China (Grant No. 11272051).
FEM BASED PARAMETRIC DESIGN STUDY OF TIRE PROFILE USING DEDICATED CAD MODEL AND TRANSLATION CODE
Directory of Open Access Journals (Sweden)
Nikola Korunović
2014-12-01
Full Text Available In this paper a finite element method (FEM based parametric design study of the tire profile shape and belt width is presented. One of the main obstacles that similar studies have faced is how to change the finite element mesh after a modification of the tire geometry is performed. In order to overcome this problem, a new approach is proposed. It implies automatic update of the finite elements mesh, which follows the change of geometric design parameters on a dedicated CAD model. The mesh update is facilitated by an originally developed mapping and translation code. In this way, the performance of a large number of geometrically different tire design variations may be analyzed in a very short time. Although a pilot one, the presented study has also led to the improvement of the existing tire design.
International Nuclear Information System (INIS)
Vard, Alireza; Jamshidi, Kamal; Movahhedinia, Naser
2012-01-01
This paper presents a fully automated approach to detect the intima and media-adventitia borders in intravascular ultrasound images based on parametric active contour models. To detect the intima border, we compute a new image feature applying a combination of short-term autocorrelations calculated for the contour pixels. These feature values are employed to define an energy function of the active contour called normalized cumulative short-term autocorrelation. Exploiting this energy function, the intima border is separated accurately from the blood region contaminated by high speckle noise. To extract media-adventitia boundary, we define a new form of energy function based on edge, texture and spring forces for the active contour. Utilizing this active contour, the media-adventitia border is identified correctly even in presence of branch openings and calcifications. Experimental results indicate accuracy of the proposed methods. In addition, statistical analysis demonstrates high conformity between manual tracing and the results obtained by the proposed approaches.
An Online Method for Interpolating Linear Parametric Reduced-Order Models
Amsallem, David; Farhat, Charbel
2011-01-01
A two-step online method is proposed for interpolating projection-based linear parametric reduced-order models (ROMs) in order to construct a new ROM for a new set of parameter values. The first step of this method transforms each precomputed ROM into a consistent set of generalized coordinates. The second step interpolates the associated linear operators on their appropriate matrix manifold. Real-time performance is achieved by precomputing inner products between the reduced-order bases underlying the precomputed ROMs. The proposed method is illustrated by applications in mechanical and aeronautical engineering. In particular, its robustness is demonstrated by its ability to handle the case where the sampled parameter set values exhibit a mode veering phenomenon. © 2011 Society for Industrial and Applied Mathematics.
Quantum Brownian motion in a bath of parametric oscillators: A model for system-field interactions
International Nuclear Information System (INIS)
Hu, B.L.; Matacz, A.
1994-01-01
The quantum Brownian motion paradigm provides a unified framework where one can see the interconnection of some basic quantum statistical processes such as decoherence, dissipation, particle creation, noise, and fluctuation. The present paper continues the investigation begun in earlier papers on the quantum Brownian motion in a general environment via the influence functional formalism. Here, the Brownian particle is coupled linearly to a bath of the most general time-dependent quadratic oscillators. This bath of parametric oscillators minics a scalar field, while the motion of the Brownian particle modeled by a single oscillator could be used to depict the behavior of a particle detector, a quantum field mode, or the scale factor of the Universe. An important result of this paper is the derivation of the influence functional encompassing the noise and dissipation kernels in terms of the Bogolubov coefficients, thus setting the stage for the influence functional formalism treatment of problems in quantum field theory in curved spacetime. This method enables one to trace the source of statistical processes such as decoherence and dissipation to vacuum fluctuations and particle creation, and in turn impart a statistical mechanical interpretation of quantum field processes. With this result we discuss the statistical mechanical origin of quantum noise and thermal radiance from black holes and from uniformly accelerated observers in Minkowski space as well as from the de Sitter universe discovered by Hawking, Unruh, and Gibbons and Hawking. We also derive the exact evolution operator and master equation for the reduced density matrix of the system interacting with a parametric oscillator bath in an initial squeezed thermal state. These results are useful for decoherence and back reaction studies for systems and processes of interest in semiclassical cosmology and gravity. Our model and results are also expected to be useful for related problems in quantum optics
Parametric Packet-Layer Model for Evaluation Audio Quality in Multimedia Streaming Services
Egi, Noritsugu; Hayashi, Takanori; Takahashi, Akira
We propose a parametric packet-layer model for monitoring audio quality in multimedia streaming services such as Internet protocol television (IPTV). This model estimates audio quality of experience (QoE) on the basis of quality degradation due to coding and packet loss of an audio sequence. The input parameters of this model are audio bit rate, sampling rate, frame length, packet-loss frequency, and average burst length. Audio bit rate, packet-loss frequency, and average burst length are calculated from header information in received IP packets. For sampling rate, frame length, and audio codec type, the values or the names used in monitored services are input into this model directly. We performed a subjective listening test to examine the relationships between these input parameters and perceived audio quality. The codec used in this test was the Advanced Audio Codec-Low Complexity (AAC-LC), which is one of the international standards for audio coding. On the basis of the test results, we developed an audio quality evaluation model. The verification results indicate that audio quality estimated by the proposed model has a high correlation with perceived audio quality.
Rosenberg, Leigh; Hihn, Jairus; Roust, Kevin; Warfield, Keith
2000-01-01
This paper presents an overview of a parametric cost model that has been built at JPL to estimate costs of future, deep space, robotic science missions. Due to the recent dramatic changes in JPL business practices brought about by an internal reengineering effort known as develop new products (DNP), high-level historic cost data is no longer considered analogous to future missions. Therefore, the historic data is of little value in forecasting costs for projects developed using the DNP process. This has lead to the development of an approach for obtaining expert opinion and also for combining actual data with expert opinion to provide a cost database for future missions. In addition, the DNP cost model has a maximum of objective cost drivers which reduces the likelihood of model input error. Version 2 is now under development which expands the model capabilities, links it more tightly with key design technical parameters, and is grounded in more rigorous statistical techniques. The challenges faced in building this model will be discussed, as well as it's background, development approach, status, validation, and future plans.
A Novel Parametric Modeling Method and Optimal Design for Savonius Wind Turbines
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Baoshou Zhang
2017-03-01
Full Text Available Under the inspiration of polar coordinates, a novel parametric modeling and optimization method for Savonius wind turbines was proposed to obtain the highest power output, in which a quadratic polynomial curve was bent to describe a blade. Only two design parameters are needed for the shape-complicated blade. Therefore, this novel method reduces sampling scale. A series of transient simulations was run to get the optimal performance coefficient (power coefficient C p for different modified turbines based on computational fluid dynamics (CFD method. Then, a global response surface model and a more precise local response surface model were created according to Kriging Method. These models defined the relationship between optimization objective Cp and design parameters. Particle swarm optimization (PSO algorithm was applied to find the optimal design based on these response surface models. Finally, the optimal Savonius blade shaped like a “hook” was obtained. Cm (torque coefficient, Cp and flow structure were compared for the optimal design and the classical design. The results demonstrate that the optimal Savonius turbine has excellent comprehensive performance. The power coefficient Cp is significantly increased from 0.247 to 0.262 (6% higher. The weight of the optimal blade is reduced by 17.9%.
Nonlinear Container Ship Model for the Study of Parametric Roll Resonance
DEFF Research Database (Denmark)
Holden, Christian; Galeazzi, Roberto; Rodríguez, Claudio
2007-01-01
Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to 40, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head ...
Lazeroms, Werner M. J.; Jenkins, Adrian; Hilmar Gudmundsson, G.; van de Wal, Roderik S. W.
2018-01-01
Basal melting below ice shelves is a major factor in mass loss from the Antarctic Ice Sheet, which can contribute significantly to possible future sea-level rise. Therefore, it is important to have an adequate description of the basal melt rates for use in ice-dynamical models. Most current ice models use rather simple parametrizations based on the local balance of heat between ice and ocean. In this work, however, we use a recently derived parametrization of the melt rates based on a buoyant meltwater plume travelling upward beneath an ice shelf. This plume parametrization combines a non-linear ocean temperature sensitivity with an inherent geometry dependence, which is mainly described by the grounding-line depth and the local slope of the ice-shelf base. For the first time, this type of parametrization is evaluated on a two-dimensional grid covering the entire Antarctic continent. In order to apply the essentially one-dimensional parametrization to realistic ice-shelf geometries, we present an algorithm that determines effective values for the grounding-line depth and basal slope in any point beneath an ice shelf. Furthermore, since detailed knowledge of temperatures and circulation patterns in the ice-shelf cavities is sparse or absent, we construct an effective ocean temperature field from observational data with the purpose of matching (area-averaged) melt rates from the model with observed present-day melt rates. Our results qualitatively replicate large-scale observed features in basal melt rates around Antarctica, not only in terms of average values, but also in terms of the spatial pattern, with high melt rates typically occurring near the grounding line. The plume parametrization and the effective temperature field presented here are therefore promising tools for future simulations of the Antarctic Ice Sheet requiring a more realistic oceanic forcing.
Automating the Simulation of SME Processes through a Discrete Event Parametric Model
Directory of Open Access Journals (Sweden)
Francesco Aggogeri
2015-02-01
Full Text Available At the factory level, the manufacturing system can be described as a group of processes governed by complex weaves of engineering strategies and technologies. Decision- making processes involve a lot of information, driven by managerial strategies, technological implications and layout constraints. Many factors affect decisions, and their combination must be carefully managed to determine the best solutions to optimize performances. In this way, advanced simulation tools could support the decisional process of many SMEs. The accessibility of these tools is limited by knowledge, cost, data availability and development time. These tools should be used to support strategic decisions rather than specific situations. In this paper, a novel approach is proposed that aims to facilitate the simulation of manufacturing processes by fast modelling and evaluation. The idea is to realize a model that is able to be automatically adapted to the user’s specific needs. The model must be characterized by a high degree of flexibility, configurability and adaptability in order to automatically simulate multiple/heterogeneous industrial scenarios. In this way, even a SME can easily access a complex tool, perform thorough analyses and be supported in taking strategic decisions. The parametric DES model is part of a greater software platform developed during COPERNICO EU funded project.
A parametric investigation of hydrogen hcci combustion using a multi-zone model approach
International Nuclear Information System (INIS)
Komninos, N.P.; Hountalas, D.T.; Rakopoulos, C.D.
2007-01-01
The purpose of the present study is to examine the effect of various operating variables of a homogeneous charge compression ignition (HCCI) engine fueled with hydrogen, using a multi-zone model developed by the authors. The multi-zone model consists of zones, which are allotted spatial locations within the combustion chamber. The model takes into account heat transfer between the zones and the combustion chamber walls, providing a spatial temperature distribution during the closed part of the engine cycle, i.e. compression, combustion and expansion. Mass transfer between zones is also accounted for, based on the geometric configuration of the zones, and includes the flow of mass in and out of the crevice regions, represented by the crevice zone. Combustion is incorporated using chemical kinetics based on a chemical reaction mechanism for the oxidation of hydrogen. This chemical reaction mechanism also includes the reactions for nitrogen oxides formation. Using the multi-zone model a parametric investigation is conducted, in order to determine the effect of engine speed, equivalence ratio, compression ratio, inlet pressure and inlet temperature, on the performance, combustion characteristics and emissions of an HCCI engine fueled with hydrogen
Steinhauer, H. M.
2012-01-01
Engineering graphics has historically been viewed as a challenging course to teach as students struggle to grasp and understand the fundamental concepts and then to master their proper application. The emergence of stable, fast, affordable 3D parametric modeling platforms such as CATIA, Pro-E, and AutoCAD while providing several pedagogical…
Update on Multi-Variable Parametric Cost Models for Ground and Space Telescopes
Stahl, H. Philip; Henrichs, Todd; Luedtke, Alexander; West, Miranda
2012-01-01
Parametric cost models can be used by designers and project managers to perform relative cost comparisons between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. This paper reports on recent revisions and improvements to our ground telescope cost model and refinements of our understanding of space telescope cost models. One interesting observation is that while space telescopes are 50X to 100X more expensive than ground telescopes, their respective scaling relationships are similar. Another interesting speculation is that the role of technology development may be different between ground and space telescopes. For ground telescopes, the data indicates that technology development tends to reduce cost by approximately 50% every 20 years. But for space telescopes, there appears to be no such cost reduction because we do not tend to re-fly similar systems. Thus, instead of reducing cost, 20 years of technology development may be required to enable a doubling of space telescope capability. Other findings include: mass should not be used to estimate cost; spacecraft and science instrument costs account for approximately 50% of total mission cost; and, integration and testing accounts for only about 10% of total mission cost.
Splettstoesser, W. R.; Schultz, K. J.; Boxwell, D. A.; Schmitz, F. H.
1984-01-01
Acoustic data taken in the anechoic Deutsch-Niederlaendischer Windkanal (DNW) have documented the blade vortex interaction (BVI) impulsive noise radiated from a 1/7-scale model main rotor of the AH-1 series helicopter. Averaged model scale data were compared with averaged full scale, inflight acoustic data under similar nondimensional test conditions. At low advance ratios (mu = 0.164 to 0.194), the data scale remarkable well in level and waveform shape, and also duplicate the directivity pattern of BVI impulsive noise. At moderate advance ratios (mu = 0.224 to 0.270), the scaling deteriorates, suggesting that the model scale rotor is not adequately simulating the full scale BVI noise; presently, no proved explanation of this discrepancy exists. Carefully performed parametric variations over a complete matrix of testing conditions have shown that all of the four governing nondimensional parameters - tip Mach number at hover, advance ratio, local inflow ratio, and thrust coefficient - are highly sensitive to BVI noise radiation.
Parametric modeling and stagger angle optimization of an axial flow fan
International Nuclear Information System (INIS)
Li, M X; Zhang, C H; Liu, Y; Zheng, S Y
2013-01-01
Axial flow fans are widely used in every field of social production. Improving their efficiency is a sustained and urgent demand of domestic industry. The optimization of stagger angle is an important method to improve fan performance. Parametric modeling and calculation process automation are realized in this paper to improve optimization efficiency. Geometric modeling and mesh division are parameterized based on GAMBIT. Parameter setting and flow field calculation are completed in the batch mode of FLUENT. A control program is developed in Visual C++ to dominate the data exchange of mentioned software. It also extracts calculation results for optimization algorithm module (provided by Matlab) to generate directive optimization control parameters, which as feedback are transferred upwards to modeling module. The center line of the blade airfoil, based on CLARK y profile, is constructed by non-constant circulation and triangle discharge method. Stagger angles of six airfoil sections are optimized, to reduce the influence of inlet shock loss as well as gas leak in blade tip clearance and hub resistance at blade root. Finally an optimal solution is obtained, which meets the total pressure requirement under given conditions and improves total pressure efficiency by about 6%
Towards a Multi-Variable Parametric Cost Model for Ground and Space Telescopes
Stahl, H. Philip; Henrichs, Todd
2016-01-01
Parametric cost models can be used by designers and project managers to perform relative cost comparisons between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. This paper hypothesizes a single model, based on published models and engineering intuition, for both ground and space telescopes: OTA Cost approximately (X) D(exp (1.75 +/- 0.05)) lambda(exp(-0.5 +/- 0.25) T(exp -0.25) e (exp (-0.04)Y). Specific findings include: space telescopes cost 50X to 100X more ground telescopes; diameter is the most important CER; cost is reduced by approximately 50% every 20 years (presumably because of technology advance and process improvements); and, for space telescopes, cost associated with wavelength performance is balanced by cost associated with operating temperature. Finally, duplication only reduces cost for the manufacture of identical systems (i.e. multiple aperture sparse arrays or interferometers). And, while duplication does reduce the cost of manufacturing the mirrors of segmented primary mirror, this cost savings does not appear to manifest itself in the final primary mirror assembly (presumably because the structure for a segmented mirror is more complicated than for a monolithic mirror).
Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI
Energy Technology Data Exchange (ETDEWEB)
Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim; Emberton, Mark [University College London, Research Department of Urology, London (United Kingdom); Kirkham, Alex; Allen, Clare [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)
2014-09-17
We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. (orig.)
Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI
International Nuclear Information System (INIS)
Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit; Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki; Abd-Alazeez, Mohamed; Ahmed, Hashim; Emberton, Mark; Kirkham, Alex; Allen, Clare; Freeman, Alex
2015-01-01
We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. (orig.)
Integrated System-Level Optimization for Concurrent Engineering With Parametric Subsystem Modeling
Schuman, Todd; DeWeck, Oliver L.; Sobieski, Jaroslaw
2005-01-01
The introduction of concurrent design practices to the aerospace industry has greatly increased the productivity of engineers and teams during design sessions as demonstrated by JPL's Team X. Simultaneously, advances in computing power have given rise to a host of potent numerical optimization methods capable of solving complex multidisciplinary optimization problems containing hundreds of variables, constraints, and governing equations. Unfortunately, such methods are tedious to set up and require significant amounts of time and processor power to execute, thus making them unsuitable for rapid concurrent engineering use. This paper proposes a framework for Integration of System-Level Optimization with Concurrent Engineering (ISLOCE). It uses parametric neural-network approximations of the subsystem models. These approximations are then linked to a system-level optimizer that is capable of reaching a solution quickly due to the reduced complexity of the approximations. The integration structure is described in detail and applied to the multiobjective design of a simplified Space Shuttle external fuel tank model. Further, a comparison is made between the new framework and traditional concurrent engineering (without system optimization) through an experimental trial with two groups of engineers. Each method is evaluated in terms of optimizer accuracy, time to solution, and ease of use. The results suggest that system-level optimization, running as a background process during integrated concurrent engineering sessions, is potentially advantageous as long as it is judiciously implemented.
Realistic modelling of the seismic input: Site effects and parametric studies
International Nuclear Information System (INIS)
Romanelli, F.; Vaccari, F.; Panza, G.F.
2002-11-01
We illustrate the work done in the framework of a large international cooperation, showing the very recent numerical experiments carried out within the framework of the EC project 'Advanced methods for assessing the seismic vulnerability of existing motorway bridges' (VAB) to assess the importance of non-synchronous seismic excitation of long structures. The definition of the seismic input at the Warth bridge site, i.e. the determination of the seismic ground motion due to an earthquake with a given magnitude and epicentral distance from the site, has been done following a theoretical approach. In order to perform an accurate and realistic estimate of site effects and of differential motion it is necessary to make a parametric study that takes into account the complex combination of the source and propagation parameters, in realistic geological structures. The computation of a wide set of time histories and spectral information, corresponding to possible seismotectonic scenarios for different sources and structural models, allows us the construction of damage scenarios that are out of the reach of stochastic models, at a very low cost/benefit ratio. (author)
O'Reilly, Meaghan Anne; Whyne, Cari Marisa
2008-08-01
A comparative analysis of parametric and patient-specific finite element (FE) modeling of spinal motion segments. To develop patient-specific FE models of spinal motion segments using mesh-morphing methods applied to a parametric FE model. To compare strain and displacement patterns in parametric and morphed models for both healthy and metastatically involved vertebrae. Parametric FE models may be limited in their ability to fully represent patient-specific geometries and material property distributions. Generation of multiple patient-specific FE models has been limited because of computational expense. Morphing methods have been successfully used to generate multiple specimen-specific FE models of caudal rat vertebrae. FE models of a healthy and a metastatic T6-T8 spinal motion segment were analyzed with and without patient-specific material properties. Parametric and morphed models were compared using a landmark-based morphing algorithm. Morphing of the parametric FE model and including patient-specific material properties both had a strong impact on magnitudes and patterns of vertebral strain and displacement. Small but important geometric differences can be represented through morphing of parametric FE models. The mesh-morphing algorithm developed provides a rapid method for generating patient-specific FE models of spinal motion segments.
Haque, Md Mazharul; Washington, Simon
2014-01-01
The use of mobile phones while driving is more prevalent among young drivers-a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21-26 years old and split evenly by gender. Drivers' reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted
Creixell-Mediante, Ester; Jensen, Jakob S.; Naets, Frank; Brunskog, Jonas; Larsen, Martin
2018-06-01
Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system performance and modelling them accurately requires a precise description of the strong interaction between the light-weight parts and the internal and surrounding air over a wide frequency range. Parametric optimization of the FE model can be used to reduce the vibroacoustic feedback in a device during the design phase; however, it requires solving the model iteratively for multiple frequencies at different parameter values, which becomes highly time consuming when the system is large. Parametric Model Order Reduction (pMOR) techniques aim at reducing the computational cost associated with each analysis by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we present an adaptive pMOR technique where the construction of the projection basis is embedded in the optimization process and requires fewer full system analyses, while the accuracy of the reduced system is monitored by a cheap error indicator. The performance of the proposed method is evaluated for a 4-parameter optimization of a frequency response for a hearing aid model, evaluated at 300 frequencies, where the objective function evaluations become more than one order of magnitude faster than for the full system.
International Nuclear Information System (INIS)
Khalvati, Farzad; Wong, Alexander; Haider, Masoom A.
2015-01-01
Prostate cancer is the most common form of cancer and the second leading cause of cancer death in North America. Auto-detection of prostate cancer can play a major role in early detection of prostate cancer, which has a significant impact on patient survival rates. While multi-parametric magnetic resonance imaging (MP-MRI) has shown promise in diagnosis of prostate cancer, the existing auto-detection algorithms do not take advantage of abundance of data available in MP-MRI to improve detection accuracy. The goal of this research was to design a radiomics-based auto-detection method for prostate cancer via utilizing MP-MRI data. In this work, we present new MP-MRI texture feature models for radiomics-driven detection of prostate cancer. In addition to commonly used non-invasive imaging sequences in conventional MP-MRI, namely T2-weighted MRI (T2w) and diffusion-weighted imaging (DWI), our proposed MP-MRI texture feature models incorporate computed high-b DWI (CHB-DWI) and a new diffusion imaging modality called correlated diffusion imaging (CDI). Moreover, the proposed texture feature models incorporate features from individual b-value images. A comprehensive set of texture features was calculated for both the conventional MP-MRI and new MP-MRI texture feature models. We performed feature selection analysis for each individual modality and then combined best features from each modality to construct the optimized texture feature models. The performance of the proposed MP-MRI texture feature models was evaluated via leave-one-patient-out cross-validation using a support vector machine (SVM) classifier trained on 40,975 cancerous and healthy tissue samples obtained from real clinical MP-MRI datasets. The proposed MP-MRI texture feature models outperformed the conventional model (i.e., T2w+DWI) with regard to cancer detection accuracy. Comprehensive texture feature models were developed for improved radiomics-driven detection of prostate cancer using MP-MRI. Using a
Evaluation of treatment response in depression studies using a Bayesian parametric cure rate model.
