Parametric Modeling of Electron Beam Loss in Synchrotron Light Sources
Sayyar-Rodsari, B.; Schweiger, C.; Hartman, E.; Corbett, J.; Lee, M.; Lui, P.; Paterson, E.; /SLAC
2007-11-28
Synchrotron light is used for a wide variety of scientific disciplines ranging from physical chemistry to molecular biology and industrial applications. As the electron beam circulates, random single-particle collisional processes lead to decay of the beam current in time. We report a simulation study in which a combined neural network (NN) and first-principles (FP) model is used to capture the decay in beam current due to Touschek, Bremsstrahlung, and Coulomb effects. The FP block in the combined model is a parametric description of the beam current decay where model parameters vary as a function of beam operating conditions (e.g. vertical scraper position, RF voltage, number of the bunches, and total beam current). The NN block provides the parameters of the FP model and is trained (through constrained nonlinear optimization) to capture the variation in model parameters as operating condition of the beam changes. Simulation results will be presented to demonstrate that the proposed combined framework accurately models beam decay as well as variation to model parameters without direct access to parameter values in the model.
Parametric Explosion Spectral Model
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.
Modeling and optimization of photon pair sources based on spontaneous parametric down-conversion
Kolenderski, Piotr; Banaszek, Konrad; Wasilewski, Wojciech
2009-07-15
We address the problem of efficient modeling of photon pairs generated in spontaneous parametric down-conversion and coupled into single-mode fibers. It is shown that when the range of relevant transverse wave vectors is restricted by the pump and fiber modes, the computational complexity can be reduced substantially with the help of the paraxial approximation, while retaining the full spectral characteristics of the source. This approach can serve as a basis for efficient numerical calculations or can be combined with analytically tractable approximations of the phase-matching function. We introduce here a cosine-Gaussian approximation of the phase-matching function that works for a broader range of parameters than the Gaussian model used previously. The developed modeling tools are used to evaluate characteristics of the photon pair sources such as the pair production rate and the spectral purity quantifying frequency correlations. Strategies to generate spectrally uncorrelated photons, necessary in multiphoton interference experiments, are analyzed with respect to trade-offs between parameters of the source.
Model and parametric uncertainty in source-based kinematic models of earthquake ground motion
Hartzell, Stephen; Frankel, Arthur; Liu, Pengcheng; Zeng, Yuehua; Rahman, Shariftur
2011-01-01
Four independent ground-motion simulation codes are used to model the strong ground motion for three earthquakes: 1994 Mw 6.7 Northridge, 1989 Mw 6.9 Loma Prieta, and 1999 Mw 7.5 Izmit. These 12 sets of synthetics are used to make estimates of the variability in ground-motion predictions. In addition, ground-motion predictions over a grid of sites are used to estimate parametric uncertainty for changes in rupture velocity. We find that the combined model uncertainty and random variability of the simulations is in the same range as the variability of regional empirical ground-motion data sets. The majority of the standard deviations lie between 0.5 and 0.7 natural-log units for response spectra and 0.5 and 0.8 for Fourier spectra. The estimate of model epistemic uncertainty, based on the different model predictions, lies between 0.2 and 0.4, which is about one-half of the estimates for the standard deviation of the combined model uncertainty and random variability. Parametric uncertainty, based on variation of just the average rupture velocity, is shown to be consistent in amplitude with previous estimates, showing percentage changes in ground motion from 50% to 300% when rupture velocity changes from 2.5 to 2.9 km/s. In addition, there is some evidence that mean biases can be reduced by averaging ground-motion estimates from different methods.
Wey, Andrew; Connett, John; Rudser, Kyle
2015-07-01
For estimating conditional survival functions, non-parametric estimators can be preferred to parametric and semi-parametric estimators due to relaxed assumptions that enable robust estimation. Yet, even when misspecified, parametric and semi-parametric estimators can possess better operating characteristics in small sample sizes due to smaller variance than non-parametric estimators. Fundamentally, this is a bias-variance trade-off situation in that the sample size is not large enough to take advantage of the low bias of non-parametric estimation. Stacked survival models estimate an optimally weighted combination of models that can span parametric, semi-parametric, and non-parametric models by minimizing prediction error. An extensive simulation study demonstrates that stacked survival models consistently perform well across a wide range of scenarios by adaptively balancing the strengths and weaknesses of individual candidate survival models. In addition, stacked survival models perform as well as or better than the model selected through cross-validation. Finally, stacked survival models are applied to a well-known German breast cancer study.
Parametric Modeling for Fluid Systems
NASA Technical Reports Server (NTRS)
Pizarro, Yaritzmar Rosario; Martinez, Jonathan
2013-01-01
Fluid Systems involves different projects that require parametric modeling, which is a model that maintains consistent relationships between elements as is manipulated. One of these projects is the Neo Liquid Propellant Testbed, which is part of Rocket U. As part of Rocket U (Rocket University), engineers at NASA's Kennedy Space Center in Florida have the opportunity to develop critical flight skills as they design, build and launch high-powered rockets. To build the Neo testbed; hardware from the Space Shuttle Program was repurposed. Modeling for Neo, included: fittings, valves, frames and tubing, between others. These models help in the review process, to make sure regulations are being followed. Another fluid systems project that required modeling is Plant Habitat's TCUI test project. Plant Habitat is a plan to develop a large growth chamber to learn the effects of long-duration microgravity exposure to plants in space. Work for this project included the design and modeling of a duct vent for flow test. Parametric Modeling for these projects was done using Creo Parametric 2.0.
Parametric Model Checking with VerICS
NASA Astrophysics Data System (ADS)
Knapik, Michał; Niewiadomski, Artur; Penczek, Wojciech; Półrola, Agata; Szreter, Maciej; Zbrzezny, Andrzej
The paper presents the verification system verICS, extended with the three new modules aimed at parametric verification of Elementary Net Systems, Distributed Time Petri Nets, and a subset of UML. All the modules exploit Bounded Model Checking for verifying parametric reachability and the properties specified in the logic PRTECTL - the parametric extension of the existential fragment of CTL.
Towards an Empirically Based Parametric Explosion Spectral Model
Ford, S R; Walter, W R; Ruppert, S; Matzel, E; Hauk, T; Gok, R
2009-08-31
Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before been tested. The focus of our work is on the local and regional distances (< 2000 km) and phases (Pn, Pg, Sn, Lg) necessary to see small explosions. We are developing a parametric model of the nuclear explosion seismic source spectrum that is compatible with the earthquake-based geometrical spreading and attenuation models developed using the Magnitude Distance Amplitude Correction (MDAC) techniques (Walter and Taylor, 2002). The explosion parametric model will be particularly important in regions without any prior explosion data for calibration. The model is being developed using the available body of seismic data at local and regional distances for past nuclear explosions at foreign and domestic test sites. Parametric modeling is a simple and practical approach for widespread monitoring applications, prior to the capability to carry out fully deterministic modeling. The achievable goal of our parametric model development is to be able to predict 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. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.
Modeling personnel turnover in the parametric organization
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1991-01-01
A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.
Parametric modelling of a knee joint prosthesis.
Khoo, L P; Goh, J C; Chow, S L
1993-01-01
This paper presents an approach for the establishment of a parametric model of knee joint prosthesis. Four different sizes of a commercial prosthesis are used as an example in the study. A reverse engineering technique was employed to reconstruct the prosthesis on CATIA, a CAD (computer aided design) system. Parametric models were established as a result of the analysis. Using the parametric model established and the knee data obtained from a clinical study on 21 pairs of cadaveric Asian knees, the development of a prototype prosthesis that suits a patient with a very small knee joint is presented. However, it was found that modification to certain parameters may be inevitable due to the uniqueness of the Asian knee. An avenue for rapid modelling and eventually economical production of a customized knee joint prosthesis for patients is proposed and discussed.
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.
THz-wave parametric sources and imaging applications
NASA Astrophysics Data System (ADS)
Kawase, Kodo
2004-12-01
We have studied the generation of terahertz (THz) waves by optical parametric processes based on laser light scattering from the polariton mode of nonlinear crystals. Using parametric oscillation of MgO-doped LiNbO3 crystal pumped by a nano-second Q-switched Nd:YAG laser, we have realized a widely tunable coherent THz-wave sources with a simple configuration. We have also developed a novel basic technology for THz imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral trasillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.
Parametric identification of human operator models
NASA Technical Reports Server (NTRS)
Ninz, N. R.
1982-01-01
The accurate and efficient identification of the human operator is still a need in human factors engineering especially concerning multivariable control. Control theoretic identification methods need to be tested with human operator models under realistic boundary conditons. The requirements and criteria for the use of parametric methods, selected models as well as the Maximum Likelihood Method and the Extended Kalman Filter are displayed. The experiments and results are comparatively discussed from the point of practical engineering.
Parametric Cost Models for Space Telescopes
NASA Technical Reports Server (NTRS)
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.
Hyperbolic and semi-parametric models in finance
NASA Astrophysics Data System (ADS)
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.
Degeneracies in parametrized modified gravity models
Hojjati, Alireza
2013-01-01
We study degeneracies between parameters in some of the widely used parametrized modified gravity models. We investigate how different observables from a future photometric weak lensing survey such as LSST, correlate the effects of these parameters and to what extent the degeneracies are broken. We also study the impact of other degenerate effects, namely massive neutrinos and some of the weak lensing systematics, on the correlations.
Semi-Parametric Generalized Linear Models.
1985-08-01
is nonsingular, upper triangular, and of full rank r. It is known (Dongarra et al., 1979) that G-1 FT is the Moore - Penrose inverse of L . Therefore... GENERALIZED LINEAR pq Mathematics Research Center University of Wisconsin-Madison 610 Walnut Street Madison, Wisconsin 53705 TI C August 1985 E T NOV 7 8...North Carolina 27709 -. -.. . - -.-. g / 6 O5’o UNIVERSITY OF WISCONSIN-MADISON MATHD4ATICS RESEARCH CENTER SD4I-PARAMETRIC GENERALIZED LINEAR MODELS
Ground-Based Telescope Parametric Cost Model
NASA Technical Reports Server (NTRS)
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.
Parametric Model of an Aerospike Rocket Engine
NASA Technical Reports Server (NTRS)
Korte, J. J.
2000-01-01
A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHTI multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.
Parametric Model of an Aerospike Rocket Engine
NASA Technical Reports Server (NTRS)
Korte, J. J.
2000-01-01
A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHT multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.
Acoustic intensity in the interaction region of a parametric source
NASA Astrophysics Data System (ADS)
Lauchle, G. C.; Gabrielson, T. B.; van Tol, D. J.; Kottke, N. F.; McConnell, J. A.
2003-10-01
The goal of this project was to measure acoustic intensity in the strong interaction region of a parametric source in order to obtain a clear definition of the source-generation region and to separate the local generation (the reactive field) from propagation (the real or active field). The acoustic intensity vector was mapped in the interaction region of a parametric projector at Lake Seneca. The source was driven with primary signals at 22 kHz and 27 kHz. Receiving sensors were located 8.5 meters from the projector. At that range, the secondary at 5 kHz was between 40 and 45 dB below either primary. For the primary levels used, the plane-wave shock inception distance would have been at least 14 meters. Furthermore, the Rayleigh distance for the projector was about 4 meters so the measurements at 8.5 meters were in the strong interaction region but not in saturation. Absorption was negligible over these ranges. The intensity measurements were made at fixed range but varying azimuth angle and varying depth thus developing a two-dimensional cross-section of the secondary beam. Measurements of both the active and reactive intensity vectors will be presented along with a discussion of measurement error. [Work supported by ONR Code 321SS.
Modeling Personnel Turnover in the Parametric Organization
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1991-01-01
A primary issue in organizing a new parametric cost analysis function is to determine the skill mix and number of personnel required. The skill mix can be obtained by a functional decomposition of the tasks required within the organization and a matrixed correlation with educational or experience backgrounds. The number of personnel is a function of the skills required to cover all tasks, personnel skill background and cross training, the intensity of the workload for each task, migration through various tasks by personnel along a career path, personnel hiring limitations imposed by management and the applicant marketplace, personnel training limitations imposed by management and personnel capability, and the rate at which personnel leave the organization for whatever reason. Faced with the task of relating all of these organizational facets in order to grow a parametric cost analysis (PCA) organization from scratch, it was decided that a dynamic model was required in order to account for the obvious dynamics of the forming organization. The challenge was to create such a simple model which would be credible during all phases of organizational development. The model development process was broken down into the activities of determining the tasks required for PCA, determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the dynamic model, implementing the dynamic model, and testing the dynamic model.
Mathematically trivial control of sound using a parametric beam focusing source.
Tanaka, Nobuo; Tanaka, Motoki
2011-01-01
By exploiting a case regarded as trivial, this paper presents global active noise control using a parametric beam focusing source (PBFS). As with a dipole model, one is used for a primary sound source and the other for a control sound source, the control effect for minimizing a total acoustic power depends on the distance between the two. When the distance becomes zero, the total acoustic power becomes null, hence nothing less than a trivial case. Because of the constraints in practice, there exist difficulties in placing a control source close enough to a primary source. However, by projecting a sound beam of a parametric array loudspeaker onto the target sound source (primary source), a virtual sound source may be created on the target sound source, thereby enabling the collocation of the sources. In order to further ensure feasibility of the trivial case, a PBFS is then introduced in an effort to meet the size of the two sources. Reflected sound wave of the PBFS, which is tantamount to the virtual sound source output, aims to suppress the primary sound. Finally, a numerical analysis as well as an experiment is conducted, verifying the validity of the proposed methodology.
Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models
ERIC Educational Resources Information Center
Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum
2011-01-01
Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…
Approximately Integrable Linear Statistical Models in Non-Parametric Estimation
1990-08-01
OTIC I EL COPY Lfl 0n Cf) NAPPROXIMATELY INTEGRABLE LINEAR STATISTICAL MODELS IN NON- PARAMETRIC ESTIMATION by B. Ya. Levit University of Maryland...Integrable Linear Statistical Models in Non- Parametric Estimation B. Ya. Levit Sumnmary / The notion of approximately integrable linear statistical models...models related to the study of the "next" order optimality in non- parametric estimation . It appears consistent to keep the exposition at present at the
Parametric modeling of quantile regression coefficient functions.
Frumento, Paolo; Bottai, Matteo
2016-03-01
Estimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile regression model depend on the order of the quantile being estimated. For example, the coefficients for the median are generally different from those of the 10th centile. In this article, we describe an approach to modeling the regression coefficients as parametric functions of the order of the quantile. This approach may have advantages in terms of parsimony, efficiency, and may expand the potential of statistical modeling. Goodness-of-fit measures and testing procedures are discussed, and the results of a simulation study are presented. We apply the method to analyze the data that motivated this work. The described method is implemented in the qrcm R package.
uvmcmcfit: Parametric models to interferometric data fitter
NASA Astrophysics Data System (ADS)
Bussmann, Shane; Leung, Tsz Kuk (Daisy); Conley, Alexander
2016-06-01
Uvmcmcfit fits parametric models to interferometric data. It is ideally suited to extract the maximum amount of information from marginally resolved observations with interferometers like the Atacama Large Millimeter Array (ALMA), Submillimeter Array (SMA), and Plateau de Bure Interferometer (PdBI). uvmcmcfit uses emcee (ascl:1303.002) to do Markov Chain Monte Carlo (MCMC) and can measure the goodness of fit from visibilities rather than deconvolved images, an advantage when there is strong gravitational lensing and in other situations. uvmcmcfit includes a pure-Python adaptation of Miriad’s (ascl:1106.007) uvmodel task to generate simulated visibilities given observed visibilities and a model image and a simple ray-tracing routine that allows it to account for both strongly lensed systems (where multiple images of the lensed galaxy are detected) and weakly lensed systems (where only a single image of the lensed galaxy is detected).
Assessing the fit of parametric cure models.
Wileyto, E Paul; Li, Yimei; Chen, Jinbo; Heitjan, Daniel F
2013-04-01
Survival data can contain an unknown fraction of subjects who are "cured" in the sense of not being at risk of failure. We describe such data with cure-mixture models, which separately model cure status and the hazard of failure among non-cured subjects. No diagnostic currently exists for evaluating the fit of such models; the popular Schoenfeld residual (Schoenfeld, 1982. Partial residuals for the proportional hazards regression-model. Biometrika 69, 239-241) is not applicable to data with cures. In this article, we propose a pseudo-residual, modeled on Schoenfeld's, to assess the fit of the survival regression in the non-cured fraction. Unlike Schoenfeld's approach, which tests the validity of the proportional hazards (PH) assumption, our method uses the full hazard and is thus also applicable to non-PH models. We derive the asymptotic distribution of the residuals and evaluate their performance by simulation in a range of parametric models. We apply our approach to data from a smoking cessation drug trial.
Parametric System Model for a Stirling Radioisotope Generator
NASA Technical Reports Server (NTRS)
Schmitz, Paul C.
2014-01-01
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 Stirling Radioisotope Generator (SRG). Using the General Purpose Heat Source (GPHS approximately 250 watt thermal) modules as the thermal building block around 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.
Parametric System Model for a Stirling Radioisotope Generator
NASA Technical Reports Server (NTRS)
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.
Energy scaling of terahertz-wave parametric sources.
Tang, Guanqi; Cong, Zhenhua; Qin, Zengguang; Zhang, Xingyu; Wang, Weitao; Wu, Dong; Li, Ning; Fu, Qiang; Lu, Qingming; Zhang, Shaojun
2015-02-23
Terahertz-wave parametric oscillators (TPOs) have advantages of room temperature operation, wide tunable range, narrow line-width, good coherence. They have also disadvantage of small pulse energy. In this paper, several factors preventing TPOs from generating high-energy THz pulses and the corresponding solutions are analyzed. A scheme to generate high-energy THz pulses by using the combination of a TPO and a Stokes-pulse-injected terahertz-wave parametric generator (spi-TPG) is proposed and demonstrated. A TPO is used as a source to generate a seed pulse for the surface-emitted spi-TPG. The time delay between the pump and Stokes pulses is adjusted to guarantee they have good temporal overlap. The pump pulses have a large pulse energy and a large beam size. The Stokes beam is enlarged to make its size be larger than the pump beam size to have a large effective interaction volume. The experimental results show that the generated THz pulse energy from the spi-TPG is 1.8 times as large as that obtained from the TPO for the same pumping pulse energy density of 0.90 J/cm(2) and the same pumping beam size of 3.0 mm. When the pumping beam sizes are 5.0 and 7.0 mm, the enhancement times are 3.7 and 7.5, respectively. The spi-TPG here is similar to a difference frequency generator; it can also be used as a Stokes pulse amplifier.
Toward an Empirically-based Parametric Explosion Spectral Model
NASA Astrophysics Data System (ADS)
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.
Using a Parametric Solid Modeler as an Instructional Tool
ERIC Educational Resources Information Center
Devine, Kevin L.
2008-01-01
This paper presents the results of a quasi-experimental study that brought 3D constraint-based parametric solid modeling technology into the high school mathematics classroom. This study used two intact groups; a control group and an experimental group, to measure the extent to which using a parametric solid modeler during instruction affects…
Parametric Wave Transformation Models on Natural Beaches
NASA Astrophysics Data System (ADS)
Apotsos, A. A.; Raubenheimer, B.; Elgar, S.; Guza, R. T.
2006-12-01
Seven parametric models for wave height transformation across the surf zone [e.g., Thornton and Guza, 1983] are tested with observations collected between the shoreline and about 5-m water depth during 2 experiments on a barred beach near Duck, NC, and between the shoreline and about 3.5-m water depth during 2 experiments on unbarred beaches near La Jolla, CA. Offshore wave heights ranged from about 0.1 to 3.0 m. Beach profiles were surveyed approximately every other day. The models predict the observations well. Root-mean-square errors between observed and simulated wave heights are small in water depths h > 2 m (average rms errors < 10%), and increase with decreasing depth for h < 2 m (average rms errors > 20%). The lowest rms errors (i.e., the most accurate predictions) are achieved by tuning a free parameter, γ, in each model. To tune the models accurately to the data considered here, observations are required at 3 to 5 locations, and must span the surf zone. No tuned or untuned model provides the best predictions for all data records in any one experiment. The best fit γ's for each model-experiment pair are represented well with an empirical hyperbolic tangent curve based on the inverse Iribarren number. In 3 of the 4 data sets, estimating γ for each model using an average curve based on the predictions and observations from all 4 experiments typically improves model-data agreement relative to using a constant or previously determined empirical γ. The best fit γ's at the 4th experiment (conducted off La Jolla, CA) are roughly 20% smaller than the γ's for the other 3 experiments, and thus using the experiment-averaged curve increases prediction errors. Possible causes for the smaller γ's at the 4th experiment will be discussed. Funded by ONR and NSF.
Forecasting Marine Corps Enlisted Attrition Through Parametric Modeling
2009-03-01
OF PAGES 85 14. SUBJECT TERMS Forecasting, Attrition, Marine Corps NEAS losses, Gompertz Model, Survival Analysis 16. PRICE CODE 17. SECURITY...18 1. Parametric Proportional Hazards Models ......................................18 2. Gompertz Models...19 a. Gompertz Hazard Function....................................................19 b. Gompertz Cumulative
Parametric Testing of Launch Vehicle FDDR Models
NASA Technical Reports Server (NTRS)
Schumann, Johann; Bajwa, Anupa; Berg, Peter; Thirumalainambi, Rajkumar
2011-01-01
For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.
Mixing parametrizations for ocean climate modelling
NASA Astrophysics Data System (ADS)
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
Penalized Likelihood for General Semi-Parametric Regression Models.
1985-05-01
should be stressed that q, while it may be somewhat less than n, will still be ’large’, and parametric estimation of £ will not be appropriate...Partial spline models for the semi- parametric estimation of functions of several variables, in Statistical Analysis of Time Series, Tokyo: Institute of
Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1998-01-01
A global nonlinear parametric modeling technique is described and demonstrated. The technique uses multivariate orthogonal modeling functions generated from the data to determine nonlinear model structure, then expands each retained modeling function into an ordinary multivariate polynomial. The final model form is a finite multivariate power series expansion for the dependent variable in terms of the independent variables. Partial derivatives of the identified models can be used to assemble globally valid linear parameter varying models. The technique is demonstrated by identifying global nonlinear parametric models for nondimensional aerodynamic force and moment coefficients from a subsonic wind tunnel database for the F-16 fighter aircraft. Results show less than 10% difference between wind tunnel aerodynamic data and the nonlinear parameterized model for a simulated doublet maneuver at moderate angle of attack. Analysis indicated that the global nonlinear parametric models adequately captured the multivariate nonlinear aerodynamic functional dependence.
Validation of a Parametric Approach for 3d Fortification Modelling: Application to Scale Models
NASA Astrophysics Data System (ADS)
Jacquot, K.; Chevrier, C.; Halin, G.
2013-02-01
Parametric modelling approach applied to cultural heritage virtual representation is a field of research explored for years since it can address many limitations of digitising tools. For example, essential historical sources for fortification virtual reconstructions like plans-reliefs have several shortcomings when they are scanned. To overcome those problems, knowledge based-modelling can be used: knowledge models based on the analysis of theoretical literature of a specific domain such as bastioned fortification treatises can be the cornerstone of the creation of a parametric library of fortification components. Implemented in Grasshopper, these components are manually adjusted on the data available (i.e. 3D surveys of plans-reliefs or scanned maps). Most of the fortification area is now modelled and the question of accuracy assessment is raised. A specific method is used to evaluate the accuracy of the parametric components. The results of the assessment process will allow us to validate the parametric approach. The automation of the adjustment process can finally be planned. The virtual model of fortification is part of a larger project aimed at valorising and diffusing a very unique cultural heritage item: the collection of plans-reliefs. As such, knowledge models are precious assets when automation and semantic enhancements will be considered.
Semi-parametric estimation in failure time mixture models.
Taylor, J M
1995-09-01
A mixture model is an attractive approach for analyzing failure time data in which there are thought to be two groups of subjects, those who could eventually develop the endpoint and those who could not develop the endpoint. The proposed model is a semi-parametric generalization of the mixture model of Farewell (1982). A logistic regression model is proposed for the incidence part of the model, and a Kaplan-Meier type approach is used to estimate the latency part of the model. The estimator arises naturally out of the EM algorithm approach for fitting failure time mixture models as described by Larson and Dinse (1985). The procedure is applied to some experimental data from radiation biology and is evaluated in a Monte Carlo simulation study. The simulation study suggests the semi-parametric procedure is almost as efficient as the correct fully parametric procedure for estimating the regression coefficient in the incidence, but less efficient for estimating the latency distribution.
THz-wave parametric source and its imaging applications
NASA Astrophysics Data System (ADS)
Kawase, Kodo
2004-08-01
Widely tunable coherent terahertz (THz) wave generation has been demonstrated based on the parametric oscillation using MgO doped LiNbO3 crystal pumped by a Q-switched Nd:YAG laser. This method exhibits multiple advantages like wide tunability, coherency and compactness of its system. We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes. The samples we used were methamphetamine and MDMA, two of the most widely consumed illegal drugs in Japan, and aspirin as a reference.
Broadband picosecond radiation source based on noncollinear optical parametric amplifier
Arakcheev, V G; Morozov, V B; Vereshchagin, A K; Vereshchagin, K A; Tunkin, V G; Yakovlev, D V
2014-04-28
Amplification of broadband radiation of modeless dye laser by a noncollinear optical parametric amplifier based on a KTP crystal has been implemented upon pumping by 63-ps second-harmonic pulses of a Nd : YAG laser. Pulses with a bandwidth of 21 nm, a duration of 26 ps and an energy of 1.2 mJ have been obtained at the centre wavelength of 685 nm. (nonlinear optical phenomena)
The parametrization of radio source coordinates in VLBI and its impact on the CRF
NASA Astrophysics Data System (ADS)
Karbon, Maria; Heinkelmann, Robert; Mora-Diaz, Julian; Xu, Minghui; Nilsson, Tobias; Schuh, Harald
2016-04-01
dramatically in time. Hence, each source would have to be modeled individually. Considering this, the shear amount of sources, in our study more than 600 are included, sets practical limitations. We decided to use the multivariate adaptive regression splines (MARS) procedure to parametrize the source coordinates, as they allow a great deal of automation as it combines recursive partitioning and spline fitting in an optimal way. The algorithm finds the ideal knot positions for the splines and thus the best number of polynomial pieces to fit the data. We investigate linear and cubic splines determined by MARS to "human" determined linear splines and their impact on the CRF. Within this work we try to answer the following questions: How can we find optimal criteria for the definition of the defining and unstable sources? What are the best polynomials for the individual categories? How much can we improve the CRF by extending the parametrization of the sources?
Homaeinezhad, M R; Sabetian, P; Feizollahi, A; Ghaffari, A; Rahmani, R
2012-02-01
The major focus of this study is to present a performance accuracy assessment framework based on mathematical modelling of cardiac system multiple measurement signals. Three mathematical algebraic subroutines with simple structural functions for synthetic generation of the synchronously triggered electrocardiogram (ECG), phonocardiogram (PCG) and arterial blood pressure (ABP) signals are described. In the case of ECG signals, normal and abnormal PQRST cycles in complicated conditions such as fascicular ventricular tachycardia, rate dependent conduction block and acute Q-wave infarctions of inferior and anterolateral walls can be simulated. Also, continuous ABP waveform with corresponding individual events such as systolic, diastolic and dicrotic pressures with normal or abnormal morphologies can be generated by another part of the model. In addition, the mathematical synthetic PCG framework is able to generate the S4-S1-S2-S3 cycles in normal and in cardiac disorder conditions such as stenosis, insufficiency, regurgitation and gallop. In the PCG model, the amplitude and frequency content (5-700 Hz) of each sound and variation patterns can be specified. The three proposed models were implemented to generate artificial signals with varies abnormality types and signal-to-noise ratios (SNR), for quantitative detection-delineation performance assessment of several ECG, PCG and ABP individual event detectors designed based on the Hilbert transform, discrete wavelet transform, geometric features such as area curve length (ACLM), the multiple higher order moments (MHOM) metric, and the principal components analysed geometric index (PCAGI). For each method the detection-delineation operating characteristics were obtained automatically in terms of sensitivity, positive predictivity and delineation (segmentation) error rms and checked by the cardiologist. The Matlab m-file script of the synthetic ECG, ABP and PCG signal generators are available in the Appendix.
Parametric Modeling of Transverse Phase Space of an RF Photoinjector
Hartman, E.; Sayyar-Rodsari, B.; Schweiger, C.A.; Lee, M.J.; Lui, P.; Paterson, Ewan; Schmerge, J.F.; /SLAC
2008-01-24
High brightness electron beam sources such as rf photo-injectors as proposed for SASE FELs must consistently produce the desired beam quality. We report the results of a study in which a combined neural network (NN) and first-principles (FP) model is used to model the transverse phase space of the beam as a function of quadrupole strength, while beam charge, solenoid field, accelerator gradient, and linac voltage and phase are kept constant. The parametric transport matrix between the exit of the linac section and the spectrometer screen constitutes the FP component of the combined model. The NN block provides the parameters of the transport matrix as functions of quad current. Using real data from SLAC Gun Test Facility, we will highlight the significance of the constrained training of the NN block and show that the phase space of the beam is accurately modeled by the combined NN and FP model, while variations of beam matrix parameters with the quad current are correctly captured. We plan to extend the combined model in the future to capture the effects of variations in beam charge, solenoid field, and accelerator voltage and phase.
NASA Astrophysics Data System (ADS)
Blom, Philip S.; Marcillo, Omar E.
2017-03-01
A method is developed to apply acoustic tomography methods to a localized network of infrasound arrays with intention of monitoring the atmosphere state in the region around the network using non-local sources without requiring knowledge of the precise source location or non-local atmosphere state. Closely spaced arrays provide a means to estimate phase velocities of signals that can provide limiting bounds on certain characteristics of the atmosphere. Larger spacing between such clusters provide a means to estimate celerity from propagation times along multiple unique stratospherically or thermospherically ducted propagation paths and compute more precise estimates of the atmosphere state. In order to avoid the commonly encountered complex, multimodal distributions for parametric atmosphere descriptions and to maximize the computational efficiency of the method, an optimal parametrization framework is constructed. This framework identifies the ideal combination of parameters for tomography studies in specific regions of the atmosphere and statistical model selection analysis shows that high quality corrections to the middle atmosphere winds can be obtained using as few as three parameters. Comparison of the resulting estimates for synthetic data sets shows qualitative agreement between the middle atmosphere winds and those estimated from infrasonic traveltime observations.
NASA Astrophysics Data System (ADS)
Metzger, W. J.; Novák, T.; Csörgő, T.; Kittel, W.
A short review of Bose-Einstein correlations in hadronic e+e- annihilation is presented. Bose-Einstein correlations of pairs of identical charged pions in hadronic Z-boson decays are analyzed in terms of various parametrizations. A good description is achieved using a Lévy stable distribution in conjunction with a hadronization model having highly correlated configuration and momentum space, the τ-model. Using these results, the source function is reconstructed.
Parametric Model for Astrophysical Proton-Proton Interactions and Applications
Karlsson, Niklas
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
Kang, Jiqiang; Wei, Xiaoming; Li, Bowen; Wang, Xie; Yu, Luoqin; Tan, Sisi; Jinata, Chandra; Wong, Kenneth K. Y.
2016-01-01
We proposed a sensitivity enhancement method of the interference-based signal detection approach and applied it on a swept-source optical coherence tomography (SS-OCT) system through all-fiber optical parametric amplifier (FOPA) and parametric balanced detector (BD). The parametric BD was realized by combining the signal and phase conjugated idler band that was newly-generated through FOPA, and specifically by superimposing these two bands at a photodetector. The sensitivity enhancement by FOPA and parametric BD in SS-OCT were demonstrated experimentally. The results show that SS-OCT with FOPA and SS-OCT with parametric BD can provide more than 9 dB and 12 dB sensitivity improvement, respectively, when compared with the conventional SS-OCT in a spectral bandwidth spanning over 76 nm. To further verify and elaborate their sensitivity enhancement, a bio-sample imaging experiment was conducted on loach eyes by conventional SS-OCT setup, SS-OCT with FOPA and parametric BD at different illumination power levels. All these results proved that using FOPA and parametric BD could improve the sensitivity significantly in SS-OCT systems. PMID:27446655
Kang, Jiqiang; Wei, Xiaoming; Li, Bowen; Wang, Xie; Yu, Luoqin; Tan, Sisi; Jinata, Chandra; Wong, Kenneth K Y
2016-04-01
We proposed a sensitivity enhancement method of the interference-based signal detection approach and applied it on a swept-source optical coherence tomography (SS-OCT) system through all-fiber optical parametric amplifier (FOPA) and parametric balanced detector (BD). The parametric BD was realized by combining the signal and phase conjugated idler band that was newly-generated through FOPA, and specifically by superimposing these two bands at a photodetector. The sensitivity enhancement by FOPA and parametric BD in SS-OCT were demonstrated experimentally. The results show that SS-OCT with FOPA and SS-OCT with parametric BD can provide more than 9 dB and 12 dB sensitivity improvement, respectively, when compared with the conventional SS-OCT in a spectral bandwidth spanning over 76 nm. To further verify and elaborate their sensitivity enhancement, a bio-sample imaging experiment was conducted on loach eyes by conventional SS-OCT setup, SS-OCT with FOPA and parametric BD at different illumination power levels. All these results proved that using FOPA and parametric BD could improve the sensitivity significantly in SS-OCT systems.
ANSYS PARAMETRIC MODEL FOR TANK DST-AY
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This report documents the parametric ANSYS models developed for dome load analyses of double-shell tanks. The default model parameters are specific to the AY tanks but can be easily modified for tank-specific analysis of AN, AW, AP, AZ or SY tanks. Both axisymmetric slice and full 360 degree models are provided. The purpose of this calculation is to develop a parametric finite element analysis model of the Hanford Site underground waste storage tanks. This is not an analysis. Instead, the present calculation develops a parametric model of the double shell tank DST-AY, which is based on Buyer-supplied as-built drawings and information for the analyses of record (AOR) for Double-Shell Tanks (DSTs), encompassing the existing tank load conditions. The computer model has various parameters that can be either changed directly or easily added by a knowledgeable ANSYS user. These parameters are modified to consider field conditions, such as in-situ wall thickness of primary steel tank, dead and live loads, moving loads, berm loads, soil overburden depth plus surrounding soil, internal waste level and waste specific gravity, internal vapor pressure, and thermal loads within the tank. This document contains sample calculations that demonstrate how various aspects of the parametric model function. These sample calculations in this document are not to be used for assessing the structural integrity of the DST-AY tanks at the Hanford Site.
Bayesian non-parametrics and the probabilistic approach to modelling
Ghahramani, Zoubin
2013-01-01
Modelling is fundamental to many fields of science and engineering. A model can be thought of as a representation of possible data one could predict from a system. The probabilistic approach to modelling uses probability theory to express all aspects of uncertainty in the model. The probabilistic approach is synonymous with Bayesian modelling, which simply uses the rules of probability theory in order to make predictions, compare alternative models, and learn model parameters and structure from data. This simple and elegant framework is most powerful when coupled with flexible probabilistic models. Flexibility is achieved through the use of Bayesian non-parametrics. This article provides an overview of probabilistic modelling and an accessible survey of some of the main tools in Bayesian non-parametrics. The survey covers the use of Bayesian non-parametrics for modelling unknown functions, density estimation, clustering, time-series modelling, and representing sparsity, hierarchies, and covariance structure. More specifically, it gives brief non-technical overviews of Gaussian processes, Dirichlet processes, infinite hidden Markov models, Indian buffet processes, Kingman’s coalescent, Dirichlet diffusion trees and Wishart processes. PMID:23277609
Update on Parametric Cost Models for Space Telescopes
NASA Technical Reports Server (NTRS)
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
NASA Astrophysics Data System (ADS)
Wei, Jie; Zhang, Chun-Hui; Wang, Qin
2017-02-01
We present a new scheme on implementing the passive quantum key distribution with thermal distributed parametric down-conversion source. In this scheme, only one-intensity decoy state is employed, but we can achieve very precise estimation on the single-photon-pulse contribution by utilizing those built-in decoy states. Moreover, we compare the new scheme with other practical methods, i.e., the standard three-intensity decoy-state BB84 protocol using either weak coherent states or parametric down-conversion source. Through numerical simulations, we demonstrate that our new scheme can drastically improve both the secure transmission distance and the key generation rate.
Parametric time delay modeling for floating point units
NASA Astrophysics Data System (ADS)
Fahmy, Hossam A. H.; Liddicoat, Albert A.; Flynn, Michael J.
2002-12-01
A parametric time delay model to compare floating point unit implementations is proposed. This model is used to compare a previously proposed floating point adder using a redundant number representation with other high-performance implementations. The operand width, the fan-in of the logic gates and the radix of the redundant format are used as parameters to the model. The comparison is done over a range of operand widths, fan-in and radices to show the merits of each implementation.
Automated parametrical antenna modelling for ambient assisted living applications
NASA Astrophysics Data System (ADS)
Kazemzadeh, R.; John, W.; Mathis, W.
2012-09-01
In this paper a parametric modeling technique for a fast polynomial extraction of the physically relevant parameters of inductively coupled RFID/NFC (radio frequency identification/near field communication) antennas is presented. The polynomial model equations are obtained by means of a three-step procedure: first, full Partial Element Equivalent Circuit (PEEC) antenna models are determined by means of a number of parametric simulations within the input parameter range of a certain antenna class. Based on these models, the RLC antenna parameters are extracted in a subsequent model reduction step. Employing these parameters, polynomial equations describing the antenna parameter with respect to (w.r.t.) the overall antenna input parameter range are extracted by means of polynomial interpolation and approximation of the change of the polynomials' coefficients. The described approach is compared to the results of a reference PEEC solver with regard to accuracy and computation effort.
Source finding, parametrization, and classification for the extragalactic Effelsberg-Bonn H i Survey
NASA Astrophysics Data System (ADS)
Flöer, L.; Winkel, B.; Kerp, J.
2014-09-01
Context. Source extraction for large-scale H i surveys currently involves large amounts of manual labor. For data volumes expected from future H i surveys with upcoming facilities, this approach is not feasible any longer. Aims: We describe the implementation of a fully automated source finding, parametrization, and classification pipeline for the Effelsberg-Bonn H i Survey (EBHIS). With future radio astronomical facilities in mind, we want to explore the feasibility of a completely automated approach to source extraction for large-scale H i surveys. Methods: Source finding is implemented using wavelet denoising methods, which previous studies show to be a powerful tool, especially in the presence of data defects. For parametrization, we automate baseline fitting, mask optimization, and other tasks based on well-established algorithms, currently used interactively. For the classification of candidates, we implement an artificial neural network, which is trained on a candidate set comprised of false positives from real data and simulated sources. Using simulated data, we perform a thorough analysis of the algorithms implemented. Results: We compare the results from our simulations to the parametrization accuracy of the H i Parkes All-Sky Survey (HIPASS) survey. Even though HIPASS is more sensitive than EBHIS in its current state, the parametrization accuracy and classification reliability match or surpass the manual approach used for HIPASS data.
Bayesian non parametric modelling of Higgs pair production
NASA Astrophysics Data System (ADS)
Scarpa, Bruno; Dorigo, Tommaso
2017-03-01
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.
Scene Parsing With Integration of Parametric and Non-Parametric Models
NASA Astrophysics Data System (ADS)
Shuai, Bing; Zuo, Zhen; Wang, Gang; Wang, Bing
2016-05-01
We adopt Convolutional Neural Networks (CNNs) to be our parametric model to learn discriminative features and classifiers for local patch classification. Based on the occurrence frequency distribution of classes, an ensemble of CNNs (CNN-Ensemble) are learned, in which each CNN component focuses on learning different and complementary visual patterns. The local beliefs of pixels are output by CNN-Ensemble. Considering that visually similar pixels are indistinguishable under local context, we leverage the global scene semantics to alleviate the local ambiguity. The global scene constraint is mathematically achieved by adding a global energy term to the labeling energy function, and it is practically estimated in a non-parametric framework. A large margin based CNN metric learning method is also proposed for better global belief estimation. In the end, the integration of local and global beliefs gives rise to the class likelihood of pixels, based on which maximum marginal inference is performed to generate the label prediction maps. Even without any post-processing, we achieve state-of-the-art results on the challenging SiftFlow and Barcelona benchmarks.
Scene Parsing With Integration of Parametric and Non-Parametric Models.
Shuai, Bing; Zuo, Zhen; Wang, Gang; Wang, Bing
2016-05-01
We adopt convolutional neural networks (CNNs) to be our parametric model to learn discriminative features and classifiers for local patch classification. Based on the occurrence frequency distribution of classes, an ensemble of CNNs (CNN-Ensemble) are learned, in which each CNN component focuses on learning different and complementary visual patterns. The local beliefs of pixels are output by CNN-Ensemble. Considering that visually similar pixels are indistinguishable under local context, we leverage the global scene semantics to alleviate the local ambiguity. The global scene constraint is mathematically achieved by adding a global energy term to the labeling energy function, and it is practically estimated in a non-parametric framework. A large margin-based CNN metric learning method is also proposed for better global belief estimation. In the end, the integration of local and global beliefs gives rise to the class likelihood of pixels, based on which maximum marginal inference is performed to generate the label prediction maps. Even without any post-processing, we achieve the state-of-the-art results on the challenging SiftFlow and Barcelona benchmarks.
Parametric Modeling and Fault Tolerant Control
NASA Technical Reports Server (NTRS)
Wu, N. Eva; Ju, Jianhong
2000-01-01
Fault tolerant control is considered for a nonlinear aircraft model expressed as a linear parameter-varying system. By proper parameterization of foreseeable faults, the linear parameter-varying system can include fault effects as additional varying parameters. A recently developed technique in fault effect parameter estimation allows us to assume that estimates of the fault effect parameters are available on-line. Reconfigurability is calculated for this model with respect to the loss of control effectiveness to assess the potentiality of the model to tolerate such losses prior to control design. The control design is carried out by applying a polytopic method to the aircraft model. An error bound on fault effect parameter estimation is provided, within which the Lyapunov stability of the closed-loop system is robust. Our simulation results show that as long as the fault parameter estimates are sufficiently accurate, the polytopic controller can provide satisfactory fault-tolerance.
Cosmic star formation probed via parametric stack-fitting of known sources to radio imaging
NASA Astrophysics Data System (ADS)
Roseboom, I. G.; Best, P. N.
2014-04-01
The promise of multiwavelength astronomy has been tempered by the large disparity in sensitivity and resolution between different wavelength regimes. Here, we present a statistical approach which attempts to overcome this by fitting parametric models directly to image data. Specifically, we fit a model for the radio luminosity function (LF) of star-forming galaxies to pixel intensity distributions at 1.4 GHz coincident with near-IR selected sources in COSMOS. Taking a mass-limited sample in redshift bins across the range 0 < z < 4, we are able to fit the radio LF with ˜0.2 dex precision in the key parameters (e.g. Φ*,L*). Good agreement is seen between our results and those using standard methods at radio and other wavelengths. Integrating our LFs to get the star formation rate density, we find that galaxies with M* > 109.5 M⊙ contribute ≳50 per cent of cosmic star formation at 0 < z < 4. The scalability of our approach is empirically estimated, with the precision in LF parameter estimates found to scale with the number of sources in the stack, Ns, as ∝ √{N_s}. This type of approach will be invaluable in the multiwavelength analysis of upcoming surveys with the Square Kilometre Array pathfinder facilities: LOFAR, ASKAP and MeerKAT.
Parametric modeling of zoom lens barrels
NASA Astrophysics Data System (ADS)
Pierce, Charles W.
2001-12-01
Today's customer requires zoom lens designs that are compact, inexpensive, and at six-sigma quality levels. While incorporating these customer requirements, a design team must often work within compressed design cycles and minimal product development budgets. These customer and project constraints, coupled with the inherent complexity of a zoom lens module, force the design team to try new and innovative techniques to deliver their products. This paper presents the methods used to develop lens barrels for several zoom lens module projects at Eastman Kodak Company. The lens barrel, a critical interface between the mechanical and optical systems, presented a technical barrier from both an engineering analysis and manufacturing perspective. The method used to overcome these barriers consisted of identifying several key functional parameters, creating a parameter-driven 3-D solid model in a commercially available CAD system, and then using the model to make iterative, data-driven design decisions while leveraging the model to create engineering drawings and the necessary prototypes and production tooling. As a result, the designs were able to meet their size, cost, and design cycle time requirements while realizing a better than anticipated first pass yield and quality level.
Single-variable parametric cost models for space telescopes
NASA Astrophysics Data System (ADS)
Stahl, H. Philip; Henrichs, Todd; Smart, Christian; Prince, Frank A.
2010-07-01
Parametric cost models are routinely used to plan missions, compare concepts, and justify technology investments. Unfortunately, there is no definitive space telescope cost model. For example, historical cost estimating relationships (CERs) based on primary mirror diameter vary by an order of magnitude. We present new single-variable cost models for space telescope optical telescope assembly (OTA). They are based on data collected from 30 different space telescope missions. Standard statistical methods are used to derive CERs for OTA cost versus aperture diameter and mass. The results are compared with previously published models
Parametric design calculations using Green's function to determine unique source
NASA Astrophysics Data System (ADS)
Carter, L. L.; Lan, J. S.
1991-01-01
The energy dependence of the current incident on a macrocell can in principle be determined if the Green's function and the interior flux due to the total current are known. The Green's function is the flux within some portion of the macrocell due to a unit source in each energy group. It was demonstrated that the appropriate solution for the current is obtained for the higher energy groups in a fast reactor example. However, the lower energy groups are very sensitive to the downscattering and the solution even led to negative values for the incident partial current in some energy groups, which is not physical. In this particular example, the preliminary design study was insensitive to the incident current of the lower energy groups. For problems where the lower groups are important, it would seem prudent to abandon the exact solution and use a weighted least squares solution. Such a weighted least squares solution could assign importance for obtaining nearly the exact solution for as many energy groups as possible, while simultaneously making slight adjustments in the higher energy currents to obtain downscatter contributions that will approximately perserve the flux in the lower energy groups.
ERIC Educational Resources Information Center
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…
Modeling of autoresonant control of a parametrically excited screen machine
NASA Astrophysics Data System (ADS)
Abolfazl Zahedi, S.; Babitsky, Vladimir
2016-10-01
Modelling of nonlinear dynamic response of a screen machine described by the nonlinear coupled differential equations and excited by the system of autoresonant control is presented. The displacement signal of the screen is fed to the screen excitation directly by means of positive feedback. Negative feedback is used to fix the level of screen amplitude response within the expected range. The screen is anticipated to vibrate with a parametric resonance and the excitation, stabilization and control response of the system are studied in the stable mode. Autoresonant control is thoroughly investigated and output tracking is reported. The control developed provides the possibility of self-tuning and self-adaptation mechanisms that allow the screen machine to maintain a parametric resonant mode of oscillation under a wide range of uncertainty of mass and viscosity.
Multivariable Parametric Cost Model for Ground Optical Telescope Assembly
NASA Technical Reports Server (NTRS)
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
NASA Technical Reports Server (NTRS)
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.
Dynamics of the Kitaev chain model under parametric pumping
NASA Astrophysics Data System (ADS)
Zvyagin, A. A.
2014-07-01
Dynamics of the Kitaev chain model under the effect of parametric pumping is studied. Two contributions to dynamical characteristics are considered: from the extended eigenstates and from the edge bound state (zero Majorana modes). It is shown that in the dynamical regime the frequencies of Rabi oscillations for zero Majorana modes are much larger than those related to gapped extended states. In the steady-state regime, the Rabi oscillations are blurred due to relaxation processes, and only oscillations of the characteristics of the model with the pumping frequency exist, producing absorption of the pumping power by extended states. Experimental realizations of the considered effect are discussed.
Parametric uncertainty modeling for application to robust control
NASA Technical Reports Server (NTRS)
Belcastro, Christine M.; Chang, B.-C.; Fischl, Robert
1993-01-01
Viewgraphs and a paper on parametric uncertainty modeling for application to robust control are included. Advanced robust control system analysis and design is based on the availability of an uncertainty description which separates the uncertain system elements from the nominal system. Although this modeling structure is relatively straightforward to obtain for multiple unstructured uncertainties modeled throughout the system, it is difficult to formulate for many problems involving real parameter variations. Furthermore, it is difficult to ensure that the uncertainty model is formulated such that the dimension of the resulting model is minimal. A procedure for obtaining an uncertainty model for real uncertain parameter problems in which the uncertain parameters can be represented in a multilinear form is presented. Furthermore, the procedure is formulated such that the resulting uncertainty model is minimal (or near minimal) relative to a given state space realization of the system. The approach is demonstrated for a multivariable third-order example problem having four uncertain parameters.
