Baillet, S.; Mosher, J. C.; Jerbi, K.; Leahy, R. M.
2001-01-01
Reliable estimation of the local spatial extent of neural activity is a key to the quantitative analysis of MEG sources across subjects and conditions. In association with an understanding of the temporal dynamics among multiple areas, this would represent a major advance in electrophysiological source imaging. Parametric current dipole approaches to MEG (and EEG) source localization can rapidly generate a physical model of neural current generators using a limited number of parameters. However, physiological interpretation of these models is often difficult, especially in terms of the spatial extent of the true cortical activity. In new approaches using multipolar source models [3, 5], similar problems remain in the analysis of the higher-order source moments as parameters of cortical extent. Image-based approaches to the inverse problem provide a direct estimate of cortical current generators, but computationally expensive nonlinear methods are required to produce focal sources [1,4]. Recent efforts describe how a cortical patch can be grown until a best fit to the data is reached in the least-squares sense [6], but computational considerations necessitate that the growth be seeded in predefined regions of interest. In a previous study [2], a source obtained using a parametric model was remapped onto the cortex by growing a patch of cortical dipoles in the vicinity of the parametric source until the forward MEG or EEG fields of the parametric and cortical sources matched. The source models were dipoles and first-order multipoles. We propose to combine the parametric and imaging methods for MEG source characterization to take advantage of (i) the parsimonious and computationally efficient nature of parametric source localization methods and (ii) the anatomical and physiological consistency of imaging techniques that use relevant a priori information. By performing the cortical remapping imaging step by matching the multipole expansions of the original parametric
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.
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.
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.
NASA Astrophysics Data System (ADS)
Lambrakos, S. G.
2016-04-01
A general methodology for inverse thermal analysis of steady-state energy deposition in plate structures, typically welds, is extended with respect to its formulation. This methodology is in terms of numerical-analytical basis functions, which provide parametric representations of weld-temperature histories that can be adopted as input data to various types of computational procedures, such as those for prediction of solid-state phase transformations and mechanical response. The extension of the methodology presented here concerns construction of numerical-analytical basis functions and their associated parameterizations, which permit optimal and convenient parameter optimization with respect to different types of weld-workpiece boundary conditions, energy source characteristics, and experimental measurements adoptable as weld-temperature history constraints. Prototype inverse thermal analyses of a steel weld are presented that provide proof of concept for inverse thermal analysis using these basis functions.
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.
Terahertz parametric sources and imaging applications
NASA Astrophysics Data System (ADS)
Yamashita, M.; Ogawa, Y.; Otani, C.; Kawase, K.
2005-12-01
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 LiNbO 3 or MgO-doped LiNbO 3 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 report the detailed characteristics of the oscillation and the radiation including tunability, spatial and temporal coherency, uni directivity, and efficiency. A Fourier transform limited THz-wave spectrum narrowing was achieved by introducing the injection seeding method. Further, we have developed a spectroscopic THz imaging system using a TPO, which allows detection and identification of drugs concealed in envelopes, by introducing the component spatial pattern analysis. Several images of the envelope are recorded at different THz frequencies and then processed. The final result is an image that reveals what substances are present in the envelope, in what quantity, and how they are distributed across the envelope area. The example presented here shows the identification of three drugs, two of which illegal, while one is an over-the-counter drug.
Parametric Cost Models for Space Telescopes
NASA Technical Reports Server (NTRS)
Stahl, H. Philip
2010-01-01
A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.
Parametric models for samples of random functions
Grigoriu, M.
2015-09-15
A new class of parametric models, referred to as sample parametric models, is developed for random elements that match sample rather than the first two moments and/or other global properties of these elements. The models can be used to characterize, e.g., material properties at small scale in which case their samples represent microstructures of material specimens selected at random from a population. The samples of the proposed models are elements of finite-dimensional vector spaces spanned by samples, eigenfunctions of Karhunen–Loève (KL) representations, or modes of singular value decompositions (SVDs). The implementation of sample parametric models requires knowledge of the probability laws of target random elements. Numerical examples including stochastic processes and random fields are used to demonstrate the construction of sample parametric models, assess their accuracy, and illustrate how these models can be used to solve efficiently stochastic equations.
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.
Marmarelis, Vasilis Z.; Berger, Theodore W.
2009-01-01
Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in the central nervous system (CNS). The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the form of Volterra kernels) that transforms the presynaptic signals into postsynaptic signals. In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input–output data. Results show that the non-parametric models accurately and efficiently replicate the input–output transformations of the parametric models. Volterra kernels provide a general and quantitative representation of the STP. PMID:18506609
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.
Practical quantum repeaters with parametric down-conversion sources
NASA Astrophysics Data System (ADS)
Krovi, Hari; Guha, Saikat; Dutton, Zachary; Slater, Joshua A.; Simon, Christoph; Tittel, Wolfgang
2016-03-01
Conventional wisdom suggests that realistic quantum repeaters will require quasi-deterministic sources of entangled photon pairs. In contrast, we here study a quantum repeater architecture that uses simple parametric down-conversion sources, as well as frequency-multiplexed multimode quantum memories and photon-number-resolving detectors. We show that this approach can significantly extend quantum communication distances compared to direct transmission. This shows that important trade-offs are possible between the different components of quantum repeater architectures.
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.
Single Photon Interference with Spontaneous Parametric Downconversion Source
NASA Astrophysics Data System (ADS)
Alexander, Preston; Baldwin, Scott; McCracken, S. Blane; Smith, R. Seth
2015-04-01
During the past two years, a Quantum Optics Laboratory was constructed and tested at Francis Marion University. A spontaneous parametric downconversion source was used to create pairs of correlated photons for use in single photon tests of quantum mechanics. In this experiment, single photon interference was demonstrated by using a spontaneous parametric downconversion source. The two beams emanating from the downconversion crystal are referred to as the signal and idler beams. Detector A was placed in front the idler beam. The signal beam was sent to a polarization interferometer that was followed by a 50/50 beam splitter. The reflected and transmitted beams were incident on Detectors B and B'. By observing the presence or absence of coincidences, it was possible to demonstrate both particle and wave behaviors for light. In particular, if individual photons are passed through a polarization interferometer, it was shown that they will interfere with themselves. The details of the experimental setup and the results will be presented.
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.
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.
Power-law parametrized quintessence model
Rahvar, Sohrab; Movahed, M. Sadegh
2007-01-15
We propose a simple power-law parametrized quintessence model with time-varying equation of state and obtain corresponding quintessence potential of this model. This model is compared with Supernova Type Ia (SNIa) Gold sample data, size of baryonic acoustic peak from Sloan Digital Sky Survey (SDSS), the position of the acoustic peak from the CMB observations and structure formation from the 2dFGRS survey and put constrain on the parameters of model. The parameters from the best fit indicates that the equation of state of this model at the present time is w{sub 0}=-1.40{sub -0.65}{sup +0.40} at 1{sigma} confidence level. Finally we calculate the age of universe in this model and compare it with the age of old cosmological objects.
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…
NASA Astrophysics Data System (ADS)
Gersch, W.; Brotherton, T.; Braun, S.
1980-04-01
A multiple input/scalar output stationary time series identification problem is considered from a parametric model time domain point of view. Particular emphasis is on the source identification problem. Closed form formula estimates of the individual source power contributions are expressed in terms of sample correlations that are obtained from the observed input and output time series and from parametric models fitted to that data. The estimates of the noise power contributions are asymptotically jointly normally distributed. The mean values and covariance matrix of those estimates yield confidence interval estimates of the individual and joint power contributions. The motivation for developing a rational polynomial transfer function or ARMA model of the multi-input scalar output plus additive noise situation is given. A two correlated input/single output version of this model is considered for a Monte Carlo simulation study. Parametric ARMA and approximate AR models are fitted to the simulated data. The asymptotic normality, and the distribution of the mean and covariances of the source power contribution computed from the ARMA and AR models are appraised. Several facets of the relative performance of windowed periodogram and AR model spectral analysis are examined for the multiple input/scalar output identification problem. The points that are emphasized are that conventional windowed periodogram spectral analysis is subjective, not particularly satisfactory for the sharp spectral peak situation that is commonly encountered in vibration data analysis and very likely not as good as "objective" Akaike criterion order AR modelled spectral analysis.
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).
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.
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 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.
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. PMID:25836452
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
Global Nonlinear Parametric Modeling with Application to F-16 Aerodynamics
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
1997-01-01
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.
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.
High average power parametric frequency conversion-new concepts and new pump sources
Velsko, S.P.; Webb, M.S.
1994-03-01
A number of applications, including long range remote sensing and antisensor technology, require high average power tunable radiation in several distinct spectral regions. Of the many issues which determine the deployability of optical parametric oscillators (OPOS) and related systems, efficiency and simplicity are among the most important. It is only recently that the advent of compact diode laser pumped solid state lasers has produced pump sources for parametric oscillators which can make compact, efficient, high average power tunable sources possible. In this paper we outline several different issues in parametric oscillator and pump laser development which are currently under study at Lawrence Livermore National Laboratory.
Incident Duration Modeling Using Flexible Parametric Hazard-Based Models
2014-01-01
Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers. This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model. Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008. Results show that different factors significantly affect different incident time phases, whose best distributions were diverse. Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents. The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time. PMID:25530753
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)
Parametric models of reflectance spectra for dyed fabrics
NASA Astrophysics Data System (ADS)
Aiken, Daniel C.; Ramsey, Scott; Mayo, Troy; Lambrakos, Samuel G.; Peak, Joseph
2016-05-01
This study examines parametric modeling of NIR reflectivity spectra for dyed fabrics, which provides for both their inverse and direct modeling. The dye considered for prototype analysis is triarylamine dye. The fabrics considered are camouflage textiles characterized by color variations. The results of this study provide validation of the constructed parametric models, within reasonable error tolerances for practical applications, including NIR spectral characteristics in camouflage textiles, for purposes of simulating NIR spectra corresponding to various dye concentrations in host fabrics, and potentially to mixtures of dyes.
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?
Developing Parametric Building Models - the Gandis Use Case
NASA Astrophysics Data System (ADS)
Thaller, W.; Krispel, U.; Havemann, S.; Redi, I.; Redi, A.; Fellner, D. W.
2011-09-01
In the course of a project related to green building design, we have created a group of eight parametric building models that can be manipulated interactively with respect to dimensions, number of floors, and a few other parameters. We report on the commonalities and differences between the models and the abstractions that we were able to identify.
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
A Parametric Approach to Numerical Modeling of TKR Contact Forces
Lundberg, Hannah J.; Foucher, Kharma C.; Wimmer, Markus A.
2009-01-01
In vivo knee contact forces are difficult to determine using numerical methods because there are more unknown forces than equilibrium equations available. We developed parametric methods for computing contact forces across the knee joint during the stance phase of level walking. Three-dimensional contact forces were calculated at two points of contact between the tibia and the femur, one on the lateral aspect of the tibial plateau, and one on the medial side. Muscle activations were parametrically varied over their physiologic range resulting in a solution space of contact forces. The obtained solution space was reasonably small and the resulting force pattern compared well to a previous model from the literature for kinematics and external kinetics from the same patient. Peak forces of the parametric model and the previous model were similar for the first half of the stance phase, but differed for the second half. The previous model did not take into account the transverse external moment about the knee and could not calculate muscle activation levels. Ultimately, the parametric model will result in more accurate contact force inputs for total knee simulators, as current inputs are not generally based on kinematics and kinetics inputs from TKR patients. PMID:19155015
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
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. PMID:27446655
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
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.
New approach in bats' sonar signals parametrization and modelling
NASA Astrophysics Data System (ADS)
Herman, Krzysztof; Gudra, Tadeusz
2010-01-01
Parameterization of bats' echolocation signal is essentially based on determination of spectral power density by means of the classic Fourier transform FFT. This study presents an alternative solution in this area of research, that is parametric and non-parametric modelling of short-time signals. The above mentioned methods are based on modelling of white noise with the use of digital filters the transmission of which was set in a way that allows the output signal to be as close to the modelled signal as possible. Proper selection of parameterization method - MA (Moving Average), AR (Autoregressive), ARMA (Autoregressive Moving Average), in respect of the character of signal spectrum (line spectrum, noise) maximally reduces the number of filter coefficients and improves the accuracy of bat's signal modelling. The work also presents the possibility of using the suggested parameterization methods in automatic species identification.
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.
A Parametric Empirical Bayesian framework for fMRI-constrained MEG/EEG source reconstruction
Henson, Richard N; Flandin, Guillaume; Friston, Karl J; Mattout, Jérémie
2010-01-01
We describe an asymmetric approach to fMRI and MEG/EEG fusion in which fMRI data are treated as empirical priors on electromagnetic sources, such that their influence depends on the MEG/EEG data, by virtue of maximizing the model evidence. This is important if the causes of the MEG/EEG signals differ from those of the fMRI signal. Furthermore, each suprathreshold fMRI cluster is treated as a separate prior, which is important if fMRI data reflect neural activity arising at different times within the EEG/MEG data. We present methodological considerations when mapping from a 3D fMRI Statistical Parametric Map to a 2D cortical surface and thence to the covariance components used within our Parametric Empirical Bayesian framework. Our previous introduction of a canonical (inverse-normalized) cortical mesh also allows deployment of fMRI priors that live in a template space; for example, from a group analysis of different individuals. We evaluate the ensuing scheme with MEG and EEG data recorded simultaneously from 12 participants, using the same face-processing paradigm under which independent fMRI data were obtained. Because the fMRI priors become part of the generative model, we use the model evidence to compare (i) multiple versus single, (ii) valid versus invalid, (iii) binary versus continuous, and (iv) variance versus covariance fMRI priors. For these data, multiple, valid, binary, and variance fMRI priors proved best for a standard Minimum Norm inversion. Interestingly, however, inversion using Multiple Sparse Priors benefited little from additional fMRI priors, suggesting that they already provide a sufficiently flexible generative model. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc. PMID:20091791
A parametric vocal fold model based on magnetic resonance imaging.
Wu, Liang; Zhang, Zhaoyan
2016-08-01
This paper introduces a parametric three-dimensional body-cover vocal fold model based on magnetic resonance imaging (MRI) of the human larynx. Major geometric features that are observed in the MRI images but missing in current vocal fold models are discussed, and their influence on vocal fold vibration is evaluated using eigenmode analysis. Proper boundary conditions for the model are also discussed. Based on control parameters corresponding to anatomic landmarks that can be easily measured, this model can be adapted toward a subject-specific vocal fold model for voice production research and clinical applications. PMID:27586774
Fiber-integrated 780 nm source for visible parametric generation.
Hu, D J J; Murray, R T; Legg, T; Runcorn, T H; Zhang, M; Woodward, R I; Lim, J L; Wang, Y; Luan, F; Gu, B; Shum, P P; Kelleher, E J R; Popov, S V; Taylor, J R
2014-12-01
We report the development of a fully fiber-integrated pulsed master oscillator power fibre amplifier (MOPFA) source at 780 nm, producing 3.5 W of average power with 410 ps pulses at a repetition rate of 50 MHz. The source consists of an intensity modulated 1560 nm laser diode amplified in an erbium fiber amplifier chain, followed by a fiber coupled periodically poled lithium niobate crystal module for frequency doubling. The source is then used for generating visible light through four-wave mixing in a length of highly nonlinear photonic crystal fiber: 105 mW at 668 nm and 95 mW at 662 nm are obtained, with pump to anti-Stokes conversion slope efficiencies exceeding 6% in both cases. PMID:25606903
Point matching based on non-parametric model
NASA Astrophysics Data System (ADS)
Liu, Renfeng; Zhang, Cong; Tian, Jinwen
2015-12-01
Establishing reliable feature correspondence between two images is a fundamental problem in vision analysis and it is a critical prerequisite in a wide range of applications including structure-from-motion, 3D reconstruction, tracking, image retrieval, registration, and object recognition. The feature could be point, line, curve or surface, among which the point feature is primary and is the foundation of all features. Numerous techniques related to point matching have been proposed within a rich and extensive literature, which are typically studied under rigid/affine or non-rigid motion, corresponding to parametric and non-parametric models for the underlying image relations. In this paper, we provide a review of our previous work on point matching, focusing on nonparametric models. We also make an experimental comparison of the introduced methods, and discuss their advantages and disadvantages as well.
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…
Parametric Modeling of the Mouse Left Ventricular Myocardial Fiber Structure.
Merchant, Samer S; Gomez, Arnold David; Morgan, James L; Hsu, Edward W
2016-09-01
Magnetic resonance diffusion tensor imaging (DTI) has greatly facilitated detailed quantifications of myocardial structures. However, structural patterns, such as the distinctive transmural rotation of the fibers, remain incompletely described. To investigate the validity and practicality of pattern-based analysis, 3D DTI was performed on 13 fixed mouse hearts and fiber angles in the left ventricle were transformed and fitted to parametric expressions constructed from elementary functions of the prolate spheroidal spatial variables. It was found that, on average, the myocardial fiber helix angle could be represented to 6.5° accuracy by the equivalence of a product of 10th-order polynomials of the radial and longitudinal variables, and 17th-order Fourier series of the circumferential variable. Similarly, the fiber imbrication angle could be described by 10th-order polynomials and 24th-order Fourier series, to 5.6° accuracy. The representations, while relatively concise, did not adversely affect the information commonly derived from DTI datasets including the whole-ventricle mean fiber helix angle transmural span and atlases constructed for the group. The unique ability of parametric models for predicting the 3D myocardial fiber structure from finite number of 2D slices was also demonstrated. These findings strongly support the principle of parametric modeling for characterizing myocardial structures in the mouse and beyond. PMID:26942586
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.
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.
A parametric single scattering channel model for non-line-of-sight ultraviolet communications
NASA Astrophysics Data System (ADS)
Ding, Haipeng; Chen, Gang; Majumdar, Arun K.; Xu, Zhengyuan
2008-08-01
Recent advances in ultraviolet (UV) semiconductor sources and detectors have inspired significant research activities in short-range UV communications, particularly in non-line-of-sight (NLOS) channel conditions due to atmospheric scattering. However, a scattering channel involves complex interactions of photons with atmospheric particles. This paper presents a parametric channel model that greatly simplifies channel characterization. For a short range link, single scattering may dominate in some scenarios. We model the channel impulse response with a gamma function as well as its variants to better fit the prediction by a widely adopted analytical single scattering model. Normalized mean square fitting error is adopted to validate our parametric model. Path losses and channel bandwidths are subsequently studied under different geometrical link configurations.
DPpackage: Bayesian Non- and Semi-parametric Modelling in R.
Jara, Alejandro; Hanson, Timothy E; Quintana, Fernando A; Müller, Peter; Rosner, Gary L
2011-04-01
Data analysis sometimes requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against mis-specification of the probability model. In the Bayesian context, this is accomplished by placing a prior distribution on a function space, such as the space of all probability distributions or the space of all regression functions. Unfortunately, posterior distributions ranging over function spaces are highly complex and hence sampling methods play a key role. This paper provides an introduction to a simple, yet comprehensive, set of programs for the implementation of some Bayesian non- and semi-parametric models in R, DPpackage. Currently DPpackage includes models for marginal and conditional density estimation, ROC curve analysis, interval-censored data, binary regression data, item response data, longitudinal and clustered data using generalized linear mixed models, and regression data using generalized additive models. The package also contains functions to compute pseudo-Bayes factors for model comparison, and for eliciting the precision parameter of the Dirichlet process prior. To maximize computational efficiency, the actual sampling for each model is carried out using compiled FORTRAN. PMID:21796263
On the influence of model parametrization in elastic full waveform tomography
NASA Astrophysics Data System (ADS)
Köhn, D.; De Nil, D.; Kurzmann, A.; Przebindowska, A.; Bohlen, T.
2012-10-01
Elastic Full Waveform Tomography (FWT) aims to reduce the misfit between recorded and modelled data, to deduce a very detailed model of elastic material parameters in the underground. The choice of the elastic model parameters to be inverted affects the convergence and quality of the reconstructed subsurface model. Using the Cross-Triangle-Squares (CTS) model three elastic parametrizations, Lamé parameters m1 = [λ, μ, ρ], seismic velocities m2 = [Vp, Vs, ρ] and seismic impedances m3 = [Ip, Is, ρ] for far-offset reflection seismic acquisition geometries with explosive point sources and free-surface condition are studied. In each CTS model the three elastic parameters are assigned to three different geometrical objects that are spatially separated. The results of the CTS model study reveal a strong requirement of a sequential frequency inversion from low to high frequencies to reconstruct the density model. Using only high-frequency data, cross-talk artefacts have an influence on the quantitative reconstruction of the material parameters, while for a sequential frequency inversion only structural artefacts, representing the boundaries of different model parameters, are present. During the inversion, the Lamé parameters, seismic velocities and impedances could be reconstructed well. However, using the Lamé parametrization ?-artefacts are present in the λ model, while similar artefacts are suppressed when using seismic velocities or impedances. The density inversion shows the largest ambiguity for all parametrizations. However, the artefacts are again more dominant, when using the Lamé parameters and suppressed for seismic velocity and impedance parametrization. The afore mentioned results are confirmed for a geologically more realistic modified Marmousi-II model. Using a conventional streamer acquisition geometry the P-velocity, S-velocity and density models of the subsurface were reconstructed successfully and are compared with the results of the Lam
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.
Facial Performance Transfer via Deformable Models and Parametric Correspondence.
Asthana, Akshay; de la Hunty, Miles; Dhall, Abhinav; Goecke, Roland
2012-09-01
The issue of transferring facial performance from one person's face to another's has been an area of interest for the movie industry and the computer graphics community for quite some time. In recent years, deformable face models, such as the Active Appearance Model (AAM), have made it possible to track and synthesize faces in real time. Not surprisingly, deformable face model-based approaches for facial performance transfer have gained tremendous interest in the computer vision and graphics community. In this paper, we focus on the problem of real-time facial performance transfer using the AAM framework. We propose a novel approach of learning the mapping between the parameters of two completely independent AAMs, using them to facilitate the facial performance transfer in a more realistic manner than previous approaches. The main advantage of modeling this parametric correspondence is that it allows a "meaningful" transfer of both the nonrigid shape and texture across faces irrespective of the speakers' gender, shape, and size of the faces, and illumination conditions. We explore linear and nonlinear methods for modeling the parametric correspondence between the AAMs and show that the sparse linear regression method performs the best. Moreover, we show the utility of the proposed framework for a cross-language facial performance transfer that is an area of interest for the movie dubbing industry. PMID:21931176
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.
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.
Modification of the method of parametric estimation of atmospheric distortion in MODTRAN model
NASA Astrophysics Data System (ADS)
Belov, A. M.
2015-12-01
The paper presents a modification of the method of parametric estimation of atmospheric distortion in MODTRAN model as well as experimental research of the method. The experimental research showed that the base method does not take into account physical meaning of atmospheric spherical albedo parameter and presence of outliers in source data that results to overall atmospheric correction accuracy decreasing. Proposed modification improves the accuracy of atmospheric correction in comparison with the base method. The modification consists in the addition of nonnegativity constraint on the atmospheric spherical albedo estimated value and the addition of preprocessing stage aimed to adjust source data.
Numerical Models of Broad-Bandwidth Nanosecond Optical Parametric Oscillators
Bowers, M.S.; Gehr. R.J.; Smith, A.V.
1998-10-22
We present three new methods for modeling broad-bandwidth, nanosecond optitcal parametric oscillators in the plane-wave approximation. Each accounts for the group-velocity differences that determine the operating linewidth of unseeded optical parametric oscillators, and each allows the signal and idler waves to develop from quantum noise. The first two methods are based on split-step integration methods in which nonlinear mixing and propagation are calculated separately on alternate steps. One method relies on Fourier transforming handle propagation, wiih mixing integrated over a the fields between t and u to Az step: the other transforms between z and k= in the propagation step, with mixing integrated over At. The third method is based on expansion of the three optical fields in terms of their respective longitudinal empty cavity modes, taking into account the cavity boundary condi- tions. Equations describing the time development of the mode amplitudes are solved to yield the time dependence of the three output fields. These plane-wave models exclude diffractive effects, but can be readily extended to include them.
Pixel-based parametric source depth map for Cerenkov luminescence imaging
NASA Astrophysics Data System (ADS)
Altabella, L.; Boschi, F.; Spinelli, A. E.
2016-01-01
Optical tomography represents a challenging problem in optical imaging because of the intrinsically ill-posed inverse problem due to photon diffusion. Cerenkov luminescence tomography (CLT) for optical photons produced in tissues by several radionuclides (i.e.: 32P, 18F, 90Y), has been investigated using both 3D multispectral approach and multiviews methods. Difficult in convergence of 3D algorithms can discourage to use this technique to have information of depth and intensity of source. For these reasons, we developed a faster 2D corrected approach based on multispectral acquisitions, to obtain source depth and its intensity using a pixel-based fitting of source intensity. Monte Carlo simulations and experimental data were used to develop and validate the method to obtain the parametric map of source depth. With this approach we obtain parametric source depth maps with a precision between 3% and 7% for MC simulation and 5-6% for experimental data. Using this method we are able to obtain reliable information about the source depth of Cerenkov luminescence with a simple and flexible procedure.
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
Channeling and parametric X-ray studies at the SAGA Light Source
NASA Astrophysics Data System (ADS)
Takabayashi, Y.; Korotchenko, K. B.; Pivovarov, Yu. L.; Tukhfatullin, T. A.
2013-11-01
We present experimental results on channeling and parametric X-ray radiation obtained using a 255-MeV electron beam from an injector linac at the SAGA Light Source. Using a screen monitor, we observed both channeling phenomena and doughnut scattering by measuring the profile of an electron beam transmitted through a 20-μm-thick Si crystal. We also measured the angular distribution of parametric X-ray radiation using an imaging plate as a two-dimensional X-ray detector. The obtained results are in good agreement with theory. The final goal of these studies is the first observation of diffracted channeling radiation, and our strategy for achieving this is discussed.
Neugebauer, Romain; Fireman, Bruce; Roy, Jason A.; Raebel, Marsha A.; Nichols, Gregory A.; O’Connor, Patrick J.
2013-01-01
Objective Clinical trials are unlikely to ever be launched for many Comparative Effectiveness Research (CER) questions. Inferences from hypothetical randomized trials may however be emulated with marginal structural modeling (MSM) using observational data but success in adjusting for time-dependent confounding and selection bias typically relies on parametric modeling assumptions. If these assumptions are violated, inferences from MSM may be inaccurate. In this article, we motivate the application of a data-adaptive estimation approach called Super Learning to avoid reliance on arbitrary parametric assumptions in CER. Study Design and Setting Using the electronic health records data from adults with new onset type 2 diabetes, we implemented MSM with inverse probability weighting estimation to evaluate the effect of three oral anti-diabetic therapies on the worsening of glomerular filtration rate. Results Inferences from IPW estimation were noticeably sensitive to the parametric assumptions about the associations between both the exposure and censoring processes and the main suspected source of confounding, i.e., time-dependent measurements of hemoglobin A1c. Super Learning was successfully implemented to harness flexible confounding and selection bias adjustment from existing machine learning algorithms. Conclusion Erroneous IPW inference about clinical effectiveness due to arbitrary and incorrect modeling decisions may be avoided with Super Learning. PMID:23849160
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. PMID:15300453
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.
Modeling Frequency Comb Sources
NASA Astrophysics Data System (ADS)
Li, Feng; Yuan, Jinhui; Kang, Zhe; Li, Qian; Wai, P. K. A.
2016-06-01
Frequency comb sources have revolutionized metrology and spectroscopy and found applications in many fields. Stable, low-cost, high-quality frequency comb sources are important to these applications. Modeling of the frequency comb sources will help the understanding of the operation mechanism and optimization of the design of such sources. In this paper,we review the theoretical models used and recent progress of the modeling of frequency comb sources.
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
Linear-optical qubit amplification with spontaneous parametric down-conversion source
NASA Astrophysics Data System (ADS)
Ou-Yang, Yang; Feng, Zhao-Feng; Zhou, Lan; Sheng, Yu-Bo
2016-01-01
A single photon is the basic building block in quantum communication. However, it is sensitive to photon loss. In this paper, we discuss a linear-optical amplification protocol for protecting a single photon with a practical spontaneous parametric down-conversion (SPDC) source. Our protocol revealed that in a practical experimental condition, the amplification using entanglement as an auxiliary is more powerful than the amplification using a single photon as an auxiliary, for the vacuum state in the SPDC source does not disturb the amplification and can be eliminated automatically. Moreover, the weak SPDC source will become another advantage to benefit the amplification, as the double-pair emission error can be decreased. Our protocol may be useful in future quantum cryptography, especially in the device-independent quantum key distribution.
Kaneda, Fumihiro; Garay-Palmett, Karina; U'Ren, Alfred B; Kwiat, Paul G
2016-05-16
We report on the generation of an indistinguishable heralded single-photon state, using highly nondegenerate spontaneous parametric downconversion (SPDC). Spectrally factorable photon pairs can be generated by incorporating a broadband pump pulse and a group-velocity matching (GVM) condition in a periodically-poled potassium titanyl phosphate (PPKTP) crystal. The heralding photon is in the near IR, close to the peak detection efficiency of off-the-shelf Si single-photon detectors; meanwhile, the heralded photon is in the telecom L-band where fiber losses are at a minimum. We observe spectral factorability of the SPDC source and consequently high purity (90%) of the produced heralded single photons by several different techniques. Because this source can also realize a high heralding efficiency (> 90%), it would be suitable for time-multiplexing techniques, enabling a pseudo-deterministic single-photon source, a critical resource for optical quantum information and communication technology. PMID:27409894
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. PMID:22627277
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.
Testing wave-function-collapse models using parametric heating of a trapped nanosphere
NASA Astrophysics Data System (ADS)
Goldwater, Daniel; Paternostro, Mauro; Barker, P. F.