Santen, Gijs; Danhof, Meindert; Della Pasqua, Oscar
2008-10-01
Efficacy trials with antidepressant drugs often fail to show significant treatment effect even though efficacious treatments are investigated. This failure can, amongst other factors, be attributed to the lack of sensitivity of the statistical method as well as of the endpoints to pharmacological activity. For regulatory purposes the most widely used efficacy endpoint is still the mean change in HAM-D score at the end of the study, despite evidence from literature showing that the HAM-D scale might not be a sensitive tool to assess drug effect and that changes from baseline at the end of treatment may not reflect the extent of response. In the current study, we evaluate the prospect of applying a Bayesian parametric cure rate model (CRM) to analyse antidepressant effect in efficacy trials with paroxetine. The model is based on a survival approach, which allows for a fraction of surviving patients indefinitely after completion of treatment. Data was extracted from GlaxoSmithKline's clinical databases. Response was defined as a 50% change from baseline HAM-D at any assessment time after start of therapy. Survival times were described by a log-normal distribution and drug effect was parameterised as a covariate on the fraction of non-responders. The model was able to fit the data from different studies accurately and results show that response to treatment does not lag for two weeks, as is mythically believed. In conclusion, we demonstrate how parameterisation of a survival model can be used to characterise treatment response in depression trials. The method contrasts with the long-established snapshot on changes from baseline, as it incorporates the time course of response throughout treatment.
International Nuclear Information System (INIS)
Bachoc, F.
2013-01-01
The parametric estimation of the covariance function of a Gaussian process is studied, in the framework of the Kriging model. Maximum Likelihood and Cross Validation estimators are considered. The correctly specified case, in which the covariance function of the Gaussian process does belong to the parametric set used for estimation, is first studied in an increasing-domain asymptotic framework. The sampling considered is a randomly perturbed multidimensional regular grid. Consistency and asymptotic normality are proved for the two estimators. It is then put into evidence that strong perturbations of the regular grid are always beneficial to Maximum Likelihood estimation. The incorrectly specified case, in which the covariance function of the Gaussian process does not belong to the parametric set used for estimation, is then studied. It is shown that Cross Validation is more robust than Maximum Likelihood in this case. Finally, two applications of the Kriging model with Gaussian processes are carried out on industrial data. For a validation problem of the friction model of the thermal-hydraulic code FLICA 4, where experimental results are available, it is shown that Gaussian process modeling of the FLICA 4 code model error enables to considerably improve its predictions. Finally, for a meta modeling problem of the GERMINAL thermal-mechanical code, the interest of the Kriging model with Gaussian processes, compared to neural network methods, is shown. (author) [fr
Zhu, Yanjie; Peng, Xi; Wu, Yin; Wu, Ed X; Ying, Leslie; Liu, Xin; Zheng, Hairong; Liang, Dong
2017-02-01
To develop a new model-based method with spatial and parametric constraints (MB-SPC) aimed at accelerating diffusion tensor imaging (DTI) by directly estimating the diffusion tensor from highly undersampled k-space data. The MB-SPC method effectively incorporates the prior information on the joint sparsity of different diffusion-weighted images using an L1-L2 norm and the smoothness of the diffusion tensor using a total variation seminorm. The undersampled k-space datasets were obtained from fully sampled DTI datasets of a simulated phantom and an ex-vivo experimental rat heart with acceleration factors ranging from 2 to 4. The diffusion tensor was directly reconstructed by solving a minimization problem with a nonlinear conjugate gradient descent algorithm. The reconstruction performance was quantitatively assessed using the normalized root mean square error (nRMSE) of the DTI indices. The MB-SPC method achieves acceptable DTI measures at an acceleration factor up to 4. Experimental results demonstrate that the proposed method can estimate the diffusion tensor more accurately than most existing methods operating at higher net acceleration factors. The proposed method can significantly reduce artifact, particularly at higher acceleration factors or lower SNRs. This method can easily be adapted to MR relaxometry parameter mapping and is thus useful in the characterization of biological tissue such as nerves, muscle, and heart tissue. © 2016 American Association of Physicists in Medicine.
Parametric analyses of DEMO Divertor using two dimensional transient thermal hydraulic modelling
Domalapally, Phani; Di Caro, Marco
2018-05-01
Among the options considered for cooling of the Plasma facing components of the DEMO reactor, water cooling is a conservative option because of its high heat removal capability. In this work a two-dimensional transient thermal hydraulic code is developed to support the design of the divertor for the projected DEMO reactor with water as a coolant. The mathematical model accounts for transient 2D heat conduction in the divertor section. Temperature-dependent properties are used for more accurate analysis. Correlations for single phase flow forced convection, partially developed subcooled nucleate boiling, fully developed subcooled nucleate boiling and film boiling are used to calculate the heat transfer coefficients on the channel side considering the swirl flow, wherein different correlations found in the literature are compared against each other. Correlation for the Critical Heat Flux is used to estimate its limit for a given flow conditions. This paper then investigates the results of the parametric analysis performed, whereby flow velocity, diameter of the coolant channel, thickness of the coolant pipe, thickness of the armor material, inlet temperature and operating pressure affect the behavior of the divertor under steady or transient heat fluxes. This code will help in understanding the basic parameterś effect on the behavior of the divertor, to achieve a better design from a thermal hydraulic point of view.
Edge Sharpness Assessment by Parametric Modeling: Application to Magnetic Resonance Imaging.
Ahmad, R; Ding, Y; Simonetti, O P
2015-05-01
In biomedical imaging, edge sharpness is an important yet often overlooked image quality metric. In this work, a semi-automatic method to quantify edge sharpness in the presence of significant noise is presented with application to magnetic resonance imaging (MRI). The method is based on parametric modeling of image edges. First, an edge map is automatically generated and one or more edges-of-interest (EOI) are manually selected using graphical user interface. Multiple exclusion criteria are then enforced to eliminate edge pixels that are potentially not suitable for sharpness assessment. Second, at each pixel of the EOI, an image intensity profile is read along a small line segment that runs locally normal to the EOI. Third, the profiles corresponding to all EOI pixels are individually fitted with a sigmoid function characterized by four parameters, including one that represents edge sharpness. Last, the distribution of the sharpness parameter is used to quantify edge sharpness. For validation, the method is applied to simulated data as well as MRI data from both phantom imaging and cine imaging experiments. This method allows for fast, quantitative evaluation of edge sharpness even in images with poor signal-to-noise ratio. Although the utility of this method is demonstrated for MRI, it can be adapted for other medical imaging applications.
Parametric CAD and Fea Model of a Saddle Tapping Tee
DEFF Research Database (Denmark)
A. Kristensen, Anders Schmidt; Lund Jepsen, Kristian
2007-01-01
Often it is necessary to branch of a pipe section on an oilrig. This operation is often performed by making a so-called "Hot Tapping", which involves welding a pipe and a flange on to the pipe section. A spherical valve and a gate are mounted on to the flange, i.e. weld-o-let. In order to perform...... the welding operations a so-called habitat must be constructed. This habitat encapsulates the "Hot Tapping" spot and is relatively costly. Thus, to avoid weld operations on to the pipeline, a solution with clamps has been developed, i.e. a Saddle Tapping Tee. The Saddle Tapping Tee is clamped on the pipe...... is determined from paragraph K302.3.2 in ASME B31.3. A full parametric 3D CAD model of the Saddle Tapping Tee is developed where a number of user-defined parameters are controlled from an Excel spreadsheet allowing parameter studies and technical documentation to be generated effectively. The same Excel spread...
Fluid flow in porous media using image-based modelling to parametrize Richards' equation.
Cooper, L J; Daly, K R; Hallett, P D; Naveed, M; Koebernick, N; Bengough, A G; George, T S; Roose, T
2017-11-01
The parameters in Richards' equation are usually calculated from experimentally measured values of the soil-water characteristic curve and saturated hydraulic conductivity. The complex pore structures that often occur in porous media complicate such parametrization due to hysteresis between wetting and drying and the effects of tortuosity. Rather than estimate the parameters in Richards' equation from these indirect measurements, image-based modelling is used to investigate the relationship between the pore structure and the parameters. A three-dimensional, X-ray computed tomography image stack of a soil sample with voxel resolution of 6 μm has been used to create a computational mesh. The Cahn-Hilliard-Stokes equations for two-fluid flow, in this case water and air, were applied to this mesh and solved using the finite-element method in COMSOL Multiphysics. The upscaled parameters in Richards' equation are then obtained via homogenization. The effect on the soil-water retention curve due to three different contact angles, 0°, 20° and 60°, was also investigated. The results show that the pore structure affects the properties of the flow on the large scale, and different contact angles can change the parameters for Richards' equation.
Feliciano, Julio Lebron; Kazemi, Amirkhosro; Carbajal, Gerardo; Tutkun, Murat; Bocanegra Evans, Humberto; Curet, Oscar; Castillo, Luciano
2017-11-01
Mangroves are tropical and subtropical trees that aid in protecting coastlines by dissipating the energy carried by tidal flows. These trees attenuate the devastating effects of powerful natural disasters such as hurricanes. Their roots form complex networks extending out of the water's surface and interacting with the tidal flow in estuaries, deltas, and other inter-tidal areas. This study focuses on the parametrization of the hydrodynamics of mangrove root-like geometries and the effect of the mangrove patch porosity and flexural stiffness. A multivariable non-dimensional empirical correlation is proposed to obtain a self-similar solution that describes the hydrodynamics. We introduced an effective-diameter length scale based on the wake signature of the mangrove root models. It was found that in this new dimensionless parameter, based on the Reynolds number and porosity, was able to characterize the drag coefficient. This analysis is complemented with high-resolution PIV experiments performed in a water tank under various flow and porosity conditions. Furthermore, we analyzed the Vortex-Induced Vibrations (VIVs) of the flexible mangrove patch that produce oscillating energy as a potential source for energy harvesting.
Wouters, Hendrik; Blahak, Ulrich; Helmert, Jürgen; Raschendorfer, Matthias; Demuzere, Matthias; Fay, Barbara; Trusilova, Kristina; Mironov, Dmitrii; Reinert, Daniel; Lüthi, Daniel; Machulskaya, Ekaterina
2015-04-01
In order to address urban climate at the regional scales, a new efficient urban land-surface parametrization TERRA_URB has been developed and coupled to the atmospheric numerical model COSMO-CLM. Hereby, several new advancements for urban land-surface models are introduced which are crucial for capturing the urban surface-energy balance and its seasonal dependency in the mid-latitudes. This includes a new PDF-based water-storage parametrization for impervious land, the representation of radiative absorption and emission by greenhouse gases in the infra-red spectrum in the urban canopy layer, and the inclusion of heat emission from human activity. TERRA_URB has been applied in offline urban-climate studies during European observation campaigns at Basel (BUBBLE), Toulouse (CAPITOUL), and Singapore, and currently applied in online studies for urban areas in Belgium, Germany, Switzerland, Helsinki, Singapore, and Melbourne. Because of its computational efficiency, high accuracy and its to-the-point conceptual easiness, TERRA_URB has been selected to become the standard urban parametrization of the atmospheric numerical model COSMO(-CLM). This allows for better weather forecasts for temperature and precipitation in cities with COSMO, and an improved assessment of urban outdoor hazards in the context of global climate change and urban expansion with COSMO-CLM. We propose additional extensions to TERRA_URB towards a more robust representation of cities over the world including their structural design. In a first step, COSMO's standard EXTernal PARarameter (EXTPAR) tool is updated for representing the cities into the land cover over the entire globe. Hereby, global datasets in the standard EXTPAR tool are used to retrieve the 'Paved' or 'sealed' surface Fraction (PF) referring to the presence of buildings and streets. Furthermore, new global data sets are incorporated in EXTPAR for describing the Anthropogenic Heat Flux (AHF) due to human activity, and optionally the
Haj-Ali, Rami; Marom, Gil; Ben Zekry, Sagit; Rosenfeld, Moshe; Raanani, Ehud
2012-09-21
The complex three-dimensional (3D) geometry of the native tricuspid aortic valve (AV) is represented by select parametric curves allowing for a general construction and representation of the 3D-AV structure including the cusps, commissures and sinuses. The proposed general mathematical description is performed by using three independent parametric curves, two for the cusp and one for the sinuses. These curves are used to generate different surfaces that form the structure of the AV. Additional dependent curves are also generated and utilized in this process, such as the joint curve between the cusps and the sinuses. The model's feasibility to generate patient-specific parametric geometry is examined against 3D-transesophageal echocardiogram (3D-TEE) measurements from a non-pathological AV. Computational finite-element (FE) mesh can then be easily constructed from these surfaces. Examples are given for constructing several 3D-AV geometries by estimating the needed parameters from echocardiographic measurements. The average distance (error) between the calculated geometry and the 3D-TEE measurements was only 0.78±0.63mm. The proposed general 3D parametric method is very effective in quantitatively representing a wide range of native AV structures, with and without pathology. It can also facilitate a methodical quantitative investigation over the effect of pathology and mechanical loading on these major AV parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
H.-W. Wong
2010-04-01
Full Text Available Condensation trails (contrails formed from water vapor emissions behind aircraft engines are the most uncertain components of the aviation impacts on climate change. To gain improved knowledge of contrail and contrail-induced cirrus cloud formation, understanding of contrail ice particle formation immediately after aircraft engines is needed. Despite many efforts spent in modeling the microphysics of ice crystal formation in jet regime (with a plume age <5 s, systematic understanding of parametric effects of variables affecting contrail ice particle formation is still limited. In this work, we apply a microphysical parcel modeling approach to study contrail ice particle formation in near-field aircraft plumes up to 1000 m downstream of an aircraft engine in the soot-rich regime (soot number emission index >1×10^{15} (kg-fuel^{−1} at cruise. The effects of dilution history, ion-mediated nucleation, ambient relative humidity, fuel sulfur contents, and initial soot emissions were investigated. Our simulation results suggest that ice particles are mainly formed by water condensation on emitted soot particles. The growth of ice coated soot particles is driven by water vapor emissions in the first 1000 m and by ambient relative humidity afterwards. The presence of chemi-ions does not significantly contribute to the formation of ice particles in the soot-rich regime, and the effect of fuel sulfur contents is small over the range typical of standard jet fuels. The initial properties of soot emissions play the most critical role, and our calculations suggest that higher number concentration and smaller size of contrail particle nuclei may be able to effectively suppress the formation of contrail ice particles. Further modeling and experimental studies are needed to verify if our findings can provide a possible approach for contrail mitigation.
Ermida, S. L.; Trigo, I. F.; DaCamara, C.; Ghent, D.
2017-12-01
Land surface temperature (LST) values retrieved from satellite measurements in the thermal infrared (TIR) may be strongly affected by spatial anisotropy. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a parametric model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. Two models are consistently analyzed to evaluate their performance of and to assess their respective potential to correct directional effects on LST for a wide range of surface conditions, in terms of tree coverage, vegetation density, surface emissivity. We also propose an optimization of the correction of directional effects through a synergistic use of both models. The models are calibrated using LST data as provided by two sensors: MODIS on-board NASA's TERRA and AQUA; and SEVIRI on-board EUMETSAT's MSG. As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is stratified by means of a cluster analysis using information on land cover type, fraction of vegetation cover and topography. The models are then adjusted to LST data corresponding to each cluster. It is shown that the quality of the cluster based models is very close to the pixel based ones. Furthermore, the reduced number of parameters allows improving the model trough the incorporation of a
Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI.
Dikaios, Nikolaos; Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki; Abd-Alazeez, Mohamed; Kirkham, Alex; Allen, Clare; Ahmed, Hashim; Emberton, Mark; Freeman, Alex; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit
2015-02-01
We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. • MRI helps find prostate cancer in the anterior of the gland • Logistic regression models based on mp-MRI can classify prostate cancer • Computers can help confirm cancer in areas doctors are uncertain about.
International Nuclear Information System (INIS)
Ma, Peizheng; Wang, Lin-Shu; Guo, Nianhua
2014-01-01
Highlights: • Investigated cooling of thermally homeostatic buildings in 7 U.S. cities by modeling. • Natural energy is harnessed by cooling tower to extract heat for building cooling. • Systematically studied possibility and conditions of using cooling tower in buildings. • Diurnal ambient temperature amplitude is taken into account in cooling tower cooling. • Homeostatic building cooling is possible in locations with large ambient T amplitude. - Abstract: A case is made that while it is important to mitigate dissipative losses associated with heat dissipation and mechanical/electrical resistance for engineering efficiency gain, the “architect” of energy efficiency is the conception of best heat extraction frameworks—which determine the realm of possible efficiency. This precept is applied to building energy efficiency here. Following a proposed process assumption-based design method, which was used for determining the required thermal qualities of building thermal autonomy, this paper continues this line of investigation and applies heat extraction approach investigating the extent of building partial homeostasis and the possibility of full homeostasis by using cooling tower in one summer in seven selected U.S. cities. Cooling tower heat extraction is applied parametrically to hydronically activated radiant-surfaces model-buildings. Instead of sizing equipment as a function of design peak hourly temperature as it is done in heat balance design-approach of selecting HVAC equipment, it is shown that the conditions of using cooling tower depend on both “design-peak” daily-mean temperature and the distribution of diurnal range in hourly temperature (i.e., diurnal temperature amplitude). Our study indicates that homeostatic building with natural cooling (by cooling tower alone) is possible only in locations of special meso-scale climatic condition such as Sacramento, CA. In other locations the use of cooling tower alone can only achieve homeostasis
Energy Technology Data Exchange (ETDEWEB)
Hourdin, Frederic; Musat, Ionela; Bony, Sandrine; Codron, Francis; Dufresne, Jean-Louis; Fairhead, Laurent; Grandpeix, Jean-Yves; LeVan, Phu; Li, Zhao-Xin; Lott, Francois [CNRS/UPMC, Laboratoire de Meteorologie Dynamique (LMD/IPSL), Paris Cedex 05 (France); Braconnot, Pascale; Friedlingstein, Pierre [Laboratoire des Sciences du Climat et de l' Environnement (LSCE/IPSL), Saclay (France); Filiberti, Marie-Angele [Institut Pierre Simon Laplace (IPSL), Paris (France); Krinner, Gerhard [Laboratoire de Glaciologie et Geophysique de l' Environnement, Grenoble (France)
2006-12-15
The LMDZ4 general circulation model is the atmospheric component of the IPSL-CM4 coupled model which has been used to perform climate change simulations for the 4th IPCC assessment report. The main aspects of the model climatology (forced by observed sea surface temperature) are documented here, as well as the major improvements with respect to the previous versions, which mainly come form the parametrization of tropical convection. A methodology is proposed to help analyse the sensitivity of the tropical Hadley-Walker circulation to the parametrization of cumulus convection and clouds. The tropical circulation is characterized using scalar potentials associated with the horizontal wind and horizontal transport of geopotential (the Laplacian of which is proportional to the total vertical momentum in the atmospheric column). The effect of parametrized physics is analysed in a regime sorted framework using the vertical velocity at 500 hPa as a proxy for large scale vertical motion. Compared to Tiedtke's convection scheme, used in previous versions, the Emanuel's scheme improves the representation of the Hadley-Walker circulation, with a relatively stronger and deeper large scale vertical ascent over tropical continents, and suppresses the marked patterns of concentrated rainfall over oceans. Thanks to the regime sorted analyses, these differences are attributed to intrinsic differences in the vertical distribution of convective heating, and to the lack of self-inhibition by precipitating downdraughts in Tiedtke's parametrization. Both the convection and cloud schemes are shown to control the relative importance of large scale convection over land and ocean, an important point for the behaviour of the coupled model. (orig.)
Degeling, Koen; IJzerman, Maarten J.; Koopman, Miriam; Koffijberg, Hendrik
2017-01-01
Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by ...
A parametric FE modeling of brake for non-linear analysis
Energy Technology Data Exchange (ETDEWEB)
Ahmed,Ibrahim; Fatouh, Yasser [Automotive and Tractors Technology Department, Faculty of Industrial Education, Helwan University, Cairo (Egypt); Aly, Wael [Refrigeration and Air-Conditioning Technology Department, Faculty of Industrial Education, Helwan University, Cairo (Egypt)
2013-07-01
A parametric modeling of a drum brake based on 3-D Finite Element Methods (FEM) for non-contact analysis is presented. Many parameters are examined during this study such as the effect of drum-lining interface stiffness, coefficient of friction, and line pressure on the interface contact. Firstly, the modal analysis of the drum brake is also studied to get the natural frequency and instability of the drum to facilitate transforming the modal elements to non-contact elements. It is shown that the Unsymmetric solver of the modal analysis is efficient enough to solve this linear problem after transforming the non-linear behavior of the contact between the drum and the lining to a linear behavior. A SOLID45 which is a linear element is used in the modal analysis and then transferred to non-linear elements which are Targe170 and Conta173 that represent the drum and lining for contact analysis study. The contact analysis problems are highly non-linear and require significant computer resources to solve it, however, the contact problem give two significant difficulties. Firstly, the region of contact is not known based on the boundary conditions such as line pressure, and drum and friction material specs. Secondly, these contact problems need to take the friction into consideration. Finally, it showed a good distribution of the nodal reaction forces on the slotted lining contact surface and existing of the slot in the middle of the lining can help in wear removal due to the friction between the lining and the drum. Accurate contact stiffness can give a good representation for the pressure distribution between the lining and the drum. However, a full contact of the front part of the slotted lining could occur in case of 20, 40, 60 and 80 bar of piston pressure and a partially contact between the drum and lining can occur in the rear part of the slotted lining.
An Efficient Bundle Adjustment Model Based on Parallax Parametrization for Environmental Monitoring
Chen, R.; Sun, Y. Y.; Lei, Y.