Model reduction for parametric instability analysis in shells conveying fluid
NASA Astrophysics Data System (ADS)
Kochupillai, Jayaraj; Ganesan, N.; Padmanabhan, Chandramouli
2003-05-01
Flexible pipes conveying fluid are often subjected to parametric excitation due to time-periodic flow fluctuations. Such systems are known to exhibit complex instability phenomena such as divergence and coupled-mode flutter. Investigators have typically used weighted residual techniques, to reduce the continuous system model into a discrete model, based on approximation functions with global support, for carrying out stability analysis. While this approach is useful for straight pipes, modelling based on FEM is needed for the study of complicated piping systems, where the approximation functions used are local in support. However, the size of the problem is now significantly larger and for computationally efficient stability analysis, model reduction is necessary. In this paper, model reduction techniques are developed for the analysis of parametric instability in flexible pipes conveying fluids under a mean pressure. It is shown that only those linear transformations which leave the original eigenvalues of the linear time invariant system unchanged are admissible. The numerical technique developed by Friedmann and Hammond (Int. J. Numer. Methods Eng. Efficient 11 (1997) 1117) is used for the stability analysis. One of the key research issues is to establish criteria for deciding the basis vectors essential for an accurate stability analysis. This paper examines this issue in detail and proposes new guidelines for their selection.
Two-parametric model of electron beam in computational dosimetry for radiation processing
NASA Astrophysics Data System (ADS)
Lazurik, V. M.; Lazurik, V. T.; Popov, G.; Zimek, Z.
2016-07-01
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: E0 - energy mono-energetic and mono-directional electron source, X0 - 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 Ep- the most probably energy and Rp - practical range) can be linked with characteristics of two-parametric model (E0, X0), 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.
A simple pond parametrization for malaria transmission models
NASA Astrophysics Data System (ADS)
Tompkins, A. M.; Asare, E.; Amekudzi, L. K.
2012-04-01
In order to model malaria effectively using a dynamical modelling approach, a realistic representation of the surface hydrology is required. Achieving this goal is hindered by the fact that key vector breeding sites are small in spatial scale, ranging from small permanent ponds to temporary puddles. This small spatial scale confounds modelling efforts as the topography on such small scales is unknown, and also renders detection by remote sensing techniques difficult implying a requirement of in-situ measurements. Results from ongoing measurements of breeding sites in Kumasi (Ghana) are shown, along with attempts to reproduce these using a simple pond 'parametrization'. The significant impact of the pond model implementation and settings on malaria simulations using the new VECTRI dynamical disease model is demonstrated.
Fine, D R; Lurie, R E; Candy, G P
1994-11-01
Renal function is often characterized by the activity/time curves obtained by imaging the aorta and kidney. Non-parametric deconvolution of the activity/time curves is clinically useful as a diagnostic tool in determining renal transit times. Typically non-parametric deconvolution is performed using a technique that does not require a priori information, e.g. matrix-based and Fourier-transform methods. Using data filtering and conservation of mass constraints, non-parametric deconvolution continues to exhibit noise in the deconvolved curves. This noise hampers the identification of renal transit times. Given the shortcomings of non-parametric deconvolution, a parametric model of the renal response has been developed. Our model is shown to be anatomically and physiologically plausible. In this paper, the parametric model structure is used, in conjunction with experimental data, to estimate renal physiological parameters. These parameters include the filtration fraction, renal blood transit time and urine transit times. The model parameters are then related to the minimum transit time (MinTT), mean transit time (MTT), glomerular filtration rate (GFR) and parenchymal transit time index (PTTI). As deconvolution techniques often produce negative artifacts, Fine et al developed a technique to determine an aorta background to minimize this effect. In this paper this work is extended to determine a reasonable renal background from aorta activity/time curves. Non-parametric deconvolution is used to provide initial estimates of model parameters. The model is then fitted to twelve healthy background-corrected kidneys by an iterative parameter-estimation technique. The normal values correspond to those reported in the literature. These normal values are then used to identify renal arterial stenosis in two renal hypertensive patients. The results suggest that parametric identification, based on a renal-retention-function model, may provide additional anatomical and
Automated, Parametric Geometry Modeling and Grid Generation for Turbomachinery Applications
NASA Technical Reports Server (NTRS)
Harrand, Vincent J.; Uchitel, Vadim G.; Whitmire, John B.
2000-01-01
The objective of this Phase I project is to develop a highly automated software system for rapid geometry modeling and grid generation for turbomachinery applications. The proposed system features a graphical user interface for interactive control, a direct interface to commercial CAD/PDM systems, support for IGES geometry output, and a scripting capability for obtaining a high level of automation and end-user customization of the tool. The developed system is fully parametric and highly automated, and, therefore, significantly reduces the turnaround time for 3D geometry modeling, grid generation and model setup. This facilitates design environments in which a large number of cases need to be generated, such as for parametric analysis and design optimization of turbomachinery equipment. In Phase I we have successfully demonstrated the feasibility of the approach. The system has been tested on a wide variety of turbomachinery geometries, including several impellers and a multi stage rotor-stator combination. In Phase II, we plan to integrate the developed system with turbomachinery design software and with commercial CAD/PDM software.
Model for coherence transfer in a backward optical parametric oscillator
NASA Astrophysics Data System (ADS)
Montes, Carlos; Aschieri, Pierre; Picozzi, Antonio
2011-09-01
The mirrorless backward optical parametric oscillator (BOPO), where the signal and idler waves are propagating in opposite directions, will establish a distributed feedback mechanism and thus optical parametric oscillation without the need to apply mirrors or external feedback to the cavity. It has been recently demonstrated experimentally by exploiting the periodic poling technique in second-order nonlinear crystals, that the sub-micrometer structured medium achieves an efficient quasi-phase-matching of the three wave interaction in the backward configuration. A remarkable property of such BOPO is the high degree of coherence of the backward wave component, whose spectrum may be several order of magnitudes narrower than that of the pump, due to the convectioninduced phase-locking mechanism. Experimentally and numerically proved the transfer of coherent phase modulations from the pump wave to the parametrically down-converted waves, we show here that this is also possible for a broad bandwidth spectrally incoherent pump. In order to accurately describe the nonlinear counter-propagation dynamics of the three dispersive waves, we have developed for the first time to our knowledge a new numerical scheme which combines the method of the trajectories usually employed to solve the three-wave interaction and the intraband group velocity dispersion effect is performed in the spectral domain with the help of the Fast Fourier Transform (FFT) technique. The model accurately conserves the number of photons and the Manley-Rowe invariants. This allowed us to predict various configurations of MOPOs in which, thanks to the convection-induced phase-locking mechanism, a highly coherent backward wave is spontaneously generated from a highly incoherent pump wave.
Uncertainties in volcanic plume modeling: A parametric study using FPLUME
NASA Astrophysics Data System (ADS)
Macedonio, G.; Costa, A.; Folch, A.
2016-10-01
We carry out a parametric study in order to identify and quantify the effects of uncertainties on pivotal parameters controlling the dynamics of volcanic plumes. The study builds upon numerical simulations using FPLUME, an integral steady-state model based on the Buoyant Plume Theory generalized in order to account for volcanic processes (particle fallout and re-entrainment, water phase changes, effects of wind, etc). As reference cases for strong and weak plumes, we consider the cases defined during the IAVCEI Commission on tephra hazard modeling inter-comparison study (Costa et al., 2016). The parametric study quantifies the effect of typical uncertainties on total mass eruption rate, column height, mixture exit velocity, temperature and water content, and particle size. Moreover, a sensitivity study investigates the role of wind entrainment and intensity, atmospheric humidity, water phase changes, and particle fallout and re-entrainment. Results show that the leading-order parameters that control plume height are the mass eruption rate and the air entrainment coefficient, especially for weak plumes.
Parametric Thermal Soak Model for Earth Entry Vehicles
NASA Technical Reports Server (NTRS)
Agrawal, Parul; Samareh, Jamshid; Doan, Quy D.
2013-01-01
The analysis and design of an Earth Entry Vehicle (EEV) is multidisciplinary in nature, requiring the application many disciplines. An integrated tool called Multi Mission System Analysis for Planetary Entry Descent and Landing or M-SAPE is being developed as part of Entry Vehicle Technology project under In-Space Technology program. Integration of a multidisciplinary problem is a challenging task. Automation of the execution process and data transfer among disciplines can be accomplished to provide significant benefits. Thermal soak analysis and temperature predictions of various interior components of entry vehicle, including the impact foam and payload container are part of the solution that M-SAPE will offer to spacecraft designers. The present paper focuses on the thermal soak analysis of an entry vehicle design based on the Mars Sample Return entry vehicle geometry and discusses a technical approach to develop parametric models for thermal soak analysis that will be integrated into M-SAPE. One of the main objectives is to be able to identify the important parameters and to develop correlation coefficients so that, for a given trajectory, can estimate the peak payload temperature based on relevant trajectory parameters and vehicle geometry. The models are being developed for two primary thermal protection (TPS) materials: 1) carbon phenolic that was used for Galileo and Pioneer Venus probes and, 2) Phenolic Impregnated Carbon Ablator (PICA), TPS material for Mars Science Lab mission. Several representative trajectories were selected from a very large trade space to include in the thermal analysis in order to develop an effective parametric thermal soak model. The selected trajectories covered a wide range of heatload and heatflux combinations. Non-linear, fully transient, thermal finite element simulations were performed for the selected trajectories to generate the temperature histories at the interior of the vehicle. Figure 1 shows the finite element model
Two-parametric fractional statistics models for anyons
NASA Astrophysics Data System (ADS)
Rovenchak, Andrij
2014-08-01
In the paper, two-parametric models of fractional statistics are proposed in order to determine the functional form of the distribution function of free anyons. From the expressions of the second and third virial coefficients, an approximate correspondence is shown to hold for three models, namely, the nonadditive Polychronakos statistics and both the incomplete and the nonadditive modifications of the Haldane-Wu statistics. The difference occurs only in the fourth virial coefficient leading to a small correction in the equation of state. For the two generalizations of the Haldane-Wu statistics, the solutions for the statistics parameters g, q exist in the whole domain of the anyonic parameter α ∈ [0; 1], unlike the nonadditive Polychronakos statistics. It is suggested that the search for the expression of the anyonic distribution function should be made within some modifications of the Haldane-Wu statistics.
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
2017-03-27
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. () and Hens et al. (). 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.
Parametric Thermal Models of the Transient Reactor Test Facility (TREAT)
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.
Assessment of parametric uncertainty for groundwater reactive transport modeling,
Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun
2014-01-01
The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood
User's manual for heat-pump seasonal-performance model (SPM) with selected parametric examples
Not Available
1982-06-30
The Seasonal Performance Model (SPM) was developed to provide an accurate source of seasonal energy consumption and cost predictions for the evaluation of heat pump design options. The program uses steady state heat pump performance data obtained from manufacturers' or Computer Simulation Model runs. The SPM was originally developed in two forms - a cooling model for central air conditioners and heat pumps and a heating model for heat pumps. The original models have undergone many modifications, which are described, to improve the accuracy of predictions and to increase flexibility for use in parametric evaluations. Insights are provided into the theory and construction of the major options, and into the use of the available options and output variables. Specific investigations provide examples of the possible applications of the model. (LEW)
A Bayesian non-parametric Potts model with application to pre-surgical FMRI data.
Johnson, Timothy D; Liu, Zhuqing; Bartsch, Andreas J; Nichols, Thomas E
2013-08-01
The Potts model has enjoyed much success as a prior model for image segmentation. Given the individual classes in the model, the data are typically modeled as Gaussian random variates or as random variates from some other parametric distribution. In this article, we present a non-parametric Potts model and apply it to a functional magnetic resonance imaging study for the pre-surgical assessment of peritumoral brain activation. In our model, we assume that the Z-score image from a patient can be segmented into activated, deactivated, and null classes, or states. Conditional on the class, or state, the Z-scores are assumed to come from some generic distribution which we model non-parametrically using a mixture of Dirichlet process priors within the Bayesian framework. The posterior distribution of the model parameters is estimated with a Markov chain Monte Carlo algorithm, and Bayesian decision theory is used to make the final classifications. Our Potts prior model includes two parameters, the standard spatial regularization parameter and a parameter that can be interpreted as the a priori probability that each voxel belongs to the null, or background state, conditional on the lack of spatial regularization. We assume that both of these parameters are unknown, and jointly estimate them along with other model parameters. We show through simulation studies that our model performs on par, in terms of posterior expected loss, with parametric Potts models when the parametric model is correctly specified and outperforms parametric models when the parametric model in misspecified.
Numerical model of solar dynamic radiator for parametric analysis
NASA Technical Reports Server (NTRS)
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. The SD module rejects waste heat from the power conversion cycle to space through a pumped-loop, multi-panel, deployable radiator. The baseline radiator configuration was defined during the Space Station conceptual design phase and is a function of the state point and heat rejection requirements of the power conversion unit. Requirements determined by the overall station design such as mass, system redundancy, micrometeoroid and space debris impact survivability, launch packaging, costs, and thermal and structural interaction with other station components have also been design drivers for the radiator configuration. 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. A brief description and discussion of the numerical model, it's capabilities and limitations, and results of the parametric studies performed is presented.
Sowa, Michael G; Smith, Michael S D; Kendall, Catherine; Bock, Erika R; Ko, Alex C-T; Choo-Smith, Lin-P'ing; Stone, Nicholas
2006-08-01
Identification and quantification of molecular species are central applications of molecular spectroscopy. In complex multicomponent systems like tissue samples, linear parametric models are often used to estimate the relative concentrations of the biochemical components of the sample. In situations where not all of the components of the sample are known or modeled, such parametric models can suffer from omitted variable bias and result in skewed estimates of component concentrations. We propose a semi-parametric approach that tries to avoid this omitted variable bias by effectively including unknown covariates as a non-parametric term in the regression equation. Constituent concentrations estimated with such partial linear models should outperform strict parametric linear models when the user has limited information on the composition of a multi-constituent system.
Multivariable parametric cost model for space and ground telescopes
NASA Astrophysics Data System (ADS)
Stahl, H. Philip; Henrichs, Todd
2016-09-01
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 (X) D (1.75 +/- 0.05) λ (-0.5 +/- 0.25) T-0.25 e (-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).
Open Source Molecular Modeling
Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan
2016-01-01
The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. PMID:27631126
Je, Yub; Lee, Haksue; Park, Jongkyu; Moon, Wonkyu
2010-06-01
An ultrasonic radiator is developed to generate a difference frequency sound from two frequencies of ultrasound in air with a parametric array. A design method is proposed for an ultrasonic radiator capable of generating highly directive, high-amplitude ultrasonic sound beams at two different frequencies in air based on a modification of the stepped-plate ultrasonic radiator. The stepped-plate ultrasonic radiator was introduced by Gallego-Juarez et al. [Ultrasonics 16, 267-271 (1978)] in their previous study and can effectively generate highly directive, large-amplitude ultrasonic sounds in air, but only at a single frequency. Because parametric array sources must be able to generate sounds at more than one frequency, a design modification is crucial to the application of a stepped-plate ultrasonic radiator as a parametric array source in air. The aforementioned method was employed to design a parametric radiator for use in air. A prototype of this design was constructed and tested to determine whether it could successfully generate a difference frequency sound with a parametric array. The results confirmed that the proposed single small-area transducer was suitable as a parametric radiator in air.
Parametric plate-bridge dynamic filter model of violin radiativity.
Bissinger, George
2012-07-01
A hybrid, deterministic-statistical, parametric "dynamic filter" model of the violin's radiativity profile [characterized by an averaged-over-sphere, mean-square radiativity (R(ω)(2))] is developed based on the premise that acoustic radiation depends on (1) how strongly it vibrates [characterized by the averaged-over-corpus, mean-square mobility (Y(ω)(2))] and (2) how effectively these vibrations are turned into sound, characterized by the radiation efficiency, which is proportional to (R(ω)(2))/(Y(ω)(2)). Two plate mode frequencies were used to compute 1st corpus bending mode frequencies using empirical trend lines; these corpus bending modes in turn drive cavity volume flows to excite the two lowest cavity modes A0 and A1. All widely-separated, strongly-radiating corpus and cavity modes in the low frequency deterministic region are then parameterized in a dual-Helmholtz resonator model. Mid-high frequency statistical regions are parameterized with the aid of a distributed-excitation statistical mobility function (no bridge) to help extract bridge filter effects associated with (a) bridge rocking mode frequency changes and (b) bridge-corpus interactions from 14-violin-average, excited-via-bridge (Y(ω)(2)) and (R(ω)(2)). Deterministic-statistical regions are rejoined at ~630 Hz in a mobility-radiativity "trough" where all violin quality classes had a common radiativity. Simulations indicate that typical plate tuning has a significantly weaker effect on radiativity profile trends than bridge tuning.
NASA Astrophysics Data System (ADS)
Ferrero, Enrico; Mortarini, Luca; Purghè, Federico
2017-04-01
A model for the evaluation of the concentration fluctuation variance is coupled with a one-particle Lagrangian stochastic model and results compared to a wind-tunnel simulation experiment. In this model the concentration variance evolves along the particle trajectories according to the same Langevin equation used for the simulation of the velocity field, and its dissipation is taken into account through a decay term with a finite time scale. Indeed, while the mean concentration is conserved, the concentration variance is not and our model takes into account its dissipation. A simple parametrization for the dissipation time scale is proposed and it is found that it depends linearly on time and on the ratio between the size and the height of the source through a scaling factor of 1 / 3.
Parametric Dielectric Model of Comet Churyumov-Gerasimenko
NASA Astrophysics Data System (ADS)
Heggy, E.; Palmer, E. M.; Kofman, W. W.; Clifford, S. M.; Righter, K.; Herique, A.
2012-12-01
In 2014, the European Space Agency's Rosetta mission is scheduled to rendezvous with Comet 67P/Churyumov-Gerasimenko (Comet 67P). Rosetta's CONSERT experiment aims to explore the cometary nucleus' geophysical properties using radar tomography. The expected scientific return and inversion algorithms are mainly dependent on our understanding of the dielectric properties of the comet nucleus and how they vary with the spatial distribution of geophysical parameters. Using observations of comets 9P/Tempel 1 and 81P/Wild 2 in combination with dielectric laboratory measurements of temperature, porosity, and dust-to-ice mass ratio dependencies for cometary analog material, we have constructed two hypothetical three-dimensional parametric dielectric models of Comet 67P's nucleus to assess different dielectric scenarios of the inner structure. Our models suggest that dust-to-ice mass ratios and porosity variations generate the most significant measurable dielectric contrast inside the comet nucleus, making it possible to explore the structural and compositional hypotheses of cometary nuclei. Surface dielectric variations, resulting from temperature changes induced by solar illumination of the comet's faces, have also been modeled and suggest that the real part of the dielectric constant varies from 1.9 to 3.0, hence changing the surface radar reflectivity. For CONSERT, this variation could be significant at low incidence angles, when the signal propagates through a length of dust mantle comparable to the wavelength. The overall modeled dielectric permittivity spatial and temporal variations are therefore consistent with the expected deep penetration of CONSERT's transmitted wave through the nucleus. It is also clear that changes in the physical properties of the nucleus induce sufficient variation in the dielectric properties of cometary material to allow their inversion from radar tomography.
Coupled mode parametric resonance in a vibrating screen model
NASA Astrophysics Data System (ADS)
Slepyan, Leonid I.; Slepyan, Victor I.
2014-02-01
We consider a simple dynamic model of the vibrating screen operating in the parametric resonance (PR) mode. This model was used in the course of designing and setting of such a screen in LPMC. The PR-based screen compares favorably with conventional types of such machines, where the transverse oscillations are excited directly. It is characterized by larger values of the amplitude and by insensitivity to damping in a rather wide range. The model represents an initially strained system of two equal masses connected by a linearly elastic string. Self-equilibrated, longitudinal, harmonic forces act on the masses. Under certain conditions this results in transverse, finite-amplitude oscillations of the string. The problem is reduced to a system of two ordinary differential equations coupled by the geometric nonlinearity. Damping in both the transverse and longitudinal oscillations is taken into account. Free and forced oscillations of this mass-string system are examined analytically and numerically. The energy exchange between the longitudinal and transverse modes of free oscillations is demonstrated. An exact analytical solution is found for the forced oscillations, where the coupling plays the role of a stabilizer. In a more general case, the harmonic analysis is used with neglect of the higher harmonics. Explicit expressions for all parameters of the steady nonlinear oscillations are determined. The domains are found where the analytically obtained steady oscillation regimes are stable. Over the frequency ranges, where the steady oscillations exist, a perfect correspondence is found between the amplitudes obtained analytically and numerically. Illustrations based on the analytical and numerical simulations are presented.
A non-parametric model for the cosmic velocity field
NASA Astrophysics Data System (ADS)
Branchini, E.; Teodoro, L.; Frenk, C. S.; Schmoldt, I.; Efstathiou, G.; White, S. D. M.; Saunders, W.; Sutherland, W.; Rowan-Robinson, M.; Keeble, O.; Tadros, H.; Maddox, S.; Oliver, S.
1999-09-01
We present a self-consistent non-parametric model of the local cosmic velocity field derived from the distribution of IRAS galaxies in the PSCz redshift survey. The survey has been analysed using two independent methods, both based on the assumptions of gravitational instability and linear biasing. The two methods, which give very similar results, have been tested and calibrated on mock PSCz catalogues constructed from cosmological N-body simulations. The denser sampling provided by the PSCz survey compared with previous IRAS galaxy surveys allows an improved reconstruction of the density and velocity fields out to large distances. The most striking feature of the model velocity field is a coherent large-scale streaming motion along the baseline connecting Perseus-Pisces, the Local Supercluster, the Great Attractor and the Shapley Concentration. We find no evidence for back-infall on to the Great Attractor. Instead, material behind and around the Great Attractor is inferred to be streaming towards the Shapley Concentration, aided by the compressional push of two large nearby underdensities. The PSCz model velocities compare well with those predicted from the 1.2-Jy redshift survey of IRAS galaxies and, perhaps surprisingly, with those predicted from the distribution of Abell/ACO clusters, out to 140h^-1Mpc. Comparison of the real-space density fields (or, alternatively, the peculiar velocity fields) inferred from the PSCz and cluster catalogues gives a relative (linear) bias parameter between clusters and IRAS galaxies of b_c=4.4+/-0.6. Finally, we implement a likelihood analysis that uses all the available information on peculiar velocities in our local Universe to estimate beta_Omega 0 0.6 b_0.6 -0.15 +0.22 (1sigma), where b is the bias parameter for IRAS galaxies.
Open source molecular modeling.
Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan
2016-09-01
The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. An updated online version of this catalog can be found at https://opensourcemolecularmodeling.github.io.
Parametric model of ventilators simulated in OpenFOAM and Elmer
NASA Astrophysics Data System (ADS)
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.
Application of Parametric Models to a Survival Analysis of Hemodialysis Patients
Montaseri, Maryam; Charati, Jamshid Yazdani; Espahbodi, Fateme
2016-01-01
Background Hemodialysis is the most common renal replacement therapy in patients with end stage renal disease (ESRD). Objectives The present study compared the performance of various parametric models in a survival analysis of hemodialysis patients. Methods This study consisted of 270 hemodialysis patients who were referred to Imam Khomeini and Fatima Zahra hospitals between November 2007 and November 2012. The Akaike information criterion (AIC) and residuals review were used to compare the performance of the parametric models. The computations were done using STATA Software, with significance accepted at a level of 0.05. Results The results of a multivariate analysis of the variables in the parametric models showed that the mean serum albumin and the clinic attended were the most important predictors in the survival of the hemodialysis patients (P < 0.05). Among the parametric models tested, the results indicated that the performance of the Weibull model was the highest. Conclusions Parametric models may provide complementary data for clinicians and researchers about how risks vary over time. The Weibull model seemed to show the best fit among the parametric models of the survival of hemodialysis patients. PMID:27896235
Parametric Modelling of As-Built Beam Framed Structure in Bim Environment
NASA Astrophysics Data System (ADS)
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 Models of NIR Transmission and Reflectivity Spectra for Dyed Fabrics
2015-07-29
control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 5d. PROJECT NUMBER 5e...Unlimited Unclassified Unlimited 36 Daniel Aiken (202) 279-5293 Parametric Modeling Inverse /direct analysis Dielectric function This study examines...parametric modeling of near-infrared (NIR) transmission and reflectivity spectra for dyed fabrics, which provides for both their inverse and direct
First-Order Parametric Model of Reflectance Spectra for Dyed Fabrics
2016-02-19
Aiken S. RAmSey T. mAyo Signature Technology Office Tactical Electronic Warfare Division S.G. LAmbRAkoS Center for Computational Materials Science ...Materials Science and Technology Division J. PeAk Signature Technology Office Tactical Electronic Warfare Division February 19, 2016 Approved for...Unclassified Unlimited 31 Daniel Aiken (202) 279-5293 Parametric modeling Inverse/ direct analysis This report describes a first-order parametric model of
Identification of the 1PL Model with Guessing Parameter: Parametric and Semi-Parametric Results
ERIC Educational Resources Information Center
San Martin, Ernesto; Rolin, Jean-Marie; Castro, Luis M.
2013-01-01
In this paper, we study the identification of a particular case of the 3PL model, namely when the discrimination parameters are all constant and equal to 1. We term this model, 1PL-G model. The identification analysis is performed under three different specifications. The first specification considers the abilities as unknown parameters. It is…
A proposal for a consistent parametrization of earth models
NASA Astrophysics Data System (ADS)
Forbriger, Thomas; Friederich, Wolfgang
2005-08-01
The current way to parametrize earth models in terms of real-valued seismic velocities and quality factors is incomplete as it does not specify how complex-valued viscoelastic moduli or complex velocities should be computed from them. Various ways to do this can be found in the literature. Depending on the context they may specify (1) the real part of the viscoelastic modulus, (2) the absolute value of the viscoelastic modulus, (3) the real part of complex velocity or (4) the phase velocity of a propagating plane wave. We propose here to exclusively use the first alternative because it is the only one which allows both a flexible choice of elastic parameters and a mathematically rigorous evaluation of the complex-valued viscoelastic moduli. The other definitions only permit an evaluation of viscoelastic moduli if the tabulated quality factors are directly associated with the listed velocities. Ignoring the subtle differences between the three definitions leads to variations in viscoelastic moduli which are second order in 1/Q where Q is a quality factor. This may be the reason why the topic has never been discussed in the literature. In case of shallow seismic media, however, where quality factors may assume values of less than 10, the subtle differences become noticeable in synthetic seismograms. It is then essential to use the same definition in all algorithms to make results comparable. Matters become worse for anisotropic media, which are commonly specified in terms of real elastic moduli and quality factors for effective isotropic moduli. In that case, the complex-valued viscoelastic moduli cannot be determined uniquely. However, interpreting the tabulated constants as the real parts of the complex-valued viscoelastic moduli at least allows a consistent definition, which respects the relative magnitude of the anelastic and anisotropic parts compared to the elastic parts. It should be noted that all these considerations apply to complex-valued viscoelastic
NASA Astrophysics Data System (ADS)
Artamonov, A. A.; Mishev, A. L.; Usoskin, I. G.
2016-11-01
Results of a comparison of a new model CRAC:EPII (Cosmic Ray Atmospheric Cascade: Electron Precipitation Induced Ionization) with a commonly used parametric model of atmospheric ionization is presented. The CRAC:EPII is based on a Monte Carlo simulation of precipitating electrons propagation and interaction with matter in the Earth's atmosphere. It explicitly considers energy deposit: ionization, pair production, Compton scattering, generation of Bremsstrahlung high energy photons, photo-ionization and annihilation of positrons, multiple scattering as physical processes accordingly. Propagation of precipitating electrons and their interactions with air is simulated with the GEANT4 simulation tool PLANETOCOSMICS code using NRLMSISE-00 atmospheric model. Ionization yields are computed and compared with a parametrization model for different energies of incident precipitating energetic electrons, using simulated fluxes of mono-energetic particles. A good agreement between the two models is achieved in the mesosphere but the contribution of Bremsstrahlung in the stratosphere, which is not accounted for in the parametric models, is found significant. As an example, we calculated profiles of the ion production rates in the middle and upper atmosphere (below 100 km) on the basis of balloon-born measured spectra of precipitating electrons for 30-October-2002 and 07-January-2004.
The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans
Boes, Jennifer L.; Bule, Maria; Hoff, Benjamin A.; Chamberlain, Ryan; Lynch, David A.; Stojanovska, Jadranka; Martinez, Fernando J.; Han, Meilan K.; Kazerooni, Ella A.; Ross, Brian D.; Galbán, Craig J.
2015-01-01
Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPD-Gene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented. PMID:26568983
The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans.
Boes, Jennifer L; Bule, Maria; Hoff, Benjamin A; Chamberlain, Ryan; Lynch, David A; Stojanovska, Jadranka; Martinez, Fernando J; Han, Meilan K; Kazerooni, Ella A; Ross, Brian D; Galbán, Craig J
2015-09-01
Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPD-Gene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented.
Augmenting Parametric Optimal Ascent Trajectory Modeling with Graph Theory
NASA Technical Reports Server (NTRS)
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 regression model for survival data: Weibull regression model as an example
2016-01-01
Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846
Parametric uncertainties in global model simulations of black carbon column mass concentration
NASA Astrophysics Data System (ADS)
Pearce, Hana; Lee, Lindsay; Reddington, Carly; Carslaw, Ken; Mann, Graham
2016-04-01
Previous studies have deduced that the annual mean direct radiative forcing from black carbon (BC) aerosol may regionally be up to 5 W m-2 larger than expected due to underestimation of global atmospheric BC absorption in models. We have identified the magnitude and important sources of parametric uncertainty in simulations of BC column mass concentration from a global aerosol microphysics model (GLOMAP-Mode). A variance-based uncertainty analysis of 28 parameters has been performed, based on statistical emulators trained on model output from GLOMAP-Mode. This is the largest number of uncertain model parameters to be considered in a BC uncertainty analysis to date and covers primary aerosol emissions, microphysical processes and structural parameters related to the aerosol size distribution. We will present several recommendations for further research to improve the fidelity of simulated BC. In brief, we find that the standard deviation around the simulated mean annual BC column mass concentration varies globally between 2.5 x 10-9 g cm-2 in remote marine regions and 1.25 x 10-6 g cm-2 near emission sources due to parameter uncertainty Between 60 and 90% of the variance over source regions is due to uncertainty associated with primary BC emission fluxes, including biomass burning, fossil fuel and biofuel emissions. While the contributions to BC column uncertainty from microphysical processes, for example those related to dry and wet deposition, are increased over remote regions, we find that emissions still make an important contribution in these areas. It is likely, however, that the importance of structural model error, i.e. differences between models, is greater than parametric uncertainty. We have extended our analysis to emulate vertical BC profiles at several locations in the mid-Pacific Ocean and identify the parameters contributing to uncertainty in the vertical distribution of black carbon at these locations. We will present preliminary comparisons of
Pradhan, Biswabrata; Dewanji, Anup
2009-07-10
In this work, we consider the parametric estimation of quality adjusted lifetime (QAL) distribution in progressive illness-death models. The main idea of this paper is to derive the theoretical distribution of QAL for the progressive illness-death models, under parametric models for the sojourn time distributions in different states, and then replace the model parameters by their estimates obtained by standard techniques of survival analysis. The method of estimation of the model parameters is also described. A data set of IBCSG Trial V has been analyzed for illustration. Extension to more general illness-death models is also discussed.
NASA Astrophysics Data System (ADS)
Daneshkhah, Alireza; Remesan, Renji; Chatrabgoun, Omid; Holman, Ian P.
2016-09-01
This paper highlights the usefulness of the minimum information and parametric pair-copula construction (PCC) to model the joint distribution of flood event properties. Both of these models outperform other standard multivariate copula in modeling multivariate flood data that exhibiting complex patterns of dependence, particularly in the tails. In particular, the minimum information pair-copula model shows greater flexibility and produces better approximation of the joint probability density and corresponding measures have capability for effective hazard assessments. The study demonstrates that any multivariate density can be approximated to any degree of desired precision using minimum information pair-copula model and can be practically used for probabilistic flood hazard assessment.
A convolution model for computing the far-field directivity of a parametric loudspeaker array.
Shi, Chuang; Kajikawa, Yoshinobu
2015-02-01
This paper describes a method to compute the far-field directivity of a parametric loudspeaker array (PLA), whereby the steerable parametric loudspeaker can be implemented when phased array techniques are applied. The convolution of the product directivity and the Westervelt's directivity is suggested, substituting for the past practice of using the product directivity only. Computed directivity of a PLA using the proposed convolution model achieves significant improvement in agreement to measured directivity at a negligible computational cost.
2001-03-14
parametric estimation algorithms of the interference components simplify and improve existing STAP methods. The resulting modeling and processing methods provide new parametric tools to estimate and mitigate the Doppler ambiguous clutter. The estimation algorithms the authors propose enable the estimation of the interference signals using the observations in only a single range gate. The proposed method is particularly suitable for non-stationary clutter and jamming environments. The approach provides a new analytical insight into the STAP
Modeling of finite-amplitude sound beams: second order fields generated by a parametric loudspeaker.
Yang, Jun; Sha, Kan; Gan, Woon-Seng; Tian, Jing
2005-04-01
The nonlinear interaction of sound waves in air has been applied to sound reproduction for audio applications. A directional audible sound can be generated by amplitude-modulating the ultrasound carrier with an audio signal, then transmitting it from a parametric loudspeaker. This brings the need of a computationally efficient model to describe the propagation of finite-amplitude sound beams for the system design and optimization. A quasilinear analytical solution capable of fast numerical evaluation is presented for the second-order fields of the sum-, difference-frequency and second harmonic components. It is based on a virtual-complex-source approach, wherein the source field is treated as an aggregation of a set of complex virtual sources located in complex distance, then the corresponding fundamental sound field is reduced to the computation of sums of simple functions by exploiting the integrability of Gaussian functions. By this result, the five-dimensional integral expressions for the second-order sound fields are simplified to one-dimensional integrals. Furthermore, a substantial analytical reduction to sums of single integrals also is derived for an arbitrary source distribution when the basis functions are expressible as a sum of products of trigonometric functions. The validity of the proposed method is confirmed by a comparison of numerical results with experimental data previously published for the rectangular ultrasonic transducer.
Kernel based model parametrization and adaptation with applications to battery management systems
NASA Astrophysics Data System (ADS)
Weng, Caihao
With the wide spread use of energy storage systems, battery state of health (SOH) monitoring has become one of the most crucial challenges in power and energy research, as SOH significantly affects the performance and life cycle of batteries as well as the systems they are interacting with. Identifying the SOH and adapting of the battery energy/power management system accordingly are thus two important challenges for applications such as electric vehicles, smart buildings and hybrid power systems. This dissertation focuses on the identification of lithium ion battery capacity fading, and proposes an on-board implementable model parametrization and adaptation framework for SOH monitoring. Both parametric and non-parametric approaches that are based on kernel functions are explored for the modeling of battery charging data and aging signature extraction. A unified parametric open circuit voltage model is first developed to improve the accuracy of battery state estimation. Several analytical and numerical methods are then investigated for the non-parametric modeling of battery data, among which the support vector regression (SVR) algorithm is shown to be the most robust and consistent approach with respect to data sizes and ranges. For data collected on LiFePO 4 cells, it is shown that the model developed with the SVR approach is able to predict the battery capacity fading with less than 2% error. Moreover, motivated by the initial success of applying kernel based modeling methods for battery SOH monitoring, this dissertation further exploits the parametric SVR representation for real-time battery characterization supported by test data. Through the study of the invariant properties of the support vectors, a kernel based model parametrization and adaptation framework is developed. The high dimensional optimization problem in the learning algorithm could be reformulated as a parameter estimation problem, that can be solved by standard estimation algorithms such as the
Parametric Modeling in the CAE Process: Creating a Family of Models
NASA Technical Reports Server (NTRS)
Brown, Christopher J.
2011-01-01
This Presentation meant as an example - Give ideas of approaches to use - The significant benefit of PARAMETRIC geometry based modeling The importance of planning before you build Showcase some NX capabilities - Mesh Controls - Associativity - Divide Face - Offset Surface Reminder - This only had to be done once! - Can be used for any cabinet in that "family" Saves a lot of time if pre-planned Allows re-use in the future
A parametric model of the spectral periodicity of stimulus frequency otoacoustic emissions
NASA Astrophysics Data System (ADS)
Lineton, Ben; Lutman, Mark E.
2003-08-01
A model for estimating the spectral period of stimulus frequency otoacoustic emissions (SFOAEs) is presented. The model characterizes the frequency spectrum of an SFOAE in terms of four parameters which can be directly related to cochlear mechanical quantities featuring in the theory of SFOAE generation proposed by Zweig and Shera [J. Acoust. Soc. Am. 98, 2018-2047 (1995)]. The results of applying the parametric model to SFOAEs generated by cochlear models suggest that it gives a sensitive measure of spectral period. It is concluded that the parametric model may be a useful tool for detecting small changes in cochlear function using SFOAE measurements.
NASA Astrophysics Data System (ADS)
Hemmings, J. C. P.; Challenor, P. G.; Yool, A.
2014-09-01
Biogeochemical ocean circulation models used to investigate the role of plankton ecosystems in global change rely on adjustable parameters to compensate for missing biological complexity. In principle, optimal parameter values can be estimated by fitting models to observational data, including satellite ocean colour products such as chlorophyll that achieve good spatial and temporal coverage of the surface ocean. However, comprehensive parametric analyses require large ensemble experiments that are computationally infeasible with global 3-D simulations. Site-based simulations provide an efficient alternative but can only be used to make reliable inferences about global model performance if robust quantitative descriptions of their relationships with the corresponding 3-D simulations can be established. The feasibility of establishing such a relationship is investigated for an intermediate complexity biogeochemistry model (MEDUSA) coupled with a widely-used global ocean model (NEMO). A site-based mechanistic emulator is constructed for surface chlorophyll output from this target model as a function of model parameters. The emulator comprises an array of 1-D simulators and a statistical quantification of the uncertainty in their predictions. The unknown parameter-dependent biogeochemical environment, in terms of initial tracer concentrations and lateral flux information required by the simulators, is a significant source of uncertainty. It is approximated by a mean environment derived from a small ensemble of 3-D simulations representing variability of the target model behaviour over the parameter space of interest. The performance of two alternative uncertainty quantification schemes is examined: a direct method based on comparisons between simulator output and a sample of known target model "truths" and an indirect method that is only partially reliant on knowledge of target model output. In general, chlorophyll records at a representative array of oceanic sites
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.
Parametrically Guided Generalized Additive Models with Application to Mergers and Acquisitions Data
Fan, Jianqing; Maity, Arnab; Wang, Yihui; Wu, Yichao
2012-01-01
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. PMID:23645976
SAMPLE AOR CALCULATION USING ANSYS FULL PARAMETRIC MODEL FOR TANK SST-SX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS parametric 360-degree model for single-shell tank SX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric full model for the single shell tank (SST) SX to deal with asymmetry loading conditions and provide a sample analysis of the SST-SX tank based on analysis of record (AOR) loads. The SST-SX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS SLICE PARAMETRIC MODEL FOR TANK SST-SX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS slice parametric model for single-shell tank SX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for the single shell tank (SST) SX, and provide a sample analysis of the SST-SX tank based on analysis of record (AOR) loads. The SST-SX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS AXISYMMETRIC PARAMETRIC MODEL FOR TANK SST-S
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS axisymmetric parametric model for single-shell tank S and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for single shell tank (SST) S, and provide a sample analysis of SST-S tank based on analysis of record (AOR) loads. The SST-S model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS SLICE PARAMETRIC MODEL FOR TANK SST-BX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS slice parametric model for single-shell tank BX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for the single shell tank (SST) BX, and provide a sample analysis of the SST-BX tank based on analysis of record (AOR) loads. The SST-BX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS SLICE PARAMETRIC MODEL FOR TANK SST-A
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS slice parametric model for single-shell tank A and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for the single shell tank (S) A, and provide a sample analysis of the SST-S tank based on analysis of record (AOR) loads. The SST-A model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS AXISYMMETRIC PARAMETRIC MODEL FOR TANK SST-AX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS axisymmetric parametric model for single-shell tank AX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for single shell tank (SST) AX, and provide a sample analysis of SST-AX tank based on analysis of record (AOR) loads. The SST-AX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS SLICE PARAMETRIC MODEL FOR TANK SST-S
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS slice parametric model for single-shell tank S and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for the single shell tank (SST) S, and provide a sample analysis of the SST-S tank based on analysis of record (AOR) loads. The SST-S model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS SLICE PARAMETRIC MODEL FOR TANK SST-AX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS slice parametric model for single-shell tank AX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for the single shell tank (SST) AX, and provide a sample analysis of the SST-AX tank based on analysis of record (AOR) loads. The SST-AX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS AXISYMMETRIC PARAMETRIC MODEL FOR TANK SST-SX
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS axisymmetric parametric model for single-shell tank SX and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for single shell tank (SST) SX, and provide a sample analysis of the SST-SX tank based on analysis of record (AOR) loads. The SST-SX model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
SAMPLE AOR CALCULATION USING ANSYS AXISYMMETRIC PARAMETRIC MODEL FOR TANK SST-A
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS axisymmetric parametric model for single-shell tank A and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to develop a parametric model for single shell tank (SST) A, and provide a sample analysis of SST-A tank based on analysis of record (AOR) loads. The SST-A model is based on buyer-supplied as-built drawings and information for the AOR for SSTs, encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
Parametric Mass Modeling for Mars Entry, Descent and Landing System Analysis Study
NASA Technical Reports Server (NTRS)
Samareh, Jamshid A.; Komar, D. R.
2011-01-01
This paper provides an overview of the parametric mass models used for the Entry, Descent, and Landing Systems Analysis study conducted by NASA in FY2009-2010. The study examined eight unique exploration class architectures that included elements such as a rigid mid-L/D aeroshell, a lifting hypersonic inflatable decelerator, a drag supersonic inflatable decelerator, a lifting supersonic inflatable decelerator implemented with a skirt, and subsonic/supersonic retro-propulsion. Parametric models used in this study relate the component mass to vehicle dimensions and mission key environmental parameters such as maximum deceleration and total heat load. The use of a parametric mass model allows the simultaneous optimization of trajectory and mass sizing parameters.
Tatarinova, Tatiana; Neely, Michael; Bartroff, Jay; van Guilder, Michael; Yamada, Walter; Bayard, David; Jelliffe, Roger; Leary, Robert; Chubatiuk, Alyona; Schumitzky, Alan
2013-04-01
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian (B) approaches. In this paper we discuss the nonparametric case using both maximum likelihood and Bayesian approaches. We present two nonparametric methods for estimating the unknown joint population distribution of model parameter values in a pharmacokinetic/pharmacodynamic (PK/PD) dataset. The first method is the NP Adaptive Grid (NPAG). The second is the NP Bayesian (NPB) algorithm with a stick-breaking process to construct a Dirichlet prior. Our objective is to compare the performance of these two methods using a simulated PK/PD dataset. Our results showed excellent performance of NPAG and NPB in a realistically simulated PK study. This simulation allowed us to have benchmarks in the form of the true population parameters to compare with the estimates produced by the two methods, while incorporating challenges like unbalanced sample times and sample numbers as well as the ability to include the covariate of patient weight. We conclude that both NPML and NPB can be used in realistic PK/PD population analysis problems. The advantages of one versus the other are discussed in the paper. NPAG and NPB are implemented in R and freely available for download within the Pmetrics package from www.lapk.org.
Neely, Michael; Bartroff, Jay; van Guilder, Michael; Yamada, Walter; Bayard, David; Jelliffe, Roger; Leary, Robert; Chubatiuk, Alyona; Schumitzky, Alan
2013-01-01
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian (B) approazches. In this paper we discuss the nonparametric case using both maximum likelihood and Bayesian approaches. We present two nonparametric methods for estimating the unknown joint population distribution of model parameter values in a pharmacokinetic/pharmacodynamic (PK/PD) dataset. The first method is the NP Adaptive Grid (NPAG). The second is the NP Bayesian (NPB) algorithm with a stick-breaking process to construct a Dirichlet prior. Our objective is to compare the performance of these two methods using a simulated PK/PD dataset. Our results showed excellent performance of NPAG and NPB in a realistically simulated PK study. This simulation allowed us to have benchmarks in the form of the true population parameters to compare with the estimates produced by the two methods, while incorporating challenges like unbalanced sample times and sample numbers as well as the ability to include the covariate of patient weight. We conclude that both NPML and NPB can be used in realistic PK/PD population analysis problems. The advantages of one versus the other are discussed in the paper. NPAG and NPB are implemented in R and freely available for download within the Pmetrics package from www.lapk.org. PMID:23404393
NASA Astrophysics Data System (ADS)
Venkatesan, K.; Ramanujam, R.; Kuppan, P.
2016-04-01
This paper presents a parametric effect, microstructure, micro-hardness and optimization of laser scanning parameters (LSP) on heating experiments during laser assisted machining of Inconel 718 alloy. The laser source used for experiments is a continuous wave Nd:YAG laser with maximum power of 2 kW. The experimental parameters in the present study are cutting speed in the range of 50-100 m/min, feed rate of 0.05-0.1 mm/rev, laser power of 1.25-1.75 kW and approach angle of 60-90°of laser beam axis to tool. The plan of experiments are based on central composite rotatable design L31 (43) orthogonal array. The surface temperature is measured via on-line measurement using infrared pyrometer. Parametric significance on surface temperature is analysed using response surface methodology (RSM), analysis of variance (ANOVA) and 3D surface graphs. The structural change of the material surface is observed using optical microscope and quantitative measurement of heat affected depth that are analysed by Vicker's hardness test. The results indicate that the laser power and approach angle are the most significant parameters to affect the surface temperature. The optimum ranges of laser power and approach angle was identified as 1.25-1.5 kW and 60-65° using overlaid contour plot. The developed second order regression model is found to be in good agreement with experimental values with R2 values of 0.96 and 0.94 respectively for surface temperature and heat affected depth.
NASA Astrophysics Data System (ADS)
Maji, Partha Sona; Roy Chaudhuri, Partha
2016-03-01
In this article, we have presented a new design methodology of obtaining wide band parametric sources based on highly nonlinear chalcogenide material of As2S3. The dispersion profile of the photonic crystal fiber (PCF) has been engineered wisely by reducing the diameter of the second air-hole ring to have a favorable higher order dispersion parameter. The parametric gain dependence upon fiber length, pump power, and different pumping wavelengths has been investigated in detail. Based upon the nonlinear four wave mixing phenomenon, we are able to achieve a wideband parametric amplifier with peak gain of 29 dB with FWHM of ≈2000 nm around the IR wavelength by proper tailoring of the dispersion profile of the PCF with a continuous wave Erbium (Er3+)-doped ZBLAN fiber laser emitting at 2.8 μm as the pump source with an average power of 5 W. The new design methodology will unleash a new dimension to the chalcogenide material based investigation for wavelength translation around IR wavelength band.
Discrete K-valued Logic for Multi-parametrical Modeling of a Robotic Agent
NASA Astrophysics Data System (ADS)
Bykovsky, A. Yu.
K-valued Allen-Givone algebra is potentially a good tool for multi-parametric modeling of robotic and multi-agent systems, because a multiple-valued truth table can be directly applied for the accumulation of expert knowledge and the reconstruction of switching functions. The computational cost for their minimization will limit the real information capacity of such a model.
Zhang, Yu; Manjavacas, Alejandro; Hogan, Nathaniel J; Zhou, Linan; Ayala-Orozco, Ciceron; Dong, Liangliang; Day, Jared K; Nordlander, Peter; Halas, Naomi J
2016-05-11
Active optical processes such as amplification and stimulated emission promise to play just as important a role in nanoscale optics as they have in mainstream modern optics. The ability of metallic nanostructures to enhance optical nonlinearities at the nanoscale has been shown for a number of nonlinear and active processes; however, one important process yet to be seen is optical parametric amplification. Here, we report the demonstration of surface plasmon-enhanced difference frequency generation by integration of a nonlinear optical medium, BaTiO3, in nanocrystalline form within a plasmonic nanocavity. These nanoengineered composite structures support resonances at pump, signal, and idler frequencies, providing large enhancements of the confined fields and efficient coupling of the wavelength-converted idler radiation to the far-field. This nanocomplex works as a nanoscale tunable infrared light source and paves the way for the design and fabrication of a surface plasmon-enhanced optical parametric amplifier.
ERIC Educational Resources Information Center
Dyehouse, Melissa A.
2009-01-01
This study compared the model-data fit of a parametric item response theory (PIRT) model to a nonparametric item response theory (NIRT) model to determine the best-fitting model for use with ordinal-level alternate assessment ratings. The PIRT Generalized Graded Unfolding Model (GGUM) was compared to the NIRT Mokken model. Chi-square statistics…
Bayesian non-parametric inference for stochastic epidemic models using Gaussian Processes
Xu, Xiaoguang; Kypraios, Theodore; O'Neill, Philip D.
2016-01-01
This paper considers novel Bayesian non-parametric methods for stochastic epidemic models. Many standard modeling and data analysis methods use underlying assumptions (e.g. concerning the rate at which new cases of disease will occur) which are rarely challenged or tested in practice. To relax these assumptions, we develop a Bayesian non-parametric approach using Gaussian Processes, specifically to estimate the infection process. The methods are illustrated with both simulated and real data sets, the former illustrating that the methods can recover the true infection process quite well in practice, and the latter illustrating that the methods can be successfully applied in different settings. PMID:26993062
Parametrizing coarse grained models for molecular systems at equilibrium
NASA Astrophysics Data System (ADS)
Kalligiannaki, E.; Chazirakis, A.; Tsourtis, A.; Katsoulakis, M. A.; Plecháč, P.; Harmandaris, V.