2016-07-01
We propose a mechanism for testing the theory of collapse models such as continuous spontaneous localization (CSL) by examining the parametric heating rate of a trapped nanosphere. The random localizations of the center of mass for a given particle predicted by the CSL model can be understood as a stochastic force embodying a source of heating for the nanosphere. We show that by utilizing a Paul trap to levitate the particle and optical cooling, it is possible to reduce environmental decoherence to such a level that CSL dominates the dynamics and contributes the main source of heating. We show that this approach allows measurements to be made on the time scale of seconds and that the free parameter λcsl which characterizes the model ought to be testable to values as low as 10-12 Hz.
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)
Modeling segregation of bidisperse granular materials: A parametric study
NASA Astrophysics Data System (ADS)
Schlick, Conor; Fan, Yi; Umbanhowar, Paul; Ottino, Julio; Lueptow, Richard
2013-11-01
Predicting segregation and mixing of size bidisperse granular material is a challenging problem with many industrial applications. Using an accurate segregation model based on kinematic properties of the flow that we recently developed, we present a parametric study of segregation of bidisperse granular material in quasi-two-dimensional bounded heaps. The model depends on the Péclet number, Pe, which is the ratio of the advection rate to the diffusion rate, and Λ, which is the ratio of the segregation rate to the advection rate. Both dimensionless parameters depend on the feed rate, the particle size ratio, and the system size. Systematic variation of Λ and Pe demonstrates how the spatial particle configuration depends on the interplay of advection, segregation, and diffusion. At large values of Pe and Λ, segregation dominates and the heap consists of distinct regions of small (upstream) and large (downstream) particles, whereas at low values of Pe and Λ, diffusion dominates which results in a well-mixed heap. Advection plays an important role for large Pe and small Λ and preserves the initial configuration of particles in the feed zone. Y.F. was funded by The Dow Chemical Company. C.S. was supported by NSF Grant CMMI-1000469.
Unsteady wind loads for TMT: replacing parametric models with CFD
NASA Astrophysics Data System (ADS)
MacMartin, Douglas G.; Vogiatzis, Konstantinos
2014-08-01
Unsteady wind loads due to turbulence inside the telescope enclosure result in image jitter and higher-order image degradation due to M1 segment motion. Advances in computational fluid dynamics (CFD) allow unsteady simulations of the flow around realistic telescope geometry, in order to compute the unsteady forces due to wind turbulence. These simulations can then be used to understand the characteristics of the wind loads. Previous estimates used a parametric model based on a number of assumptions about the wind characteristics, such as a von Karman spectrum and frozen-flow turbulence across M1, and relied on CFD only to estimate parameters such as mean wind speed and turbulent kinetic energy. Using the CFD-computed forces avoids the need for assumptions regarding the flow. We discuss here both the loads on the telescope that lead to image jitter, and the spatially-varying force distribution across the primary mirror, using simulations with the Thirty Meter Telescope (TMT) geometry. The amplitude, temporal spectrum, and spatial distribution of wind disturbances are all estimated; these are then used to compute the resulting image motion and degradation. There are several key differences relative to our earlier parametric model. First, the TMT enclosure provides sufficient wind reduction at the top end (near M2) to render the larger cross-sectional structural areas further inside the enclosure (including M1) significant in determining the overall image jitter. Second, the temporal spectrum is not von Karman as the turbulence is not fully developed; this applies both in predicting image jitter and M1 segment motion. And third, for loads on M1, the spatial characteristics are not consistent with propagating a frozen-flow turbulence screen across the mirror: Frozen flow would result in a relationship between temporal frequency content and spatial frequency content that does not hold in the CFD predictions. Incorporating the new estimates of wind load characteristics
Modeling neuron-glia interactions: from parametric model to neuromorphic hardware.
Ghaderi, Viviane S; Allam, Sushmita L; Ambert, N; Bouteiller, J-M C; Choma, J; Berger, T W
2011-01-01
Recent experimental evidence suggests that glial cells are more than just supporting cells to neurons - they play an active role in signal transmission in the brain. We herein propose to investigate the importance of these mechanisms and model neuron-glia interactions at synapses using three approaches: A parametric model that takes into account the underlying mechanisms of the physiological system, a non-parametric model that extracts its input-output properties, and an ultra-low power, fast processing, neuromorphic hardware model. We use the EONS (Elementary Objects of the Nervous System) platform, a highly elaborate synaptic modeling platform to investigate the influence of astrocytic glutamate transporters on postsynaptic responses in the detailed micro-environment of a tri-partite synapse. The simulation results obtained using EONS are then used to build a non-parametric model that captures the essential features of glutamate dynamics. The structure of the non-parametric model we use is specifically designed for efficient hardware implementation using ultra-low power subthreshold CMOS building blocks. The utilization of the approach described allows us to build large-scale models of neuron/glial interaction and consequently provide useful insights on glial modulation during normal and pathological neural function. PMID:22255113
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.
Surface differentiation by parametric modeling of infrared intensity scans
NASA Astrophysics Data System (ADS)
Aytac, Tayfun; Barshan, Billur
2005-06-01
We differentiate surfaces with different properties with simple low-cost IR emitters and detectors in a location-invariant manner. The intensity readings obtained with such sensors are highly dependent on the location and properties of the surface, which complicates the differentiation and localization process. Our approach, which models IR intensity scans parametrically, can distinguish different surfaces independent of their positions. Once the surface type is identified, its position (r,θ) can also be estimated. The method is verified experimentally with wood; Styrofoam packaging material; white painted matte wall; white and black cloth; and white, brown, and violet paper. A correct differentiation rate of 100% is achieved for six surfaces, and the surfaces are localized within absolute range and azimuth errors of 0.2 cm and 1.1 deg, respectively. The differentiation rate decreases to 86% for seven surfaces and to 73% for eight surfaces. The method demonstrated shows that simple IR sensors, when coupled with appropriate signal processing, can be used to recognize different types of surfaces in a location-invariant manner.
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. PMID:20550249
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. PMID:22779493
A versatile design for resonant guided-wave parametric down-conversion sources for quantum repeaters
NASA Astrophysics Data System (ADS)
Brecht, Benjamin; Luo, Kai-Hong; Herrmann, Harald; Silberhorn, Christine
2016-05-01
Quantum repeaters—fundamental building blocks for long-distance quantum communication—are based on the interaction between photons and quantum memories. The photons must fulfil stringent requirements on central frequency, spectral bandwidth and purity in order for this interaction to be efficient. We present a design scheme for monolithically integrated resonant photon-pair sources based on parametric down-conversion in nonlinear waveguides, which facilitate the generation of such photons. We investigate the impact of different design parameters on the performance of our source. The generated photon spectral bandwidths can be varied between several tens of MHz up to around 1 GHz, facilitating an efficient coupling to different memories. The central frequency of the generated photons can be coarsely tuned by adjusting the pump frequency, poling period and sample temperature, and we identify stability requirements on the pump laser and sample temperature that can be readily fulfilled with off-the-shelf components. We find that our source is capable of generating high-purity photons over a wide range of photon bandwidths. Finally, the PDC emission can be frequency fine-tuned over several GHz by simultaneously adjusting the sample temperature and pump frequency. We conclude our study with demonstrating the adaptability of our source to different quantum memories.
Modeling the evolution of infrared galaxies: a parametric backward evolution model
NASA Astrophysics Data System (ADS)
Béthermin, M.; Dole, H.; Lagache, G.; Le Borgne, D.; Penin, A.
2011-05-01
Aims: We attempt to model the infrared galaxy evolution in as simple a way as possible and reproduce statistical properties such as the number counts between 15 μm and 1.1 mm, the luminosity functions, and the redshift distributions. We then use the fitted model to interpret observations from Spitzer, AKARI, BLAST, LABOCA, AzTEC, SPT, and Herschel, and make predictions for Planck and future experiments such as CCAT or SPICA. Methods: This model uses an evolution in density and luminosity of the luminosity function parametrized by broken power-laws with two breaks at redshift ~0.9 and 2, and contains the two populations of the Lagache model: normal and starburst galaxies. We also take into account the effect of the strong lensing of high-redshift sub-millimeter galaxies. This effect is significant in the sub-mm and mm range near 50 mJy. It has 13 free parameters and eight additional calibration parameters. We fit the parameters to the IRAS, Spitzer, Herschel, and AzTEC measurements with a Monte Carlo Markov chain. Results: The model adjusted to deep counts at key wavelengths reproduces the counts from mid-infrared to millimeter wavelengths, as well as the mid-infrared luminosity functions. We discuss the contribution to both the cosmic infrared background (CIB) and the infrared luminosity density of the different populations. We also estimate the effect of the lensing on the number counts, and discuss the discovery by the South Pole Telescope (SPT) of a very bright population lying at high redshift. We predict the contribution of the lensed sources to the Planck number counts, the confusion level for future missions using a P(D) formalism, and the Universe opacity to TeV photons caused by the CIB. Material of the model (software, tables and predictions) is available online.
NASA Astrophysics Data System (ADS)
Meinke, I.
2003-04-01
A new method is presented to validate cloud parametrization schemes in numerical atmospheric models with satellite data of scanning radiometers. This method is applied to the regional atmospheric model HRM (High Resolution Regional Model) using satellite data from ISCCP (International Satellite Cloud Climatology Project). Due to the limited reliability of former validations there has been a need for developing a new validation method: Up to now differences between simulated and measured cloud properties are mostly declared as deficiencies of the cloud parametrization scheme without further investigation. Other uncertainties connected with the model or with the measurements have not been taken into account. Therefore changes in the cloud parametrization scheme based on such kind of validations might not be realistic. The new method estimates uncertainties of the model and the measurements. Criteria for comparisons of simulated and measured data are derived to localize deficiencies in the model. For a better specification of these deficiencies simulated clouds are classified regarding their parametrization. With this classification the localized model deficiencies are allocated to a certain parametrization scheme. Applying this method to the regional model HRM the quality of forecasting cloud properties is estimated in detail. The overestimation of simulated clouds in low emissivity heights especially during the night is localized as model deficiency. This is caused by subscale cloudiness. As the simulation of subscale clouds in the regional model HRM is described by a relative humidity parametrization these deficiencies are connected with this parameterization.
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.
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…
Parametric design study of ``mini-generator`` with 6-watt heat source
Schock, A.; Or, C.T.
1995-01-20
The Fairchild study showed that generator designs based on a single 1-watt RHU had very poor thermal efficiencies. At their optimum operating point, more than half of the generated heat was lost through the thermal insulation. This resulted in system efficiency of only 2.2%, compared to 7.2% for current Radioisotope Thermoelectric Generators (RTGs). Moreover, there were serious doubts about the fabricability of the required multicouples, particularly of the series/parallel connections between the large number (900) of thermoelectric legs of very small cross-section (0.21 mm square). All in all, the preceding paper showed that neither JPL`s Power Stick design nor the Fairchild-generated derivatives based on the 1-watt heat source looked promising. The present paper describes a similar parametric study of a mini-generator based on a 6-watt heat source, and compares its performance and fabricability to that of the optimum Power Stick derivative and of the current RTG design for the same mission. {copyright} 1995 {ital American} {ital Institute} {ital of} {ital Physics}
Parametric design study of ``mini-generator'' with 6-watt heat source
NASA Astrophysics Data System (ADS)
Schock, Alfred; Or, Chuen T.
1995-01-01
The Fairchild study showed that generator designs based on a single 1-watt RHU had very poor thermal efficiencies. At their optimum operating point, more than half of the generated heat was lost through the thermal insulation. This resulted in system efficiency of only 2.2%, compared to 7.2% for current Radioisotope Thermoelectric Generators (RTGs). Moreover, there were serious doubts about the fabricability of the required multicouples, particularly of the series/parallel connections between the large number (900) of thermoelectric legs of very small cross-section (0.21 mm square). All in all, the preceding paper showed that neither JPL's Power Stick design nor the Fairchild-generated derivatives based on the 1-watt heat source looked promising. The present paper describes a similar parametric study of a mini-generator based on a 6-watt heat source, and compares its performance and fabricability to that of the optimum Power Stick derivative and of the current RTG design for the same mission.
Parametrization of flavor mixing in the standard model
Fritzsch, H. |; Xing, Z.
1998-01-01
It is shown that there exist nine different ways to describe the flavor mixing, in terms of three rotation angles and one CP-violating phase, within the standard electroweak theory of six quarks. For the assignment of the complex phase there essentially exists a continuum of possibilities, if one allows the phase to appear in more than four elements of the mixing matrix. If the phase is restricted to four elements, the phase assignment is uniquely defined. If one imposes the constraint that the phase disappears in a natural way in the chiral limit in which the masses of the u and d quarks are turned off, only three of the nine parametrizations are acceptable. In particular the {open_quotes}standard{close_quotes} parametrization advocated by the Particle Data Group is not permitted. One parametrization, in which the CP-violating phase is restricted to the light quark sector, stands up as the most favorable description of the flavor mixing. {copyright} {ital 1997} {ital The American Physical Society}
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.
Accelerated Hazards Model based on Parametric Families Generalized with Bernstein Polynomials
Chen, Yuhui; Hanson, Timothy; Zhang, Jiajia
2015-01-01
Summary A transformed Bernstein polynomial that is centered at standard parametric families, such as Weibull or log-logistic, is proposed for use in the accelerated hazards model. This class provides a convenient way towards creating a Bayesian non-parametric prior for smooth densities, blending the merits of parametric and non-parametric methods, that is amenable to standard estimation approaches. For example optimization methods in SAS or R can yield the posterior mode and asymptotic covariance matrix. This novel nonparametric prior is employed in the accelerated hazards model, which is further generalized to time-dependent covariates. The proposed approach fares considerably better than previous approaches in simulations; data on the effectiveness of biodegradable carmustine polymers on recurrent brain malignant gliomas is investigated. PMID:24261450
NASA Astrophysics Data System (ADS)
Ahlrichs, Andreas; Benson, Oliver
2016-01-01
We present a bright, simple-to-setup, single-mode source of indistinguishable photon pairs at the cesium D1-line with a bandwidth of about 100 MHz. The source is based on degenerate, cavity enhanced spontaneous parametric down-conversion utilizing the cluster effect. The setup relies on a microcontroller-based digital locking system. A brightness of 1.1 ×103/(s m W ) detected, indistinguishable photon pairs could be measured.
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
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. PMID:25698012
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
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. PMID:16060510
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
Adaptivity Assessment of Regional Semi-Parametric VTEC Modeling to Different Data Distributions
NASA Astrophysics Data System (ADS)
Durmaz, Murat; Onur Karslıoǧlu, Mahmut
2014-05-01
Semi-parametric modelling of Vertical Total Electron Content (VTEC) combines parametric and non-parametric models into a single regression model for estimating the parameters and functions from Global Positioning System (GPS) observations. The parametric part is related to the Differential Code Biases (DCBs), which are fixed unknown parameters of the geometry-free linear combination (or the so called ionospheric observable). On the other hand, the non-parametric component is referred to the spatio-temporal distribution of VTEC which is estimated by applying the method of Multivariate Adaptive Regression B-Splines (BMARS). BMARS algorithm builds an adaptive model by using tensor product of univariate B-splines that are derived from the data. The algorithm searches for best fitting B-spline basis functions in a scale by scale strategy, where it starts adding large scale B-splines to the model and adaptively decreases the scale for including smaller scale features through a modified Gram-Schmidt ortho-normalization process. Then, the algorithm is extended to include the receiver DCBs where the estimates of the receiver DCBs and the spatio-temporal VTEC distribution can be obtained together in an adaptive semi-parametric model. In this work, the adaptivity of regional semi-parametric modelling of VTEC based on BMARS is assessed in different ground-station and data distribution scenarios. To evaluate the level of adaptivity the resulting DCBs and VTEC maps from different scenarios are compared not only with each other but also with CODE distributed GIMs and DCB estimates .
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
Applying Statistical Models and Parametric Distance Measures for Music Similarity Search
NASA Astrophysics Data System (ADS)
Lukashevich, Hanna; Dittmar, Christian; Bastuck, Christoph
Automatic deriving of similarity relations between music pieces is an inherent field of music information retrieval research. Due to the nearly unrestricted amount of musical data, the real-world similarity search algorithms have to be highly efficient and scalable. The possible solution is to represent each music excerpt with a statistical model (ex. Gaussian mixture model) and thus to reduce the computational costs by applying the parametric distance measures between the models. In this paper we discuss the combinations of applying different parametric modelling techniques and distance measures and weigh the benefits of each one against the others.
Tang, Wan; Lu, Naiji; Chen, Tian; Wang, Wenjuan; Gunzler, Douglas David; Han, Yu; Tu, Xin M
2015-10-30
Zero-inflated Poisson (ZIP) and negative binomial (ZINB) models are widely used to model zero-inflated count responses. These models extend the Poisson and negative binomial (NB) to address excessive zeros in the count response. By adding a degenerate distribution centered at 0 and interpreting it as describing a non-risk group in the population, the ZIP (ZINB) models a two-component population mixture. As in applications of Poisson and NB, the key difference between ZIP and ZINB is the allowance for overdispersion by the ZINB in its NB component in modeling the count response for the at-risk group. Overdispersion arising in practice too often does not follow the NB, and applications of ZINB to such data yield invalid inference. If sources of overdispersion are known, other parametric models may be used to directly model the overdispersion. Such models too are subject to assumed distributions. Further, this approach may not be applicable if information about the sources of overdispersion is unavailable. In this paper, we propose a distribution-free alternative and compare its performance with these popular parametric models as well as a moment-based approach proposed by Yu et al. [Statistics in Medicine 2013; 32: 2390-2405]. Like the generalized estimating equations, the proposed approach requires no elaborate distribution assumptions. Compared with the approach of Yu et al., it is more robust to overdispersed zero-inflated responses. We illustrate our approach with both simulated and real study data. PMID:26078035
The impact of impervious water-storage parametrization on urban climate modelling
NASA Astrophysics Data System (ADS)
Wouters, Hendrik; Demuzere, Matthias; De Ridder, Koen; van Lipzig, Nicole
2015-04-01
In order to improve the representation of the water balance in urban land-surface models, we present a new impervious water-storage parametrization that assumes a distribution of water reservoirs. It has been implemented in TERRA-URB, a new urban parametrization for COSMO-CLM's standard land-surface module TERRA-ML. The water-storage capacity and the maximal wet surface fraction of the urban impervious land cover consisting of streets and buildings are estimated for Toulouse centre by matching the modelled and observed evapotranspiration (ET) rates. They amount to 1.31 ± 0.20 kg m-2} and 12 ± 4%, respectively. The model successfully reproduces the timespan and magnitude of increased ET for both urban observations campaigns CAPITOUL and BUBBLE. Our sensitivity study reveals that water-storage parametrization largely affects the performance of modelled ET rates. Hereby, the simulation employing the new water-storage parametrization is improved compared to arbitrary or existing water-storage parametrizations. The ET, surface sensible heat exchange and upwelling infra-red radiation are all affected until 12 day-time hours after rainfall on average. The modelled annual-mean ET during the CAPITOUL campaign from the urban land in Toulouse is an order of magnitude lower than that observed for the natural surroundings.
An autoregressive point source model for spatial processes
Hughes-Oliver, Jacqueline M.; Heo, Tae-Young; Ghosh, Sujit K.
2009-01-01
We suggest a parametric modeling approach for nonstationary spatial processes driven by point sources. Baseline near-stationarity, which may be reasonable in the absence of a point source, is modeled using a conditional autoregressive (CAR) Markov random field. Variability due to the point source is captured by our proposed autoregressive point source (ARPS) model. Inference proceeds according to the Bayesian hierarchical paradigm, and is implemented using Markov chain Monte Carlo (MCMC) methods. The parametric approach allows a formal test of effectiveness of the point source. Application is made to a real dataset on electric potential measurements in a field containing a metal pole and the finding is that our approach captures the pole’s impact on small-scale variability of the electric potential process. PMID:19936263
Choosing a 'best' global aerosol model: Can observations constrain parametric uncertainty?
NASA Astrophysics Data System (ADS)
Browse, Jo; Reddington, Carly; Pringle, Kirsty; Regayre, Leighton; Lee, Lindsay; Schmidt, Anja; Field, Paul; Carslaw, Kenneth
2015-04-01
Anthropogenic aerosol has been shown to contribute to climate change via direct radiative forcing and cloud-aerosol interactions. While the role of aerosol as a climate agent is likely to diminish as CO2 emissions increase, recent studies suggest that uncertainty in modelled aerosol is likely to dominate uncertainty in future forcing projections. Uncertainty in modelled aerosol derives from uncertainty in the representation of emissions and aerosol processes (parametric uncertainty) as well as structural error. Here we utilise Latin hyper-cube sampling methods to produce an ensemble model (composed of 280 runs) of a global model of aerosol processes (GLOMAP) spanning 31 parametric ranges. Using an unprecedented number of observations made available by the GASSP project we have evaluated our ensemble model against a multi-variable (CCN, BC mass, PM2.5) data-set to determine if 'an ideal' aerosol model exists. Ignoring structural errors, optimization of a global model against multiple data-sets to within a factor of 2 is possible, with multiple model runs identified. However, (even regionally) the parametric range of our 'best' model runs is very wide with the same model skill arising from multiple parameter settings. Our results suggest that 'traditional' in-situ measurements are insufficient to constrain parametric uncertainty. Thus, to constrain aerosol in climate models, future evaluations must include process based observations.
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
NASA Astrophysics Data System (ADS)
Vu, H. X.; Bezzerides, B.; Dubois, D. F.
1998-11-01
A fully kinetic, reduced-description particle-in-cell (RPIC) model is presented in which deviations from quasineutrality, electron and ion kinetic effects, and nonlinear interactions between low-frequency and high-frequency parametric instabilities are modeled correctly. The model is based on a reduced description where the electromagnetic field is represented by three separate temporal WKB envelopes in order to model low-frequency and high-frequency parametric instabilities. Because temporal WKB approximations are invoked, the simulation can be performed on the electron time scale instead of the time scale of the light waves. The electrons and ions are represented by discrete finite-size particles, permitting electron and ion kinetic effects to be modeled properly. The Poisson equation is utilized to ensure that space-charge effects are included. Although RPIC is fully three dimensional, it has been implemented in only two dimensions on a CRAY-T3D with 512 processors and on the Accelerated Strategic Computing Initiative (ASCI) parallel computer at Los Alamos National Laboratory, and the resulting simulation code has been named ASPEN. Given the current computers available to the authors, one and two dimensional simulations are feasible to, and have been, performed. Three dimensional simulations are much more expensive, and are not feasible at this time. However, with rapidly advancing computer technologies, three dimensional simulations may be feasible in the near future. We believe this code is the first PIC code capable of simulating the interaction between low-frequency and high-frequency parametric instabilites in multiple dimensions. Test simulations of stimulated Raman scattering (SRS), stimulated Brillouin scattering (SBS), and Langmuir decay instability (LDI), are presented.
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.
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.
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…
Theoretical models proposed to date have been unable to clearly predict expected biological results from exposure to low intensity electric and magnetic fields (EMF). n this paper we clarify a heuristic ion parametric resonance (IPR) model that describes the expected forms of res...
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.
NASA Astrophysics Data System (ADS)
Palacio, Carlos; Camacho, Gonzalo; García-Rodríguez, Carlos
2015-12-01
The extraction of concentration depth profiles from ARXPS data has been carried out using noisy simulated data and two different approaches, using either simple parametric models or general algorithms with Tikhonov regularization schemes. Among the single parametric models the only one that is stable and robust against noise is that using only one parameter, with the uncertainty of the parameter displaying a linear dependence on the input noise level. For Tikhonov regularization schemes, a guide is given to choose the appropriate regularization parameter, which is based on the use of the S-curve in conjunction with the constraints introduced by χ2, and which provides user-independent results.
Formation of parametric images using mixed-effects models: a feasibility study.
Huang, Husan-Ming; Shih, Yi-Yu; Lin, Chieh
2016-03-01
Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26915793
Shafieloo, Arman
2012-05-01
By introducing Crossing functions and hyper-parameters I show that the Bayesian interpretation of the Crossing Statistics [1] can be used trivially for the purpose of model selection among cosmological models. In this approach to falsify a cosmological model there is no need to compare it with other models or assume any particular form of parametrization for the cosmological quantities like luminosity distance, Hubble parameter or equation of state of dark energy. Instead, hyper-parameters of Crossing functions perform as discriminators between correct and wrong models. Using this approach one can falsify any assumed cosmological model without putting priors on the underlying actual model of the universe and its parameters, hence the issue of dark energy parametrization is resolved. It will be also shown that the sensitivity of the method to the intrinsic dispersion of the data is small that is another important characteristic of the method in testing cosmological models dealing with data with high uncertainties.
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.
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.
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. PMID:27089276
Can we construct back parametrizations of a given model structure using large sample hydrology?
NASA Astrophysics Data System (ADS)
Gharari, Shervan; Gupta, Hoshin; Hrachowitz, Markus; Fenicia, Fabrizio; Savenije, Hubert
2015-04-01
A unified strategy for measurement of information content in hierarchal model building seems lacking. Firstly the model structure is built by its building blocks (control volumes or state variables) as well as interconnecting fluxes (formation of control volumes and fluxes). Secondly, parameterizations of model are designed, as an example the effect of a specific type of stage-discharge relation for a control volume can be explored. At the final stage the parameter values are quantified. In each step and based on assumptions made, more and more information is added to the model. In this study we try to relax our assumption of shape of parameterization. We try to construct parametrizations of a hydrological model, by relaxing the assumptions, given a specific model structure and various forcing data from different catchments across various climatic conditions. This study helps us to find out whether there is a general pattern exist for parametrization of a given model structure.
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. PMID:26847949
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.
PARAMETRIC MODEL FOR CONSTITUTIVE PROPERTIES GOVERNING MULTIPHASE FLOW IN POROUS MEDIA
A parametric model is developed to describe relative permeability-saturation-fluid pressure functional relationships in two- or three-fluid phase porous media systems subject to monotonic saturation paths. All functions are obtained as simple closed-form expressions convenient fo...
EMPIRICAL TEST OF AN ION PARAMETRIC RESONANCE MODEL FOR MAGNETIC FIELD INTERACTIONS WITH PC-12 CELLS
A companion paper [Blanchard and B 19931 describes a predictive heuristic ion parametric resonance (IPR) model of magnetic field interactions with biological systems based on a selective relation between the ratio of the static magnetic field to the frequency of the AC magnetic f...
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. PMID:25524862
Moore, Julia L; Remais, Justin V
2014-03-01
Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and non-linear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear versus non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development. PMID:24443079
PARAMETRIC METHODOLOGIES OF CLOUD VERTICAL TRANSPORT FOR ACID DEPOSITION MODELS
A CUmulus VENTing (CUVENT) cloud module has been developed that calculates the vertical flux of mass from the boundary layer to the cloud layer by an ensemble of nonprecipitating subgrid-scale air mass clouds. This model will be integrated into the Regional Acid Deposition Model ...
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.
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.
Parametric reduced models for the nonlinear Schrödinger equation
NASA Astrophysics Data System (ADS)
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.
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.
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.
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
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.
Self-phase-locked divide-by-2 optical parametric oscillator as a broadband frequency comb source
NASA Astrophysics Data System (ADS)
Wong, S.; Plettner, T.; Vodopyanov, K. L.; Byer, R. L.
2009-02-01
We investigate coherence properties of a degenerate synchronously-pumped optical parametric oscillator (SPOPO) as a divide-by-2 subharmonic generator. Type 0 (e-ee) periodically-poled MgO : LiNbO3 was used as a nonlinear gain crystal and a femtosecond mode-locked Ti:Sapphire laser at 775 nm - as a pump source. We observed that the SPOPO longitudinal modes at degeneracy were phase-coherent with that of the pump. The self-phase-locking and self-stabilization effect can be explained in terms of mutual injection locking between the signal and the idler frequencies of the SPOPO. We confirmed the phase-locking effect by performing interference between pump and frequency-doubled output, as well as beat frequency measurements between the SPOPO output and (i) the pump laser and (ii) an independent continuous-wave (CW) laser. A frequency locking range around SPOPO degeneracy Δf was measured as a function of pump power, when the SPOPO operated in the phase-locking regime. We have found that Δf increased monotonically with the pump power and decreased with the cavity Q, in good accord with our theoretical model based on coupled nonlinear optical wave equations. When the proper regime was chosen, the SPOPO remained phase-locked to the pump without any active stabilization even in the presence of environmental noise. At degeneracy (around 1550 nm), the SPOPO produced 70-fs output pulses with the FWHM spectral width of 210 cm-1 that is 2.6 times broader than the spectrum of the pump laser.
Dahan, David; Shumakher, Evgeny; Eisenstein, Gadi
2005-07-01
A self-starting optical pulse source based on mutually coupled optoelectronic oscillators is described. The system employs a phototransistor-based microwave oscillator that is coupled to a fiber cavity optoelectronic oscillator with an intracavity fiber parametric amplifier. It self-starts and exhibits 3 ps pulses at a rate of 10 GHz with extremely low jitter of 30, 29, and 40 fs (for integration bandwidths of 100 Hz-15 kHz, 500 Hz-1 MHz, and 100 Hz-1 MHz, respectively). PMID:16075517
Testing goodness of fit of parametric models for censored data.
Nysen, Ruth; Aerts, Marc; Faes, Christel
2012-09-20
We propose and study a goodness-of-fit test for left-censored, right-censored, and interval-censored data assuming random censorship. Main motivation comes from dietary exposure assessment in chemical risk assessment, where the determination of an appropriate distribution for concentration data is of major importance. We base the new goodness-of-fit test procedure proposed in this paper on the order selection test. As part of the testing procedure, we extend the null model to a series of nested alternative models for censored data. Then, we use a modified AIC model selection to select the best model to describe the data. If a model with one or more extra parameters is selected, then we reject the null hypothesis. As an alternative to the use of the asymptotic null distribution of the test statistic, we define a bootstrap-based procedure. We illustrate the applicability of the test procedure on data of cadmium concentrations and on data from the Signal Tandmobiel study and demonstrate its performance characteristics through simulation studies. PMID:22714389
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. PMID:23716678
Parametric modelling of temporal variations in radon concentrations in homes
Revzan, K.L.; Turk, B.H.; Harrison, J.; Nero, A.V.; Sextro, R.G.