2017-12-01
With the rapid development of Unmanned Aircraft Systems (UAS), more and more research fields have been successfully equipped with this mature technology, among which is environmental monitoring. One difficult task is how to acquire accurate position of ground object in order to reconstruct the scene more accurate. To handle this problem, we combine bundle adjustment method from Photogrammetry with parallax parametrization from Computer Vision to create a new method call APCP (aerial polar-coordinate photogrammetry). One impressive advantage of this method compared with traditional method is that the 3-dimensional point in space is represented using three angles (elevation angle, azimuth angle and parallax angle) rather than the XYZ value. As the basis for APCP, bundle adjustment could be used to optimize the UAS sensors' pose accurately, reconstruct the 3D models of environment, thus serving as the criterion of accurate position for monitoring. To verity the effectiveness of the proposed method, we test on several UAV dataset obtained by non-metric digital cameras with large attitude angles, and we find that our methods could achieve 1 or 2 times better efficiency with no loss of accuracy than traditional ones. For the classical nonlinear optimization of bundle adjustment model based on the rectangular coordinate, it suffers the problem of being seriously dependent on the initial values, making it unable to converge fast or converge to a stable state. On the contrary, APCP method could deal with quite complex condition of UAS when conducting monitoring as it represent the points in space with angles, including the condition that the sequential images focusing on one object have zero parallax angle. In brief, this paper presents the parameterization of 3D feature points based on APCP, and derives a full bundle adjustment model and the corresponding nonlinear optimization problems based on this method. In addition, we analyze the influence of convergence and
Gu, Yongxian
The demand of portable power generation systems for both domestic and military applications has driven the advances of mesoscale internal combustion engine systems. This dissertation was devoted to the gasdynamic modeling and parametric study of the mesoscale internal combustion swing engine/generator systems. First, the system-level thermodynamic modeling for the swing engine/generator systems has been developed. The system performance as well as the potentials of both two- and four-stroke swing engine systems has been investigated based on this model. Then through parameterc studies, the parameters that have significant impacts on the system performance have been identified, among which, the burn time and spark advance time are the critical factors related to combustion process. It is found that the shorter burn time leads to higher system efficiency and power output and the optimal spark advance time is about half of the burn time. Secondly, the turbulent combustion modeling based on levelset method (G-equation) has been implemented into the commercial software FLUENT. Thereafter, the turbulent flame propagation in a generic mesoscale combustion chamber and realistic swing engine chambers has been studied. It is found that, in mesoscale combustion engines, the burn time is dominated by the mean turbulent kinetic energy in the chamber. It is also shown that in a generic mesoscale combustion chamber, the burn time depends on the longest distance between the initial ignition kernel to its walls and by changing the ignition and injection locations, the burn time can be reduced by a factor of two. Furthermore, the studies of turbulent flame propagation in real swing engine chambers show that the combustion can be enhanced through in-chamber turbulence augmentation and with higher engine frequency, the burn time is shorter, which indicates that the in-chamber turbulence can be induced by the motion of moving components as well as the intake gas jet flow. The burn time
DEFF Research Database (Denmark)
Mazzucco, Andrea; Rothuizen, Erasmus; Jørgensen, Jens-Erik
2016-01-01
to the phase change material, mainly occurs after the fueling is completed, resulting in a hydrogen peak temperature higher than 85 C and a lower fueled mass than a gas-cooled system. Such a mass reduction accounts for 12% with respect to the case of a standard tank system fueled at 40 C. A parametric analysis...
A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models
DEFF Research Database (Denmark)
Podolskij, Mark; Ziggel, Daniel
statistic. Under rather weak assumptions on the drift and volatility we prove weak convergence of the test statistic to a centered mixed Gaussian distribution. As a consequence we obtain a test, which is consistent for any fixed alternative. Moreover, we present a parametric bootstrap procedure which...
The Use of Metaphors as a Parametric Design Teaching Model: A Case Study
Agirbas, Asli
2018-01-01
Teaching methodologies for parametric design are being researched all over the world, since there is a growing demand for computer programming logic and its fabrication process in architectural education. The computer programming courses in architectural education are usually done in a very short period of time, and so students have no chance to…
International Nuclear Information System (INIS)
Schröpfer, Gerold; Lorenz, Gunar; Rouvillois, Stéphane; Breit, Stephen
2010-01-01
This paper provides a brief summary of the state-of-the-art of MEMS-specific modeling techniques and describes the validation of new models for a parametric component library. Two recently developed 3D modeling tools are described in more detail. The first one captures a methodology for designing MEMS devices and simulating them together with integrated electronics within a standard electronic design automation (EDA) environment. The MEMS designer can construct the MEMS model directly in a 3D view. The resulting 3D model differs from a typical feature-based 3D CAD modeling tool in that there is an underlying behavioral model and parametric layout associated with each MEMS component. The model of the complete MEMS device that is shared with the standard EDA environment can be fully parameterized with respect to manufacturing- and design-dependent variables. Another recent innovation is a process modeling tool that allows accurate and highly realistic visualization of the step-by-step creation of 3D micro-fabricated devices. The novelty of the tool lies in its use of voxels (3D pixels) rather than conventional 3D CAD techniques to represent the 3D geometry. Case studies for experimental devices are presented showing how the examination of these virtual prototypes can reveal design errors before mask tape out, support process development before actual fabrication and also enable failure analysis after manufacturing.
Directory of Open Access Journals (Sweden)
MARINA I AVERSA
2011-03-01
Full Text Available Age and growth for the beaked skate was estimated from bands in the vertebral centra of 689 individuals obtained from incidental catches of the Argentine hake (Merluccius hubbsi fishery. Age bias plots and indices of precision indicated that ageing method was precise and unbiased (% CV = 3 % PA = 82.09 %. Edge and marginal increment analysis of the vertebrae support the hypothesis of annual band pair deposition. Three growth models were fitted to length-at-age and the two-phase growth model produced the best fit. This feature has never been described before for D. chilensis and can be related to changes in energy allocation and the shift from juvenile to adult phase. The unrealistic biological estimates of the von Bertalanffy growth model illustrates the importance of fitting alternative models to the data. Female beaked skates reached greater size in length (L∝ as well as in disc width (L∝ = 138.2 cm; DW∝ = 92.46 cm and have lower growth rate (k = 0.08 yr-1 than males (L∝ = 106.7 cm; DW∝ = 74.52 cm; k = 0.121 yr-1. This study provides basic information on age and growth for the beaked skate, D. chilensis, which were previously not available for its south Atlantic range of distribution.La edad y el crecimiento de la raya picuda fue estimado a partir de las bandas en los cuerpos vertebrales de 689 individuos obtenidos de las capturas incidentales de la pesquería de merluza argentina (Merluccius hubbsi. Gráficos de sesgos y el análisis de precisión indicaron que el método utilizado para la determinación de la edad es preciso y no sesgado (% CV = 3 % PA = 82.09 %. El análisis del tipo de borde e incremento marginal vertebral confirmó la hipótesis del depósito anual de un par de bandas. Se ajustaron tres modelos de crecimiento a los datos de largo a la edad y el modelo de dos fases produjo el mejor ajuste. Esta característica nunca antes fue descripta para Dipturus chilensis y podría relacionarse con un cambio en la cuota de
Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker
2012-08-01
Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.
DEFF Research Database (Denmark)
Rosthøj, Susanne; Keiding, Niels
2004-01-01
When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. Measures of predictive accuracy are used to assess the accuracy of the predictions based on the covariates and the regression model. We give a ...... a detailed and general introduction to the two measures and the estimation procedures. The framework we set up allows for a study of the effect of misspecification on the quantities estimated. We also introduce a generalization to survival analysis....
Czech Academy of Sciences Publication Activity Database
Svoboda, Jiří; Gamsjäger, E.
2011-01-01
Roč. 102, č. 6 (2011), s. 666-673 ISSN 1862-5282 R&D Projects: GA MŠk(CZ) OC10029 Institutional research plan: CEZ:AV0Z20410507 Keywords : modelling * phase transformation * ediffusion Subject RIV: BJ - Thermodynamics Impact factor: 0.830, year: 2011
Forecasting Exchange Rate Density Using Parametric Models: the Case of Brazil
Directory of Open Access Journals (Sweden)
Benjamin Miranda Tabak
2007-06-01
Full Text Available This paper employs a recently developed parametric technique to obtain density forecasts for the Brazilian exchange rate, using the exchange rate options market. Empirical results suggest that the option market contains useful information about future exchange rate density. These results suggests that density forecasts using options markets may add value for portfolio and risk management, and may be useful for financial regulators to assess financial stability.
Directory of Open Access Journals (Sweden)
G. Lebedeva
2004-06-01
Full Text Available In the publication the methodical aspects of a mathematical model of the combined parametrical analysis of an indicator process and thermal loading on the diesel engine piston have been considered. A thermodynamic model of a diesel engine cycle is developed. The executed development is intended for use during researches and on the initial stages of design work. Its realization for high revolution diesel engines of perspective type CHN15/15 allowed to choose rational variants for the organization of an indicator process and to prove power ranges of application for not cooled and created cooled oil welded pistons.
Directory of Open Access Journals (Sweden)
I. Foyo-Moreno
2000-11-01
Full Text Available Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l., an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290–385 nm. After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those
Directory of Open Access Journals (Sweden)
I. Foyo-Moreno
Full Text Available Since the discovery of the ozone depletion in Antarctic and the globally declining trend of stratospheric ozone concentration, public and scientific concern has been raised in the last decades. A very important consequence of this fact is the increased broadband and spectral UV radiation in the environment and the biological effects and heath risks that may take place in the near future. The absence of widespread measurements of this radiometric flux has lead to the development and use of alternative estimation procedures such as the parametric approaches. Parametric models compute the radiant energy using available atmospheric parameters. Some parametric models compute the global solar irradiance at surface level by addition of its direct beam and diffuse components. In the present work, we have developed a comparison between two cloudless sky parametrization schemes. Both methods provide an estimation of the solar spectral irradiance that can be integrated spectrally within the limits of interest. For this test we have used data recorded in a radiometric station located at Granada (37.180°N, 3.580°W, 660 m a.m.s.l., an inland location. The database includes hourly values of the relevant variables covering the years 1994-95. The performance of the models has been tested in relation to their predictive capability of global solar irradiance in the UV range (290–385 nm. After our study, it appears that information concerning the aerosol radiative effects is fundamental in order to obtain a good estimation. The original version of SPCTRAL2 provides estimates of the experimental values with negligible mean bias deviation. This suggests not only the appropriateness of the model but also the convenience of the aerosol features fixed in it to Granada conditions. SMARTS2 model offers increased flexibility concerning the selection of different aerosol models included in the code and provides the best results when the selected models are those
Energy Technology Data Exchange (ETDEWEB)
Boehme, M.
2004-07-01
Continuos improvement of processes and methodologies is one key element to shorten development time, reduce costs, and improve quality, and therefore to answer growing customer demands and global competition. This work describes a new concept of introducing the principles of parametric modeling to the entire product data model in the area of automotive development. Based on the idea, that not only geometric dimensions can be described by parameters, the method of parametric modeling is applied to the complete product model. The concept assumes four major principles: First, the parameters of the product model are handled independently from their proprietary data formats. Secondly, a strictly hierarchical structure is required for the parametric description of the product. The third principle demands an object-based parameterization. Finally the use of parameter-sets for the description of logical units of the product model tree is part of the concept. Those four principles are addressing the following main objectives: Supporting and improving Simultaneous Engineering, achieving data consistency over all development phases, digital approval of product properties, and incorporation of the design intent into the product model. Further improvement of the automotive development process can be achieved with the introduction of parametric product modeling using the principles described in this paper. (orig.) [German] Die Forderung nach kuerzeren Entwicklungszeiten, Reduzierung der Kosten und verbesserter Qualitaet erfordert eine stetige Verbesserung von Prozessen und Methoden in der Produktentwicklung. In dieser Arbeit wird ein neuer Ansatz vorgestellt, der die Methodik des parametrischen Konstruierens auf das gesamte Produktmodell in der Fahrzeugentwicklung anwendet, und somit weitere Potentiale zur Verbesserung des Produktentstehungsprozesses erschliesst. Ausgehend von der Annahme, dass nicht nur geometrische Abmessungen als Parameter beschrieben werden koennen, wird die
Zhang, Kai; Cao, Libo; Wang, Yulong; Hwang, Eunjoo; Reed, Matthew P; Forman, Jason; Hu, Jingwen
2017-10-01
Field data analyses have shown that obesity significantly increases the occupant injury risks in motor vehicle crashes, but the injury assessment tools for people with obesity are largely lacking. The objectives of this study were to use a mesh morphing method to rapidly generate parametric finite element models with a wide range of obesity levels and to evaluate their biofidelity against impact tests using postmortem human subjects (PMHS). Frontal crash tests using three PMHS seated in a vehicle rear seat compartment with body mass index (BMI) from 24 to 40 kg/m 2 were selected. To develop the human models matching the PMHS geometry, statistical models of external body shape, rib cage, pelvis, and femur were applied to predict the target geometry using age, sex, stature, and BMI. A mesh morphing method based on radial basis functions was used to rapidly morph a baseline human model into the target geometry. The model-predicted body excursions and injury measures were compared to the PMHS tests. Comparisons of occupant kinematics and injury measures between the tests and simulations showed reasonable correlations across the wide range of BMI levels. The parametric human models have the capability to account for the obesity effects on the occupant impact responses and injury risks. © 2017 The Obesity Society.
Beller, S.; Monteiller, V.; Combe, L.; Operto, S.; Nolet, G.
2018-02-01
Full-waveform inversion (FWI) is not yet a mature imaging technology for lithospheric imaging from teleseismic data. Therefore, its promise and pitfalls need to be assessed more accurately according to the specifications of teleseismic experiments. Three important issues are related to (1) the choice of the lithospheric parametrization for optimization and visualization, (2) the initial model and (3) the acquisition design, in particular in terms of receiver spread and sampling. These three issues are investigated with a realistic synthetic example inspired by the CIFALPS experiment in the Western Alps. Isotropic elastic FWI is implemented with an adjoint-state formalism and aims to update three parameter classes by minimization of a classical least-squares difference-based misfit function. Three different subsurface parametrizations, combining density (ρ) with P and S wave speeds (Vp and Vs) , P and S impedances (Ip and Is), or elastic moduli (λ and μ) are first discussed based on their radiation patterns before their assessment by FWI. We conclude that the (ρ, λ, μ) parametrization provides the FWI models that best correlate with the true ones after recombining a posteriori the (ρ, λ, μ) optimization parameters into Ip and Is. Owing to the low frequency content of teleseismic data, 1-D reference global models as PREM provide sufficiently accurate initial models for FWI after smoothing that is necessary to remove the imprint of the layering. Two kinds of station deployments are assessed: coarse areal geometry versus dense linear one. We unambiguously conclude that a coarse areal geometry should be favoured as it dramatically increases the penetration in depth of the imaging as well as the horizontal resolution. This results because the areal geometry significantly increases local wavenumber coverage, through a broader sampling of the scattering and dip angles, compared to a linear deployment.
Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design
Holt, James B.; Dees, Patrick D.; Diaz, Manuel J.
2015-01-01
-modal due to the interaction of various constraints. Additionally, when these obstacles are coupled with The Program to Optimize Simulated Trajectories [1] (POST), an industry standard program to optimize ascent trajectories that is difficult to use, it requires expert trajectory analysts to effectively optimize a vehicle's ascent trajectory. As it has been pointed out, the paradigm of trajectory optimization is still a very manual one because using modern computational resources on POST is still a challenging problem. The nuances and difficulties involved in correctly utilizing, and therefore automating, the program presents a large problem. In order to address these issues, the authors will discuss a methodology that has been developed. The methodology is two-fold: first, a set of heuristics will be introduced and discussed that were captured while working with expert analysts to replicate the current state-of-the-art; secondly, leveraging the power of modern computing to evaluate multiple trajectories simultaneously, and therefore, enable the exploration of the trajectory's design space early during the pre-conceptual and conceptual phases of design. When this methodology is coupled with design of experiments in order to train surrogate models, the authors were able to visualize the trajectory design space, enabling parametric optimal ascent trajectory information to be introduced with other pre-conceptual and conceptual design tools. The potential impact of this methodology's success would be a fully automated POST evaluation suite for the purpose of conceptual and preliminary design trade studies. This will enable engineers to characterize the ascent trajectory's sensitivity to design changes in an arbitrary number of dimensions and for finding settings for trajectory specific variables, which result in optimal performance for a "dialed-in" launch vehicle design. The effort described in this paper was developed for the Advanced Concepts Office [2] at NASA Marshall
PARAMETRIC DRAWINGS VS. AUTOLISP
Directory of Open Access Journals (Sweden)
PRUNĂ Liviu
2015-06-01
Full Text Available In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed by the drawing, in the idea to construct outlines or blocks which can be used in the projection process.
PARAMETRIC DRAWINGS VS. AUTOLISP
PRUNĂ Liviu; SLONOVSCHI Andrei
2015-01-01
In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed...
International Nuclear Information System (INIS)
Cassardo, C.; Carena, E.; Longhetto, A.
1998-01-01
The Land Surface Process Model (LSPM) has been improved with respect to the 1. version of 1994. The modifications have involved the parametrizations of the radiation terms and of turbulent heat fluxes. A parametrization of runoff has also been developed, in order to close the hydrologic balance. This 2. version of LSPM has been validated against experimental data gathered at Mottarone (Verbania, Northern Italy) during a field experiment. The results of this validation show that this new version is able to apportionate the energy into sensible and latent heat fluxes. LSPM has also been submitted to a series of sensitivity tests in order to investigate the hydrological part of the model. The physical quantities selected in these sensitivity experiments have been the initial soil moisture content and the rainfall intensity. In each experiment, the model has been forced by using the observations carried out at the synoptic stations of San Pietro Capofiume (Po Valley, Italy). The observed characteristics of soil and vegetation (not involved in the sensitivity tests) have been used as initial and boundary conditions. The results of the simulation show that LSPM can reproduce well the energy, heat and water budgets and their behaviours with varying the selected parameters. A careful analysis of the LSPM output shows also the importance to identify the effective soil type
Madi, Raneem; Huibert de Rooij, Gerrit; Mielenz, Henrike; Mai, Juliane
2018-02-01
Few parametric expressions for the soil water retention curve are suitable for dry conditions. Furthermore, expressions for the soil hydraulic conductivity curves associated with parametric retention functions can behave unrealistically near saturation. We developed a general criterion for water retention parameterizations that ensures physically plausible conductivity curves. Only 3 of the 18 tested parameterizations met this criterion without restrictions on the parameters of a popular conductivity curve parameterization. A fourth required one parameter to be fixed. We estimated parameters by shuffled complex evolution (SCE) with the objective function tailored to various observation methods used to obtain retention curve data. We fitted the four parameterizations with physically plausible conductivities as well as the most widely used parameterization. The performance of the resulting 12 combinations of retention and conductivity curves was assessed in a numerical study with 751 days of semiarid atmospheric forcing applied to unvegetated, uniform, 1 m freely draining columns for four textures. Choosing different parameterizations had a minor effect on evaporation, but cumulative bottom fluxes varied by up to an order of magnitude between them. This highlights the need for a careful selection of the soil hydraulic parameterization that ideally does not only rely on goodness of fit to static soil water retention data but also on hydraulic conductivity measurements. Parameter fits for 21 soils showed that extrapolations into the dry range of the retention curve often became physically more realistic when the parameterization had a logarithmic dry branch, particularly in fine-textured soils where high residual water contents would otherwise be fitted.
Korez, Robert; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž
2014-10-01
Gradual degeneration of intervertebral discs of the lumbar spine is one of the most common causes of low back pain. Although conservative treatment for low back pain may provide relief to most individuals, surgical intervention may be required for individuals with significant continuing symptoms, which is usually performed by replacing the degenerated intervertebral disc with an artificial implant. For designing implants with good bone contact and continuous force distribution, the morphology of the intervertebral disc space and vertebral body endplates is of considerable importance. In this study, we propose a method for parametric modeling of the intervertebral disc space in three dimensions (3D) and show its application to computed tomography (CT) images of the lumbar spine. The initial 3D model of the intervertebral disc space is generated according to the superquadric approach and therefore represented by a truncated elliptical cone, which is initialized by parameters obtained from 3D models of adjacent vertebral bodies. In an optimization procedure, the 3D model of the intervertebral disc space is incrementally deformed by adding parameters that provide a more detailed morphometric description of the observed shape, and aligned to the observed intervertebral disc space in the 3D image. By applying the proposed method to CT images of 20 lumbar spines, the shape and pose of each of the 100 intervertebral disc spaces were represented by a 3D parametric model. The resulting mean (±standard deviation) accuracy of modeling was 1.06±0.98mm in terms of radial Euclidean distance against manually defined ground truth points, with the corresponding success rate of 93% (i.e. 93 out of 100 intervertebral disc spaces were modeled successfully). As the resulting 3D models provide a description of the shape of intervertebral disc spaces in a complete parametric form, morphometric analysis was straightforwardly enabled and allowed the computation of the corresponding
International Nuclear Information System (INIS)
Marchal, Xavier
1992-01-01
In order to use CAD efficiently in the analysis and design of electronic Integrated circuits, adequate modeling of active non-linear devices such as MOSFET transistors must be available to the designer. Many mathematical forms can be given to those models, such as explicit relations, or implicit equations to be solved. A major requirement in developing MOS transistor models for IC simulation is the availability of electrical characteristic curves over a wide range of channel width and length, including the sub-micrometer range. To account in a convenient way for bulk charge influence on I_D_S = f(V_D_S, V_G_S, v_B_S) device characteristics, all 3 standard SPICE MOS models use an empirical fitting parameter called the 'charge sharing factor'. Unfortunately, this formulation produces models which only describe correctly either some of the short channel phenomena, or some particular operating conditions (low injection, avalanche effect, etc.). We present here a cellular model (CDM = Charge Distributed Model) implemented in the open modular SPICE-PAC Simulator; this model is derived from the 4-terminal WANG charge controlled MOSFET model, using the charge sheet approximation. The CDM model describes device characteristics in ail operating regions without introducing drain current discontinuities and without requiring a 'charge sharing factor'. A usual problem to be faced by designers when they simulate MOS ICs is to find a reliable source of model parameters. Though most models have a physical basis, some of their parameters cannot be easily estimated from physical considerations. It can also happen that physically determined parameters values do not produce a good fit to measured device characteristics. Thus it is generally necessary to extract model parameters from measured transistor data, to ensure that model equations approximate measured curves accurately enough. Model parameters extraction can be done in 2 different ways, exposed in this thesis. The first
DEFF Research Database (Denmark)
Niero, Monia; Di Felice, F.; Ren, J.
2014-01-01
LCA methodology is time and resource consuming particularly when it comes to data collection and handling, therefore companies, particularly Small and Medium Enterprises (SMEs), are inclined to use streamlined approaches to shorten the resource-consuming life cycle inventory (LCI) phase. An effec......LCA methodology is time and resource consuming particularly when it comes to data collection and handling, therefore companies, particularly Small and Medium Enterprises (SMEs), are inclined to use streamlined approaches to shorten the resource-consuming life cycle inventory (LCI) phase...... study of a SME in the wooden pallet sector, investigating to what extent the use of parametric LCI models can be beneficial both in evaluating the environmental impacts of similar products and in providing a preliminary assessment of the potential environmental impacts of new products. We developed...... an LCI parametric model describing the LCI of a range of wooden pallets and tested its effectiveness with a reference product, namely a non-reversible pallet with four-way blocks. The identified parameters refer to the technical characteristics of the product system, e.g. the number and dimension...