2016-10-01
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.
Efficient model reduction of parametrized systems by matrix discrete empirical interpolation
NASA Astrophysics Data System (ADS)
Negri, Federico; Manzoni, Andrea; Amsallem, David
2015-12-01
In this work, we apply a Matrix version of the so-called Discrete Empirical Interpolation (MDEIM) for the efficient reduction of nonaffine parametrized systems arising from the discretization of linear partial differential equations. Dealing with affinely parametrized operators is crucial in order to enhance the online solution of reduced-order models (ROMs). However, in many cases such an affine decomposition is not readily available, and must be recovered through (often) intrusive procedures, such as the empirical interpolation method (EIM) and its discrete variant DEIM. In this paper we show that MDEIM represents a very efficient approach to deal with complex physical and geometrical parametrizations in a non-intrusive, efficient and purely algebraic way. We propose different strategies to combine MDEIM with a state approximation resulting either from a reduced basis greedy approach or Proper Orthogonal Decomposition. A posteriori error estimates accounting for the MDEIM error are also developed in the case of parametrized elliptic and parabolic equations. Finally, the capability of MDEIM to generate accurate and efficient ROMs is demonstrated on the solution of two computationally-intensive classes of problems occurring in engineering contexts, namely PDE-constrained shape optimization and parametrized coupled problems.
Investigating Microvibration Sources Modelling
NASA Astrophysics Data System (ADS)
Addari, Daniele; Aglietti, Guglielmo S.; Remedia, Marcello
2014-06-01
One of the challenges related to microvibration is investigating the characterisation of the microvibration sources (here emphasis is given to reaction wheel assemblies) on board satellites. This usually involves series of experiments to characterise the hardware and produce representative models. Here we present a methodology that gives good estimates covering a wide frequency range and reduce the complexity of the test campaign.In addition, a practical example of coupling between a reaction wheel assembly and a structural panel where the coupled loads have been estimated using the mathematical model and compared with experimental test results (retrieved using an interface load transducer) will be presented, giving indications of the level of accuracy that can be expected from this type of analyses.
Crash risk analysis for Shanghai urban expressways: A Bayesian semi-parametric modeling approach.
Yu, Rongjie; Wang, Xuesong; Yang, Kui; Abdel-Aty, Mohamed
2016-10-01
Urban expressway systems have been developed rapidly in recent years in China; it has become one key part of the city roadway networks as carrying large traffic volume and providing high traveling speed. Along with the increase of traffic volume, traffic safety has become a major issue for Chinese urban expressways due to the frequent crash occurrence and the non-recurrent congestions caused by them. For the purpose of unveiling crash occurrence mechanisms and further developing Active Traffic Management (ATM) control strategies to improve traffic safety, this study developed disaggregate crash risk analysis models with loop detector traffic data and historical crash data. Bayesian random effects logistic regression models were utilized as it can account for the unobserved heterogeneity among crashes. However, previous crash risk analysis studies formulated random effects distributions in a parametric approach, which assigned them to follow normal distributions. Due to the limited information known about random effects distributions, subjective parametric setting may be incorrect. In order to construct more flexible and robust random effects to capture the unobserved heterogeneity, Bayesian semi-parametric inference technique was introduced to crash risk analysis in this study. Models with both inference techniques were developed for total crashes; semi-parametric models were proved to provide substantial better model goodness-of-fit, while the two models shared consistent coefficient estimations. Later on, Bayesian semi-parametric random effects logistic regression models were developed for weekday peak hour crashes, weekday non-peak hour crashes, and weekend non-peak hour crashes to investigate different crash occurrence scenarios. Significant factors that affect crash risk have been revealed and crash mechanisms have been concluded.
A Parametric Cost Model for Estimating Acquisition Costs of Conventional U.S. Navy Surface Ships.
1999-09-01
techniques return cost estimating relationships able to predict average procurement cost from ship light displacement, ship overall length, ship ... propulsion shaft horsepower or number of propulsion engines. The formulated parametric cost model is approximate and appropriate only for rough order of
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.
Preliminary Multi-Variable Parametric Cost Model for Space Telescopes
NASA Technical Reports Server (NTRS)
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.
NASA Astrophysics Data System (ADS)
Braun, David J.; Sutas, Andrius; Vijayakumar, Sethu
2017-01-01
Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.
Modeling Sodium Iodide Detector Response Using Parametric Equations
2013-03-22
Detection Methodologies In 2001 a group of woodcutters in Lja, Georgia found two ‘objects’ in the forest (unshielded strontium -90 sources, each approx...especially between 10 and 20 cm. Comparing the backscatter at 100 cm shows that 89 % of the maximum backscatter registers in the detector versus the 82
Moore, Julia L
2014-01-01
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 nonlinear 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 vs. 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. PMID:24443079
Flexible parametric modelling of the cause-specific cumulative incidence function.
Lambert, Paul C; Wilkes, Sally R; Crowther, Michael J
2017-04-30
Competing risks arise with time-to-event data when individuals are at risk of more than one type of event and the occurrence of one event precludes the occurrence of all other events. A useful measure with competing risks is the cause-specific cumulative incidence function (CIF), which gives the probability of experiencing a particular event as a function of follow-up time, accounting for the fact that some individuals may have a competing event. When modelling the cause-specific CIF, the most common model is a semi-parametric proportional subhazards model. In this paper, we propose the use of flexible parametric survival models to directly model the cause-specific CIF where the effect of follow-up time is modelled using restricted cubic splines. The models provide smooth estimates of the cause-specific CIF with the important advantage that the approach is easily extended to model time-dependent effects. The models can be fitted using standard survival analysis tools by a combination of data expansion and introducing time-dependent weights. Various link functions are available that allow modelling on different scales and have proportional subhazards, proportional odds and relative absolute risks as particular cases. We conduct a simulation study to evaluate how well the spline functions approximate subhazard functions with complex shapes. The methods are illustrated using data from the European Blood and Marrow Transplantation Registry showing excellent agreement between parametric estimates of the cause-specific CIF and those obtained from a semi-parametric model. We also fit models relaxing the proportional subhazards assumption using alternative link functions and/or including time-dependent effects. Copyright © 2016 John Wiley & Sons, Ltd.
Change point models for cognitive tests using semi-parametric maximum likelihood
van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E.
2013-01-01
Random-effects change point models are formulated for longitudinal data obtained from cognitive tests. The conditional distribution of the response variable in a change point model is often assumed to be normal even if the response variable is discrete and shows ceiling effects. For the sum score of a cognitive test, the binomial and the beta-binomial distributions are presented as alternatives to the normal distribution. Smooth shapes for the change point models are imposed. Estimation is by marginal maximum likelihood where a parametric population distribution for the random change point is combined with a non-parametric mixing distribution for other random effects. An extension to latent class modelling is possible in case some individuals do not experience a change in cognitive ability. The approach is illustrated using data from a longitudinal study of Swedish octogenarians and nonagenarians that began in 1991. Change point models are applied to investigate cognitive change in the years before death. PMID:23471297
Logistic distributed activation energy model--Part 1: Derivation and numerical parametric study.
Cai, Junmeng; Jin, Chuan; Yang, Songyuan; Chen, Yong
2011-01-01
A new distributed activation energy model is presented using the logistic distribution to mathematically represent the pyrolysis kinetics of complex solid fuels. A numerical parametric study of the logistic distributed activation energy model is conducted to evaluate the influences of the model parameters on the numerical results of the model. The parameters studied include the heating rate, reaction order, frequency factor, mean of the logistic activation energy distribution, standard deviation of the logistic activation energy distribution. The parametric study addresses the dependence on the forms of the calculated α-T and dα/dT-T curves (α: reaction conversion, T: temperature). The study results would be very helpful to the application of the logistic distributed activation energy model, which is the main subject of the next part of this series.
NASA Astrophysics Data System (ADS)
Brustlein, Sophie; Ferrand, Patrick; Walther, Nico; Brasselet, Sophie; Billaudeau, Cyrille; Marguet, Didier; Rigneault, Hervé
2011-02-01
We present the assets and constraints of using optical parametric oscillators (OPOs) to perform point scanning nonlinear microscopy and spectroscopy with special emphasis on coherent Raman spectroscopy. The difterent possible configurations starting with one OPO and two OPOs are described in detail and with comments that are intended to be practically useful for the user. Explicit examples on test samples such as nonlinear organic crystal, polystyrene beads, and fresh mouse tissues are given. Special emphasis is given to background-free coherent Raman anti-Stokes scattering (CARS) imaging, including CARS hyperspectral imaging in a fully automated mode with commercial OPOs.
Numerical Models of Broad Bandwidth Nanosecond Optical Parametric Oscillators
Bowers, M.S.; Gehr, R.J.; Smith, A.V.
1998-10-14
We describe results from three new methods of numerically modeling broad-bandwidth, nanosecond OPO's in the plane-wave approximate ion. They account for differences in group velocities among the three mixing waves, and also include a qutt~ttun noise model.
Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.
Vayrynen, Eero; Noponen, Kai; Vipin, Ashwati; Thow, X Y; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo
2016-09-01
In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.
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.
Development of lake parametrization in the INMCM climate model
NASA Astrophysics Data System (ADS)
Bogomolov, V.; Stepanenko, V.; Volodin, E.
2016-11-01
Land surface schemes (LSS or terrestrial models) are a crucial component of both Numerical Weather Prediction (NWP) systems and climate models. An important land- surface type is lakes. This paper presents the mechanism of incorporation of a model LAKE into a coupled general circulation model of the atmosphere and ocean INMCM4, with a space resolution 2° to 1.5° and 21 levels in height, with two-way interaction. A new map for 14 land types distribution was created using a digital map of inland waters for the entire globe. The digital map of water bodies includes the fraction of lake area on the land surface, and the average depth of water bodies, both on the grid of the climate model. This digital map is based on a dataset consisting of 14 000 freshwater lakes. In order to increase the time step in the LAKE model, the k-ε parameterization has been replaced by the parameterization of Henderson-Sellers. With the amended INMCM4 model, numerical experiments were carried out to simulate global climate during the second half of the XX century. The effects of the new lake parameterization on the surface temperature and heat fluxes are analyzed.
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.
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-01-01
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. PMID:23275882
A parametric ribcage geometry model accounting for variations among the adult population.
Wang, Yulong; Cao, Libo; Bai, Zhonghao; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen
2016-09-06
The objective of this study is to develop a parametric ribcage model that can account for morphological variations among the adult population. Ribcage geometries, including 12 pair of ribs, sternum, and thoracic spine, were collected from CT scans of 101 adult subjects through image segmentation, landmark identification (1016 for each subject), symmetry adjustment, and template mesh mapping (26,180 elements for each subject). Generalized procrustes analysis (GPA), principal component analysis (PCA), and regression analysis were used to develop a parametric ribcage model, which can predict nodal locations of the template mesh according to age, sex, height, and body mass index (BMI). Two regression models, a quadratic model for estimating the ribcage size and a linear model for estimating the ribcage shape, were developed. The results showed that the ribcage size was dominated by the height (p=0.000) and age-sex-interaction (p=0.007) and the ribcage shape was significantly affected by the age (p=0.0005), sex (p=0.0002), height (p=0.0064) and BMI (p=0.0000). Along with proper assignment of cortical bone thickness, material properties and failure properties, this parametric ribcage model can directly serve as the mesh of finite element ribcage models for quantifying effects of human characteristics on thoracic injury risks.
Brayton Power Conversion System Parametric Design Modelling for Nuclear Electric Propulsion
NASA Technical Reports Server (NTRS)
Ashe, Thomas L.; Otting, William D.
1993-01-01
The parametrically based closed Brayton cycle (CBC) computer design model was developed for inclusion into the NASA LeRC overall Nuclear Electric Propulsion (NEP) end-to-end systems model. The code is intended to provide greater depth to the NEP system modeling which is required to more accurately predict the impact of specific technology on system performance. The CBC model is parametrically based to allow for conducting detailed optimization studies and to provide for easy integration into an overall optimizer driver routine. The power conversion model includes the modeling of the turbines, alternators, compressors, ducting, and heat exchangers (hot-side heat exchanger and recuperator). The code predicts performance to significant detail. The system characteristics determined include estimates of mass, efficiency, and the characteristic dimensions of the major power conversion system components. These characteristics are parametrically modeled as a function of input parameters such as the aerodynamic configuration (axial or radial), turbine inlet temperature, cycle temperature ratio, power level, lifetime, materials, and redundancy.
Geometric Model for a Parametric Study of the Blended-Wing-Body Airplane
NASA Technical Reports Server (NTRS)
Mastin, C. Wayne; Smith, Robert E.; Sadrehaghighi, Ideen; Wiese, Micharl R.
1996-01-01
A parametric model is presented for the blended-wing-body airplane, one concept being proposed for the next generation of large subsonic transports. The model is defined in terms of a small set of parameters which facilitates analysis and optimization during the conceptual design process. The model is generated from a preliminary CAD geometry. From this geometry, airfoil cross sections are cut at selected locations and fitted with analytic curves. The airfoils are then used as boundaries for surfaces defined as the solution of partial differential equations. Both the airfoil curves and the surfaces are generated with free parameters selected to give a good representation of the original geometry. The original surface is compared with the parametric model, and solutions of the Euler equations for compressible flow are computed for both geometries. The parametric model is a good approximation of the CAD model and the computed solutions are qualitatively similar. An optimal NURBS approximation is constructed and can be used by a CAD model for further refinement or modification of the original geometry.
Numerical model of solar dynamic radiator for parametric analysis
NASA Technical Reports Server (NTRS)
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.
Bifurcation analysis of parametrically excited bipolar disorder model
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Hamerly, Ryan; Marandi, Alireza; Jankowski, Marc; Fejer, M. M.; Yamamoto, Yoshihisa; Mabuchi, Hideo
2016-12-01
We develop reduced models that describe half-harmonic generation in a synchronously pumped optical parametric oscillator above threshold, where nonlinearity, dispersion, and group-velocity mismatch are all relevant. These models are based on (1) an eigenmode expansion for low pump powers, (2) a simultonlike sech-pulse ansatz for intermediate powers, and (3) dispersionless box-shaped pulses for high powers. Analytic formulas for pulse compression, degenerate vs nondegenerate operation, and stability are derived and compared to numerical and experimental results.
Novel parametric reduced order model for aeroengine blade dynamics
NASA Astrophysics Data System (ADS)
Yuan, Jie; Allegri, Giuliano; Scarpa, Fabrizio; Rajasekaran, Ramesh; Patsias, Sophoclis
2015-10-01
The work introduces a novel reduced order model (ROM) technique to describe the dynamic behavior of turbofan aeroengine blades. We introduce an equivalent 3D frame model to describe the coupled flexural/torsional mode shapes, with their relevant natural frequencies and associated modal masses. The frame configurations are identified through a structural identification approach based on a simulated annealing algorithm with stochastic tunneling. The cost functions are constituted by linear combinations of relative errors associated to the resonance frequencies, the individual modal assurance criteria (MAC), and on either overall static or modal masses. When static masses are considered the optimized 3D frame can represent the blade dynamic behavior with an 8% error on the MAC, a 1% error on the associated modal frequencies and a 1% error on the overall static mass. When using modal masses in the cost function the performance of the ROM is similar, but the overall error increases to 7%. The approach proposed in this paper is considerably more accurate than state-of-the-art blade ROMs based on traditional Timoshenko beams, and provides excellent accuracy at reduced computational time when compared against high fidelity FE models. A sensitivity analysis shows that the proposed model can adequately predict the global trends of the variations of the natural frequencies when lumped masses are used for mistuning analysis. The proposed ROM also follows extremely closely the sensitivity of the high fidelity finite element models when the material parameters are used in the sensitivity.
Principles of parametric estimation in modeling language competition
Zhang, Menghan; Gong, Tao
2013-01-01
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. PMID:23716678
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.
Non-parametric iterative model constraint graph min-cut for automatic kidney segmentation.
Freiman, M; Kronman, A; Esses, S J; Joskowicz, L; Sosna, J
2010-01-01
We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori estimation of a model-driven Markov random field. A non-parametric hybrid shape and intensity model is treated as a latent variable in the energy functional. The latent model and labeling map that minimize the energy functional are then simultaneously computed with an expectation maximization approach. The main advantages of our method are that it does not assume a fixed parametric prior model, which is subjective to inter-patient variability and registration errors, and that it combines both the model and the image information into a unified graph min-cut based segmentation framework. We evaluated our method on 20 kidneys from 10 CT datasets with and without contrast agent for which ground-truth segmentations were generated by averaging three manual segmentations. Our method yields an average volumetric overlap error of 10.95%, and average symmetric surface distance of 0.79 mm. These results indicate that our method is accurate and robust for kidney segmentation.
Parametric-based brain Magnetic Resonance Elastography using a Rayleigh damping material model.
Petrov, Andrii Y; Sellier, Mathieu; Docherty, Paul D; Chase, J Geoffrey
2014-10-01
The three-parameter Rayleigh damping (RD) model applied to time-harmonic Magnetic Resonance Elastography (MRE) has potential to better characterise fluid-saturated tissue systems. However, it is not uniquely identifiable at a single frequency. One solution to this problem involves simultaneous inverse problem solution of multiple input frequencies over a broad range. As data is often limited, an alternative elegant solution is a parametric RD reconstruction, where one of the RD parameters (μI or ρI) is globally constrained allowing accurate identification of the remaining two RD parameters. This research examines this parametric inversion approach as applied to in vivo brain imaging. Overall, success was achieved in reconstruction of the real shear modulus (μR) that showed good correlation with brain anatomical structures. The mean and standard deviation shear stiffness values of the white and gray matter were found to be 3±0.11kPa and 2.2±0.11kPa, respectively, which are in good agreement with values established in the literature or measured by mechanical testing. Parametric results with globally constrained μI indicate that selecting a reasonable value for the μI distribution has a major effect on the reconstructed ρI image and concomitant damping ratio (ξd). More specifically, the reconstructed ρI image using a realistic μI=333Pa value representative of a greater portion of the brain tissue showed more accurate differentiation of the ventricles within the intracranial matter compared to μI=1000Pa, and ξd reconstruction with μI=333Pa accurately captured the higher damping levels expected within the vicinity of the ventricles. Parametric RD reconstruction shows potential for accurate recovery of the stiffness characteristics and overall damping profile of the in vivo living brain despite its underlying limitations. Hence, a parametric approach could be valuable with RD models for diagnostic MRE imaging with single frequency data.
Parametric Modeling as a Technology of Rapid Prototyping in Light Industry
NASA Astrophysics Data System (ADS)
Tomilov, I. N.; Grudinin, S. N.; Frolovsky, V. D.; Alexandrov, A. A.
2016-04-01
The paper deals with the parametric modeling method of virtual mannequins for the purposes of design automation in clothing industry. The described approach includes the steps of generation of the basic model on the ground of the initial one (obtained in 3D-scanning process), its parameterization and deformation. The complex surfaces are presented by the wireframe model. The modeling results are evaluated with the set of similarity factors. Deformed models are compared with their virtual prototypes. The results of modeling are estimated by the standard deviation factor.
Modelling and validation of magnetorheological brake responses using parametric approach
NASA Astrophysics Data System (ADS)
Z, Zainordin A.; A, Abdullah M.; K, Hudha
2013-12-01
Magnetorheological brake (MR Brake) is one x-by-wire systems which performs better than conventional brake systems. MR brake consists of a rotating disc that is immersed with Magnetorheological Fluid (MR Fluid) in an enclosure of an electromagnetic coil. The applied magnetic field will increase the yield strength of the MR fluid where this fluid was used to decrease the speed of the rotating shaft. The purpose of this paper is to develop a mathematical model to represent MR brake with a test rig. The MR brake model is developed based on actual torque characteristic which is coupled with motion of a test rig. Next, the experimental are performed using MR brake test rig and obtained three output responses known as angular velocity response, torque response and load displacement response. Furthermore, the MR brake was subjected to various current. Finally, the simulation results of MR brake model are then verified with experimental results.
Song, Guo-Zhu; Wu, Fang-Zhou; Zhang, Mei; Yang, Guo-Jian
2016-01-01
Quantum repeater is the key element in quantum communication and quantum information processing. Here, we investigate the possibility of achieving a heralded quantum repeater based on the scattering of photons off single emitters in one-dimensional waveguides. We design the compact quantum circuits for nonlocal entanglement generation, entanglement swapping, and entanglement purification, and discuss the feasibility of our protocols with current experimental technology. In our scheme, we use a parametric down-conversion source instead of ideal single-photon sources to realize the heralded quantum repeater. Moreover, our protocols can turn faulty events into the detection of photon polarization, and the fidelity can reach 100% in principle. Our scheme is attractive and scalable, since it can be realized with artificial solid-state quantum systems. With developed experimental technique on controlling emitter-waveguide systems, the repeater may be very useful in long-distance quantum communication. PMID:27350159
PARAMETRIC STUDY OF GROUND SOURCE HEAT PUMP SYSTEM FOR HOT AND HUMID CLMATE
Zhu, Jiang; Tao, Yong X.
2011-12-15
The U-tube sizes and varied thermal conductivity with different grout materials are studied based on the benchmark residential building in Hot-humid Pensacola, Florida. In this study, the benchmark building is metered and the data is used to validate the simulation model. And a list of comparative simulation cases with varied parameter value are simulated to study the importance of pipe size and grout to the ground source heat pump energy consumption. The simulation software TRNSYS [1] is employed to fulfill this task. The results show the preliminary energy saving based on varied parameters. Future work needs to be conducted for the cost analysis, include the installation cost from contractor and materials cost.
Framework for the Parametric System Modeling of Space Exploration Architectures
NASA Technical Reports Server (NTRS)
Komar, David R.; Hoffman, Jim; Olds, Aaron D.; Seal, Mike D., II
2008-01-01
This paper presents a methodology for performing architecture definition and assessment prior to, or during, program formulation that utilizes a centralized, integrated architecture modeling framework operated by a small, core team of general space architects. This framework, known as the Exploration Architecture Model for IN-space and Earth-to-orbit (EXAMINE), enables: 1) a significantly larger fraction of an architecture trade space to be assessed in a given study timeframe; and 2) the complex element-to-element and element-to-system relationships to be quantitatively explored earlier in the design process. Discussion of the methodology advantages and disadvantages with respect to the distributed study team approach typically used within NASA to perform architecture studies is presented along with an overview of EXAMINE s functional components and tools. An example Mars transportation system architecture model is used to demonstrate EXAMINE s capabilities in this paper. However, the framework is generally applicable for exploration architecture modeling with destinations to any celestial body in the solar system.
Parametric Estimation in a Recurrent Competing Risks Model.
Taylor, Laura L; Peña, Edsel A
2013-01-01
A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the competing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. Maximum likelihood estimators of the parameters of the marginal distribution functions associated with each of the competing risks and also of the system lifetime distribution function are presented. Estimators are derived under perfect and partial repair strategies. Consistency and asymptotic properties of the estimators are obtained. The estimation methods are applied to a data set of failures for cars under warranty. Simulation studies are used to ascertain the small sample properties and the efficiency gains of the resulting estimators.
Magnetoviscoelasticity parametric model of an MR elastomer vibration mitigation device
NASA Astrophysics Data System (ADS)
Zhu, Jun-Tao; Xu, Zhao-Dong; Guo, Ying-Qing
2012-07-01
Both experimental and modeling studies of magnetic field induced viscoelastic properties of magnetorheological (MR) elastomers under different loading cases are discussed. Anisotropic MR elastomer (MRE) samples with different concentrations of carbonyl iron powder, natural rubber and additives are fabricated and four MRE vibration mitigation devices are manufactured to investigate the dynamic viscoelastic properties of MREs under varying magnetic fields, displacement amplitudes and frequencies in the shear mode. The characteristics of the dynamic properties of the MRE devices are obtained in terms of the experimentally determined shear storage modulus and loss factor. These results demonstrate that the MREs exhibit variable stiffness and damping properties. Based on the studies of properties of viscoelastic materials and the experimental results of MREs, a parameter model is proposed to describe MRE performances. The four parameters under various working conditions, such as magnetic field, displacement amplitude and frequency, are identified by using the Matlab optimization algorithm. Comparisons between experimental and numerical results are discussed, and the results show that the proposed parameter model can describe the performances of MRE devices very well.
Klein, Katelyn F; Hu, Jingwen; Reed, Matthew P; Hoff, Carrie N; Rupp, Jonathan D
2015-10-01
Statistical models were developed that predict male and female femur geometry as functions of age, body mass index (BMI), and femur length as part of an effort to develop lower-extremity finite element models with geometries that are parametric with subject characteristics. The process for developing these models involved extracting femur geometry from clinical CT scans of 62 men and 36 women, fitting a template finite element femur mesh to the surface geometry of each patient, and then programmatically determining thickness at each nodal location. Principal component analysis was then performed on the thickness and geometry nodal coordinates, and linear regression models were developed to predict principal component scores as functions of age, BMI, and femur length. The average absolute errors in male and female external surface geometry model predictions were 4.57 and 4.23 mm, and the average absolute errors in male and female thickness model predictions were 1.67 and 1.74 mm. The average error in midshaft cortical bone areas between the predicted geometries and the patient geometries was 4.4%. The average error in cortical bone area between the predicted geometries and a validation set of cadaver femur geometries across 5 shaft locations was 2.9%.
Cheng, Huihui; Luo, Zhengqian; Ye, Chenchun; Huang, Yizhong; Liu, Chun; Cai, Zhiping
2013-01-20
Mid-infrared fiber optical parametric oscillators (MIR FOPOs) based on the degenerate four-wave mixing (DFWM) of tellurite photonic crystal fibers (PCFs) are proposed and modeled for the first time. Using the DFWM coupled-wave equations, numerical simulations are performed to analyze the effects of tellurite PCFs, single-resonant cavity, and pump source on the MIR FOPO performances. The numerical results show that: (1) although a longer tellurite PCF can decrease the pump threshold of MIR FOPOs to a few watts only, the high conversion-efficiency of MIR idler usually requires a short-length optimum PCF with low loss; (2) compared with the single-pass DFWM configurations of the MIR fiber sources published previously, the stable oscillation of signal light in single-resonant cavity can significantly promote the MIR idler output efficiency. With a suggested tellurite PCF as parametric gain medium, the theoretical prediction indicates that such a MIR FOPO could obtain a wide MIR-tunable range and a high conversion efficiency of more than 10%.
Parametric nonlinear lumped element model for circular CMUTs in collapsed mode.
Aydoğdu, Elif; Ozgurluk, Alper; Atalar, Abdullah; Köymen, Hayrettin
2014-01-01
We present a parametric equivalent circuit model for a circular CMUT in collapsed mode. First, we calculate the collapsed membrane deflection, utilizing the exact electrical force distribution in the analytical formulation of membrane deflection. Then we develop a lumped element model of collapsed membrane operation. The radiation impedance for collapsed mode is also included in the model. The model is merged with the uncollapsed mode model to obtain a simulation tool that handles all CMUT behavior, in transmit or receive. Large- and small-signal operation of a single CMUT can be fully simulated for any excitation regime. The results are in good agreement with FEM simulations.
Nonlinear parametric model for Granger causality of time series
NASA Astrophysics Data System (ADS)
Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano
2006-06-01
The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.
Otero, Marta; Zabkova, Miriam; Rodrigues, Alírio E
2005-09-01
Thermal parametric pumping is a cyclic adsorptive process based on periodic changes in the bed temperature simultaneously with flow reversal. This is an innovative technology which may allow removing phenolic compounds from waste solutions to be recovered and recycled. The recovery and/or purification of liquid streams containing phenol and 4-nitrophenol by adsorptive parametric pumping was studied in this work. An automated parametric pumping pilot unit was operated in semi-continuous recuperative mode. The adsorbent used was the polymeric resin Sephabeads SP206 (Mitsubishi Kasei Corporation, Japan) and temperatures of the hot and the cold half-cycles were 333 and 293 K, respectively. Basic data were obtained from batch equilibrium experiments and fixed-bed adsorption. Different experimental conditions were run and two simplified models were used to simulate the results: an equilibrium model and a linear driving force (LDF) model. Experimental and simulated results using the LDF model were in quite good agreement. Purification levels below three orders of magnitude lower than the concentration of the feed solution were obtained for phenol and 4-nitrophenol.
SAMPLE AOR CALCULATION USING ANSYS PARAMETRIC MODEL FOR TANK SST-AY
JULYK, L.J.; MACKEY, T.C.
2003-06-19
This document documents the ANSYS parametric model for double-shell tank AY and provides sample calculation for analysis-of-record mechanical load conditions. The purpose of this calculation is to provide a sample analysis of the DST-AY tanks based on AOR loads, plus loads identified in the Statement of Work (SOW) for CHG contract 92879. This is not an analysis. Instead, the present calculation utilizes the parametric model generated for the double shell tank DST-AY, which is based on Buyer-supplied as-built drawings and information for the analyses of record (AOR) for Double-Shell Tanks (DSTs), encompassing the existing tank load conditions, and evaluates stresses and deformations throughout the tank and surrounding soil mass.
Volterra model of the parametric array loudspeaker operating at ultrasonic frequencies.
Shi, Chuang; Kajikawa, Yoshinobu
2016-11-01
The parametric array loudspeaker (PAL) is an application of the parametric acoustic array in air, which can be applied to transmit a narrow audio beam from an ultrasonic emitter. However, nonlinear distortion is very perceptible in the audio beam. Modulation methods to reduce the nonlinear distortion are available for on-axis far-field applications. For other applications, preprocessing techniques are wanting. In order to develop a preprocessing technique with general applicability to a wide range of operating conditions, the Volterra filter is investigated as a nonlinear model of the PAL in this paper. Limitations of the standard audio-to-audio Volterra filter are elaborated. An improved ultrasound-to-ultrasound Volterra filter is proposed and empirically demonstrated to be a more generic Volterra model of the PAL.
Small parametric model for nonlinear dynamics of large scale cyclogenesis with wind speed variations
NASA Astrophysics Data System (ADS)
Erokhin, Nikolay; Shkevov, Rumen; Zolnikova, Nadezhda; Mikhailovskaya, Ludmila
2016-07-01
It is performed a numerical investigation of a self consistent small parametric model (SPM) for large scale cyclogenesis (RLSC) by usage of connected nonlinear equations for mean wind speed and ocean surface temperature in the tropical cyclone (TC). These equations may describe the different scenario of temporal dynamics of a powerful atmospheric vortex during its full life cycle. The numerical calculations have shown that relevant choice of SPMTs incoming parameters allows to describe the seasonal behavior of regional large scale cyclogenesis dynamics for a given number of TC during the active season. It is shown that SPM allows describe also the variable wind speed variations inside the TC. Thus by usage of the nonlinear small parametric model it is possible to study the features of RLSCTs temporal dynamics during the active season in the region given and to analyze the relationship between regional cyclogenesis parameters and different external factors like the space weather including the solar activity level and cosmic rays variations.
TVC (Thrust Vector Control) Jet Vane Thermal Modeling Using Parametric System Identification
1988-03-18
Parametric system identification procedures, using the software package MATRIXx, are applied to the problem of simulating the thermal response of a...Boundary layer convection and stagnation point heating are considered as thermal inputs, and the associated resistances are estimated. System ... identification is used to determine the appropriate values for the convective resistances and the vane mount thermal sink. The identified model, which is linear
Parametrically guided estimation in nonparametric varying coefficient models with quasi-likelihood
Davenport, Clemontina A.; Maity, Arnab; Wu, Yichao
2015-01-01
Varying coefficient models allow us to generalize standard linear regression models to incorporate complex covariate effects by modeling the regression coefficients as functions of another covariate. For nonparametric varying coefficients, we can borrow the idea of parametrically guided estimation to improve asymptotic bias. In this paper, we develop a guided estimation procedure for the nonparametric varying coefficient models. Asymptotic properties are established for the guided estimators and a method of bandwidth selection via bias-variance tradeoff is proposed. We compare the performance of the guided estimator with that of the unguided estimator via both simulation and real data examples. PMID:26146469
Tsoumpas, Charalampos; Turkheimer, Federico E; Thielemans, Kris
2008-04-01
In dynamic positron emission tomography (PET) studies, the time changing activity of the radiotracer is measured through multiple consecutive frames. Subsequent pixel-by-pixel application of the appropriate kinetic model provides quantitative information in terms of images of the distribution of the physiological parameter of interest. In this context, iterative reconstruction methods may be used to reconstruct for each time frame a static image of appreciable higher quality than the analytical algorithms, especially in low-count cases. Furthermore, if the reconstruction algorithm also models the kinetics of the measured counts, the parametric image is expected to be of even higher quality. In this work, we investigate the methodology to directly reconstruct parametric images in three-dimensional PET when the kinetic model is linear in its parameters (Patlak plot) and compare with indirectly estimated parametric maps, where the radioactivity distribution was estimated by the filtered back projection and ordered subsets expectation maximization algorithms. Both real and simulated data for tracers with irreversible kinetics in brain studies are included. The results demonstrate appreciable smaller standard deviation and mean squared error characteristics for the direct reconstruction. However, some regions may converge slowly. The FBP and ordered subsets expectation maximization (OSEM) indirect estimations have a similar level of bias after matching their resolutions, but OSEM has smaller standard deviation.
Pyka, Martin; Klatt, Sebastian; Cheng, Sen
2014-01-01
Computational models of neural networks can be based on a variety of different parameters. These parameters include, for example, the 3d shape of neuron layers, the neurons' spatial projection patterns, spiking dynamics and neurotransmitter systems. While many well-developed approaches are available to model, for example, the spiking dynamics, there is a lack of approaches for modeling the anatomical layout of neurons and their projections. We present a new method, called Parametric Anatomical Modeling (PAM), to fill this gap. PAM can be used to derive network connectivities and conduction delays from anatomical data, such as the position and shape of the neuronal layers and the dendritic and axonal projection patterns. Within the PAM framework, several mapping techniques between layers can account for a large variety of connection properties between pre- and post-synaptic neuron layers. PAM is implemented as a Python tool and integrated in the 3d modeling software Blender. We demonstrate on a 3d model of the hippocampal formation how PAM can help reveal complex properties of the synaptic connectivity and conduction delays, properties that might be relevant to uncover the function of the hippocampus. Based on these analyses, two experimentally testable predictions arose: (i) the number of neurons and the spread of connections is heterogeneously distributed across the main anatomical axes, (ii) the distribution of connection lengths in CA3-CA1 differ qualitatively from those between DG-CA3 and CA3-CA3. Models created by PAM can also serve as an educational tool to visualize the 3d connectivity of brain regions. The low-dimensional, but yet biologically plausible, parameter space renders PAM suitable to analyse allometric and evolutionary factors in networks and to model the complexity of real networks with comparatively little effort. PMID:25309338
Pyka, Martin; Klatt, Sebastian; Cheng, Sen
2014-01-01
Computational models of neural networks can be based on a variety of different parameters. These parameters include, for example, the 3d shape of neuron layers, the neurons' spatial projection patterns, spiking dynamics and neurotransmitter systems. While many well-developed approaches are available to model, for example, the spiking dynamics, there is a lack of approaches for modeling the anatomical layout of neurons and their projections. We present a new method, called Parametric Anatomical Modeling (PAM), to fill this gap. PAM can be used to derive network connectivities and conduction delays from anatomical data, such as the position and shape of the neuronal layers and the dendritic and axonal projection patterns. Within the PAM framework, several mapping techniques between layers can account for a large variety of connection properties between pre- and post-synaptic neuron layers. PAM is implemented as a Python tool and integrated in the 3d modeling software Blender. We demonstrate on a 3d model of the hippocampal formation how PAM can help reveal complex properties of the synaptic connectivity and conduction delays, properties that might be relevant to uncover the function of the hippocampus. Based on these analyses, two experimentally testable predictions arose: (i) the number of neurons and the spread of connections is heterogeneously distributed across the main anatomical axes, (ii) the distribution of connection lengths in CA3-CA1 differ qualitatively from those between DG-CA3 and CA3-CA3. Models created by PAM can also serve as an educational tool to visualize the 3d connectivity of brain regions. The low-dimensional, but yet biologically plausible, parameter space renders PAM suitable to analyse allometric and evolutionary factors in networks and to model the complexity of real networks with comparatively little effort.
Shang, Yaping; Xu, Jiangming; Wang, Peng; Li, Xiao; Zhou, Pu; Xu, Xiaojun
2016-09-19
The longterm stability of the laser system is very important in many applications. In this letter, an ultra-stable, broadband, mid-infrared (MIR) optical parametric oscillator (OPO) pumped by a super-fluorescent fiber source is demonstrated. An idler MIR output power of 11.3 W with excellent beam quality was obtained and the corresponding pump-to-idler conversion slope efficiency was 15.9%. Furthermore, during 1h measurement at full power operation, the peak-to-peak fluctuation of idler output power was less than 1.9% and the corresponding standard deviation was less than 0.4% RMS, which was much better than that of a traditional single mode fiber laser pumped OPO system (10.9% for peak-to-peak fluctuation and 1.8% RMS for the standard deviation) in another experiment for comparison. To our knowledge, this is the first demonstration on a high-power, ultra-stable OPO system by using the modefree pump source, which offered an effective approach to achieve an ultra-stable MIR source and broadened the range of the super-fluorescent fiber source applications.
Third-order spontaneous parametric down-conversion in thin optical fibers as a photon-triplet source
Corona, Maria; Garay-Palmett, Karina; U'Ren, Alfred B.
2011-09-15
We study the third-order spontaneous parametric down-conversion (TOSPDC) process, as a means to generate entangled photon triplets. Specifically, we consider thin optical fibers as the nonlinear medium to be used as the basis for TOSPDC in configurations where phase matching is attained through the use of more than one fiber transverse modes. Our analysis in this paper, which follows from our earlier paper [Opt. Lett. 36, 190-192 (2011)], aims to supply experimentalists with the details required in order to design a TOSPDC photon-triplet source. Specifically, our analysis focuses on the photon triplet state, on the rate of emission, and on the TOSPDC phase-matching characteristics for the cases of frequency-degenerate and frequency nondegenerate TOSPDC.
NASA Technical Reports Server (NTRS)
Hashemi-Kia, M.; Toossi, M.
1990-01-01
As a result of this work, a reduction procedure has been developed which can be applied to large finite element model of airframe type structures. This procedure, which is tailored to be used with MSC/NASTRAN finite element code, is applied to the full airframe dynamic finite element model of AH-64A Attack Helicopter. The applicability of the resulting reduced model to parametric and optimization studies is examined. Through application of the design sensitivity analysis, the viability and efficiency of this reduction technique has been demonstrated in a vibration reduction study.
Improvement of the Analytical Model of a Laminated Core Parametric Motor
NASA Astrophysics Data System (ADS)
Tajima, Katsubumi; Sato, Tadashi; Sakamoto, Yoshinori
A laminated core parametric induction motor has desirable features and the planer structure to make it possible to reduce the production cost of the motor by mass production. In the past work, we showed the validity to apply the two-dimensional reluctance network analytical model to the dynamic analysis of the motor while the rotor is driving. In this paper, we investigate the improvement the accuracy of the analytical method of the motor by using new reluctance network analytical model of the motor. In this model, the magnetic circuits of the stator and the rotor are connected by the variable reluctances that are expressed as the function of the rotating angle.
Modeling a MEMS deformable mirror using non-parametric estimation techniques.
Guzmán, Dani; Juez, Francisco Javier de Cos; Myers, Richard; Guesalaga, Andrés; Lasheras, Fernando Sánchez
2010-09-27
Using non-parametric estimation techniques, we have modeled an area of 126 actuators of a micro-electro-mechanical deformable mirror with 1024 actuators. These techniques produce models applicable to open-loop adaptive optics, where the turbulent wavefront is measured before it hits the deformable mirror. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. Our experiments have achieved positioning errors of 3.1% rms of the peak-to-peak wavefront excursion.
Vitković, Nikola; Mitić, Jelena; Manić, Miodrag; Trajanović, Miroslav; Husain, Karim; Petrović, Slađana; Arsić, Stojanka
2015-01-01
Geometrically accurate and anatomically correct 3D models of the human bones are of great importance for medical research and practice in orthopedics and surgery. These geometrical models can be created by the use of techniques which can be based on input geometrical data acquired from volumetric methods of scanning (e.g., Computed Tomography (CT)) or on the 2D images (e.g., X-ray). Geometrical models of human bones created in such way can be applied for education of medical practitioners, preoperative planning, etc. In cases when geometrical data about the human bone is incomplete (e.g., fractures), it may be necessary to create its complete geometrical model. The possible solution for this problem is the application of parametric models. The geometry of these models can be changed and adapted to the specific patient based on the values of parameters acquired from medical images (e.g., X-ray). In this paper, Method of Anatomical Features (MAF) which enables creation of geometrically precise and anatomically accurate geometrical models of the human bones is implemented for the creation of the parametric model of the Human Mandible Coronoid Process (HMCP). The obtained results about geometrical accuracy of the model are quite satisfactory, as it is stated by the medical practitioners and confirmed in the literature.
Parametric analysis of three dimensional flow models applied to tidal energy sites in Scotland
NASA Astrophysics Data System (ADS)
Rahman, Anas; Venugopal, Vengatesan
2017-04-01
This paper presents a detailed parametric analysis on various input parameters of two different numerical models, namely Telemac3D and Delft3D, used for the simulation of tidal current flow at potential tidal energy sites in the Pentland Firth in Scotland. The motivation behind this work is to investigate the influence of the input parameters on the above 3D models, as the majority of past research has mainly focused on using the 2D depth-averaged flow models for this region. An extended description of the models setup, along with the utilised parameters is provided. The International Hydrographic Organisation (IHO) tidal gauges and Acoustic Doppler and Current Profiler (ADCP) measurements are used in calibrating model output to ensure the robustness of the models. Extensive parametric study on the impact of varying drag coefficients, roughness formulae and turbulence models has been investigated and reported. The results indicate that both Telemac3D and Delft3D models are able to produce excellent comparison against measured data; however, with Delft3D, the model parameters which provided higher correlation with the measured data, are found to be different from those reported in the previous literature, which could be attributed to the choice of boundary conditions and the mesh size.
NASA Astrophysics Data System (ADS)
Andreadis, G. M.; Podias, A. K. M.; Tsiakaras, P. E.
In the present work, a model-based parametric analysis of the performance of a direct ethanol polymer electrolyte membrane fuel cell (DE-PEMFC) is conducted with the purpose to investigate the effect of several parameters on the cell's operation. The analysis is based on a previously validated one-dimensional mathematical model that describes the operation of a DE-PEMFC in steady state. More precisely, the effect of several operational and structural parameters on (i) the ethanol crossover rate from the anode to the cathode side of the cell, (ii) the parasitic current generation (mixed potential formation) and (iii) the total cell performance is investigated. According to the model predictions it was found that the increase of the ethanol feed concentration leads to higher ethanol crossover rates, higher parasitic currents and higher mixed potential values resulting in the decrease of the cell's power density. However there is an optimum ethanol feed concentration (approximately 1.0 mol L -1) for which the cell power density reaches its highest value. The platinum (Pt) loading of the anode and the cathode catalytic layers affects strongly the cell performance. Higher values of Pt loading of the catalytic layers increase the specific reaction surface area resulting in higher cell power densities. An increase of the anode catalyst loading compared to an equal one of the cathode catalyst loading has greater impact on the cell's power density. Another interesting finding is that increasing the diffusion layers' porosity up to a certain extent, improves the cell power density despite the fact that the parasitic current increases. This is explained by the fact that the reactants' concentrations over the catalysts are increased, leading to lower activation overpotential values, which are the main source of the total cell overpotentials. Moreover, the use of a thicker membrane leads to lower ethanol crossover rate, lower parasitic current and lower mixed potential values
Parametrization of orographic thermal effect on the deep convection triggering in Global Model
NASA Astrophysics Data System (ADS)
Jingmei, Y.; Jean-Yves, G.; Alain, L.
2013-05-01
The work is based on the hypothesis that anabatic winds (or valley breeze) is an important mechanism of deep convection triggering. Induced by the temperature difference between the mountain surface and the environmental air, anabatic winds own a kinetic energy which may eventually overcome the Planet Boundary Layer inhibition (CIN, Convective Inhibition) and allows the associated convection to develop into the free troposphere. This sub-grid scale phenomenon needs a special parametrization in general circulation models (GCMs). Its lack of representation in present GCM versions is thought of being the cause of the deficit of deep convection systems genesis observed in certain orographical zones, as Mount Cameroun in West Africa for example. A valley breeze parametrization has been designed and built in a GCM (LMDZ). The model computes kinetic energy of the valley breeze in relation to the sub-grid scale orographical characteristics (elevation, slope, orientation). It consists of a grid slim layer along the mountain surface. It is coupled with a multi-layers conductive-capacitive soil model. The coupling is accomplished by using the energy budget at the surface of the mountain. The model was tested in the dynamical mode by systematic sensitivity analysis to the principal parameters and to the environmental conditions. It has then been implemented in the 1D version of the GCM (SCM, Single Column Model), coupled with the Emanuel deep convection scheme, and tested against a radiative-convective equilibrium case and the Hapex campaign case. The stationnary solution of the aeraulic part of the model has been adopted for the GCM. The parametrization finally has been introduced in the 3D version of the GCM, in the diagnostic mode (without coupling to the convection process). It gives a spatial distribution of the triggering frequency of deep convection in coherence with that of the satellite image observation in the West Africa region, during the West African Monsoon
Parametric sensitivity analysis of an agro-economic model of management of irrigation water
NASA Astrophysics Data System (ADS)
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.
Constrained parametric model for simultaneous inference of two cumulative incidence functions.
Shi, Haiwen; Cheng, Yu; Jeong, Jong-Hyeon
2013-01-01
We propose a parametric regression model for the cumulative incidence functions (CIFs) commonly used for competing risks data. The model adopts a modified logistic model as the baseline CIF and a generalized odds-rate model for covariate effects, and it explicitly takes into account the constraint that a subject with any given prognostic factors should eventually fail from one of the causes such that the asymptotes of the CIFs should add up to one. This constraint intrinsically holds in a nonparametric analysis without covariates, but is easily overlooked in a semiparametric or parametric regression setting. We hence model the CIF from the primary cause assuming the generalized odds-rate transformation and the modified logistic function as the baseline CIF. Under the additivity constraint, the covariate effects on the competing cause are modeled by a function of the asymptote of the baseline distribution and the covariate effects on the primary cause. The inference procedure is straightforward by using the standard maximum likelihood theory. We demonstrate desirable finite-sample performance of our model by simulation studies in comparison with existing methods. Its practical utility is illustrated in an analysis of a breast cancer dataset to assess the treatment effect of tamoxifen, adjusting for age and initial pathological tumor size, on breast cancer recurrence that is subject to dependent censoring by second primary cancers and deaths.
Animal models of source memory.
Crystal, Jonathon D
2016-01-01
Source memory is the aspect of episodic memory that encodes the origin (i.e., source) of information acquired in the past. Episodic memory (i.e., our memories for unique personal past events) typically involves source memory because those memories focus on the origin of previous events. Source memory is at work when, for example, someone tells a favorite joke to a person while avoiding retelling the joke to the friend who originally shared the joke. Importantly, source memory permits differentiation of one episodic memory from another because source memory includes features that were present when the different memories were formed. This article reviews recent efforts to develop an animal model of source memory using rats. Experiments are reviewed which suggest that source memory is dissociated from other forms of memory. The review highlights strengths and weaknesses of a number of animal models of episodic memory. Animal models of source memory may be used to probe the biological bases of memory. Moreover, these models can be combined with genetic models of Alzheimer's disease to evaluate pharmacotherapies that ultimately have the potential to improve memory.
Modeling Magnetospheric Sources
NASA Technical Reports Server (NTRS)
Walker, Raymond J.; Ashour-Abdalla, Maha; Ogino, Tatsuki; Peroomian, Vahe; Richard, Robert L.
2001-01-01
We have used global magnetohydrodynamic, simulations of the interaction between the solar wind and magnetosphere together with single particle trajectory calculations to investigate the sources of plasma entering the magnetosphere. In all of our calculations solar wind plasma primarily enters the magnetosphere when the field line on which it is convecting reconnects. When the interplanetary magnetic field has a northward component the reconnection is in the polar cusp region. In the simulations plasma in the low latitude boundary layer (LLBL) can be on either open or closed field lines. Open field lines occur when the high latitude reconnection occurs in only one cusp. In the MHD calculations the ionosphere does not contribute significantly to the LLBL for northward IMF. The particle trajectory calculations show that ions preferentially enter in the cusp region where they can be accelerated by non-adiabatic motion across the high latitude electric field. For southward IMF in the MHD simulations the plasma in the middle and inner magnetosphere comes from the inner (ionospheric) boundary of the simulation. Solar wind plasma on open field lines is confined to high latitudes and exits the tailward boundary of the simulation without reaching the plasma sheet. The LLBL is populated by both ionospheric and solar wind plasma. When the particle trajectories are included solar wind ions can enter the middle magnetosphere. We have used both the MHD simulations and the particle calculations to estimate source rates for the magnetosphere which are consistent with those inferred from observations.
X-1 to X-Wings: Developing a Parametric Cost Model
NASA Technical Reports Server (NTRS)
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 modeling of quantile regression coefficient functions with censored and truncated data.