1988-01-01
The /sup 222/Rn concentrations in the living area, the basement, and the undelying soil of a New Jersey home have been measured at half-hour intervals over the course of a year, as have indoor and outdoor temperatures, wind speed and direction, and indoor-outdoor and basement-subslab pressures; in addition, periods of furnace opration have been logged. We generalize and extend an existing radon entry model in order to demonstrate the dependence of the radon concentration on the environmental variales and the extent of furnace use. The model contains parameters which are dependent on geological and structural factors which have not been measured or otherwise determined; statistical methods are used to find the best values of the parameters. The non-linear regression of the model predictions (over time) on the measured living area radon concentrations yields an R)aup 2) of 0.88. 9 refs., 2 figs
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.
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.
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
Peña, Edsel A.
2014-01-01
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. PMID:25346751
Derraz, Foued; Forzy, Gérard; Delebarre, Arnaud; Taleb-Ahmed, Abdelmalik; Oussalah, Mourad; Peyrodie, Laurent; Verclytte, Sebastien
2015-11-01
Prostate contours delineation on Magnetic Resonance (MR) images is a challenging and important task in medical imaging with applications of guiding biopsy, surgery and therapy. While a fully automated method is highly desired for this application, it can be a very difficult task due to the structure and surrounding tissues of the prostate gland. Traditional active contours-based delineation algorithms are typically quite successful for piecewise constant images. Nevertheless, when MR images have diffuse edges or multiple similar objects (e.g. bladder close to prostate) within close proximity, such approaches have proven to be unsuccessful. In order to mitigate these problems, we proposed a new framework for bi-stage contours delineation algorithm based on directional active contours (DAC) incorporating prior knowledge of the prostate shape. We first explicitly addressed the prostate contour delineation problem based on fast globally DAC that incorporates both statistical and parametric shape prior model. In doing so, we were able to exploit the global aspects of contour delineation problem by incorporating a user feedback in contours delineation process where it is shown that only a small amount of user input can sometimes resolve ambiguous scenarios raised by DAC. In addition, once the prostate contours have been delineated, a cost functional is designed to incorporate both user feedback interaction and the parametric shape prior model. Using data from publicly available prostate MR datasets, which includes several challenging clinical datasets, we highlighted the effectiveness and the capability of the proposed algorithm. Besides, the algorithm has been compared with several state-of-the-art methods. PMID:26009857
Bayesian parametrization of coarse-grain dissipative dynamics models
NASA Astrophysics Data System (ADS)
Dequidt, Alain; Solano Canchaya, Jose G.
2015-08-01
We introduce a new bottom-up method for the optimization of dissipative coarse-grain models. The method is based on Bayesian optimization of the likelihood to reproduce a coarse-grained reference trajectory obtained from analysis of a higher resolution molecular dynamics trajectory. This new method is related to force matching techniques, but using the total force on each grain averaged on a coarse time step instead of instantaneous forces. It has the advantage of not being limited to pairwise short-range interactions in the coarse-grain model and also yields an estimation of the friction parameter controlling the dynamics. The theory supporting the method is exposed in a practical perspective, with an analytical solution for the optimal set of parameters. The method was first validated by using it on a system with a known optimum. The new method was then tested on a simple system: n-pentane. The local molecular structure of the optimized model is in excellent agreement with the reference system. An extension of the method allows to get also an excellent agreement for the equilibrium density. As for the dynamic properties, they are also very satisfactory, but more sensitive to the choice of the coarse-grain representation. The quality of the final force field depends on the definition of the coarse grain degrees of freedom and interactions. We consider this method as a serious alternative to other methods like iterative Boltzmann inversion, force matching, and Green-Kubo formulae.
Spectrally pure RF photonic source based on a resonant optical hyper-parametric oscillator
NASA Astrophysics Data System (ADS)
Liang, W.; Eliyahu, D.; Matsko, A. B.; Ilchenko, V. S.; Seidel, D.; Maleki, L.
2014-03-01
We demonstrate a free running 10 GHz microresonator-based RF photonic hyper-parametric oscillator characterized with phase noise better than -60 dBc/Hz at 10 Hz, -90 dBc/Hz at 100 Hz, and -150 dBc/Hz at 10 MHz. The device consumes less than 25 mW of optical power. A correlation between the frequency of the continuous wave laser pumping the nonlinear resonator and the generated RF frequency is confirmed. The performance of the device is compared with the performance of a standard optical fiber based coupled opto-electronic oscillator of OEwaves.
Fitting of Parametric Building Models to Oblique Aerial Images
NASA Astrophysics Data System (ADS)
Panday, U. S.; Gerke, M.
2011-09-01
In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS) data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of - 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for completeness of
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. PMID:24402904
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.
A new steerable pressure force for parametric deformable models
NASA Astrophysics Data System (ADS)
Kong, Jun; Cooper, Lee; Sharma, Ashish; Kurc, Tahsin; Brat, Daniel; Saltz, Joel
2011-03-01
Active contour models have been widely used in various image analysis applications. Despite their usefulness, there are problems limiting their utility, such as capture range, concavity conformation, and convergence rate. This paper presents a new pressure-like force that not only improves contour convergence rate, but also encourages contours to conform to concave regions. Unlike the traditional pressure force, this new force does not require users' input for the force direction and is steerable according to the image content. Better convergence rate as well as force normalization consistency of this new force are presented when compared with those of the gradient vector flow force field on synthetic images. Accuracies of these two methods are compared against the manual markups on a set of cardiac MRI images. Moreover, results on a MRI image smoothed at different levels demonstrate the robustness of this new force to noise.
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%. PMID:23338203
Towards the generation of a parametric foot model using principal component analysis: A pilot study.
Scarton, Alessandra; Sawacha, Zimi; Cobelli, Claudio; Li, Xinshan
2016-06-01
There have been many recent developments in patient-specific models with their potential to provide more information on the human pathophysiology and the increase in computational power. However they are not yet successfully applied in a clinical setting. One of the main challenges is the time required for mesh creation, which is difficult to automate. The development of parametric models by means of the Principle Component Analysis (PCA) represents an appealing solution. In this study PCA has been applied to the feet of a small cohort of diabetic and healthy subjects, in order to evaluate the possibility of developing parametric foot models, and to use them to identify variations and similarities between the two populations. Both the skin and the first metatarsal bones have been examined. Besides the reduced sample of subjects considered in the analysis, results demonstrated that the method adopted herein constitutes a first step towards the realization of a parametric foot models for biomechanical analysis. Furthermore the study showed that the methodology can successfully describe features in the foot, and evaluate differences in the shape of healthy and diabetic subjects. PMID:27068864
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.
Modeling parametric scattering instabilities in large-scale expanding plasmas
NASA Astrophysics Data System (ADS)
Masson-Laborde, P. E.; Hüller, S.; Pesme, D.; Casanova, M.; Loiseau, P.; Labaune, Ch.
2006-06-01
We present results from two-dimensional simulations of long scale-length laser-plasma interaction experiments performed at LULI. With the goal of predictive modeling of such experiments with our code Harmony2D, we take into account realistic plasma density and velocity profiles, the propagation of the laser light beam and the scattered light, as well as the coupling with the ion acoustic waves in order to describe Stimulated Brillouin Scattering (SBS). Laser pulse shaping is taken into account to follow the evolution ofthe SBS reflectivity as close as possible to the experiment. The light reflectivity is analyzed by distinguishing the backscattered light confined in the solid angle defined by the aperture of the incident light beam and the scattered light outside this cone. As in the experiment, it is observed that the aperture of the scattered light tends to increase with the mean intensity of the RPP-smoothed laser beam. A further common feature between simulations and experiments is the observed localization of the SBS-driven ion acoustic waves (IAW) in the front part of the target (with respect to the incoming laser beam).
Classification performance prediction using parametric scattering feature models
NASA Astrophysics Data System (ADS)
Chiang, Hung-Chih; Moses, Randolph L.; Potter, Lee C.
2000-08-01
We consider a method for estimating classification performance of a model-based synthetic aperture radar (SAR) automatic target recognition system. Target classification is performed by comparing an unordered feature set extracted from a measured SAR image chip with an unordered feature set predicted from a hypothesized target class and pose. A Bayes likelihood metric that incorporates uncertainty in both the predicted and extracted feature vectors is used to compute the match score. Evaluation of the match likelihoods requires a correspondence between the unordered predicted and extracted feature sets. This is a bipartite graph matching problem with insertions and deletions; we show that the optimal match can be found in polynomial time. We extend the results in 1 to estimate classification performance for a ten-class SAR ATR problem. We consider a synthetic classification problem to validate the classifier and to address resolution and robustness questions in the likelihood scoring method. Specifically, we consider performance versus SAR resolution, performance degradation due to mismatch between the assumed and actual feature statistics, and performance impact of correlated feature attributes.
Modeling of PT-systems based on Optical Parametric Amplification and Stimulated Raman Scattering
NASA Astrophysics Data System (ADS)
Sukhinin, Alexey; Litchinitser, Natalia
2016-05-01
Most of the research on PT-materials has been performed with the premise that the gain of the system is based on the amplitude-independent or linear amplification mechanisms. In this talk, I will discuss the theoretical model that includes nonlinear optical effects such as Optical Parametric Amplification and Stimulated Raman Scattering to realize larger optical gain. This setup could lead to a build-up of the next generation of PT-materials.
Parametric Studies and Optimization of Eddy Current Techniques through Computer Modeling
Todorov, E. I.
2007-03-21
The paper demonstrates the use of computer models for parametric studies and optimization of surface and subsurface eddy current techniques. The study with high-frequency probe investigates the effect of eddy current frequency and probe shape on the detectability of flaws in the steel substrate. The low-frequency sliding probe study addresses the effect of conductivity between the fastener and the hole, frequency and coil separation distance on detectability of flaws in subsurface layers.
NASA Astrophysics Data System (ADS)
Song, Guo-Zhu; Wu, Fang-Zhou; Zhang, Mei; Yang, Guo-Jian
2016-06-01
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.
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
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
Jiang Zhu; Yong X. Tao
2011-11-01
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.
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. PMID:25309338
NASA Astrophysics Data System (ADS)
Saffin, Leo; Methven, John; Gray, Sue
2016-04-01
Numerical models of the atmosphere combine a dynamical core, which approximates solutions to the adiabatic and frictionless governing equations, with the tendencies arising from the parametrization of physical processes. Tracers of potential vorticity (PV) can be used to accumulate the tendencies of parametrized physical processes and diagnose their impacts on the large-scale dynamics. This is due to two key properties of PV, conservation following an air mass and invertibility which relates the PV distribution to the balanced dynamics of the atmosphere. Applying the PV tracers to many short forecasts allows for a systematic investigation of the behaviour of parametrized physical processes. The forecasts are 2.5 day lead time forecasts run using the Met Office Unified Model (MetUM) initialised at 0Z for each day in November/December/January 2013/14. The analysis of the PV tracers has been focussed on regions where diabatic processes can be important (tropopause ridges and troughs, frontal regions and the boundary layer top). The tropopause can be described as a surface of constant PV with a sharp PV gradient. Previous work using the PV tracers in individual case studies has shown that parametrized physical processes act to enhance the tropopause PV contrast which can affect the Rossby wave phase speed. The short forecasts show results consistent with a systematic enhancement of tropopause PV contrast by diabatic processes and show systematically different behaviour between ridges and troughs. The implication of this work is that a failure to correctly represent the effects of diabatic processes on the tropopause in models can lead to poor Rossby wave evolution and potentially downstream forecast busts.
Deng, Jie; Jin, Ning; Yin, Xiaoming; Yang, Guang-Yu; Zhang, Zhuoli; Omary, Reed A.; Larson, Andrew C.
2010-01-01
PURPOSE To develop a quantitative multi-parametric PROPELLER (periodically rotated overlapping parallel lines with enhanced reconstruction) MRI approach and its application in a diethylnitrosamine (DEN) chemically-induced rodent model of hepatocarcinogensis for lesion characterization. MATERIALS AND METHODS In nine rabbits with 33 cirrhosis-associated hepatic nodules including regenerative nodule (RN), dysplastic nodule (DN), hepatocellular carcinoma (HCC) and cyst, multi-parametric PROPELLER MRI (diffusion-weighted, T2/M0 (proton density) mapping and T1-weighted) were performed. Apparent diffusion coefficient (ADC) maps, T2 and M0 maps of each tumor were generated. We compared ADC, T2 and M0 measurements for each type of hepatic nodule, confirmed at histopathology. RESULTS PROPELLER images and resultant parametric maps were inherently co-registered without image distortion or motion artifacts. All types of hepatic nodules demonstrated complex imaging characteristics within conventional T1- and T2-weighted images. Quantitatively, cysts were distinguished from RN, DN and HCC with significantly higher ADC and T2; however, there was no significant difference of ADC and T2 between HCC, DN and RN. Mean tumor M0 values of HCC were significantly higher than those of DN, RN and cysts. CONCLUSION This study exploited quantitative PROPELLER MRI and multi-dimensional analysis approaches in an attempt to differentiate hepatic nodules in the DEN rodent model of hepatocarcinogensis. This method offers great potential for parallel parameterization during non-invasive interrogation of hepatic tissue properties. PMID:20432363
Yu, Jintao; Liang, Yi; Thompson, Simon; Cull, Grant; Wang, Lin
2014-01-01
The aim of the study was to establish a parametric transfer function to describe the relationship between ocular perfusion pressure (OPP) and blood flow (BF) in the optic nerve head (ONH). A third-order parametric theoretical model was proposed to describe the ONH OPP-BF relationship within the lower OPP range of the autoregulation curve (< 80 mmHg) based on experimentally induced BF response to a rapid intraocular pressure (IOP) increase in 6 rhesus monkeys. The theoretical and actual data fitted well and suggest that this parametric third-order transfer function can effectively describe both the linear and nonlinear feature in dynamic and static autoregulation in the ONH within the OPP range studied. It shows that the BF autoregulation fully functions when the OPP was > 40 mmHg and becomes incomplete when the OPP was < 40 mmHg. This model may be used to help investigating the features of autoregulation in the ONH under different experimental conditions. PMID:24665355
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.
The Parametric Model of the Human Mandible Coronoid Process Created by Method of Anatomical Features
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. PMID:26064183
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
Dynamical many-body phases of the parametrically driven, dissipative Dicke model
NASA Astrophysics Data System (ADS)
Chitra, R.; Zilberberg, O.
2015-08-01
Control and manipulation of quantum engineered systems allows for the utilization of time-dependent parametric modulations for accessing novel out-of-equilibrium phenomena. In the absence of such driving, the dissipative Dicke model exhibits a fascinating out-of-equilibrium many-body phase transition as a function of a coupling between a driven photonic cavity and numerous two-level atoms. We study the effect of a parametric modulation of this coupling and discover a rich phase diagram as a function of the modulation strength. We find that in addition to the established normal and super-radiant phases, a new phase with pulsed superradiance, which we term dynamical normal phase, appears when the system is parametrically driven. Employing different methods, we characterize the different phases and the transitions between them. Specific heed is paid to the role of dissipation in determining the phase boundaries. Our analysis paves the road for the experimental study of dynamically stabilized phases of interacting light and matter.
Finding parametric representations of the cortical sulci using an active contour model.
Vaillant, M; Davatzikos, C
1997-09-01
The cortical sulci are brain structures resembling thin convoluted ribbons embedded in three dimensions. The importance of the sulci lies primarily in their relation to the cytoarchitectonic and functional organization of the underlying cortex and in their utilization as features in non-rigid registration methods. This paper presents a methodology for extracting parametric representations of the cerebral sulcus from magnetic resonance images. The proposed methodology is based on deformable models utilizing characteristics of the cortical shape. Specifically, a parametric representation of a sulcus is determined by the motion of an active contour along the medial surface of the corresponding cortical fold. The active contour is initialized along the outer boundary of the brain and deforms toward the deep root of a sulcus under the influence of an external force field, restricting it to lie along the medial surface of the particular cortical fold. A parametric representation of the medial surface of the sulcus is obtained as the active contour traverses the sulcus. Based on the first fundamental form of this representation, the location and degree of an interruption of a sulcus can be readily quantified; based on its second fundamental form, shape properties of the sulcus can be determined. This methodology is tested on magnetic resonance images and it is applied to three medical imaging problems: quantitative morphological analysis of the central sulcus; mapping of functional activation along the primary motor cortex and non-rigid registration of brain images. PMID:9873912
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.
Low Dimensional Models of Shell Vibrations. Parametrically Excited Vibrations of Cylinder Shells
NASA Astrophysics Data System (ADS)
Popov, A. A.; Thompson, J. M. T.; McRobie, F. A.
1998-01-01
Vibrations of cylindrical shells parametrically excited by axial forcing are considered. The governing system of two coupled non-linear partial differential equations is discretized by using Lagrange equations. The computation is simplified significantly by the application of computer algebra and as a result low dimensional models of shell vibrations are readily obtained. After applying numerical continuation techniques and ideas from dynamical systems theory, complete bifurcation diagrams are constructed. The principal aim is to investigate the interaction between different modes of shell vibration. Results for system models with two of the lowest modes are discussed.
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.
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.
A data-driven multi-cloud model for stochastic parametrization of deep convection.
Dorrestijn, J; Crommelin, D T; Biello, J A; Böing, S J
2013-05-28
Stochastic subgrid models have been proposed to capture the missing variability and correct systematic medium-term errors in general circulation models. In particular, the poor representation of subgrid-scale deep convection is a persistent problem that stochastic parametrizations are attempting to correct. In this paper, we construct such a subgrid model using data derived from large-eddy simulations (LESs) of deep convection. We use a data-driven stochastic parametrization methodology to construct a stochastic model describing a finite number of cloud states. Our model emulates, in a computationally inexpensive manner, the deep convection-resolving LES. Transitions between the cloud states are modelled with Markov chains. By conditioning the Markov chains on large-scale variables, we obtain a conditional Markov chain, which reproduces the time evolution of the cloud fractions. Furthermore, we show that the variability and spatial distribution of cloud types produced by the Markov chains become more faithful to the LES data when local spatial coupling is introduced in the subgrid Markov chains. Such spatially coupled Markov chains are equivalent to stochastic cellular automata. PMID:23588052
Application of a hazard-based visual predictive check to evaluate parametric hazard models.
Huh, Yeamin; Hutmacher, Matthew M
2016-02-01
Parametric models used in time to event analyses are evaluated typically by survival-based visual predictive checks (VPC). Kaplan-Meier survival curves for the observed data are compared with those estimated using model-simulated data. Because the derivative of the log of the survival curve is related to the hazard--the typical quantity modeled in parametric analysis--isolation, interpretation and correction of deficiencies in the hazard model determined by inspection of survival-based VPC's is indirect and thus more difficult. The purpose of this study is to assess the performance of nonparametric hazard estimators of hazard functions to evaluate their viability as VPC diagnostics. Histogram-based and kernel-smoothing estimators were evaluated in terms of bias of estimating the hazard for Weibull and bathtub-shape hazard scenarios. After the evaluation of bias, these nonparametric estimators were assessed as a method for VPC evaluation of the hazard model. The results showed that nonparametric hazard estimators performed reasonably at the sample sizes studied with greater bias near the boundaries (time equal to 0 and last observation) as expected. Flexible bandwidth and boundary correction methods reduced these biases. All the nonparametric estimators indicated a misfit of the Weibull model when the true hazard was a bathtub shape. Overall, hazard-based VPC plots enabled more direct interpretation of the VPC results compared to survival-based VPC plots. PMID:26563504
Multi-scale hierarchical approach for parametric mapping: assessment on multi-compartmental models.
Rizzo, G; Turkheimer, F E; Bertoldo, A
2013-02-15
This paper investigates a new hierarchical method to apply basis function to mono- and multi-compartmental models (Hierarchical-Basis Function Method, H-BFM) at a voxel level. This method identifies the parameters of the compartmental model in its nonlinearized version, integrating information derived at the region of interest (ROI) level by segmenting the cerebral volume based on anatomical definition or functional clustering. We present the results obtained by using a two tissue-four rate constant model with two different tracers ([(11)C]FLB457 and [carbonyl-(11)C]WAY100635), one of the most complex models used in receptor studies, especially at the voxel level. H-BFM is robust and its application on both [(11)C]FLB457 and [carbonyl-(11)C]WAY100635 allows accurate and precise parameter estimates, good quality parametric maps and a low percentage of voxels out of physiological bound (<8%). The computational time depends on the number of basis functions selected and can be compatible with clinical use (~6h for a single subject analysis). The novel method is a robust approach for PET quantification by using compartmental modeling at the voxel level. In particular, different from other proposed approaches, this method can also be used when the linearization of the model is not appropriate. We expect that applying it to clinical data will generate reliable parametric maps. PMID:23220428
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. PMID:24986109
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
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)
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.
Testing parametric BRDF models with CHRIS/PROBA acquisitions over agricultural crops
NASA Astrophysics Data System (ADS)
Verger, Aleixandre; Camacho-de Coca, Fernando; Meli, Joaquin
2004-10-01
A proper determination of the BRDF is of interest for land surface studies in different topics such as albedo estimation, correction of anisotropy effects, and retrieval of vegetation parameters by defining optimal geometries. In this paper, we evaluate a set of parametric models widely-used for BRDF characterisation (Roujean model, Ambrals combinations, non-linear RPV and the empirical Walthall's model). These models are inverted and tested against atmospherically-corrected BRF measurements acquired with the CHRIS (Compact High Resolution Imaging Spectrometer) instrument on board the PROBA (Project for On-Board Autonomy) satellite over an agricultural test site located in Barrax, Spain) during the SPARC (SPectra bARrax Campaign) 2003 campaign. The study area presents different land crops with high variability in LAI values from 0 to 6. The objectives of the present study are to determine how well the different parametric BRDF models are able to fit CHRIS/PROBA's observed multiangular reflectances in order to determine the nadir-zenith reflectance, which is the optimal geometry to retrieve the fractional vegetation coverage (FVC), and to describe the anisotropy of vegetation canopies, which can be useful to estimate accurately the leaf area index (LAI). To do so, performance indicators are obtained for the different models. The results of this study show that all the tested models are fairly accurate in the entire spectral range (RMS<0.016 at 674 nm and RMS<0.025 at 803 nm) and thus are suitable for normalisation purposes. However, most of them are not able to describe BRDF features such as the hot spot, which hampers the use of these models for exploiting the directional information. There are no significant differences, for the experimental conditions, among those evaluated although the best models appear to be the linear Ross-Li model (low RMS) and the non-linear RPV model (more realistic BRDF).
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.
Integrated modeling for parametric evaluation of smart x-ray optics
NASA Astrophysics Data System (ADS)
Dell'Agostino, S.; Riva, M.; Spiga, D.; Basso, S.; Civitani, Marta
2014-08-01
This work is developed in the framework of AXYOM project, which proposes to study the application of a system of piezoelectric actuators to grazing-incidence X-ray telescope optic prototypes: thin glass or plastic foils, in order to increase their angular resolution. An integrated optomechanical model has been set up to evaluate the performances of X-ray optics under deformation induced by Piezo Actuators. Parametric evaluation has been done looking at different number and position of actuators to optimize the outcome. Different evaluations have also been done over the actuator types, considering Flexible Piezoceramic, Multi Fiber Composites piezo actuators, and PVDF.
Parametric modeling in distributed optical fiber vibration sensing system for position determination
NASA Astrophysics Data System (ADS)
Wu, Hongyan; Wang, Jian; Jia, Bo
2016-04-01
Distributed optical fiber vibration sensing system is widely used as a monitoring system in communication cable and pipeline of long distances. When a vibration signal occurs at a particular position along the fiber, the response of the system, in the frequency domain, presents a series of periodic maxima and minima (or null frequencies). These minima depend on the position of the vibration signal along the fiber. Power spectral estimation methods are considered to denoise the power spectrum of the system and determine these minima precisely. The experimental results show higher accuracy of the position using a parametric model with appropriate selection of order p and q than just using fast Fourier transform algorithm.
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. PMID:26609644
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.
Parametric scaling of neutral and ion excited state densities in an argon helicon source
NASA Astrophysics Data System (ADS)
McCarren, D.; Scime, E.
2016-04-01
We report measurements of the absolute density and temperature of ion and neutral excited states in an argon helicon source. The excited ion state density, which depends on ion density, electron density, and electron temperature, increases sharply with increasing magnetic field in the source. The neutral argon metastable density measurements are consistent with an increasing ionization fraction with increasing magnetic field strength. The ion temperature shows no evidence of increased heating with increasing magnetic field strength (which has only been observed in helicon sources operating at driving frequencies close to the lower hybrid frequency). The measurements were obtained through cavity ring down spectroscopy, a measurement technique that does not require the target excited state to be metastable or part of a fluorescence scheme; and is therefore applicable to any laser accessible atomic or ionic transition in a plasma.
Parametric study of compound semiconductor etching utilizing inductively coupled plasma source
Constantine, C.; Johnson, D.; Barratt, C.
1996-07-01
Inductively Coupled Plasma (ICP) sources are extremely promising for large-area, high-ion density etching or deposition processes. In this review the authors compare results for GaAs and GaN etching with both ICP and Electron Cyclotron Resonance (ECR) sources on the same single-wafer platform. The ICP is shown to be capable of very high rates with excellent anisotropy for fabrication of GaAs vias or deep mesas in GaAs or GaN waveguide structures.
NASA Astrophysics Data System (ADS)
Monteiro, M. J. P. F. G.; Christensen-Dalsgaard, J.; Thompson, M. J.
1996-03-01
Some alternatives to the traditional mixing-length theory (MLT) have recently been proposed for modelling convective heat transport inside stars. The ideal formulation is one that does not involve any free parameters. However, in our present state of ignorance we still need at least one free parameter in order to build solar models with the correct radius. Having adjusted this parameter (e.g. the mixing-length parameter α_c_) to obtain the observed radius, we cannot discriminate non-seismically between different convective theories, regardless of how low-efficiency convection is treated. In this paper we consider how the additional information provided by global p-mode frequencies can be used to investigate low-efficiency convection at the top of the solar convective envelope and discriminate between different theories. We consider a parametrization which in addition to the mixing length has two further parameters: one (β_c_) which regulates the relative degree of overadiabaticity (or inefficiency) of convection, and a second (m) that affects the transition between the regimes of efficient and inefficient convection. Our parametrization includes traditional MLT__ and the theory of Canuto & Mazzitelli as particular cases. We study the effect of varying these parameters by constructing a series of envelope models with the same depth of the convection zone and computing their oscillation frequencies. We discuss our results in terms of kernels relating frequency changes to changes in the structure of the superadiabatic region.
Parametrization of Extended Gaussian Disorder Models from Microscopic Charge Transport Simulations.
Kordt, Pascal; Stenzel, Ole; Baumeier, Björn; Schmidt, Volker; Andrienko, Denis
2014-06-10
Simulations of organic semiconducting devices using drift-diffusion equations are vital for the understanding of their functionality as well as for the optimization of their performance. Input parameters for these equations are usually determined from experiments and do not provide a direct link to the chemical structures and material morphology. Here we demonstrate how such a parametrization can be performed by using atomic-scale (microscopic) simulations. To do this, a stochastic network model, parametrized on atomistic simulations, is used to tabulate charge mobility in a wide density range. After accounting for finite-size effects at small charge densities, the data is fitted to the uncorrelated and correlated extended Gaussian disorder models. Surprisingly, the uncorrelated model reproduces the results of microscopic simulations better than the correlated one, compensating for spatial correlations present in a microscopic system by a large lattice constant. The proposed method retains the link to the material morphology and the underlying chemistry and can be used to formulate structure-property relationships or optimize devices prior to compound synthesis. PMID:26580771
A parametric sizing model for Molten Regolith Electrolysis reactors to produce oxygen on the Moon
NASA Astrophysics Data System (ADS)
Schreiner, Samuel S.; Sibille, Laurent; Dominguez, Jesus A.; Hoffman, Jeffrey A.
2016-04-01
We present a parametric sizing model for a Molten Regolith Electrolysis (MRE) reactor that produces oxygen and molten metals from lunar regolith. The model has a foundation of regolith material property models validated using data from Apollo samples and simulants. A multiphysics simulation of an MRE reactor is developed and leveraged to generate a database linking reactor design and performance trends. A novel design methodology is created which utilizes this database to parametrically design an MRE reactor that can (1) sustain the required current, operating temperature, and mass of molten regolith to meet a desired oxygen production level, (2) operate for long periods of time by protecting the reactor walls from the corrosive molten regolith with a layer of solid "frozen" regolith, and (3) 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. Sensitivity analyses are presented for several design variables, including operating temperature, regolith feedstock composition, and the degree of operational flexibility.
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 modeling of energy filtering by energy barriers in thermoelectric nanocomposites
NASA Astrophysics Data System (ADS)
Zianni, Xanthippi; Narducci, Dario
2015-01-01
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 shape representation by a deformable NURBS model for cardiac functional measurements.
Chen, Sheng Yong; Guan, Qiu
2011-03-01
This paper proposes a method of parametric representation and functional measurement of 3-D cardiac shapes in a deformable nonuniform rational B-splines (NURBS) model. This representation makes it very easy to automatically evaluate the functional parameters and myocardial kinetics of the heart, since quantitative analysis can be followed in a simple way. In the model, local deformation and motion on the cardiac shape are expressed in adjustable parameters. Especially, an effective integral algorithm is used for volumetric measurement of a NURBS shape since the volume is the most basic parameter in cardiac functional analysis. This method promises the numerical computation to be very convenient, efficient, and accurate, in comparison with traditional methods. Practical experiments are carried out, and results show that the algorithm can get satisfactory measurement accuracy and efficiency. The parametric NURBS model in cylindrical coordinates is not only very suitable to fit the anatomical surfaces of a cardiac shape, but also easy for geometric transformation and nonrigid registration, and able to represent local dynamics and kinetics, and thus, can easily be applied for quantitative and functional analysis of the heart. PMID:20952325
Convection- and SASI-driven flows in parametrized models of core-collapse supernova explosions
NASA Astrophysics Data System (ADS)
Endeve, E.; Cardall, C. Y.; Budiardja, R. D.; Mezzacappa, A.