International Nuclear Information System (INIS)
Frepoli, Cesare; Oriani, Luca
2006-01-01
In recent years, non-parametric or order statistics methods have been widely used to assess the impact of the uncertainties within Best-Estimate LOCA evaluation models. The bounding of the uncertainties is achieved with a direct Monte Carlo sampling of the uncertainty attributes, with the minimum trial number selected to 'stabilize' the estimation of the critical output values (peak cladding temperature (PCT), local maximum oxidation (LMO), and core-wide oxidation (CWO A non-parametric order statistics uncertainty analysis was recently implemented within the Westinghouse Realistic Large Break LOCA evaluation model, also referred to as 'Automated Statistical Treatment of Uncertainty Method' (ASTRUM). The implementation or interpretation of order statistics in safety analysis is not fully consistent within the industry. This has led to an extensive public debate among regulators and researchers which can be found in the open literature. The USNRC-approved Westinghouse method follows a rigorous implementation of the order statistics theory, which leads to the execution of 124 simulations within a Large Break LOCA analysis. This is a solid approach which guarantees that a bounding value (at 95% probability) of the 95 th percentile for each of the three 10 CFR 50.46 ECCS design acceptance criteria (PCT, LMO and CWO) is obtained. The objective of this paper is to provide additional insights on the ASTRUM statistical approach, with a more in-depth analysis of pros and cons of the order statistics and of the Westinghouse approach in the implementation of this statistical methodology. (authors)
NASA's X-Plane Database and Parametric Cost Model v 2.0
Sterk, Steve; Ogluin, Anthony; Greenberg, Marc
2016-01-01
The NASA Armstrong Cost Engineering Team with technical assistance from NASA HQ (SID)has gone through the full process in developing new CERs from Version #1 to Version #2 CERs. We took a step backward and reexamined all of the data collected, such as dependent and independent variables, cost, dry weight, length, wingspan, manned versus unmanned, altitude, Mach number, thrust, and skin. We used a well- known statistical analysis tool called CO$TAT instead of using "R" multiple linear or the "Regression" tool found in Microsoft Excel(TradeMark). We setup an "array of data" by adding 21" dummy variables;" we analyzed the standard error (SE) and then determined the "best fit." We have parametrically priced-out several future X-planes and compared our results to those of other resources. More work needs to be done in getting "accurate and traceable cost data" from historical X-plane records!
A non-parametric framework for estimating threshold limit values
Directory of Open Access Journals (Sweden)
Ulm Kurt
2005-11-01
Full Text Available Abstract Background To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. Methods We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. Results In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. Conclusion The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.
DEFF Research Database (Denmark)
Niero, Monia; Di Felice, Francesco; Ren, Jingzheng
2014-01-01
, as the information required for fulfilling the LCI are standard information about the features of the wooden pallet and its manufacturing process. The contribution analysis on the reference product revealed that the most contributing life cycle stages are wood and nails extraction and manufacturing (positive value......This study discusses the use of parameterization within the life cycle inventory (LCI) in the wooden pallet sector, in order to test the effectiveness of LCI parametric models to calculate the environmental impacts of similar products. Starting from a single case study, the objectives of this paper......; these correlations can be used to improve the design of new wooden pallets.The conceptual scheme for defining the model is based on ISO14040-44 standards. First of all, the product system was defined identifying the life cycle of a generic wood pallet, as well as its life cycle stages. A list of independent...
Directory of Open Access Journals (Sweden)
Francisco Javier Trujillo
2017-02-01
Full Text Available In this work, the study of the influence of cutting parameters (cutting speed, feed, and depth of cut on the tool wear used in in the dry turning of cylindrical bars of the UNS A97075 (Al-Zn alloy, has been analyzed. In addition, a study of the physicochemical mechanisms of the secondary adhesion wear has been carried out. The behavior of this alloy, from the point of view of tool wear, has been compared to similar aeronautical aluminum alloys, such as the UNS A92024 (Al-Cu alloy and UNS A97050 (Al-Zn alloy. Furthermore, a first approach to the measurement of the 2D surface of the adhered material on the rake face of the tool has been conducted. Finally, a parametric model has been developed from the experimental results. This model allows predicting the intensity of the secondary adhesion wear as a function of the cutting parameters applied.
Directory of Open Access Journals (Sweden)
Koen Degeling
2017-12-01
Full Text Available Abstract Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Methods Two approaches, 1 using non-parametric bootstrapping and 2 using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Results Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500, the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25, yielding infeasible modeling outcomes. Conclusions Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik
2017-12-15
Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.
Anurose, T. J.; Subrahamanyam, D. Bala
2013-06-01
We discuss the impact of the differential treatment of the roughness lengths for momentum and heat (z_{0m} and z_{0h}) in the flux parametrization scheme of the high-resolution regional model (HRM) for a heterogeneous terrain centred around Thiruvananthapuram, India (8.5°N, 76.9°E). The magnitudes of sensible heat flux ( H) obtained from HRM simulations using the original parametrization scheme differed drastically from the concurrent in situ observations. With a view to improving the performance of this parametrization scheme, two distinct modifications are incorporated: (1) In the first method, a constant value of 100 is assigned to the z_{0m}/z_{0h} ratio; (2) and in the second approach, this ratio is treated as a function of time. Both these modifications in the HRM model showed significant improvements in the H simulations for Thiruvananthapuram and its adjoining regions. Results obtained from the present study provide a first-ever comparison of H simulations using the modified parametrization scheme in the HRM model with in situ observations for the Indian coastal region, and suggest a differential treatment of z_{0m} and z_{0h} in the flux parametrization scheme.
Directory of Open Access Journals (Sweden)
Corrado Dimauro
2010-11-01
Full Text Available Test day records for milk yield of 57,390 first lactation Canadian Holsteins were analyzed with a linear model that included the fixed effects of herd-test date and days in milk (DIM interval nested within age and calving season. Residuals from this model were analyzed as a new variable and fitted with a five parameter model, fourth-order Legendre polynomials, with linear, quadratic and cubic spline models with three knots. The fit of the models was rather poor, with about 30-40% of the curves showing an adjusted R-square lower than 0.20 across all models. Results underline a great difficulty in modelling individual deviations around the mean curve for milk yield. However, the Ali and Schaeffer (5 parameter model and the fourth-order Legendre polynomials were able to detect two basic shapes of individual deviations among the mean curve. Quadratic and, especially, cubic spline functions had better fitting performances but a poor predictive ability due to their great flexibility that results in an abrupt change of the estimated curve when data are missing. Parametric and orthogonal polynomials seem to be robust and affordable under this standpoint.
Timoshinova, T. S.; Shmatov, D. P.; Kretinin, A. V.; Drozdov, I. G.
2017-11-01
While formulating a mathematical model of the flow and interaction between oxygen-methane fuel combustion products with tangentially swirled ballast water injected in the end of the combustion chamber in CAE product Fluent, which integrated into the ANSYS Workbench platform, the problem of structural-parametric synthesis is solved for structure optimization of the model. Equations are selected from the catalogue of Fluent physical models. Also optimization helps to find “regime” model parameters that determine the specific implementation of the model inside the synthesized structure. As a result, such solutions which were developed during creation of a numerical algorithm, as the choice of a turbulence model and the state equation, the methods for determining the thermodynamic thermophysical characteristics of combustion products, the choice of the radiation model, the choice of the resistance law for drops, the choice of the expression which allows to evaluate swirling flows lateral force, determination of the turbulent dispersion strength, choice of the mass exchange law, etc. Fields of temperature, pressure, velocity and volume fraction of phases were obtained at different ballast water mass flows. Dependence of wall temperature from mass flow of ballast water is constructed, that allows us to compare results of the experiment and mathematical modeling.
Alfano, R.; Soetemans, D.; Bauman, G. S.; Gibson, E.; Gaed, M.; Moussa, M.; Gomez, J. A.; Chin, J. L.; Pautler, S.; Ward, A. D.
2018-02-01
Multi-parametric MRI (mp-MRI) is becoming a standard in contemporary prostate cancer screening and diagnosis, and has shown to aid physicians in cancer detection. It offers many advantages over traditional systematic biopsy, which has shown to have very high clinical false-negative rates of up to 23% at all stages of the disease. However beneficial, mp-MRI is relatively complex to interpret and suffers from inter-observer variability in lesion localization and grading. Computer-aided diagnosis (CAD) systems have been developed as a solution as they have the power to perform deterministic quantitative image analysis. We measured the accuracy of such a system validated using accurately co-registered whole-mount digitized histology. We trained a logistic linear classifier (LOGLC), support vector machine (SVC), k-nearest neighbour (KNN) and random forest classifier (RFC) in a four part ROI based experiment against: 1) cancer vs. non-cancer, 2) high-grade (Gleason score ≥4+3) vs. low-grade cancer (Gleason score work will form the basis for a tool that enhances the radiologist's ability to detect malignancies, potentially improving biopsy guidance, treatment selection, and focal therapy for prostate cancer patients, maximizing the potential for cure and increasing quality of life.
Non-parametric early seizure detection in an animal model of temporal lobe epilepsy
Talathi, Sachin S.; Hwang, Dong-Uk; Spano, Mark L.; Simonotto, Jennifer; Furman, Michael D.; Myers, Stephen M.; Winters, Jason T.; Ditto, William L.; Carney, Paul R.
2008-03-01
The performance of five non-parametric, univariate seizure detection schemes (embedding delay, Hurst scale, wavelet scale, nonlinear autocorrelation and variance energy) were evaluated as a function of the sampling rate of EEG recordings, the electrode types used for EEG acquisition, and the spatial location of the EEG electrodes in order to determine the applicability of the measures in real-time closed-loop seizure intervention. The criteria chosen for evaluating the performance were high statistical robustness (as determined through the sensitivity and the specificity of a given measure in detecting a seizure) and the lag in seizure detection with respect to the seizure onset time (as determined by visual inspection of the EEG signal by a trained epileptologist). An optimality index was designed to evaluate the overall performance of each measure. For the EEG data recorded with microwire electrode array at a sampling rate of 12 kHz, the wavelet scale measure exhibited better overall performance in terms of its ability to detect a seizure with high optimality index value and high statistics in terms of sensitivity and specificity.
Parametric dictionary learning for modeling EAP and ODF in diffusion MRI.
Merlet, Sylvain; Caruyer, Emmanuel; Deriche, Rachid
2012-01-01
In this work, we propose an original and efficient approach to exploit the ability of Compressed Sensing (CS) to recover diffusion MRI (dMRI) signals from a limited number of samples while efficiently recovering important diffusion features such as the ensemble average propagator (EAP) and the orientation distribution function (ODF). Some attempts to sparsely represent the diffusion signal have already been performed. However and contrarly to what has been presented in CS dMRI, in this work we propose and advocate the use of a well adapted learned dictionary and show that it leads to a sparser signal estimation as well as to an efficient reconstruction of very important diffusion features. We first propose to learn and design a sparse and parametric dictionary from a set of training diffusion data. Then, we propose a framework to analytically estimate in closed form two important diffusion features: the EAP and the ODF. Various experiments on synthetic, phantom and human brain data have been carried out and promising results with reduced number of atoms have been obtained on diffusion signal reconstruction, thus illustrating the added value of our method over state-of-the-art SHORE and SPF based approaches.
A Monte Carlo-adjusted goodness-of-fit test for parametric models describing spatial point patterns
Dao, Ngocanh
2014-04-03
Assessing the goodness-of-fit (GOF) for intricate parametric spatial point process models is important for many application fields. When the probability density of the statistic of the GOF test is intractable, a commonly used procedure is the Monte Carlo GOF test. Additionally, if the data comprise a single dataset, a popular version of the test plugs a parameter estimate in the hypothesized parametric model to generate data for theMonte Carlo GOF test. In this case, the test is invalid because the resulting empirical level does not reach the nominal level. In this article, we propose a method consisting of nested Monte Carlo simulations which has the following advantages: the bias of the resulting empirical level of the test is eliminated, hence the empirical levels can always reach the nominal level, and information about inhomogeneity of the data can be provided.We theoretically justify our testing procedure using Taylor expansions and demonstrate that it is correctly sized through various simulation studies. In our first data application, we discover, in agreement with Illian et al., that Phlebocarya filifolia plants near Perth, Australia, can follow a homogeneous Poisson clustered process that provides insight into the propagation mechanism of these plants. In our second data application, we find, in contrast to Diggle, that a pairwise interaction model provides a good fit to the micro-anatomy data of amacrine cells designed for analyzing the developmental growth of immature retina cells in rabbits. This article has supplementary material online. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
Karabatsos, George
2017-02-01
Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected
International Nuclear Information System (INIS)
Baumjohann, F.; Kroening, J.
1999-01-01
The present paper originates from a contribution to the safety assessment of a reactor pressure vessel (RPV). Investigations evaluating the safety against brittle fracture (exclosure of crack initiation and arrest assessments) are completed by calculations concerning ductile crack extension. Crack geometries including the expected crack extension are generated parametrically by a computer code and are used for further calculations with finite element programs. J-integrals of ductile growing cracks located between two comparative contours are determined by interpolation. The comparative contours are loaded by instationary temperature and pressure fields and are evaluated in advance. Taking the stability condition into consideration, the ductile crack extension is determined by pursuing the equilibrium between loading and crack resistance. The automatic modelling and a mathematical program processing the finite element results evaluate the crack growth of the finite element results very effectively. (orig.)
Symmetry-breaking in the response of the parametrically excited pendulum model
International Nuclear Information System (INIS)
Bishop, S.R.; Sofroniou, A.; Shi, P.
2005-01-01
A planar pendulum is considered which is parametrically excited by a periodic vertical force. The amplitude and frequency of the excitation are used as control parameters. The downward, hanging and the upward, inverted positions correspond to equilibrium positions if we only consider the variation in angle measured from the downward position. For moderate levels of forcing, there are zones that exist in the space of control parameters, where the downward hanging position is unstable and initial conditions that are close to the hanging position lead to steady state oscillations of period-2. To review this situation, this paper describes the development of these oscillations as the amplitude of forcing is varied. In the largest zone, a symmetry-breaking occurs which brings about a pair of asymmetric oscillations. This break in symmetry of the period-2 solution can lead to either an increase or decrease in the amplitude of the forthcoming swing and reference to the experimental significance of this angle change is noted in this paper. Typically, further increases of the parameter produce a cascade of period doubling bifurcations, before most oscillating solutions eventually lose their stability so that the system must experience a rotation. As a result, symmetry-breaking becomes an effective precursor to escape from the local potential well around the hanging position. Here we compare this behaviour with that in other resonance zones. The change of geometric structure when the symmetry-breaking bifurcation occurs is examined and graphically represented as a 'pinched' cylinder-like shape, compared with the Moebius strip that has been associated with the period-doubling bifurcation. The paper also refers to practical problems, where the introduction of nonlinearity means that potentially all frequencies below the main zone of the control space lead to dangerous effects and in some scenarios disastrous outcomes
Simard, M.; Liu, K.; Denbina, M. W.; Jensen, D.; Rodriguez, E.; Liao, T. H.; Christensen, A.; Jones, C. E.; Twilley, R.; Lamb, M. P.; Thomas, N. A.
2017-12-01
Our goal is to estimate the fluxes of water and sediments throughout the Wax Lake-Atchafalaya basin. This was achieved by parametrization of a set of 1D (HEC-RAS) and 2D (DELFT3D) hydrology models with state of the art remote sensing measurements of water surface elevation, water surface slope and total suspended sediment (TSS) concentrations. The model implementations are spatially explicit, simulating river currents, lateral flows to distributaries and marshes, and spatial variations of sediment concentrations. Three remote sensing instruments were flown simultaneously to collect data over the Wax Lake-Atchafalaya basin, and along with in situ field data. A Riegl Lidar was used to measure water surface elevation and slope, while the UAVSAR L-band radar collected data in repeat-pass interferometric mode to measure water level change within adjacent marshes and islands. These data were collected several times as the tide rose and fell. AVRIS-NG instruments measured water surface reflectance spectra, used to estimate TSS. Bathymetry was obtained from sonar transects and water level changes were recorded by 19 water level pressure transducers. We used several Acoustic Doppler Current Profiler (ADCP) transects to estimate river discharge. The remotely sensed measurements of water surface slope were small ( 1cm/km) and varied slightly along the channel, especially at the confluence with bayous and the intra-coastal waterway. The slope also underwent significant changes during the tidal cycle. Lateral fluxes to island marshes were mainly observed by UAVSAR close to the distributaries. The extensive remote sensing measurements showed significant disparity with the hydrology model outputs. Observed variations in water surface slopes were unmatched by the model and tidal wave propagation was much faster than gauge measurements. The slope variations were compensated for in the models by tuning local lateral fluxes, bathymetry and riverbed friction. Overall, the simpler 1D
Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad
2015-11-01
One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.
International Nuclear Information System (INIS)
Das, Shiva K.; Zhou Sumin; Zhang, Junan; Yin, F.-F.; Dewhirst, Mark W.; Marks, Lawrence B.
2007-01-01
Purpose: To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. Methods and Materials: The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a 'boosting' process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. Results: The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. Conclusions: Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation
Meneguz, Elena; Thomson, David; Witham, Claire; Kusmierczyk-Michulec, Jolanta
2015-04-01
NAME is a Lagrangian atmospheric dispersion model used by the Met Office to predict the dispersion of both natural and man-made contaminants in the atmosphere, e.g. volcanic ash, radioactive particles and chemical species. Atmospheric convection is responsible for transport and mixing of air resulting in a large exchange of heat and energy above the boundary layer. Although convection can transport material through the whole troposphere, convective clouds have a small horizontal length scale (of the order of few kilometres). Therefore, for large-scale transport the horizontal scale on which the convection exists is below the global NWP resolution used as input to NAME and convection must be parametrized. Prior to the work presented here, the enhanced vertical mixing generated by non-resolved convection was reproduced by randomly redistributing Lagrangian particles between the cloud base and cloud top with probability equal to 1/25th of the NWP predicted convective cloud fraction. Such a scheme is essentially diffusive and it does not make optimal use of all the information provided by the driving meteorological model. To make up for these shortcomings and make the parametrization more physically based, the convection scheme has been recently revised. The resulting version, presented in this paper, is now based on the balance equation between upward, entrainment and detrainment fluxes. In particular, upward mass fluxes are calculated with empirical formulas derived from Cloud Resolving Models and using the NWP convective precipitation diagnostic as closure. The fluxes are used to estimate how many particles entrain, move upward and detrain. Lastly, the scheme is completed by applying a compensating subsidence flux. The performance of the updated convection scheme is benchmarked against available observational data of passive tracers. In particular, radioxenon is a noble gas that can undergo significant long range transport: this study makes use of observations of
Ivanova, Violeta M.; Sousa, Rita; Murrihy, Brian; Einstein, Herbert H.
2014-06-01
This paper presents results from research conducted at MIT during 2010-2012 on modeling of natural rock fracture systems with the GEOFRAC three-dimensional stochastic model. Following a background summary of discrete fracture network models and a brief introduction of GEOFRAC, the paper provides a thorough description of the newly developed mathematical and computer algorithms for fracture intensity, aperture, and intersection representation, which have been implemented in MATLAB. The new methods optimize, in particular, the representation of fracture intensity in terms of cumulative fracture area per unit volume, P32, via the Poisson-Voronoi Tessellation of planes into polygonal fracture shapes. In addition, fracture apertures now can be represented probabilistically or deterministically whereas the newly implemented intersection algorithms allow for computing discrete pathways of interconnected fractures. In conclusion, results from a statistical parametric study, which was conducted with the enhanced GEOFRAC model and the new MATLAB-based Monte Carlo simulation program FRACSIM, demonstrate how fracture intensity, size, and orientations influence fracture connectivity.
Macromechanical Parametric Amplification
DEFF Research Database (Denmark)
Neumeyer, Stefan
between the two peaks can be altered. The first experimental bistable amplified steady-state responses are also reported. The derived analytical models and experimental setups can readily be extended to investigate other factors. Some of the results are also applicable to the more general field of systems...... for energy harvesting. Using analytical, numerical, and experimental methods, the thesis focuses on superthreshold pumping (above the systems parametric instability threshold), nonlinear effects, frequency response backbones, and frequency detuning effects for parametric amplifiers. Part one of the thesis...... covers superthreshold pumping and nonlinear effects. Superthresh-old pumping produces some useful characteristics. For instance, strong superthreshold pumping yields a high gain even though nonlinear effects tend to reduce it. In addition, a narrower excitation phase range is realized for which...
Snorradóttir, Bergthóra S; Jónsdóttir, Fjóla; Sigurdsson, Sven Th; Másson, Már
2014-08-01
A model is presented for transdermal drug delivery from single-layered silicone matrix systems. The work is based on our previous results that, in particular, extend the well-known Higuchi model. Recently, we have introduced a numerical transient model describing matrix systems where the drug dissolution can be non-instantaneous. Furthermore, our model can describe complex interactions within a multi-layered matrix and the matrix to skin boundary. The power of the modelling approach presented here is further illustrated by allowing the possibility of a donor solution. The model is validated by a comparison with experimental data, as well as validating the parameter values against each other, using various configurations with donor solution, silicone matrix and skin. Our results show that the model is a good approximation to real multi-layered delivery systems. The model offers the ability of comparing drug release for ibuprofen and diclofenac, which cannot be analysed by the Higuchi model because the dissolution in the latter case turns out to be limited. The experiments and numerical model outlined in this study could also be adjusted to more general formulations, which enhances the utility of the numerical model as a design tool for the development of drug-loaded matrices for trans-membrane and transdermal delivery. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.
Parametrization of turbulence models using 3DVAR data assimilation in laboratory conditions
Olbert, A. I.; Nash, S.; Ragnoli, E.; Hartnett, M.
2013-12-01
In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ɛ model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ɛ model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. Such analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows. This research further demonstrates how 3DVAR can be utilized to identify and quantify shortcomings of the numerical model and consequently to improve forecasting by correct parameterization of the turbulence models. Such improvements may greatly benefit physical oceanography in terms of
Parametric FEM for geometric biomembranes
Bonito, Andrea; Nochetto, Ricardo H.; Sebastian Pauletti, M.
2010-05-01
We consider geometric biomembranes governed by an L2-gradient flow for bending energy subject to area and volume constraints (Helfrich model). We give a concise derivation of a novel vector formulation, based on shape differential calculus, and corresponding discretization via parametric FEM using quadratic isoparametric elements and a semi-implicit Euler method. We document the performance of the new parametric FEM with a number of simulations leading to dumbbell, red blood cell and toroidal equilibrium shapes while exhibiting large deformations.