Frumento, Paolo; Bottai, Matteo
2017-02-09
Quantile regression coefficient functions describe how the coefficients of a quantile regression model depend on the order of the quantile. A method for parametric modeling of quantile regression coefficient functions was discussed in a recent article. The aim of the present work is to extend the existing framework to censored and truncated data. We propose an estimator and derive its asymptotic properties. We discuss goodness-of-fit measures, present simulation results, and analyze the data that motivated this article. The described estimator has been implemented in the R package qrcm.
A Parametric Study of Erupting Flux Rope Rotation: Modeling the 'Cartwheel CME' on 9 April 2008
NASA Technical Reports Server (NTRS)
Kliem, B.; Toeroek, T.; Thompson, W. T.
2012-01-01
The rotation of erupting filaments in the solar corona is addressed through a parametric simulation study of unstable, rotating flux ropes in bipolar force-free initial equilibrium. The Lorentz force due to the external shear-field component and the relaxation of tension in the twisted field are the major contributors to the rotation in this model, while reconnection with the ambient field is of minor importance, due to the field's simple structure. In the low-beta corona, the rotation is not guided by the changing orientation of the vertical field component's polarity inversion line with height. The model yields strong initial rotations which saturate in the corona and differ qualitatively from the profile of rotation vs. height obtained in a recent simulation of an eruption without preexisting flux rope. Both major mechanisms writhe the flux rope axis, converting part of the initial twist helicity, and produce rotation profiles which, to a large part, are very similar within a range of shear-twist combinations. A difference lies in the tendency of twist-driven rotation to saturate at lower heights than shear-driven rotation. For parameters characteristic of the source regions of erupting filaments and coronal mass ejections, the shear field is found to be the dominant origin of rotations in the corona and to be required if the rotation reaches angles of order 90 degrees and higher; it dominates even if the twist exceeds the threshold of the helical kink instability. The contributions by shear and twist to the total rotation can be disentangled in the analysis of observations if the rotation and rise profiles are simultaneously compared with model calculations. The resulting twist estimate allows one to judge whether the helical kink instability occurred. This is demonstrated for the erupting prominence in the "Cartwheel CME" on 9 April 2008, which has shown a rotation of approximately 115 deg. up to a height of 1.5 Solar R above the photosphere. Out of a range of
Advanced parametrical modelling of 24 GHz radar sensor IC packaging components
NASA Astrophysics Data System (ADS)
Kazemzadeh, R.; John, W.; Wellmann, J.; Bala, U. B.; Thiede, A.
2011-08-01
This paper deals with the development of an advanced parametrical modelling concept for packaging components of a 24 GHz radar sensor IC used in automotive driver assistance systems. For fast and efficient design of packages for system-in-package modules (SiP), a simplified model for the description of parasitic electromagnetic effects within the package is desirable, as 3-D field computation becomes inefficient due to the high density of conductive elements of the various signal paths in the package. By using lumped element models for the characterization of the conductive components, a fast indication of the design's signal-quality can be gained, but so far does not offer enough flexibility to cover the whole range of geometric arrangements of signal paths in a contemporary package. This work pursues to meet the challenge of developing a flexible and fast package modelling concept by defining parametric lumped-element models for all basic signal path components, e.g. bond wires, vias, strip lines, bumps and balls.
Battaglia, N.; Trac, H.; Cen, R.; Loeb, A.
2013-10-20
We present a new method for modeling inhomogeneous cosmic reionization on large scales. Utilizing high-resolution radiation-hydrodynamic simulations with 2048{sup 3} dark matter particles, 2048{sup 3} gas cells, and 17 billion adaptive rays in a L = 100 Mpc h {sup –1} box, we show that the density and reionization redshift fields are highly correlated on large scales (∼> 1 Mpc h {sup –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 {sup –1}) in order to make mock observations and theoretical predictions.
A photometric approach to parametric modelling for optimising multisegmented photodetector rings
NASA Astrophysics Data System (ADS)
Yoon, P. S.; Siddons, D. P.
2013-06-01
An analytical (theoretical) method for parametric modelling to optimise fluorescent-type x-ray photodetectors has been developed. The primary purpose of this method is to maximise detector's photon-detection efficiency, thereby enhancing its spatial sensitivity. On the basis of the definition of the solid angle, its sensor-target subsystem was fully parametrised in three dimensions. And afterwards real-valued analytical functions of detector's solid angle were derived, leading to a series of further calculations. As a result of this parametric modelling, a miniaturised ultrasensitive photodetector system was designed with its peak total solid angle as large as 0.70 (steradian) at a practical optimum working distance of 3.0 (mm). Subsequent difference-over-sum calculations yield an enhancement in spatial resolution by a factor of four within its linear band. With the application of this optimisation algorithm embedded in this analytical model, one round of prototyping is sufficient to reach its desired spatial sensitivity, resulting in a drastic reduction of prototyping time and cost. Accordingly, this analytical model with full parametrisation has proved itself to be an indispensable and versatile design tool to utilise in a design phase of such position-sensitive photodetectors. It is therefore envisioned that this photometric approach to modelling photodetectors can be augmented for designing different types of optical instruments in a wide range of scientific disciplines.
Logan, R W; Nitta, C K; Chidester, S K
2006-02-28
One of the final steps in building a numerical model of a physical, mechanical, thermal, or chemical process, is to assess its accuracy as well as its sensitivity to input parameters and modeling technique. In this work, we demonstrate one simple process to take a top-down or integral view of the model, one which can implicitly reflect any couplings between parameters, to assess the importance of each aspect of modeling technique. We illustrate with an example of a comparison of a finite element model with data for violent reaction of explosives in accident scenarios. We show the relative importance of each of the main parametric inputs, and the contributions of model form and grid convergence. These can be directly related to the importance factors for the system being analyzed as a whole, and help determine which factors need more attention in future analyses and tests.
Economic policy optimization based on both one stochastic model and the parametric control theory
NASA Astrophysics Data System (ADS)
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)
NASA Astrophysics Data System (ADS)
Weaver, R.; Plesko, C. S.; Gisler, G. R.
2013-12-01
We are performing detailed hydrodynamic simulations of the interaction from a strong explosion with sample Asteroid objects. The purpose of these simulations is to apply modern hydrodynamic codes that have been well verified and validated (V&V) to the problem of mitigating the hazard from a potentially hazardous object (PHO), an asteroid or comet that is on an Earth crossing orbit. The code we use for these simulations is the RAGE code from Los Alamos National Laboratory [1-6]. Initial runs were performed using a spherical object. Next we ran simulations using the shape form from a known asteroid: 25143 Itokawa. This particular asteroid is not a PHO but we use its shape to consider the influence of non-spherical objects. The initial work was performed using 2D cylindrically symmetric simulations and simple geometries. We then performed a major fully 3D simulation. For an Itokawa size object (~500 m) and an explosion energies ranging from 0.5 - 1 megatons, the velocities imparted to all of the PHO "rocks" in all cases were many m/s. The velocities calculated were much larger than escape velocity and would preclude re-assembly of the fragments. The dispersion of the asteroid remnants is very directional from a surface burst, with all fragments moving away from the point of the explosion. This detail can be used to time the intercept for maximum movement off the original orbit. Results from these previous studies will be summarized for background. In the new work presented here we show a variety of parametric studies around these initial simulations. We modified the explosion energy by +/- 20% and varied the internal composition from a few large "rocks" to several hundred smaller rocks. The results of these parametric studies will be presented. We have also extended our work [6],[7] to stand-off nuclear bursts and will present the initial results for the energy deposition by a generic source into the non-uniform composition asteroid. The goal of this new work is to
NASA Astrophysics Data System (ADS)
Fischer, Cornelia; Bartlome, Richard; Sigrist, Markus W.
2005-04-01
In this paper, we present first results of a spectral characterisation of doping substances using a resonant optoacoustic cell and a Nd:YAG laser pumped optical parametric generation (OPG) laser source in the mid-infrared wavelength range between 3.0 and 4.0 μm with periodically poled LiNbO3 as nonlinear medium for the frequency conversion. Single spectra covering a wavelength range of about 220 nm can be conducted within less than 2 hours (3s averaging time, 7s between consecutive data points, about 0.3nm step-width). Despite the large linewidth of the OPG source of 240 GHz (8 cm-1), the laser spectrometer is well suited for the spectral analysis of these large organic molecules as they exhibit structured continuum absorption over a wide spectral range rather than isolated absorption peaks. We present measured spectra of ephedrine, alprenolol, ethacrynic acid, etc. and discuss the potential of laser-based detection of doping substances both as a supplement to existing methods and in view of a fast in situ screening technique at sporting events.
Hybrid Model of Inhomogeneous Solar Wind Plasma Heating by Alfven Wave Spectrum: Parametric Studies
NASA Technical Reports Server (NTRS)
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.
Model rotor high-speed impulsive noise - Parametric variations and full-scale comparisons
NASA Astrophysics Data System (ADS)
Splettstoesser, W. R.; Schultz, K. J.; Schmitz, F. H.; Boxwell, D. A.
1983-05-01
The results of a 1/7-scale model of the AH-1 series helicopter main rotor test in the German-Dutch anechoic wind tunnel are discussed, with emphasis given on exploring the important scaling parameters of helicopter-rotor high-speed impulsive noise. Nondimensional parameters are derived from the governing equations and employed to compare the model rotor measurements with full-scale investigations, using an equivalent in-flight technique. The peak acoustic pressure, impulsive noise directivity, and acoustic waveform of the model are found to scale well in shape and in amplitude with full-scale results. Parametric variations of the model-rotor acoustic measurements, such as the change of the high-speed impulsive noise level over a range of advancing-tip Mach numbers at constant advance ratio or constant velocity, are presented. It is concluded that model-scale rotors can be used to explore potential acoustic design innovations on full-scale helicopters.
Development of Parametric Mass and Volume Models for an Aerospace SOFC/Gas Turbine Hybrid System
NASA Technical Reports Server (NTRS)
Tornabene, Robert; Wang, Xiao-yen; Steffen, Christopher J., Jr.; Freeh, Joshua E.
2005-01-01
In aerospace power systems, mass and volume are key considerations to produce a viable design. The utilization of fuel cells is being studied for a commercial aircraft electrical power unit. Based on preliminary analyses, a SOFC/gas turbine system may be a potential solution. This paper describes the parametric mass and volume models that are used to assess an aerospace hybrid system design. The design tool utilizes input from the thermodynamic system model and produces component sizing, performance, and mass estimates. The software is designed such that the thermodynamic model is linked to the mass and volume model to provide immediate feedback during the design process. It allows for automating an optimization process that accounts for mass and volume in its figure of merit. Each component in the system is modeled with a combination of theoretical and empirical approaches. A description of the assumptions and design analyses is presented.
Nakhaee, F; Law, M
2011-03-01
Parametric survival models have not previously been applied to survival following a diagnosis of HIV/AIDS in Australia. Four different parametric models--exponential, Weibull, log-normal and log-logistic--were applied to data both on HIV-positive cases and on cases diagnosed with AIDS collected through the national HIV/AIDS surveillance system. Using likelihood based goodness-of-fit criteria the Weibull model was found to be the best-fitted model for predicting survival following a diagnosis of HIV infection without and with a diagnosis of AIDS. Several covariates-age, sex, combined HIV exposure category, CD4 cell counts, antiretroviral treatment and AIDS-defining illnesses--were included in the parametric model to predict factors associated with future mortality. Predicted deaths were in agreement with the observed deaths following HIV infection and AIDS. The Weibull model will be applied for future projections of deaths from HIV/AIDS.
Raybaut, Myriam; Schmid, Thomas; Godard, Antoine; Mohamed, Ajmal K; Lefebvre, Michel; Marnas, Fabien; Flamant, Pierre; Bohman, Axel; Geiser, Peter; Kaspersen, Peter
2009-07-01
We report on a 2.05 microm nanosecond master oscillator power amplifier optical parametric source for CO2 differential-absorption lidar. The master oscillator consists of an entangled-cavity nanosecond optical parametric oscillator based on a type II periodically poled lithium niobate crystal that provides highly stable single-longitudinal-mode radiation. The signal emission is amplified by a multistage parametric amplifier to generate up to 11 mJ in a nearly diffraction-limited beam with an M2 quality factor of approximately 1.5 while maintaining single-longitudinal-mode emission with a frequency stability better than 3 MHz rms. This approach can be readily applied to the detection of various greenhouse gases.
Shamshery, Pulkit; Wang, Ruo-Qian; Tran, Davis V; Winter V, Amos G
2017-01-01
Drip irrigation is a means of distributing the exact amount of water a plant needs by dripping water directly onto the root zone. It can produce up to 90% more crops than rain-fed irrigation, and reduce water consumption by 70% compared to conventional flood irrigation. Drip irrigation may enable millions of poor farmers to rise out of poverty by growing more and higher value crops, while not contributing to overconsumption of water. Achieving this impact will require broadening the engineering knowledge required to design new, low-cost, low-power drip irrigation technology, particularly for poor, off-grid communities in developing countries. For more than 50 years, pressure compensating (PC) drip emitters-which can maintain a constant flow rate under variations in pressure, to ensure uniform water distribution on a field-have been designed and optimized empirically. This study presents a parametric model that describes the fluid and solid mechanics that govern the behavior of a common PC emitter architecture, which uses a flexible diaphragm to limit flow. The model was validated by testing nine prototypes with geometric variations, all of which matched predicted performance to within R2 = 0.85. This parametric model will enable irrigation engineers to design new drip emitters with attributes that improve performance and lower cost, which will promote the use of drip irrigation throughout the world.
Parametric modeling of energy filtering by energy barriers in thermoelectric nanocomposites
Zianni, Xanthippi E-mail: xzianni@gmail.com; Narducci, Dario
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
Developing two non-parametric performance models for higher learning institutions
NASA Astrophysics Data System (ADS)
Kasim, Maznah Mat; Kashim, Rosmaini; Rahim, Rahela Abdul; Khan, Sahubar Ali Muhamed Nadhar
2016-08-01
Measuring the performance of higher learning Institutions (HLIs) is a must for these institutions to improve their excellence. This paper focuses on formation of two performance models: efficiency and effectiveness models by utilizing a non-parametric method, Data Envelopment Analysis (DEA). The proposed models are validated by measuring the performance of 16 public universities in Malaysia for year 2008. However, since data for one of the variables is unavailable, an estimate was used as a proxy to represent the real data. The results show that average efficiency and effectiveness scores were 0.817 and 0.900 respectively, while six universities were fully efficient and eight universities were fully effective. A total of six universities were both efficient and effective. It is suggested that the two proposed performance models would work as complementary methods to the existing performance appraisal method or as alternative methods in monitoring the performance of HLIs especially in Malaysia.
Evaluation of parametric models by the prediction error in colorectal cancer survival analysis
Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Orooji, Arezoo; Pourhoseingholi, Mohamad Amin; Zali, Mohammad Reza
2015-01-01
Aim: The aim of this study is to determine the factors influencing predicted survival time for patients with colorectal cancer (CRC) using parametric models and select the best model by predicting error’s technique. Background: Survival models are statistical techniques to estimate or predict the overall time up to specific events. Prediction is important in medical science and the accuracy of prediction is determined by a measurement, generally based on loss functions, called prediction error. Patients and methods: A total of 600 colorectal cancer patients who admitted to the Cancer Registry Center of Gastroenterology and Liver Disease Research Center, Taleghani Hospital, Tehran, were followed at least for 5 years and have completed selected information for this study. Body Mass Index (BMI), Sex, family history of CRC, tumor site, stage of disease and histology of tumor included in the analysis. The survival time was compared by the Log-rank test and multivariate analysis was carried out using parametric models including Log normal, Weibull and Log logistic regression. For selecting the best model, the prediction error by apparent loss was used. Results: Log rank test showed a better survival for females, BMI more than 25, patients with early stage at diagnosis and patients with colon tumor site. Prediction error by apparent loss was estimated and indicated that Weibull model was the best one for multivariate analysis. BMI and Stage were independent prognostic factors, according to Weibull model. Conclusion: In this study, according to prediction error Weibull regression showed a better fit. Prediction error would be a criterion to select the best model with the ability to make predictions of prognostic factors in survival analysis. PMID:26328040
Grain-scale modeling and splash parametrization for aeolian sand transport
NASA Astrophysics Data System (ADS)
Lämmel, Marc; Dzikowski, Kamil; Kroy, Klaus; Oger, Luc; Valance, Alexandre
2017-02-01
The collision of a spherical grain with a granular bed is commonly parametrized by the splash function, which provides the velocity of the rebounding grain and the velocity distribution and number of ejected grains. Starting from elementary geometric considerations and physical principles, like momentum conservation and energy dissipation in inelastic pair collisions, we derive a rebound parametrization for the collision of a spherical grain with a granular bed. Combined with a recently proposed energy-splitting model [Ho et al., Phys. Rev. E 85, 052301 (2012), 10.1103/PhysRevE.85.052301] that predicts how the impact energy is distributed among the bed grains, this yields a coarse-grained but complete characterization of the splash as a function of the impact velocity and the impactor-bed grain-size ratio. The predicted mean values of the rebound angle, total and vertical restitution, ejection speed, and number of ejected grains are in excellent agreement with experimental literature data and with our own discrete-element computer simulations. We extract a set of analytical asymptotic relations for shallow impact geometries, which can readily be used in coarse-grained analytical modeling or computer simulations of geophysical particle-laden flows.
A shape constrained parametric active contour model for breast contour detection.
Lee, Juhun; Muralidhar, Gautam S; Reece, Gregory P; Markey, Mia K
2012-01-01
Quantitative measures of breast morphology can help a breast cancer survivor to understand outcomes of reconstructive surgeries. One bottleneck of quantifying breast morphology is that there are only a few reliable automation algorithms for detecting the breast contour. This study proposes a novel approach for detecting the breast contour, which is based on a parametric active contour model. In addition to employing the traditional parametric active contour model, the proposed approach enforces a mathematical shape constraint based on the catenary curve, which has been previously shown to capture the overall shape of the breast contour reliably. The mathematical shape constraint regulates the evolution of the active contour and helps the contour evolve towards the breast, while minimizing the undesired effects of other structures such as, the nipple/areola and scars. The efficacy of the proposed approach was evaluated on anterior posterior photographs of women who underwent or were scheduled for breast reconstruction surgery including autologous tissue reconstruction. The proposed algorithm shows promising results for detecting the breast contour.
Estimating the loss in expectation of life due to cancer using flexible parametric survival models.
Andersson, Therese M-L; Dickman, Paul W; Eloranta, Sandra; Lambe, Mats; Lambert, Paul C
2013-12-30
A useful summary measure for survival data is the expectation of life, which is calculated by obtaining the area under a survival curve. The loss in expectation of life due to a certain type of cancer is the difference between the expectation of life in the general population and the expectation of life among the cancer patients. This measure is used little in practice as its estimation generally requires extrapolation of both the expected and observed survival. A parametric distribution can be used for extrapolation of the observed survival, but it is difficult to find a distribution that captures the underlying shape of the survival function after the end of follow-up. In this paper, we base our extrapolation on relative survival, because it is more stable and reliable. Relative survival is defined as the observed survival divided by the expected survival, and the mortality analogue is excess mortality. Approaches have been suggested for extrapolation of relative survival within life-table data, by assuming that the excess mortality has reached zero (statistical cure) or has stabilized to a constant. We propose the use of flexible parametric survival models for relative survival, which enables estimating the loss in expectation of life on individual level data by making these assumptions or by extrapolating the estimated linear trend at the end of follow-up. We have evaluated the extrapolation from this model using data on four types of cancer, and the results agree well with observed data.
NASA Technical Reports Server (NTRS)
Schreiner, Samuel S.; Dominguez, Jesus A.; Sibille, Laurent; Hoffman, Jeffrey A.
2015-01-01
We present a parametric sizing model for a Molten Electrolysis Reactor that produces oxygen and molten metals from lunar regolith. The model has a foundation of regolith material properties validated using data from Apollo samples and simulants. A multiphysics simulation of an MRE reactor is developed and leveraged to generate a vast database of reactor performance and design trends. A novel design methodology is created which utilizes this database to parametrically design an MRE reactor that 1) can sustain the required mass of molten regolith, current, and operating temperature to meet the desired oxygen production level, 2) can operate for long durations via joule heated, cold wall operation in which molten regolith does not touch the reactor side walls, 3) can support a range of electrode separations to enable operational flexibility. Mass, power, and performance estimates for an MRE reactor are presented for a range of oxygen production levels. The effects of several design variables are explored, including operating temperature, regolith type/composition, batch time, and the degree of operational flexibility.
Developing integrated parametric planning models for budgeting and managing complex projects
NASA Technical Reports Server (NTRS)
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.
Kvist, Kajsa; Gerster, Mette; Andersen, Per Kragh; Kessing, Lars Vedel
2007-12-30
For recurrent events there is evidence that misspecification of the frailty distribution can cause severe bias in estimated regression coefficients (Am. J. Epidemiol 1998; 149:404-411; Statist. Med. 2006; 25:1672-1684). In this paper we adapt a procedure originally suggested in (Biometrika 1999; 86:381-393) for parallel data for checking the gamma frailty to recurrent events. To apply the model checking procedure, a consistent non-parametric estimator for the marginal gap time distributions is needed. This is in general not possible due to induced dependent censoring in the recurrent events setting, however, in (Biometrika 1999; 86:59-70) a non-parametric estimator for the joint gap time distributions based on the principle of inverse probability of censoring weights is suggested. Here, we attempt to apply this estimator in the model checking procedure and the performance of the method is investigated with simulations and applied to Danish registry data. The method is further investigated using the usual Kaplan-Meier estimator and a marginalized estimator for the marginal gap time distributions. We conclude that the procedure only works when the recurrent event is common and when the intra-individual association between gap times is weak.
NASA Astrophysics Data System (ADS)
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.
High-power, Yb-fiber-laser-pumped, picosecond parametric source tunable across 752-860 nm.
Kumar, S Chaitanya; Kimmelma, O; Ebrahim-Zadeh, M
2012-05-01
We report a stable, high-power source of picosecond pulses in the near-infrared based on intracavity second harmonic generation (SHG) of a MgO:PPLN optical parametric oscillator synchronously pumped at 81 MHz by a mode-locked Yb-fiber laser. By exploiting the large spectral acceptance bandwidth for Type I (oo→e) SHG in β-BaB2O4 and a 5 mm crystal, we have generated picosecond pulses over 752-860 nm spectral range under minimal angle tuning, with as much as 3.5 W of output power at 778 nm and >2 W over 73% of the tuning range, in good beam quality with TEM00 spatial profile and M2<1.4. The SHG output pulses have durations of 15.2 ps, with a spectral bandwidth of ∼3.4 nm at 784 nm. In addition, the oscillator simultaneously provides a signal power of >1 W over 1505-1721 nm (25 THz) and idler power >1.8 W over 2787-3630 nm (25 THz), corresponding to a total (signal plus idler) tuning range of 1059 nm. The SHG, signal, and idler output exhibit passive long-term power stability better than 1.6%, 1.3%, and 1.6% rms, respectively, over 14 h.
Gu, Chenglin; Hu, Minglie; Fan, Jintao; Song, Youjian; Liu, Bowen; Chai, Lu; Wang, Chingyue; Reid, Derryck T
2015-03-09
We report a high average power tunable 51 MHz femtosecond ultraviolet (UV) laser source based on an intra-cavity sum frequency mixing optical parametric oscillator (OPO) pumped by a fiber laser. The UV laser is generated by sum frequency generation (SFG) between the second harmonic of a mode-locked Yb-fiber laser and the signal of the OPO. A non-collinear configuration is used in the SFG to compensate the group velocity mismatch, and to increase the SFG conversion efficiency dramatically. Tunable ultraviolet pulses within the wavelength range from 385 to 400 nm have been produced with a maximum average power of 402 mW and a pulse width of 286 fs at 2 W Yb-fiber laser pump, corresponding to 20.1% near-infrared to UV conversion efficiency at 387 nm. To our knowledge, this is the first demonstration of tunable femtosecond UV pulse generation from a fiber laser pumped OPO, and is also the highest average power tunable UV femtosecond pulses from an OPO.
NASA Astrophysics Data System (ADS)
Wen-Long, Tian; Zhao-Hua, Wang; Jiang-Feng, Zhu; Zhi-Yi, Wei
2016-01-01
We demonstrate a widely tunable near-infrared source from 767 nm to 874 nm generated by the intracavity second harmonic generation (SHG) in an optical parametric oscillator pumped by a Yb:LYSO solid-state laser. The home-made Yb:LYSO oscillator centered at 1035 nm delivers an average power of 2 W and a pulse duration as short as 351 fs. Two MgO doped periodically poled lithium niobates (MgO:PPLN) with grating periods of 28.5-31.5 μm in steps of 0.5 μm and 19.5-21.3 μm in steps of 0.2 μm are used for the OPO and intracavity SHG, respectively. The maximum average output power of 180 mW at 798 nm was obtained and the output pulses have pulse duration of 313 fs at 792 nm if a sech2-pulse shape was assumed. In addition, tunable signal femtosecond pulses from 1428 nm to 1763 nm are also realized with the maximum average power of 355 mW at 1628 nm. Project supported by the National Key Basic Research Program of China (Grant No. 2013CB922402), the National Key Scientific Instruments Development Program of China (Grant No. 2012YQ120047), the National Natural Science Foundation of China (Grant Nos. 61205130 and 11174361), and the Key Deployment Project of Chinese Academy of Sciences (Grant No. KJZD-EW-L11-03).
A model for straight and helical solar jets. II. Parametric study of the plasma beta
NASA Astrophysics Data System (ADS)
Pariat, E.; Dalmasse, K.; DeVore, C. R.; Antiochos, S. K.; Karpen, J. T.
2016-11-01
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. We aim to establish that a single model can generally reproduce the observed properties of these jet-like events. Methods: 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 β on the generation and properties of solar-like jets. Results: The parametric study validates our model of jets for plasma β ranging from 10-3 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 β ≤ 1. We introduces the new result that the plasma β 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 enable us to understand the energisation, triggering, and driving processes of jet-like events. Our model enables 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.
Modeling and Simulation of a Parametrically Resonant Micromirror With Duty-Cycled Excitation.
Shahid, Wajiha; Qiu, Zhen; Duan, Xiyu; Li, Haijun; Wang, Thomas D; Oldham, Kenn R
2014-12-01
High frequency large scanning angle electrostatically actuated microelectromechanical systems (MEMS) mirrors are used in a variety of applications involving fast optical scanning. A 1-D parametrically resonant torsional micromirror for use in biomedical imaging is analyzed here with respect to operation by duty-cycled square waves. Duty-cycled square wave excitation can have significant advantages for practical mirror regulation and/or control. The mirror's nonlinear dynamics under such excitation is analyzed in a Hill's equation form. This form is used to predict stability regions (the voltage-frequency relationship) of parametric resonance behavior over large scanning angles using iterative approximations for nonlinear capacitance behavior of the mirror. Numerical simulations are also performed to obtain the mirror's frequency response over several voltages for various duty cycles. Frequency sweeps, stability results, and duty cycle trends from both analytical and simulation methods are compared with experimental results. Both analytical models and simulations show good agreement with experimental results over the range of duty cycled excitations tested. This paper discusses the implications of changing amplitude and phase with duty cycle for robust open-loop operation and future closed-loop operating strategies.
Modeling and Simulation of a Parametrically Resonant Micromirror With Duty-Cycled Excitation
Shahid, Wajiha; Qiu, Zhen; Duan, Xiyu; Li, Haijun; Wang, Thomas D.; Oldham, Kenn R.
2014-01-01
High frequency large scanning angle electrostatically actuated microelectromechanical systems (MEMS) mirrors are used in a variety of applications involving fast optical scanning. A 1-D parametrically resonant torsional micromirror for use in biomedical imaging is analyzed here with respect to operation by duty-cycled square waves. Duty-cycled square wave excitation can have significant advantages for practical mirror regulation and/or control. The mirror’s nonlinear dynamics under such excitation is analyzed in a Hill’s equation form. This form is used to predict stability regions (the voltage-frequency relationship) of parametric resonance behavior over large scanning angles using iterative approximations for nonlinear capacitance behavior of the mirror. Numerical simulations are also performed to obtain the mirror’s frequency response over several voltages for various duty cycles. Frequency sweeps, stability results, and duty cycle trends from both analytical and simulation methods are compared with experimental results. Both analytical models and simulations show good agreement with experimental results over the range of duty cycled excitations tested. This paper discusses the implications of changing amplitude and phase with duty cycle for robust open-loop operation and future closed-loop operating strategies. PMID:25506188
NASA Astrophysics Data System (ADS)
Alsing, Paul M.
2015-04-01
In this paper we extend the investigation of Adami and Ver Steeg (2014 Class. Quantum Grav. 31 075015) to treat the process of black hole (BH) particle emission effectively as the analogous quantum optical process of parametric down conversion with a dynamical (depleted versus non-depleted) ‘pump’ source mode which models the evaporating BH energy degree of freedom. We investigate both the short time (non-depleted pump) and long time (depleted pump) regimes of the quantum state and its impact on the Holevo channel capacity for commu.nicating information from the far past to the far future in the presence of Hawking radiation. The new feature introduced in this work is the coupling of the emitted Hawking radiation modes through the common BH ‘source pump’ mode which phenomenologically represents a quantized energy degree of freedom of the gravitational field. This (zero-dimensional) model serves as a simplified arena to explore BH particle production/evaporation and back-action effects under an explicitly unitary evolution that enforces quantized energy/particle conservation. Within our analogous quantum optical model we examine the entanglement between two emitted particle/anti-particle and anti-particle/particle pairs coupled via the BH evaporating ‘pump’ source. We also analytically and dynamically verify the ‘Page information time’ for our model, which refers to the conventionally held belief that the information in the BH radiation becomes significant after the BH has evaporated half its initial energy into the outgoing radiation. Lastly, we investigate the effect of BH particle production/evaporation on two modes in the exterior region of the BH event horizon that are initially maximally entangled, when one mode falls inward and interacts with the BH, and the other remains forever outside and non-interacting.
Time-varying linear and nonlinear parametric model for Granger causality analysis.
Li, Yang; Wei, Hua-Liang; Billings, Steve A; Liao, Xiao-Feng
2012-04-01
Statistical measures such as coherence, mutual information, or correlation are usually applied to evaluate the interactions between two or more signals. However, these methods cannot distinguish directions of flow between two signals. The capability to detect causalities is highly desirable for understanding the cooperative nature of complex systems. The main objective of this work is to present a linear and nonlinear time-varying parametric modeling and identification approach that can be used to detect Granger causality, which may change with time and may not be detected by traditional methods. A numerical example, in which the exact causal influences relationships, is presented to illustrate the performance of the method for time-varying Granger causality detection. The approach is applied to EEG signals to track and detect hidden potential causalities. One advantage of the proposed model, compared with traditional Granger causality, is that the results are easier to interpret and yield additional insights into the transient directed dynamical Granger causality interactions.
Heat Transfer Parametric System Identification
1993-06-01
Transfer Parametric System Identification 6. AUTHOR(S Parker, Gregory K. 7. PERFORMING ORGANIZATION NAME(S) AND AOORESS(ES) 8. PERFORMING ORGANIZATION...distribution is unlimited. Heat Transfer Parametric System Identification by Gregory K. Parker Lieutenant, United States Navy BS., DeVry Institute of...Modeling Concept ........ ........... 3 2. Lumped Parameter Approach ...... ......... 4 3. Parametric System Identification ....... 4 B. BASIC MODELING
Parametric Resonance Revisited
NASA Astrophysics Data System (ADS)
van den Broeck, C.; Bena, I.
The phenomenon of parametric resonance is revisited. Several physical examples are reviewed and an exactly solvable model is discussed. A mean field theory is presented for globally coupled parametric oscillators with randomly distributed phases. A new type of collective instability appears, which is similar in nature to that of noise induced phase transitions.
Fuzzy modeling for chaotic systems via interval type-2 T-S fuzzy model with parametric uncertainty
NASA Astrophysics Data System (ADS)
Hasanifard, Goran; Gharaveisi, Ali Akbar; Vali, Mohammad Ali
2014-02-01
A motivation for using fuzzy systems stems in part from the fact that they are particularly suitable for processes when the physical systems or qualitative criteria are too complex to model and they have provided an efficient and effective way in the control of complex uncertain nonlinear systems. To realize a fuzzy model-based design for chaotic systems, it is mostly preferred to represent them by T-S fuzzy models. In this paper, a new fuzzy modeling method has been introduced for chaotic systems via the interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy model. An IT2 fuzzy model is proposed to represent a chaotic system subjected to parametric uncertainty, covered by the lower and upper membership functions of the interval type-2 fuzzy sets. Investigating many well-known chaotic systems, it is obvious that nonlinear terms have a single common variable or they depend only on one variable. If it is taken as the premise variable of fuzzy rules and another premise variable is defined subject to parametric uncertainties, a simple IT2 T-S fuzzy dynamical model can be obtained and will represent many well-known chaotic systems. This IT2 T-S fuzzy model can be used for physical application, chaotic synchronization, etc. The proposed approach is numerically applied to the well-known Lorenz system and Rossler system in MATLAB environment.
NASA Technical Reports Server (NTRS)
Borisenkov, Y. P.
1974-01-01
A small parametric, nonadiabatic model for precomputation of meteorological fields on the basis of complete equations, along with its energetic analogs is described. The model incorporates integral characteristics of the components of the wind speed and the analogous functions of the total fluxes of the ocean, and uses a Cartesian isobaric system of coordinates.
Tropical cyclone wind field asymmetry—Development and evaluation of a new parametric model
NASA Astrophysics Data System (ADS)
Olfateh, Mohammad; Callaghan, David P.; Nielsen, Peter; Baldock, Tom E.
2017-01-01
A new parametric model is developed to describe the wind field asymmetry commonly observed in tropical cyclones or hurricanes in a reference frame fixed at its center. Observations from 21 hurricanes from the North Atlantic basin and TC Roger (1993) in the Coral Sea are analyzed to determine the azimuthal and radial asymmetry typical in these mesoscale systems after removing the forward speed. On the basis of the observations, a new asymmetric directional wind model is proposed which adjusts the widely used Holland (1980) axisymmetric wind model to account for the action of blocking high-pressure systems, boundary layer friction, and forward speed. The model is tested against the observations and demonstrated to capture the physical features of asymmetric cyclones and provides a better fit to observed winds than the Holland model. Optimum values and distributions of the model parameters are derived for use in statistical modeling. Finally, the model is used to investigate the asymmetric character of TC systems, including the azimuth of the maximum wind speed, the degree of asymmetry, and the relationship between asymmetry and forward speed.
NASA Astrophysics Data System (ADS)
Karbon, Maria; Heinkelmann, Robert; Mora-Diaz, Julian; Xu, Minghui; Nilsson, Tobias; Schuh, Harald
2016-09-01
The radio sources within the most recent celestial reference frame (CRF) catalog ICRF2 are represented by a single, time-invariant coordinate pair. The datum sources were chosen mainly according to certain statistical properties of their position time series. Yet, such statistics are not applicable unconditionally, and also ambiguous. However, ignoring systematics in the source positions of the datum sources inevitably leads to a degradation of the quality of the frame and, therefore, also of the derived quantities such as the Earth orientation parameters. One possible approach to overcome these deficiencies is to extend the parametrization of the source positions, similarly to what is done for the station positions. We decided to use the multivariate adaptive regression splines algorithm to parametrize the source coordinates. It allows a great deal of automation, by combining recursive partitioning and spline fitting in an optimal way. The algorithm finds the ideal knot positions for the splines and, thus, the best number of polynomial pieces to fit the data autonomously. With that we can correct the ICRF2 a priori coordinates for our analysis and eliminate the systematics in the position estimates. This allows us to introduce also special handling sources into the datum definition, leading to on average 30 % more sources in the datum. We find that not only the CPO can be improved by more than 10 % due to the improved geometry, but also the station positions, especially in the early years of VLBI, can benefit greatly.
Adams, Matthew S.; Scott, Serena J.; Salgaonkar, Vasant A.; Sommer, Graham; Diederich, Chris J.
2016-01-01
Purpose To investigate endoluminal ultrasound applicator configurations for volumetric thermal ablation and hyperthermia of pancreatic tumors using 3D acoustic and biothermal finite element models. Materials and Methods Parametric studies compared endoluminal heating performance for varying applicator transducer configurations (planar, curvilinear-focused, or radial-diverging), frequencies (1–5 MHz), and anatomical conditions. Patient-specific pancreatic head and body tumor models were used to evaluate feasibility of generating hyperthermia and thermal ablation using an applicator positioned in the duodenal or stomach lumen. Temperature and thermal dose were calculated to define ablation (>240 EM43°C) and moderate hyperthermia (40–45 °C) boundaries, and to assess sparing of sensitive tissues. Proportional-integral control was incorporated to regulate maximum temperature to 70–80 °C for ablation and 45 °C for hyperthermia in target regions. Results Parametric studies indicated that 1–3 MHz planar transducers are most suitable for volumetric ablation, producing 5–8 cm3 lesion volumes for a stationary 5 minute sonication. Curvilinear-focused geometries produce more localized ablation to 20–45 mm depth from the GI tract and enhance thermal sparing (Tmax<42 °C) of the luminal wall. Patient anatomy simulations show feasibility in ablating 60.1–92.9% of head/body tumor volumes (4.3–37.2 cm3) with dose <15 EM43°C in the luminal wall for 18–48 min treatment durations, using 1–3 applicator placements in GI lumen. For hyperthermia, planar and radial-diverging transducers could maintain up to 8 cm3 and 15 cm3 of tissue, respectively, between 40–45 °C for a single applicator placement. Conclusions Modeling studies indicate the feasibility of endoluminal ultrasound for volumetric thermal ablation or hyperthermia treatment of pancreatic tumor tissue. PMID:27097663
Ma, Weiping; Feng, Yang; Chen, Kani; Ying, Zhiliang
2015-11-01
Motivated by modeling and analysis of mass-spectrometry data, a semi- and nonparametric model is proposed that consists of linear parametric components for individual location and scale and a nonparametric regression function for the common shape. A multi-step approach is developed that simultaneously estimates the parametric components and the nonparametric function. Under certain regularity conditions, it is shown that the resulting estimators is consistent and asymptotic normal for the parametric part and achieve the optimal rate of convergence for the nonparametric part when the bandwidth is suitably chosen. Simulation results are presented to demonstrate the effectiveness and finite-sample performance of the method. The method is also applied to a SELDI-TOF mass spectrometry data set from a study of liver cancer patients.
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.
Semiparametric modeling: Correcting low-dimensional model error in parametric models
Berry, Tyrus; Harlim, John
2016-03-01
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.
NASA Technical Reports Server (NTRS)
Dittmar, J. H.
1977-01-01
A high tip speed turboprop is being considered as a future energy conservative airplane. The high tip speed of the propeller combined with the cruise speed of the airplane may result in supersonic relative flow on the propeller tips. These supersonic blade sections could generate noise that is a cabin environment problem. An existing supersonic propeller noise model was parametrically investigated to identify and evaluate the noise reduction variables. Both independent and interdependent parameter variations (constant propeller thrust) were performed. The noise reductions indicated by the independent investigation varied from sizable in the case of reducing Mach number to minimal for adjusting the thickness and loading distributions. The noise reduction possibilities of decreasing relative Mach number were further investigated during the interdependent variations. The interdependent investigation indicated that significant noise reductions could be achieved by increasing the propeller diameter and/or increasing the number of propeller blades while maintaining a constant propeller thrust.
Skew-Quad Parametric-Resonance Ionization Cooling: Theory and Modeling
Afanaciev, Andre; Derbenev, Yaroslav S.; Morozov, Vasiliy; Sy, Amy; Johnson, Rolland P.
2015-09-01
Muon beam ionization cooling is a key component for the next generation of high-luminosity muon colliders. To reach adequately high luminosity without excessively large muon intensities, it was proposed previously to combine ionization cooling with techniques using a parametric resonance (PIC). Practical implementation of PIC proposal is a subject of this report. We show that an addition of skew quadrupoles to a planar PIC channel gives enough flexibility in the design to avoid unwanted resonances, while meeting the requirements of radially-periodic beam focusing at ionization-cooling plates, large dynamic aperture and an oscillating dispersion needed for aberration corrections. Theoretical arguments are corroborated with models and a detailed numerical analysis, providing step-by-step guidance for the design of Skew-quad PIC (SPIC) beamline.
Moment stability for a predator-prey model with parametric dichotomous noises
NASA Astrophysics Data System (ADS)
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).
Parametric geometric model and shape optimization of an underwater glider with blended-wing-body
NASA Astrophysics Data System (ADS)
Sun, Chunya; Song, Baowei; Wang, Peng
2015-11-01
Underwater glider, as a new kind of autonomous underwater vehicles, has many merits such as long-range, extended-duration and low costs. The shape of underwater glider is an important factor in determining the hydrodynamic efficiency. In this paper, a high lift to drag ratio configuration, the Blended-Wing-Body (BWB), is used to design a small civilian under water glider. In the parametric geometric model of the BWB underwater glider, the planform is defined with Bezier curve and linear line, and the section is defined with symmetrical airfoil NACA 0012. Computational investigations are carried out to study the hydrodynamic performance of the glider using the commercial Computational Fluid Dynamics (CFD) code Fluent. The Kriging-based genetic algorithm, called Efficient Global Optimization (EGO), is applied to hydrodynamic design optimization. The result demonstrates that the BWB underwater glider has excellent hydrodynamic performance, and the lift to drag ratio of initial design is increased by 7% in the EGO process.
The Analytical Parametrization of Fusion Barrier by Using the Skyrme Energy-Density Function Model
NASA Astrophysics Data System (ADS)
Zanganeh, V.; Mirzaei, M.; N., Wang
2015-08-01
Using the skyrme energy density formalism, a pocket formula is introduced for barrier heights and positions of 95 fusion reactions (48 ≤ ZP ZT ≤ 1520) with respect to the charge and mass numbers of the interacting nuclei. It is shown that the parameterized values of RB and VB are able to reproduce the corresponding experimental data with good accuracy. Moreover, the absolute errors of our formulas are less than those obtained using the analytical parametrization forms of the fusion barrier based on the proximity versions. The ability of the parameterized forms of the barrier heights and its positions to reproduce the experimental data of the fusion cross section have been analyzed using the Wong model.
Parametric Packet-Layer Model for Evaluation Audio Quality in Multimedia Streaming Services
NASA Astrophysics Data System (ADS)
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.
Fernandez Lastra, C; Gonzalez Lopez, F; Dominguez-Gil, A; Mariño, E L
1988-07-01
The aim of the present study was to attempt to discriminate between single- and two-compartment kinetic models used for calculating the pharmacokinetic parameters of bentazepam when the plasma concentrations of different administrations are used as initial data during multiple dosage regimes. Determination of the best estimated pharmacokinetic parameters was performed using non-linear regression analysis, weighting the data as a function of the error of the analytical technique. Bentazepam was administered at a dose of 25 mg orally at intervals of 8, 12 or 24 h to a total of 9 patients. The mean values of the parameters established for the single-compartment model were Ka = 2.024 h-1; Vd = 2.198 l/kg and Ke = 0.130 h-1. For the two-compartment model these values were: Ka = 2.134 h-1, Vc = 2.049 l/kg, K10 = 0.154 h-1, K12 = 0.042 h-1 and K21 = 0.103 h-1. By application of the MAICE test mean AIC values of 41.62 and 42.52 were obtained for the single- and two-compartment models, respectively. The most suitable kinetic model was determined for each patient according to the predictive nature of the individual parameters of the two kinetic models and by analysis of the residuals of the non-linear regressions of the parametric estimation.
NASA Astrophysics Data System (ADS)
Kozlovská, Mária; Čabala, Jozef; Struková, Zuzana
2014-11-01
Information technology is becoming a strong tool in different industries, including construction. The recent trend of buildings designing is leading up to creation of the most comprehensive virtual building model (Building Information Model) in order to solve all the problems relating to the project as early as in the designing phase. Building information modelling is a new way of approaching to the design of building projects documentation. Currently, the building site layout as a part of the building design documents has a very little support in the BIM environment. Recently, the research of designing the construction process conditions has centred on improvement of general practice in planning and on new approaches to construction site layout planning. The state of art in field of designing the construction process conditions indicated an unexplored problem related to connection of knowledge system with construction site facilities (CSF) layout through interactive modelling. The goal of the paper is to present the methodology for execution of 3D construction site facility allocation model (3D CSF-IAM), based on principles of parametric and interactive modelling.
Peng, Nie; Bang-Fa, Ni; Wei-Zhi, Tian
2013-02-01
Application of effective interaction depth (EID) principle for parametric normalization of full energy peak efficiencies at different counting positions, originally for quasi-point sources, has been extended to bulky sources (within ∅30 mm×40 mm) with arbitrary matrices. It is also proved that the EID function for quasi-point source can be directly used for cylindrical bulky sources (within ∅30 mm×40 mm) with the geometric center as effective point source for low atomic number (Z) and low density (D) media and high energy γ-rays. It is also found that in general EID for bulky sources is dependent upon Z and D of the medium and the energy of the γ-rays in question. In addition, the EID principle was theoretically verified by MCNP calculations.
The use of algorithmic behavioural transfer functions in parametric EO system performance models
NASA Astrophysics Data System (ADS)
Hickman, Duncan L.; Smith, Moira I.
2015-10-01
The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach
NASA Astrophysics Data System (ADS)
Wang, Bao; Zhao, Zhixiong; Wei, Guo-Wei
2016-09-01
In this work, a systematic protocol is proposed to automatically parametrize the non-polar part of implicit solvent models with polar and non-polar components. The proposed protocol utilizes either the classical Poisson model or the Kohn-Sham density functional theory based polarizable Poisson model for modeling polar solvation free energies. Four sets of radius parameters are combined with four sets of charge force fields to arrive at a total of 16 different parametrizations for the polar component. For the non-polar component, either the standard model of surface area, molecular volume, and van der Waals interactions or a model with atomic surface areas and molecular volume is employed. To automatically parametrize a non-polar model, we develop scoring and ranking algorithms to classify solute molecules. The their non-polar parametrization is obtained based on the assumption that similar molecules have similar parametrizations. A large database with 668 experimental data is collected and employed to validate the proposed protocol. The lowest leave-one-out root mean square (RMS) error for the database is 1.33 kcal/mol. Additionally, five subsets of the database, i.e., SAMPL0-SAMPL4, are employed to further demonstrate that the proposed protocol. The optimal RMS errors are 0.93, 2.82, 1.90, 0.78, and 1.03 kcal/mol, respectively, for SAMPL0, SAMPL1, SAMPL2, SAMPL3, and SAMPL4 test sets. The corresponding RMS errors for the polarizable Poisson model with the Amber Bondi radii are 0.93, 2.89, 1.90, 1.16, and 1.07 kcal/mol, respectively.
NASA Technical Reports Server (NTRS)
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.
Parametric modeling for quantitative analysis of pulmonary structure to function relationships
NASA Astrophysics Data System (ADS)
Haider, Clifton R.; Bartholmai, Brian J.; Holmes, David R., III; Camp, Jon J.; Robb, Richard A.
2005-04-01
While lung anatomy is well understood, pulmonary structure-to-function relationships such as the complex elastic deformation of the lung during respiration are less well documented. Current methods for studying lung anatomy include conventional chest radiography, high-resolution computed tomography (CT scan) and magnetic resonance imaging with polarized gases (MRI scan). Pulmonary physiology can be studied using spirometry or V/Q nuclear medicine tests (V/Q scan). V/Q scanning and MRI scans may demonstrate global and regional function. However, each of these individual imaging methods lacks the ability to provide high-resolution anatomic detail, associated pulmonary mechanics and functional variability of the entire respiratory cycle. Specifically, spirometry provides only a one-dimensional gross estimate of pulmonary function, and V/Q scans have poor spatial resolution, reducing its potential for regional assessment of structure-to-function relationships. We have developed a method which utilizes standard clinical CT scanning to provide data for computation of dynamic anatomic parametric models of the lung during respiration which correlates high-resolution anatomy to underlying physiology. The lungs are segmented from both inspiration and expiration three-dimensional (3D) data sets and transformed into a geometric description of the surface of the lung. Parametric mapping of lung surface deformation then provides a visual and quantitative description of the mechanical properties of the lung. Any alteration in lung mechanics is manifest by alterations in normal deformation of the lung wall. The method produces a high-resolution anatomic and functional composite picture from sparse temporal-spatial methods which quantitatively illustrates detailed anatomic structure to pulmonary function relationships impossible for translational methods to provide.