2016-02-01
We present initial results from three-dimensional simulations of parametrized core-collapse supernova (CCSN) explosions obtained with our astrophysical simulation code General Astrophysical Simulation System (GenASIS). We are interested in nonlinear flows resulting from neutrino-driven convection and the standing accretion shock instability (SASI) in the CCSN environment prior to and during the explosion. By varying parameters in our model that control neutrino heating and shock dissociation, our simulations result in convection-dominated and SASI-dominated evolution. We describe this initial set of simulation results in some detail. To characterize the turbulent flows in the simulations, we compute and compare velocity power spectra from convection-dominated and SASI-dominated (both non-exploding and exploding) models. When compared to SASI-dominated models, convection-dominated models exhibit significantly more power on small spatial scales.
A non-parametric probabilistic model for soil-structure interaction
NASA Astrophysics Data System (ADS)
Laudarin, F.; Desceliers, C.; Bonnet, G.; Argoul, P.
2013-07-01
The paper investigates the effect of soil-structure interaction on the dynamic response of structures. A non-parametric probabilistic formulation for the modelling of an uncertain soil impedance is used to account for the usual lack of information on soil properties. Such a probabilistic model introduces the physical coupling stemming from the soil heterogeneity around the foundation. Considering this effect, even a symmetrical building displays a torsional motion when submitted to earthquake loading. The study focuses on a multi-story building modeled by using equivalent Timoshenko beam models which have different mass distributions. The probability density functions of the maximal internal forces and moments in a given building are estimated by Monte Carlo simulations. Some results on the stochastic modal analysis of the structure are also given.
a Model for the Parametric Analysis and Optimization of Inertance Tube Pulse Tube Refrigerators
NASA Astrophysics Data System (ADS)
Dodson, C.; Lopez, A.; Roberts, T.; Razani, A.
2008-03-01
A first order model developed for the design analysis and optimization of Inertance Tube Pulse Tube Refrigerators (ITPTRs) is integrated with the code NIST REGEN 3.2 capable of modeling the regenerative heat exchangers used in ITPTRs. The model is based on the solution of simultaneous non-linear differential equations representing the inertance tube, an irreversibility parameter model for the pulse tube, and REGEN 3.2 to simulate the regenerator. The integration of REGEN 3.2 is accomplished by assuming a sinusoidal pressure wave at the cold side of the regenerator. In this manner, the computational power of REGEN 3.2 is conveniently used to reduce computational time required for parametric analysis and optimization of ITPTRs. The exergy flow and exergy destruction (irreversibility) of each component of ITPTRs is calculated and the effect of important system parameters on the second law efficiency of the refrigerators is presented.
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.
Parametric study of a corrosion model applied to lead-bismuth flow systems
NASA Astrophysics Data System (ADS)
Zhang, Jinsuo; Li, Ning
2003-09-01
The corrosion of steels exposed to flowing liquid metals is influenced by local and axial conditions of the flow systems. Despite of this, most existing corrosion models only consider the mean values based on local conditions. The present study refines a model for flowing liquid metal under non-isothermal conditions. The model is based on solving the mass transport equation in the boundary layer. Two kinds of flows are investigated: through an open pipe system and through a closed loop system. The model is applied to a lead-bismuth eutectic (LBE) test loop. A parametric study illustrates the effects of the axial temperature profile on corrosion. The study provides important insight to the design, operation and testing of such loop systems.
NASA Astrophysics Data System (ADS)
Lee, L. A.; Carslaw, K. S.; Pringle, K. J.
2012-04-01
Global aerosol contributions to radiative forcing (and hence climate change) are persistently subject to large uncertainty in successive Intergovernmental Panel on Climate Change (IPCC) reports (Schimel et al., 1996; Penner et al., 2001; Forster et al., 2007). As such more complex global aerosol models are being developed to simulate aerosol microphysics in the atmosphere. The uncertainty in global aerosol model estimates is currently estimated by measuring the diversity amongst different models (Textor et al., 2006, 2007; Meehl et al., 2007). The uncertainty at the process level due to the need to parameterise in such models is not yet understood and it is difficult to know whether the added model complexity comes at a cost of high model uncertainty. In this work the model uncertainty and its sources due to the uncertain parameters is quantified using variance-based sensitivity analysis. Due to the complexity of a global aerosol model we use Gaussian process emulation with a sufficient experimental design to make such as a sensitivity analysis possible. The global aerosol model used here is GLOMAP (Mann et al., 2010) and we quantify the sensitivity of numerous model outputs to 27 expertly elicited uncertain model parameters describing emissions and processes such as growth and removal of aerosol. Using the R package DiceKriging (Roustant et al., 2010) along with the package sensitivity (Pujol, 2008) it has been possible to produce monthly global maps of model sensitivity to the uncertain parameters over the year 2008. Global model outputs estimated by the emulator are shown to be consistent with previously published estimates (Spracklen et al. 2010, Mann et al. 2010) but now we have an associated measure of parameter uncertainty and its sources. It can be seen that globally some parameters have no effect on the model predictions and any further effort in their development may be unnecessary, although a structural error in the model might also be identified. The
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.
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.
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.
Parametric Study of Synthetic-Jet-Based Flow Control on a Vertical Tail Model
NASA Astrophysics Data System (ADS)
Monastero, Marianne; Lindstrom, Annika; Beyar, Michael; Amitay, Michael
2015-11-01
Separation control over the rudder of the vertical tail of a commercial airplane using synthetic-jet-based flow control can lead to a reduction in tail size, with an associated decrease in drag and increase in fuel savings. A parametric, experimental study was undertaken using an array of finite span synthetic jets to investigate the sensitivity of the enhanced vertical tail side force to jet parameters, such as jet spanwise spacing and jet momentum coefficient. A generic wind tunnel model was designed and fabricated to fundamentally study the effects of the jet parameters at varying rudder deflection and model sideslip angles. Wind tunnel results obtained from pressure measurements and tuft flow visualization in the Rensselaer Polytechnic Subsonic Wind Tunnel show a decrease in separation severity and increase in model performance in comparison to the baseline, non-actuated case. The sensitivity to various parameters will be presented.
A. Hassan; H. Bekhit; Y. Zhang; J. Chapman
2008-09-15
Uncertainty built into conceptual groundwater flow and transport models and associated parametric uncertainty should be appropriately included when such models are used to develop detection monitoring networks for contaminated sites. We compare alternative approaches of propagating such uncertainty from the flow and transport model into the network design. The focus is on detection monitoring networks where the primary objective is to intercept the contaminant before it reaches a boundary of interest (e.g., compliance boundary). Different uncertainty propagation approaches identify different well locations and different well combinations (networks) as having the highest detection efficiency. It is thus recommended that multiple uncertainty propagation approaches are considered. If several approaches yield consistent results in terms of identifying the best performing candidate wells and the best performing well network for detecting a contaminant plume, this would provide confidence in the suitability of the selected well locations.
A model-based parametric study of impact force during running.
Zadpoor, Amir Abbas; Nikooyan, Ali Asadi; Arshi, Ahmad Reza
2007-01-01
This paper deals with the impact force during foot-ground impact activities such as the running. A previously developed model is used for this study. The model is a lumped-parameter one consisting of four masses connected to each other via linear springs and viscous dampers. A shoe-specific nonlinear function is used for representation of the ground reaction force. The authors have previously showed that the previous version of the model as well as its simulation is incorrect. This paper slightly modifies the previous model so as it is able to produce results in agreement with the experiments. Then, the modified model is simulated for two typical shoe types. A parametric study is also conducted. The parametric study concerns with the effects of masses, mass ratios, stiffness constants, and damping coefficients on the dynamics of the impact. It is shown that the impact forces increase as the rigid and wobbling masses increase. However, the increase in the impact forces is not the same for all the masses. It is found that the impact force increases as the touchdown velocities increase. Simulations imply that the variations of the damping coefficients result in larger variations of the impact force compared to the stiffness. The effect of the variation of gravity on the simulated impact force is also explored. It is concluded that both the first and the second peaks of the impact force are increased with gravity. An in-depth discussion is included to compare results of the current paper with results of other investigators. PMID:17092510
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
Uncertainties in volcanic plume modeling: a parametric study using FPLUME model
NASA Astrophysics Data System (ADS)
Macedonio, Giovanni; Costa, Antonio; Folch, Arnau
2016-04-01
Tephra transport and dispersal models are commonly used for volcanic hazard assessment and tephra dispersal (ash cloud) forecasts. The proper quantification of the parameters defining the source term in the dispersal models, and in particular the estimation of the mass eruption rate, plume height, and particle vertical mass distribution, is of paramount importance for obtaining reliable results in terms of particle mass concentration in the atmosphere and loading on the ground. The study builds upon numerical simulations of 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 exercise. The goal was to explore the leading order role of each parameter in order to assess which should be better constrained to better quantify the eruption source parameters for use by the dispersal models. Moreover, a sensitivity analysis 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 are the mass eruption rate and the air entrainment coefficient, specially for weak plumes.
Expert-Guided Generative Topographical Modeling with Visual to Parametric Interaction
2016-01-01
Introduced by Bishop et al. in 1996, Generative Topographic Mapping (GTM) is a powerful nonlinear latent variable modeling approach for visualizing high-dimensional data. It has shown useful when typical linear methods fail. However, GTM still suffers from drawbacks. Its complex parameterization of data make GTM hard to fit and sensitive to slight changes in the model. For this reason, we extend GTM to a visual analytics framework so that users may guide the parameterization and assess the data from multiple GTM perspectives. Specifically, we develop the theory and methods for Visual to Parametric Interaction (V2PI) with data using GTM visualizations. The result is a dynamic version of GTM that fosters data exploration. We refer to the new version as V2PI-GTM. In this paper, we develop V2PI-GTM in stages and demonstrate its benefits within the context of a text mining case study. PMID:26905728
Martinez, L C; Calzado, A
2016-01-01
A parametric model is used for the calculation of the CT number of some selected human tissues of known compositions (Hi) in two hybrid systems, one SPECT-CT and one PET-CT. Only one well characterized substance, not necessarily tissue-like, needs to be scanned with the protocol of interest. The linear attenuation coefficients of these tissues for some energies of interest (μ(i)) have been calculated from their tabulated compositions and the NIST databases. These coefficients have been compared with those calculated with the bilinear model from the CT number (μ(B)i). No relevant differences have been found for bones and lung. In the soft tissue region, the differences can be up to 5%. These discrepancies are attributed to the different chemical composition for the tissues assumed by both methods. PMID:26454019
Expert-Guided Generative Topographical Modeling with Visual to Parametric Interaction.
Han, Chao; House, Leanna; Leman, Scotland C
2016-01-01
Introduced by Bishop et al. in 1996, Generative Topographic Mapping (GTM) is a powerful nonlinear latent variable modeling approach for visualizing high-dimensional data. It has shown useful when typical linear methods fail. However, GTM still suffers from drawbacks. Its complex parameterization of data make GTM hard to fit and sensitive to slight changes in the model. For this reason, we extend GTM to a visual analytics framework so that users may guide the parameterization and assess the data from multiple GTM perspectives. Specifically, we develop the theory and methods for Visual to Parametric Interaction (V2PI) with data using GTM visualizations. The result is a dynamic version of GTM that fosters data exploration. We refer to the new version as V2PI-GTM. In this paper, we develop V2PI-GTM in stages and demonstrate its benefits within the context of a text mining case study. PMID:26905728
Melbourne, Andrew; Toussaint, Nicolas; Owen, David; Simpson, Ivor; Anthopoulos, Thanasis; De Vita, Enrico; Atkinson, David; Ourselin, Sebastien
2016-07-01
Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software package for such multi-contrast Magnetic Resonance Imaging that provides a unified model-fitting framework. We describe model-fitting functionality for Arterial Spin Labeled MRI, T1 Relaxometry, T2 relaxometry and Diffusion Weighted imaging, providing command line documentation to generate the figures in the manuscript. Software and data (using the nifti file format) used in this article are simultaneously provided for download. We also present some extended applications of the joint model fitting framework applied to diffusion weighted imaging and T2 relaxometry, in order to both improve parameter estimation in these models and generate new parameters that link different MR modalities. NiftyFit is intended as a clear and open-source educational release so that the user may adapt and develop their own functionality as they require. PMID:26972806
Bayesian Semi- and Non-parametric Models for Longitudinal Data with Multiple Membership Effects in R
Savitsky, Terrance D.; Paddock, Susan M.
2014-01-01
We introduce growcurves for R that performs analysis of repeated measures multiple membership (MM) data. This data structure arises in studies under which an intervention is delivered to each subject through the subject's participation in a set of multiple elements that characterize the intervention. In our motivating study design under which subjects receive a group cognitive behavioral therapy (CBT) treatment, an element is a group CBT session and each subject attends multiple sessions that, together, comprise the treatment. The sets of elements, or group CBT sessions, attended by subjects will partly overlap with some of those from other subjects to induce a dependence in their responses. The growcurves package offers two alternative sets of hierarchical models: 1. Separate terms are specified for multivariate subject and MM element random effects, where the subject effects are modeled under a Dirichlet process prior to produce a semi-parametric construction; 2. A single term is employed to model joint subject-by-MM effects. A fully non-parametric dependent Dirichlet process formulation allows exploration of differences in subject responses across different MM elements. This model allows for borrowing information among subjects who express similar longitudinal trajectories for flexible estimation. growcurves deploys “estimation” functions to perform posterior sampling under a suite of prior options. An accompanying set of “plot” functions allow the user to readily extract by-subject growth curves. The design approach intends to anticipate inferential goals with tools that fully extract information from repeated measures data. Computational efficiency is achieved by performing the sampling for estimation functions using compiled C++. PMID:25400517
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).
NASA Astrophysics Data System (ADS)
Seshadreesan, Kaushik P.; Takeoka, Masahiro; Sasaki, Masahide
2016-04-01
Device-independent quantum key distribution (DIQKD) guarantees unconditional security of a secret key without making assumptions about the internal workings of the devices used for distribution. It does so using the loophole-free violation of a Bell's inequality. The primary challenge in realizing DIQKD in practice is the detection loophole problem that is inherent to photonic tests of Bell' s inequalities over lossy channels. We revisit the proposal of Curty and Moroder [Phys. Rev. A 84, 010304(R) (2011), 10.1103/PhysRevA.84.010304] to use a linear optics-based entanglement-swapping relay (ESR) to counter this problem. We consider realistic models for the entanglement sources and photodetectors: more precisely, (a) polarization-entangled states based on pulsed spontaneous parametric down-conversion sources with infinitely higher-order multiphoton components and multimode spectral structure, and (b) on-off photodetectors with nonunit efficiencies and nonzero dark-count probabilities. We show that the ESR-based scheme is robust against the above imperfections and enables positive key rates at distances much larger than what is possible otherwise.
Semiparametric modeling: Correcting low-dimensional model error in parametric models
NASA Astrophysics Data System (ADS)
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.
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
2013-01-01
Background Applying a statistical method implies identifying underlying (model) assumptions and checking their validity in the particular context. One of these contexts is association modeling for epistasis detection. Here, depending on the technique used, violation of model assumptions may result in increased type I error, power loss, or biased parameter estimates. Remedial measures for violated underlying conditions or assumptions include data transformation or selecting a more relaxed modeling or testing strategy. Model-Based Multifactor Dimensionality Reduction (MB-MDR) for epistasis detection relies on association testing between a trait and a factor consisting of multilocus genotype information. For quantitative traits, the framework is essentially Analysis of Variance (ANOVA) that decomposes the variability in the trait amongst the different factors. In this study, we assess through simulations, the cumulative effect of deviations from normality and homoscedasticity on the overall performance of quantitative Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect 2-locus epistasis signals in the absence of main effects. Methodology Our simulation study focuses on pure epistasis models with varying degrees of genetic influence on a quantitative trait. Conditional on a multilocus genotype, we consider quantitative trait distributions that are normal, chi-square or Student’s t with constant or non-constant phenotypic variances. All data are analyzed with MB-MDR using the built-in Student’s t-test for association, as well as a novel MB-MDR implementation based on Welch’s t-test. Traits are either left untransformed or are transformed into new traits via logarithmic, standardization or rank-based transformations, prior to MB-MDR modeling. Results Our simulation results show that MB-MDR controls type I error and false positive rates irrespective of the association test considered. Empirically-based MB-MDR power estimates for MB-MDR with Welch
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.
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.
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.
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.
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
Parametric retrieval model for estimating aerosol size distribution via the AERONET, LAGOS station.
Emetere, Moses Eterigho; Akinyemi, Marvel Lola; Akin-Ojo, Omololu
2015-12-01
The size characteristics of atmospheric aerosol over the tropical region of Lagos, Southern Nigeria were investigated using two years of continuous spectral aerosol optical depth measurements via the AERONET station for four major bands i.e. blue, green, red and infrared. Lagos lies within the latitude of 6.465°N and longitude of 3.406°E. Few systems of dispersion model was derived upon specified conditions to solve challenges on aerosols size distribution within the Stokes regime. The dispersion model was adopted to derive an aerosol size distribution (ASD) model which is in perfect agreement with existing model. The parametric nature of the formulated ASD model shows the independence of each band to determine the ASD over an area. The turbulence flow of particulates over the area was analyzed using the unified number (Un). A comparative study via the aid of the Davis automatic weather station was carried out on the Reynolds number, Knudsen number and the Unified number. The Reynolds and Unified number were more accurate to describe the atmospheric fields of the location. The aerosols loading trend in January to March (JFM) and August to October (ASO) shows a yearly 15% retention of aerosols in the atmosphere. The effect of the yearly aerosol retention can be seen to partly influence the aerosol loadings between October and February. PMID:26452005
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.
Ji, Songbai; Ghadyani, Hamidreza; Bolander, Richard P.; Beckwith, Jonathan G.; Ford, James C.; Mcallister, Thomas W.; Flashman, Laura A.; Paulsen, Keith D.; Ernstrom, Karin; Jain, Sonia; Raman, Rema; Zhang, Liying; Greenwald, Richard M.
2015-01-01
A number of human head finite element (FE) models have been developed from different research groups over the years to study the mechanisms of traumatic brain injury. These models can vary substantially in model features and parameters, making it important to evaluate whether simulation results from one model are readily comparable with another, and whether response-based injury thresholds established from a specific model can be generalized when a different model is employed. The purpose of this study is to parametrically compare regional brain mechanical responses from three validated head FE models to test the hypothesis that regional brain responses are dependent on the specific head model employed as well as the region of interest (ROI). The Dartmouth Scaled and Normalized Model (DSNM), the Simulated Injury Monitor (SIMon), and the Wayne State University Head Injury Model (WSUHIM) were selected for comparisons. For model input, 144 unique kinematic conditions were created to represent the range of head impacts sustained by male collegiate hockey players during play. These impacts encompass the 50th, 95th, and 99th percentile peak linear and rotational accelerations at 16 impact locations around the head. Five mechanical variables (strain, strain rate, strain × strain rate, stress, and pressure) in seven ROIs reported from the FE models were compared using Generalized Estimating Equation statistical models. Highly significant differences existed among FE models for nearly all output variables and ROIs. The WSUHIM produced substantially higher peak values for almost all output variables regardless of the ROI compared to the DSNM and SIMon models (p < 0.05). DSNM also produced significantly different stress and pressure compared with SIMon for all ROIs (p < 0.05), but such differences were not consistent across ROIs for other variables. Regardless of FE model, most output variables were highly correlated with linear and rotational peak accelerations. The
NASA Astrophysics Data System (ADS)
Shi, X.; Ye, M.; Curtis, G. P.; Lu, D.; Meyer, P. D.; Yabusaki, S.; Wu, J.
2011-12-01
Assessment of parametric uncertainty for groundwater reactive transport models is challenging, because the models are highly nonlinear with respect to their parameters due to nonlinear reaction equations and process coupling. The nonlinearity may yield parameter distributions that are non-Gaussian and have multiple modes. For such parameter distributions, the widely used nonlinear regression methods may not be able to accurately quantify predictive uncertainty. One solution to this problem is to use Markov Chain Monte Carlo (MCMC) techniques. Both the nonlinear regression and MCMC methods are used in this study for quantification of parametric uncertainty of a surface complexation model (SCM), developed to simulate hexavalent uranium [U(VI)] transport in column experiments. Firstly, a brute force Monte Carlo (MC) simulation with hundreds of thousands of model executions is conducted to understand the surface of objective function and predictive uncertainty of uranium concentration. Subsequently, the Gauss-Marquardt-Levenberg method is applied to calibrate the model. It shows that, even with multiple initial guesses, the local optimization method has difficulty of finding the global optimum because of the rough surface of the objective function and local optima/minima due to model nonlinearity. Another problem of the nonlinear regression is the underestimation of predictive uncertainty, as both the linear and nonlinear confidence intervals are narrower than that obtained from the native MC simulation. Since the naïve MC simulation is computationally expensive, the above challenges for parameter estimation and predictive uncertainty analysis are addressed using a computationally efficient MCMC technique, the DiffeRential Evolution Adaptive Metropolis algorithm (DREAM) algorithm. The results obtained from running DREAM compared with those from brute force Monte Carlo simulations shown that MCMC not only successfully infers the multi-modals posterior probability
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.
A Semi-parametric Nonlinear Model for Event-Related fMRI
Zhang, Tingting; Li, Fan; Gonzalez, Marlen Z.; Maresh, Erin L.; Coan, James A.
2014-01-01
Nonlinearity in evoked hemodynamic responses often presents in event-related fMRI studies. Volterra series, a higher-order extension of linear convolution, has been used in the literature to construct a nonlinear characterization of hemodynamic responses. Estimation of the Volterra kernel coefficients in these models is usually challenging due to the large number of parameters. We propose a new semi-parametric model based on Volterra series for the hemodynamic responses that greatly reduces the number of parameters and enables “information borrowing” among subjects. This model assumes that in the same brain region and under the same stimulus, the hemodynamic responses across subjects share a common but unknown functional shape that can differ in magnitude, latency and degree of interaction. We develop a computationally-efficient strategy based on splines to estimate the model parameters, and a hypothesis test on nonlinearity. The proposed method is compared with several existing methods via extensive simulations, and is applied to a real event-related fMRI study. PMID:24742917
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. PMID:26394029
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.
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…
Technology Transfer Automated Retrieval System (TEKTRAN)
Parametric non-linear regression (PNR) techniques commonly are used to develop weed seedling emergence models. Such techniques, however, require statistical assumptions that are difficult to meet. To examine and overcome these limitations, we compared PNR with a nonparametric estimation technique. F...
NASA Astrophysics Data System (ADS)
Wang, W. L.; Yu, D. S.; Zhou, Z.
2015-10-01
Due to the high-speed operation of modern rail vehicles and severe in-service environment of their hydraulic dampers, it has become important to establish more practical and accurate damper models and apply those models in high-speed transit problem studies. An improved full parametric model with actual in-service parameters, such as variable viscous damping, comprehensive stiffness and small mounting clearance was established for a rail vehicle's axle-box hydraulic damper. A subtle variable oil property model was built and coupled to the modelling process, which included modelling of the dynamic flow losses and the relief-valve system dynamics. The experiments validated the accuracy and robustness of the established full in-service parametric model and simulation which captured the damping characteristics over an extremely wide range of excitation speeds. Further simulations were performed using the model to uncover the effects of key in-service parameter variations on the nominal damping characteristics of the damper. The obtained in-service parametric model coupled all of the main factors that had significant impacts on the damping characteristics, so that the model could be useful in more extensive parameter effects analysis, optimal specification and product design optimisation of hydraulic dampers for track-friendliness, ride comfort and other high-speed transit problems.
NASA Astrophysics Data System (ADS)
Hong, Sung-Kwon; Epureanu, Bogdan I.; Castanier, Matthew P.
2014-09-01
The goal of this work is to develop a numerical model for the vibration of hybrid electric vehicle (HEV) battery packs to enable probabilistic forced response simulations for the effects of variations. There are two important types of variations that affect their structural response significantly: the prestress that is applied when joining the cells within a pack; and the small, random structural property discrepancies among the cells of a battery pack. The main contributions of this work are summarized as follows. In order to account for these two important variations, a new parametric reduced order model (PROM) formulation is derived by employing three key observations: (1) the stiffness matrix can be parameterized for different levels of prestress, (2) the mode shapes of a battery pack with cell-to-cell variation can be represented as a linear combination of the mode shapes of the nominal system, and (3) the frame holding each cell has vibratory motion. A numerical example of an academic battery pack with pouch cells is presented to demonstrate that the PROM captures the effects of both prestress and structural variation on battery packs. The PROM is validated numerically by comparing full-order finite element models (FEMs) of the same systems.
Computational modeling and parametric study of a rotary actuator driven by piezoelectric composites
NASA Astrophysics Data System (ADS)
Li, Hing L.; Lee, ShiWei R.
1998-07-01
An innovative actuation principle was introduced in a previous study to drive a rotary actuator by piezoelectric composite laminate. The driving element is a three layer laminated beam with piezoceramics sandwiched between two antisymmetric composite laminae. By taking advantage of the structural coupling, a rotary actuator similar to ultrasonic motors can be implemented. A prototype of the mentioned actuator has been fabricated. The objective of this study is to model this device by finite element method. A commercial finite element code, ANSYS, was employed to simulate the rotary actuator. The piezoelectric laminate and the rotor were modeled by solid brick elements and special constraint element was used to account for the contact between two separate bodies. Static and transient dynamic analyses were conducted to simulate the deformation and the angular motion of the rotary actuator, respectively. Parametric study was performed by modal and harmonic analyses to investigate the dynamic response of the driving laminate. The results of this study confirmed the proposed actuation principle and the developed computational model may be used for the optimization of future design.
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%.
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.
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.
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
Limitations in the rapid extraction of evoked potentials using parametric modeling.
De Silva, A C; Sinclair, N C; Liley, D T J
2012-05-01
The rapid extraction of variations in evoked potentials (EPs) is of great clinical importance. Parametric modeling using autoregression with an exogenous input (ARX) and robust evoked potential estimator (REPE) are commonly used methods for extracting EPs over the conventional moving time average. However, a systematic study of the efficacy of these methods, using known synthetic EPs, has not been performed. Therefore, the current study evaluates the restrictions of these methods in the presence of known and systematic variations in EP component latency and signal-to-noise ratios (SNR). In the context of rapid extraction, variations of wave V of the auditory brainstem in response to stimulus intensity were considered. While the REPE methods were better able to recover the simulated model of the EP, morphology and the latency of the ARX-estimated EPs was a closer match to the actual EP than than that of the REPE-estimated EPs. We, therefore, concluded that ARX rapid extraction would perform better with regards to the rapid tracking of latency variations. By tracking simulated and empirically induced latency variations, we conclude that rapid EP extraction using ARX modeling is only capable of extracting latency variations of an EP in relatively high SNRs and, therefore, should be used with caution in low-noise environments. In particular, it is not a suitable method for the rapid extraction of early EP components such as the auditory brainstem potential. PMID:22394572
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.
NASA Technical Reports Server (NTRS)
Boxwell, D. A.; Schmitz, F. H.; Splettstoesser, W. R.; Schultz, K. J.
1985-01-01
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 scalig 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.
NASA Astrophysics Data System (ADS)
Li, Zhongyang; Bing, Pibin; Yao, Jianquan; Xu, Degang; Zhong, Kai
2012-09-01
A high-powered pulsed terahertz (THz)-wave has been parametrically generated via a surface-emitted THz-wave parametric oscillator (TPO). The effective parametric gain length under the noncollinear phase matching condition was calculated for optimization of the parameters of the TPO. A large volume crystal of MgO:LiNbO3 was used as the gain medium. THz-wave radiation covering a frequency range from 0.87 to 2.73 THz was obtained. The average power of the THz-wave was 9.12 μW at 1.75 THz when the pump energy was 94 mJ, corresponding to an energy conversion efficiency of about 9.7×10-6 and a photon conversion efficiency of about 0.156%. The THz-wave power in our experiments is high enough for practical applications to spectrum analysis and imaging.
Open source layered sensing model
NASA Astrophysics Data System (ADS)
Rovito, Todd V.; Abayowa, Bernard O.; Talbert, Michael L.
2011-06-01
This paper will look at using open source tools (Blender [17], LuxRender [18], and Python [19]) to build an image processing model for exploring combinations of sensors/platforms for any given image resolution. The model produces camera position, camera attitude, and synthetic camera data that can be used for exploitation purposes. We focus on electro-optical (EO) visible sensors to simplify the rendering but this work could be extended to use other rendering tools that support different modalities. Due to the computational complexity of ray tracing we employ the Amazon Elastic Cloud Computer to help speed up the generation of large ray traced scenes. The key idea of the paper is to provide an architecture for layered sensing simulation which is modular in design and constructed on open-source off-the-shelf software. This architecture shows how leveraging existing open-source software allows for practical layered sensing modeling to be rapidly assimilated and utilized in real-world applications. In this paper we demonstrate our model output is automatically exploitable by using generated data with an innovative video frame mosaic algorithm.
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
Bayesian kinematic earthquake source models
NASA Astrophysics Data System (ADS)
Minson, S. E.; Simons, M.; Beck, J. L.; Genrich, J. F.; Galetzka, J. E.; Chowdhury, F.; Owen, S. E.; Webb, F.; Comte, D.; Glass, B.; Leiva, C.; Ortega, F. H.
2009-12-01
Most coseismic, postseismic, and interseismic slip models are based on highly regularized optimizations which yield one solution which satisfies the data given a particular set of regularizing constraints. This regularization hampers our ability to answer basic questions such as whether seismic and aseismic slip overlap or instead rupture separate portions of the fault zone. We present a Bayesian methodology for generating kinematic earthquake source models with a focus on large subduction zone earthquakes. Unlike classical optimization approaches, Bayesian techniques sample the ensemble of all acceptable models presented as an a posteriori probability density function (PDF), and thus we can explore the entire solution space to determine, for example, which model parameters are well determined and which are not, or what is the likelihood that two slip distributions overlap in space. Bayesian sampling also has the advantage that all a priori knowledge of the source process can be used to mold the a posteriori ensemble of models. Although very powerful, Bayesian methods have up to now been of limited use in geophysical modeling because they are only computationally feasible for problems with a small number of free parameters due to what is called the "curse of dimensionality." However, our methodology can successfully sample solution spaces of many hundreds of parameters, which is sufficient to produce finite fault kinematic earthquake models. Our algorithm is a modification of the tempered Markov chain Monte Carlo (tempered MCMC or TMCMC) method. In our algorithm, we sample a "tempered" a posteriori PDF using many MCMC simulations running in parallel and evolutionary computation in which models which fit the data poorly are preferentially eliminated in favor of models which better predict the data. We present results for both synthetic test problems as well as for the 2007 Mw 7.8 Tocopilla, Chile earthquake, the latter of which is constrained by InSAR, local high
Density-based load estimation using two-dimensional finite element models: a parametric study.