Parametric analysis of LIBRETTO-4 and 5 in-pile tritium transport model on EcosimPro
Energy Technology Data Exchange (ETDEWEB)
Alcalde, Pablo Martínez, E-mail: pablomiguel.martinez@externos.ciemat.es [Universidad Nacional de Educación a Distancia (UNED), c/Juan del Rosal 12, 28040 Madrid (Spain); Moreno, Carlos; Ibarra, Ángel [CIEMAT, Avda. Complutense 40, 28040 Madrid (Spain)
2014-10-15
Highlights: • Introduction of a new tritium transport model of LIBRETTO-4 and 5 on EcosimPro{sup ®}. • Analysis of model input parameter and variable sensitivities and effects on tritium simulated fluxes. • Demonstrations of high tritium out-flux dependencies on lead-lithium parameters. • Rough fitting achievements proposed by Li17Pb solubility or recombination increase. - Abstract: A new model for LIBRETTO-4/1, 4/2 and 5 experiments have been developed on ECOSIMPro{sup ©} tool to simulate tritium in-pile breeding and transport into two separate purge gas channels with He + 0.1%H{sub 2}. Release from lead lithium eutectic plenum with coupled permeation through an austenitic steel wall on the first and single permeation through EUROFER-97 in the temperature ranges of 300–550 °C can be simulated tuning the transport parameters involved. A parametric study has been performed to reduce the degrees of freedom and to determine the error caused in the simulation due to the uncertainty in experimental input data. The information obtained is essential for the experimental benchmarking. The Tritium Permeation Percentage (TPP) is an output calculated parameter with low variations between 2 and 6% along the whole experimental time easy to compare (730 Full Power Days for LIBRETTO-4 and 520 for 5). Tritium transport parameter ranges verifying this output are defined herein.
Seyed, Mohammadali Rahmati; Mostafa, Rostami; Borhan, Beigzadeh
2018-04-27
The parametric optimization techniques have been widely employed to predict human gait trajectories; however, their applications to reveal the other aspects of gait are questionable. The aim of this study is to investigate whether or not the gait prediction model is able to justify the movement trajectories for the higher average velocities. A planar, seven-segment model with sixteen muscle groups was used to represent human neuro-musculoskeletal dynamics. At first, the joint angles, ground reaction forces (GRFs) and muscle activations were predicted and validated for normal average velocity (1.55 m/s) in the single support phase (SSP) by minimizing energy expenditure, which is subject to the non-linear constraints of the gait. The unconstrained system dynamics of extended inverse dynamics (USDEID) approach was used to estimate muscle activations. Then by scaling time and applying the same procedure, the movement trajectories were predicted for higher average velocities (from 2.07 m/s to 4.07 m/s) and compared to the pattern of movement with fast walking speed. The comparison indicated a high level of compatibility between the experimental and predicted results, except for the vertical position of the center of gravity (COG). It was concluded that the gait prediction model can be effectively used to predict gait trajectories for higher average velocities.
Directory of Open Access Journals (Sweden)
Xiangyang Liu
2018-03-01
Full Text Available An appropriate model to correct thermal radiation anisotropy is important for the wide applications of land surface temperature (LST. This paper evaluated the performance of three published directional thermal radiation models—the Roujean–Lagouarde (RL model, the Bidirectional Reflectance Distribution Function (BRDF model, and the Vinnikov model—at canopy and pixel scale using simulation, airborne, and satellite data. The results at canopy scale showed that (1 the three models could describe directional anisotropy well and the Vinnikov model performed the best, especially for erectophile canopy or low leaf area index (LAI; (2 the three models reached the highest fitting accuracy when the LAI varied from 1 to 2; and (3 the capabilities of the three models were all restricted by the hotspot effect, plant height, plant spacing, and three-dimensional structure. The analysis at pixel scale indicated a consistent result that the three models presented a stable effect both on verification and validation, but the Vinnikov model had the best ability in the erectophile canopy (savannas and grassland and low LAI (barren or sparsely vegetated areas. Therefore, the Vinnikov model was calibrated for different land cover types to instruct the angular correction of LST. Validation with the Surface Radiation Budget Network (SURFRAD-measured LST demonstrated that the root mean square (RMSE of the Moderate Resolution Imaging Spectroradiometer (MODIS LST product could be decreased by 0.89 K after angular correction. In addition, the corrected LST showed better spatial uniformity and higher angular correlation.
Non-parametric Bayesian graph models reveal community structure in resting state fMRI
DEFF Research Database (Denmark)
Andersen, Kasper Winther; Madsen, Kristoffer H.; Siebner, Hartwig Roman
2014-01-01
Modeling of resting state functional magnetic resonance imaging (rs-fMRI) data using network models is of increasing interest. It is often desirable to group nodes into clusters to interpret the communication patterns between nodes. In this study we consider three different nonparametric Bayesian...... models for node clustering in complex networks. In particular, we test their ability to predict unseen data and their ability to reproduce clustering across datasets. The three generative models considered are the Infinite Relational Model (IRM), Bayesian Community Detection (BCD), and the Infinite...... between clusters. BCD restricts the between-cluster link probabilities to be strictly lower than within-cluster link probabilities to conform to the community structure typically seen in social networks. IDM only models a single between-cluster link probability, which can be interpreted as a background...
Ramezani Tehrani, Fahimeh; Mansournia, Mohammad Ali; Solaymani-Dodaran, Masoud; Steyerberg, Ewout; Azizi, Fereidoun
2016-06-01
This study aimed to improve existing prediction models for age at menopause. We identified all reproductive aged women with regular menstrual cycles who met our eligibility criteria (n = 1,015) in the Tehran Lipid and Glucose Study-an ongoing population-based cohort study initiated in 1998. Participants were examined every 3 years and their reproductive histories were recorded. Blood levels of antimüllerian hormone (AMH) were measured at the time of recruitment. Age at menopause was estimated based on serum concentrations of AMH using flexible parametric survival models. The optimum model was selected according to Akaike Information Criteria and the realness of the range of predicted median menopause age. We followed study participants for a median of 9.8 years during which 277 women reached menopause and found that a spline-based proportional odds model including age-specific AMH percentiles as the covariate performed well in terms of statistical criteria and provided the most clinically relevant and realistic predictions. The range of predicted median age at menopause for this model was 47.1 to 55.9 years. For those who reached menopause, the median of the absolute mean difference between actual and predicted age at menopause was 1.9 years (interquartile range 2.9). The model including the age-specific AMH percentiles as the covariate and using proportional odds as its covariate metrics meets all the statistical criteria for the best model and provides the most clinically relevant and realistic predictions for age at menopause for reproductive-aged women.
A Parametric Energy Model for Energy Management of Long Belt Conveyors
Directory of Open Access Journals (Sweden)
Tebello Mathaba
2015-12-01
Full Text Available As electricity prices continue to rise, the increasing need for energy management requires better understanding of models for energy-consuming applications, such as conveyor belts. Conveyor belts are used in a wide range of industries, including power generation, mining and mineral processing. Conveyor technological advances are leading to increasingly long conveyor belts being commissioned. Thus, the energy consumption of each individual belt conveyor unit is becoming increasingly significant. This paper proposes a generic energy model for belt conveyors with long troughed belts. The model has a two-parameter power equation, and it uses a partial differential equation to capture the variable amount of material mass per unit length throughout the belt length. Verification results show that the power consumption calculations of the newly proposed simpler model are consistent with those of a known non-linear model with an error of less than 4%. The online parameter identification set-up of the model is proposed. Simulations indicate that the parameters can be identified successfully from data with up to 15% measurement noise. Results show that the proposed model gives better predictions of the power consumed and material delivered by a long conveyor belt than the steady-state models in the current literature.
Parametric identification of the model with one predator and two prey species
CSIR Research Space (South Africa)
Shatalov, M
2008-09-01
Full Text Available In this paper a mathematical model describing the interaction of a lion population with that of the zebra and wildebeest populations is considered. The traditional method uses a model with known coefficients and a CAS numerical routine to determine...
DEFF Research Database (Denmark)
Rohde, John; Toftegaard, Thomas Skjødeberg
2012-01-01
such as antennas and PCB traces. The models presented are benchmarked against real-life measurements and conventional circuit models. Furthermore, two example parallel-resonance circuits are designed based on interpolation of the results and validated by measurements in order to demonstrate the accuracy...
Regression Is a Univariate General Linear Model Subsuming Other Parametric Methods as Special Cases.
Vidal, Sherry
Although the concept of the general linear model (GLM) has existed since the 1960s, other univariate analyses such as the t-test and the analysis of variance models have remained popular. The GLM produces an equation that minimizes the mean differences of independent variables as they are related to a dependent variable. From a computer printout…
Hamby, D M
2002-01-01
Reconstructed meteorological data are often used in some form of long-term wind trajectory models for estimating the historical impacts of atmospheric emissions. Meteorological data for the straight-line Gaussian plume model are put into a joint frequency distribution, a three-dimensional array describing atmospheric wind direction, speed, and stability. Methods using the Gaussian model and joint frequency distribution inputs provide reasonable estimates of downwind concentration and have been shown to be accurate to within a factor of four. We have used multiple joint frequency distributions and probabilistic techniques to assess the Gaussian plume model and determine concentration-estimate uncertainty and model sensitivity. We examine the straight-line Gaussian model while calculating both sector-averaged and annual-averaged relative concentrations at various downwind distances. The sector-average concentration model was found to be most sensitive to wind speed, followed by horizontal dispersion (sigmaZ), the importance of which increases as stability increases. The Gaussian model is not sensitive to stack height uncertainty. Precision of the frequency data appears to be most important to meteorological inputs when calculations are made for near-field receptors, increasing as stack height increases.
Hydrologic models are used to simulate the responses of agricultural systems to different inputs and management strategies to identify alternative management practices to cope up with future climate and/or geophysical changes. The Agricultural Policy/Environmental eXtender (APEX) is a model develope...
Development, Validation and Parametric study of a 3-Year-Old Child Head Finite Element Model
Cui, Shihai; Chen, Yue; Li, Haiyan; Ruan, ShiJie
2015-12-01
Traumatic brain injury caused by drop and traffic accidents is an important reason for children's death and disability. Recently, the computer finite element (FE) head model has been developed to investigate brain injury mechanism and biomechanical responses. Based on CT data of a healthy 3-year-old child head, the FE head model with detailed anatomical structure was developed. The deep brain structures such as white matter, gray matter, cerebral ventricle, hippocampus, were firstly created in this FE model. The FE model was validated by comparing the simulation results with that of cadaver experiments based on reconstructing the child and adult cadaver experiments. In addition, the effects of skull stiffness on the child head dynamic responses were further investigated. All the simulation results confirmed the good biofidelity of the FE model.
Energy Technology Data Exchange (ETDEWEB)
Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim U.; Emberton, Mark [University College London, Research Department of Urology, Division of Surgery and Interventional Science, London (United Kingdom); Kirkham, Alex [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)
2015-09-15
To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer. Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models. The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer. LR-models dependent on DCE-MRI parameters alone are not interchangeable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application. (orig.)
Nerovny, N. A.; Zimin, V. N.
2018-04-01
In this paper, the problem of representing the light pressure force upon the surface of a thin wrinkled film is discussed. The common source of wrinkles is the shear deformation of the membrane sample. The optical model of such a membrane is assumed to be optically orthotropic and an analytic equation for infinitesimal light pressure force is written. A linear regression model in the case of wrinkle geometry, where a surface element can have different optical parameters, is constructed and the Bayesian approach is used to calculate the parameters of this model.
Maghareh, Amin; Silva, Christian E.; Dyke, Shirley J.
2018-05-01
Hydraulic actuators play a key role in experimental structural dynamics. In a previous study, a physics-based model for a servo-hydraulic actuator coupled with a nonlinear physical system was developed. Later, this dynamical model was transformed into controllable canonical form for position tracking control purposes. For this study, a nonlinear device is designed and fabricated to exhibit various nonlinear force-displacement profiles depending on the initial condition and the type of materials used as replaceable coupons. Using this nonlinear system, the controllable canonical dynamical model is experimentally validated for a servo-hydraulic actuator coupled with a nonlinear physical system.
International Nuclear Information System (INIS)
Mueller, Pablo
2004-01-01
The aim of this work was to develop a model to simulate the evolution of the thermodynamic variables in a nuclear reactor containment with pressure suppression pool under accidental transients.We wanted a program able to give fast results, to facilitate the physical interpretation of the phenomena involved, and to make parametric studies.We did not pretend to get a precise result of a particular case.The program was made to be used as a design tool for the containment and to solve the interactions with the primary cooling system and the other security systems of the reactor, on a conceptual design context.The model consists on energy and mass balances on control volumes with liquid water, steam and a non-condensable gas like air.The dynamics of the system is shown with a base case during a loss of coolant accident.Sensibility and effects of varying some important parameters like volumes and heat and mass transfer coefficients are studied.Finally the results for the CAREM-25 reactor are compared with the codes CORAN, MELCOR 1.8.4 and CONTAIN 2.0 [es
International Nuclear Information System (INIS)
Ghosal, M.K.; Tiwari, G.N.
2006-01-01
A thermal model has been developed to investigate the potential of using the stored thermal energy of the ground for greenhouse heating and cooling with the help of an earth to air heat exchanger (EAHE) system integrated with the greenhouse located in the premises of IIT, Delhi, India. Experiments were conducted extensively throughout the year 2003, but the developed model was validated against typical clear and sunny days experiments. Parametric studies performed for the EAHE coupled with the greenhouse illustrate the effects of buried pipe length, pipe diameter, mass flow rate of air, depth of ground and types of soil on the greenhouse air temperatures. The temperatures of the greenhouse air, with the experimental parameters of the EAHE, were found to be, on average 7-8 deg. C higher in the winter and 5-6 deg. C lower in the summer than those of the same greenhouse without the EAHE. The greenhouse air temperatures increase in the winter and decrease in the summer with increasing pipe length, decreasing pipe diameter, decreasing mass flow rate of flowing air inside buried pipe and increasing depth of ground up to 4 m. The predicted and measured values of the greenhouse air temperatures that were verified, in terms of root mean square percent deviation and correlation coefficient, exhibited fair agreement
Directory of Open Access Journals (Sweden)
Richard N Henson
2011-08-01
Full Text Available We review recent methodological developments within a Parametric Empirical Bayesian (PEB framework for reconstructing intracranial sources of extracranial electroencephalographic (EEG and magnetoencephalographic (MEG data under linear Gaussian assumptions. The PEB framework offers a natural way to integrate multiple constraints (spatial priors on this inverse problem, such as those derived from different modalities (e.g., from functional magnetic resonance imaging, fMRI or from multiple replications (e.g., subjects. Using variations of the same basic generative model, we illustrate the application of PEB to three cases: 1 symmetric integration (fusion of MEG and EEG; 2 asymmetric integration of MEG or EEG with fMRI, and 3 group-optimisation of spatial priors across subjects. We evaluate these applications on multimodal data acquired from 18 subjects, focusing on energy induced by face perception within a time-frequency window of 100-220ms, 8-18Hz. We show the benefits of multi-modal, multi-subject integration in terms of the model evidence and the reproducibility (over subjects of cortical responses to faces.
Bennett, Iain; Paracha, Noman; Abrams, Keith; Ray, Joshua
2018-01-01
Rank Preserving Structural Failure Time models are one of the most commonly used statistical methods to adjust for treatment switching in oncology clinical trials. The method is often applied in a decision analytic model without appropriately accounting for additional uncertainty when determining the allocation of health care resources. The aim of the study is to describe novel approaches to adequately account for uncertainty when using a Rank Preserving Structural Failure Time model in a decision analytic model. Using two examples, we tested and compared the performance of the novel Test-based method with the resampling bootstrap method and with the conventional approach of no adjustment. In the first example, we simulated life expectancy using a simple decision analytic model based on a hypothetical oncology trial with treatment switching. In the second example, we applied the adjustment method on published data when no individual patient data were available. Mean estimates of overall and incremental life expectancy were similar across methods. However, the bootstrapped and test-based estimates consistently produced greater estimates of uncertainty compared with the estimate without any adjustment applied. Similar results were observed when using the test based approach on a published data showing that failing to adjust for uncertainty led to smaller confidence intervals. Both the bootstrapping and test-based approaches provide a solution to appropriately incorporate uncertainty, with the benefit that the latter can implemented by researchers in the absence of individual patient data. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Agarkov S.A.
2015-03-01
Full Text Available A new approach to the identification of parameters of the Nomoto generalized vessel model has been proposed. The apparatus of classical calculus and the method of least squares have been used
International Nuclear Information System (INIS)
Shvets', D.V.
2009-01-01
By the first approximation analyzing stability conditions of unperturbed solution of one-dimensional dynamic model with magnetic interaction between two superconducting rings obtained. The stability region in the frozen magnetic flux parameters space was constructed.
Re-parametrization of a swine model to predict growth performance of broilers
Dukhta, G.; van Milgen, Jacob; Kövér, G.; Halas, V.
2017-01-01
The aim of the study was to investigate whether a pig growth model is suitable to be modified and adapted for broilers. As monogastric animals, pigs and poultry share many similarities in their digestion and metabolism, many structures (body protein and lipid stores) and the nutrient flows of the underlying metabolic pathways are similar among species. For that purpose, the InraPorc model was used as a basis to predict growth performance and body composition at slaughter in broilers. First...
The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model
Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter
2018-02-01
We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.
Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling
Energy Technology Data Exchange (ETDEWEB)
Peterson, John R.; Marshall, P.J.; /KIPAC, Menlo Park; Andersson, K.; /Stockholm U. /SLAC
2005-08-05
We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.
Degeling, Koen; Ijzerman, Maarten J.; Koopman, Miriam; Koffijberg, Hendrik
2017-01-01
Background: Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive
Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik
2017-01-01
Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive
International Nuclear Information System (INIS)
Salimi, Mohsen; Amidpour, Majid
2017-01-01
Highlights: • Integration of small MED unit with gas engine power cycle is studied in this paper. • Modeling, simulation, parametric study and sensitivity analysis were performed. • A thermodynamic model for heat recovery and power generation of the gas engine has been presented. • Annualized Cost of System (ACS) has been employed for economic assessment. • Economic feasibilty dependence of integrated system on natural gas and water prices has been investigated. - Abstract: Due to thermal nature of multi-effect desalination (MED), its integration with a suitable power cycle is highly desirable for waste heat recovery. One of the proper power cycle for proposed integration is internal combustion engine (ICE). The exhaust gas heat of ICE is used to produce motive steam for the required heat for the first effect of MED system. Also, the water jacket heat is utilized in a heat exchanger to pre-heat the seawater. This paper studies a thermodynamic model for a tri-generation system composed of ICE integrated with MED. The ICE thermodynamic model has been used in place of different empirical efficiency relations to estimate performance – load curves reasonably. The entire system performance has been coded in MATLAB, and the results of proposed thermodynamic model for the engine have been verified by manufacturer catalogue. By increasing the engine load from 40% to 100%, the water production of MED unit will increase from 4.38 cubic meters per day to 26.78 cubic meters per day and the tri-generation efficiency from 31% to 56%. Economic analyses of the MED unit integrated with ICE was performed based on Annualized Cost of System method. This integration makes the system more economical. It has been determined that in higher market prices for fresh water (more than 7 US$ per cubic meter), the increase in effects number is more significant to the period of return decrement.
Directory of Open Access Journals (Sweden)
Eloranta Sandra
2012-06-01
Full Text Available Abstract Background Relative survival is commonly used for studying survival of cancer patients as it captures both the direct and indirect contribution of a cancer diagnosis on mortality by comparing the observed survival of the patients to the expected survival in a comparable cancer-free population. However, existing methods do not allow estimation of the impact of isolated conditions (e.g., excess cardiovascular mortality on the total excess mortality. For this purpose we extend flexible parametric survival models for relative survival, which use restricted cubic splines for the baseline cumulative excess hazard and for any time-dependent effects. Methods In the extended model we partition the excess mortality associated with a diagnosis of cancer through estimating a separate baseline excess hazard function for the outcomes under investigation. This is done by incorporating mutually exclusive background mortality rates, stratified by the underlying causes of death reported in the Swedish population, and by introducing cause of death as a time-dependent effect in the extended model. This approach thereby enables modeling of temporal trends in e.g., excess cardiovascular mortality and remaining cancer excess mortality simultaneously. Furthermore, we illustrate how the results from the proposed model can be used to derive crude probabilities of death due to the component parts, i.e., probabilities estimated in the presence of competing causes of death. Results The method is illustrated with examples where the total excess mortality experienced by patients diagnosed with breast cancer is partitioned into excess cardiovascular mortality and remaining cancer excess mortality. Conclusions The proposed method can be used to simultaneously study disease patterns and temporal trends for various causes of cancer-consequent deaths. Such information should be of interest for patients and clinicians as one way of improving prognosis after cancer is
Ferrarini, Luca; Veer, Ilya M; van Lew, Baldur; Oei, Nicole Y L; van Buchem, Mark A; Reiber, Johan H C; Rombouts, Serge A R B; Milles, J
2011-06-01
In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity. Copyright © 2010 Elsevier Inc. All rights reserved.
Rights, Jason D; Sterba, Sonya K
2016-11-01
Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.
Kink dynamics in a parametric ϕ 6 system: a model with controllably many internal modes
Demirkaya, A.; Decker, R.; Kevrekidis, P. G.; Christov, I. C.; Saxena, A.
2017-12-01
We explore a variant of the ϕ 6 model originally proposed in Phys. Rev. D 12 (1975) 1606 as a prototypical, so-called, "bag" model in which domain walls play the role of quarks within hadrons. We examine the steady state of the model, namely an apparent bound state of two kink structures. We explore its linearization, and we find that, as a function of a parameter controlling the curvature of the potential, an effectively arbitrary number of internal modes may arise in the point spectrum of the linearization about the domain wall profile. We explore some of the key characteristics of kink-antikink collisions, such as the critical velocity and the multi-bounce windows, and how they depend on the principal parameter of the model. We find that the critical velocity exhibits a non-monotonic dependence on the parameter controlling the curvature of the potential. For the multi-bounce windows, we find that their range and complexity decrease as the relevant parameter decreases (and as the number of internal modes in the model increases). We use a modified collective coordinates method [in the spirit of recent works such as Phys. Rev. D 94 (2016) 085008] in order to capture the relevant phenomenology in a semi-analytical manner.
Development of a parametric kinematic model of the human hand and a novel robotic exoskeleton.
Burton, T M W; Vaidyanathan, R; Burgess, S C; Turton, A J; Melhuish, C
2011-01-01
This paper reports the integration of a kinematic model of the human hand during cylindrical grasping, with specific focus on the accurate mapping of thumb movement during grasping motions, and a novel, multi-degree-of-freedom assistive exoskeleton mechanism based on this model. The model includes thumb maximum hyper-extension for grasping large objects (~> 50 mm). The exoskeleton includes a novel four-bar mechanism designed to reproduce natural thumb opposition and a novel synchro-motion pulley mechanism for coordinated finger motion. A computer aided design environment is used to allow the exoskeleton to be rapidly customized to the hand dimensions of a specific patient. Trials comparing the kinematic model to observed data of hand movement show the model to be capable of mapping thumb and finger joint flexion angles during grasping motions. Simulations show the exoskeleton to be capable of reproducing the complex motion of the thumb to oppose the fingers during cylindrical and pinch grip motions. © 2011 IEEE
Bayesian Non-Parametric Mixtures of GARCH(1,1 Models
Directory of Open Access Journals (Sweden)
John W. Lau
2012-01-01
Full Text Available Traditional GARCH models describe volatility levels that evolve smoothly over time, generated by a single GARCH regime. However, nonstationary time series data may exhibit abrupt changes in volatility, suggesting changes in the underlying GARCH regimes. Further, the number and times of regime changes are not always obvious. This article outlines a nonparametric mixture of GARCH models that is able to estimate the number and time of volatility regime changes by mixing over the Poisson-Kingman process. The process is a generalisation of the Dirichlet process typically used in nonparametric models for time-dependent data provides a richer clustering structure, and its application to time series data is novel. Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. The methodology is illustrated on the Standard and Poor's 500 financial index.