ERIC Educational Resources Information Center
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…
Reis, Yara; Bernardo-Faura, Marti; Richter, Daniela; Wolf, Thomas; Brors, Benedikt; Hamacher-Brady, Anne; Eils, Roland; Brady, Nathan R
2012-01-01
Mitochondria exist as a network of interconnected organelles undergoing constant fission and fusion. Current approaches to study mitochondrial morphology are limited by low data sampling coupled with manual identification and classification of complex morphological phenotypes. Here we propose an integrated mechanistic and data-driven modeling approach to analyze heterogeneous, quantified datasets and infer relations between mitochondrial morphology and apoptotic events. We initially performed high-content, multi-parametric measurements of mitochondrial morphological, apoptotic, and energetic states by high-resolution imaging of human breast carcinoma MCF-7 cells. Subsequently, decision tree-based analysis was used to automatically classify networked, fragmented, and swollen mitochondrial subpopulations, at the single-cell level and within cell populations. Our results revealed subtle but significant differences in morphology class distributions in response to various apoptotic stimuli. Furthermore, key mitochondrial functional parameters including mitochondrial membrane potential and Bax activation, were measured under matched conditions. Data-driven fuzzy logic modeling was used to explore the non-linear relationships between mitochondrial morphology and apoptotic signaling, combining morphological and functional data as a single model. Modeling results are in accordance with previous studies, where Bax regulates mitochondrial fragmentation, and mitochondrial morphology influences mitochondrial membrane potential. In summary, we established and validated a platform for mitochondrial morphological and functional analysis that can be readily extended with additional datasets. We further discuss the benefits of a flexible systematic approach for elucidating specific and general relationships between mitochondrial morphology and apoptosis.
NASA Astrophysics Data System (ADS)
Giron Palomares, Jose Benjamin; Hsieh, Sheng-Jen
2014-05-01
A methodology based on active infrared thermography to study and characterize hidden solder joint shapes on a multi cover PCB assembly was investigated. A numerical model was developed to simulate the active thermography methodology and was proven to determine the grand average cooling rates with maximum errors of 8.85% (one cover) and 13.36% (two covers). A parametric analysis was performed by varying the number of covers, heat flux provided, and the amount of heating time. Grand average cooling rate distances among contiguous solder joint shapes, as well as solder joints discriminability, were determined to be directly proportional to heat flux, and inversely proportional to the number of covers and heating time. Finally, a mathematical model was developed to determine the appropriate total amount of energy needed to discriminate among hidden solder joints with a "good" discriminability for one and two covers, and a "regular" discriminability for up to five covers. The mathematical model was proven to predict the total amount of energy to achieve a "good" discriminability for one cover within a 10% of error with respect to the experimental active thermography model.
Bilgili, D; Ryu, D; Ergönül, Ö; Ebrahimi, N
2016-03-01
Infectious diseases that can be spread directly or indirectly from one person to another are caused by pathogenic microorganisms such as bacteria, viruses, parasites, or fungi. Infectious diseases remain one of the greatest threats to human health and the analysis of infectious disease data is among the most important application of statistics. In this article, we develop Bayesian methodology using parametric bivariate accelerated lifetime model to study dependency between the colonization and infection times for Acinetobacter baumannii bacteria which is leading cause of infection among the hospital infection agents. We also study their associations with covariates such as age, gender, apache score, antibiotics use 3 months before admission and invasive mechanical ventilation use. To account for singularity, we use Singular Bivariate Extreme Value distribution to model residuals in Bivariate Accelerated lifetime model under the fully Bayesian framework. We analyze a censored data related to the colonization and infection collected in five major hospitals in Turkey using our methodology. The data analysis done in this article is for illustration of our proposed method and can be applied to any situation that our model can be used.
Jet-induced ground effects on a parametric flat-plate model in hover
NASA Technical Reports Server (NTRS)
Wardwell, Douglas A.; Hange, Craig E.; Kuhn, Richard E.; Stewart, Vearl R.
1993-01-01
The jet-induced forces generated on short takeoff and vertical landing (STOVL) aircraft when in close proximity to the ground can have a significant effect on aircraft performance. Therefore, accurate predictions of these aerodynamic characteristics are highly desirable. Empirical procedures for estimating jet-induced forces during the vertical/short takeoff and landing (V/STOL) portions of the flight envelope are currently limited in accuracy. The jet-induced force data presented significantly add to the current STOVL configurations data base. Further development of empirical prediction methods for jet-induced forces, to provide more configuration diversity and improved overall accuracy, depends on the viability of this STOVL data base. The data base may also be used to validate computational fluid dynamics (CFD) analysis codes. The hover data obtained at the NASA Ames Jet Calibration and Hover Test (JCAHT) facility for a parametric flat-plate model is presented. The model tested was designed to allow variations in the planform aspect ratio, number of jets, nozzle shape, and jet location. There were 31 different planform/nozzle configurations tested. Each configuration had numerous pressure taps installed to measure the pressures on the undersurface of the model. All pressure data along with the balance jet-induced lift and pitching-moment increments are tabulated. For selected runs, pressure data are presented in the form of contour plots that show lines of constant pressure coefficient on the model undersurface. Nozzle-thrust calibrations and jet flow-pressure survey information are also provided.
NASA Astrophysics Data System (ADS)
Franzmann, E. L.; Fiege, J. D.
2016-12-01
We introduce a software package called PolCat for modelling magnetized molecular cloud cores using submillimetre linear polarization and continuum intensity maps from thermal dust emission. Our PolCat modelling software builds a three-dimensional triaxial core model via the use of consecutive parametrized coordinate transformations, and produces simulated polarization maps to fit to observational datasets. We utilize a multi-objective evolutionary optimizer to search the parameter space to simultaneously minimize χ2 for the intensity and polarization position angle maps. The aim of this paper is to test PolCat by applying it to several artificial data sets, characterizing the capabilities and performance of the code using approximately 400 test runs. We find that PolCat is able to distinguish between polarization maps of twisted and non-twisted field geometries and identify the symmetry of the twist when one exists in the data. PolCat generally obtains the correct shapes of cores when fit to models with the correct field geometry. We characterized the degeneracy of our models due to orientation, finding that there are at least eight degenerate core orientations that produce identical polarization maps for the case of triaxial cores. The degeneracy increases with core symmetry. We expect PolCat to be a useful tool for modelling observational polarization data sets. Our tests demonstrate that the code can often eliminate incorrect field configurations, while finding a range or potential models that can explain the data. Physical considerations can often further reduce the set of allowed models, resulting in reasonable constraints on field geometry.
NASA Technical Reports Server (NTRS)
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.
Update on Multi-Variable Parametric Cost Models for Ground and Space Telescopes
NASA Technical Reports Server (NTRS)
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.
Towards a Multi-Variable Parametric Cost Model for Ground and Space Telescopes
NASA Technical Reports Server (NTRS)
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).
NASA Technical Reports Server (NTRS)
Gersh-Range, Jessica A.; Arnold, William R.; Peck, Mason A.; Stahl, H. Philip
2011-01-01
Since future astrophysics missions require space telescopes with apertures of at least 10 meters, there is a need for on-orbit assembly methods that decouple the size of the primary mirror from the choice of launch vehicle. One option is to connect the segments edgewise using mechanisms analogous to damped springs. To evaluate the feasibility of this approach, a parametric ANSYS model that calculates the mode shapes, natural frequencies, and disturbance response of such a mirror, as well as of the equivalent monolithic mirror, has been developed. This model constructs a mirror using rings of hexagonal segments that are either connected continuously along the edges (to form a monolith) or at discrete locations corresponding to the mechanism locations (to form a segmented mirror). As an example, this paper presents the case of a mirror whose segments are connected edgewise by mechanisms analogous to a set of four collocated single-degree-of-freedom damped springs. The results of a set of parameter studies suggest that such mechanisms can be used to create a 15-m segmented mirror that behaves similarly to a monolith, although fully predicting the segmented mirror performance would require incorporating measured mechanism properties into the model. Keywords: segmented mirror, edgewise connectivity, space telescope
Cabras, Stefano; Castellanos, Maria Eugenia; Perra, Silvia
2014-11-20
This paper considers the problem of selecting a set of regressors when the response variable is distributed according to a specified parametric model and observations are censored. Under a Bayesian perspective, the most widely used tools are Bayes factors (BFs), which are undefined when improper priors are used. In order to overcome this issue, fractional (FBF) and intrinsic (IBF) BFs have become common tools for model selection. Both depend on the size, Nt , of a minimal training sample (MTS), while the IBF also depends on the specific MTS used. In the case of regression with censored data, the definition of an MTS is problematic because only uncensored data allow to turn the improper prior into a proper posterior and also because full exploration of the space of the MTSs, which includes also censored observations, is needed to avoid bias in model selection. To address this concern, a sequential MTS was proposed, but it has the drawback of an increase of the number of possible MTSs as Nt becomes random. For this reason, we explore the behaviour of the FBF, contextualizing its definition to censored data. We show that these are consistent, providing also the corresponding fractional prior. Finally, a large simulation study and an application to real data are used to compare IBF, FBF and the well-known Bayesian information criterion.
A Recurrent Network Model of Somatosensory Parametric Working Memory in the Prefrontal Cortex
Miller, Paul; Brody, Carlos D; Romo, Ranulfo; Wang, Xiao-Jing
2015-01-01
A parametric working memory network stores the information of an analog stimulus in the form of persistent neural activity that is monotonically tuned to the stimulus. The family of persistent firing patterns with a continuous range of firing rates must all be realizable under exactly the same external conditions (during the delay when the transient stimulus is withdrawn). How this can be accomplished by neural mechanisms remains an unresolved question. Here we present a recurrent cortical network model of irregularly spiking neurons that was designed to simulate a somatosensory working memory experiment with behaving monkeys. Our model reproduces the observed positively and negatively monotonic persistent activity, and heterogeneous tuning curves of memory activity. We show that fine-tuning mathematically corresponds to a precise alignment of cusps in the bifurcation diagram of the network. Moreover, we show that the fine-tuned network can integrate stimulus inputs over several seconds. Assuming that such time integration occurs in neural populations downstream from a tonically persistent neural population, our model is able to account for the slow ramping-up and ramping-down behaviors of neurons observed in prefrontal cortex. PMID:14576212
Solar tower power plant using a particle-heated steam generator: Modeling and parametric study
NASA Astrophysics Data System (ADS)
Krüger, Michael; Bartsch, Philipp; Pointner, Harald; Zunft, Stefan
2016-05-01
Within the framework of the project HiTExStor II, a system model for the entire power plant consisting of volumetric air receiver, air-sand heat exchanger, sand storage system, steam generator and water-steam cycle was implemented in software "Ebsilon Professional". As a steam generator, the two technologies fluidized bed cooler and moving bed heat exchangers were considered. Physical models for the non-conventional power plant components as air- sand heat exchanger, fluidized bed coolers and moving bed heat exchanger had to be created and implemented in the simulation environment. Using the simulation model for the power plant, the individual components and subassemblies have been designed and the operating parameters were optimized in extensive parametric studies in terms of the essential degrees of freedom. The annual net electricity output for different systems was determined in annual performance calculations at a selected location (Huelva, Spain) using the optimized values for the studied parameters. The solution with moderate regenerative feed water heating has been found the most advantageous. Furthermore, the system with moving bed heat exchanger prevails over the system with fluidized bed cooler due to a 6 % higher net electricity yield.
Parametric modeling and stagger angle optimization of an axial flow fan
NASA Astrophysics Data System (ADS)
Li, M. X.; Zhang, C. H.; Liu, Y.; Y Zheng, S.
2013-12-01
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%.
Application of a Momentum Source Model to the RAH-66 Comanche FANTAIL
NASA Technical Reports Server (NTRS)
Nygaard, Tor A.; Dimanlig, Arsenio C.; Meadowcroft, Edward T.
2004-01-01
A Momentum Source Model has been revised and implemented in the flow solver OVERFLOW-D. In this approach, the fan forces are evaluated from two-dimensional airfoil tables as a function of local Mach number and angle-of-attack and applied as source terms in the discretized Navier-Stokes equations. The model revisions include a new model for forces in the tip region and axial distribution of the source terms. The model revisions improve the results significantly. The Momentum Source Model agrees well with a discrete blade model for all computed collective pitch angles. The two models agree well with experimental data for thrust vs. torque. The Momentum Source Model is a good complement to Discrete Blade Models for ducted fan computations. The lower computational and labor costs make parametric studies, optimization studies and interactional aerodynamics studies feasible for cases beyond what is practical with a Discrete Blade Model today.
Hess, Jeremy J.; Ebi, Kristie L.; Markandya, Anil; Balbus, John M.; Wilkinson, Paul; Haines, Andy; Chalabi, Zaid
2014-01-01
simultaneously improving health. Citation: Remais JV, Hess JJ, Ebi KL, Markandya A, Balbus JM, Wilkinson P, Haines A, Chalabi Z. 2014. Estimating the health effects of greenhouse gas mitigation strategies: addressing parametric, model, and valuation challenges. Environ Health Perspect 122:447–455; http://dx.doi.org/10.1289/ehp.1306744 PMID:24583270
Kimel-Naor, Shani; Abboud, Shimon; Arad, Marina
2016-08-01
Osteoporosis is defined as bone microstructure deterioration resulting a decrease of bone's strength. Measured bone mineral density (BMD) constitutes the main tool for Osteoporosis diagnosis, management, and defines patient's fracture risk. In the present study, parametric electrical impedance tomography (pEIT) method was examined for monitoring BMD, using a computerized simulation model and preliminary real measurements. A numerical solver was developed to simulate surface potentials measured over a 3D computerized pelvis model. Varying cortical and cancellous BMD were simulated by changing bone conductivity and permittivity. Up to 35% and 16% change was found in the real and imaginary modules of the calculated potential, respectively, while BMD changes from 100% (normal) to 60% (Osteoporosis). Negligible BMD relative error was obtained with SNR>60 [dB]. Position changes errors indicate that for long term monitoring, measurement should be taken at the same geometrical configuration with great accuracy. The numerical simulations were compared to actual measurements that were acquired from a healthy male subject using a five electrodes belt bioimpedance device. The results suggest that pEIT may provide an inexpensive easy to use tool for frequent monitoring BMD in small clinics during pharmacological treatment, as a complementary method to DEXA test.
NASA Astrophysics Data System (ADS)
Ding, Baocang; Pan, Hongguang
2016-08-01
The output feedback robust model predictive control (MPC), for the linear parameter varying (LPV) system with norm-bounded disturbance, is addressed, where the model parametric matrices are only known to be bounded within a polytope. The previous techniques of norm-bounding technique, quadratic boundedness (QB), dynamic output feedback, and ellipsoid (true-state bound; TSB) refreshment formula for guaranteeing recursive feasibility, are fused into the newly proposed approaches. In the notion of QB, the full Lyapunov matrix is applied for the first time in this context. The single-step dynamic output feedback robust MPC, where the infinite-horizon control moves are parameterised as a dynamic output feedback law, is the main topic of this paper, while the multi-step method is also suggested. In order to strictly guarantee the physical constraints, the outer bound of the true state replaces the true state itself, so tightness of this bound has a major effect on the control performance. In order to tighten the TSB, a procedure for refreshing the real-time ellipsoid based on that of the last sampling instant is given. This paper is conclusive for the past results and far-reaching for the future researches. Two benchmark examples are given to show the effectiveness of the novel results.
Integrated System-Level Optimization for Concurrent Engineering With Parametric Subsystem Modeling
NASA Technical Reports Server (NTRS)
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.
Vorontsov, Sergei V.; Jefferies, Stuart M. E-mail: stuartj@ifa.hawaii.edu
2013-11-20
We describe a global parametric model for the observed power spectra of solar oscillations of intermediate and low degree. A physically motivated parameterization is used as a substitute for a direct description of mode excitation and damping as these mechanisms remain poorly understood. The model is targeted at the accurate fitting of power spectra coming from Doppler-velocity measurements and uses an adaptive response function that accounts for both the vertical and horizontal components of the velocity field on the solar surface and for possible instrumental and observational distortions. The model is continuous in frequency, can easily be adapted to intensity measurements, and extends naturally to the analysis of high-frequency pseudomodes (interference peaks at frequencies above the atmospheric acoustic cutoff).
Dynamic modelling and stability parametric analysis of a flexible spacecraft with fuel slosh
NASA Astrophysics Data System (ADS)
Gasbarri, Paolo; Sabatini, Marco; Pisculli, Andrea
2016-10-01
Modern spacecraft often contain large quantities of liquid fuel to execute station keeping and attitude manoeuvres for space missions. In general the combined liquid-structure system is very difficult to model, and the analyses are based on some assumed simplifications. A realistic representation of the liquid dynamics inside closed containers can be approximated by an equivalent mechanical system. This technique can be considered a very useful mathematical tool for solving the complete dynamics problem of a space-system containing liquid. Thus they are particularly useful when designing a control system or to study the stability margins of the coupled dynamics. The commonly used equivalent mechanical models are the mass-spring models and the pendulum models. As far as the spacecraft modelling is concerned they are usually considered rigid; i.e. no flexible appendages such as solar arrays or antennas are considered when dealing with the interaction of the attitude dynamics with the fuel slosh. In the present work the interactions among the fuel slosh, the attitude dynamics and the flexible appendages of a spacecraft are first studied via a classical multi-body approach. In particular the equations of attitude and orbit motion are first derived for the partially liquid-filled flexible spacecraft undergoing fuel slosh; then several parametric analyses will be performed to study the stability conditions of the system during some assigned manoeuvers. The present study is propaedeutic for the synthesis of advanced attitude and/or station keeping control techniques able to minimize and/or reduce an undesired excitation of the satellite flexible appendages and of the fuel sloshing mass.
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
NASA Astrophysics Data System (ADS)
Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei
2015-11-01
In this paper, we present a comparative study of bias correction methods for regional climate model simulations considering the distributional parametric uncertainty underlying the observations/models. In traditional bias correction schemes, the statistics of the simulated model outputs are adjusted to those of the observation data. However, the model output and the observation data are only one case (i.e., realization) out of many possibilities, rather than being sampled from the entire population of a certain distribution due to internal climate variability. This issue has not been considered in the bias correction schemes of the existing climate change studies. Here, three approaches are employed to explore this issue, with the intention of providing a practical tool for bias correction of daily rainfall for use in hydrologic models ((1) conventional method, (2) non-informative Bayesian method, and (3) informative Bayesian method using a Weather Generator (WG) data). The results show some plausible uncertainty ranges of precipitation after correcting for the bias of RCM precipitation. The informative Bayesian approach shows a narrower uncertainty range by approximately 25-45% than the non-informative Bayesian method after bias correction for the baseline period. This indicates that the prior distribution derived from WG may assist in reducing the uncertainty associated with parameters. The implications of our results are of great importance in hydrological impact assessments of climate change because they are related to actions for mitigation and adaptation to climate change. Since this is a proof of concept study that mainly illustrates the logic of the analysis for uncertainty-based bias correction, future research exploring the impacts of uncertainty on climate impact assessments and how to utilize uncertainty while planning mitigation and adaptation strategies is still needed.
Progress in optical parametric oscillators
NASA Technical Reports Server (NTRS)
Fan, Y. X.; Byer, R. L.
1984-01-01
It is pointed out that tunable coherent sources are very useful for many applications, including spectroscopy, chemistry, combustion diagnostics, and remote sensing. Compared with other tunable sources, optical parametric oscillators (OPO) offer the potential advantage of a wide wavelength operating range, which extends from 0.2 micron to 25 microns. The current status of OPO is examined, taking into account mainly advances made during the last decade. Attention is given to early LiNbO3 parametric oscillators, problems which have prevented wide use of parametric oscillators, the demonstration of OPO's using urea and AgGaS2, progress related to picosecond OPO's, a breakthrough in nanosecond parametric oscillators, the first demonstration of a waveguide and fiber parametric amplification and generation, the importance of chalcopyrite crystals, and theoretical work performed with the aim to understand the factors affecting the parametric oscillator performance.
NASA Astrophysics Data System (ADS)
Noh, Seong Jin; Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis
2016-04-01
There have been tremendous improvements in distributed hydrologic modeling (DHM) which made a process-based simulation with a high spatiotemporal resolution applicable on a large spatial scale. Despite of increasing information on heterogeneous property of a catchment, DHM is still subject to uncertainties inherently coming from model structure, parameters and input forcing. Sequential data assimilation (DA) may facilitate improved streamflow prediction via DHM using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is, however, often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. If parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by DHM may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we present a global multi-parametric ensemble approach to incorporate parametric uncertainty of DHM in DA to improve streamflow predictions. To effectively represent and control uncertainty of high-dimensional parameters with limited number of ensemble, MPR method is incorporated with DA. Lagged particle filtering is utilized to consider the response times and non-Gaussian characteristics of internal hydrologic processes. The hindcasting experiments are implemented to evaluate impacts of the proposed DA method on streamflow predictions in multiple European river basins
A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit
NASA Technical Reports Server (NTRS)
Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.
2016-01-01
Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and
Readout IC requirement trends based on a simplified parametric seeker model.
Osborn, Thor D.
2010-03-01
Modern space based optical sensors place substantial demands on the focal plane array readout integrated circuit. Active pixel readout designs offer direct access to individual pixel data but require analog to digital conversion at or near each pixel. Thus, circuit designers must create precise, fundamentally analog circuitry within tightly constrained areas on the integrated circuit. Rapidly changing phenomena necessitate tradeoffs between sampling and conversion speed, data precision, and heat generation adjacent the detector array, especially of concern for thermally sensitive space grade infrared detectors. A simplified parametric model is presented that illustrates seeker system performance and analog to digital conversion requirements trends in the visible through mid-wave infrared, for varying sample rate. Notional limiting-case Earth optical backgrounds were generated using MODTRAN4 with a range of cloud extremes and approximate practical albedo limits for typical surface features from a composite of the Mosart and Aster spectral albedo databases. The dynamic range requirements imposed by these background spectra are discussed in the context of optical band selection and readout design impacts.
Martinez-Murcia, Francisco J; Górriz, Juan M; Ramírez, Javier; Ortiz, Andres
2016-11-01
The usage of biomedical imaging in the diagnosis of dementia is increasingly widespread. A number of works explore the possibilities of computational techniques and algorithms in what is called computed aided diagnosis. Our work presents an automatic parametrization of the brain structure by means of a path generation algorithm based on hidden Markov models (HMMs). The path is traced using information of intensity and spatial orientation in each node, adapting to the structure of the brain. Each path is itself a useful way to characterize the distribution of the tissue inside the magnetic resonance imaging (MRI) image by, for example, extracting the intensity levels at each node or generating statistical information of the tissue distribution. Additionally, a further processing consisting of a modification of the grey level co-occurrence matrix (GLCM) can be used to characterize the textural changes that occur throughout the path, yielding more meaningful values that could be associated to Alzheimer's disease (AD), as well as providing a significant feature reduction. This methodology achieves moderate performance, up to 80.3% of accuracy using a single path in differential diagnosis involving Alzheimer-affected subjects versus controls belonging to the Alzheimer's disease neuroimaging initiative (ADNI).
Testing of the Trim Tab Parametric Model in NASA Langley's Unitary Plan Wind Tunnel
NASA Technical Reports Server (NTRS)
Murphy, Kelly J.; Watkins, Anthony N.; Korzun, Ashley M.; Edquist, Karl T.
2013-01-01
In support of NASA's Entry, Descent, and Landing technology development efforts, testing of Langley's Trim Tab Parametric Models was conducted in Test Section 2 of NASA Langley's Unitary Plan Wind Tunnel. The objectives of these tests were to generate quantitative aerodynamic data and qualitative surface pressure data for experimental and computational validation and aerodynamic database development. Six component force-and-moment data were measured on 38 unique, blunt body trim tab configurations at Mach numbers of 2.5, 3.5, and 4.5, angles of attack from -4deg to +20deg, and angles of sideslip from 0deg to +8deg. Configuration parameters investigated in this study were forebody shape, tab area, tab cant angle, and tab aspect ratio. Pressure Sensitive Paint was used to provide qualitative surface pressure mapping for a subset of these flow and configuration variables. Over the range of parameters tested, the effects of varying tab area and tab cant angle were found to be much more significant than varying tab aspect ratio relative to key aerodynamic performance requirements. Qualitative surface pressure data supported the integrated aerodynamic data and provided information to aid in future analyses of localized phenomena for trim tab configurations.
Stephenson, J; Chadwick, B L; Playle, R A; Treasure, E T
2010-01-01
Caries in primary teeth is an ongoing issue in children's dental health. Its quantification is affected by clustering of data within children and the concurrent risk of exfoliation of primary teeth. This analysis of caries data of 103,776 primary molar tooth surfaces from a cohort study of 2,654 British children aged 4-5 years at baseline applied multilevel competing risks survival analysis methodology to identify factors significantly associated with caries occurrence in primary tooth surfaces in the presence of the concurrent risk of exfoliation, and assessed the effect of exfoliation on caries development. Multivariate multilevel parametric survival models were applied at surface level to the analysis of the sound-carious and sound-exfoliation transitions to which primary tooth surfaces are subject. Socio-economic class, fluoridation status and surface type were found to be the strongest predictors of primary caries, with the highest rates of occurrence and lowest median survival times associated with occlusal surfaces of children from poor socio-economic class living in non-fluoridated areas. The concurrent risk of exfoliation was shown to reduce the distinction in survival experience between different types of surfaces, and between surfaces of teeth from children of different socio-economic class or fluoridation status. Clustering of data had little effect on inferences of parameter significance.
NASA Astrophysics Data System (ADS)
Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien
2006-03-01
Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.
NASA Astrophysics Data System (ADS)
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
Refinement of numerical models and parametric study of SOFC stack performance
NASA Astrophysics Data System (ADS)
Burt, Andrew C.
The presence of multiple air and fuel channels per fuel cell and the need to combine many cells in series result in complex steady-state temperature distributions within Solid Oxide Fuel Cell (SOFC) stacks. Flow distribution in these channels, when non-uniform, has a significant effect on cell and stack performance. Large SOFC stacks are very difficult to model using full 3-D CFD codes because of the resource requirements needed to solve for the many scales involved. Studies have shown that implementations based on Reduced Order Methods (ROM), if calibrated appropriately, can provide simulations of stacks consisting of more than 20 cells with reasonable computational effort. A pseudo 2-D SOFC stack model capable of studying co-flow and counter-flow cell geometries was developed by solving multiple 1-D SOFC single cell models in parallel on a Beowulf cluster. In order to study cross-flow geometries a novel Multi-Component Multi-Physics (MCMP) scheme was instantiated to produce a Reduced Order 3-D Fuel Cell Model. A C++ implementation of the MCMP scheme developed in this study utilized geometry, control volume, component, and model structures allowing each physical model to be solved only for those components for which it is relevant. Channel flow dynamics were solved using a 1-D flow model to reduce computational effort. A parametric study was conducted to study the influence of mass flow distribution, radiation, and stack size on fuel cell stack performance. Using the pseudo 2-D planar SOFC stack model with stacks of various sizes from 2 to 40 cells it was shown that, with adiabatic wall conditions, the asymmetry of the individual cell can produce a temperature distribution where high and low temperatures are found in the top and bottom cells, respectively. Heat transfer mechanisms such as radiation were found to affect the reduction of the temperature gradient near the top and bottom cell. Results from the reduced order 3-D fuel cell model showed that greater
Visible BaB2O4 optical parametric oscillator pumped at 355 nm by a single-axial-mode pulsed source
NASA Technical Reports Server (NTRS)
Fan, Y. X.; Eckardt, R. C.; Byer, R. L.; Nolting, J.; Wallenstein, R.
1988-01-01
A visible BaB2O4 optical parametric oscillator (OPO) pumped by a single-axial-mode 355-nm source has been demonstrated. An average output power of 140 mW with a signal wave conversion efficiency of 13 percent and an idler conversion efficiency of 11 percent for a total conversion efficiency of 24 percent has been achieved. The oscillator has continuously tuned from 412 nm to 2.55 microns limited by the infrared transmission range of the crystal. Through injection seeding, single-axial-mode OPO operation with a corresponding OPO linewidth of less than 3 GHz was obtained.
NASA Astrophysics Data System (ADS)
Wong, H.-W.; Miake-Lye, R. C.
2010-04-01
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 >1×1015 (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.
Foreground Bias from Parametric Models of Far-IR Dust Emission
NASA Technical Reports Server (NTRS)
Kogut, A.; Fixsen, D. J.
2016-01-01
We use simple toy models of far-IR dust emission to estimate the accuracy to which the polarization of the cosmic microwave background can be recovered using multi-frequency fits, if the parametric form chosen for the fitted dust model differs from the actual dust emission. Commonly used approximations to the far-IR dust spectrum yield CMB residuals comparable to or larger than the sensitivities expected for the next generation of CMB missions, despite fitting the combined CMB plus foreground emission to precision 0.1 percent or better. The Rayleigh-Jeans approximation to the dust spectrum biases the fitted dust spectral index by (Delta)(Beta)(sub d) = 0.2 and the inflationary B-mode amplitude by (Delta)(r) = 0.03. Fitting the dust to a modified blackbody at a single temperature biases the best-fit CMB by (Delta)(r) greater than 0.003 if the true dust spectrum contains multiple temperature components. A 13-parameter model fitting two temperature components reduces this bias by an order of magnitude if the true dust spectrum is in fact a simple superposition of emission at different temperatures, but fails at the level (Delta)(r) = 0.006 for dust whose spectral index varies with frequency. Restricting the observing frequencies to a narrow region near the foreground minimum reduces these biases for some dust spectra but can increase the bias for others. Data at THz frequencies surrounding the peak of the dust emission can mitigate these biases while providing a direct determination of the dust temperature profile.
Moore, Julia L; Liang, Song; Akullian, Adam; Remais, Justin V
2012-12-01
Developmental models, such as degree-day models, are commonly used to predict the impact of future climate change on the intensity, distribution, and timing of the transmission of infectious diseases, particularly those caused by pathogens carried by vectors or intermediate hosts. Resulting projections can be useful in policy discussions concerning regional or national responses to future distributions of important infectious diseases. Although the simplicity of degree-day models is appealing, little work has been done to analyze their ability to make reliable projections of the distribution of important pathogens, vectors, or intermediate hosts in the presence of the often considerable parametric uncertainty common to such models. Here, a population model of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, was used to investigate the sensitivity of host range predictions in Sichuan Province, China, to uncertainty in two key degree-day model parameters: delta(min) (minimum temperature threshold for development) and K (total degree-days required for completion of snail development). The intent was to examine the consequences of parametric uncertainty in a plausible biological model, rather than to generate the definitive model. Results indicate that model output, the seasonality of population dynamics, and range predictions, particularly along the edge of the range, are highly sensitive to changes in model parameters, even at levels of parametric uncertainty common to such applications. Caution should be used when interpreting the results of degree-day models used to generate predictions of disease distribution and risk under scenarios of future climate change, and predictions should be considered most reliable when the temperature ranges used in projections resemble those used to estimate model parameters. Given the potential for substantial changes in degree-day model output with modest changes in parameter values, caution is warranted when
NASA Astrophysics Data System (ADS)
Hong, Sung-Kwon; Castanier, Matthew P.; Epureanu, Bogdan I.
2009-03-01
Modeling and re-analysis techniques are proposed for predicting the dynamic response of complex structures that have suffered damage in one or more of their components. When such damages are present, the model of the healthy structure may no longer capture the system-level response or the loading from the rest of the structure on the damaged components. Hence, novel models that allow for an accurate re-analysis of the response of damaged structures are needed in important applications, including damage detection. Herein, such models are obtained by using a reduced order modeling approach based on component mode synthesis. Because the resonant response of a complex structure is often sensitive to component uncertainties (in geometric parameters such as thickness, material properties such as Young's modulus, etc.), novel parametric reduced order models (PROMs) are developed. In previous work, PROMs have been applied for handling uncertainties in a single substructure. Herein, PROMs are extended to the general case of multiple substructures with uncertain parameters or damage. Two damage cases are considered: severe structural deformation (dents), and cracks. For the first damage case, an approximate method based on static mode compensation (SMC) is used to perform fast re-analysis of the vibration response of the damaged structure. The re-analysis is performed through a range of locations and severity levels of the damage. For selected damage locations and levels, the SMC approximation is compared to full finite element analysis to demonstrate the accuracy and computational time savings for the new method. For the second damage case (cracks), the vibration problem becomes nonlinear due to the intermittent contact of the crack faces. Therefore, to estimate the resonant frequencies for a cracked structure, the bi-linear frequency approximation (BFA) is used for cracks of various lengths. Since BFA is based on linear analyses, it is fast and particularly well suited for
Moore, Julia L; Liang, Song; Akullian, Adam; Remais, Justin V
2013-01-01
Developmental models, such as degree-day models, are commonly used to predict the impact of future climate change on the intensity, distribution, and timing of the transmission of infectious diseases, particularly those caused by pathogens carried by vectors or intermediate hosts. Resulting projections can be useful in policy discussions concerning regional or national responses to future distributions of important infectious diseases. Though the simplicity of degree-day models is appealing, little work has been done to analyze their ability to make reliable projections of the distribution of important pathogens, vectors, or intermediate hosts in the presence of the often considerable parametric uncertainty common to such models. Here, a population model of Oncomelania hupensis, the intermediate host of Schistosoma japonicum, was used to investigate the sensitivity of host range predictions in Sichuan Province, China, to uncertainty in two key degree-day model parameters (δmin and K). The intent was to examine the consequences of parametric uncertainty in a plausible biological model, rather than to generate the definitive model. Results indicate that model output, the seasonality of population dynamics, and range predictions, particularly along the edge of the range, are highly sensitive to changes in model parameters, even at levels of parametric uncertainty common to such applications. Caution should be used when interpreting the results of degree-day models used to generate predictions of disease distribution and risk under scenarios of future climate change, and predictions should be considered most reliable when the temperature ranges used in projections resemble those used to estimate model parameters. Given the potential for substantial changes in output with modest changes in parameter values, particular concern is warranted when results will be used to inform policy and management decisions. PMID:23387122
2012-01-01
belongs to a wide class of domain decomposition techniques . CMS divides the global structure into several substructures, and the DOFs of each individual...oriented techniques have been developed. One such approach is to generate what is referred to as parametric reduced-order models (PROMs). PROMs...PROM) technique has been developed recently to overcome these drawbacks [14]. The concepts used in NX-PROMs are applied herein to capture the pre
Nollo, G; Porta, A; Faes, L; Del Greco, M; Disertori, M; Ravelli, F
2001-04-01
Spectral and cross-spectral analysis of R-R interval and systolic arterial pressure (SAP) spontaneous fluctuations have been proposed for noninvasive evaluation of baroreflex sensitivity (BRS). However, results are not in good agreement with clinical measurements. In this study, a bivariate parametric autoregressive model with exogenous input (ARXAR model), able to divide the R-R variability into SAP-related and -unrelated parts, was used to quantify the gain (alpha(ARXAR)) of the baroreflex regulatory mechanism. For performance assessing, two traditional noninvasive methods based on frequency domain analysis [spectral, baroreflex gain by autogressive model (alpha(AR)); cross-spectral, baroreflex gain by bivariate autoregressive model (alpha(2AR))] and one based on the time domain [baroreflex gain by sequence analysis (alpha(SEQ))] were considered and compared with the baroreflex gain by phenylephrine test (alpha(PHE)). The BRS evaluation was performed on 30 patients (61 +/- 10 yr) with recent (10 +/- 3 days) myocardial infarction. The ARXAR model allowed dividing the R-R variability (950 +/- 1,099 ms(2)) into SAP-related (256 +/- 418 ms(2)) and SAP-unrelated (694 +/- 728 ms(2)) parts. alpha(AR) (12.2 +/- 6.1 ms/mmHg) and alpha(2AR) (8.9 +/- 5.6 ms/mmHg) as well as alpha(SEQ) (12.6 +/- 7.1 ms/mmHg) overestimated BRS assessed by alpha(PHE) (6.4 +/- 4.7 ms/mmHg), whereas the ARXAR index gave a comparable value (alpha(ARXAR) = 5.4 +/- 3.3 ms/mmHg). All noninvasive methods were significantly correlated to alpha(PHE) (alpha(ARXAR) and alpha(SEQ) were more correlated than the other indexes). Thus the baroreflex gain obtained describing the causal dependence of R-R interval on SAP showed a good agreement with alpha(PHE) and may provide additional information regarding the gain estimation in the frequency domain.
NASA Astrophysics Data System (ADS)
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
NASA Astrophysics Data System (ADS)
Amsallem, David; Tezaur, Radek; Farhat, Charbel
2016-12-01
A comprehensive approach for real-time computations using a database of parametric, linear, projection-based reduced-order models (ROMs) based on arbitrary underlying meshes is proposed. In the offline phase of this approach, the parameter space is sampled and linear ROMs defined by linear reduced operators are pre-computed at the sampled parameter points and stored. Then, these operators and associated ROMs are transformed into counterparts that satisfy a certain notion of consistency. In the online phase of this approach, a linear ROM is constructed in real-time at a queried but unsampled parameter point by interpolating the pre-computed linear reduced operators on matrix manifolds and therefore computing an interpolated linear ROM. The proposed overall model reduction framework is illustrated with two applications: a parametric inverse acoustic scattering problem associated with a mockup submarine, and a parametric flutter prediction problem associated with a wing-tank system. The second application is implemented on a mobile device, illustrating the capability of the proposed computational framework to operate in real-time.
Numerical Model Of Parametric Oscillator In Proton Exchanged Ti:LiNbO3 Waveguides
NASA Astrophysics Data System (ADS)
Bava, G. P.; Montrosset, I.
1986-11-01
Integrated Optic Parametric oscillators in TIPE resonating structures are analyzed as regards the pump threshold power minimization. The amount of proton exchange has been chosen to satisfy phase-matching condition and the Ti:LiNbO3 waveguide parameters used for optimization. A comparison between TIPE and Ti structures will be discussed.
NASA Astrophysics Data System (ADS)
Mukherjee, Sananda
In recent years, there has been great interest in the potential of green roofs as an alternative roofing option to reduce the energy consumed by individual buildings as well as mitigate large scale urban environmental problems such as the heat island effect. There is a widespread recognition and a growing literature of measured data that suggest green roofs can reduce building energy consumption. This thesis investigates the potential of green roofs in reducing the building energy loads and focuses on how the different parameters of a green roof assembly affect the thermal performance of a building. A green roof assembly is modeled in Design Builder- a 3D graphical design modeling and energy use simulation program (interface) that uses the EnergyPlus simulation engine, and the simulated data set thus obtained is compared to field experiment data to validate the roof assembly model on the basis of how accurately it simulates the behavior of a green roof. Then the software is used to evaluate the thermal performance of several green roof assemblies under three different climate types, looking at the whole building energy consumption. For the purpose of this parametric simulation study, a prototypical single story small office building is considered and one parameter of the green roof is altered for each simulation run in order to understand its effect on building's energy loads. These parameters include different insulation thicknesses, leaf area indices (LAI) and growing medium or soil depth, each of which are tested under the three different climate types. The energy use intensities (EUIs), the peak and annual heating and cooling loads resulting from the use of these green roof assemblies are compared with each other and to a cool roof base case to determine the energy load reductions, if any. The heat flux through the roof is also evaluated and compared. The simulation results are then organized and finally presented as a decision support tool that would
Parametric Identification of Systems Via Linear Operators.
1978-09-01
A general parametric identification /approximation model is developed for the black box identification of linear time invariant systems in terms of... parametric identification techniques derive from the general model as special cases associated with a particular linear operator. Some possible
Alper, Kenneth; Raghavan, Manoj; Isenhart, Robert; Howard, Bryant; Doyle, Werner; John, Roy; Prichep, Leslie
2008-02-01
This preliminary study sought to localize epileptogenic regions in patients with partial epilepsy by analysis of interictal EEG activity utilizing variable resolution electromagnetic tomography (VARETA), a three-dimensional quantitative electroencephalographic (QEEG) frequency-domain distributed source modeling technique. The very narrow band (VNB) spectra spanned the frequency range 0.39 Hz to 19.1 Hz, in 0.39 Hz steps. These VNB spectra were compared to normative data and transformed to provide Z-scores for every scalp derivation, and the spatial distributions of the probable EEG generators of the most abnormal values were displayed on slices from a probabilistic MRI atlas. Each voxel was color-coded to represent the significance of the deviation relative to age appropriate normative values. We compared the resulting three-dimensional images to the localization of epileptogenic regions based on invasive intracranial EEG recordings of seizure onsets. The VARETA image indicated abnormal interictal spectral power values in regions of seizure onset identified by invasive monitoring, mainly in delta and theta range (1.5 to 8.0 Hz). The VARETA localization of the most abnormal voxel was congruent with the epileptogenic regions identified by intracranial recordings with regard to hemisphere in all 6 cases, and with regard to lobe in 5 cases. In contrast, abnormal findings with routine EEG agreed with invasive monitoring with regard to hemisphere in 3 cases and with regard to lobe in 2 cases. These results suggest that analysis of background interictal EEG utilizing distributed source models should be investigated further in clinical epilepsy.
Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing
2013-01-01
The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and “weak” local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method. PMID:23690876
Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing
2013-01-01
The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.
NASA Astrophysics Data System (ADS)
McCorkel, Joel
2016-09-01
Many inter-consistency efforts force empirical agreement between satellite and airborne sensors viewing a source nearly coincident in time and geometry that ensures consistency between sensors rather than relying on a physical understanding of the source. Several research groups organized a campaign at Algodones Dunes in March 2015 in an effort to measure and characterize parameters that can be used for a source model that will enable this physical understanding. This work will provide an overview of the parameters retrieved from airborne and ground-based measurements made during the campaign. Examples of model-based predictions of at-sensor radiance will be shown for Landsat and MODIS. This approach will provide insight into uncertainties of sensor inter-consistency studies and allow for documented SI-traceability and associate error budget. The Algodones model and subsequent test site models can be used for the assessing inter-calibration accuracies of the upcoming Climate Absolute Reflectance and Refractivity Observatory (CLARREO) Pathfinder mission.
NASA Astrophysics Data System (ADS)
Boswell, R. W.; Sutherland, O.; Charles, C.; Squire, J. P.; Chang Díaz, F. R.; Glover, T. W.; Jacobson, V. T.; Chavers, D. G.; Bengtson, R. D.; Bering, E. A.; Goulding, R. H.; Light, M.
2004-11-01
Decay waves have been observed in the megahertz range in the helium plasma generated by the variable specific impulse magnetoplasma rocket magnetoplasma thruster. They are measured using one of the tips of a triple probe connected to a 50 Ω input of a spectrum analyzer via a dc block (a small capacitor). The maximum amplitude of all waves is in the center of the plasma and does not appear correlated to the radial electron density or temperature profiles. The waves seem to be generated close to the helicon antenna that was 91 cm "upstream" from the measuring Langmuir probe. A possible explanation is parametric decay of the large amplitude helicon wave that also generates the plasma.
Continuous-wave optical parametric source for terahertz waves tunable from 1 to 4.5 THz frequency
NASA Astrophysics Data System (ADS)
Kießling, Jens; Buse, Karsten; Vodopyanov, Konstantin L.; Breunig, Ingo
2014-02-01
We demonstrate the continuous-wave operation of a cascade that has been successfully applied so far only for picosecond systems: A doubly-resonant optical-parametric oscillator (OPO) based on lithium niobate generates signal and idler waves close to degeneracy. Subsequently, these two light fields are converted to a terahertz wave via difference frequency mixing in an orientation-patterned gallium arsenide crystal placed inside the OPO cavity. Using this scheme, we achieved tunability from 1 to 4:5 THz frequency, a linewidth smaller than 10 MHz, and a Gaussian beam profile. The output power is of the order of tens of μW, with a scalability into the milliwatt regime.
Grating lobe elimination in steerable parametric loudspeaker.
Shi, Chuang; Gan, Woon-Seng
2011-02-01
In the past two decades, the majority of research on the parametric loudspeaker has concentrated on the nonlinear modeling of acoustic propagation and pre-processing techniques to reduce nonlinear distortion in sound reproduction. There are, however, very few studies on directivity control of the parametric loudspeaker. In this paper, we propose an equivalent circular Gaussian source array that approximates the directivity characteristics of the linear ultrasonic transducer array. By using this approximation, the directivity of the sound beam from the parametric loudspeaker can be predicted by the product directivity principle. New theoretical results, which are verified through measurements, are presented to show the effectiveness of the delay-and-sum beamsteering structure for the parametric loudspeaker. Unlike the conventional loudspeaker array, where the spacing between array elements must be less than half the wavelength to avoid spatial aliasing, the parametric loudspeaker can take advantage of grating lobe elimination to extend the spacing of ultrasonic transducer array to more than 1.5 wavelengths in a typical application.
[Review of urban nonpoint source pollution models].
Wang, Long; Huang, Yue-Fei; Wang, Guang-Qian
2010-10-01
The development history of urban nonpoint source pollution models is reviewed. Features, applicability and limitations of seven popular urban nonpoint source pollution models (SWMM, STORM, SLAMM, HSPF, DR3M-QUAL, MOUSE, and HydroWorks) are discussed. The methodology and research findings of uncertainty in urban nonpoint source pollution modeling are presented. Analytical probabilistic models for estimation of urban nonpoint sources are also presented. The research achievements of urban nonpoint source pollution models in China are summarized. The shortcomings and gaps of approaches on urban nonpoint source pollution models are pointed out. Improvements in modeling of pollutants buildup and washoff, sediments and pollutants transport, and pollutants biochemical reactions are desired for those seven popular models. Most of the models developed by researchers in China are empirical models, so that they can only applied for specific small areas and have inadequate accuracy. Future approaches include improving capability in fate and transport simulation of sediments and pollutants, exploring methodologies of modeling urban nonpoint source pollution in regions with little data or incomplete information, developing stochastic models for urban nonpoint source pollution simulation, and applying GIS to facilitate urban nonpoint source pollution simulation.
Cadarso-Suárez, Carmen; Roca-Pardiñas, Javier; Figueiras, Adolfo; González-Manteiga, Wenceslao
2005-04-30
The generalized additive, model (GAM) is a powerful and widely used tool that allows researchers to fit, non-parametrically, the effect of continuous predictors on a transformation of the mean response variable. Such a transformation is given by a so-called link function, and in GAMs this link function is assumed to be known. Nevertheless, if an incorrect choice is made for the link, the resulting GAM is misspecified and the results obtained may be misleading. In this paper, we propose a modified version of the local scoring algorithm that allows for the non-parametric estimation of the link function, by using local linear kernel smoothers. To better understand the effect that each covariate produces on the outcome, results are expressed in terms of the non-parametric odds ratio (OR) curves. Bootstrap techniques were used to correct the bias in the OR estimation and to construct point-wise confidence intervals. A simulation study was carried out to assess the behaviour of the resulting estimates. The proposed methodology was illustrated using data from the AIDS Register of Galicia (NW Spain), with a view to assessing the effect of the CD4 lymphocyte count on the probability of being AIDS-diagnosed via Tuberculosis (TB). This application shows how the link's flexibility makes it possible to obtain OR curve estimates that are less sensitive to the presence of outliers and unusual values that are often present in the extremes of the covariate distributions.
NASA Astrophysics Data System (ADS)
Wu, Zhiliang; Wang, Shuxin; Zhang, Lianhong; Hu, S. Jack
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.
NASA Astrophysics Data System (ADS)
Restrepo, Louis Fernando
The close location of most DOE non-reactor nuclear facilities to site boundaries and the potential for having receptors in the proximity of such facilities makes it extremely important to accurately address the impact of plume rise and building wake effects on the consequences to such individuals. Unfortunately, there is no current single computer code or model that adequately address the consequences to receptors postulated to be located within the building wake of such facilities. Existing state-of-the-art models have relied on over- simplistic plume rise and parametric wake models that were developed based on very limited amount of data or assumptions, thus potentially leading to large errors in calculations. Building wake and plume rise models implemented in existing consequence computer codes have been identified and evaluated. These models come from an extensive literature review of dispersion, transport, and consequence modeling of airborne radioactive material releases that extends over 25 years. This dissertation focuses on the evaluation of existing state-of-the-art parametric building wake dispersion models by the use of computational fluid dynamic (CFD) codes, developing potential improvements to such models, and comparing the results of such improvements to those generated by CFD models and models implemented in state- of-the-art computer codes. This dissertation also presents new dispersion models and a new analytical parametric model to deal with transient releases that decay or transform during transport.
Yan, Huiping; Qian, Yun; Lin, Guang; Leung, Lai-Yung R.; Yang, Ben; Fu, Q.
2014-03-25
Convective parameterizations used in weather and climate models all display sensitivity to model resolution and variable skill in different climatic regimes. Although parameters in convective schemes can be calibrated using observations to reduce model errors, it is not clear if the optimal parameters calibrated based on regional data can robustly improve model skill across different model resolutions and climatic regimes. In this study, this issue is investigated using a regional modeling framework based on the Weather Research and Forecasting (WRF) model. To quantify the response and sensitivity of model performance to model parameters, we identified five key input parameters and specified their ranges in the Kain-Fritsch (KF) convection scheme in WRF and calibrated them across different spatial resolutions, climatic regimes, and radiation schemes using observed precipitation data. Results show that the optimal values for the five input parameters in the KF scheme are close and model sensitivity and error exhibit similar dependence on the input parameters for all experiments conducted in this study despite differences in the precipitation climatology. We found that the model overall performances in simulating precipitation are more sensitive to the coefficients of downdraft (Pd) and entrainment (Pe) mass flux and starting height of downdraft (Ph). However, we found that rainfall biases, which are probably more related to structural errors, still exist over some regions in the simulation even with the optimal parameters, suggesting further studies are needed to identify the sources of uncertainties and reduce the model biases or structural errors associated with missed or misrepresented physical processes and/or potential problems with the modeling framework.
NASA Technical Reports Server (NTRS)
Smialek, James L.