Bona, Max A; Martin, Larry D; Fischer, Kenneth J
2006-08-01
A parametric investigation was conducted to determine the effects on the load estimation method of varying: (1) the thickness of back-plates used in the two-dimensional finite element models of long bones, (2) the number of columns of nodes in the outer medial and lateral sections of the diaphysis to which the back-plate multipoint constraints are applied and (3) the region of bone used in the optimization procedure of the density-based load estimation technique. The study is performed using two-dimensional finite element models of the proximal femora of a chimpanzee, gorilla, lion and grizzly bear. It is shown that the density-based load estimation can be made more efficient and accurate by restricting the stimulus optimization region to the metaphysis/epiphysis. In addition, a simple method, based on the variation of diaphyseal cortical thickness, is developed for assigning the thickness to the back-plate. It is also shown that the number of columns of nodes used as multipoint constraints does not have a significant effect on the method. PMID:17132530
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. PMID:27185035
The parametrically excited upside-down rod: an elastic jointed pendulum model
NASA Astrophysics Data System (ADS)
Galán, J.; Fraser, W. B.; Acheson, D. J.; Champneys, A. R.
2005-02-01
A model is studied which consists of a chain of N identical pendulums coupled by damped elastic joints subject to vertical sinusoidal forcing of its base. Particular attention is paid to the stability of the upright equilibrium configuration with a view to understanding recent experimental results on the stabilization of an unstable stiff column under parametric excitation. It is shown via an appropriate scaling argument how the continuum rod model arises by taking the limit N→∞. The effect of the inclusion of bending stiffness is first studied via asymptotics and numerics for the case N=1, showing how the static bifurcation of the pendulum varies with the four dimensionless parameters of the system; damping, bending stiffness and amplitude and frequency of excitation. For the multiple pendulum system, the bifurcation behaviour of the upright position as a function of the same four parameters is studied via numerical methods applied to the linearized equations. The damping term is found to be crucial in destroying many of the resonant instabilities that occur in the limit as N→∞. At realistic damping levels only a few instabilities remain, which are shown to be largely independent of N. These instabilities agree qualitatively with the experiments.
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.
A parametric model for reactive high-power impulse magnetron sputtering of films
NASA Astrophysics Data System (ADS)
Kozák, Tomáš; Vlček, Jaroslav
2016-02-01
We present a time-dependent parametric model for reactive HiPIMS deposition of films. Specific features of HiPIMS discharges and a possible increase in the density of the reactive gas in front of the reactive gas inlets placed between the target and the substrate are considered in the model. The model makes it possible to calculate the compound fractions in two target layers and in one substrate layer, and the deposition rate of films at fixed partial pressures of the reactive and inert gas. A simplified relation for the deposition rate of films prepared using a reactive HiPIMS is presented. We used the model to simulate controlled reactive HiPIMS depositions of stoichiometric \\text{Zr}{{\\text{O}}2} films, which were recently carried out in our laboratories with two different configurations of the {{\\text{O}}2} inlets in front of the sputtered target. The repetition frequency was 500 Hz at the deposition-averaged target power densities of 5 Wcm-2and 50 Wcm-2 with a pulse-averaged target power density up to 2 kWcm-2. The pulse durations were 50 μs and 200 μs. Our model calculations show that the to-substrate {{\\text{O}}2} inlet provides systematically lower compound fractions in the target surface layer and higher compound fractions in the substrate surface layer, compared with the to-target {{\\text{O}}2} inlet. The low compound fractions in the target surface layer (being approximately 10% at the deposition-averaged target power density of 50 Wcm-2 and the pulse duration of 200 μs) result in high deposition rates of the films produced, which are in agreement with experimental values.
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.
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
Model-based parametric study of frontostriatal abnormalities in schizophrenia patients
2010-01-01
Background Several studies have suggested that the activity of the prefrontal cortex (PFC) and the dopamine (DA) release in the striatum has an inverse relationship. One would attribute this relationship primarily to the circuitry comprised of the glutamatergic projection from the PFC to the striatum and the GABAergic projection from the striatum to the midbrain DA nucleus. However, this circuitry has not characterized satisfactorily yet, so that no quantitative analysis has ever been made on the activities of the PFC and the striatum and also the DA release in the striatum. Methods In this study, a system dynamics model of the corticostriatal system with dopaminergic innervations is constructed to describe the relationships between the activities of the PFC and the striatum and the DA release in the striatum. By taking published receptor imaging data from schizophrenia patients and healthy subjects into this model, this article analyzes the effects of striatal D2 receptor activation on the balance of the activity and neurotransmission in the frontostriatal system of schizophrenic patients in comparison with healthy controls. Results The model predicts that the suppressive effect by D2 receptors at the terminals of the glutamatergic afferents to the striatum from the PFC enhances the hypofrontality-induced elevation of striatal DA release by at most 83%. The occupancy-based estimation of the 'optimum' D2 receptor occupancy by antipsychotic drugs is 52%. This study further predicts that patients with lower PFC activity tend to have greater improvement of positive symptoms following antipsychotic medication. Conclusion This model-based parametric study would be useful for system-level analysis of the brains with psychiatric diseases. It will be able to make reliable prediction of clinical outcome when sufficient data will be available. PMID:20187970
An Evaluation of Parametric and Nonparametric Models of Fish Population Response.
Haas, Timothy C.; Peterson, James T.; Lee, Danny C.
1999-11-01
Predicting the distribution or status of animal populations at large scales often requires the use of broad-scale information describing landforms, climate, vegetation, etc. These data, however, often consist of mixtures of continuous and categorical covariates and nonmultiplicative interactions among covariates, complicating statistical analyses. Using data from the interior Columbia River Basin, USA, we compared four methods for predicting the distribution of seven salmonid taxa using landscape information. Subwatersheds (mean size, 7800 ha) were characterized using a set of 12 covariates describing physiography, vegetation, and current land-use. The techniques included generalized logit modeling, classification trees, a nearest neighbor technique, and a modular neural network. We evaluated model performance using out-of-sample prediction accuracy via leave-one-out cross-validation and introduce a computer-intensive Monte Carlo hypothesis testing approach for examining the statistical significance of landscape covariates with the non-parametric methods. We found the modular neural network and the nearest-neighbor techniques to be the most accurate, but were difficult to summarize in ways that provided ecological insight. The modular neural network also required the most extensive computer resources for model fitting and hypothesis testing. The generalized logit models were readily interpretable, but were the least accurate, possibly due to nonlinear relationships and nonmultiplicative interactions among covariates. Substantial overlap among the statistically significant (P<0.05) covariates for each method suggested that each is capable of detecting similar relationships between responses and covariates. Consequently, we believe that employing one or more methods may provide greater biological insight without sacrificing prediction accuracy.
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
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). PMID:27354189
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.
Edge Sharpness Assessment by Parametric Modeling: Application to Magnetic Resonance Imaging
Ahmad, R; Ding, Y; Simonetti, OP
2015-01-01
In biomedical imaging, edge sharpness is an important yet often overlooked image quality metric. In this work, a semi-automatic method to quantify edge sharpness in the presence of significant noise is presented with application to magnetic resonance imaging (MRI). The method is based on parametric modeling of image edges. First, an edge map is automatically generated and one or more edges-of-interest (EOI) are manually selected using graphical user interface. Multiple exclusion criteria are then enforced to eliminate edge pixels that are potentially not suitable for sharpness assessment. Second, at each pixel of the EOI, an image intensity profile is read along a small line segment that runs locally normal to the EOI. Third, the profiles corresponding to all EOI pixels are individually fitted with a sigmoid function characterized by four parameters, including one that represents edge sharpness. Last, the distribution of the sharpness parameter is used to quantify edge sharpness. For validation, the method is applied to simulated data as well as MRI data from both phantom imaging and cine imaging experiments. This method allows for fast, quantitative evaluation of edge sharpness even in images with poor signal-to-noise ratio. Although the utility of this method is demonstrated for MRI, it can be adapted for other medical imaging applications. PMID:26755895
2014-01-01
Background Early methods for estimating divergence times from gene sequence data relied on the assumption of a molecular clock. More sophisticated methods were created to model rate variation and used auto-correlation of rates, local clocks, or the so called “uncorrelated relaxed clock” where substitution rates are assumed to be drawn from a parametric distribution. In the case of Bayesian inference methods the impact of the prior on branching times is not clearly understood, and if the amount of data is limited the posterior could be strongly influenced by the prior. Results We develop a maximum likelihood method – Physher – that uses local or discrete clocks to estimate evolutionary rates and divergence times from heterochronous sequence data. Using two empirical data sets we show that our discrete clock estimates are similar to those obtained by other methods, and that Physher outperformed some methods in the estimation of the root age of an influenza virus data set. A simulation analysis suggests that Physher can outperform a Bayesian method when the real topology contains two long branches below the root node, even when evolution is strongly clock-like. Conclusions These results suggest it is advisable to use a variety of methods to estimate evolutionary rates and divergence times from heterochronous sequence data. Physher and the associated data sets used here are available online at http://code.google.com/p/physher/. PMID:25055743
NASA Astrophysics Data System (ADS)
Rastiello, Giuseppe; Federico, Francesco; Screpanti, Silvio
2015-09-01
Many abandoned room and pillar mines have been excavated not far from the surface of large areas of important European cities. In Rome, these excavations took place at shallow depths (3-15 m below the ground surface) in weak pyroclastic soft rocks. Many of these cavities have collapsed; others appear to be in a stable condition, although an appreciable percentage of their structural components (pillars, roofs, etc.) have shown increasing signs of distress from both the morphological and mechanical points of view. In this study, the stress-strain behaviour of soft rock pillars sustaining systems of cavities under vertical loads was numerically simulated, starting from the in situ initial conditions due to excavation of the cavities. The mechanical behaviour of the constituent material of the pillar was modelled according to the Modified Cam-Clay constitutive law (elasto-plastic with strain hardening). The influence of the pillar geometry (cross-section area, shape, and height) and mechanical parameters of the soft rock on the ultimate compressive strength of the pillar as a whole was parametrically investigated first. Based on the numerical results, an original relationship for pillar strength assessment was developed. Finally, the estimated pillar strengths according to the proposed formula and well-known formulations in the literature were compared.
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.
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.
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.
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.
Foreground Bias from Parametric Models of Far-IR Dust Emission
NASA Astrophysics Data System (ADS)
Kogut, A.; Fixsen, D. J.
2016-08-01
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 + foreground emission to precision 0.1% or better. The Rayleigh–Jeans approximation to the dust spectrum biases the fitted dust spectral index by {{Δ }}{β }d=0.2 and the inflationary B-mode amplitude by {{Δ }}r=0.03. Fitting the dust to a modified blackbody at a single temperature biases the best-fit CMB by {{Δ }}r\\gt 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 {{Δ }}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.
A semi-parametric model for lactation curves: development and application.
Madouasse, A; Browne, W J; Huxley, J N; Toni, F; Green, M J
2012-06-01
We propose a semi-parametric model for lactation curves that, along with stage of lactation, accounts for day of the year at milk recording and stage of gestation. Lactation is described as having 3 different phases defined by 2 change points of which the second is a function of gestation stage. Season of milk recording is modelled using cosine and sine functions. As an application, the model is used to estimate the association between intramammary infections (IMI) dynamics as measured by somatic cell count (SCC) over the dry period and the shape of the lactation curve. Milk recording data collected in 2128 herds from England and Wales between 2004 and 2007 were used in the analysis. From a random sample of 1000 of these herds, smoothed milk production was used to test the behaviour of the model and estimate model parameters. The first change point was set at 60 days in milk. The second change point was set at 100 days of gestation or 200 days in milk when the latter was not available. Using data from the 1128 remaining herds, multilevel models were then used to model individual test-day milk production within lactations within herds. Average milk production at 60 days in milk for cows of parities 1, 2, 3 and greater than 3 were 26.9 kg, 31.6 kg, 34.4 kg and 34.7 kg respectively and, after this stage, decreases in milk production per 100 days milk of lactation were 3.1 kg, 5.1 kg, 6.3 kg and 6.7 kg respectively. Compared to cows that had an SCC below 200,000 cells/mL on both the last milk recording in a lactation and the first milk recording in the following lactation, cows that had an SCC greater than 200,000 cells/mL on their first milk recording after calving had an estimated loss of milk production of between 216 and 518 kg depending on parity. These estimates demonstrate the impact of the dynamics of SCC during the dry period on milk production during the following lactation. PMID:22391019
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
Marmarelis, Vasilis Z.; Shin, Dae C.; Zhang, Yaping; Kautzky-Willer, Alexandra; Pacini, Giovanni; D’Argenio, David Z.
2013-01-01
Background: Modeling studies of the insulin–glucose relationship have mainly utilized parametric models, most notably the minimal model (MM) of glucose disappearance. This article presents results from the comparative analysis of the parametric MM and a nonparametric Laguerre based Volterra Model (LVM) applied to the analysis of insulin modified (IM) intravenous glucose tolerance test (IVGTT) data from a clinical study of gestational diabetes mellitus (GDM). Methods: An IM IVGTT study was performed 8 to 10 weeks postpartum in 125 women who were diagnosed with GDM during their pregnancy [population at risk of developing diabetes (PRD)] and in 39 control women with normal pregnancies (control subjects). The measured plasma glucose and insulin from the IM IVGTT in each group were analyzed via a population analysis approach to estimate the insulin sensitivity parameter of the parametric MM. In the nonparametric LVM analysis, the glucose and insulin data were used to calculate the first-order kernel, from which a diagnostic scalar index representing the integrated effect of insulin on glucose was derived. Results: Both the parametric MM and nonparametric LVM describe the glucose concentration data in each group with good fidelity, with an improved measured versus predicted r2 value for the LVM of 0.99 versus 0.97 for the MM analysis in the PRD. However, application of the respective diagnostic indices of the two methods does result in a different classification of 20% of the individuals in the PRD. Conclusions: It was found that the data based nonparametric LVM revealed additional insights about the manner in which infused insulin affects blood glucose concentration. PMID:23911176
Notake, Takashi; Nawata, Kouji; Kawamata, Hiroshi; Matsukawa, Takeshi; Qi, Feng; Minamide, Hiroaki
2012-11-01
We developed a difference frequency generation (DFG) source with an organic nonlinear optical crystal of DAST or BNA selectively excited by a dual-wavelength β-BaB(2)O(4) optical parametric oscillator (BBO-OPO). The dual-wavelength BBO-OPO can independently oscillate two lights with different wavelengths from 800 to 1800 nm in a cavity. THz-wave generation by using each organic crystal covers ultrawide range from 1 to 30 THz with inherent intensity dips by crystal absorption modes. The reduced outputs can be improved by switching over the crystals with adequately tuned pump wavelengths of the BBO-OPO. PMID:23187402
Kuklewicz, Christopher E.; Fiorentino, Marco; Messin, Gaetan; Wong, Franco N.C.; Shapiro, Jeffrey H.
2004-01-01
We have demonstrated a high-flux source of polarization-entangled photons using a type-II phase-matched periodically poled KTiOPO{sub 4} parametric down-converter in a collinearly propagating configuration. We have observed quantum interference between the single-beam down-converted photons with a visibility of 99% together with a measured coincidence flux of 300 s{sup -1}/mW of pump. The Clauser-Horne-Shimony-Holt version of Bell's inequality was violated with a value of 2.711{+-}0.017.
Incorporation of parametric factors into multilinear receptor model studies of Atlanta aerosol
NASA Astrophysics Data System (ADS)
Kim, Eugene; Hopke, Philip K.; Paatero, Pentti; Edgerton, Eric S.
In prior work with simulated data, ancillary variables including time resolved wind data were utilized in a multilinear model to successfully reduce rotational ambiguity and increase the number of resolved sources. In this study, time resolved wind and other data were incorporated into a model for the analysis of real measurement data. Twenty-four hour integrated PM 2.5 (particulate matter ⩽2.5 μm in aerodynamic diameter) compositional data were measured in Atlanta, GA between August 1998 and August 2000 (662 samples). A two-stage model that utilized 22 elemental species, two wind variables, and three time variables was used for this analysis. The model identified nine sources: sulfate-rich secondary aerosol I (54%), gasoline exhaust (15%), diesel exhaust (11%), nitrate-rich secondary aerosol (9%), metal processing (3%), wood smoke (3%), airborne soil (2%), sulfate-rich secondary aerosol II (2%), and the mixture of a cement kiln with a carbon-rich source (0.9%). The results of this study indicate that utilizing time resolved wind measurements aids to separate diesel exhaust from gasoline vehicle exhaust. For most of the sources, well-defined directional profiles, seasonal trends, and weekend effects were obtained.
Non-parametric temporal modeling of the hemodynamic response function via a liquid state machine.
Avesani, Paolo; Hazan, Hananel; Koilis, Ester; Manevitz, Larry M; Sona, Diego
2015-10-01
Standard methods for the analysis of functional MRI data strongly rely on prior implicit and explicit hypotheses made to simplify the analysis. In this work the attention is focused on two such commonly accepted hypotheses: (i) the hemodynamic response function (HRF) to be searched in the BOLD signal can be described by a specific parametric model e.g., double-gamma; (ii) the effect of stimuli on the signal is taken to be linearly additive. While these assumptions have been empirically proven to generate high sensitivity for statistical methods, they also limit the identification of relevant voxels to what is already postulated in the signal, thus not allowing the discovery of unknown correlates in the data due to the presence of unexpected hemodynamics. This paper tries to overcome these limitations by proposing a method wherein the HRF is learned directly from data rather than induced from its basic form assumed in advance. This approach produces a set of voxel-wise models of HRF and, as a result, relevant voxels are filterable according to the accuracy of their prediction in a machine learning framework. This approach is instantiated using a temporal architecture based on the paradigm of Reservoir Computing wherein a Liquid State Machine is combined with a decoding Feed-Forward Neural Network. This splits the modeling into two parts: first a representation of the complex temporal reactivity of the hemodynamic response is determined by a universal global "reservoir" which is essentially temporal; second an interpretation of the encoded representation is determined by a standard feed-forward neural network, which is trained by the data. Thus the reservoir models the temporal state of information during and following temporal stimuli in a feed-back system, while the neural network "translates" this data to fit the specific HRF response as given, e.g. by BOLD signal measurements in fMRI. An empirical analysis on synthetic datasets shows that the learning process can
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
NASA Technical Reports Server (NTRS)
Lua, Yuan J.; Liu, Wing K.; Belytschko, Ted
1992-01-01
A stochastic damage model for predicting the rupture of a brittle multiphase material is developed, based on the microcrack-macrocrack interaction. The model, which incorporates uncertainties in locations, orientations, and numbers of microcracks, characterizes damage by microcracking and fracture by macrocracking. A parametric study is carried out to investigate the change of the stress intensity at the macrocrack tip by the configuration of microcracks. The inherent statistical distribution of the fracture toughness arising from the intrinsic random nature of microcracks is explored using a statistical approach. For this purpose, a computer simulation model is introduced, which incorporates a statistical characterization of geometrical parameters of a random microcrack array.
NASA Astrophysics Data System (ADS)
Schröpfer, Gerold; Lorenz, Gunar; Rouvillois, Stéphane; Breit, Stephen
2010-06-01
This paper provides a brief summary of the state-of-the-art of MEMS-specific modeling techniques and describes the validation of new models for a parametric component library. Two recently developed 3D modeling tools are described in more detail. The first one captures a methodology for designing MEMS devices and simulating them together with integrated electronics within a standard electronic design automation (EDA) environment. The MEMS designer can construct the MEMS model directly in a 3D view. The resulting 3D model differs from a typical feature-based 3D CAD modeling tool in that there is an underlying behavioral model and parametric layout associated with each MEMS component. The model of the complete MEMS device that is shared with the standard EDA environment can be fully parameterized with respect to manufacturing- and design-dependent variables. Another recent innovation is a process modeling tool that allows accurate and highly realistic visualization of the step-by-step creation of 3D micro-fabricated devices. The novelty of the tool lies in its use of voxels (3D pixels) rather than conventional 3D CAD techniques to represent the 3D geometry. Case studies for experimental devices are presented showing how the examination of these virtual prototypes can reveal design errors before mask tape out, support process development before actual fabrication and also enable failure analysis after manufacturing.
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.
Halevy, A; Megidish, E; Dovrat, L; Eisenberg, H S; Becker, P; Bohatý, L
2011-10-10
We describe the full characterization of the biaxial nonlinear crystal BiB₃O₆ (BiBO) as a polarization entangled photon source using non-collinear type-II parametric down-conversion. We consider the relevant parameters for crystal design, such as cutting angles, polarization of the photons, effective nonlinearity, spatial and temporal walk-offs, crystal thickness and the effect of the pump laser bandwidth. Experimental results showing entanglement generation with high rates and a comparison to the well investigated β-BaB₂O₄ (BBO) crystal are presented as well. Changing the down-conversion crystal of a polarization entangled photon source from BBO to BiBO enhances the generation rate as if the pump power was increased by 2.5 times. Such an improvement is currently required for the generation of multiphoton entangled states. PMID:21997051
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 Astrophysics Data System (ADS)
Lange, Stefan; Rockel, Burkhardt; Volkholz, Jan; Bookhagen, Bodo
2015-05-01
This study provides a first thorough evaluation of the COnsortium for Small scale MOdeling weather prediction model in CLimate Mode (COSMO-CLM) over South America. Simulations are driven by ERA-Interim reanalysis data. Besides precipitation, we examine the surface radiation budget, cloud cover, 2 m temperatures, and the low level circulation. We evaluate against reanalysis data as well as observations from ground stations and satellites. Our analysis focuses on the sensitivity of results to the convective parametrization in comparison to their sensitivity to the representation of non-precipitating subgrid-scale clouds in the parametrization of radiation. Specifically, we compare simulations with a relative humidity versus a statistical subgrid-scale cloud scheme, in combination with convection schemes according to Tiedtke (Mon Weather Rev 117(8):1779-1800, 1989) and from the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) cycle 33r1. The sensitivity of simulated tropical precipitation to the parametrizations of convection and subgrid-scale clouds is of similar magnitude. We show that model runs with different subgrid-scale cloud schemes produce substantially different cloud ice and liquid water contents. This impacts surface radiation budgets, and in turn convection and precipitation. Considering all evaluated variables in synopsis, the model performs best with the (both non-default) IFS and statistical schemes for convection and subgrid-scale clouds, respectively. Despite several remaining deficiencies, such as a poor simulation of the diurnal cycle of precipitation or a substantial austral summer warm bias in northern Argentina, this new setup considerably reduces long-standing model biases, which have been a feature of COSMO-CLM across tropical domains.
Source modeling sleep slow waves
Murphy, Michael; Riedner, Brady A.; Huber, Reto; Massimini, Marcello; Ferrarelli, Fabio; Tononi, Giulio
2009-01-01
Slow waves are the most prominent electroencephalographic (EEG) feature of sleep. These waves arise from the synchronization of slow oscillations in the membrane potentials of millions of neurons. Scalp-level studies have indicated that slow waves are not instantaneous events, but rather they travel across the brain. Previous studies of EEG slow waves were limited by the poor spatial resolution of EEGs and by the difficulty of relating scalp potentials to the activity of the underlying cortex. Here we use high-density EEG (hd-EEG) source modeling to show that individual spontaneous slow waves have distinct cortical origins, propagate uniquely across the cortex, and involve unique subsets of cortical structures. However, when the waves are examined en masse, we find that there are diffuse hot spots of slow wave origins centered on the lateral sulci. Furthermore, slow wave propagation along the anterior−posterior axis of the brain is largely mediated by a cingulate highway. As a group, slow waves are associated with large currents in the medial frontal gyrus, the middle frontal gyrus, the inferior frontal gyrus, the anterior cingulate, the precuneus, and the posterior cingulate. These areas overlap with the major connectional backbone of the cortex and with many parts of the default network. PMID:19164756
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.
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.
Parametric Rietveld refinement
Stinton, Graham W.; Evans, John S. O.
2007-01-01
In this paper the method of parametric Rietveld refinement is described, in which an ensemble of diffraction data collected as a function of time, temperature, pressure or any other variable are fitted to a single evolving structural model. Parametric refinement offers a number of potential benefits over independent or sequential analysis. It can lead to higher precision of refined parameters, offers the possibility of applying physically realistic models during data analysis, allows the refinement of ‘non-crystallographic’ quantities such as temperature or rate constants directly from diffraction data, and can help avoid false minima. PMID:19461841
[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. PMID:21229773
PM SOURCE APPORTIONMENT/RECEPTOR MODELING
Source apportionment (receptor) models are mathematical procedures for identifying and quantifying the sources of ambient air pollutants and their effects at a site (the receptor), primarily on the basis of species concentration measurements at the receptor, and generally without...
NASA Astrophysics Data System (ADS)
Barrientos Barria, Jessica; Dobroc, Alexandre; Coudert-Alteirac, Hélène; Raybaut, Myriam; Cézard, Nicolas; Dherbecourt, Jean-Baptiste; Schmid, Thomas; Faure, Basile; Souhaité, Grégoire; Pelon, Jacques; Melkonian, Jean-Michel; Godard, Antoine; Lefebvre, Michel
2014-10-01
We report on the remote sensing capability of an integrated path differential absorption lidar (IPDIAL) instrument, for multi-species gas detection and monitoring in the 3.3-3.7 µm range. This instrument is based on an optical parametric source composed of a master oscillator-power amplifier scheme—whose core building block is a nested cavity optical parametric oscillator—emitting up to 10 µJ at 3.3 µm. Optical pumping is realized with an innovative single-frequency, 2-kHz repetition rate, nanosecond microchip laser, amplified up to 200 µJ per pulse in a single-crystal fiber amplifier. Simultaneous monitoring of mean atmospheric water vapor and methane concentrations was performed over several days by use of a topographic target, and water vapor concentration measurements show good agreement compared with an in situ hygrometer measurement. Performances of the IPDIAL instrument are assessed in terms of concentration measurement uncertainties and maximum remote achievable range.
NASA Astrophysics Data System (ADS)
Lee, Young-Hee; Ahn, Kwang-Deuk; Lee, Yong Hee
2016-06-01
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.
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.
Modeling of the vapor release from the LCROSS impact: Parametric dependencies
NASA Astrophysics Data System (ADS)
Hurley, Dana M.
2011-10-01
The Lunar Crater Observation and Sensing Satellite (LCROSS) mission included an intentional impact into the Cabeus crater, a permanently shadowed region near the Moon's south pole. The impact produced a vapor plume of volatile species liberated from the impact site. Using a Monte Carlo model to simulate the vapor plume expansion, this paper investigates the expansion as a function of the physical properties of the gas. For a thermal release scenario, the cloud expands with the highest density at the center, with the density dropping within the cloud in time as the cloud expands. When a significant non-thermal component to the velocity (a bulk speed) exists, the vapor expands as a hemispheric shell outward from the impact site. For heavier species, the high bulk velocity produces a hemisphere of higher density of gas that appears as a ring from above. For lighter gases like H2, the thermal velocity is on the same order as the bulk velocity. If the source is prolonged, the source rate is dominant in determining the local density, however. Gases produced by photodissociation have a prolonged source close to the impact site compared to promptly produced vapors.
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.
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 ...
Learning models for multi-source integration
Tejada, S.; Knoblock, C.A.; Minton, S.
1996-12-31
Because of the growing number of information sources available through the internet there are many cases in which information needed to solve a problem or answer a question is spread across several information sources. For example, when given two sources, one about comic books and the other about super heroes, you might want to ask the question {open_quotes}Is Spiderman a Marvel Super Hero?{close_quotes} This query accesses both sources; therefore, it is necessary to have information about the relationships of the data within each source and between sources to properly access and integrate the data retrieved. The SIMS information broker captures this type of information in the form of a model. All the information sources map into the model providing the user a single interface to multiple sources.
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 Astrophysics Data System (ADS)
Kataria, Tiffany; Heggy, E.; Clifford, S. M.; Lasue, J.; Kofman, W.
2008-09-01
The Comet Nucleus Sounding Experiment by Radiowave Transmission (CONSERT) onboard the ROSETTA mission will probe the nucleus of comet 67P/Churyumov-Gerasimenko in 2014. The variations in signal attenuations to be observed in the 90 MHz-radar tomographies is expected to depend mainly on the three-dimensional variations of the dielectrical properties of the cometary material as a function of porosity, temperature, and mineralogical composition. To explore the parametric space associated with the variations of these parameters and their impacts on the observed dielectrical properties inverted from the CONSERT data, we use the current state of knowledge from the observations made by Tempel-1 and Hayabusa to develop parametric dielectric models of possible internal structures of 67P/C-G. The first model reflects the layered-pile structure proposed by Belton et al. (2007), and the second reflects the rubble-pile model proposed by Weissman et al. (1986). The relative complex dielectric permittivities assigned to each dielectric model are based on laboratory measurements of chondrite dust/water ice mixtures, and are varied as a function of dust fraction, porosity and temperature. For the layered pile model, where porosity is assumed constant at the level of 70% and temperature 20m below the surface is 40 K, the dielectric constant varies mainly as a function of dust fraction, ranging between 4.386-i0.0121 in the pure surface dust mantle to 2.081-i0.000182 in one of the inner ice-rich layers. The modeled dielectric permittivities are consistent with the expected deep penetration of the CONSERT wave through the nucleus. Preliminary results suggest that the changes in the physical properties of the nucleus induce substantial variation in the dielectric properties of cometary material that can be identified in the radar tomography.