1980-08-01
varia- ble is denoted by 7, the total sum of squares of deviations from that mean is defined by n - SSTO - (-Y) (2.6) iul and the regression sum of...squares by SSR - SSTO - SSE (2.7) II 14 A selection criterion is a rule according to which a certain model out of the 2p possible models is labeled "best...dis- cussed next. 1. The R2 Criterion The coefficient of determination is defined by R2 . 1 - SSE/ SSTO . (2.8) It is clear that R is the proportion of
Energy Technology Data Exchange (ETDEWEB)
Nordstroem, T; Kilpinen, P; Hupa, M [Aabo Akademi, Turku (Finland). Combustion Chemistry Group
1997-12-31
The objective of this work has been to investigate the soot formation in a blast furnace fired with heavy fuel oil, using detailed kinetic modelling. This work has been concentrated on parameter studies that could explain under which conditions soot is formed and how that formation could be avoided. The parameters investigated were temperature, pressure, stoichiometric ratio, pyrolysis gas composition and reactor model. The calculations were based on a reaction mechanism that consists of 100 species and 446 reactions including polyaromatic hydrocarbons (PAM) up to 7 aromatic rings SULA 2 Research Programme; 4 refs.
Energy Technology Data Exchange (ETDEWEB)
Nordstroem, T.; Kilpinen, P.; Hupa, M. [Aabo Akademi, Turku (Finland). Combustion Chemistry Group
1996-12-31
The objective of this work has been to investigate the soot formation in a blast furnace fired with heavy fuel oil, using detailed kinetic modelling. This work has been concentrated on parameter studies that could explain under which conditions soot is formed and how that formation could be avoided. The parameters investigated were temperature, pressure, stoichiometric ratio, pyrolysis gas composition and reactor model. The calculations were based on a reaction mechanism that consists of 100 species and 446 reactions including polyaromatic hydrocarbons (PAM) up to 7 aromatic rings SULA 2 Research Programme; 4 refs.
Directory of Open Access Journals (Sweden)
S. A. Marrero Osorio
2008-09-01
Full Text Available El presente artículo expone una manera de diseñar paramétricamente utilizando los programas de computadora (CAD,CAE, PMS difundidos entre los diseñadores durante los últimos 20 años. La propuesta se basa en modelos matemáticosque consideran el conocimiento sobre la ingeniería del objeto de diseño y lo relacionado con la confección de su modelovirtual tridimensional, planos y otro aspectos; utilizando el Método de los Grafos Dicromáticos para resolver los problemascomputacionales que se presentan en el diseño paramétrico. Se analizan los puntos de vista de diferentes autores en relacióncon el proceso general de diseño y es ubicado dentro del mismo el diseño paramétrico, realizándose una explicación formalque permite arribar a conclusiones interesantes.Palabras claves: Diseño paramétrico, diseño asistido por computadoras (CAD, ingeniería asistida porcomputadoras (CAE, software para el modelado paramétrico (PMS, resolución de problemas._____________________________________________________________________________Abstract:The present article exposes a way to design parametrically applying programs (CAD, CAE, PMS accepted by designers along thelast 20 years. The proposal is based on mathematical models that ponder the knowledge on the engineering of the design object andthe building of its three-dimensional virtual models, blueprints and another aspects; using the dichromatic graph method to solvecomputational problems in parametric design. The points of view of different authors are analyzed in connection with the generalprocess of design, locating parametric design inside it, carrying out a formal explanation which arrives to interesting conclusions.Key words: Parametric design, computer aided design (CAD, computer aided engineering (CAE,parametric modeling software (PMS, problem solving.
DEFF Research Database (Denmark)
Nielsen, Jan; Parner, Erik
2010-01-01
In this paper, we model multivariate time-to-event data by composite likelihood of pairwise frailty likelihoods and marginal hazards using natural cubic splines. Both right- and interval-censored data are considered. The suggested approach is applied on two types of family studies using the gamma...
Dynamic modeling and explicit/multi-parametric MPC control of pressure swing adsorption systems
Khajuria, Harish; Pistikopoulos, Efstratios N.
2011-01-01
objective is to fast track H2 purity to a set point value of 99.99%. To perform this task, a rigorous and systematic framework is employed. First, a high fidelity detailed dynamic model is built to represent the system's real operation, and understand its
Modeling and parametric simulations of solid oxide fuel cells with methane carbon dioxide reforming
International Nuclear Information System (INIS)
Ni, Meng
2013-01-01
Highlights: ► A 2D model is developed for solid oxide fuel cells (SOFCs). ► CH 4 reforming by CO 2 (MCDR) is included. ► SOFC with MCDR shows comparable performance with methane steam reforming SOFC. ► Increasing CO electrochemical oxidation greatly enhances the SOFC performance. ► Effects of potential and temperature on SOFC performance are also discussed. - Abstract: A two-dimensional model is developed to simulate the performance of solid oxide fuel cells (SOFCs) fed with CO 2 and CH 4 mixture. The electrochemical oxidations of both CO and H 2 are included. Important chemical reactions are considered in the model, including methane carbon dioxide reforming (MCDR), reversible water gas shift reaction (WGSR), and methane steam reforming (MSR). It’s found that at a CH 4 /CO 2 molar ratio of 50/50, MCDR and reversible WGSR significantly influence the cell performance while MSR is negligibly small. The performance of SOFC fed with CO 2 /CH 4 mixture is comparable to SOFC running on CH 4 /H 2 O mixtures. The electric output of SOFC can be enhanced by operating the cell at a low operating potential or at a high temperature. In addition, the development of anode catalyst with high activity towards CO electrochemical oxidation is important for SOFC performance enhancement. The model can serve as a useful tool for optimization of the SOFC system running on CH 4 /CO 2 mixtures
DEFF Research Database (Denmark)
Petersen, Jørgen Holm
2016-01-01
This paper describes a new approach to the estimation in a logistic regression model with two crossed random effects where special interest is in estimating the variance of one of the effects while not making distributional assumptions about the other effect. A composite likelihood is studied...
An estimating equation for parametric shared frailty models with marginal additive hazards
DEFF Research Database (Denmark)
Pipper, Christian Bressen; Martinussen, Torben
2004-01-01
Multivariate failure time data arise when data consist of clusters in which the failure times may be dependent. A popular approach to such data is the marginal proportional hazards model with estimation under the working independence assumption. In some contexts, however, it may be more reasonable...
International Nuclear Information System (INIS)
Martin Urreta, J.C.; Bilbao, P.; Cacicedo, J.M.; Ensunza, P.; Megueruela, J.T.
1988-01-01
In this paper the problem of dose fractionation, the expression of this and its mathematical development is studied. Likewise, a comparative study -using an exemple- between the linear quadratic model proposed by Fowler amongst others, and the time-dose fractionation of Orton and Ellis, is made. (Author)
Caridakis, G; Karpouzis, K; Drosopoulos, A; Kollias, S
2012-12-01
Modeling and recognizing spatiotemporal, as opposed to static input, is a challenging task since it incorporates input dynamics as part of the problem. The vast majority of existing methods tackle the problem as an extension of the static counterpart, using dynamics, such as input derivatives, at feature level and adopting artificial intelligence and machine learning techniques originally designed for solving problems that do not specifically address the temporal aspect. The proposed approach deals with temporal and spatial aspects of the spatiotemporal domain in a discriminative as well as coupling manner. Self Organizing Maps (SOM) model the spatial aspect of the problem and Markov models its temporal counterpart. Incorporation of adjacency, both in training and classification, enhances the overall architecture with robustness and adaptability. The proposed scheme is validated both theoretically, through an error propagation study, and experimentally, on the recognition of individual signs, performed by different, native Greek Sign Language users. Results illustrate the architecture's superiority when compared to Hidden Markov Model techniques and variations both in terms of classification performance and computational cost. Copyright © 2012 Elsevier Ltd. All rights reserved.
Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images
International Nuclear Information System (INIS)
Štern, Darko; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž
2011-01-01
Accurate and objective evaluation of vertebral deformations is of significant importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is focused on three-dimensional (3D) computed tomography (CT) and magnetic resonance (MR) imaging techniques, the established methods for evaluation of vertebral deformations are limited to measuring deformations in two-dimensional (2D) x-ray images. In this paper, we propose a method for quantitative description of vertebral body deformations by efficient modelling and segmentation of vertebral bodies in 3D. The deformations are evaluated from the parameters of a 3D superquadric model, which is initialized as an elliptical cylinder and then gradually deformed by introducing transformations that yield a more detailed representation of the vertebral body shape. After modelling the vertebral body shape with 25 clinically meaningful parameters and the vertebral body pose with six rigid body parameters, the 3D model is aligned to the observed vertebral body in the 3D image. The performance of the method was evaluated on 75 vertebrae from CT and 75 vertebrae from T 2 -weighted MR spine images, extracted from the thoracolumbar part of normal and pathological spines. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images, as the proposed 3D model is able to describe both normal and pathological vertebral body deformations. The method may therefore be used for initialization of whole vertebra segmentation or for quantitative measurement of vertebral body deformations.
International Nuclear Information System (INIS)
Berwald, D.H.; Mendelsohn, S.S.; Myers, T.J.; Paulson, C.C.; Peacock, M.A.; Piaszczyk, CM.; Rathke, J.W.; Piechowiak, E.M.
1996-01-01
Emerging applications for high power rf linacs include fusion materials testing, generation of intense spallation neutrons for neutron physics and materials studies, production of nuclear materials and destruction of nuclear waste. Each requires the selection of an optimal configuration and operating parameters for its accelerator, rf power system and other supporting subsystems. Because of the high cost associated with these facilities, economic considerations become paramount, dictating a full evaluation of the electrical and rf performance, system reliability/availability, and capital, operating, and life cycle costs. The Accelerator Systems Model (ASM), expanded and modified by Northrop Grumman during 1993-96, provides a unique capability for detailed layout and evaluation of a wide variety of normal and superconducting accelerator and rf power configurations. This paper will discuss the current capabilities of ASM, including the available models and data base, and types of trade studies that can be performed for the above applications. (author)
Parametric Modeling of the Safety Effects of NextGen Terminal Maneuvering Area Conflict Scenarios
Rogers, William H.; Waldron, Timothy P.; Stroiney, Steven R.
2011-01-01
The goal of this work was to analytically identify and quantify the issues, challenges, technical hurdles, and pilot-vehicle interface issues associated with conflict detection and resolution (CD&R)in emerging operational concepts for a NextGen terminal aneuvering area, including surface operations. To this end, the work entailed analytical and trade studies focused on modeling the achievable safety benefits of different CD&R strategies and concepts in the current and future airport environment. In addition, crew-vehicle interface and pilot performance enhancements and potential issues were analyzed based on review of envisioned NextGen operations, expected equipage advances, and human factors expertise. The results of perturbation analysis, which quantify the high-level performance impact of changes to key parameters such as median response time and surveillance position error, show that the analytical model developed could be useful in making technology investment decisions.
The parametrization of Coulomb barrier heights and positions using the double folding model
International Nuclear Information System (INIS)
Qu, W.W.; Zhang, G.L.; Le, X.Y.
2011-01-01
The Coulomb barrier heights and positions are systematically shown with mass numbers and charge radii of the interacting nuclei. The nuclear potential is calculated by using the double folding model with the density-dependence nucleon-nucleon interaction (CDM3Y6). The pocket formulas are obtained for the Coulomb barrier heights and positions by analyzing several hundreds of heavy-ion systems with mass numbers from light nuclei to heavy nuclei. The parameterized formulas can reproduce the calculated barrier heights and positions by using the double folding model within the accuracy of ±1%. Moreover, the results are agreeable with the experimental data. The relation between the barrier height and the barrier position is also studied.
Parametric sensitivity of a CFD model concerning the hydrodynamics of trickle-bed reactor (TBR
Directory of Open Access Journals (Sweden)
Janecki Daniel
2016-03-01
Full Text Available The aim of the present study was to investigate the sensitivity of a multiphase Eulerian CFD model with respect to relations defining drag forces between phases. The mean relative error as well as standard deviation of experimental and computed values of pressure gradient and average liquid holdup were used as validation criteria of the model. Comparative basis for simulations was our own data-base obtained in experiments carried out in a TBR operating at a co-current downward gas and liquid flow. Estimated errors showed that the classical equations of Attou et al. (1999 defining the friction factors Fjk approximate experimental values of hydrodynamic parameters with the best agreement. Taking this into account one can recommend to apply chosen equations in the momentum balances of TBR.
Rajeswaran, Jeevanantham; Blackstone, Eugene H; Ehrlinger, John; Li, Liang; Ishwaran, Hemant; Parides, Michael K
2018-01-01
Atrial fibrillation is an arrhythmic disorder where the electrical signals of the heart become irregular. The probability of atrial fibrillation (binary response) is often time varying in a structured fashion, as is the influence of associated risk factors. A generalized nonlinear mixed effects model is presented to estimate the time-related probability of atrial fibrillation using a temporal decomposition approach to reveal the pattern of the probability of atrial fibrillation and their determinants. This methodology generalizes to patient-specific analysis of longitudinal binary data with possibly time-varying effects of covariates and with different patient-specific random effects influencing different temporal phases. The motivation and application of this model is illustrated using longitudinally measured atrial fibrillation data obtained through weekly trans-telephonic monitoring from an NIH sponsored clinical trial being conducted by the Cardiothoracic Surgery Clinical Trials Network.
Quasi-Dimensional Modelling and Parametric Studies of a Heavy-Duty HCCI Engine
Directory of Open Access Journals (Sweden)
Sunil Kumar Pandey
2011-01-01
Full Text Available A quasi-dimensional modelling study is conducted for the first time for a heavy duty, diesel-fuelled, multicylinder engine operating in HCCI mode. This quasidimensional approach involves a zero-dimensional single-zone homogeneous charge compression ignition (HCCI combustion model along with a one-dimensional treatment of the intake and exhaust systems. A skeletal chemical kinetic scheme for n-heptane was used in the simulations. Exhaust gas recirculation (EGR and compression ratio (CR were the two parameters that were altered in order to deal with the challenges of combustion phasing control and operating load range extension. Results from the HCCI mode simulations show good potential when compared to conventional diesel performance with respect to important performance parameters such as peak firing pressure, specific fuel consumption, peak pressure rise, and combustion noise. This study shows that HCCI combustion mode can be employed at part load of 25% varying the EGR rates between 0 and 60%.
Identification of a parametric, discrete-time model of ankle stiffness.
Guarin, Diego L; Jalaleddini, Kian; Kearney, Robert E
2013-01-01
Dynamic ankle joint stiffness defines the relationship between the position of the ankle and the torque acting about it and can be separated into intrinsic and reflex components. Under stationary conditions, intrinsic stiffness can described by a linear second order system while reflex stiffness is described by Hammerstein system whose input is delayed velocity. Given that reflex and intrinsic torque cannot be measured separately, there has been much interest in the development of system identification techniques to separate them analytically. To date, most methods have been nonparametric and as a result there is no direct link between the estimated parameters and those of the stiffness model. This paper presents a novel algorithm for identification of a discrete-time model of ankle stiffness. Through simulations we show that the algorithm gives unbiased results even in the presence of large, non-white noise. Application of the method to experimental data demonstrates that it produces results consistent with previous findings.
Non-parametric Bayesian models of response function in dynamic image sequences
Czech Academy of Sciences Publication Activity Database
Tichý, Ondřej; Šmídl, Václav
2016-01-01
Roč. 151, č. 1 (2016), s. 90-100 ISSN 1077-3142 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Response function * Blind source separation * Dynamic medical imaging * Probabilistic models * Bayesian methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.498, year: 2016 http://library.utia.cas.cz/separaty/2016/AS/tichy-0456983.pdf
Parametric Variation for Detailed Model of External Grid in Offshore Wind Power Plants
DEFF Research Database (Denmark)
Myagkov, Vladimir; Petersen, Lennart; Laza, Burutxaga
2014-01-01
The representation of the external grid impedance is a key element in harmonic studies for offshore wind farms. The external grid impedance is here represented by two different approaches: by a simplified impedance model, based on values for short-circuit power and XR-ratio and by locus diagrams...... for defining a procedure for conducting harmonic studies in wind farms that can be used in commercial project developments....
Directory of Open Access Journals (Sweden)
Shayoni Ray
Full Text Available Cleft formation during submandibular salivary gland branching morphogenesis is the critical step initiating the growth and development of the complex adult organ. Previous experimental studies indicated requirements for several epithelial cellular processes, such as proliferation, migration, cell-cell adhesion, cell-extracellular matrix (matrix adhesion, and cellular contraction in cleft formation; however, the relative contribution of each of these processes is not fully understood since it is not possible to experimentally manipulate each factor independently. We present here a comprehensive analysis of several cellular parameters regulating cleft progression during branching morphogenesis in the epithelial tissue of an early embryonic salivary gland at a local scale using an on lattice Monte-Carlo simulation model, the Glazier-Graner-Hogeweg model. We utilized measurements from time-lapse images of mouse submandibular gland organ explants to construct a temporally and spatially relevant cell-based 2D model. Our model simulates the effect of cellular proliferation, actomyosin contractility, cell-cell and cell-matrix adhesions on cleft progression, and it was used to test specific hypotheses regarding the function of these parameters in branching morphogenesis. We use innovative features capturing several aspects of cleft morphology and quantitatively analyze clefts formed during functional modification of the cellular parameters. Our simulations predict that a low epithelial mitosis rate and moderate level of actomyosin contractility in the cleft cells promote cleft progression. Raising or lowering levels of contractility and mitosis rate resulted in non-progressive clefts. We also show that lowered cell-cell adhesion in the cleft region and increased cleft cell-matrix adhesions are required for cleft progression. Using a classifier-based analysis, the relative importance of these four contributing cellular factors for effective cleft
Semi-parametric proportional intensity models robustness for right-censored recurrent failure data
Energy Technology Data Exchange (ETDEWEB)
Jiang, S.T. [College of Engineering, University of Oklahoma, 202 West Boyd St., Room 107, Norman, OK 73019 (United States); Landers, T.L. [College of Engineering, University of Oklahoma, 202 West Boyd St., Room 107, Norman, OK 73019 (United States)]. E-mail: landers@ou.edu; Rhoads, T.R. [College of Engineering, University of Oklahoma, 202 West Boyd St., Room 107, Norman, OK 73019 (United States)
2005-10-01
This paper reports the robustness of the four proportional intensity (PI) models: Prentice-Williams-Peterson-gap time (PWP-GT), PWP-total time (PWP-TT), Andersen-Gill (AG), and Wei-Lin-Weissfeld (WLW), for right-censored recurrent failure event data. The results are beneficial to practitioners in anticipating the more favorable engineering application domains and selecting appropriate PI models. The PWP-GT and AG prove to be models of choice over ranges of sample sizes, shape parameters, and censoring severity. At the smaller sample size (U=60), where there are 30 per class for a two-level covariate, the PWP-GT proves to perform well for moderate right-censoring (P {sub c}{<=}0.8), where 80% of the units have some censoring, and moderately decreasing, constant, and moderately increasing rates of occurrence of failures (power-law NHPP shape parameter in the range of 0.8{<=}{delta}{<=}1.8). For the large sample size (U=180), the PWP-GT performs well for severe right-censoring (0.8
model proves to outperform the PWP-TT and WLW for stationary processes (HPP) across a wide range of right-censorship (0.0{<=}P {sub c}{<=}1.0) and for sample sizes of 60 or more.
Directory of Open Access Journals (Sweden)
Jo Nishino
2018-04-01
Full Text Available Genome-wide association studies (GWAS suggest that the genetic architecture of complex diseases consists of unexpectedly numerous variants with small effect sizes. However, the polygenic architectures of many diseases have not been well characterized due to lack of simple and fast methods for unbiased estimation of the underlying proportion of disease-associated variants and their effect-size distribution. Applying empirical Bayes estimation of semi-parametric hierarchical mixture models to GWAS summary statistics, we confirmed that schizophrenia was extremely polygenic [~40% of independent genome-wide SNPs are risk variants, most within odds ratio (OR = 1.03], whereas rheumatoid arthritis was less polygenic (~4 to 8% risk variants, significant portion reaching OR = 1.05 to 1.1. For rheumatoid arthritis, stratified estimations revealed that expression quantitative loci in blood explained large genetic variance, and low- and high-frequency derived alleles were prone to be risk and protective, respectively, suggesting a predominance of deleterious-risk and advantageous-protective mutations. Despite genetic correlation, effect-size distributions for schizophrenia and bipolar disorder differed across allele frequency. These analyses distinguished disease polygenic architectures and provided clues for etiological differences in complex diseases.
Energy Technology Data Exchange (ETDEWEB)
Wu, Zhiliang; Wang, Shuxin; Zhang, Lianhong [School of Mechanical Engineering, Tianjin University, Tianjin 300072 (China); Hu, S. Jack [Department of Mechanical Engineering, The University of Michigan, Ann Arbor, MI 48109-2125 (United States)
2009-04-15
This paper presents an analytical model of the electrical contact resistance between the carbon paper gas diffusion layers (GDLs) and the graphite bipolar plates (BPPs) in a proton exchange membrane (PEM) fuel cell. The model is developed based on the classical statistical contact theory for a PEM fuel cell, using the same probability distributions of the GDL structure and BPP surface profile as previously described in Wu et al. [Z. Wu, Y. Zhou, G. Lin, S. Wang, S.J. Hu, J. Power Sources 182 (2008) 265-269] and Zhou et al. [Y. Zhou, G. Lin, A.J. Shih, S.J. Hu, J. Power Sources 163 (2007) 777-783]. Results show that estimates of the contact resistance compare favorably with experimental data by Zhou et al. [Y. Zhou, G. Lin, A.J. Shih, S.J. Hu, J. Power Sources 163 (2007) 777-783]. Factors affecting the contact behavior are systematically studied using the analytical model, including the material properties of the two contact bodies and factors arising from the manufacturing processes. The transverse Young's modulus of chopped carbon fibers in the GDL and the surface profile of the BPP are found to be significant to the contact resistance. The factor study also sheds light on the manufacturing requirements of carbon fiber GDLs for a better contact performance in PEM fuel cells. (author)
Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach
Chowdhury, R.; Adhikari, S.
2012-10-01
Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.