2002-01-01
An equation has been developed to model the iterative scale growth and spalling process that occurs during cyclic oxidation of high temperature materials. Parabolic scale growth and spalling of a constant surface area fraction have been assumed. Interfacial spallation of the only the thickest segments was also postulated. This simplicity allowed for representation by a simple deterministic summation series. Inputs are the parabolic growth rate constant, the spall area fraction, oxide stoichiometry, and cycle duration. Outputs include the net weight change behavior, as well as the total amount of oxygen and metal consumed, the total amount of oxide spalled, and the mass fraction of oxide spalled. The outputs all follow typical well-behaved trends with the inputs and are in good agreement with previous interfacial models.
Strauch, K; Fimmers, R; Kurz, T; Deichmann, K A; Wienker, T F; Baur, M P
2000-01-01
We present two extensions to linkage analysis for genetically complex traits. The first extension allows investigators to perform parametric (LOD-score) analysis of traits caused by imprinted genes-that is, of traits showing a parent-of-origin effect. By specification of two heterozygote penetrance parameters, paternal and maternal origin of the mutation can be treated differently in terms of probability of expression of the trait. Therefore, a single-disease-locus-imprinting model includes four penetrances instead of only three. In the second extension, parametric and nonparametric linkage analysis with two trait loci is formulated for a multimarker setting, optionally taking imprinting into account. We have implemented both methods into the program GENEHUNTER. The new tools, GENEHUNTER-IMPRINTING and GENEHUNTER-TWOLOCUS, were applied to human family data for sensitization to mite allergens. The data set comprises pedigrees from England, Germany, Italy, and Portugal. With single-disease-locus-imprinting MOD-score analysis, we find several regions that show at least suggestive evidence for linkage. Most prominently, a maximum LOD score of 4.76 is obtained near D8S511, for the English population, when a model that implies complete maternal imprinting is used. Parametric two-trait-locus analysis yields a maximum LOD score of 6.09 for the German population, occurring exactly at D4S430 and D18S452. The heterogeneity model specified for analysis alludes to complete maternal imprinting at both disease loci. Altogether, our results suggest that the two novel formulations of linkage analysis provide valuable tools for genetic mapping of multifactorial traits. PMID:10796874
NASA Astrophysics Data System (ADS)
Lee, Young-Hee; Ahn, Kwang-Deuk; Lee, Yong Hee
2016-12-01
We have developed a parametrization of tidal effects for use in the Noah land-surface model and have validated the land-surface model using observations taken over a tidal flat of the western coast of South Korea. The parametrization is based on the energy budget of a water layer with varying thickness above the soil. During flood tide, heat transfer by the moving water is considered in addition to the surface energy budget. In addition, partial penetration of solar radiation through the water layer is considered in the surface energy budget, and the water thickness varying with time is used as an additional input. Seven days with clear-sky conditions and westerly winds during the daytime are selected for validation of the model. Two simulations are performed in an offline mode: a control simulation without the tidal effect (CONTROL) and a simulation with the tidal effect (TIDE). Comparisons of results have been made with eddy-covariance measurements and soil temperature data for the tidal flats. Observations show that inundation significantly reduces both sensible and latent heat fluxes during daytime, which is well simulated in the TIDE simulation. The diurnal variation and magnitude of soil temperature are better simulated in the TIDE than in the CONTROL simulation. Some underestimation of the latent heat flux over the water surface is partly attributed to the use of one layer of water and the underestimated roughness length at this site. In addition, other model deficiencies are discussed.
Sources, Sinks, and Model Accuracy
Spatial demographic models are a necessary tool for understanding how to manage landscapes sustainably for animal populations. These models, therefore, must offer precise and testable predications about animal population dynamics and how animal demographic parameters respond to ...
Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; Fleming, Paul A.; Ruben, S. D.; Marden, J. R.; Pao, L. Y.
2016-01-01
This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limited number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.
A model for managing sources of groundwater pollution
Gorelick, S.M.
1982-08-01
The waste disposal capacity of a groundwater system can be maximized maintaining water quality at specified locations by using a groundwater pollutant source management model that is based upon linear programing and numerical simulation. The decision variables of the management model are solute waste disposal rates at various facilities distributed over space. A concentration response matrix is used in the management model to describe transient solute transport and is developed using th U.S. Geological Survey solute transport simulation model. The management model was applied to a complex hypothetical groundwater system. Large-scale management models were formulated as dual linear programing problems to reduce numerically stable, available code. Optimal solutions to problems with successively longer management time horizons indicated that disposal schedules at some sites are relatively independent of the number of disopsal rates. Sensitivity analysis using parametric linear programing showed that a sharp reduction in total waste disposal potential occurs if disposal rates at any site are increased beyond their values.
Enabling Parametric Optimal Ascent Trajectory Modeling During Early Phases of Design
NASA Technical Reports Server (NTRS)
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
Binding energy and structure of e{sup +}Li and e{sup -}Li using a parametric model potential
Shertzer, J.; Ward, S. J.
2006-02-15
The parametric model potential developed by Peach for describing the electron interaction with the alkali-metal ion core yields energy levels that are in excellent agreement with the measurements of the spectra. Because of its relative simplicity, the l-independent model potential is an attractive choice for studying positron-alkali-metal collisions. In order to test how well the model potential can be used to describe an effective three-body system, we use the Peach model potential to calculate the energy and geometry of the weakly bound e{sup +}Li and e{sup -}Li systems. The binding energy is in good agreement with calculations using the exact Hamiltonian.
NASA Astrophysics Data System (ADS)
Genoni, M.; Riva, M.; Pariani, G.; Aliverti, M.; Moschetti, M.
2016-08-01
We present the details of a paraxial parametric model of a high resolution spectrograph which can be used as a tool, characterized by good approximation and reliability, at a system engineering level. This model can be exploited to perform a preliminary evaluation of the different parameters as long as different possible architectures of high resolution spectrograph like the one under design for the E-ELT (for the moment called E-ELT HIRES in order to avoid wrong association with the HIRES spectrograph at Keck telescope). The detailed equations flow concerning the first order effects of all the spectrograph components is described; in addition a comparison with the data of a complete physical ESPRESSO spectrograph model is presented as a model proof.
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
Frepoli, Cesare; Oriani, Luca
2006-07-01
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{sup 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 Astrophysics Data System (ADS)
Zhang, Xiaojing; Musson-Genon, Luc; Dupont, Eric; Milliez, Maya; Carissimo, Bertrand
2014-05-01
A detailed numerical simulation of a radiation fog event with a single column model is presented, which takes into account recent developments in microphysical parametrizations. One-dimensional simulations are performed using the computational fluid dynamics model Code_Saturne and the results are compared to a very detailed in situ dataset collected during the ParisFog campaign, which took place near Paris, France, during the winter 2006-2007. Special attention is given to the detailed and complete diurnal simulations and to the role of microphysics in the fog life cycle. The comparison between the simulated and the observed visibility, in the single-column model case study, shows that the evolution of radiation fog is correctly simulated. Sensitivity simulations show that fog development and dissipation are sensitive to the droplet-size distribution through sedimentation/deposition processes but the aerosol number concentration in the coarse mode has a low impact on the time of fog formation.
NASA Astrophysics Data System (ADS)
Fai, S.; Filippi, M.; Paliaga, S.
2013-07-01
Whether a house of worship or a simple farmhouse, the fabrication of a building reveals both the unspoken cultural aspirations of the builder and the inevitable exigencies of the construction process. In other-words, why buildings are made is intimately and inevitably associated with how buildings are made. Nowhere is this more evident than in vernacular architecture. At the Carleton Immersive Media Studio (CIMS) we are concerned that the de-population of Canada's rural areas, paucity of specialized tradespersons, and increasing complexity of building codes threaten the sustainability of this invaluable cultural resource. For current and future generations, the quantitative and qualitative values of traditional methods of construction are essential for an inclusive cultural memory. More practically, and equally pressing, an operational knowledge of these technologies is essential for the conservation of our built heritage. To address these concerns, CIMS has launched a number of research initiatives over the past five years that explore novel protocols for the documentation and dissemination of knowledge related to traditional methods of construction. Our current project, Cultural Diversity and Material Imagination in Canadian Architecture (CDMICA), made possible through funding from Canada's Social Sciences and Humanities Research Council (SSHRC), explores the potential of building information modelling (BIM) within the context of a web-based environment. In this paper, we discuss our work-to-date on the development of a web-based library of BIM details that is referenced to ''typical'' assemblies culled from 19C and early 20C construction manuals. The parametric potential of these ''typical'' details is further refined by evidence from the documentation of ''specific'' details studied during comprehensive surveys of extant heritage buildings. Here, we consider a BIM of the roof truss assembly of one of the oldest buildings in Canada's national
NASA's X-Plane Database and Parametric Cost Model v 2.0
NASA Technical Reports Server (NTRS)
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!
Hwang, Eunjoo; Hu, Jingwen; Chen, Cong; Klein, Katelyn F; Miller, Carl S; Reed, Matthew P; Rupp, Jonathan D; Hallman, Jason J
2016-11-01
Occupant stature and body shape may have significant effects on injury risks in motor vehicle crashes, but the current finite element (FE) human body models (HBMs) only represent occupants with a few sizes and shapes. Our recent studies have demonstrated that, by using a mesh morphing method, parametric FE HBMs can be rapidly developed for representing a diverse population. However, the biofidelity of those models across a wide range of human attributes has not been established. Therefore, the objectives of this study are 1) to evaluate the accuracy of HBMs considering subject-specific geometry information, and 2) to apply the parametric HBMs in a sensitivity analysis for identifying the specific parameters affecting body responses in side impact conditions. Four side-impact tests with two male post-mortem human subjects (PMHSs) were selected to evaluate the accuracy of the geometry and impact responses of the morphed HBMs. For each PMHS test, three HBMs were simulated to compare with the test results: the original Total Human Model for Safety (THUMS) v4.01 (O-THUMS), a parametric THUMS (P-THUMS), and a subject-specific THUMS (S-THUMS). The P-THUMS geometry was predicted from only age, sex, stature, and BMI using our statistical geometry models of skeleton and body shape, while the S-THUMS geometry was based on each PMHS's CT data. The simulation results showed a preliminary trend that the correlations between the PTHUMS- predicted impact responses and the four PMHS tests (mean-CORA: 0.84, 0.78, 0.69, 0.70) were better than those between the O-THUMS and the normalized PMHS responses (mean-CORA: 0.74, 0.72, 0.55, 0.63), while they are similar to the correlations between S-THUMS and the PMHS tests (mean-CORA: 0.85, 0.85, 0.67, 0.72). The sensitivity analysis using the PTHUMS showed that, in side impact conditions, the HBM skeleton and body shape geometries as well as the body posture were more important in modeling the occupant impact responses than the bone and soft
The Commercial Open Source Business Model
NASA Astrophysics Data System (ADS)
Riehle, Dirk
Commercial open source software projects are open source software projects that are owned by a single firm that derives a direct and significant revenue stream from the software. Commercial open source at first glance represents an economic paradox: How can a firm earn money if it is making its product available for free as open source? This paper presents the core properties of com mercial open source business models and discusses how they work. Using a commercial open source approach, firms can get to market faster with a superior product at lower cost than possible for traditional competitors. The paper shows how these benefits accrue from an engaged and self-supporting user community. Lacking any prior comprehensive reference, this paper is based on an analysis of public statements by practitioners of commercial open source. It forges the various anecdotes into a coherent description of revenue generation strategies and relevant business functions.
Open Source Cable Models for EMI Simulations
NASA Astrophysics Data System (ADS)
Greedy, S.; Smartt, C.; Thomas, D. W. P.
2016-05-01
This paper describes the progress of work towards an Open Source software toolset suitable for developing Spice based multi-conductor cable models. The issues related to creating a transmission line model for implementation in Spice which include the frequency dependent properties of real cables are presented and the viability of spice cable models is demonstrated through application to a three conductor crosstalk model. Development of the techniques to include models of shielded cables and incident field excitation has been demonstrated.
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
Chalcogenide optical parametric oscillator.
Ahmad, Raja; Rochette, Martin
2012-04-23
We demonstrate the first optical parametric oscillator (OPO) based on chalcogenide glass. The parametric gain medium is an As(2)Se(3) chalcogenide microwire coated with a layer of polymer. The doubly-resonant OPO oscillates simultaneously at a Stokes and an anti Stokes wavelength shift of >50 nm from the pump wavelength that lies at λ(P) = 1,552 nm. The oscillator has a peak power threshold of 21.6 dBm and a conversion efficiency of >19%. This OPO experiment provides an additional application of the chalcogenide microwire technology; and considering the transparency of As(2)Se(3) glass extending far in the mid-infrared (mid-IR) wavelengths, the device holds promise for realizing mid-IR OPOs utilizing existing optical sources in the telecommunications wavelength region.
Park, Taeyoung; Krafty, Robert T.; Sánchez, Alvaro I.
2012-01-01
A Poisson regression model with an offset assumes a constant baseline rate after accounting for measured covariates, which may lead to biased estimates of coefficients in an inhomogeneous Poisson process. To correctly estimate the effect of time-dependent covariates, we propose a Poisson change-point regression model with an offset that allows a time-varying baseline rate. When the nonconstant pattern of a log baseline rate is modeled with a nonparametric step function, the resulting semi-parametric model involves a model component of varying dimension and thus requires a sophisticated varying-dimensional inference to obtain correct estimates of model parameters of fixed dimension. To fit the proposed varying-dimensional model, we devise a state-of-the-art MCMC-type algorithm based on partial collapse. The proposed model and methods are used to investigate an association between daily homicide rates in Cali, Colombia and policies that restrict the hours during which the legal sale of alcoholic beverages is permitted. While simultaneously identifying the latent changes in the baseline homicide rate which correspond to the incidence of sociopolitical events, we explore the effect of policies governing the sale of alcohol on homicide rates and seek a policy that balances the economic and cultural dependencies on alcohol sales to the health of the public. PMID:23393408
NASA Astrophysics Data System (ADS)
Hagemann, Mark; Park, Mi-Hyun
2017-04-01
This study assessed the capacity of semi-parametric regression models to predict riverine solute concentrations during extreme high-flow hydrologic events, when such events are absent from the models' calibration data. Using a large dataset from 459 monitoring stations across the US Northeast, the models showed a tendency to overpredict extreme-event concentrations, with increasing bias and variance for increasingly extreme hydrologic conditions. The validation framework in this study effectively compared model performance across disparate hydrologic regimes and constituents, yet can be used to estimate individual model performance under an unobserved extreme-flow condition, regardless of whether any extreme-flow data are available for that model. The validation procedure can further be generalized to explore model performance in an arbitrarily defined extreme condition for a broad range of model types. Despite an overall increase in uncertainty for extreme-event concentration estimates, estimates under extreme hydrologic conditions could be improved by taking into account the observed bias in the aggregated regional database.
Nascimento, Jacinto C; Marques, Jorge S; Lemos, João M
2013-05-01
Many approaches to trajectory analysis, such as clustering or classification, use probabilistic generative models, thus not requiring trajectory alignment/registration. Switched linear dynamical models (e.g., HMMs) have been used in this context, due to their ability to describe different motion regimes. However, these models are not suitable for handling space-dependent dynamics that are more naturally captured by nonlinear models. As is well known, these are more difficult to identify. In this paper, we propose a new way of modeling trajectories, based on a mixture of parametric motion vector fields that depend on a small number of parameters. Switching among these fields follows a probabilistic mechanism, characterized by a field of stochastic matrices. This approach allows representing a wide variety of trajectories and modeling space-dependent behaviors without using global nonlinear dynamical models. Experimental evaluation is conducted in both synthetic and real scenarios. The latter concerning with human trajectory modeling for activity classification, a central task in video surveillance.
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
Source characterization refinements for routine modeling applications
NASA Astrophysics Data System (ADS)
Paine, Robert; Warren, Laura L.; Moore, Gary E.
2016-03-01
Steady-state dispersion models recommended by various environmental agencies worldwide have generally been evaluated with traditional stack release databases, including tracer studies. The sources associated with these field data are generally those with isolated stacks or release points under relatively ideal conditions. Many modeling applications, however, involve sources that act to modify the local dispersion environment as well as the conditions associated with plume buoyancy and final plume rise. The source characterizations affecting plume rise that are introduced and discussed in this paper include: 1) sources with large fugitive heat releases that result in a local urbanized effect, 2) stacks on or near individual buildings with large fugitive heat releases that tend to result in buoyant "liftoff" effects counteracting aerodynamic downwash effects, 3) stacks with considerable moisture content, which leads to additional heat of condensation during plume rise - an effect that is not considered by most dispersion models, and 4) stacks in a line that result in at least partial plume merging and buoyancy enhancement under certain conditions. One or more of these effects are appropriate for a given modeling application. We present examples of specific applications for one or more of these procedures in the paper. This paper describes methods to introduce the four source characterization approaches to more accurately simulate plume rise to a variety of dispersion models. The authors have focused upon applying these methods to the AERMOD modeling system, which is the United States Environmental Protection Agency's preferred model in addition to being used internationally, but the techniques are applicable to dispersion models worldwide. While the methods could be installed directly into specific models such as AERMOD, the advantage of implementing them outside the model is to allow them to be applicable to numerous models immediately and also to allow them to
Phenomenological Modeling of Infrared Sources: Recent Advances
NASA Technical Reports Server (NTRS)
Leung, Chun Ming; Kwok, Sun (Editor)
1993-01-01
Infrared observations from planned space facilities (e.g., ISO (Infrared Space Observatory), SIRTF (Space Infrared Telescope Facility)) will yield a large and uniform sample of high-quality data from both photometric and spectroscopic measurements. To maximize the scientific returns of these space missions, complementary theoretical studies must be undertaken to interpret these observations. A crucial step in such studies is the construction of phenomenological models in which we parameterize the observed radiation characteristics in terms of the physical source properties. In the last decade, models with increasing degree of physical realism (in terms of grain properties, physical processes, and source geometry) have been constructed for infrared sources. Here we review current capabilities available in the phenomenological modeling of infrared sources and discuss briefly directions for future research in this area.
Jaspers, Stijn; Verbeke, Geert; Böhning, Dankmar; Aerts, Marc
2016-01-01
In the last decades, considerable attention has been paid to the collection of antimicrobial resistance data, with the aim of monitoring non-wild-type isolates. This monitoring is performed based on minimum inhibition concentration (MIC) values, which are collected through dilution experiments. We present a semi-parametric mixture model to estimate the entire MIC density on the continuous scale. The parametric first component is extended with a non-parametric second component and a new back-fitting algorithm, based on the Vertex Exchange Method, is proposed. Our data example shows how to estimate the MIC density for Escherichia coli tested for ampicillin and how to use this estimate for model-based classification. A simulation study was performed, showing the promising behavior of the new method, both in terms of density estimation as well as classification.
Parametric studies of magnetic-optic imaging using finite-element models
NASA Astrophysics Data System (ADS)
Chao, C.; Udpa, L.; Xuan, L.; Fitzpatrick, G.; Thorne, D.; Shih, W.
2000-05-01
Magneto-optic imaging is a relatively new sensor application of bubble memory technology to NDI. The Magneto-Optic Imager (MOI) uses a magneto-optic (MO) sensor to produce analog images of magnetic flux leakage from surface and subsurface defects. The flux leakage is produced by eddy current induction techniques in nonferrous metals and magnetic yokes are used in ferromagnetic materials. The technique has gained acceptance in the aircraft maintenance industry for use to detect surface-breaking cracks and corrosion. Until recently, much of the MOI development has been empirical in nature since the electromagnetic processes that produce images are rather complex. The availability of finite element techniques to numerically solve Maxwell's equations, in conjunction with MOI observations, allows greater understanding of the capabilities of the instrument. In this paper, we present a systematic set of finite element calculations along with MOI measurements on specific defects to quantify the current capability of the MOI as well as its desired performance. Parametric studies including effects of liftoff and proximity of edges are also studied.—This material is based upon work supported by the Federal Aviation Administration under Contract #DTFA03-98-D-00008, Delivery Order #IA013 and performed at Iowa State University's Center for NDE as part of the Center for Aviation Systems Reliability program.
Nonparametric and parametric estimation for a linear germination-growth model.
Chiu, S N; Quine, M P; Stewart, M
2000-09-01
Seeds are planted on the interval [0, L] at various locations. Each seed has a location x and a potential germination time t epsilon [0, infinity), and it is assumed that the collection of such (x, t) pairs forms a Poisson process in [0, L] x [0, infinity) with intensity measure dxd lambda(t). From each seed that germinates, an inhibiting region grows bidirectionally at rate 2v. These regions inhibit germination of any seed in the region with a later potential germination time. Thus, seeds only germinate in the uninhibited part of [0, L]. We want to estimate lambda on the basis of one or more realizations of the process, the data being the locations and germination times of the germinated seeds. We derive the maximum likelihood estimator of v and a nonparametric estimator of lambda and describe methods of obtaining parametric estimates from it, illustrating these with reference to gamma densities. Simulation results are described and the methods applied to some neurobiological data. An Appendix outlines the S-PLUS code used.
NASA Astrophysics Data System (ADS)
Zhu, Liangzhu; Zhang, Lei; Virkar, Anil V.
2015-09-01
A parametric equation describing polarization in solid oxide fuel cells (SOFC) in terms of experimentally measurable parameters is presented. The equation explicitly describes activation and concentration polarizations at the two electrodes and the ohmic loss as functions of current density. Using known values of parameters measured on cell materials and components, various polarizations are estimated as functions of current density and the possible performance characteristics are assessed. The calculated performance curves using measurements made on cell materials and components are in good agreement with actual fuel cell tests. Using the model, prospects for ultra-high power density SOFC at intermediate temperatures (<800 °C) are examined. The results show that even in thin electrolyte film anode-supported cells, the ohmic contribution can be substantial, not all of it being attributable to electrolyte and electrode materials. The results also show that the electrode particle size has a substantial effect on the activation polarization.
Momentum structure of the self-energy and its parametrization for the two-dimensional Hubbard model
NASA Astrophysics Data System (ADS)
Pudleiner, P.; Schäfer, T.; Rost, D.; Li, G.; Held, K.; Blümer, N.
2016-05-01
We compute the self-energy for the half-filled Hubbard model on a square lattice using lattice quantum Monte Carlo simulations and the dynamical vertex approximation. The self-energy is strongly momentum-dependent, but it can be parametrized via the noninteracting energy-momentum dispersion ɛk, except for pseudogap features right at the Fermi edge. That is, it can be written as Σ (ɛk,ω ) , with two energylike parameters (ɛ , ω ) instead of three (kx, ky, and ω ). The self-energy has two rather broad and weakly dispersing high-energy features and a sharp ω =ɛk feature at high temperatures, which turns to ω =-ɛk at low temperatures. Altogether this yields a Z - and reversed-Z -like structure, respectively, for the imaginary part of Σ (ɛk,ω ) . We attribute the change of the low-energy structure to antiferromagnetic spin fluctuations.
Fjodorova, Natalja; Novič, Marjana
2015-09-03
Engineering optimization is an actual goal in manufacturing and service industries. In the tutorial we represented the concept of traditional parametric estimation models (Factorial Design (FD) and Central Composite Design (CCD)) for searching optimal setting parameters of technological processes. Then the 2D mapping method based on Auto Associative Neural Networks (ANN) (particularly, the Feed Forward Bottle Neck Neural Network (FFBN NN)) was described in comparison with traditional methods. The FFBN NN mapping technique enables visualization of all optimal solutions in considered processes due to the projection of input as well as output parameters in the same coordinates of 2D map. This phenomenon supports the more efficient way of improving the performance of existing systems. Comparison of two methods was performed on the bases of optimization of solder paste printing processes as well as optimization of properties of cheese. Application of both methods enables the double check. This increases the reliability of selected optima or specification limits.
Bim from Laser SCANS… not Just for Buildings: Nurbs-Based Parametric Modeling of a Medieval Bridge
NASA Astrophysics Data System (ADS)
Barazzetti, L.; Banfi, F.; Brumana, R.; Previtali, M.; Roncoroni, F.
2016-06-01
Building Information Modelling is not limited to buildings. BIM technology includes civil infrastructures such as roads, dams, bridges, communications networks, water and wastewater networks and tunnels. This paper describes a novel methodology for the generation of a detailed BIM of a complex medieval bridge. The use of laser scans and images coupled with the development of algorithms able to handle irregular shapes allowed the creation of advanced parametric objects, which were assembled to obtain an accurate BIM. The lack of existing object libraries required the development of specific families for the different structural elements of the bridge. Finally, some applications aimed at assessing the stability and safety of the bridge are illustrated and discussed. The BIM of the bridge can incorporate this information towards a new "BIMonitoring" concept to preserve the geometric complexity provided by point clouds, obtaining a detailed BIM with object relationships and attributes.
Anatomical constraints for neuromagnetic source models
NASA Astrophysics Data System (ADS)
George, John S.; Lewis, Paul S.; Ranken, D. M.; Kaplan, L.; Wood, C. C.
1991-07-01
The localization of neural electromagnetic sources from measurements at the head surface requires the solution of an inverse problem; that is, the determination of the number, location, spatial configuration, strength, and time-course of the neuronal currents that give rise to the magnetic field or potential distribution. In most general form, the neuromagnetic and electrical inverse problems are ill-posed and have no unique solution; however, approximate solutions are possible if assumptions are made regarding the shape and conductivity of the head and the number and configuration of neuronal currents responsible for the surface distributions. To help resolve ambiguities and to reduce the number and range of free parameters required to model complex neuromagnetic sources, the authors are investigating strategies to constrain the locations of allowable sources, based on a knowledge of individual anatomy. The key assumption, justified by both physiological evidence and theoretical considerations, is that the dominant neuromagnetic sources which contribute to surface field distributions reside within the cortex. It is demonstrated that anatomically constrained source modeling strategies can produce significant improvements in source localization; however, the conclusion is that additional improvements in model fitting or source reconstruction procedures are required.
The impact of parametrized convection on cloud feedback.
Webb, Mark J; Lock, Adrian P; Bretherton, Christopher S; Bony, Sandrine; Cole, Jason N S; Idelkadi, Abderrahmane; Kang, Sarah M; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D; Zhao, Ming
2015-11-13
We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that 'ConvOff' models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback
The impact of parametrized convection on cloud feedback
Webb, Mark J.; Lock, Adrian P.; Bretherton, Christopher S.; Bony, Sandrine; Cole, Jason N. S.; Idelkadi, Abderrahmane; Kang, Sarah M.; Koshiro, Tsuyoshi; Kawai, Hideaki; Ogura, Tomoo; Roehrig, Romain; Shin, Yechul; Mauritsen, Thorsten; Sherwood, Steven C.; Vial, Jessica; Watanabe, Masahiro; Woelfle, Matthew D.; Zhao, Ming
2015-01-01
We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud
NASA Astrophysics Data System (ADS)
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.
García-Betances, Rebeca I; Cabrera-Umpiérrez, María Fernanda; Ottaviano, Manuel; Pastorino, Matteo; Arredondo, María T
2016-02-22
Despite the speedy evolution of Information and Computer Technology (ICT), and the growing recognition of the importance of the concept of universal design in all domains of daily living, mainstream ICT-based product designers and developers still work without any truly structured tools, guidance or support to effectively adapt their products and services to users' real needs. This paper presents the approach used to define and evaluate parametric cognitive models that describe interaction and usage of ICT by people with aging- and disability-derived functional impairments. A multisensorial training platform was used to train, based on real user measurements in real conditions, the virtual parameterized user models that act as subjects of the test-bed during all stages of simulated disabilities-friendly ICT-based products design. An analytical study was carried out to identify the relevant cognitive functions involved, together with their corresponding parameters as related to aging- and disability-derived functional impairments. Evaluation of the final cognitive virtual user models in a real application has confirmed that the use of these models produce concrete valuable benefits to the design and testing process of accessible ICT-based applications and services. Parameterization of cognitive virtual user models allows incorporating cognitive and perceptual aspects during the design process.
García-Betances, Rebeca I.; Cabrera-Umpiérrez, María Fernanda; Ottaviano, Manuel; Pastorino, Matteo; Arredondo, María T.
2016-01-01
Despite the speedy evolution of Information and Computer Technology (ICT), and the growing recognition of the importance of the concept of universal design in all domains of daily living, mainstream ICT-based product designers and developers still work without any truly structured tools, guidance or support to effectively adapt their products and services to users’ real needs. This paper presents the approach used to define and evaluate parametric cognitive models that describe interaction and usage of ICT by people with aging- and disability-derived functional impairments. A multisensorial training platform was used to train, based on real user measurements in real conditions, the virtual parameterized user models that act as subjects of the test-bed during all stages of simulated disabilities-friendly ICT-based products design. An analytical study was carried out to identify the relevant cognitive functions involved, together with their corresponding parameters as related to aging- and disability-derived functional impairments. Evaluation of the final cognitive virtual user models in a real application has confirmed that the use of these models produce concrete valuable benefits to the design and testing process of accessible ICT-based applications and services. Parameterization of cognitive virtual user models allows incorporating cognitive and perceptual aspects during the design process. PMID:26907296
Gebraad, P. M. O.; Teeuwisse, F. W.; van Wingerden, J. W.; ...
2016-01-01
This article presents a wind plant control strategy that optimizes the yaw settings of wind turbines for improved energy production of the whole wind plant by taking into account wake effects. The optimization controller is based on a novel internal parametric model for wake effects, called the FLOw Redirection and Induction in Steady-state (FLORIS) model. The FLORIS model predicts the steady-state wake locations and the effective flow velocities at each turbine, and the resulting turbine electrical energy production levels, as a function of the axial induction and the yaw angle of the different rotors. The FLORIS model has a limitedmore » number of parameters that are estimated based on turbine electrical power production data. In high-fidelity computational fluid dynamics simulations of a small wind plant, we demonstrate that the optimization control based on the FLORIS model increases the energy production of the wind plant, with a reduction of loads on the turbines as an additional effect.« less
Henson, Richard N; Wakeman, Daniel G; Litvak, Vladimir; Friston, Karl J
2011-01-01
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-optimization of spatial priors across subjects. We evaluate these applications on multi-modal data acquired from 18 subjects, focusing on energy induced by face perception within a time-frequency window of 100-220 ms, 8-18 Hz. 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.
NASA Astrophysics Data System (ADS)
Brauer, Claudia; Torfs, Paul; Teuling, Ryan; Uijlenhoet, Remko
2014-05-01
We present the Wageningen Lowland Runoff Simulator (WALRUS), a novel rainfall-runoff model to fill the gap between complex, spatially distributed models for lowland catchments and simple, parametric models for mountainous catchments. From observations and experience from two Dutch field sites (the Hupsel Brook catchment and the Cabauw polder), we identified key processes for runoff generation in lowland catchments and important feedbacks between components in the hydrological system. We used this knowledge to design a parametric model which can be used all over the world in both freely draining lowland catchments and polders with controlled water levels. While using only four parameters which require calibration, WALRUS explicitly accounts for processes that are important in lowland areas: (1) Groundwater-unsaturated zone coupling: WALRUS contains one soil reservoir, which is divided effectively by the (dynamic) groundwater table into a groundwater zone and a vadose zone. The condition of this soil reservoir is described by two strongly dependent variables: the groundwater depth and the storage deficit (the effective thickness of empty pores). This implementation enables capillary rise when the top soil has dried through evapotranspiration. (2) Wetness-dependent flowroutes: The storage deficit determines the division of rain water between the soil reservoir (slow routes: infiltration, percolation and groundwater flow) and a quickflow reservoir (quick routes: drainpipe, macropore and overland flow). (3) Groundwater-surface water feedbacks: Surface water forms an explicit part of the model structure. Drainage depends on the difference between surface water level and groundwater level (rather than groundwater level alone), allowing for feedbacks and infiltration of surface water into the soil. (4) Seepage and surface water supply: Groundwater seepage and surface water supply or extraction (pumping) are added to or subtracted from the soil or surface water reservoir
NASA Astrophysics Data System (ADS)
Kang, Kai; Qin, Shao-Jing; Wang, Chui-Lin
2010-10-01
In this paper, we developed a new parametrization method to calculate the localization length in one-dimensional Anderson model with diagonal disorder. This method can avoid the divergence difficulty encountered in the conventional methods, and significantly save computing time as well.
NASA Astrophysics Data System (ADS)
Rogers, Adam; Safi-Harb, Samar
2016-04-01
A wealth of X-ray and radio observations has revealed in the past decade a growing diversity of neutron stars (NSs) with properties spanning orders of magnitude in magnetic field strength and ages, and with emission processes explained by a range of mechanisms dictating their radiation properties. However, serious difficulties exist with the magneto-dipole model of isolated NS fields and their inferred ages, such as a large range of observed braking indices (n, with values often <3) and a mismatch between the NS and associated supernova remnant (SNR) ages. This problem arises primarily from the assumptions of a constant magnetic field with n = 3, and an initial spin period that is much smaller than the observed current period. It has been suggested that a solution to this problem involves magnetic field evolution, with some NSs having magnetic fields buried within the crust by accretion of fall-back supernova material following their birth. In this work, we explore a parametric phenomenological model for magnetic field growth that generalizes previous suggested field evolution functions, and apply it to a variety of NSs with both secure SNR associations and known ages. We explore the flexibility of the model by recovering the results of previous work on buried magnetic fields in young NSs. Our model fits suggest that apparently disparate classes of NSs may be related to one another through the time evolution of the magnetic field.
NASA Astrophysics Data System (ADS)
Zhu, Xiaowei; Iungo, G. Valerio; Leonardi, Stefano; Anderson, William
2017-02-01
For a horizontally homogeneous, neutrally stratified atmospheric boundary layer (ABL), aerodynamic roughness length, z_0, is the effective elevation at which the streamwise component of mean velocity is zero. A priori prediction of z_0 based on topographic attributes remains an open line of inquiry in planetary boundary-layer research. Urban topographies - the topic of this study - exhibit spatial heterogeneities associated with variability of building height, width, and proximity with adjacent buildings; such variability renders a priori, prognostic z_0 models appealing. Here, large-eddy simulation (LES) has been used in an extensive parametric study to characterize the ABL response (and z_0) to a range of synthetic, urban-like topographies wherein statistical moments of the topography have been systematically varied. Using LES results, we determined the hierarchical influence of topographic moments relevant to setting z_0. We demonstrate that standard deviation and skewness are important, while kurtosis is negligible. This finding is reconciled with a model recently proposed by Flack and Schultz (J Fluids Eng 132:041203-1-041203-10, 2010), who demonstrate that z_0 can be modelled with standard deviation and skewness, and two empirical coefficients (one for each moment). We find that the empirical coefficient related to skewness is not constant, but exhibits a dependence on standard deviation over certain ranges. For idealized, quasi-uniform cubic topographies and for complex, fully random urban-like topographies, we demonstrate strong performance of the generalized Flack and Schultz model against contemporary roughness correlations.
Some Simple Propagation Models for Linear and Parametric Sources in Shallow Water.
1980-04-09
or eigenray angle 0i, there is one loss producing bottom bounce each time the horizontal range cycles through an incremental distance 2H/0. Thus at...factor which is dependent on the steepness of the eigenray angles. This start- ing range for the applicability of Eq. (5) is of course applicable to the...broad beam case, *- > 0c. Although it is difficult to illustrate mode stripping, a sketch of a few modal eigenrays is offered in Fig. 3 for the case
Non-parametric Bayesian graph models reveal community structure in resting state fMRI.
Andersen, Kasper Winther; Madsen, Kristoffer H; Siebner, Hartwig Roman; Schmidt, Mikkel N; Mørup, Morten; Hansen, Lars Kai
2014-10-15
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 Diagonal Model (IDM). The models define probabilities of generating links within and between clusters and the difference between the models lies in the restrictions they impose upon the between-cluster link probabilities. IRM is the most flexible model with no restrictions on the probabilities of links 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 noise probability. These probabilistic models are compared against three other approaches for node clustering, namely Infomap, Louvain modularity, and hierarchical clustering. Using 3 different datasets comprising healthy volunteers' rs-fMRI we found that the BCD model was in general the most predictive and reproducible model. This suggests that rs-fMRI data exhibits community structure and furthermore points to the significance of modeling heterogeneous between-cluster link probabilities.
Meyer, Swen; Blaschek, Michael; Duttmann, Rainer; Ludwig, Ralf
2016-02-01
According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources, agricultural productivity and drinking water supply. Current projections of future hydrological change, based on regional climate model results and subsequent hydrological modeling schemes, are very uncertain and poorly validated. The Rio Mannu di San Sperate Basin, located in Sardinia, Italy, is one test site of the CLIMB project. The Water Simulation Model (WaSiM) was set up to model current and future hydrological conditions. The availability of measured meteorological and hydrological data is poor as it is common for many Mediterranean catchments. In this study we conducted a soil sampling campaign in the Rio Mannu catchment. We tested different deterministic and hybrid geostatistical interpolation methods on soil textures and tested the performance of the applied models. We calculated a new soil texture map based on the best prediction method. The soil model in WaSiM was set up with the improved new soil information. The simulation results were compared to standard soil parametrization. WaSiMs was validated with spatial evapotranspiration rates using the triangle method (Jiang and Islam, 1999). WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. The climate change impact was assessed based on differences between reference and future time series. The simulated results show a reduction of all hydrological quantities in the future in the spring season. Furthermore simulation results reveal an earlier onset of dry conditions in the catchment. We show that a solid soil model setup based on short-term field measurements can improve long-term modeling results, which is especially important
Rigatos, G; Rigatou, E; Djida, J D
2015-01-01
The derivative-free nonlinear Kalman filter is proposed for state estimation and fault diagnosis in distributed parameter systems of the wave-type and particularly in the Peyrard-Bishop-Dauxois model of DNA dynamics. At a first stage, a nonlinear filtering approach is introduced for estimating the dynamics of the Peyrard-Bishop-Dauxois 1D nonlinear wave equation, through the processing of a small number of measurements. It is shown that the numerical solution of the associated partial differential equation results in a set of nonlinear ordinary differential equations. With the application of a diffeomorphism that is based on differential flatness theory it is shown that an equivalent description of the system is obtained in the linear canonical (Brunovsky) form. This transformation enables to obtain local estimates about the state vector of the DNA model through the application us of the standard Kalman filter recursion. At a second stage, the local statistical approach to fault diagnosis is used to perform fault diagnosis for this distributed parameter system by processing with statistical tools the differences (residuals) between the output of the Kalman filter and the measurements obtained from the distributed parameter system. Optimal selection of the fault threshold is succeeded by using the local statistical approach to fault diagnosis. The efficiency of the proposed filtering approach in the problem of fault diagnosis for parametric change detection, in nonlinear wave-type models of DNA dynamics, is confirmed through simulation experiments.
NASA Astrophysics Data System (ADS)
Casarini, L.; Bonometto, S. A.; Tessarotto, E.; Corasaniti, P.-S.
2016-08-01
We discuss an extension of the Coyote emulator to predict non-linear matter power spectra of dark energy (DE) models with a scale factor dependent equation of state of the form w = w0+(1-a)wa. The extension is based on the mapping rule between non-linear spectra of DE models with constant equation of state and those with time varying one originally introduced in ref. [40]. Using a series of N-body simulations we show that the spectral equivalence is accurate to sub-percent level across the same range of modes and redshift covered by the Coyote suite. Thus, the extended emulator provides a very efficient and accurate tool to predict non-linear power spectra for DE models with w0-wa parametrization. According to the same criteria we have developed a numerical code that we have implemented in a dedicated module for the CAMB code, that can be used in combination with the Coyote Emulator in likelihood analyses of non-linear matter power spectrum measurements. All codes can be found at https://github.com/luciano-casarini/pkequal.
Jovian S emission: Model of radiation source
NASA Astrophysics Data System (ADS)
Ryabov, B. P.
1994-04-01
A physical model of the radiation source and an excitation mechanism have been suggested for the S component in Jupiter's sporadic radio emission. The model provides a unique explanation for most of the interrelated phenomena observed, allowing a consistent interpretation of the emission cone structure, behavior of the integrated radio spectrum, occurrence probability of S bursts, location and size of the radiation source, and fine structure of the dynamic spectra. The mechanism responsible for the S bursts is also discussed in connection with the L type emission. Relations are traced between parameters of the radio emission and geometry of the Io flux tube. Fluctuations in the current amplitude through the tube are estimated, along with the refractive index value and mass density of the plasma near the radiation source.
NASA Astrophysics Data System (ADS)
Valotto, Gabrio; Varin, Cristiano
2016-01-01
An additive modeling approach is employed to provide a statistical description of hourly variation in concentrations of NOx measured in proximity of the Venice "Marco Polo" International Airport, Italy. Differently from several previous studies on airport emissions based on daily time series, the paper analyzes hourly data because variations of NOx concentrations during the day are informative about the prevailing emission source. The statistical analysis is carried out using a one-year time series. Confounder effects due to seasonality, meteorology and airport traffic volume are accounted for by suitable covariates. Four different model specifications of increasing complexity are considered. The model with the aircraft source expressed as the NOx emitted near the airport is found to have the best predictive quality. Although the aircraft source is statistically significant, the comparison of model-based predictions suggests that the relative impact of aircraft emissions to ambient NOx concentrations is limited and the road traffic is the likely dominant source near the sampling point.
A Theory of Cramer-Rao Bounds for Constrained Parametric Models
2010-01-01
finite impulse response iid independent and identically distributed LSE least squares estimate (or estimator) MIMO multiple-input, multiple-output ML...1, . . . , K, and 4. the calibrated model (with constraints and a transformation of parameters). For generality, we consider the full ( MIMO ) model...are then presented in the communications context for the convolutive mixture model and the calibrated array model. Report Documentation Page Form
A Semi-Parametric Bayesian Mixture Modeling Approach for the Analysis of Judge Mediated Data
ERIC Educational Resources Information Center
Muckle, Timothy Joseph
2010-01-01
Existing methods for the analysis of ordinal-level data arising from judge ratings, such as the Multi-Facet Rasch model (MFRM, or the so-called Facets model) have been widely used in assessment in order to render fair examinee ability estimates in situations where the judges vary in their behavior or severity. However, this model makes certain…
Shukla, Mukesh Kumar; Maji, Partha Sona; Das, Ritwick
2016-07-01
We present an efficient and tunable source generating multi-watt single-frequency red radiation by intra-cavity frequency doubling of the signal in a MgO-doped periodically poled LiNbO_{3} (MgO:PPLN)-based singly resonant optical parametric oscillator (SRO). By optimally designing the SRO cavity in a six-mirror configuration, we generate ≈276 nm tunable idler radiation in mid-infrared with a maximum power of P_{i}=2.05 W at a pump power of P_{p}=14.0 W. The resonant signal is frequency doubled using a 10 mm-long BiB_{3}O_{6} (BiBO) crystal which resulted in tunability of a red beam from ≈753 to 780 nm band with maximum power P_{r}≈4.0 W recorded at λ_{r}≈756 nm. The deployment of a six-mirror SRO ensures single-frequency generation of red across the entire tuning range by inducing additional losses to Raman modes of LiNbO_{3} and, thus, inhibiting their oscillation. Using a scanning Fabry-Perot interferometer (FPI), nominal linewidth of the red beam is measured to ≈3 MHz which changes marginally over the entire tuning range. Long-term (over 1 h) peak-to-peak frequency fluctuation of the generated red beam is estimated to be about 3.3 GHz under free-running conditions at P_{p}=14.0 W. The generated red beam is delivered in a TEM_{00} mode profile with M^{2}≤1.32 at maximum power in a red beam.
SOURCE APPORTIONMENT RESULTS, UNCERTAINTIES, AND MODELING TOOLS
Advanced multivariate receptor modeling tools are available from the U.S. Environmental Protection Agency (EPA) that use only speciated sample data to identify and quantify sources of air pollution. EPA has developed both EPA Unmix and EPA Positive Matrix Factorization (PMF) and ...
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.
NASA Astrophysics Data System (ADS)
Wouters, Hendrik; Demuzere, Matthias; Blahak, Ulrich; Fortuniak, Krzysztof; Maiheu, Bino; Camps, Johan; Tielemans, Daniël; van Lipzig, Nicole P. M.
2016-09-01
This paper presents the Semi-empirical URban canopY parametrization (SURY) v1.0, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters - containing the three-dimensional information - into bulk parameters. As a result, it brings canopy-dependent urban physics to existing bulk urban land-surface schemes of atmospheric models. At the same time, SURY preserves a low computational cost of bulk schemes for efficient numerical weather prediction and climate modelling at the convection-permitting scales. It offers versatility and consistency for employing both urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (v5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (v2.0). The model reproduces very well the urban heat islands observed from in situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of atmospheric modelling with the COSMO-CLM model is addressed for the urban canopy parameter ranges from the local climate zones of http://WUDAPT.org. City-scale effects are found in modelling the land-surface temperatures, air temperatures and associated urban heat islands. Recommendations are formulated for more precise urban atmospheric modelling at the convection-permitting scales. It is concluded that urban canopy parametrizations including SURY, combined with the deployment of the WUDAPT urban database platform and advancements in atmospheric modelling systems, are essential.
Quantiles, Parametric-Select Density Estimations, and Bi-Information Parameter Estimators.
1982-06-01
A non- parametric estimation method forms estimators which are not based on parametric models. Important examples of non-parametric estimators of a...raw descriptive functions F, f, Q, q, fQ. One distinguishes between parametric and non-parametric methods of estimating smooth functions. A parametric ... estimation method : (1) assumes a family F8, fo’ Q0, qo’ foQ8 of functions, called parametric models, which are indexed by a parameter 6 = ( l
Parametrization of turbulence models using 3DVAR data assimilation in laboratory conditions
NASA Astrophysics Data System (ADS)
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
Beer-Lambert-Law Parametric Model of Reflectance Spectra for Dyed Fabrics
2016-06-06
electromagnetic spectrum. Devices such as Gen 3 Extended Blue Night Vision (NV) devices have increased spectral response from the visual to NIR...the fact that certain NIR dye treatments fail to provide effective contrast matching in the SWIR spectrum. Advances in detector technologies, e.g...region and an Indium Gallium Arsenide (InGaAs) detector for the NIR- SWIR (860 - 2500 nm) region. Radiation sources included a deuterium lamp for
An automated shell for management of parametric dispersion/deposition modeling
Paddock, R.A.; Absil, M.J.G.; Peerenboom, J.P.; Newsom, D.E.; North, M.J.; Coskey, R.J. Jr.
1994-03-01
In 1993, the US Army tasked Argonne National Laboratory to perform a study of chemical agent dispersion and deposition for the Chemical Stockpile Emergency Preparedness Program using an existing Army computer model. The study explored a wide range of situations in terms of six parameters: agent type, quantity released, liquid droplet size, release height, wind speed, and atmospheric stability. A number of discrete values of interest were chosen for each parameter resulting in a total of 18,144 possible different combinations of parameter values. Therefore, the need arose for a systematic method to assemble the large number of input streams for the model, filter out unrealistic combinations of parameter values, run the model, and extract the results of interest from the extensive model output. To meet these needs, we designed an automated shell for the computer model. The shell processed the inputs, ran the model, and reported the results of interest. By doing so, the shell compressed the time needed to perform the study and freed the researchers to focus on the evaluation and interpretation of the model predictions. The results of the study are still under review by the Army and other agencies; therefore, it would be premature to discuss the results in this paper. However, the design of the shell could be applied to other hazards for which multiple-parameter modeling is performed. This paper describes the design and operation of the shell as an example for other hazards and models.
Crowther, Michael J; Look, Maxime P; Riley, Richard D
2014-09-28
Multilevel mixed effects survival models are used in the analysis of clustered survival data, such as repeated events, multicenter clinical trials, and individual participant data (IPD) meta-analyses, to investigate heterogeneity in baseline risk and covariate effects. In this paper, we extend parametric frailty models including the exponential, Weibull and Gompertz proportional hazards (PH) models and the log logistic, log normal, and generalized gamma accelerated failure time models to allow any number of normally distributed random effects. Furthermore, we extend the flexible parametric survival model of Royston and Parmar, modeled on the log-cumulative hazard scale using restricted cubic splines, to include random effects while also allowing for non-PH (time-dependent effects). Maximum likelihood is used to estimate the models utilizing adaptive or nonadaptive Gauss-Hermite quadrature. The methods are evaluated through simulation studies representing clinically plausible scenarios of a multicenter trial and IPD meta-analysis, showing good performance of the estimation method. The flexible parametric mixed effects model is illustrated using a dataset of patients with kidney disease and repeated times to infection and an IPD meta-analysis of prognostic factor studies in patients with breast cancer. User-friendly Stata software is provided to implement the methods.
Yamamoto, Yu; Yamada, Shoichi
2016-02-20
We conducted one-dimensional and two-dimensional hydrodynamic simulations of post-shock revival evolutions in core-collapse supernovae, employing the simple neutrino light bulb approximation to produce explosions rather easily. In order to estimate the explosion energy, we took into proper account nuclear recombinations and fusions consistently with the equation of state for matter not in statistical equilibrium in general. The methodology is similar to our previous work, but is somehow improved. In this paper, we studied the influence of the progenitor structure on the dynamics systematically. In order to expedite our understanding of the systematics, we constructed six parametric progenitor models, which are different in masses of Fe iron core and Si+S layer, instead of employing realistic models provided by stellar evolution calculations, which are sometimes of stochastic nature as a function of stellar mass on the main sequence. We found that the explosion energy is tightly correlated with the mass accretion rate at shock revival irrespective of dimension and the progenitors with light iron cores but with rather high entropies, which have yet to be produced by realistic stellar evolution calculations, may reproduce the canonical values of explosion energy and nickel mass. The mass of the Si+S layer is also important in the mass accretion history after bounce, on the other hand; the higher mass accretion rates and resultant heavier cores tend to hamper strong explosions.