Gal, Yaniv; Mehnert, Andrew; Bradley, Andrew; McMahon, Kerry; Crozier, Stuart
2007-01-01
This paper presents an empirical evaluation of the goodness-of-fit (GOF) of four parametric models of contrast enhancement for dynamic resonance imaging of the breast: the Tofts, Brix, and Hayton pharmacokinetic models, and a novel empiric model. The goodness-of-fit of each model was evaluated with respect to: (i) two model-fitting algorithms (Levenberg-Marquardt and Nelder-Mead) and two fitting tolerances; and (ii) temporal resolution. In the first case the GOF was measured using data from three dynamic contrast-enhanced (DCE) MRI data sets from routine clinical examinations: one case with benign enhancement, one with malignant enhancement, and one with normal findings. Results are presented for fits to both the whole breast volume and to a selected region of interest. In the second case the GOF was measured by first fitting the models to several temporally sub-sampled versions of a custom high temporal resolution data set (subset of the breast volume containing a malignant lesion), and then comparing the fitted results to the original full temporal resolution data. Our results demonstrate that under the various optimization conditions considered, in general, both the proposed empiric model and the Hayton model fit the data equally well and that both of these models fit the data better than the Tofts and Brix models. PMID:18001891
Kildemo, Morten; Maria, Jérôme; Ellingsen, Pål G; Aas, Lars M S
2013-07-29
Decomposition methods have been applied to in-plane Mueller matrix ellipsometric scattering data of the Spectralon reflectance standard. Data were measured at the wavelengths 532 nm and 1500 nm, using an achromatic optimal Mueller matrix scatterometer applying a photomultiplier tube and a high gain InGaAs detector for the two wavelengths. A parametric model with physical significance was deduced through analysis of the product decomposed matrices. It is found that when the data are analyzed as a function of the scattering angle, similar to particle scattering, the matrix elements are largely independent of incidence angle. To the first order, we propose that a Guassian lineshape is appropriate to describe the polarization index, while the decomposed diagonal elements of the retardance matrix have a form resembling Rayleigh single scattering. New models are proposed for the off diagonal elements of the measured Mueller matrix. PMID:23938723
Weisheimer, Antje; Corti, Susanna; Palmer, Tim; Vitart, Frederic
2014-06-28
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
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
NASA Astrophysics Data System (ADS)
Jiang, Jin-Wu
2015-08-01
We propose parametrizing the Stillinger-Weber potential for covalent materials starting from the valence force-field model. All geometrical parameters in the Stillinger-Weber potential are determined analytically according to the equilibrium condition for each individual potential term, while the energy parameters are derived from the valence force-field model. This parametrization approach transfers the accuracy of the valence force field model to the Stillinger-Weber potential. Furthermore, the resulting Stilliinger-Weber potential supports stable molecular dynamics simulations, as each potential term is at an energy-minimum state separately at the equilibrium configuration. We employ this procedure to parametrize Stillinger-Weber potentials for single-layer MoS2 and black phosphorous. The obtained Stillinger-Weber potentials predict an accurate phonon spectrum and mechanical behaviors. We also provide input scripts of these Stillinger-Weber potentials used by publicly available simulation packages including GULP and LAMMPS.
Perceptual evaluation of voice source models.
Kreiman, Jody; Garellek, Marc; Chen, Gang; Alwan, Abeer; Gerratt, Bruce R
2015-07-01
Models of the voice source differ in their fits to natural voices, but it is unclear which differences in fit are perceptually salient. This study examined the relationship between the fit of five voice source models to 40 natural voices, and the degree of perceptual match among stimuli synthesized with each of the modeled sources. Listeners completed a visual sort-and-rate task to compare versions of each voice created with the different source models, and the results were analyzed using multidimensional scaling. Neither fits to pulse shapes nor fits to landmark points on the pulses predicted observed differences in quality. Further, the source models fit the opening phase of the glottal pulses better than they fit the closing phase, but at the same time similarity in quality was better predicted by the timing and amplitude of the negative peak of the flow derivative (part of the closing phase) than by the timing and/or amplitude of peak glottal opening. Results indicate that simply knowing how (or how well) a particular source model fits or does not fit a target source pulse in the time domain provides little insight into what aspects of the voice source are important to listeners. PMID:26233000
NASA Astrophysics Data System (ADS)
Anurose, T. J.; Subrahamanyam, D. Bala
2013-06-01
We discuss the impact of the differential treatment of the roughness lengths for momentum and heat (z_{0m} and z_{0h}) in the flux parametrization scheme of the high-resolution regional model (HRM) for a heterogeneous terrain centred around Thiruvananthapuram, India (8.5°N, 76.9°E). The magnitudes of sensible heat flux ( H) obtained from HRM simulations using the original parametrization scheme differed drastically from the concurrent in situ observations. With a view to improving the performance of this parametrization scheme, two distinct modifications are incorporated: (1) In the first method, a constant value of 100 is assigned to the z_{0m}/z_{0h} ratio; (2) and in the second approach, this ratio is treated as a function of time. Both these modifications in the HRM model showed significant improvements in the H simulations for Thiruvananthapuram and its adjoining regions. Results obtained from the present study provide a first-ever comparison of H simulations using the modified parametrization scheme in the HRM model with in situ observations for the Indian coastal region, and suggest a differential treatment of z_{0m} and z_{0h} in the flux parametrization scheme.
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
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. PMID:23380856
NASA Astrophysics Data System (ADS)
Branch, Allan C.
1998-01-01
Parametric mapping (PM) lies midway between older and proven artificial landmark based guidance systems and yet to be realized vision based guidance systems. It is a simple yet effective natural landmark recognition system offering freedom from the need for enhancements to the environment. Development of PM systems can be inexpensive and rapid and they are starting to appear in commercial and industrial applications. Together with a description of the structural framework developed to generically describe robot mobility, this paper illustrates clearly the parts of any mobile robot navigation and guidance system and their interrelationships. Among other things, the importance of the richness of the reference map, and not necessarily the sensor map, is introduced, the benefits of dynamic path planners to alleviate the need for separate object avoidance, and the independence of the PM system to the type of sensor input is shown.
IMM filtering on parametric data for multi-sensor fusion
NASA Astrophysics Data System (ADS)
Shafer, Scott; Owen, Mark W.
2014-06-01
In tracking, many types of sensor data can be obtained and utilized to distinguish a particular target. Commonly, kinematic information is used for tracking, but this can be combined with identification attributes and parametric information passively collected from the targets emitters. Along with the standard tracking process (predict, associate, score, update, and initiate) that operates in all kinematic trackers, parametric data can also be utilized to perform these steps and provide a means for feature fusion. Feature fusion, utilizing parametrics from multiple sources, yields a rich data set providing many degrees of freedom to separate and correlate data into appropriate tracks. Parametric radar data can take on many dynamics to include: stable, agile, jitter, and others. By utilizing a running sample mean and sample variance a good estimate of radar parametrics is achieved. However, when dynamics are involved, a severe lag can occur and a non-optimal estimate is achieved. This estimate can yield incorrect associations in feature space and cause track fragmentation or miscorrelation. In this paper we investigate the accuracy of the interacting multiple model (IMM) filter at estimating the first and second moments of radar parametrics. The algorithm is assessed by Monte Carlo simulation and compared against a running sample mean/variance technique. We find that the IMM approach yields a better result due to its ability to quickly adapt to dynamical systems with the proper model and tuning.
Results on Levy stable parametrizations of Bose-Einstein Correlations
Novak, Tamas
2006-04-11
Bose-Einstein correlations of identical charged-pion pairs produced in hadronic Z decays are analyzed in terms of various parametrizations. A good description is achieved using Levy stable distributions. The source function is reconstructed with the help of the {tau}-model.
Quarles, C. Derrick; Carado, Anthony J.; Barinaga, Charles J.; Koppenaal, David W.; Marcus, R. Kenneth
2012-01-01
A new, low power ionization source for the elemental analysis of aqueous solutions has recently been described. The liquid sampling-atmospheric pressure glow discharge (LS-APGD) source operates at relatively low currents (<20 mA) and solution flow rates (<50 μL min-1), yielding a relatively simple alternative for atomic mass spectrometry applications. The LS-APGD has been interfaced to what is otherwise an organic, LC-MS mass analyzer, the Thermo Scientific Exactive Orbitrap without any modifications; other than removing the electrospray ionization (ESI) source supplied with that instrument. A glow discharge is initiated between the surface of the test solution exiting a glass capillary and a metallic counter electrode mounted at a 90° angle and separated by a distance of ~5 mm. As with any plasma-based ionization source, there are key discharge operation and ion sampling parameters that affect the intensity and composition of the derived mass spectra; including signal-to-background ratios. We describe here a preliminary parametric evaluation of the roles of discharge current, solution flow rate, argon sheath gas flow rate, and ion sampling distance as they apply on this mass analyzer system. A cursive evaluation of potential matrix effects due to the presence of easily ionized elements (EIEs) indicate that sodium concentrations of up to 500 μg mL-1 generally cause suppressions of less than 50%, dependant upon the analyte species. Based on the results of this series of studies, preliminary limits of detection (LOD) have been established through the generation of calibration functions. Whilst solution-based concentrations LOD levels of 0.02 – 2 μg mL-1 3 are not impressive on the surface, the fact that they are determined via discrete 5 μL injections leads to mass-based detection limits at picogram to singlenanogram levels. The overhead costs associated with source operation (10 W d.c. power, solution flow rates of <50 μL min-1, and gas flow rates <10 mL min
Quarles, C Derrick; Carado, Anthony J; Barinaga, Charles J; Koppenaal, David W; Marcus, R Kenneth
2012-01-01
A new, low-power ionization source for the elemental analysis of aqueous solutions has recently been described. The liquid sampling-atmospheric pressure glow discharge (LS-APGD) source operates at relatively low currents (<20 mA) and solution flow rates (<50 μL min(-1)), yielding a relatively simple alternative for atomic mass spectrometry applications. The LS-APGD has been interfaced to what is otherwise an organic, LC-MS mass analyzer, the Thermo Scientific Exactive Orbitrap without any modifications, other than removing the electrospray ionization source supplied with that instrument. A glow discharge is initiated between the surface of the test solution exiting a glass capillary and a metallic counter electrode mounted at a 90° angle and separated by a distance of ~5 mm. As with any plasma-based ionization source, there are key discharge operation and ion sampling parameters that affect the intensity and composition of the derived mass spectra, including signal-to-background ratios. We describe here a preliminary parametric evaluation of the roles of discharge current, solution flow rate, argon sheath gas flow rate, and ion sampling distance as they apply on this mass analyzer system. A cursive evaluation of potential matrix effects due to the presence of easily ionized elements indicate that sodium concentrations of up to 50 μg mL(-1) generally cause suppressions of less than 50%, dependant upon the analyte species. Based on the results of this series of studies, preliminary limits of detection (LOD) have been established through the generation of calibration functions. While solution-based concentration LOD levels of 0.02-2 μg mL(-1) are not impressive on the surface, the fact that they are determined via discrete 5 μL injections leads to mass-based detection limits at picogram to single-nanogram levels. The overhead costs associated with source operation (10 W d.c. power, solution flow rates of <50 μL min(-1), and gas flow rates <10 mL min(-1)) are
Ding, Li; Mariñas, Benito J; Schideman, Lance C; Snoeyink, Vernon L; Li, Qilin
2006-01-01
Natural organic matter (NOM) hinders adsorption of trace organic compounds on powdered activated carbon (PAC) via two dominant mechanisms: direct site competition and pore blockage. COMPSORB, a three-component model that incorporates these two competitive mechanisms, was developed in a previous study to describe the removal of trace contaminants in continuous-flow hybrid PAC adsorption/membrane filtration systems. Synthetic solutions containing two model compounds as surrogates for NOM were used in the original study to elucidate competitive effects and to verify the model. In the present study, a quantitative method to characterize the components of NOM that are responsible for competitive adsorption effects in natural water was developed to extend the application of COMPSORB to natural water systems. Using batch adsorption data, NOM was differentiated into two fictive fractions, representing the strongly competing and pore blocking components, and each was treated as a single compound. The equilibrium and kinetic parameters for these fictive compounds were calculated using simplified adsorption models. This parametrization procedure was carried out on two different natural waters, and the model was verified with experimental data obtained for atrazine removal from natural water in a PAC/membrane system. The model predicted the system performance reasonably well and highlighted the importance of considering both direct site competition and pore blockage effects of NOM in modeling these systems. PMID:16433371
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.
Tufto, Jarle; Ringsby, Thor-Harald; Dhondt, André A; Adriaensen, Frank; Matthysen, Erik
2005-01-01
Natal dispersal capture-recapture data from five fragmented populations of house sparrows, great tits, and blue tits were analyzed using maximum likelihood methods. A new two-parametric distribution was constructed that includes four distributions previously used as special cases in the literature. Dispersal standard deviations were estimated at 22.9 km for the house sparrows and ranged from 0.66 to 4.4 km for the tits. Female great tits and blue tits dispersed consistently further than males. Estimates of the shape parameter of the dispersal distribution ranged from 0.66 to 2.27, indicating strong to moderately leptokurtic dispersal displacements. There were significant effects of density on local immigration rates and a consistent tendency for immigration rates to depend underproportionally on local densities. Potential implications of the shape of the dispersal distribution for the spread of invading organisms were investigated and compared with previous results. It is shown that the wave speed, for a given dispersal standard deviation, depends only to some extent on leptokurtosis, provided that the intrinsic growth rate of the population is moderate or small. In estimating the dispersal standard deviation, however, incorrect assumptions about the degree of leptokurtosis can lead to a large bias in estimation and predictions. PMID:15729635
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. PMID:26272992
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
2015-09-01
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. PMID:26388367
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.
Constant-sound-speed parametrization for Nambu-Jona-Lasinio models of quark matter in hybrid stars
NASA Astrophysics Data System (ADS)
Ranea-Sandoval, Ignacio F.; Han, Sophia; Orsaria, Milva G.; Contrera, Gustavo A.; Weber, Fridolin; Alford, Mark G.
2016-04-01
The discovery of pulsars as heavy as 2 solar masses has led astrophysicists to rethink the core compositions of neutron stars, ruling out many models for the nuclear equations of state (EoS). We explore the hybrid stars that occur when hadronic matter is treated in a relativistic mean-field approximation and quark matter is modeled by three-flavor local and nonlocal Nambu-Jona-Lasinio (NJL) models with repulsive vector interactions. The NJL models typically yield equations of state that feature a first-order transition to quark matter. Assuming that the quark-hadron surface tension is high enough to disfavor mixed phases and restricting to EoSs that allow stars to reach 2 solar masses, we find that the appearance of the quark-matter core either destabilizes the star immediately (this is typical for nonlocal NJL models) or leads to a very short hybrid star branch in the mass-radius relation (this is typical for local NJL models). Using the constant-sound-speed parametrization we can see that the reason for the near absence of hybrid stars is that the transition pressure is fairly high and the transition is strongly first order.
Tagging Water Sources in Atmospheric Models
NASA Technical Reports Server (NTRS)
Bosilovich, M.
2003-01-01
Tagging of water sources in atmospheric models allows for quantitative diagnostics of how water is transported from its source region to its sink region. In this presentation, we review how this methodology is applied to global atmospheric models. We will present several applications of the methodology. In one example, the regional sources of water for the North American Monsoon system are evaluated by tagging the surface evaporation. In another example, the tagged water is used to quantify the global water cycling rate and residence time. We will also discuss the need for more research and the importance of these diagnostics in water cycle studies.
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
High brightness EUV light source modeling
NASA Astrophysics Data System (ADS)
Zakharov, Sergey V.; Choi, Peter; Zakharov, Vasily S.
2010-04-01
EUV source for actinic mask metrology, particularly for defect inspection, requires extremely high brightness. The selfabsorption of radiation limits the in-band EUV radiance of the source plasma and the etendue constraint limits the usable power of a conventional single unit EUV source. Theoretical study and numerical modelling has been carried out to address fundamental issues in tin and xenon plasmas and to optimize the performance of EUV sources. The highly ionized xenon plasma in the presence of fast electrons demonstrates the enhanced radiance. Theoretical models and robust modelling tools are being further developed under an international collaboration project FIRE in the frame of the EU FP7 IAPP program. NANO-UV is delivering a new generation of EUV light source with an intrinsic photon collector. Extensive numerical modelling has provided basic numbers to select the optimal regimes for tin and xenon based source operation. From these designs, a family of specially configured multiplexed source structures is being introduced to address the mask metrology needs.
Characterization and modeling of the heat source
Glickstein, S.S.; Friedman, E.
1993-10-01
A description of the input energy source is basic to any numerical modeling formulation designed to predict the outcome of the welding process. The source is fundamental and unique to each joining process. The resultant output of any numerical model will be affected by the initial description of both the magnitude and distribution of the input energy of the heat source. Thus, calculated weld shape, residual stresses, weld distortion, cooling rates, metallurgical structure, material changes due to excessive temperatures and potential weld defects are all influenced by the initial characterization of the heat source. Understandings of both the physics and the mathematical formulation of these sources are essential for describing the input energy distribution. This section provides a brief review of the physical phenomena that influence the input energy distributions and discusses several different models of heat sources that have been used in simulating arc welding, high energy density welding and resistance welding processes. Both simplified and detailed models of the heat source are discussed.
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.; 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 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
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
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.
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
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
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.
ON THE ROBUSTNESS OF z = 0-1 GALAXY SIZE MEASUREMENTS THROUGH MODEL AND NON-PARAMETRIC FITS
Mosleh, Moein; Franx, Marijn; Williams, Rik J.
2013-11-10
We present the size-stellar mass relations of nearby (z = 0.01-0.02) Sloan Digital Sky Survey galaxies, for samples selected by color, morphology, Sérsic index n, and specific star formation rate. Several commonly employed size measurement techniques are used, including single Sérsic fits, two-component Sérsic models, and a non-parametric method. Through simple simulations, we show that the non-parametric and two-component Sérsic methods provide the most robust effective radius measurements, while those based on single Sérsic profiles are often overestimates, especially for massive red/early-type galaxies. Using our robust sizes, we show for all sub-samples that the mass-size relations are shallow at low stellar masses and steepen above ∼3-4 × 10{sup 10} M{sub ☉}. The mass-size relations for galaxies classified as late-type, low-n, and star-forming are consistent with each other, while blue galaxies follow a somewhat steeper relation. The mass-size relations of early-type, high-n, red, and quiescent galaxies all agree with each other but are somewhat steeper at the high-mass end than previous results. To test potential systematics at high redshift, we artificially redshifted our sample (including surface brightness dimming and degraded resolution) to z = 1 and re-fit the galaxies using single Sérsic profiles. The sizes of these galaxies before and after redshifting are consistent and we conclude that systematic effects in sizes and the size-mass relation at z ∼ 1 are negligible. Interestingly, since the poorer physical resolution at high redshift washes out bright galaxy substructures, single Sérsic fitting appears to provide more reliable and unbiased effective radius measurements at high z than for nearby, well-resolved galaxies.
NASA Astrophysics Data System (ADS)
Luo, Zhiwen; Li, Yuguo
2011-10-01
This paper reports the results of a parametric CFD study on idealized city models to investigate the potential of slope flow in ventilating a city located in a mountainous region when the background synoptic wind is absent. Examples of such a city include Tokyo in Japan, Los Angeles and Phoenix in the US, and Hong Kong. Two types of buoyancy-driven flow are considered, i.e., slope flow from the mountain slope (katabatic wind at night and anabatic wind in the daytime), and wall flow due to heated/cooled urban surfaces. The combined buoyancy-driven flow system can serve the purpose of dispersing the accumulated urban air pollutants when the background wind is weak or absent. The microscopic picture of ventilation performance within the urban structures was evaluated in terms of air change rate (ACH) and age of air. The simulation results reveal that the slope flow plays an important role in ventilating the urban area, especially in calm conditions. Katabatic flow at night is conducive to mitigating the nocturnal urban heat island. In the present parametric study, the mountain slope angle and mountain height are assumed to be constant, and the changing variables are heating/cooling intensity and building height. For a typical mountain of 500 m inclined at an angle of 20° to the horizontal level, the interactive structure is very much dependent on the ratio of heating/cooling intensity as well as building height. When the building is lower than 60 m, the slope wind dominates. When the building is as high as 100 m, the contribution from the urban wall flow cannot be ignored. It is found that katabatic wind can be very beneficial to the thermal environment as well as air quality at the pedestrian level. The air change rate for the pedestrian volume can be as high as 300 ACH.
Das, Shiva K. . E-mail: shiva.das@duke.edu; Zhou Sumin; Zhang, Junan; Yin, F.-F.; Dewhirst, Mark W.; Marks, Lawrence B.
2007-07-15
Purpose: To develop and test a model to predict for lung radiation-induced Grade 2+ pneumonitis. Methods and Materials: The model was built from a database of 234 lung cancer patients treated with radiotherapy (RT), of whom 43 were diagnosed with pneumonitis. The model augmented the predictive capability of the parametric dose-based Lyman normal tissue complication probability (LNTCP) metric by combining it with weighted nonparametric decision trees that use dose and nondose inputs. The decision trees were sequentially added to the model using a 'boosting' process that enhances the accuracy of prediction. The model's predictive capability was estimated by 10-fold cross-validation. To facilitate dissemination, the cross-validation result was used to extract a simplified approximation to the complicated model architecture created by boosting. Application of the simplified model is demonstrated in two example cases. Results: The area under the model receiver operating characteristics curve for cross-validation was 0.72, a significant improvement over the LNTCP area of 0.63 (p = 0.005). The simplified model used the following variables to output a measure of injury: LNTCP, gender, histologic type, chemotherapy schedule, and treatment schedule. For a given patient RT plan, injury prediction was highest for the combination of pre-RT chemotherapy, once-daily treatment, female gender and lowest for the combination of no pre-RT chemotherapy and nonsquamous cell histologic type. Application of the simplified model to the example cases revealed that injury prediction for a given treatment plan can range from very low to very high, depending on the settings of the nondose variables. Conclusions: Radiation pneumonitis prediction was significantly enhanced by decision trees that added the influence of nondose factors to the LNTCP formulation.
NASA Astrophysics Data System (ADS)
Ivanova, Violeta M.; Sousa, Rita; Murrihy, Brian; Einstein, Herbert H.
2014-06-01
This paper presents results from research conducted at MIT during 2010-2012 on modeling of natural rock fracture systems with the GEOFRAC three-dimensional stochastic model. Following a background summary of discrete fracture network models and a brief introduction of GEOFRAC, the paper provides a thorough description of the newly developed mathematical and computer algorithms for fracture intensity, aperture, and intersection representation, which have been implemented in MATLAB. The new methods optimize, in particular, the representation of fracture intensity in terms of cumulative fracture area per unit volume, P32, via the Poisson-Voronoi Tessellation of planes into polygonal fracture shapes. In addition, fracture apertures now can be represented probabilistically or deterministically whereas the newly implemented intersection algorithms allow for computing discrete pathways of interconnected fractures. In conclusion, results from a statistical parametric study, which was conducted with the enhanced GEOFRAC model and the new MATLAB-based Monte Carlo simulation program FRACSIM, demonstrate how fracture intensity, size, and orientations influence fracture connectivity.
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.
Chen, Liu Qi; Randtke, Edward A.; Jones, Kyle M.; Moon, Brianna F.; Howison, Christine M.; Pagel, Mark D.
2016-01-01
Purpose We aimed to develop pixelwise maps of tumor acidosis to aid in evaluating extracellular tumor pH (pHe) in cancer biology. Procedures MCF-7 and MDA-MB-231 mouse models were imaged during a longitudinal study. AcidoCEST MRI and a series of image processing methods were used to produce parametric maps of tumor pHe, and tumor pHe was also measured with a pH microsensor. Results Sufficient contrast-to-noise for producing pHe maps was achieved by using standard image processing methods. A comparison of pHe values measured with acidoCEST MRI and a pH microsensor showed that acidoCEST MRI measured tumor pHe with an accuracy of 0.034 pH units. The MCF-7 tumor model was found to be more acidic compared to the MDA-MB-231 tumor model. The pHe was not related to tumor size during the longitudinal study. Conclusions These results show that acidoCEST MRI can create pixelwise tumor pHe maps of mouse models of cancer. PMID:25622809
Lehman, L.; Brown, T. P.
2002-02-26
The controls on the potentiometric surface and temperature distribution at Yucca Mountain have long been thought to be related to major fault zones. The exact way the faults influence these distributions has been somewhat elusive. The parametric studies discussed in this paper show that the fault zone x, y and z permeability tensors, as well as the alignment of the fault zone in relation to the flow field (1), are major contributing factors in the pressure and temperature distributions. A series of runs were conducted for the State of Nevada with a 3-dimensional model utilizing the AT2VOC version of the A-TOUGH code (2),(3). The runs were conducted under steady state conditions and utilized fully coupled heat and flow conditions. The model setup and boundary conditions are fully described. Comparisons were done with varying degrees of anisotropic permeability ratios in the fault zones. The resulting temperature and pressure profiles are compared. The model, while simple, allowed us to examine the relationship of the head and temperature distributions to the position and permeability of major fault zones. It is our conclusion that the major faults included in this model do significantly affect the observed head and temperature distributions. Performance Assessments currently may not reflect actual doses at the Compliance boundary due to the potential for radionuclide flow to be captured in the Ghost Dance Fault and be transported primarily south with little dilution and dispersion.
Edwin A. Harvego; Michael G. McKellar; James E. O'Brien; J. Stephen Herring
2009-09-01
High Temperature Electrolysis (HTE), when coupled to an advanced nuclear reactor capable of operating at reactor outlet temperatures of 800 °C to 950 °C, has the potential to efficiently produce the large quantities of hydrogen needed to meet future energy and transportation needs. To evaluate the potential benefits of nuclear-driven hydrogen production, the UniSim process analysis software was used to evaluate different reactor concepts coupled to a reference HTE process design concept. The reference HTE concept included an Intermediate Heat Exchanger and intermediate helium loop to separate the reactor primary system from the HTE process loops and additional heat exchangers to transfer reactor heat from the intermediate loop to the HTE process loops. The two process loops consisted of the water/steam loop feeding the cathode side of a HTE electrolysis stack, and the sweep gas loop used to remove oxygen from the anode side. The UniSim model of the process loops included pumps to circulate the working fluids and heat exchangers to recover heat from the oxygen and hydrogen product streams to improve the overall hydrogen production efficiencies. The reference HTE process loop model was coupled to separate UniSim models developed for three different advanced reactor concepts (a high-temperature helium cooled reactor concept and two different supercritical CO2 reactor concepts). Sensitivity studies were then performed to evaluate the affect of reactor outlet temperature on the power cycle efficiency and overall hydrogen production efficiency for each of the reactor power cycles. The results of these sensitivity studies showed that overall power cycle and hydrogen production efficiencies increased with reactor outlet temperature, but the power cycles producing the highest efficiencies varied depending on the temperature range considered.
NASA Astrophysics Data System (ADS)
Meneguz, Elena; Thomson, David; Witham, Claire; Kusmierczyk-Michulec, Jolanta
2015-04-01
NAME is a Lagrangian atmospheric dispersion model used by the Met Office to predict the dispersion of both natural and man-made contaminants in the atmosphere, e.g. volcanic ash, radioactive particles and chemical species. Atmospheric convection is responsible for transport and mixing of air resulting in a large exchange of heat and energy above the boundary layer. Although convection can transport material through the whole troposphere, convective clouds have a small horizontal length scale (of the order of few kilometres). Therefore, for large-scale transport the horizontal scale on which the convection exists is below the global NWP resolution used as input to NAME and convection must be parametrized. Prior to the work presented here, the enhanced vertical mixing generated by non-resolved convection was reproduced by randomly redistributing Lagrangian particles between the cloud base and cloud top with probability equal to 1/25th of the NWP predicted convective cloud fraction. Such a scheme is essentially diffusive and it does not make optimal use of all the information provided by the driving meteorological model. To make up for these shortcomings and make the parametrization more physically based, the convection scheme has been recently revised. The resulting version, presented in this paper, is now based on the balance equation between upward, entrainment and detrainment fluxes. In particular, upward mass fluxes are calculated with empirical formulas derived from Cloud Resolving Models and using the NWP convective precipitation diagnostic as closure. The fluxes are used to estimate how many particles entrain, move upward and detrain. Lastly, the scheme is completed by applying a compensating subsidence flux. The performance of the updated convection scheme is benchmarked against available observational data of passive tracers. In particular, radioxenon is a noble gas that can undergo significant long range transport: this study makes use of observations of
SWQM: Source Water Quality Modeling Software
2008-01-08
The Source Water Quality Modeling software (SWQM) simulates the water quality conditions that reflect properties of water generated by water treatment facilities. SWQM consists of a set of Matlab scripts that model the statistical variation that is expected in a water treatment facilitys water, such as pH and chlorine levels.
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
Industrial Source Complex (ISC) dispersion model. Software
Schewe, G.; Sieurin, E.
1980-01-01
The model updates various EPA dispersion model algorithms and combines them in two computer programs that can be used to assess the air quality impact of emissions from the wide variety of source types associated with an industrial source complex. The ISC Model short-term program ISCST, an updated version of the EPA Single Source (CRSTER) Model uses sequential hourly meteorological data to calculate values of average concentration or total dry deposition for time periods of 1, 2, 3, 4, 6, 8, 12 and 24 hours. Additionally, ISCST may be used to calculate 'N' is 366 days. The ISC Model long-term computer program ISCLT, a sector-averaged model that updates and combines basic features of the EPA Air Quality Display Model (AQDM) and the EPA Climatological Dispersion Model (CDM), uses STAR Summaries to calculate seasonal and/or annual average concentration or total deposition values. Both the ISCST and ISCLT programs make the same basic dispersion-model assumptions. Additionally, both the ISCST and ISCLT programs use either a polar or a Cartesian receptor grid...Software Description: The programs are written in the FORTRAN IV programming language for implementation on a UNIVAC 1110 computer and also on medium-to-large IBM or CDC systems. 65,000k words of core storage are required to operate the model.