Modeling the dynamic operation of a small fin plate heat exchanger – parametric analysis
Directory of Open Access Journals (Sweden)
Motyliński Konrad
2015-09-01
Full Text Available Given its high efficiency, low emissions and multiple fuelling options, the solid oxide fuel cells (SOFC offer a promising alternative for stationary power generators, especially while engaged in micro-combined heat and power (μ-CHP units. Despite the fact that the fuel cells are a key component in such power systems, other auxiliaries of the system can play a critical role and therefore require a significant attention. Since SOFC uses a ceramic material as an electrolyte, the high operating temperature (typically of the order of 700–900 °C is required to achieve sufficient performance. For that reason both the fuel and the oxidant have to be preheated before entering the SOFC stack. Hot gases exiting the fuel cell stack transport substantial amount of energy which has to be partly recovered for preheating streams entering the stack and for heating purposes. Effective thermal integration of the μ-CHP can be achieved only when proper technical measures are used. The ability of efficiently preheating the streams of oxidant and fuel relies on heat exchangers which are present in all possible configurations of power system with solid oxide fuel cells. In this work a compact, fin plate heat exchanger operating in the high temperature regime was under consideration. Dynamic model was proposed for investigation of its performance under the transitional states of the fuel cell system. Heat exchanger was simulated using commercial modeling software. The model includes key geometrical and functional parameters. The working conditions of the power unit with SOFC vary due to the several factors, such as load changes, heating and cooling procedures of the stack and others. These issues affect parameters of the incoming streams to the heat exchanger. The mathematical model of the heat exchanger is based on a set of equations which are simultaneously solved in the iterative process. It enables to define conditions in the outlets of both the hot and the
Weisheimer, Antje; Corti, Susanna; Palmer, Tim; Vitart, Frederic
2014-01-01
The finite resolution of general circulation models of the coupled atmosphere–ocean system and the effects of sub-grid-scale variability present a major source of uncertainty in model simulations on all time scales. The European Centre for Medium-Range Weather Forecasts has been at the forefront of developing new approaches to account for these uncertainties. In particular, the stochastically perturbed physical tendency scheme and the stochastically perturbed backscatter algorithm for the atmosphere are now used routinely for global numerical weather prediction. The European Centre also performs long-range predictions of the coupled atmosphere–ocean climate system in operational forecast mode, and the latest seasonal forecasting system—System 4—has the stochastically perturbed tendency and backscatter schemes implemented in a similar way to that for the medium-range weather forecasts. Here, we present results of the impact of these schemes in System 4 by contrasting the operational performance on seasonal time scales during the retrospective forecast period 1981–2010 with comparable simulations that do not account for the representation of model uncertainty. We find that the stochastic tendency perturbation schemes helped to reduce excessively strong convective activity especially over the Maritime Continent and the tropical Western Pacific, leading to reduced biases of the outgoing longwave radiation (OLR), cloud cover, precipitation and near-surface winds. Positive impact was also found for the statistics of the Madden–Julian oscillation (MJO), showing an increase in the frequencies and amplitudes of MJO events. Further, the errors of El Niño southern oscillation forecasts become smaller, whereas increases in ensemble spread lead to a better calibrated system if the stochastic tendency is activated. The backscatter scheme has overall neutral impact. Finally, evidence for noise-activated regime transitions has been found in a cluster analysis of mid
Essays on parametric and nonparametric modeling and estimation with applications to energy economics
Gao, Weiyu
My dissertation research is composed of two parts: a theoretical part on semiparametric efficient estimation and an applied part in energy economics under different dynamic settings. The essays are related in terms of their applications as well as the way in which models are constructed and estimated. In the first essay, efficient estimation of the partially linear model is studied. We work out the efficient score functions and efficiency bounds under four stochastic restrictions---independence, conditional symmetry, conditional zero mean, and partially conditional zero mean. A feasible efficient estimation method for the linear part of the model is developed based on the efficient score. A battery of specification test that allows for choosing between the alternative assumptions is provided. A Monte Carlo simulation is also conducted. The second essay presents a dynamic optimization model for a stylized oilfield resembling the largest developed light oil field in Saudi Arabia, Ghawar. We use data from different sources to estimate the oil production cost function and the revenue function. We pay particular attention to the dynamic aspect of the oil production by employing petroleum-engineering software to simulate the interaction between control variables and reservoir state variables. Optimal solutions are studied under different scenarios to account for the possible changes in the exogenous variables and the uncertainty about the forecasts. The third essay examines the effect of oil price volatility on the level of innovation displayed by the U.S. economy. A measure of innovation is calculated by decomposing an output-based Malmquist index. We also construct a nonparametric measure for oil price volatility. Technical change and oil price volatility are then placed in a VAR system with oil price and a variable indicative of monetary policy. The system is estimated and analyzed for significant relationships. We find that oil price volatility displays a significant
A Parametric Study to Improve Steam Explosion Models by Using a TROI Test
International Nuclear Information System (INIS)
Park, I. K.; Kim, J. H.; Min, B. T.; Hong, S. W.
2009-01-01
The overall objective of the OECD programme SERENA (Steam Explosion Resolution for Nuclear Applications) is to consolidate the understanding on FCI phenomenology and assess a method for reliable estimation of the magnitude of loadings for realistic reactor conditions, in order to bring about an understanding and predictability of FCI energetic to desirable levels for a risk management. Main conclusion of phase 1 is that in the absence of pre-existing loads, an in-vessel steam explosion would not challenge the integrity of the vessel, and damage to the cavity is to be expected for an ex-vessel explosion because the level of the loads cannot be predicted due to a large scattering of the results. One major uncertainty that does not allow for a convergence towards consistent predictions is that there is no data on the component distribution in a premixture at the time of the explosion, especially the level of a void. Global void fraction is only available from level-swell measurements. The other major uncertainty is the explosion behavior of corium melts. SERENA phase 2 project which has been conducted since 1st Oct. 2007 is aimed a resolution of the uncertainties on the void fraction and the melt composition effect by performing a limited number of well-designed tests with advanced instrumentations to clarify the nature of a prototypic material with mild steam explosion characteristics and to provide innovative experimental data for a computer code validation. An analytical working group (AWG) is established with the aim of increasing the capabilities the FCI models/codes for use in reactor analyses by complementing the work performed in Phase-1. The main tasks of the group are: performing pre-, posttest calculations, improving the common understanding of those key phenomena such as breakup, void fraction, and fragmentation, addressing the scaling effect and application to the reactor case, In this paper, the pre- and post-test calculation for the first TROI test
Mean – Variance parametric Model for the Classification based on Cries of Babies
Khalid Nazim S. A; Dr. M.B Sanjay Pande
2010-01-01
Cry is a feature which makes a individual to take certain care about the infant which has initiated it. It is also equally understood that cry makes a person to take certain steps. In the present work, we have tried to implement a mathematical model which can classify the cry into its cluster or group based on certain parameters based on which a cry is classified into a normal or abnormal. To corroborate the methodology we taken 17 distinguished features of cry. The implemented mathematical m...
International Nuclear Information System (INIS)
Rabi, Jose A.; Mohamad, Abdulmajeed A.
2004-01-01
Radon-222 is a radionuclide exhaled from phosphogypsum by-produced at phosphate fertilizer industries. Alternative large-scale application of this waste may indicate a material substitute for civil engineering provided that environmental issues concerning its disposal and management are overcome. The first part of this paper outlines a steady-state two-dimensional model for 222 Rn transport through porous media, inside which emanation (source term) and decay (sink term) exist. Boussinesq approach is evoked for the laminar buoyancy-driven interstitial air flow, which is also modeled according to Darcy-Brinkman formulation. In order to account for simultaneous effects of entailed physical parameters, governing equations are cast into dimensionless form. Apart from usual controlling parameters like Reynolds, Prandtl, Schmidt, Grashof and Darcy numbers, three unconventional dimensionless groups are put forward. Having in mind 222 Rn transport in phosphogypsum-bearing porous media, the physical meaning of those newly introduced parameters and representative values for the involved physical parameters are presented. A limiting diffusion-dominated scenario is addressed, for which an analytical solution is deduced for boundary conditions including an impermeable phosphogypsum stack base and a non-zero fixed concentration activity at the stack top. Accordingly, an expression for the average Sherwood number corresponding to the normalized 222 Rn exhalation rate is presented
Modelling of a passive autocatalytic hydrogen recombiner – a parametric study
Directory of Open Access Journals (Sweden)
Rożeń Antoni
2015-03-01
Full Text Available Operation of a passive autocatalytic hydrogen recombiner (PAR has been investigated by means of computational fluid dynamics methods (CFD. The recombiner is a self-active and self-adaptive device used to remove hydrogen from safety containments of light water nuclear reactors (LWR by means of a highly exothermic reaction with oxygen at the surface of a platinum or palladium catalyst. Different turbulence models (k-ω, k-ɛ, intermittency, RSM were applied in numerical simulations of: gas flow, heat and mass transport and chemical surface reactions occurring in PAR. Turbulence was found to improve mixing and mass transfer and increase hydrogen recombination rate for high gas flow rates. At low gas flow rates, simulation results converged to those obtained for the limiting case of laminar flow. The large eddy simulation technique (LES was used to select the best RANS (Reynolds average stress model. Comparison of simulation results obtained for two- and three-dimensional computational grids showed that heat and mass transfer occurring in PAR were virtually two-dimensional processes. The effect of hydrogen thermal diffusion was also discussed in the context of possible hydrogen ignition inside the recombiner.
Directory of Open Access Journals (Sweden)
El Harrouni Khalid
2018-01-01
Full Text Available The traditional courtyard house of the Mediterranean Basin has been viewed as a complex regulating system that creates a microclimate which historically worked, and still works, in a passive way to provide acceptable thermal comfort in summer. The internal courtyard is generally described as a positive factor that can moderate extreme outdoor climatic conditions. However, some researches have shown that the courtyard could become a negative factor from the energy efficiency point of view. For this purpose, this paper is based on a research study exploring sustainable characteristics of Moroccan traditional housing and its climatic adaptation, delving into the Rabat-Salé case study. A traditional courtyard model is used as a case study to analyze the indoor thermal comfort without using mechanical heating and cooling systems. The thermal behavior of the rooms surrounding the courtyard is analyzed under a temperate and humid climate of Rabat-Salé medina. The simulation modelling is carried out to analyze the effectiveness of different parameters to improve the indoor climate during summer and winter, including the façade orientation, the air infiltration, the surroundings, the ceiling height, the walls and roof/ceiling insulation and the shading devices. Tools for climatic design, Mahoney’s tables, Givoni and Szokolay bio climatic diagrams have been also used to improve design strategies in terms of thermal comfort.
Modelling of Cortical Bone Tissue as a Fluid Saturated Double-Porous Material - Parametric Study
Directory of Open Access Journals (Sweden)
Jana TURJANICOVÁ
2013-06-01
Full Text Available In this paper, the cortical bone tissue is considered as a poroelastic material with periodic structure represented at microscopic and mesoscopic levels. The pores of microscopic scale are connected with the pores of mesoscopic scale creating one system of connected network filled with compressible fluid. The method of asymptotic homogenization is applied to upscale the microscopic model of the fluid-solid interaction under a static loading. Obtained homogenized coefficients describe material properties of the poroelastic matrix fractured by fluid-filled pores whose geometry is described at the mesoscopic level. The second-level upscaling provides homogenized poroelastic coefficients relevant on the macroscopic scale. Furthermore, we study the dependence of these coefficients on geometrical parameters on related microscopic and macroscopic scales.
Khalilpour, Rajab
2011-08-12
The modeling and optimal design/operation of gas membranes for postcombustion carbon capture (PCC) is presented. A systematic methodology is presented for analysis of membrane systems considering multicomponent flue gas with CO 2 as target component. Simplifying assumptions is avoided by namely multicomponent flue gas represented by CO 2/N 2 binary mixture or considering the co/countercurrent flow pattern of hollow-fiber membrane system as mixed flow. Optimal regions of flue gas pressures and membrane area were found within which a technoeconomical process system design could be carried out. High selectivity was found to not necessarily have notable impact on PCC membrane performance, rather, a medium selectivity combined with medium or high permeance could be more advantageous. © 2011 American Institute of Chemical Engineers (AIChE).
Parametric analysis of a TOUGH2 model for the unsaturated zone at Yucca Mountain
Energy Technology Data Exchange (ETDEWEB)
Xiang, Y.; Mishra, S.; Dunlap, B. [CRWMS M& O/INTERA, Inc., Las Vegas, NV (United States)
1995-03-01
Yucca Mountain in Nevada is currently being investigated for suitability as a potential site for the disposal of high-level radioactive waste and spent nuclear fuel. As the most important natural barrier against radionuclide migration to the accessible environment, the unsaturated zone at Yucca mountain is a key constituent in assessing the ambient geohydrology. A three-dimensional site-scale TOUGH2 model of the unsaturated zone is currently under development by Lawrence Berkeley Laboratory (LBL) and the United States Geological Survey (USGS) consists of six hydrogeologic units - TCw (Tiva Canyon welded), PTn (Paintbrush nonwelded), TSw (Topopah Spring welded), TSv (Topopah Spring welded-vitrophyre), CHnz (Calico Hills nonwelded-vitric), and CHnz (Calico Hills nonwelded-zeolitic), which are further subdivided into seventeen layers to represent additional lithologic detail. Based on the work of Klavetter and Peters, the fractured units TCw and TSw are treated as equivalent continua with specified threshold saturation for triggering fracture flow.
Multi-Higgs doublet models: physical parametrization, sum rules and unitarity bounds
Bento, Miguel P.; Haber, Howard E.; Romão, J. C.; Silva, João P.
2017-11-01
If the scalar sector of the Standard Model is non-minimal, one might expect multiple generations of the hypercharge-1/2 scalar doublet analogous to the generational structure of the fermions. In this work, we examine the structure of a Higgs sector consisting of N Higgs doublets (where N ≥ 2). It is particularly convenient to work in the so-called charged Higgs basis, in which the neutral Higgs vacuum expectation value resides entirely in the first Higgs doublet, and the charged components of remaining N - 1 Higgs doublets are mass-eigenstate fields. We elucidate the interactions of the gauge bosons with the physical Higgs scalars and the Goldstone bosons and show that they are determined by an N × 2 N matrix. This matrix depends on ( N - 1)(2 N - 1) real parameters that are associated with the mixing of the neutral Higgs fields in the charged Higgs basis. Among these parameters, N - 1 are unphysical (and can be removed by rephasing the physical charged Higgs fields), and the remaining 2( N - 1)2 parameters are physical. We also demonstrate a particularly simple form for the cubic interaction and some of the quartic interactions of the Goldstone bosons with the physical Higgs scalars. These results are applied in the derivation of Higgs coupling sum rules and tree-level unitarity bounds that restrict the size of the quartic scalar couplings. In particular, new applications to three Higgs doublet models with an order-4 CP symmetry and with a Z_3 symmetry, respectively, are presented.
Energy Technology Data Exchange (ETDEWEB)
Mohammed, Irshad [Fermilab; Gnedin, Nickolay Y. [Fermilab
2017-07-07
Baryonic effects are amongst the most severe systematics to the tomographic analysis of weak lensing data which is the principal probe in many future generations of cosmological surveys like LSST, Euclid etc.. Modeling or parameterizing these effects is essential in order to extract valuable constraints on cosmological parameters. In a recent paper, Eifler et al. (2015) suggested a reduction technique for baryonic effects by conducting a principal component analysis (PCA) and removing the largest baryonic eigenmodes from the data. In this article, we conducted the investigation further and addressed two critical aspects. Firstly, we performed the analysis by separating the simulations into training and test sets, computing a minimal set of principle components from the training set and examining the fits on the test set. We found that using only four parameters, corresponding to the four largest eigenmodes of the training set, the test sets can be fitted thoroughly with an RMS $\\sim 0.0011$. Secondly, we explored the significance of outliers, the most exotic/extreme baryonic scenarios, in this method. We found that excluding the outliers from the training set results in a relatively bad fit and degraded the RMS by nearly a factor of 3. Therefore, for a direct employment of this method to the tomographic analysis of the weak lensing data, the principle components should be derived from a training set that comprises adequately exotic but reasonable models such that the reality is included inside the parameter domain sampled by the training set. The baryonic effects can be parameterized as the coefficients of these principle components and should be marginalized over the cosmological parameter space.
Miller, S W; Dennis, R G
1996-12-01
A parametric model was developed to describe the relationship between muscle moment arm and joint angle. The model was applied to the dorsiflexor muscle group in mice, for which the moment arm was determined as a function of ankle angle. The moment arm was calculated from the torque measured about the ankle upon application of a known force along the line of action of the dorsiflexor muscle group. The dependence of the dorsiflexor moment arm on ankle angle was modeled as r = R sin(a + delta), where r is the moment arm calculated from the measured torque and a is the joint angle. A least-squares curve fit yielded values for R, the maximum moment arm, and delta, the angle at which the maximum moment arm occurs as offset from 90 degrees. Parametric models were developed for two strains of mice, and no differences were found between the moment arms determined for each strain. Values for the maximum moment arm, R, for the two different strains were 0.99 and 1.14 mm, in agreement with the limited data available from the literature. While in some cases moment arm data may be better fitted by a polynomial, use of the parametric model provides a moment arm relationship with meaningful anatomical constants, allowing for the direct comparison of moment arm characteristics between different strains and species.
International Nuclear Information System (INIS)
Calise, F.; Ferruzzi, G.; Vanoli, L.
2009-01-01
This paper presents a very detailed local exergy analysis of a tubular Solid Oxide Fuel Cell (SOFC) stack. In particular, a complete parametric analysis has been carried out, in order to assess the effects of the synthesis/design parameters on the local irreversibilities in the components of the stack. A finite-volume axial-symmetric model of the tubular internal reforming Solid Oxide Fuel Cell stack under investigation has been used. The stack consists of: SOFC tubes, tube-in-tube pre-reformer and tube and shell catalytic burner. The model takes into account the effects of heat/mass transfer and chemical/electrochemical reactions. The model allows one to predict the performance of a SOFC stack once a series of design and operative parameters are fixed, but also to investigate the source and localization of inefficiency. To this scope, an exergy analysis was implemented. The SOFC tube, the pre-reformer and the catalytic burner are discretized along their longitudinal axes. Detailed models of the kinetics of the reforming, catalytic combustion and electrochemical reactions are implemented. Pressure drops, convection heat transfer and overvoltages are calculated on the basis of the work previously developed by the authors. The heat transfer model includes the contribution of thermal radiation, so improving the models previously used by the authors. Radiative heat transfer is calculated on the basis of the slice-to-slice configuration factors and corresponding radiosities. On the basis of this thermochemical model, an exergy analysis has been carried out, in order to localize the sources and the magnitude of irreversibilities along the components of the stack. In addition, the main synthesis/design variables were varied in order to assess their effect on the exergy destruction within the component to which the parameter directly refers ('endogenous' contribution) and on the exergy destruction of all remaining components ('exogenous' contribution). Then, this analysis
Malinovic-Milicevic, S.; Mihailovic, D. T.; Radovanovic, M. M.
2015-07-01
This paper focuses on the development and application of a technique for filling the daily erythemal UV dose data gaps and the reconstruction of the past daily erythemal UV doses in Novi Sad, Serbia. The technique implies developing the empirical equation for estimation of daily erythemal UV doses by means of relative daily sunshine duration under all sky conditions. A good agreement was found between modeled and measured values of erythemal UV doses. This technique was used for filling the short gaps in the erythemal UV dose measurement series (2003-2009) as well as for the reconstruction of the past time-series values (1981-2002). Statistically significant positive erythemal UV dose trend of 6.9 J m-2 per year was found during the period 1981-2009. In relation to the reference period 1981-1989, an increase in the erythemal UV dose of 6.92 % is visible in the period 1990-1999 and the increase of 9.67 % can be seen in the period 2000-2009. The strongest increase in erythemal UV doses has been found for winter and spring seasons.
International Nuclear Information System (INIS)
Hiroshima, Fumio
2002-01-01
Scaling limits of the Hamiltonian H of a system of N charged particles coupled to a quantized radiation field are considered. Ultraviolet cutoffs, λ 1 ,...,λ N , are imposed on the radiation field and the Coulomb gauge is taken. It is the so-called Pauli-Fierz model in nonrelativistic quantum electrodynamics. We mainly consider two cases: (i) all the ultraviolet cutoffs are identical, λ 1 =···=λ N , (ii) supports of ultraviolet cutoffs have no intersection, supp λ i intersection supp λ j = null-set , i≠j. The Hamiltonian acts on L 2 (R dN )(multiply-in-circle sign)F, where F is a symmetric Fock space, and has the form H=H el (multiply-in-circle sign)1+B+1(multiply-in-circle sign)H quad . Here H el denotes a particle Hamiltonian, H quad a quadratic field operator, and B an interaction term. The scaling is introduced as H(κ)=H el (multiply-in-circle sign)1+κ l B+κ 2 1(multiply-in-circle sign)H quad , where κ is a scaling parameter and l≤2 a parameter of the scaling. Performing a mass renormalization we consider the scaling limit of H(κ) as κ→∞ in the strong resolvent sense. Then effective Hamiltonians H eff in L 2 (R dN ) infected with reaction of effect of the radiation field is derived. In particular (1) effective Hamiltonians with an effective potential for l=2, and (2) effective Hamiltonians with an observed mass for l=1, are obtained
Directory of Open Access Journals (Sweden)
Homayoun Ebrahimian
2013-06-01
Full Text Available Background & Objectives: The development of technology has naturally given rise to an increase in environmental low-frequency electromagnetic fields and consequently has attracted scholars' attention. Most of the studies have focused on transmission lines and power system distribution with 50 Hz. This research is an attempt to show the effect of 50 Hz magnetic fields on bioelectric parameters and indicates the possible influence of this change in F1 cells of Helix aspersa . Methods: The present research used Helix aspersa neuron F1 to identify the location of magnetic fields as well as the rate of effects of environmental magnetic fields on nervous system. Control group was used to study the effect of elapsed time, electrode entering and the cell membrane rupture. Intuition group and environmental group were considered in order to study the potential impact of interfering environmental factors and identify the effectiveness rate of magnetic fields, respectively. For the purpose of producing uniform magnetic field Helmholtz coil was used. Electrophysiological recording was realized under the requirements of current clamp. And, in order to show the impacts from magnetic fields on ion channels Hodgkin-Huxley cell model was applied. All data were analyzed taking the advantage of SPSS 16 software and two-way ANOVA statistical test. P < 0.05 was considered as significance level. And MATLAB software environment and PSO were used in order for applying the algorithm and estimating the parameters. Result: No statistically significant difference was found between control and sham groups in different time intervals. Once the 45.87 microtesla was applied significant differences were observed 12 minutes after the application. The highest amount of change happened 14 minutes after the application of more fields. With the application of the field, the amplitude of the sodium action potential shows decreasing trend . No significant changes were observed in
Parametric Linear Dynamic Logic
Directory of Open Access Journals (Sweden)
Peter Faymonville
2014-08-01
Full Text Available We introduce Parametric Linear Dynamic Logic (PLDL, which extends Linear Dynamic Logic (LDL by temporal operators equipped with parameters that bound their scope. LDL was proposed as an extension of Linear Temporal Logic (LTL that is able to express all ω-regular specifications while still maintaining many of LTL's desirable properties like an intuitive syntax and a translation into non-deterministic Büchi automata of exponential size. But LDL lacks capabilities to express timing constraints. By adding parameterized operators to LDL, we obtain a logic that is able to express all ω-regular properties and that subsumes parameterized extensions of LTL like Parametric LTL and PROMPT-LTL. Our main technical contribution is a translation of PLDL formulas into non-deterministic Büchi word automata of exponential size via alternating automata. This yields a PSPACE model checking algorithm and a realizability algorithm with doubly-exponential running time. Furthermore, we give tight upper and lower bounds on optimal parameter values for both problems. These results show that PLDL model checking and realizability are not harder than LTL model checking and realizability.