Kulmala, A; Tenhunen, M
2012-11-07
The signal of the dosimetric detector is generally dependent on the shape and size of the sensitive volume of the detector. In order to optimize the performance of the detector and reliability of the output signal the effect of the detector size should be corrected or, at least, taken into account. The response of the detector can be modelled using the convolution theorem that connects the system input (actual dose), output (measured result) and the effect of the detector (response function) by a linear convolution operator. We have developed the super-resolution and non-parametric deconvolution method for determination of the cylinder symmetric ionization chamber radial response function. We have demonstrated that the presented deconvolution method is able to determine the radial response for the Roos parallel plate ionization chamber with a better than 0.5 mm correspondence with the physical measures of the chamber. In addition, the performance of the method was proved by the excellent agreement between the output factors of the stereotactic conical collimators (4-20 mm diameter) measured by the Roos chamber, where the detector size is larger than the measured field, and the reference detector (diode). The presented deconvolution method has a potential in providing reference data for more accurate physical models of the ionization chamber as well as for improving and enhancing the performance of the detectors in specific dosimetric problems.
Eldeeb, Safaa M; Abdelmoula, Walid M; Shah, Syed M; Fahmy, Ahmed S
2012-01-01
Age-related macular degeneration (AMD) is a major cause of blindness and visual impairment in older adults. The wet form of the disease is characterized by abnormal blood vessels forming a choroidal neovascular membrane (CNV), that result in destruction of normal architecture of the retina. Current evaluation and follow up of wet AMD include subjective evaluation of Fluorescein Angiograms (FA) to determine the activity of the lesion and monitor the progression or regression of the disease. However, this subjective evaluation prevents accurate monitoring of the disease progression or regression in response to a pharmacologic agent. In this work, we present a method that allows objective assessment of the activity of a CNV lesion which can be statistically compared across different patient and time points. The method is based on a hypothesis that the discrepancy in the time-intensity signals among the diseased and normal retinal areas are due to an implicit transfer function whose parameters can be used to characterize the retina. The method begins with parametric modeling of the temporal variation of the lesion and background intensities. Then, the values of the model parameters are used to evaluate the change in the activity of the disease. Preliminary results on five datasets show that the calculated parameters are highly correlated with the Visual Acuity (VA) of the patients.
Modeling the Soil Moisture Parametrization in a Snow Dominated Mountainous Region
NASA Astrophysics Data System (ADS)
Kikine, Daniel; Sensoy, Aynur; Sorman, Arda
2016-04-01
The study quantifies the effects of both the soil moisture accounting and the temperature index in the event based as well as the continuous simulation of a model in a snow dominated basin. Physically based watershed model parameters are required to reproduce the historical flows and forecast the stream flows. This study demonstrates that parameterization of hydrological model is a favorable approach to perform forecasting because it employs the relationship of the calibrated model parameters and those of the watershed's physical properties. With this consideration, the temperature index (degree-day) snowmelt and the soil moisture accounting models within the Hydrologic Engineering Center's hydrologic modeling system (HEC-HMS) are applied to the Upper Euphrates watershed. The versatile 14-parameter soil moisture accounting (SMA) algorithm is utilized for a better simulation and parameterization of the watershed. The methodology was exemplified by performing various independent simulations using the meteorological data and the observed stream discharges. The soil moisture parameters were calibrated and modified according to their statistical relationships with the land use for the 2002 - 2008 period, the obtained parameter set are then validated for the 2009 - 2012 period. Model outputs are evaluated in comparison to satellite derived soil moisture and snow water equivalent data. Deterministic Numerical Weather Prediction data are used together with the conceptual model to forecast runoff for the melting period of the year 2015.
Regression Is a Univariate General Linear Model Subsuming Other Parametric Methods as Special Cases.
ERIC Educational Resources Information Center
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…
Technology Transfer Automated Retrieval System (TEKTRAN)
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
NASA Astrophysics Data System (ADS)
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.
Tsongas, G.A. ); White, T.J. )
1989-10-01
A Brayton open-cycle engine is under development. It operates similarly to a gas turbine engine, but uses reciprocating piston compressor and expander components. The design appears to have a number of advantages, including multifuel capability, the potential for lower cost, and the ability to be scaled to small sizes without significant loss in efficiency. An interactive microcomputer model has been developed that analyzes the thermodynamic performance of the engine. The model incorporates all the important irreversibilities found in piston devices, including heat transfer, mechanical friction, pressure losses, and mass loss and recirculation. There are 38 input parameters to the model. Key independent operating parameters are maximum temperature, compressor rpm, and pressure ratio. The development of the model and its assumptions are outlined in this paper. The emphasis is on model applications.
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.
NASA Astrophysics Data System (ADS)
Frick, Maximilian; Sippel, Judith; Cacace, Mauro; Scheck-Wenderoth, Magdalena
2016-04-01
The goal of this study was to quantify the influence of the geological structure and geophysical parametrization of model units on the geothermal field as calculated by 3D numerical simulations of coupled fluid and heat transport for the subsurface of Berlin, Germany. The study area is located in the Northeast German Basin which is filled with several kilometers of sediments. This sedimentary infill includes the clastic sedimentary units Middle Buntsandstein and Sedimentary Rotliegend which are of particular interest for geothermal exploration. Previous studies conducted in the Northeast German Basin have already shown the geometries and properties of the geological units majorly control the distribution of subsurface temperatures. In this study we followed a two-step approach, where we first improved an existing structural model by integrating newly available 57 geological cross-sections, well data and deep seismics (down to ~4 km). Secondly, we performed a sensitivity analysis investigating the effects of varying physical fluid and rock properties on the subsurface temperature field. The results of this study show, that the structural configuration of model units exerts the highest influence on the geothermal field (up to ± 23 K at 1000 m below sea level). Here, the Rupelian clay aquitard, displaying a heterogeneous thickness distribution, locally characterized by hydrogeological windows (i.e. domains of no thickness) enabling intra-aquifer groundwater circulation has been identified as major controlling factor. The new structural configuration of this unit (more continuous, less numerous hydrogeological windows) also leads to a reduction of the influence of different boundary conditions and heat transport mechanisms considered. Additionally, the models results show that calculated temperatures highly depend on geophysical properties of model units whereas the hydraulic conductivity of the Cenozoic succession was identified as most dominant, leading to changes
Semi-Parametric Spatial Joint Modeling of HIV and HSV-2 among Women in Kenya
Okango, Elphas; Mwambi, Henry; Ngesa, Oscar; Achia, Thomas
2015-01-01
Several diseases have common risk factors. The joint modeling of disease outcomes within a spatial statistical context may provide more insight on the interaction of diseases both at individual and at regional level. Spatial joint modeling allows for studying of the relationship between diseases and also between regions under study. One major approach for joint spatial modeling is the multivariate conditional autoregressive approach. In this approach, it is assumed that all the covariates in the study have linear effects on the multiple response variables. In this study, we relax this linearity assumption and allow some covariates to have nonlinear effects using the penalized regression splines. This model was used to jointly model the spatial variation of human immunodeficiency virus (HIV) and herpes simplex virus-type 2 (HSV-2) among women in Kenya. The model was applied to HIV and HSV-2 prevalence data among women aged 15–49 years in Kenya, derived from the 2007 Kenya AIDS indicator survey. A full Bayesian approach was used and the models were implemented in WinBUGS software. Both diseases showed significant spatial variation with highest disease burdens occurring around the Lake Victoria region. There was a nonlinear association between age of an individual and HIV and HSV-2 infection. The peak age for HIV was around 30 years while that of HSV-2 was about 40 years. A positive significant spatial correlation between HIV and HSV-2 was observed with a correlation of 0.6831(95% CI: 0.3859, 0.871). PMID:26258939
Parametric Modeling of Human Gradient Walking for Predicting Minimum Energy Expenditure
Saborit, Gerard; Casinos, Adrià
2015-01-01
A mathematical model to predict the optimum gradient for a minimum energetic cost is proposed, based on previous results that showed a minimum energetic cost when gradient is −10%. The model focuses on the variation in mechanical energy during gradient walking. It is shown that kinetic energy plays a marginal role in low speed gradient walking. Therefore, the model considers only potential energy. A mathematical parameter that depends on step length was introduced, showing that the optimal gradient is a function of that parameter. Consequently, the optimal negative gradient depends on the individual step length. The model explains why recent results do not suggest a single optimal gradient but rather a range around −10%. PMID:26417377
Integrated likelihoods in parametric survival models for highly clustered censored data.
Cortese, Giuliana; Sartori, Nicola
2016-07-01
In studies that involve censored time-to-event data, stratification is frequently encountered due to different reasons, such as stratified sampling or model adjustment due to violation of model assumptions. Often, the main interest is not in the clustering variables, and the cluster-related parameters are treated as nuisance. When inference is about a parameter of interest in presence of many nuisance parameters, standard likelihood methods often perform very poorly and may lead to severe bias. This problem is particularly evident in models for clustered data with cluster-specific nuisance parameters, when the number of clusters is relatively high with respect to the within-cluster size. However, it is still unclear how the presence of censoring would affect this issue. We consider clustered failure time data with independent censoring, and propose frequentist inference based on an integrated likelihood. We then apply the proposed approach to a stratified Weibull model. Simulation studies show that appropriately defined integrated likelihoods provide very accurate inferential results in all circumstances, such as for highly clustered data or heavy censoring, even in extreme settings where standard likelihood procedures lead to strongly misleading results. We show that the proposed method performs generally as well as the frailty model, but it is superior when the frailty distribution is seriously misspecified. An application, which concerns treatments for a frequent disease in late-stage HIV-infected people, illustrates the proposed inferential method in Weibull regression models, and compares different inferential conclusions from alternative methods.
Modelling of amorphous cellulose depolymerisation by cellulases, parametric studies and optimisation
Niu, Hongxing; Shah, Nilay; Kontoravdi, Cleo
2016-01-01
Improved understanding of heterogeneous cellulose hydrolysis by cellulases is the basis for optimising enzymatic catalysis-based cellulosic biorefineries. A detailed mechanistic model is developed to describe the dynamic adsorption/desorption and synergistic chain-end scissions of cellulases (endoglucanase, exoglucanase, and β-glucosidase) upon amorphous cellulose. The model can predict evolutions of the chain lengths of insoluble cellulose polymers and production of soluble sugars during hydrolysis. Simultaneously, a modelling framework for uncertainty analysis is built based on a quasi-Monte-Carlo method and global sensitivity analysis, which can systematically identify key parameters, help refine the model and improve its identifiability. The model, initially comprising 27 parameters, is found to be over-parameterized with structural and practical identification problems under usual operating conditions (low enzyme loadings). The parameter estimation problem is therefore mathematically ill posed. The framework allows us, on the one hand, to identify a subset of 13 crucial parameters, of which more accurate confidence intervals are estimated using a given experimental dataset, and, on the other hand, to overcome the identification problems. The model’s predictive capability is checked against an independent set of experimental data. Finally, the optimal composition of cellulases cocktail is obtained by model-based optimisation both for enzymatic hydrolysis and for the process of simultaneous saccharification and fermentation. PMID:26865832
New depositional models for Cretaceous source rocks
Kauffman, E.G.; Villamil, T. )
1993-02-01
The Cretaceous marks one of the greatest periods of source rock development in geologic history, especially in coastal and epi-continental marine basins where the number, duration, and geographic extent of Corg-rich intervals exceeds that of oceanic basins. Large-scale factors regulating Cretaceous source rocks include sealevel, sedimentation rate/type, paleoclimate and marine thermal gradients, paleoceanography (circulation, stratification, chemistry, upwelling, nutrient supply), and surface water productivity. Marine dispositional settings favored as models for Corg concentration include silled and tectonically depressed basins, intersection of OMZ's with shallow continental seas, coastal upwelling, highly stratified shallow seas, and oceanic anoxic events (OAE's). All of these settings are thought to be characterized by stagnant, anoxic/highly dysoxic water masses above the sediment-water interface, and highly stressed benthic environments. This seemingly supported by fine lamination, spare bioturbation, high pyrite and Corg content of most source rocks. But high-resolution (cm-scale) sedimentologic, paleobiologic, and geochemical analyses of Jurassic-Cretaceous source rocks reveal, instead, dynamic benthic environments with active currents, episodically crowded with diverse life in event communities, and persistently characterized by longer term, low diversity resident benthic communities. These characteristics indicate rapidly fluctuating, predominantly dysoxic to oxic waters at and above the sediment-water interface for most Corg-rich black shales. A new model for source rock generation is proposed which retains the redox boundary at or near the sediment-water interface over large areas of seafloor, in part aided by extensive development of benthic microbial mats which may contribute up to 30% of the Corg to marine source rocks.
Crop coefficients parametrization using remote sensing in basin-scale hydrological modelling
NASA Astrophysics Data System (ADS)
Hunink, Johannes E.; Eekhout, Joris P. C.; de Vente, Joris; Contreras, Sergio; Droogers, Peter
2016-04-01
Satellite-based vegetation indices as Normalized Difference Vegetation Index (NDVI) are increasingly used to derive crop coefficients (kc) for field-scale soil water balance modelling, and for operational monitoring of evapotranspiration (ET). However, for basin-scale hydrological modelling, kc values are traditionally based on literature values, crop and management specific (e.g. FAO-56). For basin-scale analysis, these tabular kc-values are prone to misinterpretations, such as, site specific crop seasons and climate variability within the catchment. Compared to the traditional approach, the advantage of using an NDVI-based method is that observed information on current vegetative status is captured, from which "real" crop coefficients may be derived. However, for future scenario analysis, no satellite-based data are available, hence, crop coefficients need to be estimated either from literature values that are not site-specific, or based on historic NDVI observations. The aim of this study is to evaluate the impacts of various crop coefficient parameterization methods on the performance of a basin-scale hydrological model. We assume actual NDVI as the best available proxy for the crop coefficient and calibrate a hydrological model (SPHY) with monthly reservoir inflows: the reference model. Then, we change the crop coefficient parameterizations of this model with three different parameterizations and compare outputs for a validation period. The study is performed in the sub-humid to semi-arid Upper Segura basin (2592 km2) in SE Spain. The three parameterization methods we evaluate are: (1) land-cover specific kc values using traditional approach from reference tables (FAO-56), (2) land-cover specific kc values obtained from seasonal trajectories of NDVI, (3) pixel-specific seasonal kc values from NDVI trajectories of each pixel. To evaluate the performance of the three methods, spatial and temporal patterns of simulated streamflow, evapotranspiration, and soil
Rathour, Rahul Kumar; Narayanan, Rishikesh
2012-11-15
Voltage-gated ion channels play a critical role in regulating neuronal intrinsic response dynamics (IRD). Here, we computationally analysed the roles of the two inactivating subthreshold conductances (A and T), individually and in various combinations with the non-inactivating h conductance, in regulating several physiological IRD measurements in the theta frequency range. We found that the independent presence of a T conductance, unlike that of an h conductance, was unable to sustain an inductive phase lead in the theta frequency range, despite its ability to mediate theta frequency resonance. The A conductance, on the other hand, when expressed independently, acted in a manner similar to a leak conductance with reference to most IRD measurements. Next, analysing the impact of pair-wise coexpression of these channels, we found that the coexpression of the h and T conductances augmented the range of parameters over which they sustained resonance and inductive phase lead. Additionally, coexpression of the A conductance with the h or the T conductance elicited changes in IRD measurements that were similar to those obtained with the expression of a leak conductance with a resonating conductance. Finally, to understand the global sensitivity of IRD measurements to all parameters associated with models expressing all three channels, we generated 100,000 neuronal models, each built with a unique set of parametric values. We categorized valid models among these by matching their IRD measurements with experimental counterparts, and found that functionally similar models could be achieved even when underlying parameters displayed tremendous variability and exhibited weak pair-wise correlations. Our results suggest that the three prominent subthreshold conductances contribute differently to intrinsic excitability and to phase coding. We postulate that the differential expression and activity-dependent plasticity of these conductances contribute to robustness of subthreshold
Nanoscale electromechanical parametric amplifier
Aleman, Benjamin Jose; Zettl, Alexander
2016-09-20
This disclosure provides systems, methods, and apparatus related to a parametric amplifier. In one aspect, a device includes an electron source electrode, a counter electrode, and a pumping electrode. The electron source electrode may include a conductive base and a flexible conductor. The flexible conductor may have a first end and a second end, with the second end of the flexible conductor being coupled to the conductive base. A cross-sectional dimension of the flexible conductor may be less than about 100 nanometers. The counter electrode may be disposed proximate the first end of the flexible conductor and spaced a first distance from the first end of the flexible conductor. The pumping electrode may be disposed proximate a length of the flexible conductor and spaced a second distance from the flexible conductor.
Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy
NASA Astrophysics Data System (ADS)
Gil, D.; Garcia-Barnes, J.; Hernández-Sabate, A.; Marti, E.
2010-03-01
Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.
The operation of a solid polymer fuel cell - A parametric model
NASA Astrophysics Data System (ADS)
Amphlett, J. C.; Farahani, M.; Mann, R. F.; Peppley, B. A.; Roberge, P. R.
An empirical model of the performance of the Ballard Power Systems Mark IV fuel cell is developed. The model contains seven parameters, each one associated with a specific operating variable. Cell voltages at 400 ASF were measured for pressures from 15 to 35 psig; temperatures of 60, 70, and 80 C; excess hydrogen feed from 5-25 percent; excess oxygen feed from 50-150 percent; and oxygen concentrations in nitrogen from 21-100 percent by volume. Polarization curves were also measured for current densities from 200-500 ASF. Using these data, a set of coefficients was determined to give the best prediction of single-cell performance. The model was then tested against data from a 12-cell stack of similar design and found to predict variation in cell voltage to within 5 percent. The model can be used to predict the electrochemical efficiency of the fuel cell in the neighborhood of a baseline condition. The utility of the model is in developing a simulation of an integrated methanol reformer/fuel cell power generating system.
Parametric estimation in a genetic mixture model with application to nuclear family data.
Shoukri, M M; McLachlan, G J
1994-03-01
The apparent conflict between the biometrician and Mendelian genetics has been recently resolved by the introduction of a genetic mixed model to analyze continuous traits measured on human families and to elucidate the mechanism of underlying major genes. The mixed model formulated by Elston and Stewart (1971, Human Heredity 21, 523-542), extended by Morton and MacLean (1974, American Journal of Human Genetics 26, 489-503), and reviewed, with further extensions, by Boyle and Elston (1979, Biometrics 35, 55-68) has become an extremely useful tool of wide applicability in the field of genetic epidemiology. This model allows for segregation at a major locus, a polygenic effect, and a sibling environmental variation. The main concern of this paper is with estimating the model parameters by the method of maximum likelihood. The expectation-maximization (EM) algorithm is developed to derive the estimates iteratively. An approximation of the information matrix when using the EM algorithm is given. We illustrate the methodology by fitting the model to the arterial blood pressure data collected by Miall and Oldham (1955, Clinical Science 14, 459-487).
Cabarrou, B; Belin, L; Somda, S M; Falcou, M C; Pierga, J Y; Kirova, Y; Delord, J P; Asselain, B; Filleron, T
2016-04-01
Use of parametric statistical models can be a solution to reduce the follow-up period time required to estimate long-term survival. Mould and Boag were the first to use the lognormal model. Competing risks methodology seems more suitable when a particular event type is of interest than classical survival analysis. The objective was to evaluate the ability of the Jeong and Fine model to predict long-term cumulative incidence. Survival data recorded by Institut Curie (Paris) from 4761 breast cancer patients treated and followed between 1981 and 2013 were used. Long-term cumulative incidence rates predicted by the model using short-term follow-up data were compared to non-parametric estimation using complete follow-up data. 20- or 25-year cumulative incidence rates for loco-regional recurrence and distant metastasis predicted by the model using a maximum of 10 years of follow-up data had a maximum difference of around 6 % compared to non-parametric estimation. Prediction rates were underestimated for the third and composite event (contralateral or second cancer or death). Predictive ability of Jeong and Fine model on breast cancer data was generally good considering the short follow-up period time used for the estimation especially when a proportion of patient did not experience loco-regional recurrence or distant metastasis.
NASA Astrophysics Data System (ADS)
Johnson, Helen; Best, Martin
2015-04-01
It has been understood for a while now that atmospheric behaviour is affected by land surface processes, modelling this relationship however still presents challenges. Most numerical weather prediction (NWP) models couple an atmospheric model to a land surface model in order to forecast the weather and/or climate. The Global Land-Atmosphere Coupling Experiment (GLACE) demonstrated that soil moisture variability has considerable control over atmospheric behaviour, particularly impacting on precipitation and temperature variability. The study also suggested that differences in coupling strengths between models may be due to differences in atmospheric parametrizations. There have since been other studies which support this claim but it is not yet clear which parameters control the land-atmosphere coupling strength or indeed what it should be. In this study we investigate whether certain atmospheric parameters hold more control than others over model sensitivity to land surface changes. We focus on the interaction of the JULES (Joint UK Land Environment Simulator) land surface model with the Met Office Unified Model (UM) that is used for operational NWP and climate prediction. For computational efficiency we ran the UM at a single site using a single column model (SCM) rather than running a global model simulation. A site in the Sahel region of West Africa was chosen as this is an area that was identified by GLACE as being especially responsive to changes in soil moisture. JULES was run several times with various different initial soil moisture profiles to create an ensemble of surface sensible and latent heat fluxes that could be used to force a set of different SCM runs in order to simulate a range of different atmospheric conditions. Various atmospheric parameters in the SCM were then perturbed to create additional sets of SCM runs with different sensitivities to soil moisture changes. By analysing the difference in spread between the standard configuration and the
Comparison of stochastic parametrization approaches in a single-column model.
Ball, Michael A; Plant, Robert S
2008-07-28
We discuss and test the potential usefulness of single-column models (SCMs) for the testing of stochastic physics schemes that have been proposed for use in general circulation models (GCMs). We argue that although single-column tests cannot be definitive in exposing the full behaviour of a stochastic method in the full GCM, and although there are differences between SCM testing of deterministic and stochastic methods, SCM testing remains a useful tool. It is necessary to consider an ensemble of SCM runs produced by the stochastic method. These can be usefully compared with deterministic ensembles describing initial condition uncertainty and also with combinations of these (with structural model changes) into poor man's ensembles. The proposed methodology is demonstrated using an SCM experiment recently developed by the GCSS (GEWEX Cloud System Study) community, simulating transitions between active and suppressed periods of tropical convection.
A parametric model for analysis of melt progression in U-A1 assemblies
Paik, I.K. ); Kim, S.H.; Leonard, M.T.; Amos, C.N. )
1990-06-15
A computational model has been developed that calculates the thermal degradation of the reactor core of the production reactors at the Savannah River Site (SRS) under postulated severe accident conditions. This model addresses heatup and degradation of the U-Al fuel and Li-Al or U-metal target assemblies and neighboring structures. Models included are those for assembly heatup due to decay heat generation, material melting and relocation, volume expansion of fuel due to foaming and melt/debris accumulation in assembly bottom end-fittings. Sample results are presented that illustrate the effect of alternative assumptions regarding the temperature at which U-Al alloy melts and relocates and the extent to which fuel foaming thermally couples adjacent fuel and target tubes. 5 refs., 6 figs., 1 tab.
Simple Parametric Model for Intensity Calibration of Cassini Composite Infrared Spectrometer Data
NASA Technical Reports Server (NTRS)
Brasunas, J.; Mamoutkine, A.; Gorius, N.
2016-01-01
Accurate intensity calibration of a linear Fourier-transform spectrometer typically requires the unknown science target and the two calibration targets to be acquired under identical conditions. We present a simple model suitable for vector calibration that enables accurate calibration via adjustments of measured spectral amplitudes and phases when these three targets are recorded at different detector or optics temperatures. Our model makes calibration more accurate both by minimizing biases due to changing instrument temperatures that are always present at some level and by decreasing estimate variance through incorporating larger averages of science and calibration interferogram scans.
Parametric Adjustments to the Rankine Vortex Wind Model for Gulf of Mexico Hurricanes
2012-11-01
Gulf of Mexico hurricanes show considerable differences between the resulting wind speeds and data. The differences are used to guide the development of adjustment factors to improve the wind fields resulting from the Rankine Vortex model. The corrected model shows a significant improvement in the shape, size, and wind speed contours for 14 out of 17 hurricanes examined. The effect on wave fields resulting from the original and modified wind fields are on the order of 4 m, which is important for the estimation of extreme wave
Lucero-Acuña, Armando; Guzmán, Roberto
2015-10-15
A mathematical model of drug release that incorporates the simultaneous contributions of initial burst, nanoparticle degradation-relaxation and diffusion was developed and used to effectively describe the release of a kinase inhibitor and anticancer drug, PHT-427. The encapsulation of this drug into PLGA nanoparticles was performed by following the single emulsion-solvent evaporation technique and the release was determined in phosphate buffer pH 7.4 at 37 °C. The size of nanoparticles was obtained in a range of 162-254 nm. The experimental release profiles showed three well defined phases: an initial fast drug release, followed by a nanoparticle degradation-relaxation slower release and then a diffusion release phase. The effects of the controlled release most relevant parameters such as drug diffusivity, initial burst constant, nanoparticle degradation-relaxation constant, and the time to achieve a maximum rate of drug release were evaluated by a parametrical analysis. The theoretical release studies were corroborated experimentally by evaluating the cytotoxicity effectiveness of the inhibitor AKT/PDK1 loaded nanoparticles over BxPC-3 pancreatic cancer cells in vitro. These studies show that the encapsulated inhibitor AKT/PDK1 in the nanoparticles is more accessible and thus more effective when compared with the drug alone, indicating their potential use in chemotherapeutic applications.
Lin, Chun-Cheng
2008-09-01
This work analyzes and attempts to enhance the accuracy and reproducibility of parametric modeling in the discrete cosine transform (DCT) domain for the estimation of abnormal intra-QRS potentials (AIQP) in signal-averaged electrocardiograms. One hundred sets of white noise with a flat frequency response were introduced to simulate the unpredictable, broadband AIQP when quantitatively analyzing estimation error. Further, a high-frequency AIQP parameter was defined to minimize estimation error caused by the overlap between normal QRS and AIQP in low-frequency DCT coefficients. Seventy-two patients from Taiwan were recruited for the study, comprising 30 patients with ventricular tachycardia (VT) and 42 without VT. Analytical results showed that VT patients had a significant decrease in the estimated AIQP. The global diagnostic performance (area under the receiver operating characteristic curve) of AIQP rose from 73.0% to 84.2% in lead Y, and from 58.3% to 79.1% in lead Z, when the high-frequency range fell from 100% to 80%. The combination of AIQP and ventricular late potentials further enhanced performance to 92.9% (specificity=90.5%, sensitivity=90%). Therefore, the significantly reduced AIQP in VT patients, possibly also including dominant unpredictable potentials within the normal QRS complex, may be new promising evidence of ventricular arrhythmias.
Cosmogenic photons strongly constrain UHECR source models
NASA Astrophysics Data System (ADS)
van Vliet, Arjen
2017-03-01
With the newest version of our Monte Carlo code for ultra-high-energy cosmic ray (UHECR) propagation, CRPropa 3, the flux of neutrinos and photons due to interactions of UHECRs with extragalactic background light can be predicted. Together with the recently updated data for the isotropic diffuse gamma-ray background (IGRB) by Fermi LAT, it is now possible to severely constrain UHECR source models. The evolution of the UHECR sources especially plays an important role in the determination of the expected secondary photon spectrum. Pure proton UHECR models are already strongly constrained, primarily by the highest energy bins of Fermi LAT's IGRB, as long as their number density is not strongly peaked at recent times.
Boundary element model for simulating sound propagation and source localization within the lungs.
Ozer, M B; Acikgoz, S; Royston, T J; Mansy, H A; Sandler, R H
2007-07-01
An acoustic boundary element (BE) model is used to simulate sound propagation in the lung parenchyma. It is computationally validated and then compared with experimental studies on lung phantom models. Parametric studies quantify the effect of different model parameters on the resulting acoustic field within the lung phantoms. The BE model is then coupled with a source localization algorithm to predict the position of an acoustic source within the phantom. Experimental studies validate the BE-based source localization algorithm and show that the same algorithm does not perform as well if the BE simulation is replaced with a free field assumption that neglects reflections and standing wave patterns created within the finite-size lung phantom. The BE model and source localization procedure are then applied to actual lung geometry taken from the National Library of Medicine's Visible Human Project. These numerical studies are in agreement with the studies on simpler geometry in that use of a BE model in place of the free field assumption alters the predicted acoustic field and source localization results. This work is relevant to the development of advanced auscultatory techniques that utilize multiple noninvasive sensors to construct acoustic images of sound generation and transmission to identify pathologies.
ERIC Educational Resources Information Center
Lee, Young-Sun; Wollack, James A.; Douglas, Jeffrey
2009-01-01
The purpose of this study was to assess the model fit of a 2PL through comparison with the nonparametric item characteristic curve (ICC) estimation procedures. Results indicate that three nonparametric procedures implemented produced ICCs that are similar to that of the 2PL for items simulated to fit the 2PL. However for misfitting items,…
Technology Transfer Automated Retrieval System (TEKTRAN)
Surface soil moisture is an important parameter in hydrology and climate investigations. Current and future satellite missions with L-band passive microwave radiometers can provide valuable information for monitoring the global soil moisture. A factor that can play a significant role in the modeling...
Kafarov, V.V.; Pisarenko, V.N.; Usacheva, I.I.
1986-04-01
A description is given of a pulse method for the investigation of heterogeneous catalytic processes, through which the parameters of a model can be evaluated with high accuracy. An example is given of the application of the procedure to an alloy catalyst.
A parametric study of the drift-tearing mode using an extended-magnetohydrodynamic model
King, Jacob R.; Kruger, S. E.
2014-10-24
The linear, collisional, constant-ψ drift-tearing mode is analyzed for different regimes of the plasma-β, ion-skin-depth parameter space with an unreduced, extended-magnetohydrodynamic model. Here, new dispersion relations are found at moderate plasma β and previous drift-tearing results are classified as applicable at small plasma β.
A comparison of NEAR actual spacecraft costs with three parametric cost models
NASA Astrophysics Data System (ADS)
Mosher, Todd J.; Lao, Norman Y.; Davalos, Evelyn T.; Bearden, David A.
1999-11-01
Costs for modern (post-1990) U.S.-built small planetary spacecraft have been shown to exhibit significantly different trends from those of larger spacecraft. These differences cannot be accounted for simply by the change in size alone. Some have attributed this departure to NASA's "faster, better, cheaper" design approach embodied by the efficiency of smaller teams, reduced government oversight, increased focus on cost, and short development periods. With the Discovery, Mars Surveyor and New Millennium programs representing the new approach to planetary exploration, it is important to understand these current cost trends and to be able to estimate costs of future proposed missions. To address this issue, The Aerospace Corporation (hereafter referred to as Aerospace) performed a study to compare the actual costs of the Near Earth Asteroid Rendezvous (NEAR) spacecraft bus (instruments were not estimated) using three different cost models; the U.S. Air Force Unmanned Spacecraft Cost Model, Version 7 (USCM-7), the Science Applications International Corporation (SAIC) NASA/Air Force Cost Model 1996 (NAFCOM96) and The Aerospace Corporation's Small Satellite Cost Model 1998 (SSCM98). The NEAR spacecraft was chosen for comparison because it was the first Discovery mission launched, and recently recognized with a Laurel award by Aviation Week and Space Technology as a benchmark for NASA's Discovery program [North, 1997]. It was also selected because the cost data has been released into the public domain [Hemmings, 1996]which makes it easy to discuss in a public forum. This paper summarizes the NEAR program, provides a short synopsis of each of the three cost models, and demonstrates how they were applied for this study.
Update on the Electron Source Model
Cowee, Misa; Winske, Dan
2012-07-17
We summarize work done in FY12 on the Los Alamos Electron Source Model (ESM), which predicts the distribution of beta-decay electrons after a high altitude nuclear explosion (HANE) as a function of L, energy, and pitch angle. In the last year we have compared model results with data taken after the Russian 2 HANE test of 1962 and presented results at the HEART conference. We discuss our future plans to continue comparison with HANE data and to develop the code to allow a more complex set of initial conditions.
A parametric study of dissociation and ionization models at 12 km/sec
NASA Technical Reports Server (NTRS)
Mitcheltree, R. A.
1991-01-01
Thermochemical nonequilibrium-solution dependence on available models for the chemical reaction rates is examined. Solutions from the Kang and Dunn (1973) reaction-rate set, the Park rate set of 1987, and the Park rate set of 1991 are compared. The blunt-nosed, axisymmetric geometry considered is a 60-deg sphere cone with nose radius of 1.07 m and cicular aft skirt. The nonequilibrium test case is 12 km/sec entry into the earth's atmosphere at 80 km altitude. The model variations are implemented into the Langley aerothermodynamics upwind relaxation algorithm code. While variations in the reaction rates have no effect on the surface pressure distribution and little effect on the convective heating, the effect on degree of ionization and radiative heating can be a factor of three.
Parametric Modeling of the Safety Effects of NextGen Terminal Maneuvering Area Conflict Scenarios
NASA Technical Reports Server (NTRS)
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.
Single sweep analysis of visual evoked potentials through a model of parametric identification.
Cerutti, S; Baselli, G; Liberati, D; Pavesi, G
1987-01-01
An original method is presented for the single sweep analysis of visual evoked potentials (VEP's). The introduced algorithm bases upon an AutoRegressive with eXogenous input (ARX) modeling. A Least Squares procedure estimates the coefficients of the model and allows to obtain a complete black-box description of the signal generation mechanism, besides providing a filtered version of the single sweep potential. The performance of the algorithm is verified on proper simulation tests and the experimental results put into evidence the noticeable improvement of signal-to-noise ratio with a consequent better recognition of the classical parameters of the peaks (latencies and amplitudes). The possibility of measuring these parameters on a single sweep basis enables to evaluate the dynamics of the Central Nervous System response during the entire course of the examination. A classification of the estimated evoked potentials in a small number of subsets, on the basis of their morphology, is also possible.
Salloum, Maher N.; Sargsyan, Khachik; Jones, Reese E.; Najm, Habib N.; Debusschere, Bert
2015-08-11
We present a methodology to assess the predictive fidelity of multiscale simulations by incorporating uncertainty in the information exchanged between the components of an atomistic-to-continuum simulation. We account for both the uncertainty due to finite sampling in molecular dynamics (MD) simulations and the uncertainty in the physical parameters of the model. Using Bayesian inference, we represent the expensive atomistic component by a surrogate model that relates the long-term output of the atomistic simulation to its uncertain inputs. We then present algorithms to solve for the variables exchanged across the atomistic-continuum interface in terms of polynomial chaos expansions (PCEs). We also consider a simple Couette flow where velocities are exchanged between the atomistic and continuum components, while accounting for uncertainty in the atomistic model parameters and the continuum boundary conditions. Results show convergence of the coupling algorithm at a reasonable number of iterations. As a result, the uncertainty in the obtained variables significantly depends on the amount of data sampled from the MD simulations and on the width of the time averaging window used in the MD simulations.
Salloum, Maher N.; Sargsyan, Khachik; Jones, Reese E.; ...
2015-08-11
We present a methodology to assess the predictive fidelity of multiscale simulations by incorporating uncertainty in the information exchanged between the components of an atomistic-to-continuum simulation. We account for both the uncertainty due to finite sampling in molecular dynamics (MD) simulations and the uncertainty in the physical parameters of the model. Using Bayesian inference, we represent the expensive atomistic component by a surrogate model that relates the long-term output of the atomistic simulation to its uncertain inputs. We then present algorithms to solve for the variables exchanged across the atomistic-continuum interface in terms of polynomial chaos expansions (PCEs). We alsomore » consider a simple Couette flow where velocities are exchanged between the atomistic and continuum components, while accounting for uncertainty in the atomistic model parameters and the continuum boundary conditions. Results show convergence of the coupling algorithm at a reasonable number of iterations. As a result, the uncertainty in the obtained variables significantly depends on the amount of data sampled from the MD simulations and on the width of the time averaging window used in the MD simulations.« less
Vehicle Sketch Pad: a Parametric Geometry Modeler for Conceptual Aircraft Design
NASA Technical Reports Server (NTRS)
Hahn, Andrew S.
2010-01-01
The conceptual aircraft designer is faced with a dilemma, how to strike the best balance between productivity and fidelity? Historically, handbook methods have required only the coarsest of geometric parameterizations in order to perform analysis. Increasingly, there has been a drive to upgrade analysis methods, but these require considerably more precise and detailed geometry. Attempts have been made to use computer-aided design packages to fill this void, but their cost and steep learning curve have made them unwieldy at best. Vehicle Sketch Pad (VSP) has been developed over several years to better fill this void. While no substitute for the full feature set of computer-aided design packages, VSP allows even novices to quickly become proficient in defining three-dimensional, watertight aircraft geometries that are adequate for producing multi-disciplinary meta-models for higher order analysis methods, wind tunnel and display models, as well as a starting point for animation models. This paper will give an overview of the development and future course of VSP.
Savitsky, Terrance D; Paddock, Susan M
2013-06-01
We develop a dependent Dirichlet process (DDP) model for repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each client through a sequence of elements which overlap with those of other clients on different occasions. Our interest concentrates on study designs for which the overlaps of sequences occur for clients who receive an intervention in a shared or grouped fashion whose memberships may change over multiple treatment events. Our motivating application focuses on evaluation of the effectiveness of a group therapy intervention with treatment delivered through a sequence of cognitive behavioral therapy session blocks, called modules. An open-enrollment protocol permits entry of clients at the beginning of any new module in a manner that may produce unique MM sequences across clients. We begin with a model that composes an addition of client and multiple membership module random effect terms, which are assumed independent. Our MM DDP model relaxes the assumption of conditionally independent client and module random effects by specifying a collection of random distributions for the client effect parameters that are indexed by the unique set of module attendances. We demonstrate how this construction facilitates examining heterogeneity in the relative effectiveness of group therapy modules over repeated measurement occasions.
Modeling and Electrostatic Focusing for a Field Emission Electron Source
2013-06-01
mechanisms of the beam formation, transport, field emission energy distributions, the effects of the emission properties, and parametric studies are...metals, the valence electrons possess the conduction energy band and are described by Sommerfeld free electron gas model with Fermi- Dirac statistics...which defines the electrons energy distribution. For the emission from not electrical conductors the Sommerfeld theory of metals with Fermi- Dirac
Andrianov, Alexey; Szabo, Aron; Sergeev, Alexander; Kim, Arkady; Chvykov, Vladimir; Kalashnikov, Mikhail
2016-11-14
We developed an improved approach to calculate the Fourier transform of signals with arbitrary large quadratic phase which can be efficiently implemented in numerical simulations utilizing Fast Fourier transform. The proposed algorithm significantly reduces the computational cost of Fourier transform of a highly chirped and stretched pulse by splitting it into two separate transforms of almost transform limited pulses, thereby reducing the required grid size roughly by a factor of the pulse stretching. The application of our improved Fourier transform algorithm in the split-step method for numerical modeling of CPA and OPCPA shows excellent agreement with standard algorithms.
NASA Astrophysics Data System (ADS)
Holtslag, A. A. M.; Boville, B. A.; Moeng, C.-H.
Vertical diffusion of heat and passive scalars (like moisture) in the convective atmospheric boundary layer are focused upon. Flux equations are analyzed with data obtained from large eddy simulations. The findings can be used in a modified flux gradient approach, which takes into account the nonlocal convective vertical exchange using the so called counter gradient transport and a nonlocal diffusivity coefficient. Previous findings are simplified and applied to a community climate model. The impact of the nonlocal approach is illustrated in comparison with the usual local diffusion approach.
Two parametric parallel strand cables modelling of a socket-type termination for high tenacity
NASA Astrophysics Data System (ADS)
Vakouftsis, Christos; Komitopoulos, Nikolaos
2014-10-01
The present study concerns the shape optimization of a socket-type cable termination, in order to define the optimum geometry which leads into a linearly decreasing axial stress along the cable. The goal of this paper is to prove that it is possible to create a single material termination which obtains the aforementioned distribution of stresses due to its geometry and at the same time eliminates the stress concentration effect at the cable entry. The importance of the casing's geometry and its impact on the distribution of the stresses is revealed in the analysis of casings different geometry. An axisymmetric model with two design parameters was developed and analyzed.
Petersen, Jørgen Holm
2016-01-15
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. For each term in the composite likelihood, a conditional likelihood is used that eliminates the influence of the random effects, which results in a composite conditional likelihood consisting of only one-dimensional integrals that may be solved numerically. Good properties of the resulting estimator are described in a small simulation study.
Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)
Guo, Zhun; Wang, Minghuai; Qian, Yun; ...
2015-07-03
In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher order closure (HOC) scheme, and 4 parameters of the Zhang-McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low-cloud properties (cloud fraction and liquid water path) can be explained bymore » the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussians closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud-regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in-cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low-cloud fraction. Furthermore, this study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.« less
Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)
Guo, Zhun; Wang, Minghuai; Qian, Yun; Larson, Vincent E.; Ghan, Steven; Ovchinnikov, Mikhail; A. Bogenschutz, Peter; Gettelman, Andrew; Zhou, Tianjun
2015-07-03
In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher order closure (HOC) scheme, and 4 parameters of the Zhang-McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low-cloud properties (cloud fraction and liquid water path) can be explained by the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussians closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud-regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in-cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low-cloud fraction. Furthermore, this study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.
NASA Astrophysics Data System (ADS)
Hemmings, J. C. P.; Challenor, P. G.; Yool, A.
2015-03-01
Biogeochemical ocean circulation models used to investigate the role of plankton ecosystems in global change rely on adjustable parameters to capture the dominant biogeochemical dynamics of a complex biological system. In principle, optimal parameter values can be estimated by fitting models to observational data, including satellite ocean colour products such as chlorophyll that achieve good spatial and temporal coverage of the surface ocean. However, comprehensive parametric analyses require large ensemble experiments that are computationally infeasible with global 3-D simulations. Site-based simulations provide an efficient alternative but can only be used to make reliable inferences about global model performance if robust quantitative descriptions of their relationships with the corresponding 3-D simulations can be established. The feasibility of establishing such a relationship is investigated for an intermediate complexity biogeochemistry model (MEDUSA) coupled with a widely used global ocean model (NEMO). A site-based mechanistic emulator is constructed for surface chlorophyll output from this target model as a function of model parameters. The emulator comprises an array of 1-D simulators and a statistical quantification of the uncertainty in their predictions. The unknown parameter-dependent biogeochemical environment, in terms of initial tracer concentrations and lateral flux information required by the simulators, is a significant source of uncertainty. It is approximated by a mean environment derived from a small ensemble of 3-D simulations representing variability of the target model behaviour over the parameter space of interest. The performance of two alternative uncertainty quantification schemes is examined: a direct method based on comparisons between simulator output and a sample of known target model "truths" and an indirect method that is only partially reliant on knowledge of the target model output. In general, chlorophyll records at a
NASA Technical Reports Server (NTRS)
Mobasseri, B. G.; Mcgillem, C. D.; Anuta, P. E. (Principal Investigator)
1978-01-01
The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.
Mathematical models for non-parametric inferences from line transect data
Burnham, K.P.; Anderson, D.R.
1976-01-01
A general mathematical theory of line transects is developed which supplies a framework for nonparametric density estimation based on either right angle or sighting distances. The probability of observing a point given its right angle distance (y) from the line is generalized to an arbitrary function g(y). Given only that g(0) = 1, it is shown there are nonparametric approaches to density estimation using the observed right angle distances. The model is then generalized to include sighting distances (r). Let f(y I r) be the conditional distribution of right angle distance given sighting distance. It is shown that nonparametric estimation based only on sighting distances requires we know the transformation of r given by f(0 I r).
A parametric model for seismic wavelets—with estimation and uncertainty quantification
NASA Astrophysics Data System (ADS)
Skauvold, Jacob; Eidsvik, Jo; Theune, Ulrich
2016-05-01
Wavelet estimation is an essential step in qualitatively and quantitatively analysing and interpreting seismic data. Applications span from seismic data quality assessment to well ties and seismic inversion. Wavelet estimation methods can be roughly separated into two approaches, data driven inversion methods and analytical definitions. We present a new analytical wavelet definition, which is based on Hermite basis functions. This wavelet model contains four parameters, which correspond to wavelet magnitude, phase, wavelet length and bandwidth. One of our main motivations for this development was to define a compact wavelet representation and an intrinsic parameter uncertainty assessment workflow, which allows us to quantify uncertainties in estimated wavelets, as well as the generation of wavelet realizations to be used, for example, in statistical seismic amplitude inversions. We present a statistical workflow to estimate the model parameters and to explore their posterior uncertainties given well log data and seismic amplitude data. This includes sampling the posterior distribution of the four wavelet parameters using Markov Chain Monte Carlo methods. We then discuss the applicability, limitations and challenges of the approach with the help of synthetic data and a North Sea data set with well logs and processed seismic amplitudes, where we also compare our method to Bayesian least-squares and a commercial wavelet estimation routine. Realizations of wavelets based on the optimized parameters and their uncertainties appear to sample the wavelet space well with reasonable variations in wavelet length, phase and amplitude while not introducing random fluctuations or wavelet lobes. The results indicate that the compact wavelet representation allows for an efficient and rather stable wavelet estimation workflow that achieves useful results in the presence of noisy data.
Comparison of a beach parametric morphodynamic model results with in situ measurements
NASA Astrophysics Data System (ADS)
Ferreira, Caroline; Silva, Paulo A.; Baptista, Paulo; Abreu, Tiago
2014-05-01
The south coastal stretch of Aveiro inlet in the Northwest coast of Portugal is subject to a highly energetic wave climate and presents generalized erosion. To characterize the morphodynamic behavior of this coastal stretch it is important to establish the relationship between the hydrodynamic forcing and beach topography changes. Furthermore, it is necessary to develop methods which enable to estimate its behavior at a short and medium term. This work presents a model which estimates the cross-shore sediment transport from the shoaling into the swash zone. The transformation of the waves (shoaling and refraction) as they propagate towards the shore are computed from the incident wave field assuming conservation of the wave energy flux and take into account the tidal level and the beach bathymetry and topography. Wave breaking is described according to Battjes & Janssen (1978) and wave dissipation follows Baldock et al.'s (1998) formulation. The cross-shore sediment transport rates in the shoaling, surf and swash zones are computed from Tinker et al.'s (2009) suspended load shape function as a function of the normalized depth, h/ hb, where hb represents the water depth at wave breaking. The performance of the model was assessed by comparing the computed significant wave height and sediment fluxes with water-level measurements and morphological variations at a transept in the coastal stretch. The hydrodynamic measurements were obtained with pressure transducers placed in the inter-tidal zone during one tidal cycle and topographic surveys with the INSHORE system (Baptista et al., 2011a,b). The results show that the computed sediment fluxes are qualitatively in agreement with the topographic observations, meaning that the parameterized sediment flux shape function provide a good basis for prediction of the beach morphodynamic behavior with low computational cost. References: Baldock, TE, Holmes, P, Bunker, S, Van Weert, P, 1998. Cross-shore hydrodynamics within
Software Model Checking Without Source Code
NASA Technical Reports Server (NTRS)
Chaki, Sagar; Ivers, James
2009-01-01
We present a framework, called AIR, for verifying safety properties of assembly language programs via software model checking. AIR extends the applicability of predicate abstraction and counterexample guided abstraction refinement to the automated verification of low-level software. By working at the assembly level, AIR allows verification of programs for which source code is unavailable-such as legacy and COTS software-and programs that use features-such as pointers, structures, and object-orientation-that are problematic for source-level software verification tools. In addition, AIR makes no assumptions about the underlying compiler technology. We have implemented a prototype of AIR and present encouraging results on several non-trivial examples.
Markov source model for printed music decoding
NASA Astrophysics Data System (ADS)
Kopec, Gary E.; Chou, Philip A.; Maltz, David A.
1995-03-01
This paper describes a Markov source model for a simple subset of printed music notation. The model is based on the Adobe Sonata music symbol set and a message language of our own design. Chord imaging is the most complex part of the model. Much of the complexity follows from a rule of music typography that requires the noteheads for adjacent pitches to be placed on opposite sides of the chord stem. This rule leads to a proliferation of cases for other typographic details such as dot placement. We describe the language of message strings accepted by the model and discuss some of the imaging issues associated with various aspects of the message language. We also point out some aspects of music notation that appear problematic for a finite-state representation. Development of the model was greatly facilitated by the duality between image synthesis and image decoding. Although our ultimate objective was a music image model for use in decoding, most of the development proceeded by using the evolving model for image synthesis, since it is computationally far less costly to image a message than to decode an image.
Parametric Modeling Investigation of a Radially-Staged Low-Emission Aviation Combustor
NASA Technical Reports Server (NTRS)
Heath, Christopher M.