Bayesian Kinematic Finite Fault Source Models (Invited)
NASA Astrophysics Data System (ADS)
Minson, S. E.; Simons, M.; Beck, J. L.
2010-12-01
Finite fault earthquake source models are inherently under-determined: there is no unique solution to the inverse problem of determining the rupture history at depth as a function of time and space when our data are only limited observations at the Earth's surface. Traditional inverse techniques rely on model constraints and regularization to generate one model from the possibly broad space of all possible solutions. However, Bayesian methods allow us to determine the ensemble of all possible source models which are consistent with the data and our a priori assumptions about the physics of the earthquake source. Until now, Bayesian techniques have been of limited utility because they are computationally intractable for problems with as many free parameters as kinematic finite fault models. We have developed a methodology called Cascading Adaptive Tempered Metropolis In Parallel (CATMIP) which allows us to sample very high-dimensional problems in a parallel computing framework. The CATMIP algorithm combines elements of simulated annealing and genetic algorithms with the Metropolis algorithm to dynamically optimize the algorithm's efficiency as it runs. We will present synthetic performance tests of finite fault models made with this methodology as well as a kinematic source model for the 2007 Mw 7.7 Tocopilla, Chile earthquake. This earthquake was well recorded by multiple ascending and descending interferograms and a network of high-rate GPS stations whose records can be used as near-field seismograms.
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…
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.
Shah, Anoop D; Bartlett, Jonathan W; Carpenter, James; Nicholas, Owen; Hemingway, Harry
2014-03-15
Multivariate imputation by chained equations (MICE) is commonly used for imputing missing data in epidemiologic research. The "true" imputation model may contain nonlinearities which are not included in default imputation models. Random forest imputation is a machine learning technique which can accommodate nonlinearities and interactions and does not require a particular regression model to be specified. We compared parametric MICE with a random forest-based MICE algorithm in 2 simulation studies. The first study used 1,000 random samples of 2,000 persons drawn from the 10,128 stable angina patients in the CALIBER database (Cardiovascular Disease Research using Linked Bespoke Studies and Electronic Records; 2001-2010) with complete data on all covariates. Variables were artificially made "missing at random," and the bias and efficiency of parameter estimates obtained using different imputation methods were compared. Both MICE methods produced unbiased estimates of (log) hazard ratios, but random forest was more efficient and produced narrower confidence intervals. The second study used simulated data in which the partially observed variable depended on the fully observed variables in a nonlinear way. Parameter estimates were less biased using random forest MICE, and confidence interval coverage was better. This suggests that random forest imputation may be useful for imputing complex epidemiologic data sets in which some patients have missing data. PMID:24589914
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. PMID:25294023
NASA Astrophysics Data System (ADS)
Mendez, Enrique Alberto
The new concept of antenna radiation center (ARC) is introduced and an empirical method to measure it from complex scattering data is presented. This concept is different from the well-known antenna phase center utilized in reflector antenna applications. A novel and efficient procedure based on a General Parametric Scattering Model (GSPM) is utilized to extract in-situ antenna radiation properties from complex antenna scattering data. This model based measurement approach has the advantage that it only requires two swept frequency scattering measurements in order to obtain antenna RCS, antenna gain and antenna radiation center in its integrated operational environment. The GSPM structure required to accurately extract arbitrary target scattering data is developed based on basic electromagnetic principles. The mathematical model structure consists of an early time response based on a point scattering model and on a late time response based on the Singularity Expansion Method (SEM). Both of these methods are implemented to take into account the target dispersion in a general fashion. Robust signal processing algorithms are utilized to extract the model parameters by exploiting the model symmetry properties in the time and frequency domains. In particular, super-resolution algorithms such as ESPRIT and MUSIC are utilized to extract scattering center location and resonance frequency information, while Least Squares techniques are used to estimate the different model amplitude coefficients as a function of time or frequency in an optimal (i.e. mean square sense) fashion. Theoretical derivations are provided to demonstrate that the GSPM can be utilized to extract antenna gain and radiation center information from scattering data. Synthetic and measured antenna scattering data are utilized to demonstrate the GSPM superior gain and radiation center results over traditional Fourier techniques. Gain transfer measurements results are also compared to the GSPM derived gain
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. PMID:24914522
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
Parametric Hazard Function Estimation.
1999-09-13
Version 00 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 ofmore » the model assumptions.« less
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.
Parametric latent class joint model for a longitudinal biomarker and recurrent events
Han, Jun; Slate, Elizabeth H.; Peña, Edsel A.
2014-01-01
SUMMARY A joint model for a longitudinal biomarker and recurrent events is proposed. This general model accommodates the effects of covariates on the biomarker and event processes, the effects of accumulating event occurrences, and effects caused by interventions after each event occurrence. Association between the biomarker and recurrent event processes is captured through a latent class structure, which also serves to handle an underlying heterogeneous population. We use the EM algorithm for maximum likelihood estimation of the model parameters and a penalized likelihood measure to determine the number of latent classes. This joint model is validated by simulation and illustrated with a data set from epileptic seizure study. PMID:17542002
PARTICULATE EMISSIONS AND CONTROL IN FLUIDIZED-BED COMBUSTION: MODELING AND PARAMETRIC PERFORMANCE
The report discusses a model, developed to describe the physical characteristics of the particulates emitted from fluidized-bed combustion (FBC) systems and to evaluate data on FBC particulate control systems. The model, which describes the particulate emissions profile from FBC,...
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...
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…
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.
NASA Astrophysics Data System (ADS)
Yamamoto, Yu; Yamada, Shoichi
2016-02-01
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.
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, 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.
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
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
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
Bubbles, Clusters and Denaturation in Genomic Dna: Modeling, Parametrization, Efficient Computation
NASA Astrophysics Data System (ADS)
Theodorakopoulos, Nikos
2011-08-01
The paper uses mesoscopic, non-linear lattice dynamics based (Peyrard-Bishop-Dauxois, PBD) modeling to describe thermal properties of DNA below and near the denaturation temperature. Computationally efficient notation is introduced for the relevant statistical mechanics. Computed melting profiles of long and short heterogeneous sequences are presented, using a recently introduced reparametrization of the PBD model, and critically discussed. The statistics of extended open bubbles and bound clusters is formulated and results are presented for selected examples.
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
Devarajan, Karthik; Ebrahimi, Nader
2010-01-01
The assumption of proportional hazards (PH) fundamental to the Cox PH model sometimes may not hold in practice. In this paper, we propose a generalization of the Cox PH model in terms of the cumulative hazard function taking a form similar to the Cox PH model, with the extension that the baseline cumulative hazard function is raised to a power function. Our model allows for interaction between covariates and the baseline hazard and it also includes, for the two sample problem, the case of two Weibull distributions and two extreme value distributions differing in both scale and shape parameters. The partial likelihood approach can not be applied here to estimate the model parameters. We use the full likelihood approach via a cubic B-spline approximation for the baseline hazard to estimate the model parameters. A semi-automatic procedure for knot selection based on Akaike’s Information Criterion is developed. We illustrate the applicability of our approach using real-life data. PMID:21076652
Fitting parametric models of diffusion MRI in regions of partial volume
NASA Astrophysics Data System (ADS)
Eaton-Rosen, Zach; Cardoso, M. J.; Melbourne, Andrew; Orasanu, Eliza; Bainbridge, Alan; Kendall, Giles S.; Robertson, Nicola J.; Marlow, Neil; Ourselin, Sebastien
2016-03-01
Regional analysis is normally done by fitting models per voxel and then averaging over a region, accounting for partial volume (PV) only to some degree. In thin, folded regions such as the cerebral cortex, such methods do not work well, as the partial volume confounds parameter estimation. Instead, we propose to fit the models per region directly with explicit PV modeling. In this work we robustly estimate region-wise parameters whilst explicitly accounting for partial volume effects. We use a high-resolution segmentation from a T1 scan to assign each voxel in the diffusion image a probabilistic membership to each of k tissue classes. We rotate the DW signal at each voxel so that it aligns with the z-axis, then model the signal at each voxel as a linear superposition of a representative signal from each of the k tissue types. Fitting involves optimising these representative signals to best match the data, given the known probabilities of belonging to each tissue type that we obtained from the segmentation. We demonstrate this method improves parameter estimation in digital phantoms for the diffusion tensor (DT) and `Neurite Orientation Dispersion and Density Imaging' (NODDI) models. The method provides accurate parameter estimates even in regions where the normal approach fails completely, for example where partial volume is present in every voxel. Finally, we apply this model to brain data from preterm infants, where the thin, convoluted, maturing cortex necessitates such an approach.
Devarajan, Karthik; Ebrahimi, Nader
2011-01-01
The assumption of proportional hazards (PH) fundamental to the Cox PH model sometimes may not hold in practice. In this paper, we propose a generalization of the Cox PH model in terms of the cumulative hazard function taking a form similar to the Cox PH model, with the extension that the baseline cumulative hazard function is raised to a power function. Our model allows for interaction between covariates and the baseline hazard and it also includes, for the two sample problem, the case of two Weibull distributions and two extreme value distributions differing in both scale and shape parameters. The partial likelihood approach can not be applied here to estimate the model parameters. We use the full likelihood approach via a cubic B-spline approximation for the baseline hazard to estimate the model parameters. A semi-automatic procedure for knot selection based on Akaike's Information Criterion is developed. We illustrate the applicability of our approach using real-life data. PMID:21076652
Smoothed Particle Inference: A Kilo-Parametric Method for X-ray Galaxy Cluster Modeling
Peterson, John R.; Marshall, P.J.; Andersson, K.; /Stockholm U. /SLAC
2005-08-05
We propose an ambitious new method that models the intracluster medium in clusters of galaxies as a set of X-ray emitting smoothed particles of plasma. Each smoothed particle is described by a handful of parameters including temperature, location, size, and elemental abundances. Hundreds to thousands of these particles are used to construct a model cluster of galaxies, with the appropriate complexity estimated from the data quality. This model is then compared iteratively with X-ray data in the form of adaptively binned photon lists via a two-sample likelihood statistic and iterated via Markov Chain Monte Carlo. The complex cluster model is propagated through the X-ray instrument response using direct sampling Monte Carlo methods. Using this approach the method can reproduce many of the features observed in the X-ray emission in a less assumption-dependent way that traditional analyses, and it allows for a more detailed characterization of the density, temperature, and metal abundance structure of clusters. Multi-instrument X-ray analyses and simultaneous X-ray, Sunyaev-Zeldovich (SZ), and lensing analyses are a straight-forward extension of this methodology. Significant challenges still exist in understanding the degeneracy in these models and the statistical noise induced by the complexity of the models.
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. PMID:26210670
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. PMID:27367094
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.
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.
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 ...
Rathour, Rahul Kumar; Narayanan, Rishikesh
2012-01-01
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
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.
Weber, Gerald
2013-01-01
Information about molecular interactions in DNA can be obtained from experimental melting temperature data by using mesoscopic statistical physics models. Here, we extend the technique to RNA and show that the new parameters correctly reproduce known properties such as the stronger hydrogen bonds of AU base pairs. We also were able to calculate a complete set of elastic constants for all 10 irreducible combinations of nearest neighbours (NNs). We believe that this is particularly useful as experimentally derived information about RNA elasticity is relatively scarce. The melting temperature prediction using the present model improves over those from traditional NN model, providing thus an alternative way to calculate these temperatures for RNA. Additionally, we calculated the site-dependent base pair oscillation to explain why RNA shows larger oscillation amplitudes despite having stronger AU hydrogen bonds. PMID:23087379
NASA Technical Reports Server (NTRS)
Boxwell, D. A.; Schmitz, F. H.; Splettstoesser, W. R.; Schultz, K. J.
1987-01-01
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, in-flight acoustic data under similar non-dimensional test conditions using an improved data analysis technique. At low advance ratios (mu = 0.164 - 0.194), the BVI impulsive noise data scale remarkably well in level, waveform, and directivity patterns. At moderate advance ratios (mu = 0.224 - 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. Measured BVI noise radiation is highly sensitive to all of the four governing nondimensional parameters--hover tip Mach number, advance ratio, local inflow ratio, and thrust coefficient.
Simple parametric model for intensity calibration of Cassini composite infrared spectrometer data.
Brasunas, J; Mamoutkine, A; Gorius, N
2016-06-10
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. PMID:27409028
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
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. PMID:27075918
A virtual source model for Kilo-voltage cone beam CT: Source characteristics and model validation
Spezi, E.; Volken, W.; Frei, D.; Fix, M. K.
2011-09-15
Purpose: The purpose of this investigation was to study the source characteristics of a clinical kilo-voltage cone beam CT unit and to develop and validate a virtual source model that could be used for treatment planning purposes. Methods: We used a previously commissioned full Monte Carlo model and new bespoke software to study the source characteristics of a clinical kilo-voltage cone beam CT (CBCT) unit. We identified the main particle sources, their spatial, energy and angular distribution for all the image acquisition presets currently used in our clinical practice. This includes a combination of two energies (100 and 120 kVp), two filters (neutral and bowtie), and eight different x-ray beam apertures. We subsequently built a virtual source model which we validated against full Monte Carlo calculations. Results: We found that the radiation output of the clinical kilo-voltage cone beam CT unit investigated in this study could be reproduced with a virtual model comprising of two sources (target and filtration cone) or three sources (target, filtration cone and bowtie filter) when additional filtration was used. With this model, we accounted for more than 97% of the photons exiting the unit. Each source in our model was characterised by a origin distribution in both X and Y directions, a fluence map, a single energy spectrum for unfiltered beams and a two dimensional energy spectrum for bowtie filtered beams. The percentage dose difference between full Monte Carlo and virtual source model based dose distributions was well within the statistical uncertainty associated with the calculations ( {+-} 2%, one standard deviation) in all cases studied. Conclusions: The virtual source that we developed is accurate in calculating the dose delivered from a commercial kilo-voltage cone beam CT unit operating with routine clinical image acquisition settings. Our data have also shown that target, filtration cone, and bowtie filter sources needed to be all included in the model
A parametric study of the drift-tearing mode using an extended-magnetohydrodynamic model
King, J. R.; Kruger, S. E.
2014-10-15
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. New dispersion relations are found at moderate plasma β and previous drift-tearing results are classified as applicable at small plasma β.
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,…
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.
NASA Astrophysics Data System (ADS)
Baraka, S. M.; Ben-Jaffel, L. B.
2014-12-01
We use particle-in-cell PIC 3D Electromagnetic, relativistic global code to address large-scale problems in magnetosphere electrodynamics. Terrestrial bow shock is simulated as an example. 3D Magnetohydrodynamics model ,MHD GUMICS in CCMC project, have been used in parallel with PIC under same scaled Solar wind (SW) and IMF conditions. We report new results from the coupling between the two models. Further investigations are required for confirmations of these results. In both codes the Earth's bow shock position is found at ~14.8 RE along the Sun-Earth line, and ~29 RE on the dusk side which is consistent with past in situ observation. Both simulations reproduce the theoretical jump conditions at the shock. However, PIC code density and temperature distributions are inflated and slightly shifted sunward when compared to MHD results. Reflected ions upstream of the bow shock may cause this sunward shift for density and temperature. Distribution of reflected ions and electrons are shown in the foreshock region, within the transition of the shock and in the downstream. The current version of PIC code can be run under modest computing facilities and resources. Additionally, existing MHD simulations should be useful to calibrate scaled properties of plasma resulting from PIC simulations for comparison with observations. Similarities and drawbacks of the results obtained by the two models are listed. The ultimate goal of using these different models in a complimentary manner rather than competitive is to better understand the macrostructure of the magnetosphere
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...
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. PMID:26216413
Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images
NASA Astrophysics Data System (ADS)
Štern, Darko; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž
2011-12-01
Accurate and objective evaluation of vertebral deformations is of significant importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is focused on three-dimensional (3D) computed tomography (CT) and magnetic resonance (MR) imaging techniques, the established methods for evaluation of vertebral deformations are limited to measuring deformations in two-dimensional (2D) x-ray images. In this paper, we propose a method for quantitative description of vertebral body deformations by efficient modelling and segmentation of vertebral bodies in 3D. The deformations are evaluated from the parameters of a 3D superquadric model, which is initialized as an elliptical cylinder and then gradually deformed by introducing transformations that yield a more detailed representation of the vertebral body shape. After modelling the vertebral body shape with 25 clinically meaningful parameters and the vertebral body pose with six rigid body parameters, the 3D model is aligned to the observed vertebral body in the 3D image. The performance of the method was evaluated on 75 vertebrae from CT and 75 vertebrae from T2-weighted MR spine images, extracted from the thoracolumbar part of normal and pathological spines. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images, as the proposed 3D model is able to describe both normal and pathological vertebral body deformations. The method may therefore be used for initialization of whole vertebra segmentation or for quantitative measurement of vertebral body deformations.
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.
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.
A parametric model and estimation techniques for the inharmonicity and tuning of the piano.
Rigaud, François; David, Bertrand; Daudet, Laurent
2013-05-01
Inharmonicity of piano tones is an essential property of their timbre that strongly influences the tuning, leading to the so-called octave stretching. It is proposed in this paper to jointly model the inharmonicity and tuning of pianos on the whole compass. While using a small number of parameters, these models are able to reflect both the specificities of instrument design and tuner's practice. An estimation algorithm is derived that can run either on a set of isolated note recordings, but also on chord recordings, assuming that the played notes are known. It is applied to extract parameters highlighting some tuner's choices on different piano types and to propose tuning curves for out-of-tune pianos or piano synthesizers. PMID:23654413
Ray, Shayoni; Yuan, Daniel; Dhulekar, Nimit; Oztan, Basak; Yener, Bülent; Larsen, Melinda
2013-01-01
Cleft formation during submandibular salivary gland branching morphogenesis is the critical step initiating the growth and development of the complex adult organ. Previous experimental studies indicated requirements for several epithelial cellular processes, such as proliferation, migration, cell-cell adhesion, cell-extracellular matrix (matrix) adhesion, and cellular contraction in cleft formation; however, the relative contribution of each of these processes is not fully understood since it is not possible to experimentally manipulate each factor independently. We present here a comprehensive analysis of several cellular parameters regulating cleft progression during branching morphogenesis in the epithelial tissue of an early embryonic salivary gland at a local scale using an on lattice Monte-Carlo simulation model, the Glazier-Graner-Hogeweg model. We utilized measurements from time-lapse images of mouse submandibular gland organ explants to construct a temporally and spatially relevant cell-based 2D model. Our model simulates the effect of cellular proliferation, actomyosin contractility, cell-cell and cell-matrix adhesions on cleft progression, and it was used to test specific hypotheses regarding the function of these parameters in branching morphogenesis. We use innovative features capturing several aspects of cleft morphology and quantitatively analyze clefts formed during functional modification of the cellular parameters. Our simulations predict that a low epithelial mitosis rate and moderate level of actomyosin contractility in the cleft cells promote cleft progression. Raising or lowering levels of contractility and mitosis rate resulted in non-progressive clefts. We also show that lowered cell-cell adhesion in the cleft region and increased cleft cell-matrix adhesions are required for cleft progression. Using a classifier-based analysis, the relative importance of these four contributing cellular factors for effective cleft progression was determined
Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach
NASA Astrophysics Data System (ADS)
Chowdhury, R.; Adhikari, S.
2012-10-01
Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.
NASA Astrophysics Data System (ADS)
Kuszli, C.; Goyette, S.; Beniston, M.
2013-12-01
Severe winds recorded during a number of winter storms are simulated over the period 1990 to 2011 with the Canadian Regional Climate Model (CRCM) at a high spatial resolution. Flow fields are first downscaled from NCEP-NCAR reanalyses and then down to 2-km grid spacing in the horizontal through a self-nesting technique. During this last step, different windgust schemes of different complexities were tested and their performances compared one to each other and to observations from MeteoSwiss national network. Simple schemes reproduced the surface observations in an overall realistic manner but differences are noticed in the hourly maximum values. In order to improve one of the simple schemes, an empirically fixed parameter in the formulation is now allowed to vary in the horizontal where values have been calibrated using the MeteoSwiss stations hourly wind maximum. Then, these unequally-spaced values are interpolated onto the model surface computational grid. The CRCM using this modified scheme is applied on the 2-km grid in order to qualify and quantify the changes of the hourly gust values. The improvements are noticeable where hourly differences between observed and simulated values are reduced at several stations. This modified simple gust scheme would be useful in numerical weather prediction modelling where an application is envisaged in the near future.
Savitsky, Terrance D.; Paddock, Susan M.
2012-01-01
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. PMID:24273629
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.
Parametric Study of Plasma Torch Operation Using a MHD Model Coupling the Arc and Electrodes
NASA Astrophysics Data System (ADS)
Alaya, M.; Chazelas, C.; Vardelle, A.
2016-01-01
Coupling of the electromagnetic and heat transfer phenomena in a non-transferred arc plasma torch is generally based on a current density profile and a temperature imposed on the cathode surface. However, it is not possible to observe the current density profile experimentally and so the computations are grounded on an estimation of current distribution at cathode tip. To eliminate this boundary condition and be able to predict the arc dynamics in the plasma torch, the cathode was included in the computational domain, the arc current was imposed on the rear surface of the cathode, and the electromagnetism and energy conservation equations for the fluid and the electrode were coupled and solved. The solution of this system of equations was implemented in a CFD computer code to model various plasma torch operating conditions. The model predictions for various arc currents were consistent and indicated that such a model could be applied with confidence to plasma torches of different geometries, such as cascaded-anode plasma torches.
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. PMID:24273629
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 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
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.
NASA Astrophysics Data System (ADS)
Lucarini, V.; Speranza, A.; Vitolo, R.
2009-04-01
A quasi-geostrophic intermediate complexity model of the mid-latitude atmospheric circulation is considered, featuring simplified baroclinic conversion and barotropic convergence processes. The model undergoes baroclinic forcing towards a given latitudinal temperature profile controlled by the forced equator-to-pole temperature difference Te. When Te increases, a transition takes place from a stationary regime-Hadley equilibrium-to a periodic regime, and eventually to a chaotic regime where evolution takes place on a strange attractor. The attractor dimension, metric entropy, and bounding box volume in phase space have a smooth dependence on Te which results in power-law scaling properties. Power-law scalings are detected also for the statistical properties of global physical observables — the total energy of the system and the averaged zonal wind. The scaling laws, which constitute the main novel result of the present work, can be thought to result from the presence of a statistical process of baroclinic adjustment, which tends to decrease the equator-to-pole temperature difference and determines the properties of the attractor of the system. The self-similarity could be of great help in setting up a theory for the overall statistical properties of the general circulation of the atmosphere and in guiding-on a heuristic basis-both data analysis and realistic simulations, going beyond the unsatisfactory mean field theories and /brute force/ approaches. A leading example for this would be the possibility of estimating the sensitivity of the output of the system with respect to changes in the parameters. Ref: Valerio Lucarini, Antonio Speranza, Renato Vitolo, Parametric smoothness and self-scaling of the statistical properties of a minimal climate model: What beyond the mean field theories?, Physica D, 234 (2007), 105-123
Modeling the dynamic operation of a small fin plate heat exchanger - parametric analysis
NASA Astrophysics Data System (ADS)
Motyliński, Konrad; Kupecki, Jakub
2015-09-01
Given its high efficiency, low emissions and multiple fuelling options, the solid oxide fuel cells (SOFC) offer a promising alternative for stationary power generators, especially while engaged in micro-combined heat and power (μ-CHP) units. Despite the fact that the fuel cells are a key component in such power systems, other auxiliaries of the system can play a critical role and therefore require a significant attention. Since SOFC uses a ceramic material as an electrolyte, the high operating temperature (typically of the order of 700-900 °C) is required to achieve sufficient performance. For that reason both the fuel and the oxidant have to be preheated before entering the SOFC stack. Hot gases exiting the fuel cell stack transport substantial amount of energy which has to be partly recovered for preheating streams entering the stack and for heating purposes. Effective thermal integration of the μ-CHP can be achieved only when proper technical measures are used. The ability of efficiently preheating the streams of oxidant and fuel relies on heat exchangers which are present in all possible configurations of power system with solid oxide fuel cells. In this work a compact, fin plate heat exchanger operating in the high temperature regime was under consideration. Dynamic model was proposed for investigation of its performance under the transitional states of the fuel cell system. Heat exchanger was simulated using commercial modeling software. The model includes key geometrical and functional parameters. The working conditions of the power unit with SOFC vary due to the several factors, such as load changes, heating and cooling procedures of the stack and others. These issues affect parameters of the incoming streams to the heat exchanger. The mathematical model of the heat exchanger is based on a set of equations which are simultaneously solved in the iterative process. It enables to define conditions in the outlets of both the hot and the cold sides
Wang, Junmei; Cieplak, Piotr; Li, Jie; Cai, Qin; Hsieh, Meng-Juei; Luo, Ray; Duan, Yong
2012-06-21
In the previous publications of this series, we presented a set of Thole induced dipole interaction models using four types of screening functions. In this work, we document our effort to refine the van der Waals parameters for the Thole polarizable models. Following the philosophy of AMBER force field development, the van der Waals (vdW) parameters were tuned for the Thole model with linear screening function to reproduce both the ab initio interaction energies and the experimental densities of pure liquids. An in-house genetic algorithm was applied to maximize the fitness of "chromosomes" which is a function of the root-mean-square errors (RMSE) of interaction energy and liquid density. To efficiently explore the vdW parameter space, a novel approach was developed to estimate the liquid densities for a given vdW parameter set using the mean residue-residue interaction energies through interpolation/extrapolation. This approach allowed the costly molecular dynamics simulations be performed at the end of each optimization cycle only and eliminated the simulations during the cycle. Test results show notable improvements over the original AMBER FF99 vdW parameter set, as indicated by the reduction in errors of the calculated pure liquid densities (d), heats of vaporization (H(vap)), and hydration energies. The average percent error (APE) of the densities of 59 pure liquids was reduced from 5.33 to 2.97%; the RMSE of H(vap) was reduced from 1.98 to 1.38 kcal/mol; the RMSE of solvation free energies of 15 compounds was reduced from 1.56 to 1.38 kcal/mol. For the interaction energies of 1639 dimers, the overall performance of the optimized vdW set is slightly better than the original FF99 vdW set (RMSE of 1.56 versus 1.63 kcal/mol). The optimized vdW parameter set was also evaluated for the exponential screening function used in the Amoeba force field to assess its applicability for different types of screening functions. Encouragingly, comparable performance was
NASA Astrophysics Data System (ADS)
Kuszli, Charles-Antoine; Goyette, Stéphane; Beniston, Martin
2014-05-01
Severe winds recorded during a number of winter storms are simulated over the period 1990 to 2011 with the Canadian Regional Climate Model (CRCM) at a high spatial resolution. Flow fields are first downscaled from NCEP-NCAR reanalyses and then down to 2-km grid spacing in the horizontal through a self-nesting technique. During this last step, different windgust schemes of different complexities were tested and their performances compared one to each other and to observations from MeteoSwiss national network. Simple schemes reproduced the surface observations in an overall realistic manner but differences are noticed in the hourly maximum values. In order to improve the scheme in operational use at MeteoSwiss, an empirically fixed parameter in the formulation is now allowed to vary in the horizontal where values have been calibrated using the MeteoSwiss stations hourly wind maximum. Then, these unequally-spaced values are statistically predicted and interpolated onto the model surface computational grid with a cokriging analysis based on elevation data such as terrain curvature, slope and aspect. This parameters' map is used to improve one of the gusts scheme and the CRCM is run on the 2-km grid in order to qualify and quantify the changes of the hourly gust values during the storms. The improvements are significant where hourly differences between observed and simulated values are reduced at several stations. The performance of this method is shown to be closely related to the analysis of the main flow regimes in Switzerland during which the storms are simulated. An application of this modified gust scheme for numerical weather prediction modelling is envisaged in the near future.
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 J.; Ovchinnikov, Mikhail; Bogenschutz, Peter; Gettelman, A.; 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. This study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.
Eakin, T; Shouman, R; Qi, Y; Liu, G; Witten, M
1995-05-01
Studies of the biology of aging (both experimental and evolutionary) frequently involve the estimation of parameters arising in various multi-parameter survival models such as the Gompertz or Weibull distribution. Standard parameter estimation methodologies, such as maximum likelihood estimation (MLE) or nonlinear regression (NLR), require knowledge of the actual life spans or their explicit algebraic equivalents in order to provide reliable parameter estimates. Many fundamental biological discussions and conclusions are highly dependent upon accurate estimates of these survival parameters (this has historically been the case in the study of genetic and environmental effects on longevity and the evolutionary biology of aging). In this article, we examine some of the issues arising in the estimation of gerontologic survival model parameters. We not only address issues of accuracy when the original life-span data are unknown, we consider the accuracy of the estimates even when the exact life spans are known. We examine these issues as applied to known experimental data on diet restriction and we fit the frequently used, two-parameter Gompertzian survival distribution to these experimental data. Consequences of methodological misuse are demonstrated and subsequently related to the values of the final parameter estimates and their associated errors. These results generalize to other multiparametric distributions such as the Weibull, Makeham, and logistic survival distributions. PMID:7743396
Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)
NASA Astrophysics Data System (ADS)
Guo, Zhun; Wang, Minghuai; Qian, Yun; Larson, Vincent E.; Ghan, Steven; Ovchinnikov, Mikhail; Bogenschutz, Peter A.; Gettelman, Andrew; Zhou, Tianjun
2015-09-01
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 four 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 Gaussian 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. This study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.
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).
NASA Astrophysics Data System (ADS)
Moncayo, Marco A.; Santhanakrishnan, Soundarapandian; Vora, Hitesh D.; Dahotre, Narendra B.
2013-06-01
In this work, both heat transfer modeling (COMSOL Multiphysics®) and experimental investigations were used to obtain the threshold multiple laser scanning processing parameters (laser power, scanning speed, fill space) for achieving more multi-faceted grains on the alumina's surface. An ytterbium doped Nd:YAG laser (1064 nm) was used to perform the experiments for the designed processing conditions such as 32-127×106 J/m2 laser energy densities with fill space values of 3-6×10-4 m. The SEM, EDX and wear results were used to quantify the effect of multiple laser processing variables on the change of microstructures (coarse grains, dendrite, multi-faceted grains) for obtaining the best processing conditions. By controlling the laser energy density with fill space, more multi-faceted grains and high wear resistance were achieved as the essential features for improving the abrasive quality.