Modelling the presence of myelin and oedema in the brain based on multi-parametric quantitative MRI
Directory of Open Access Journals (Sweden)
Marcel eWarntjes
2016-02-01
Full Text Available The aim of this study was to present a model that uses multi-parametric quantitative MRI to estimate the presence of myelin and oedema in the brain. The model relates simultaneous measurement of R1 and R2 relaxation rates and proton density to four partial volume compartments, consisting of myelin partial volume, cellular partial volume, free water partial volume and excess parenchymal water partial volume. The model parameters were obtained using spatially normalised brain images of a group of 20 healthy controls. The pathological brain was modelled in terms of the reduction of myelin content and presence of excess parenchymal water, which indicates the degree of oedema. The method was tested on spatially normalised brain images of a group of 20 age-matched multiple sclerosis (MS patients. Clear differences were observed with respect to the healthy controls: the MS group had a 79 mL smaller brain volume (1069 vs. 1148 mL, a 38 mL smaller myelin volume (119 vs. 157 mL and a 21 mL larger excess parenchymal water volume (78 vs. 57 mL. Template regions of interest of various brain structures indicated that the myelin partial volume in the MS group was 1.6±1.5% lower for grey matter (GM structures and 2.8±1.0% lower for white matter (WM structures. The excess parenchymal water partial volume was 9±10% larger for GM and 5±2% larger for WM. Manually placed ROIs indicated that the results using the template ROIs may have suffered from loss of anatomical detail due to the spatial normalization process. Examples of the application of the method on high-resolution images are provided for three individual subjects, a 45-year-old healthy subject, a 72-year-old healthy subject and a 45-year-old MS patient. The observed results agreed with the expected behaviour considering both age and disease. In conclusion, the proposed model may provide clinically important parameters such as the total brain volume, degree of myelination and degree of oedema, based on
Directory of Open Access Journals (Sweden)
Samane Hajiabbasi
2018-01-01
Conclusion In single-variable fitting, age, history of myocardial infarction, history of stroke, and kidney problems were identified to have significant effects on the time to death of the elderly. Based on one-variable semi-parametric competing risk mixture fitted models, more significant risk factors for the time to death of elderly was identified when compared with a fitted multivariate mode to the data. This implies that the role of some independent variables can be explained by other independent variables.
DEFF Research Database (Denmark)
Göçmen Bozkurt, Tuhfe; Giebel, Gregor; Poulsen, Niels Kjølstad
2014-01-01
With increasing installed capacity, wind farms are requested to downregulate more frequently, especially in the offshore environment. Determination and verification of possible (or available) power of downregulated offshore wind farms are the aims of the PossPOW project (see PossPOW.dtu.dk). Two ...... period. The re-calibrated model has to be further parametrized to include dynamic effects such as wind direction variability and meandering also considering different averaging time scales before implemented in full scale wind farms....
Gianola, Daniel; Wu, Xiao-Lin; Manfredi, Eduardo; Simianer, Henner
2010-10-01
set of combinations of parameters of a given prior distribution, the effects of the prior dissipated when the number of replicate samples per genotype was increased. Thus, the Dirichlet process model seems to be useful for gauging the number of QTLs affecting the trait: if the number of clusters inferred is small, probably just a few QTLs code for the trait. If the number of clusters inferred is large, this may imply that standard parametric models based on the baseline distribution may suffice. However, priors may be influential, especially if sample size is not large and if only a few genotypic configurations have replicate phenotypes in the sample.
Czech Academy of Sciences Publication Activity Database
Ay, N.; Jost, J.; Le, Hong-Van; Schwachhöfer, L.
2018-01-01
Roč. 24, č. 3 (2018), s. 1692-1725 ISSN 1350-7265 Institutional support: RVO:67985840 Keywords : Amari–Chentsov tensor * Fisher quadratic * form monotonicity * sufficient statistic Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 1.070, year: 2016 https://projecteuclid.org/euclid.bj/1517540458
Parametric nanomechanical amplification at very high frequency.
Karabalin, R B; Feng, X L; Roukes, M L
2009-09-01
Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.
Modeling and forecasting petroleum futures volatility
International Nuclear Information System (INIS)
Sadorsky, Perry
2006-01-01
Forecasts of oil price volatility are important inputs into macroeconometric models, financial market risk assessment calculations like value at risk, and option pricing formulas for futures contracts. This paper uses several different univariate and multivariate statistical models to estimate forecasts of daily volatility in petroleum futures price returns. The out-of-sample forecasts are evaluated using forecast accuracy tests and market timing tests. The TGARCH model fits well for heating oil and natural gas volatility and the GARCH model fits well for crude oil and unleaded gasoline volatility. Simple moving average models seem to fit well in some cases provided the correct order is chosen. Despite the increased complexity, models like state space, vector autoregression and bivariate GARCH do not perform as well as the single equation GARCH model. Most models out perform a random walk and there is evidence of market timing. Parametric and non-parametric value at risk measures are calculated and compared. Non-parametric models outperform the parametric models in terms of number of exceedences in backtests. These results are useful for anyone needing forecasts of petroleum futures volatility. (author)
Mazzetti, S.; Giannini, V.; Russo, F.; Regge, D.
2018-05-01
Computer-aided diagnosis (CAD) systems are increasingly being used in clinical settings to report multi-parametric magnetic resonance imaging (mp-MRI) of the prostate. Usually, CAD systems automatically highlight cancer-suspicious regions to the radiologist, reducing reader variability and interpretation errors. Nevertheless, implementing this software requires the selection of which mp-MRI parameters can best discriminate between malignant and non-malignant regions. To exploit functional information, some parameters are derived from dynamic contrast-enhanced (DCE) acquisitions. In particular, much CAD software employs pharmacokinetic features, such as K trans and k ep, derived from the Tofts model, to estimate a likelihood map of malignancy. However, non-pharmacokinetic models can be also used to describe DCE-MRI curves, without any requirement for prior knowledge or measurement of the arterial input function, which could potentially lead to large errors in parameter estimation. In this work, we implemented an empirical function derived from the phenomenological universalities (PUN) class to fit DCE-MRI. The parameters of the PUN model are used in combination with T2-weighted and diffusion-weighted acquisitions to feed a support vector machine classifier to produce a voxel-wise malignancy likelihood map of the prostate. The results were all compared to those for a CAD system based on Tofts pharmacokinetic features to describe DCE-MRI curves, using different quality aspects of image segmentation, while also evaluating the number and size of false positive (FP) candidate regions. This study included 61 patients with 70 biopsy-proven prostate cancers (PCa). The metrics used to evaluate segmentation quality between the two CAD systems were not statistically different, although the PUN-based CAD reported a lower number of FP, with reduced size compared to the Tofts-based CAD. In conclusion, the CAD software based on PUN parameters is a feasible means with which to
On Parametric (and Non-Parametric Variation
Directory of Open Access Journals (Sweden)
Neil Smith
2009-11-01
Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.
Directory of Open Access Journals (Sweden)
M. Bouhram
2003-08-01
Full Text Available The transport patterns of non-thermal H + and O + field-aligned flows from the dayside cusp/cleft, associated with transverse heating by means of wave-particle interactions and in combination with the poleward motion due to the magnetospheric convection are investigated. This has been accomplished by developing a steady-state, two-dimensional, trajectory-based code. The ion heating is modelled by means of a Monte Carlo technique, via the process of ion cyclotron resonance (ICR, with the electromagnetic left-hand circular polarized component of a broad-band, extremely low-frequency (BBELF turbulence. The altitude dependence of ICR heating from 1000 km to 3 Earth radii (RE is modelled by a power law spectrum, with an index a, and a parameter w0 that is proportional to the spectral density at a referenced gyrofrequency. Because of the finite latitudinal extent of the cusp/cleft, the incorporation of the horizontal convection drift leads to a maximum residence time tD of the ions when being energized. A large set of simulations has been computed so as to study the transport patterns of the H + and O + bulk parameters as a function of tD , a, and w0. Residence time effects are significant in O + density patterns while negligible for H +. When comparing the results with analytical one-dimensional theories (Chang et al., 1986; Crew et al., 1990, we find that mean ion energies and pitch angles at the poleward edge of the heating region are slightly influenced by tD and may be used as a probe of ICR parameters ( a, w0. Conversely, poleward of the heating region, upward velocity and mean energy dispersive patterns depend mainly on tD (e.g. the magnitude of the convection drift with latitudinal profiles varying versus tD . In short, the main conclusion of the paper is that any triplet (tD , a, w0 leads to a unique transport-pattern feature of ion flows associated with a cusp/cleft ionospheric source. In a companion paper, by using high-altitude (1.5–3 RE
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...
Integrable multi parametric SU(N) chain
International Nuclear Information System (INIS)
Foerster, Angela; Roditi, Itzhak; Rodrigues, Ligia M.C.S.
1996-03-01
We analyse integrable models associated to a multi parametric SU(N) R-matrix. We show that the Hamiltonians describe SU(N) chains with twisted boundary conditions and that the underlying algebraic structure is the multi parametric deformation of SU(N) enlarged by the introduction of a central element. (author). 15 refs
Baldewsing, Radj A; Schaar, Johannes A; Mastik, Frits; Oomens, Cees W J; van der Steen, Antonius F W
2005-04-01
Intravascular ultrasound (IVUS) elastography visualizes local radial strain of arteries in so-called elastograms to detect rupture-prone plaques. However, due to the unknown arterial stress distribution these elastograms cannot be directly interpreted as a morphology and material composition image. To overcome this limitation we have developed a method that reconstructs a Young's modulus image from an elastogram. This method is especially suited for thin-cap fibroatheromas (TCFAs), i.e., plaques with a media region containing a lipid pool covered by a cap. Reconstruction is done by a minimization algorithm that matches the strain image output, calculated with a parametric finite element model (PFEM) representation of a TCFA, to an elastogram by iteratively updating the PFEM geometry and material parameters. These geometry parameters delineate the TCFA media, lipid pool and cap regions by circles. The material parameter for each region is a Young's modulus, EM, EL, and EC, respectively. The method was successfully tested on computer-simulated TCFAs (n = 2), one defined by circles, the other by tracing TCFA histology, and additionally on a physical phantom (n = 1) having a stiff wall (measured EM = 16.8 kPa) with an eccentric soft region (measured EL = 4.2 kPa). Finally, it was applied on human coronary plaques in vitro (n = 1) and in vivo (n = 1). The corresponding simulated and measured elastograms of these plaques showed radial strain values from 0% up to 2% at a pressure differential of 20, 20, 1, 20, and 1 mmHg respectively. The used/reconstructed Young's moduli [kPa] were for the circular plaque EL = 50/66, EM = 1500/1484, EC = 2000/2047, for the traced plaque EL = 25/1, EM = 1000/1148, EC = 1500/1491, for the phantom EL = 4.2/4 kPa, EM = 16.8/16, for the in vitro plaque EL = n.a./29, EM = n.a./647, EC = n.a./1784 kPa and for the in vivo plaque EL = n.a./2, EM = n.a./188, Ec = n.a./188 kPa.
Brandt, James M.
1999-01-01
Approved for public release; distribution is unlimited With few effective decision-making tools to assess the affordability of major weapon systems, management of total ownership costs is continually misunderstood. Cost analysis provides a quick and reliable assessment of affordability. Because there is no standardized method for calculating reliable estimates of operating and support (O&S) costs (the principal component of total ownership cost), this thesis formulates a parametric cost mo...
Energy Technology Data Exchange (ETDEWEB)
Baudet, V
2006-06-15
Ionising treatment against cancers such as conformal radiotherapy and hadron therapy are set with error margins that take into account statistics of tumour motions, for instance. We are looking for reducing these margins by searching deformable models that would simulate displacements occurring in lungs during a treatment. It must be personalized with the geometry obtained from CT scans of the patient and also it must be parameterized with physiological measures of the patient. In this Ph. D. thesis, we decided to use a mass-spring system to model lungs because of its fast and physically realist deformations obtained in animation. As a starting point, we chose the model proposed by Van Gelder in order to parameterize a mass-spring system with rheological characteristics of an homogeneous, linear elastic isotropic material in two dimensions (2D). However, we tested this model and proved it was false. Hence we did a Lagrangian study in order to obtain a parametric model with rectangular in 2D (cubic in 3D) elements. We also determined the robustness by testing with stretching, inflating, shearing and bending experiments and also by comparing results with other infinite element method. Thus, in this Ph.D. thesis, we explain how to obtain this parametric model, and how it will be linked to physiological data and how accurate it will be. (author)
Parametric Optimization of Hospital Design
DEFF Research Database (Denmark)
Holst, Malene Kirstine; Kirkegaard, Poul Henning; Christoffersen, L.D.
2013-01-01
Present paper presents a parametric performancebased design model for optimizing hospital design. The design model operates with geometric input parameters defining the functional requirements of the hospital and input parameters in terms of performance objectives defining the design requirements...... and preferences of the hospital with respect to performances. The design model takes point of departure in the hospital functionalities as a set of defined parameters and rules describing the design requirements and preferences....
Directory of Open Access Journals (Sweden)
M. Bouhram
Full Text Available The transport patterns of non-thermal H + and O + field-aligned flows from the dayside cusp/cleft, associated with transverse heating by means of wave-particle interactions and in combination with the poleward motion due to the magnetospheric convection are investigated. This has been accomplished by developing a steady-state, two-dimensional, trajectory-based code. The ion heating is modelled by means of a Monte Carlo technique, via the process of ion cyclotron resonance (ICR, with the electromagnetic left-hand circular polarized component of a broad-band, extremely low-frequency (BBELF turbulence. The altitude dependence of ICR heating from 1000 km to 3 Earth radii (R_{E} is modelled by a power law spectrum, with an index a, and a parameter w_{0} that is proportional to the spectral density at a referenced gyrofrequency. Because of the finite latitudinal extent of the cusp/cleft, the incorporation of the horizontal convection drift leads to a maximum residence time t_{D} of the ions when being energized. A large set of simulations has been computed so as to study the transport patterns of the H + and O + bulk parameters as a function of t_{D} , a, and w_{0}. Residence time effects are significant in O + density patterns while negligible for H +. When comparing the results with analytical one-dimensional theories (Chang et al., 1986; Crew et al., 1990, we find that mean ion energies and pitch angles at the poleward edge of the heating region are slightly influenced by t_{D} and may be used as a probe of ICR parameters ( a, w_{0}. Conversely, poleward of the heating region, upward velocity and mean energy dispersive patterns depend mainly on t_{D} (e.g. the magnitude of the convection drift with latitudinal profiles varying versus
DEFF Research Database (Denmark)
Creixell Mediante, Ester; Jensen, Jakob Søndergaard; Naets, Frank
2018-01-01
Finite Element (FE) models of complex structural-acoustic coupled systems can require a large number of degrees of freedom in order to capture their physical behaviour. This is the case in the hearing aid field, where acoustic-mechanical feedback paths are a key factor in the overall system...... by projecting the full system into a reduced space. A drawback of most of the existing techniques is that the vector basis of the reduced space is built at an offline phase where the full system must be solved for a large sample of parameter values, which can also become highly time consuming. In this work, we...
Energy Technology Data Exchange (ETDEWEB)
Raynal, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires
1964-06-15
A general description of beams of polarized particles in nuclear reactions is studied; the various choices necessary to define the polarization parameters are discussed with regard to their consequences. The frequent occurrence of symmetry plane yields a set of relations among these parameters. The range of these parameters is studied in particular for a beam of particles of spin 1 and with a symmetry plane. Nuclear reactions involving two bodies are described in terms of the helicity formalism. With the use of the adopted set of polarization parameters, the polarization of the final state is studied for a given polarization in the initial state. An optical model for deuterons may consist of a scalar term, an L.S potential and tensor potentials built with the distance between the deuteron and the nucleus, its angular momentum or its relative momentum. Calculations have been made with the first two tensor potentials. Many authors have calculated a potential for deuterons starting from the nucleon-nucleus potential. These calculations are redone taking into account both the S and D waves of the deuteron. The various terms of the potential have been calculated with a set of different intrinsic wave functions. The use of a potential not limited to scalar form yields good fits for cross-sections with nuclear radii which are greater than those necessary with a purely central potential. The experimental results obtained at Saclay for the polarization of deuterons elastically scattered by Ca are not compatible with the existence of an important tensor potential; they can be accounted for by an L.S coupling potential independent of the central potential but with very small radii. (author) [French] La description de faisceaux do particules polarisees dans les reactions nucleaires est etudiee de facon generale; les choix necessaires pour definir les parametres de polarisation sont discutes en fonction de leurs consequences. L'existence tres frequente d'un plan de symetrie
Bedogni, Roberto; Pelliccioni, Maurizio; Esposito, Adolfo
2010-03-01
Due to the increased interest of the scientific community in the applications of synchrotron light, there is an increasing demand of high-energy electron facilities, testified by the construction of several new facilities worldwide. The radiation protection around such facilities requires accurate experimental methods to determine the dose due to prompt radiation fields. Neutron fields, in particular, are the most complex to measure, because they extend in energy from thermal (10 -8 MeV) up to hundreds MeV and because the responses of dosemeters and survey meters usually have large energy dependence. The Bonner Spheres Spectrometer (BSS) is in practice the only instrument able to respond over the whole energy range of interest, and for this reason it is frequently used to derive neutron spectra and dosimetric quantities in accelerator workplaces. Nevertheless, complex unfolding algorithms are needed to derive the neutron spectra from the experimental BSS data. This paper presents a parametric model specially developed for the unfolding of the experimental data measured with BSS around high-energy electron accelerators. The work consists of the following stages: (1) Generation with the FLUKA code, of a set of neutron spectra representing the radiation environment around accelerators with different electron energies; (2) formulation of a parametric model able to describe these spectra, with particular attention to the high-energy component (>10 MeV), which may be responsible for a large part of the dose in workplaces; and (3) implementation of this model in an existing unfolding code.
International Nuclear Information System (INIS)
Bedogni, Roberto; Pelliccioni, Maurizio; Esposito, Adolfo
2010-01-01
Due to the increased interest of the scientific community in the applications of synchrotron light, there is an increasing demand of high-energy electron facilities, testified by the construction of several new facilities worldwide. The radiation protection around such facilities requires accurate experimental methods to determine the dose due to prompt radiation fields. Neutron fields, in particular, are the most complex to measure, because they extend in energy from thermal (10 -8 MeV) up to hundreds MeV and because the responses of dosemeters and survey meters usually have large energy dependence. The Bonner Spheres Spectrometer (BSS) is in practice the only instrument able to respond over the whole energy range of interest, and for this reason it is frequently used to derive neutron spectra and dosimetric quantities in accelerator workplaces. Nevertheless, complex unfolding algorithms are needed to derive the neutron spectra from the experimental BSS data. This paper presents a parametric model specially developed for the unfolding of the experimental data measured with BSS around high-energy electron accelerators. The work consists of the following stages: (1) Generation with the FLUKA code, of a set of neutron spectra representing the radiation environment around accelerators with different electron energies; (2) formulation of a parametric model able to describe these spectra, with particular attention to the high-energy component (>10 MeV), which may be responsible for a large part of the dose in workplaces; and (3) implementation of this model in an existing unfolding code.
Functional summary statistics for the Johnson-Mehl model
DEFF Research Database (Denmark)
Møller, Jesper; Ghorbani, Mohammad
The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....
International Nuclear Information System (INIS)
Wagner, J.; Ramakrishnan, A.; Obloh, H.; Kunzer, M.; Koehler, K.; Johs, B.
2000-01-01
Spectroscopic ellipsometry (SE) has been used for the characterization of AlGaN/GaN and InGaN/GaN heterostructures. The resulting pseudodielectric function spectra were analyzed using a multilayer approach, describing the dielectric functions of the individual layers by a parametric oscillator model. From this analysis, the dielectric function spectra of GaN, Al x Ga 1-x N (x le 0.16), and In 0.13 Ga 0.87 N were deduced. Further, the dependence of the Al x Ga 1-x N band gap energy on the Al mole fraction was derived and compared with photoluminescence data recorded on the same material. The SE band gap data are compatible with a bowing parameter close to 1 eV for the composition dependence of the Al x Ga 1-x N gap energy. Finally, the parametric dielectric functions have been used to model the pseudodielectric function spectrum of a complete GaN/AlGaN/InGaN LED structure
Motivations of parametric studies
International Nuclear Information System (INIS)
Birac, C.
1988-01-01
The paper concerns the motivations of parametric studies in connection with the Programme for the Inspection of Steel Components PISC II. The objective of the PISC II exercise is to evaluate the effectiveness of current and advanced NDT techniques for inspection of reactor pressure vessel components. The parametric studies were initiated to determine the influence of some parameters on defect detection and dimensioning, and to increase the technical bases of the Round Robin Tests. A description is given of the content of the parametric studies including:- the effect of the defects' characteristics, the effect of equipment characteristics, the effect of cladding, and possible use of electromagnetic techniques. (U.K.)
Assessing pupil and school performance by non-parametric and parametric techniques
de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.
2010-01-01
This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall
International Nuclear Information System (INIS)
Yoo, S. H.; Kim, M. W.; Kang, S. C.; Kim, H. J.; Min, B. J.; Yoon, C.
2002-01-01
Three-dimensional analyses of fluid flow and heat transfer have been performed to assess thermal-hydraulic characteristics for moderator simulation conducted by SPEL(Sheridan Park Experimental Laboratory) experimental facility. The parametric study has also carried out to investigate the effect of major parameters such as flowrate, temperature, and heat load generated from the heaters on the temperature and flow distribution inside the moderator. In this study, three flow patterns have been identified in the moderator with flowrate, heat generation, or both. As the transition of fluid flow is progressed, it is found that the dimensionless numbers (Ar) and the ratio of buoyancy to inertia forces are constant. Moreover, the behavior of temperature distribution inside calandria has also been investigated, when the flowrate of moderator is changed with time