2016-01-01
Aviation gas-turbine combustion demands high efficiency, wide operability and minimal trace gas emissions. Performance critical design parameters include injector geometry, combustor layout, fuel-air mixing and engine cycle conditions. The present investigation explores these factors and their impact on a radially staged low-emission aviation combustor sized for a next-generation 24,000-lbf-thrust engine. By coupling multi-fidelity computational tools, a design exploration was performed using a parameterized annular combustor sector at projected 100% takeoff power conditions. Design objectives included nitrogen oxide emission indices and overall combustor pressure loss. From the design space, an optimal configuration was selected and simulated at 7.1, 30 and 85% part-power operation, corresponding to landing-takeoff cycle idle, approach and climb segments. All results were obtained by solution of the steady-state Reynolds-averaged Navier-Stokes equations. Species concentrations were solved directly using a reduced 19-step reaction mechanism for Jet-A. Turbulence closure was obtained using a nonlinear K-epsilon model. This research demonstrates revolutionary combustor design exploration enabled by multi-fidelity physics-based simulation.
Propensity score method: a non-parametric technique to reduce model dependence
2017-01-01
Propensity score analysis (PSA) is a powerful technique that it balances pretreatment covariates, making the causal effect inference from observational data as reliable as possible. The use of PSA in medical literature has increased exponentially in recent years, and the trend continue to rise. The article introduces rationales behind PSA, followed by illustrating how to perform PSA in R with MatchIt package. There are a variety of methods available for PS matching such as nearest neighbors, full matching, exact matching and genetic matching. The task can be easily done by simply assigning a string value to the method argument in the matchit() function. The generic summary() and plot() functions can be applied to an object of class matchit to check covariate balance after matching. Furthermore, there is a useful package PSAgraphics that contains several graphical functions to check covariate balance between treatment groups across strata. If covariate balance is not achieved, one can modify model specifications or use other techniques such as random forest and recursive partitioning to better represent the underlying structure between pretreatment covariates and treatment assignment. The process can be repeated until the desirable covariate balance is achieved. PMID:28164092
Shen, Li; Firpi, Hiram A; Saykin, Andrew J; West, John D
2009-06-01
Accurate and efficient segmentation of the hippocampus from brain images is a challenging issue. Although experienced anatomic tracers can be reliable, manual segmentation is a time consuming process and may not be feasible for large-scale neuroimaging studies. In this article, we compare an automated method, FreeSurfer (V4), with a published manual protocol on the determination of hippocampal boundaries from magnetic resonance imaging scans, using data from an existing mild cognitive impairment/Alzheimer's disease cohort. To perform the comparison, we develop an enhanced spherical harmonic processing framework to model and register these hippocampal traces. The framework treats the two hippocampi as a single geometric configuration and extracts the positional, orientation, and shape variables in a multiobject setting. We apply this framework to register manual tracing and FreeSurfer results together and the two methods show stronger agreement on position and orientation than shape measures. Work is in progress to examine a refined FreeSurfer segmentation strategy and an improved agreement on shape features is expected.
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1995-01-01
Parametric cost analysis is a mathematical approach to estimating cost. Parametric cost analysis uses non-cost parameters, such as quality characteristics, to estimate the cost to bring forth, sustain, and retire a product. This paper reviews parametric cost analysis and shows how it can be used within the cost deployment process.
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.
Rosetta stone for parametrized tests of gravity
NASA Astrophysics Data System (ADS)
Sampson, Laura; Yunes, Nicolás; Cornish, Neil
2013-09-01
Several model-independent parametrizations of deviations from general relativity have been developed to test Einstein’s theory. Although these different parametrizations were developed for different gravitational observables, they ultimately all test the same underlying physics. In this paper, we develop connections between the parametrized post-Newtonian, parametrized post-Keplerian, and the parametrized post-Einsteinian frameworks, developed to carry out tests of general relativity with Solar System, binary pulsar, and gravitational wave observations, respectively. These connections, although only valid under certain assumptions such as energy/momentum conservation, allow us to use knowledge gained from one framework to inform and guide tests using the others. Relating these parametrizations and combining the results from each approach strengthens our tests of general relativity.
Why preferring parametric forecasting to nonparametric methods?
Jabot, Franck
2015-05-07
A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting.
Modeling the Presence of Myelin and Edema in the Brain Based on Multi-Parametric Quantitative MRI
Warntjes, Marcel; Engström, Maria; Tisell, Anders; Lundberg, Peter
2016-01-01
The aim of this study was to present a model that uses multi-parametric quantitative MRI to estimate the presence of myelin and edema 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 normalized brain images of a group of 20 healthy controls. The pathological brain was modeled in terms of the reduction of myelin content and presence of excess parenchymal water, which indicates the degree of edema. The method was tested on spatially normalized 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 gray 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 behavior 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
The Open Source Snowpack modelling ecosystem
NASA Astrophysics Data System (ADS)
Bavay, Mathias; Fierz, Charles; Egger, Thomas; Lehning, Michael
2016-04-01
As a large number of numerical snow models are available, a few stand out as quite mature and widespread. One such model is SNOWPACK, the Open Source model that is developed at the WSL Institute for Snow and Avalanche Research SLF. Over the years, various tools have been developed around SNOWPACK in order to expand its use or to integrate additional features. Today, the model is part of a whole ecosystem that has evolved to both offer seamless integration and high modularity so each tool can easily be used outside the ecosystem. Many of these Open Source tools experience their own, autonomous development and are successfully used in their own right in other models and applications. There is Alpine3D, the spatially distributed version of SNOWPACK, that forces it with terrain-corrected radiation fields and optionally with blowing and drifting snow. This model can be used on parallel systems (either with OpenMP or MPI) and has been used for applications ranging from climate change to reindeer herding. There is the MeteoIO pre-processing library that offers fully integrated data access, data filtering, data correction, data resampling and spatial interpolations. This library is now used by several other models and applications. There is the SnopViz snow profile visualization library and application that supports both measured and simulated snow profiles (relying on the CAAML standard) as well as time series. This JavaScript application can be used standalone without any internet connection or served on the web together with simulation results. There is the OSPER data platform effort with a data management service (build on the Global Sensor Network (GSN) platform) as well as a data documenting system (metadata management as a wiki). There are several distributed hydrological models for mountainous areas in ongoing development that require very little information about the soil structure based on the assumption that in step terrain, the most relevant information is
Ebrahimzadeh, M
2003-12-15
Since its invention more than 40 years ago, the laser has become an indispensable optical tool, capable of transforming light from its naturally incoherent state to a highly coherent state in space and time. Yet, due to fundamental limitations, operation of the laser remains confined to restricted spectral and temporal regions. Nonlinear optics can overcome this limitation by allowing access to new spectral and temporal regimes through the exploitation of suitable dielectric materials in combination with the laser. In particular, optical parametric oscillators are versatile coherent light sources with unique flexibility that can provide optical radiation across an entire spectral range from the ultraviolet to the far-infrared and over all temporal scales from continuous wave to the ultrafast femtosecond domain.
Asteroid Models from Multiple Data Sources
NASA Astrophysics Data System (ADS)
Durech, J.; Carry, B.; Delbo, M.; Kaasalainen, M.; Viikinkoski, M.
In the past decade, hundreds of asteroid shape models have been derived using the lightcurve inversion method. At the same time, a new framework of three-dimensional shape modeling based on the combined analysis of widely different data sources -- such as optical lightcurves, disk-resolved images, stellar occultation timings, mid-infrared thermal radiometry, optical interferometry, and radar delay-Doppler data -- has been developed. This multi-data approach allows the determination of most of the physical and surface properties of asteroids in a single, coherent inversion, with spectacular results. We review the main results of asteroid lightcurve inversion and also recent advances in multi-data modeling. We show that models based on remote sensing data were confirmed by spacecraft encounters with asteroids, and we discuss how the multiplication of highly detailed three-dimensional models will help to refine our general knowledge of the asteroid population. The physical and surface properties of asteroids, i.e., their spin, three-dimensional shape, density, thermal inertia, and surface roughness, are among the least known of all asteroid properties. Apart from the albedo and diameter, we have access to the whole picture for only a few hundreds of asteroids. These quantities are nevertheless very important to understand, as they affect the nongravitational Yarkovsky effect responsible for meteorite delivery to Earth, as well as the bulk composition and internal structure of asteroids.
NASA Astrophysics Data System (ADS)
Varitis, E.
2016-11-01
A Reverse Engineering (RE) method for parametric modelling is presented in this paper. According to this method laser scanning data are processed by means of an algorithm and a parametric geometry is produced. The algorithm generates a spline used as a driving curve for a 2D profile, both approximated from the point cloud data, with the final geometry being produced through with a sweep based technique. The method was applied to digitize a commercial product, a bottle, and the geometry was reconstructed at high accuracy and surface quality. Finally the results of the proposed method were compared with auto surfacing from *.stl files and with surfaces generated by means of sweep commands without converting curves to splines.
NASA Astrophysics Data System (ADS)
Ahn, Chong Hyun
The most effective method for stimulating shale gas reservoirs is a massive hydraulic fracture treatment. Recent analysis using microseismic technology have shown that complex fracture networks are commonly created in the field as a result of the stimulation of shale wells. The interaction between pre-existing natural fractures and the propagating hydraulic fracture is a critical factor affecting the created complex fracture network; however, many existing numerical models simulate only planar hydraulic fractures without considering the pre-existing fractures in the formation. The shale formations already contain a large number of natural fractures, so an accurate fracture propagation model needs to be developed to optimize the fracturing process. In this research, we first characterized the mechanics of hydraulic fracturing and fluid flow in the shale gas reservoir. Then, a 2D, single-phase numerical model and a 3D, 2-phase coupled model were developed, which integrate dynamic fracture propagation, interactions between hydraulic fractures and pre-existing natural fractures, fracture fluid leakoff, and fluid flow in a petroleum reservoir. By using the developed model, we conducted parametric studies to quantify the effects of treatment rate, treatment size, fracture fluid viscosity, differential horizontal stress, natural fracture spacing, fracture toughness, matrix permeability, and proppant size on the geometry of the hydraulic fracture network. The findings elucidate important trends in hydraulic fracturing of shale reservoirs that are useful in improving the design of treatments for specific reservoir settings.
Filippi, Stefano; Motyl, Barbara; Bandera, Camillo
2009-02-01
At present, computer assisted surgery systems help orthopaedic surgeons both plan and perform surgical procedures. To enable these systems to function, it is crucial to have at one's disposal 3D models of anatomical structures, surgical tools and prostheses (if required). This paper analyses and compares three methods for generating 3D digital models of anatomical structures starting from X-ray images: parametric solid modelling/reconfiguration, global shape modelling and free-form deformation. Seven experiences involving the generation of a femur model were conducted by software developers and different skilled users. These experiences are described in detail and compared at different stages and from different points of view.
Self-seeding ring optical parametric oscillator
Smith, Arlee V.; Armstrong, Darrell J.
2005-12-27
An optical parametric oscillator apparatus utilizing self-seeding with an external nanosecond-duration pump source to generate a seed pulse resulting in increased conversion efficiency. An optical parametric oscillator with a ring configuration are combined with a pump that injection seeds the optical parametric oscillator with a nanosecond duration, mJ pulse in the reverse direction as the main pulse. A retroreflecting means outside the cavity injects the seed pulse back into the cavity in the direction of the main pulse to seed the main pulse, resulting in higher conversion efficiency.
Modeling unobserved sources of heterogeneity in animal abundance using a Dirichlet process prior
Dorazio, R.M.; Mukherjee, B.; Zhang, L.; Ghosh, M.; Jelks, H.L.; Jordan, F.
2008-01-01
In surveys of natural populations of animals, a sampling protocol is often spatially replicated to collect a representative sample of the population. In these surveys, differences in abundance of animals among sample locations may induce spatial heterogeneity in the counts associated with a particular sampling protocol. For some species, the sources of heterogeneity in abundance may be unknown or unmeasurable, leading one to specify the variation in abundance among sample locations stochastically. However, choosing a parametric model for the distribution of unmeasured heterogeneity is potentially subject to error and can have profound effects on predictions of abundance at unsampled locations. In this article, we develop an alternative approach wherein a Dirichlet process prior is assumed for the distribution of latent abundances. This approach allows for uncertainty in model specification and for natural clustering in the distribution of abundances in a data-adaptive way. We apply this approach in an analysis of counts based on removal samples of an endangered fish species, the Okaloosa darter. Results of our data analysis and simulation studies suggest that our implementation of the Dirichlet process prior has several attractive features not shared by conventional, fully parametric alternatives. ?? 2008, The International Biometric Society.
PHAZE. Parametric Hazard Function Estimation
Atwood, C.L.
1990-09-01
Phaze performs statistical inference calculations on a hazard function ( also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking of the model assumptions.
Parametrically defined differential equations
NASA Astrophysics Data System (ADS)
Polyanin, A. D.; Zhurov, A. I.
2017-01-01
The paper deals with nonlinear ordinary differential equations defined parametrically by two relations. It proposes techniques to reduce such equations, of the first or second order, to standard systems of ordinary differential equations. It obtains the general solution to some classes of nonlinear parametrically defined ODEs dependent on arbitrary functions. It outlines procedures for the numerical solution of the Cauchy problem for parametrically defined differential equations.
Wareham, Alice; Lewandowski, Kuiama S.; Williams, Ann; Dennis, Michael J.; Sharpe, Sally; Vipond, Richard; Silman, Nigel; Ball, Graham
2016-01-01
A temporal study of gene expression in peripheral blood leukocytes (PBLs) from a Mycobacterium tuberculosis primary, pulmonary challenge model Macaca fascicularis has been conducted. PBL samples were taken prior to challenge and at one, two, four and six weeks post-challenge and labelled, purified RNAs hybridised to Operon Human Genome AROS V4.0 slides. Data analyses revealed a large number of differentially regulated gene entities, which exhibited temporal profiles of expression across the time course study. Further data refinements identified groups of key markers showing group-specific expression patterns, with a substantial reprogramming event evident at the four to six week interval. Selected statistically-significant gene entities from this study and other immune and apoptotic markers were validated using qPCR, which confirmed many of the results obtained using microarray hybridisation. These showed evidence of a step-change in gene expression from an ‘early’ FOS-associated response, to a ‘late’ predominantly type I interferon-driven response, with coincident reduction of expression of other markers. Loss of T-cell-associate marker expression was observed in responsive animals, with concordant elevation of markers which may be associated with a myeloid suppressor cell phenotype e.g. CD163. The animals in the study were of different lineages and these Chinese and Mauritian cynomolgous macaque lines showed clear evidence of differing susceptibilities to Tuberculosis challenge. We determined a number of key differences in response profiles between the groups, particularly in expression of T-cell and apoptotic makers, amongst others. These have provided interesting insights into innate susceptibility related to different host `phenotypes. Using a combination of parametric and non-parametric artificial neural network analyses we have identified key genes and regulatory pathways which may be important in early and adaptive responses to TB. Using comparisons
NASA Astrophysics Data System (ADS)
Mora, Brice
2009-10-01
Foresters are faced with difficulties to obtain sub-polygon information with the mapping methods available nowadays. The main objective of this work consisted in the development of new methods able to improve the map accuracy of regenerating forest stands and mature forest stands in the South of Quebec, Canada. The Dempster-Shafer Theory (DST) and the Dezert-Smarandache Theory (DSmT) showed their ability to integrate multiple heterogenous data sources to go further than the classical classification procedures like the maximum likelihood or the spectral unmixing, in terms of map accuracy. Improvement on the ability to map regenerating stands, passed from 82.7% with the maximum likelihood method to 91.1% with the Free DSm model with a total transfer of the mass of the "Union" class to the "Intersection" class (+ 8.4%). For the mature stands, the improvement passed from 63.8% with the K nearest neighbour to 79.5% with the DST according to a classical belief structuration and the hybrid decision rule for which the conflict threshold was fixed at 10% (+ 15.7%). Our results with DST and a bayesian belief structuration showed the difficulty to model the uncertainty in the fusion process. This is probably due to the lack of scientific knowledge about the influence of the biophysical and climatic parameters on the mapped forest stands and to the necessity to model specifically the uncertainty for each source. Our work showed concrete improvement when mapping forest stands with DST which is encouraging to continue explorating the fundamental principle of the proposed hybrid decision rule. This means a particular focus on the difference between the fused masses of each potential class after the fusion, to choose the best hypothesis. Keywords. forest mapping, Quebec, deciduous stands, regenerating stands, mature stands, data fusion, Dempster-Shafer Theory, Dezert-Smarandache Theory, hybrid decision rule
An open source business model for malaria.
Årdal, Christine; Røttingen, John-Arne
2015-01-01
Greater investment is required in developing new drugs and vaccines against malaria in order to eradicate malaria. These precious funds must be carefully managed to achieve the greatest impact. We evaluate existing efforts to discover and develop new drugs and vaccines for malaria to determine how best malaria R&D can benefit from an enhanced open source approach and how such a business model may operate. We assess research articles, patents, clinical trials and conducted a smaller survey among malaria researchers. Our results demonstrate that the public and philanthropic sectors are financing and performing the majority of malaria drug/vaccine discovery and development, but are then restricting access through patents, 'closed' publications and hidden away physical specimens. This makes little sense since it is also the public and philanthropic sector that purchases the drugs and vaccines. We recommend that a more "open source" approach is taken by making the entire value chain more efficient through greater transparency which may lead to more extensive collaborations. This can, for example, be achieved by empowering an existing organization like the Medicines for Malaria Venture (MMV) to act as a clearing house for malaria-related data. The malaria researchers that we surveyed indicated that they would utilize such registry data to increase collaboration. Finally, we question the utility of publicly or philanthropically funded patents for malaria medicines, where little to no profits are available. Malaria R&D benefits from a publicly and philanthropically funded architecture, which starts with academic research institutions, product development partnerships, commercialization assistance through UNITAID and finally procurement through mechanisms like The Global Fund to Fight AIDS, Tuberculosis and Malaria and the U.S.' President's Malaria Initiative. We believe that a fresh look should be taken at the cost/benefit of patents particularly related to new malaria
NON-PARAMETRIC ESTIMATION UNDER STRONG DEPENDENCE
Zhao, Zhibiao; Zhang, Yiyun; Li, Runze
2014-01-01
We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance. PMID:25018572
NON-PARAMETRIC ESTIMATION UNDER STRONG DEPENDENCE.
Zhao, Zhibiao; Zhang, Yiyun; Li, Runze
2014-01-01
We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance.
Parametric sonars for seafloor characterization
NASA Astrophysics Data System (ADS)
Caiti, Andrea; Bergem, Oddbjorn; Dybedal, Johnny
1999-12-01
Parametric sonars are instruments capable of transmitting acoustic signals in the water with a very narrow beam and almost no sidelobes. These features are exploited in this paper to define a methodology for quantitative estimation of the geo-acoustic and morphological properties of the uppermost seafloor sediment layer. The three major components of the approach are the parametric instrument itself; the modelling of the forward-propagation problem, with the use of the Kirchhoff approximation for surface scattering and of the small-perturbation theory for the volume scattering; and the definition of a criterion for comparison between data and model predictions, which is accomplished by a generalized time-frequency analysis. In this way the estimation becomes one of a model-based identification, or a model-based inverse problem. Results from a field trial in a shallow water area of the Mediterranean are shown, and compared with independently gathered ground truth.
NASA Astrophysics Data System (ADS)
Agishev, R. R.
2017-02-01
Within the framework of generalisation of different approaches to the modelling of atmospheric lidars, the methodology capabilities for dimensionless-parametric analysis are expanded. The developed approach simplifies the analysis of the signal-to-noise ratio and potential capabilities of existing and newly developed monitoring systems with a wide variability of atmospheric and optical conditions and a great variety of modern lidars. Its applicability to the problems of remote atmospheric sensing, environmental monitoring and lidar navigation in providing the eye safety, noise immunity and reliability is discussed.
NASA Astrophysics Data System (ADS)
Verardo, E.; Atteia, O.; Rouvreau, L.
2015-12-01
In-situ bioremediation is a commonly used remediation technology to clean up the subsurface of petroleum-contaminated sites. Forecasting remedial performance (in terms of flux and mass reduction) is a challenge due to uncertainties associated with source properties and the uncertainties associated with contribution and efficiency of concentration reducing mechanisms. In this study, predictive uncertainty analysis of bio-remediation system efficiency is carried out with the null-space Monte Carlo (NSMC) method which combines the calibration solution-space parameters with the ensemble of null-space parameters, creating sets of calibration-constrained parameters for input to follow-on remedial efficiency. The first step in the NSMC methodology for uncertainty analysis is model calibration. The model calibration was conducted by matching simulated BTEX concentration to a total of 48 observations from historical data before implementation of treatment. Two different bio-remediation designs were then implemented in the calibrated model. The first consists in pumping/injection wells and the second in permeable barrier coupled with infiltration across slotted piping. The NSMC method was used to calculate 1000 calibration-constrained parameter sets for the two different models. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. The first variant implementation of the NSMC is based on a single calibrated model. In the second variant, models were calibrated from different initial parameter sets. NSMC calibration-constrained parameter sets were sampled from these different calibrated models. We demonstrate that in context of nonlinear model, second variant avoids to underestimate parameter uncertainty which may lead to a poor quantification of predictive uncertainty. Application of the proposed approach to manage bioremediation of groundwater in a real site shows that it is effective to provide support in
Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.; Burkes, Douglas
2015-06-15
Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum alloy plate-type fuel for high-performance research reactors in the United States. This work supports the U.S. Department of Energy National Nuclear Security Administration’s Office of Material Management and Minimization Reactor Conversion Program. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll-separating forces for various rolling mill geometries for PNNL, Babcock & Wilcox Co., Y-12 National Security Complex, Los Alamos National Laboratory, and Idaho National Laboratory. The model developed and presented in a previous report has been subjected to further validation study using new sets of experimental data generated from a rolling mill at PNNL. Simulation results of both hot rolling and cold rolling of uranium-10% molybdenum coupons have been compared with experimental results. The model was used to predict roll-separating forces at different temperatures and reductions for five rolling mills within the National Nuclear Security Administration Fuel Fabrication Capability project. This report also presents initial results of a finite-element model microstructure-based approach to study the surface roughness at the interface between zirconium and uranium-10% molybdenum.
Constraining Emission Models of Luminous Blazar Sources
Sikora, Marek; Stawarz, Lukasz; Moderski, Rafal; Nalewajko, Krzysztof; Madejski, Greg; /KIPAC, Menlo Park /SLAC
2009-10-30
Many luminous blazars which are associated with quasar-type active galactic nuclei display broad-band spectra characterized by a large luminosity ratio of their high-energy ({gamma}-ray) and low-energy (synchrotron) spectral components. This large ratio, reaching values up to 100, challenges the standard synchrotron self-Compton models by means of substantial departures from the minimum power condition. Luminous blazars have also typically very hard X-ray spectra, and those in turn seem to challenge hadronic scenarios for the high energy blazar emission. As shown in this paper, no such problems are faced by the models which involve Comptonization of radiation provided by a broad-line-region, or dusty molecular torus. The lack or weakness of bulk Compton and Klein-Nishina features indicated by the presently available data favors production of {gamma}-rays via up-scattering of infrared photons from hot dust. This implies that the blazar emission zone is located at parsec-scale distances from the nucleus, and as such is possibly associated with the extended, quasi-stationary reconfinement shocks formed in relativistic outflows. This scenario predicts characteristic timescales for flux changes in luminous blazars to be days/weeks, consistent with the variability patterns observed in such systems at infrared, optical and {gamma}-ray frequencies. We also propose that the parsec-scale blazar activity can be occasionally accompanied by dissipative events taking place at sub-parsec distances and powered by internal shocks and/or reconnection of magnetic fields. These could account for the multiwavelength intra-day flares occasionally observed in powerful blazars sources.
NASA Astrophysics Data System (ADS)
Ludwig, M.; Herbst, G.; Rieke-Zapp, D.; Rosenbauer, R.; Rutishauser, S.; Zellweger, A.
2013-02-01
Consecrated in 1297 as the monastery church of the four years earlier founded St. Catherine's monastery, the Gothic Church of St. Catherine was largely destroyed in a devastating bombing raid on January 2nd 1945. To counteract the process of disintegration, the departments of geo-information and lower monument protection authority of the City of Nuremburg decided to getting done a three dimensional building model of the Church of St. Catherine's. A heterogeneous set of data was used for preparation of a parametric architectural model. In effect the modeling of historic buildings can profit from the so called BIM method (Building Information Modeling), as the necessary structuring of the basic data renders it into very sustainable information. The resulting model is perfectly suited to deliver a vivid impression of the interior and exterior of this former mendicant orders' church to present observers.
Gu, Chenglin; Hu, Minglie; Zhang, Limeng; Fan, Jintao; Song, Youjian; Wang, Chingyue; Reid, Derryck T
2013-06-01
We report on the highly efficient generation of widely tunable femtosecond pulses based on intracavity second harmonic generation (SHG) and sum frequency generation (SFG) in a MgO-doped periodically poled LiNbO(3) optical parametric oscillator (OPO), which is pumped by a Yb-doped large-mode-area photonics crystal fiber femtosecond laser. Red and near infrared from intracavity SHG and SFG and infrared signals were directly obtained from the OPO. A 2 mm β-BaB(2)O(4) is applied for Type I (oo → e) intracavity SHG and SFG, and then femtosecond laser pulses over 610 nm ~ 668 nm from SFG and 716 nm ~ 970 nm from SHG are obtained with high efficiency. In addition, the oscillator simultaneously generates signal and idler femtosecond pulses over 1450 nm ~ 2200 nm and 2250 nm ~ 4000 nm, respectively.
Grell, Kathrine; Diggle, Peter J; Frederiksen, Kirsten; Schüz, Joachim; Cardis, Elisabeth; Andersen, Per K
2015-10-15
We study methods for how to include the spatial distribution of tumours when investigating the relation between brain tumours and the exposure from radio frequency electromagnetic fields caused by mobile phone use. Our suggested point process model is adapted from studies investigating spatial aggregation of a disease around a source of potential hazard in environmental epidemiology, where now the source is the preferred ear of each phone user. In this context, the spatial distribution is a distribution over a sample of patients rather than over multiple disease cases within one geographical area. We show how the distance relation between tumour and phone can be modelled nonparametrically and, with various parametric functions, how covariates can be included in the model and how to test for the effect of distance. To illustrate the models, we apply them to a subset of the data from the Interphone Study, a large multinational case-control study on the association between brain tumours and mobile phone use.
An Open Source Business Model for Malaria
Årdal, Christine; Røttingen, John-Arne
2015-01-01
Greater investment is required in developing new drugs and vaccines against malaria in order to eradicate malaria. These precious funds must be carefully managed to achieve the greatest impact. We evaluate existing efforts to discover and develop new drugs and vaccines for malaria to determine how best malaria R&D can benefit from an enhanced open source approach and how such a business model may operate. We assess research articles, patents, clinical trials and conducted a smaller survey among malaria researchers. Our results demonstrate that the public and philanthropic sectors are financing and performing the majority of malaria drug/vaccine discovery and development, but are then restricting access through patents, ‘closed’ publications and hidden away physical specimens. This makes little sense since it is also the public and philanthropic sector that purchases the drugs and vaccines. We recommend that a more “open source” approach is taken by making the entire value chain more efficient through greater transparency which may lead to more extensive collaborations. This can, for example, be achieved by empowering an existing organization like the Medicines for Malaria Venture (MMV) to act as a clearing house for malaria-related data. The malaria researchers that we surveyed indicated that they would utilize such registry data to increase collaboration. Finally, we question the utility of publicly or philanthropically funded patents for malaria medicines, where little to no profits are available. Malaria R&D benefits from a publicly and philanthropically funded architecture, which starts with academic research institutions, product development partnerships, commercialization assistance through UNITAID and finally procurement through mechanisms like The Global Fund to Fight AIDS, Tuberculosis and Malaria and the U.S.’ President’s Malaria Initiative. We believe that a fresh look should be taken at the cost/benefit of patents particularly related to new
NASA Astrophysics Data System (ADS)
Lüpkes, Christof; Gryanik, Vladimir M.; Hartmann, JöRg; Andreas, Edgar L.
2012-07-01
A hierarchy of parametrizations of the neutral 10 m drag coefficients over polar sea ice with different morphology regimes is derived on the basis of a partitioning concept that splits the total surface drag into contributions of skin drag and form drag. The new derivation, which provides drag coefficients as a function of sea ice concentration and characteristic length scales of roughness elements, needs fewer assumptions than previous similar approaches. It is shown that form drag variability can explain the variability of surface drag in the marginal sea ice zone (MIZ) and in the summertime inner Arctic regions. In the MIZ, form drag is generated by floe edges; in the inner Arctic, it is generated by edges at melt ponds and leads due to the elevation of the ice surface relative to the open water surface. It is shown that an earlier fit of observed neutral drag coefficients is obtained as a special case within the new concept when specific simplifications are made which concern the floe and melt pond geometry. Due to the different surface morphologies in the MIZ and summertime Arctic, different functional dependencies of the drag coefficients on the sea ice concentration result. These differences cause only minor differences between the MIZ and summertime drag coefficients in average conditions, but they might be locally important for atmospheric momentum transport to sea ice. The new parametrization formulae can be used for present conditions but also for future climate scenarios with changing sea ice conditions.
Extended source model for diffusive coupling.
González-Ochoa, Héctor O; Flores-Moreno, Roberto; Reyes, Luz M; Femat, Ricardo
2016-01-01
Motivated by the prevailing approach to diffusion coupling phenomena which considers point-like diffusing sources, we derived an analogous expression for the concentration rate of change of diffusively coupled extended containers. The proposed equation, together with expressions based on solutions to the diffusion equation, is intended to be applied to the numerical solution of systems exclusively composed of ordinary differential equations, however is able to account for effects due the finite size of the coupled sources.
NASA Technical Reports Server (NTRS)
Stewart, R. B.; Grose, W. L.
1975-01-01
Parametric studies were made with a multilayer atmospheric diffusion model to place quantitative limits on the uncertainty of predicting ground-level toxic rocket-fuel concentrations. Exhaust distributions in the ground cloud, cloud stabilized geometry, atmospheric coefficients, the effects of exhaust plume afterburning of carbon monoxide CO, assumed surface mixing-layer division in the model, and model sensitivity to different meteorological regimes were studied. Large-scale differences in ground-level predictions are quantitatively described. Cloud alongwind growth for several meteorological conditions is shown to be in error because of incorrect application of previous diffusion theory. In addition, rocket-plume calculations indicate that almost all of the rocket-motor carbon monoxide is afterburned to carbon dioxide CO2, thus reducing toxic hazards due to CO. The afterburning is also shown to have a significant effect on cloud stabilization height and on ground-level concentrations of exhaust products.
Developing general acoustic model for noise sources and parameters estimation
NASA Astrophysics Data System (ADS)
Madoliat, Reza; Nouri, Nowrouz Mohammad; Rahrovi, Ali
2017-02-01
Noise measured at various points around the environment can be evaluated by a series of acoustic sources. Acoustic sources with wide surface can be broken down in fluid environment using some smaller acoustic sources. The aim of this study is to make a model to indicate the type, number, direction, position and strength of these sources in a way that the main sound and the sound of equivalent sources match together in an acceptable way. When position and direction of the source is given, the strength of the source can be found using inverse method. On the other hand, considering the non-uniqueness of solution in inverse method, a different acoustic strength is obtained for the sources if different positions are selected. Selecting an arrangement of general source and using the optimization algorithm, the least possible mismatch between the main sound and the sound of equivalent sources can be achieved.
A divergence-free parametrization for dynamical dark energy
Akarsu, Özgür; Dereli, Tekin; Vazquez, J. Alberto E-mail: tdereli@ku.edu.tr
2015-06-01
We introduce a new parametrization for the dark energy, led by the same idea to the linear expansion of the equation of state in scale factor a and in redshift z, which diverges neither in the past nor future and contains the same number of degrees of freedom with the former two. We present constraints of the cosmological parameters using the most updated baryon acoustic oscillation (BAO) measurements along with cosmic microwave background (CMB) data and a recent reanalysis of Type Ia supernova (SN) data. This new parametrization allowed us to carry out successive observational analyses by decreasing its degrees of freedom systematically until ending up with a dynamical dark energy model that has the same number of parameters with ΛCDM . We found that the dark energy source with a dynamical equation of state parameter equal −2/3 at the early universe and −1 today fits the data slightly better than Λ.
NASA Technical Reports Server (NTRS)
Brown, James L.
2014-01-01
Examined is sensitivity of separation extent, wall pressure and heating to variation of primary input flow parameters, such as Mach and Reynolds numbers and shock strength, for 2D and Axisymmetric Hypersonic Shock Wave Turbulent Boundary Layer interactions obtained by Navier-Stokes methods using the SST turbulence model. Baseline parametric sensitivity response is provided in part by comparison with vetted experiments, and in part through updated correlations based on free interaction theory concepts. A recent database compilation of hypersonic 2D shock-wave/turbulent boundary layer experiments extensively used in a prior related uncertainty analysis provides the foundation for this updated correlation approach, as well as for more conventional validation. The primary CFD method for this work is DPLR, one of NASA's real-gas aerothermodynamic production RANS codes. Comparisons are also made with CFL3D, one of NASA's mature perfect-gas RANS codes. Deficiencies in predicted separation response of RANS/SST solutions to parametric variations of test conditions are summarized, along with recommendations as to future turbulence approach.
A Simple Double-Source Model for Interference of Capillaries
ERIC Educational Resources Information Center
Hou, Zhibo; Zhao, Xiaohong; Xiao, Jinghua
2012-01-01
A simple but physically intuitive double-source model is proposed to explain the interferogram of a laser-capillary system, where two effective virtual sources are used to describe the rays reflected by and transmitted through the capillary. The locations of the two virtual sources are functions of the observing positions on the target screen. An…
COMBINING SOURCES IN STABLE ISOTOPE MIXING MODELS: ALTERNATIVE METHODS
Stable isotope mixing models are often used to quantify source contributions to a mixture. Examples include pollution source identification; trophic web studies; analysis of water sources for soils, plants, or water bodies; and many others. A common problem is having too many s...
Yue, Ning J.
2008-06-15
As different types of radionuclides (e.g., {sup 131}Cs source) are introduced for clinical use in brachytherapy, the question is raised regarding whether a relatively simple method exists for the derivation of values of the half value layer (HVL) or the tenth value layer (TVL). For the radionuclide that has been clinically used for years, such as {sup 125}I and {sup 103}Pd, the sources have been manufactured and marketed by several vendors with different designs and structures. Because of the nature of emission of low energy photons for these radionuclides, energy spectra of the sources are very dependent on their individual designs. Though values of the HVL or the TVL in certain commonly used shielding materials are relatively small for these low energy photon emitting sources, the question remains how the variations in energy spectra affect the HVL (or TVL) values and whether these values can be calculated with a relatively simple method. A more fundamental question is whether a method can be established to derive the HVL (TVL) values for any brachytherapy sources and for different materials in a relatively straightforward fashion. This study was undertaken to answer these questions. Based on energy spectra, a well established semiempirical mass attenuation coefficient computing scheme was utilized to derive the HVL (TVL) values of different materials for different types of brachytherapy sources. The method presented in this study may be useful to estimate HVL (TVL) values of different materials for brachytherapy sources of different designs and containing different radionuclides.
Yue, Ning J
2008-06-01
As different types of radionuclides (e.g., 131Cs source) are introduced for clinical use in brachytherapy, the question is raised regarding whether a relatively simple method exists for the derivation of values of the half value layer (HVL) or the tenth value layer (TVL). For the radionuclide that has been clinically used for years, such as 125I and 103Pd, the sources have been manufactured and marketed by several vendors with different designs and structures. Because of the nature of emission of low energy photons for these radionuclides, energy spectra of the sources are very dependent on their individual designs. Though values of the HVL or the TVL in certain commonly used shielding materials are relatively small for these low energy photon emitting sources, the question remains how the variations in energy spectra affect the HVL (or TVL) values and whether these values can be calculated with a relatively simple method. A more fundamental question is whether a method can be established to derive the HVL (TVL) values for any brachytherapy sources and for different materials in a relatively straightforward fashion. This study was undertaken to answer these questions. Based on energy spectra, a well established semiempirical mass attenuation coefficient computing scheme was utilized to derive the HVL (TVL) values of different materials for different types of brachytherapy sources. The method presented in this study may be useful to estimate HVL (TVL) values of different materials for brachytherapy sources of different designs and containing different radionuclides.
NASA Astrophysics Data System (ADS)
Zieniuk, Eugeniusz; Kapturczak, Marta; Sawicki, Dominik
2016-06-01
In solving of boundary value problems the shapes of the boundary can be modelled by the curves widely used in computer graphics. In parametric integral equations system (PIES) such curves are directly included into the mathematical formalism. Its simplify the way of definition and modification of the shape of the boundary. Until now in PIES the B-spline, Bézier and Hermite curves were used. Recent developments in the computer graphics paid our attention, therefore we implemented in PIES possibility of defining the shape of boundary using the NURBS curves. The curves will allow us to modeling different shapes more precisely. In this paper we will compare PIES solutions (with applied NURBS) with the solutions existing in the literature.
An optoacoustic point source for acoustic scale model measurements.
Bolaños, Javier Gómez; Pulkki, Ville; Karppinen, Pasi; Hæggström, Edward
2013-04-01
A massless acoustic source is proposed for scale model work. This source is generated by focusing a pulsed laser beam to rapidly heat the air at the focal point. This produces an expanding small plasma ball which generates a sonic impulse that may be used as an acoustic point source. Repeatability, frequency response, and directivity of the source were measured to show that it can serve as a massless point source. The impulse response of a rectangular space was determined using this type of source. A good match was found between the predicted and the measured impulse responses of the space.
Spectral brilliance of parametric X-rays at the FAST facility
Sen, Tanaji; Seiss, Todd
2015-06-22
We discuss the generation of parametric X-rays in the new photoinjector at the FAST (Fermilab Accelerator Science and Technology) facility in Fermilab. These experiments will be conducted in addition to channeling X-ray radiation experiments. The low emittance electron beam makes this facility a promising source for creating brilliant X-rays. We discuss the theoretical model and present detailed calculations of the intensity spectrum, energy and angular widths and spectral brilliance under different conditions. Furthermore, we report on expected results with parametric X-rays generated while under channeling conditions.
Whispering gallery optical parametric oscillators
NASA Astrophysics Data System (ADS)
Breunig, Ingo; Buse, Karsten
2013-12-01
Whispering gallery optical parametric oscillators (WGR OPOs) are monolithic sources for tunable coherent and non-classical light. They are based on total internal reflection. Since reflection losses are negligible, their oscillation threshold can be far below one milliwatt. With sub-millimeter diameters, they are the most compact OPOs demonstrated so far. Recent experimental results demonstrate that WGR OPOs emit coherent light tunable over hundreds of nanometers. Operation in the visible as well as in the near-infrared has been demonstrated with up to 30 % conversion efficiency. These results indicate a great potential of WGR OPOs for spectroscopic and sensing applications.
Stimulated Parametric Emission Microscope Systems
NASA Astrophysics Data System (ADS)
Itoh, Kazuyoshi; Isobe, Keisuke
2006-10-01
We present a novel microscopy technique based on the fourwave mixing (FWM) process that is enhanced by two-photon electronic resonance induced by a pump pulse along with stimulated emission induced by a dump pulse. A Ti:sapphire laser and an optical parametric oscillator are used as light sources for the pump and dump pulses, respectively. We demonstrate that our FWM technique can be used to obtain two-dimensional microscopic images of an unstained leaf of Camellia sinensis and an unlabeled tobacco BY2 Cell.
Modeling a Common-Source Amplifier Using a Ferroelectric Transistor
NASA Technical Reports Server (NTRS)
Sayyah, Rana; Hunt, Mitchell; MacLeond, Todd C.; Ho, Fat D.
2010-01-01
This paper presents a mathematical model characterizing the behavior of a common-source amplifier using a FeFET. The model is based on empirical data and incorporates several variables that affect the output, including frequency, load resistance, and gate-to-source voltage. Since the common-source amplifier is the most widely used amplifier in MOS technology, understanding and modeling the behavior of the FeFET-based common-source amplifier will help in the integration of FeFETs into many circuits.
NASA Astrophysics Data System (ADS)
Offringa, A. R.; Trott, C. M.; Hurley-Walker, N.; Johnston-Hollitt, M.; McKinley, B.; Barry, N.; Beardsley, A. P.; Bowman, J. D.; Briggs, F.; Carroll, P.; Dillon, J. S.; Ewall-Wice, A.; Feng, L.; Gaensler, B. M.; Greenhill, L. J.; Hazelton, B. J.; Hewitt, J. N.; Jacobs, D. C.; Kim, H.-S.; Kittiwisit, P.; Lenc, E.; Line, J.; Loeb, A.; Mitchell, D. A.; Morales, M. F.; Neben, A. R.; Paul, S.; Pindor, B.; Pober, J. C.; Procopio, P.; Riding, J.; Sethi, S. K.; Shankar, N. U.; Subrahmanyan, R.; Sullivan, I. S.; Tegmark, M.; Thyagarajan, N.; Tingay, S. J.; Wayth, R. B.; Webster, R. L.; Wyithe, J. S. B.
2016-05-01
Experiments that pursue detection of signals from the Epoch of Reionization (EoR) are relying on spectral smoothness of source spectra at low frequencies. This article empirically explores the effect of foreground spectra on EoR experiments by measuring high-resolution full-polarization spectra for the 586 brightest unresolved sources in one of the Murchison Widefield Array (MWA) EoR fields using 45 h of observation. A novel peeling scheme is used to subtract 2500 sources from the visibilities with ionospheric and beam corrections, resulting in the deepest, confusion-limited MWA image so far. The resulting spectra are found to be affected by instrumental effects, which limit the constraints that can be set on source-intrinsic spectral structure. The sensitivity and power-spectrum of the spectra are analysed, and it is found that the spectra of residuals are dominated by point spread function sidelobes from nearby undeconvolved sources. We release a catalogue describing the spectral parameters for each measured source.
Observations and Modeling for Source Characterization
2011-02-25
and in and around the Tijuana River plume before, during and after storm events. Data were collected in February and March of 2008 and 2009 for a...sensors. These sources include riverine inputs from the Tijuana River and two outfall plumes in the region. The UUVs were also deployed to observe...California NCOM) was used to provide boundary information to the plume resolving higher resolution mesh. For example, the Tijuana River mouth, two outfall
Data Sources Available for Modeling Environmental Exposures in Older Adults
This report, “Data Sources Available for Modeling Environmental Exposures in Older Adults,” focuses on information sources and data available for modeling environmental exposures in the older U.S. population, defined here to be people 60 years and older, with an emphasis on those...
Parametric Mass Reliability Study
NASA Technical Reports Server (NTRS)
Holt, James P.
2014-01-01
The International Space Station (ISS) systems are designed based upon having redundant systems with replaceable orbital replacement units (ORUs). These ORUs are designed to be swapped out fairly quickly, but some are very large, and some are made up of many components. When an ORU fails, it is replaced on orbit with a spare; the failed unit is sometimes returned to Earth to be serviced and re-launched. Such a system is not feasible for a 500+ day long-duration mission beyond low Earth orbit. The components that make up these ORUs have mixed reliabilities. Components that make up the most mass-such as computer housings, pump casings, and the silicon board of PCBs-typically are the most reliable. Meanwhile components that tend to fail the earliest-such as seals or gaskets-typically have a small mass. To better understand the problem, my project is to create a parametric model that relates both the mass of ORUs to reliability, as well as the mass of ORU subcomponents to reliability.
Source Term Model for an Array of Vortex Generator Vanes
NASA Technical Reports Server (NTRS)
Buning, P. G. (Technical Monitor); Waithe, Kenrick A.
2003-01-01
A source term model was developed for numerical simulations of an array of vortex generators. The source term models the side force created by a vortex generator being modeled. The model is obtained by introducing a side force to the momentum and energy equations that can adjust its strength automatically based on a local flow. The model was tested and calibrated by comparing data from numerical simulations and experiments of a single low-profile vortex generator vane, which is only a fraction of the boundary layer thickness, over a flat plate. The source term model allowed a grid reduction of about seventy percent when compared with the numerical simulations performed on a fully gridded vortex generator without adversely affecting the development and capture of the vortex created. The source term model was able to predict the shape and size of the stream wise vorticity and velocity contours very well when compared with both numerical simulations and experimental data.
Neuromagnetic source reconstruction
Lewis, P.S.; Mosher, J.C.; Leahy, R.M.
1994-12-31
In neuromagnetic source reconstruction, a functional map of neural activity is constructed from noninvasive magnetoencephalographic (MEG) measurements. The overall reconstruction problem is under-determined, so some form of source modeling must be applied. We review the two main classes of reconstruction techniques-parametric current dipole models and nonparametric distributed source reconstructions. Current dipole reconstructions use a physically plausible source model, but are limited to cases in which the neural currents are expected to be highly sparse and localized. Distributed source reconstructions can be applied to a wider variety of cases, but must incorporate an implicit source, model in order to arrive at a single reconstruction. We examine distributed source reconstruction in a Bayesian framework to highlight the implicit nonphysical Gaussian assumptions of minimum norm based reconstruction algorithms. We conclude with a brief discussion of alternative non-Gaussian approachs.
Nuisance Source Population Modeling for Radiation Detection System Analysis
Sokkappa, P; Lange, D; Nelson, K; Wheeler, R
2009-10-05
A major challenge facing the prospective deployment of radiation detection systems for homeland security applications is the discrimination of radiological or nuclear 'threat sources' from radioactive, but benign, 'nuisance sources'. Common examples of such nuisance sources include naturally occurring radioactive material (NORM), medical patients who have received radioactive drugs for either diagnostics or treatment, and industrial sources. A sensitive detector that cannot distinguish between 'threat' and 'benign' classes will generate false positives which, if sufficiently frequent, will preclude it from being operationally deployed. In this report, we describe a first-principles physics-based modeling approach that is used to approximate the physical properties and corresponding gamma ray spectral signatures of real nuisance sources. Specific models are proposed for the three nuisance source classes - NORM, medical and industrial. The models can be validated against measured data - that is, energy spectra generated with the model can be compared to actual nuisance source data. We show by example how this is done for NORM and medical sources, using data sets obtained from spectroscopic detector deployments for cargo container screening and urban area traffic screening, respectively. In addition to capturing the range of radioactive signatures of individual nuisance sources, a nuisance source population model must generate sources with a frequency of occurrence consistent with that found in actual movement of goods and people. Measured radiation detection data can indicate these frequencies, but, at present, such data are available only for a very limited set of locations and time periods. In this report, we make more general estimates of frequencies for NORM and medical sources using a range of data sources such as shipping manifests and medical treatment statistics. We also identify potential data sources for industrial source frequencies, but leave the task of
Analytical model of an isolated single-atom electron source.
Engelen, W J; Vredenbregt, E J D; Luiten, O J
2014-12-01
An analytical model of a single-atom electron source is presented, where electrons are created by near-threshold photoionization of an isolated atom. The model considers the classical dynamics of the electron just after the photon absorption, i.e. its motion in the potential of a singly charged ion and a uniform electric field used for acceleration. From closed expressions for the asymptotic transverse electron velocities and trajectories, the effective source temperature and the virtual source size can be calculated. The influence of the acceleration field strength and the ionization laser energy on these properties has been studied. With this model, a single-atom electron source with the optimum electron beam properties can be designed. Furthermore, we show that the model is also applicable to ionization of rubidium atoms, and thus also describes the ultracold electron source, which is based on photoionization of laser-cooled alkali atoms.
Modeling Group Interactions via Open Data Sources
2011-08-30
data. The state-of-art search engines are designed to help general query-specific search and not suitable for finding disconnected online groups. The...groups, (2) developing innovative mathematical and statistical models and efficient algorithms that leverage existing search engines and employ
Modeling the reversible sink effect in response to transient contaminant sources
Zhao, Dongye; Little, John C.; Hodgson, Alfred T.
2001-02-01
A physically based diffusion model is used to evaluate the sink effect of diffusion-controlled indoor materials and to predict the transient contaminant concentration in indoor air in response to several time-varying contaminant sources. For simplicity, it is assumed the predominant indoor material is a homogeneous slab, initially free of contaminant, and the air within the room is well mixed. The model enables transient volatile organic compound (VOC) concentrations to be predicted based on the material/air partition coefficient (K) and the material-phase diffusion coefficient (D) of the sink. Model predictions are made for three scenarios, each mimicking a realistic situation in a building. Styrene, phenol, and naphthalene are used as representative VOCs. A styrene butadiene rubber (SBR) backed carpet, vinyl flooring (VF), and a polyurethane foam (PUF) carpet cushion are considered as typical indoor sinks. In scenarios involving a sinusoidal VOC input and a double exponential decaying input, the model predicts the sink has a modest impact for SBR/styrene, but the effect increases for VF/phenol and PUF/naphthalene. In contrast, for an episodic chemical spill, SBR is predicted to reduce the peak styrene concentration considerably. A parametric study reveals for systems involving a large equilibrium constant (K), the kinetic constant (D) will govern the shape of the resulting gas-phase concentration profile. On the other hand, for systems with a relaxed mass transfer resistance, K will dominate the profile.