Parametric Modeling in Action: High Accuracy Seismology of Kepler DAV Stars
NASA Astrophysics Data System (ADS)
Giammichele, N.; Fontaine, G.; Charpinet, S.; Brassard, P.; Greiss, S.
2015-06-01
We summarize here the efforts made on the quantitative seismic analyses performed on two ZZ Ceti stars observed with the Kepler satellite. One of them, KIC 11911480, is located close to the blue edge of the instability strip, while the other, GD 1212, is found at the red edge. We emphasize the need for parameterized modeling and the forward approach to uniquely establish the fundamental parameters of the stars. We show how the internal structures as well as rotation profiles are unravelled to surprisingly large depths for degenerates such as ZZ Ceti stars, which further confirms the loss of stellar angular momentum before the white dwarf stage detected previously in GW Vir pulsating white dwarfs. This opens up interesting prospects for the new mission to come, Kepler-2, in the field of white dwarf asteroseismology.
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.
Parametric modeling of exhaust gas emission from natural gas fired gas turbines
Bakken, L.E.; Skogly, L.
1996-07-01
Increased focus on air pollution from gas turbines in the Norwegian sector of the North Sea has resulted in taxes on CO{sub 2}. Statements made by the Norwegian authorities imply regulations and/or taxes on NO{sub x} emissions in the near future. The existing CO{sub 2} tax of NOK 0.82/Sm{sup 3} (US Dollars 0.12/Sm{sup 3}) and possible future tax on NO{sub x} are analyzed mainly with respect to operating and maintenance costs for the gas turbine. Depending on actual tax levels, the machine should be operated on full load/optimum thermal efficiency or part load to reduce specific exhaust emissions. Based on field measurements, exhaust emissions (CO{sub 2}, CO, NO{sub x}, N{sub 2}O, UHC, etc.) are established with respect to load and gas turbine performance, including performance degradation. Different NO{sub x} emission correlations are analyzed based on test results, and a proposed prediction model presented. The impact of machinery performance degradation on emission levels is particularly analyzed. Good agreement is achieved between measured and predicted NO{sub x} emissions from the proposed correlation. To achieve continuous exhaust emission control, the proposed NO{sub x} model is implemented to the on-line condition monitoring system on the Sleipner A platform, rather than introducing sensitive emission sensors in the exhaust gas stack. The on-line condition monitoring system forms an important tool in detecting machinery condition/degradation and air pollution, and achieving optimum energy conservation.
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.
Atomic modeling of the plasma EUV sources
NASA Astrophysics Data System (ADS)
Sasaki, Akira; Sunahara, Atsushi; Furukawa, Hiroyuki; Nishihara, Katsunobu; Nishikawa, Takeshi; Koike, Fumihiro; Tanuma, Hajime
2009-09-01
We present the development of population kinetics models for tin plasmas that can be employed to design an EUV source for microlithography. The atomic kinetic code is constrained for the requirement that the model must be able to calculate spectral emissivity and opacity that can be used in radiation hydrodynamic simulations. Methods to develop compact and reliable atomic model with an appropriate set of atomic states are discussed. Specifically, after investigation of model dependencies and comparison experiment, we improve the effect of configuration interaction and the treatment of satellite lines. Using the present atomic model we discuss the temperature and density dependencies of the emissivity, as well as conditions necessary to obtain high efficiency EUV power at λ = 13.5 nm.
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 Astrophysics Data System (ADS)
Glanz, Hunter; Carvalho, Luis; Sulla-Menashe, Damien; Friedl, Mark A.
2014-11-01
Time series of multispectral images are widely used to monitor and map land cover. However, high dimensionality and missing data present significant challenges for classification algorithms that use multi-temporal remotely sensed data. Further, generation and assessment of high quality training data, including detection of outliers and changed pixels in training data, is difficult. In this paper we present a new statistical framework that is based on a parametric model that enables a targeted principal component analysis (PCA) to reduce the dimensionality of multi-temporal remote sensing data. In doing so, the model provides a novel basis for land cover classification and evaluating the nature and quality of training data used for supervised classifications. The methodology we describe uses a Kronecker operator to reduce the spectral dimensionality of multi-temporal images while preserving their temporal structure, thereby providing low-dimensional data that is well-suited for classification and outlier detection problems. As part of our framework, we use an expectation-maximization method to impute missing data, and propose new metrics that characterize the representativeness and pixel-to-pixel homogeneity of training sites used for supervised classification. To evaluate our approach, we use data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and extracted more than 200 training sites where the land cover has been characterized from high spatial resolution imagery. The original input data was composed of 196 features (28 dates × 7 bands), and the PCA-based approach we describe captured 91% of the variance, in these 7 bands, in 3 components. Results from maximum likelihood classification show that the retained principal components successfully distinguish land cover classes from one another, with classification results that were comparable to supervised machine learning methods applied to the original MODIS data. Analysis of our site composition
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
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.
NASA Astrophysics Data System (ADS)
Malinovic-Milicevic, S.; Mihailovic, D. T.; Radovanovic, M. M.
2015-07-01
This paper focuses on the development and application of a technique for filling the daily erythemal UV dose data gaps and the reconstruction of the past daily erythemal UV doses in Novi Sad, Serbia. The technique implies developing the empirical equation for estimation of daily erythemal UV doses by means of relative daily sunshine duration under all sky conditions. A good agreement was found between modeled and measured values of erythemal UV doses. This technique was used for filling the short gaps in the erythemal UV dose measurement series (2003-2009) as well as for the reconstruction of the past time-series values (1981-2002). Statistically significant positive erythemal UV dose trend of 6.9 J m-2 per year was found during the period 1981-2009. In relation to the reference period 1981-1989, an increase in the erythemal UV dose of 6.92 % is visible in the period 1990-1999 and the increase of 9.67 % can be seen in the period 2000-2009. The strongest increase in erythemal UV doses has been found for winter and spring seasons.
Jensen, Benjamin D; Bandyopadhyay, Ananyo; Wise, Kristopher E; Odegard, Gregory M
2012-09-11
The development of innovative carbon-based materials can be greatly facilitated by molecular modeling techniques. Although the Reax Force Field (ReaxFF) can be used to simulate the chemical behavior of carbon-based systems, the simulation settings required for accurate predictions have not been fully explored. Using the ReaxFF, molecular dynamics (MD) simulations are used to simulate the chemical behavior of pure carbon and hydrocarbon reactive gases that are involved in the formation of carbon structures such as graphite, buckyballs, amorphous carbon, and carbon nanotubes. It is determined that the maximum simulation time step that can be used in MD simulations with the ReaxFF is dependent on the simulated temperature and selected parameter set, as are the predicted reaction rates. It is also determined that different carbon-based reactive gases react at different rates, and that the predicted equilibrium structures are generally the same for the different ReaxFF parameter sets, except in the case of the predicted formation of large graphitic structures with the Chenoweth parameter set under specific conditions. PMID:26605713
Light-pollution model for cloudy and cloudless night skies with ground-based light sources.
Kocifaj, Miroslav
2007-05-20
The scalable theoretical model of light pollution for ground sources is presented. The model is successfully employed for simulation of angular behavior of the spectral and integral sky radiance and/or luminance during nighttime. There is no restriction on the number of ground-based light sources or on the spatial distribution of these sources in the vicinity of the measuring point (i.e., both distances and azimuth angles of the light sources are configurable). The model is applicable for real finite-dimensional surface sources with defined spectral and angular radiating properties contrary to frequently used point-source approximations. The influence of the atmosphere on the transmitted radiation is formulated in terms of aerosol and molecular optical properties. Altitude and spectral reflectance of a cloud layer are the main factors introduced for simulation of cloudy and/or overcast conditions. The derived equations are translated into numerically fast code, and it is possible to repeat the entire set of calculations in real time. The parametric character of the model enables its efficient usage by illuminating engineers and/or astronomers in the study of various light-pollution situations. Some examples of numerical runs in the form of graphical results are presented. PMID:17514252
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
NASA Astrophysics Data System (ADS)
Rothfuss, Youri; Vereecken, Harry; Brüggemann, Nicolas
2015-04-01
water processes. An important challenge is to provide models with non-destructive and high resolution isotope data, both in space and time (e.g., using microporous tubing or membrane-based available setups). Moreover, parallel to field studies effort should be made to design specific experiments under controlled conditions, allowing for testing the underlying hypotheses of the above mentioned isotope-enabled SVAT models. Using isotope data obtained from these controlled experiments will improve the characterization of evaporation processes within the soil profile and ameliorate the parametrization of the respective isotope modules.
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.
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.
Qian, Yun; Yan, Huiping; Hou, Zhangshuan; Johannesson, G.; Klein, Stephen A.; Lucas, Donald; Neale, Richard; Rasch, Philip J.; Swiler, Laura P.; Tannahill, John; Wang, Hailong; Wang, Minghuai; Zhao, Chun
2015-04-10
We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics. Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.
Qian, Yun; Yan, Huiping; Hou, Zhangshuan; Johannesson, G.; Klein, Stephen A.; Lucas, Donald; Neale, Richard; Rasch, Philip J.; Swiler, Laura P.; Tannahill, John; et al
2015-04-10
We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics.more » Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less
Probing the matter and dark energy sources in a viable Big Rip model of the Universe
NASA Astrophysics Data System (ADS)
Kumar, Suresh
2014-08-01
Chevallier-Polarski-Linder (CPL) parametrization for the equation of state (EoS) of dark energy in terms of cosmic redshift or scale factor have been frequently studied in the literature. In this study, we consider cosmic time-based CPL parametrization for the EoS parameter of the effective cosmic fluid that fills the fabric of spatially flat and homogeneous Robertson-Walker (RW) spacetime in General Relativity. The model exhibits two worthy features: (i) It fits the observational data from the latest H(z) and Union 2.1 SN Ia compilations matching the success of ΛCDM model. (ii) It describes the evolution of the Universe from the matter-dominated phase to the recent accelerating phase similar to the ΛCDM model but leads to Big Rip end of the Universe contrary to the everlasting de Sitter expansion in the ΛCDM model. We investigate the matter and dark energy sources in the model, in particular, behavior of the dynamical dark energy responsible for the Big Rip end of Universe.
Source term evaluation for combustion modeling
NASA Technical Reports Server (NTRS)
Sussman, Myles A.
1993-01-01
A modification is developed for application to the source terms used in combustion modeling. The modification accounts for the error of the finite difference scheme in regions where chain-branching chemical reactions produce exponential growth of species densities. The modification is first applied to a one-dimensional scalar model problem. It is then generalized to multiple chemical species, and used in quasi-one-dimensional computations of shock-induced combustion in a channel. Grid refinement studies demonstrate the improved accuracy of the method using this modification. The algorithm is applied in two spatial dimensions and used in simulations of steady and unsteady shock-induced combustion. Comparisons with ballistic range experiments give confidence in the numerical technique and the 9-species hydrogen-air chemistry model.
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.
Johnson, R.N.
1981-10-20
A method and apparatus for converting thermal energy into mechanical energy by parametric pumping of rotary inertia. In a preferred embodiment, a modified tesla turbine rotor is positioned within a rotary boiler along its axis of rotation. An external heat source, such as solar radiation, is directed onto the outer casing of the boiler to convert the liquid to steam. As the steam spirals inwardly toward the discs of the rotor, the moment of inertia of the mass of steam is reduced to thereby substantially increase its kinetic energy. The laminar flow of steam between the discs of the rotor transfers the increased kinetic energy to the rotor which can be coupled out through an output shaft to perform mechanical work. A portion of the mechanical output can be fed back to maintain rotation of the boiler.
A uniform parametrization of moment tensors
NASA Astrophysics Data System (ADS)
Tape, Walter; Tape, Carl
2015-09-01
A moment tensor is a 3 × 3 symmetric matrix that expresses an earthquake source. We construct a parametrization of the 5-D space of all moment tensors of unit norm. The coordinates associated with the parametrization are closely related to moment tensor orientations and source types. The parametrization is uniform, in the sense that equal volumes in the coordinate domain of the parametrization correspond to equal volumes of moment tensors. Uniformly distributed points in the coordinate domain therefore give uniformly distributed moment tensors. A cartesian grid in the coordinate domain can be used to search efficiently over moment tensors. We find that uniformly distributed moment tensors have uniformly distributed orientations (eigenframes), but that their source types (eigenvalue triples) are distributed so as to favour double couples.
Magnetized jet models for radio sources
NASA Astrophysics Data System (ADS)
Siah, M. J.
1985-11-01
Previous numerical calculations of the boundary of radio jet models consisting of a relativistic fluid that flows into a confining, dimpled gas cloud are extended. When all of the azimuthal field is assumed to remain inside the jet, the resulting boundary shapes are puffed up with respect to those formed in identical potentials with no anisotropic magnetic pressure. When the azimuthal component is allowed to escape from the jet into a sheath or cocoon around it, the pinching effect of this field geometry results in better collimation. This effect is stronger near the source of the ejected plasma. Overall evolution is retarded or unchanged when pressure and energy are explicitly included.
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
Bourdon, P; Péalat, M; Fabelinsky, V I
1995-03-01
A beta-barium borate optical parametric oscillator pumped by the third harmonic of a pulsed Nd:YAG laser and seeded by a cw diode laser is described. It operates on a single longitudinal mode of its cavity, with a linewidth lower than 500 MHz (0.017 cm(-1)). The conversion efficiency of the device is as great as 20% on signal output alone. The seeded tuning range is limited by the diode's tunability. PMID:19859225
Leslie, Hannah H.; Karasek, Deborah A.; Harris, Laura F.; Chang, Emily; Abdulrahim, Naila; Maloba, May; Huchko, Megan J.
2014-01-01
Objective To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. Background Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contraception are true causes is critical for informing public health strategies as longevity increases among HIV-positive women in developing countries. Methods We developed a causal model of the factors related to combined oral contraceptive (COC) use and cervical intraepithelial neoplasia 2 or greater (CIN2+) and modified the model to fit the observed data, drawn from women in a cervical cancer screening program at HIV clinics in Kenya. Assumptions required for substantiation of a causal relationship were assessed. We estimated the population-level association using semi-parametric methods: g-computation, inverse probability of treatment weighting, and targeted maximum likelihood estimation. Results We identified 2 plausible causal paths from COC use to CIN2+: via HPV infection and via increased disease progression. Study data enabled estimation of the latter only with strong assumptions of no unmeasured confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7%) were diagnosed with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9%) increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance of this association was sensitive to method of estimation and exposure misclassification. Conclusion Use of causal modeling enabled clear representation of the causal relationship of interest and the assumptions required to estimate that relationship from the observed data. Semi-parametric estimation methods provided flexibility and reduced reliance on correct model form. Although selected results suggest an increased
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.
BRST Cohomology in Beltrami Parametrization
NASA Astrophysics Data System (ADS)
Tătaru, Liviu; Vancea, Ion V.
We study the BRST cohomology within a local conformal Lagrangian field theory model built on a two-dimensional Riemann surface with no boundary. We deal with the case of the complex structure parametrized by the Beltrami differential and the scalar matter fields. The computation of all elements of the BRST cohomology is given.
ENKI - An Open Source environmental modelling platfom
NASA Astrophysics Data System (ADS)
Kolberg, S.; Bruland, O.
2012-04-01
The ENKI software framework for implementing spatio-temporal models is now released under the LGPL license. Originally developed for evaluation and comparison of distributed hydrological model compositions, ENKI can be used for simulating any time-evolving process over a spatial domain. The core approach is to connect a set of user specified subroutines into a complete simulation model, and provide all administrative services needed to calibrate and run that model. This includes functionality for geographical region setup, all file I/O, calibration and uncertainty estimation etc. The approach makes it easy for students, researchers and other model developers to implement, exchange, and test single routines and various model compositions in a fixed framework. The open-source license and modular design of ENKI will also facilitate rapid dissemination of new methods to institutions engaged in operational water resource management. ENKI uses a plug-in structure to invoke separately compiled subroutines, separately built as dynamic-link libraries (dlls). The source code of an ENKI routine is highly compact, with a narrow framework-routine interface allowing the main program to recognise the number, types, and names of the routine's variables. The framework then exposes these variables to the user within the proper context, ensuring that distributed maps coincide spatially, time series exist for input variables, states are initialised, GIS data sets exist for static map data, manually or automatically calibrated values for parameters etc. By using function calls and memory data structures to invoke routines and facilitate information flow, ENKI provides good performance. For a typical distributed hydrological model setup in a spatial domain of 25000 grid cells, 3-4 time steps simulated per second should be expected. Future adaptation to parallel processing may further increase this speed. New modifications to ENKI include a full separation of API and user interface
Seo, Seongho; Kim, Su J; Kim, Yu K; Lee, Jee-Young; Jeong, Jae M; Lee, Dong S; Lee, Jae S
2015-12-01
In recent years, several linearized model approaches for fast and reliable parametric neuroreceptor mapping based on dynamic nuclear imaging have been developed from the simplified reference tissue model (SRTM) equation. All the methods share the basic SRTM assumptions, but use different schemes to alleviate the effect of noise in dynamic-image voxels. Thus, this study aimed to compare those approaches in terms of their performance in parametric image generation. We used the basis function method and MRTM2 (multilinear reference tissue model with two parameters), which require a division process to obtain the distribution volume ratio (DVR). In addition, a linear model with the DVR as a model parameter (multilinear SRTM) was used in two forms: one based on linear least squares and the other based on extension of total least squares (TLS). Assessment using simulated and actual dynamic [(11)C]ABP688 positron emission tomography data revealed their equivalence with the SRTM, except for different noise susceptibilities. In the DVR image production, the two multilinear SRTM approaches achieved better image quality and regional compatibility with the SRTM than the others, with slightly better performance in the TLS-based method. PMID:26243707
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
Javed, Sajid; Marsay, Leanne; Wareham, Alice; Lewandowski, Kuiama S; Williams, Ann; Dennis, Michael J; Sharpe, Sally; Vipond, Richard; Silman, Nigel; Ball, Graham; Kempsell, Karen E
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 between
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.
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.
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.
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.
Optical filtering enabled by cascaded parametric amplification.
McKinstrie, C J; Dailey, J M; Agarwal, A; Toliver, P
2016-06-27
A cascaded parametric amplifier consists of a first parametric amplifier, which amplifies an input signal and generates an idler, which is a copy of the signal, a signal processor, which controls the phases of the signal and idler, and a second parametric amplifier, which combines the signal and idler in a phase-sensitive manner. In this paper, cascaded parametric amplification is modeled and the conditions required to maximize the constructive-destructive extinction ratio are determined. The results show that a cascaded parametric amplifier can be operated as a filter: A desired signal-idler pair is amplified, whereas undesired signal-idler pairs are deamplified. For the desired signal and idler, the noise figures of the filtering process (input signal-to-noise ratio divided by the output ratios) are only slightly higher than those of the copying process: Signal-processing functionality can be achieved with only a minor degradation in signal quality. PMID:27410581
Modeling the mineralogy of atmospheric dust sources
NASA Astrophysics Data System (ADS)
Claquin, T.; Schulz, M.; Balkanski, Y. J.
1999-09-01
The variability of atmospheric dust mineralogy influences the impact of desert dust on the Earth's radiative budget and biogeochemical cycles. Until now, atmospheric transport models have assumed that dust was a constant homogeneous mixture, hence neglecting this variability. The lack of mineralogical data in arid areas prevented a better description of the atmospheric dust composition, and we propose here a new formulation to estimate the mineral content of arid surfaces on a global scale. First, we collect a Database of Arid Soil Surface Mineralogy for eight major minerals: quartz, feldspar, calcite, gypsum, illite, kaolinite, smectite, and hematite, both for the clay and silt fraction. On the basis of this, we formulate a Mean Mineralogical Table that relates classical soil types to surface mineralogy. We use this table and the geographical distribution of soil types given in the Food and Agriculture Organization Soil Map of the World to obtain the mineralogy of arid surfaces globally. In order to validate these results, we present a compilation of measured mineralogical composition of dust samples with identified sources. The correlation between observed dust mineralogy and those inferred from soil types in corresponding areas is between 0.70 and 0.94. We then calculate the maps of the single scattering albedo and of the ratio of infrared extinction to visible extinction for the erodible fraction of arid areas. Mineralogical maps presented here will be used in future studies with an emission scheme in a global transport model.
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
NASA Astrophysics Data System (ADS)
Bedogni, Roberto; Pelliccioni, Maurizio; Esposito, Adolfo
2010-03-01
Due to the increased interest of the scientific community in the applications of synchrotron light, there is an increasing demand of high-energy electron facilities, testified by the construction of several new facilities worldwide. The radiation protection around such facilities requires accurate experimental methods to determine the dose due to prompt radiation fields. Neutron fields, in particular, are the most complex to measure, because they extend in energy from thermal (10 -8 MeV) up to hundreds MeV and because the responses of dosemeters and survey meters usually have large energy dependence. The Bonner Spheres Spectrometer (BSS) is in practice the only instrument able to respond over the whole energy range of interest, and for this reason it is frequently used to derive neutron spectra and dosimetric quantities in accelerator workplaces. Nevertheless, complex unfolding algorithms are needed to derive the neutron spectra from the experimental BSS data. This paper presents a parametric model specially developed for the unfolding of the experimental data measured with BSS around high-energy electron accelerators. The work consists of the following stages: (1) Generation with the FLUKA code, of a set of neutron spectra representing the radiation environment around accelerators with different electron energies; (2) formulation of a parametric model able to describe these spectra, with particular attention to the high-energy component (>10 MeV), which may be responsible for a large part of the dose in workplaces; and (3) implementation of this model in an existing unfolding code.
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
Optimal Parametric Feedback Excitation of Nonlinear Oscillators
NASA Astrophysics Data System (ADS)
Braun, David J.
2016-01-01
An optimal parametric feedback excitation principle is sought, found, and investigated. The principle is shown to provide an adaptive resonance condition that enables unprecedentedly robust movement generation in a large class of oscillatory dynamical systems. Experimental demonstration of the theory is provided by a nonlinear electronic circuit that realizes self-adaptive parametric excitation without model information, signal processing, and control computation. The observed behavior dramatically differs from the one achievable using classical parametric modulation, which is fundamentally limited by uncertainties in model information and nonlinear effects inevitably present in real world applications.
Optimal Parametric Feedback Excitation of Nonlinear Oscillators.
Braun, David J
2016-01-29
An optimal parametric feedback excitation principle is sought, found, and investigated. The principle is shown to provide an adaptive resonance condition that enables unprecedentedly robust movement generation in a large class of oscillatory dynamical systems. Experimental demonstration of the theory is provided by a nonlinear electronic circuit that realizes self-adaptive parametric excitation without model information, signal processing, and control computation. The observed behavior dramatically differs from the one achievable using classical parametric modulation, which is fundamentally limited by uncertainties in model information and nonlinear effects inevitably present in real world applications. PMID:26871336
A practical PEM fuel cell model for simulating vehicle power sources
Amphlett, J.C.; Mann, R.F.; Peppley, B.A.; Roberge, P.R.; Rodrigues, A.
1995-07-01
The interest in fuel cell technology as an alternative to internal combustion engines is growing rapidly with the increased concern with environmental issues such s reducing vehicle emissions. Fuel cells offer a power source which produces electrical energy from fuel and oxidant which produce little or no emissions. Fuel cell power sources are being considered for both terrestrial and marine applications. The research and commercialization of such systems require system modeling to determine performance levels and fuel and oxidant requirements. A practical model will have to be flexible in its calculations depending on the information available. A model predicting the performance of a proton exchange membrane fuel cell has been developed for a Ballard Mark V 5 kW 35-cell stack. The parametric model combining both empirical and mechanistic qualities was developed to calculate the cell voltage output in terms of complex relationships between current, stack temperature, and inlet partial pressure of hydrogen and oxygen. The model utilizes an iterative computer solution to obtain a practical flexible model which could calculate any variable in terms of the others. This paper illustrates the use of a practical model to determine the fuel and oxidant requirements to achieve various levels of power required for different vehicle power supplies. Applications to automobiles, buses, locomotives, ships, submarines, and unmanned underwater vehicles with power supplies of 3--3,000 kW were investigated.
Lau, Bryan; Cole, Stephen R.; Gange, Stephen J.
2010-01-01
In the analysis of survival data, there are often competing events that preclude an event of interest from occurring. Regression analysis with competing risks is typically undertaken using a cause-specific proportional hazards model. However, modern alternative methods exist for the analysis of the subdistribution hazard with a corresponding subdistribution proportional hazards model. In this paper, we introduce a flexible parametric mixture model as a unifying method to obtain estimates of the cause-specific and subdistribution hazards and hazard ratio functions. We describe how these estimates can be summarized over time to give a single number that is comparable to the hazard ratio that is obtained from a corresponding cause-specific or subdistribution proportional hazards model. An application to the Women’s Interagency HIV Study is provided to investigate injection drug use and the time to either the initiation of effective antiretroviral therapy, or clinical disease progression as a competing event. PMID:21337360
Oostrom, Mart ); Lenhard, Robert J.
1998-01-01
To test and evaluate the ability of commonly used constitutive relations to predict multi-fluid flow, predictions for a numerical flow and transport simulator are compared to experimental data. Three quantitative experiments were conducted in one meter-long vertical columns. The columns were filled with either a uniform sand, a sand with a broad particle-size distribution, or with a layered system where a layer of a coarse-textured uniform sand was placed between two layers of a finer-textured uniform sand. After establishing a variably water-saturated condition, a slug of a light nonaqueous-phase liquid (LNAPL) was injected uniformly at a constant rate. Water and LNAPL saturations were measured as a function of time and elevation with a dual energy gamma-radiation system. The infiltration and redistribution of the LNAPL were simulated with nonhysteretic and hysteretic parametric relative permeability saturation-pressure (k-S-P ) models. The models were calibrated using two-phase air water retention data and an established scaling theory. The nonhysteretic Brooks Corey k-S-P model, which utilizes the Burdine relative permeability model, yielded predictions that closely matched the experimental data. Use of the nonhysteretic and hysteretic k-S-P models, based on the van Genuchten S-P relations and k-S relations derived from the Mualem relative permeability model, did not agree as well with the experimental data as those obtained with the Brooks-Corey k-S-P model. Explanations for the differences in performance of the three tested parametric k-S-P models are proposed.
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.
Combining sources in stable isotope mixing models: alternative methods.
Phillips, Donald L; Newsome, Seth D; Gregg, Jillian W
2005-08-01
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 sources to allow a unique solution. We discuss two alternative procedures for addressing this problem. One option is a priori to combine sources with similar signatures so the number of sources is small enough to provide a unique solution. Aggregation should be considered only when isotopic signatures of clustered sources are not significantly different, and sources are related so the combined source group has some functional significance. For example, in a food web analysis, lumping several species within a trophic guild allows more interpretable results than lumping disparate food sources, even if they have similar isotopic signatures. One result of combining mixing model sources is increased uncertainty of the combined end-member isotopic signatures and consequently the source contribution estimates; this effect can be quantified using the IsoError model (http://www.epa.gov/wed/pages/models/isotopes/isoerror1_04.htm). As an alternative to lumping sources before a mixing analysis, the IsoSource mixing model (http://www.epa.gov/wed/pages/models/isosource/isosource.htm) can be used to find all feasible solutions of source contributions consistent with isotopic mass balance. While ranges of feasible contributions for each individual source can often be quite broad, contributions from functionally related groups of sources can be summed a posteriori, producing a range of solutions for the aggregate source that may be considerably narrower. A paleo-human dietary analysis example illustrates this method, which involves a terrestrial meat food source, a combination of three terrestrial plant foods, and a combination of three marine foods. In this case, a posteriori aggregation of sources allowed
RECEPTOR MODELS RELATING AMBIENT SUSPENDED PARTICULATE MATTER TO SOURCES
The report describes the use of receptor models to determine the source contributions to ambient particulate matter loadings at sampling sites, based on common properties between sources and receptors. (This is in contrast to using source models which start with emission rates an...
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.
Monte Carlo source model for photon beam radiotherapy: photon source characteristics
Fix, Michael K.; Keall, Paul J.; Dawson, Kathryn; Siebers, Jeffrey V.
2004-11-01
A major barrier to widespread clinical implementation of Monte Carlo dose calculation is the difficulty in characterizing the radiation source within a generalized source model. This work aims to develop a generalized three-component source model (target, primary collimator, flattening filter) for 6- and 18-MV photon beams that match full phase-space data (PSD). Subsource by subsource comparison of dose distributions, using either source PSD or the source model as input, allows accurate source characterization and has the potential to ease the commissioning procedure, since it is possible to obtain information about which subsource needs to be tuned. This source model is unique in that, compared to previous source models, it retains additional correlations among PS variables, which improves accuracy at nonstandard source-to-surface distances (SSDs). In our study, three-dimensional (3D) dose calculations were performed for SSDs ranging from 50 to 200 cm and for field sizes from 1x1 to 30x30 cm{sup 2} as well as a 10x10 cm{sup 2} field 5 cm off axis in each direction. The 3D dose distributions, using either full PSD or the source model as input, were compared in terms of dose-difference and distance-to-agreement. With this model, over 99% of the voxels agreed within {+-}1% or 1 mm for the target, within 2% or 2 mm for the primary collimator, and within {+-}2.5% or 2 mm for the flattening filter in all cases studied. For the dose distributions, 99% of the dose voxels agreed within 1% or 1 mm when the combined source model--including a charged particle source and the full PSD as input--was used. The accurate and general characterization of each photon source and knowledge of the subsource dose distributions should facilitate source model commissioning procedures by allowing scaling the histogram distributions representing the subsources to be tuned.
NASA Astrophysics Data System (ADS)
Delogu, A.; Furini, F.
1991-09-01
Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.
03 SOURCE APPORTIONMENT/RECEPTOR MODELING:OBM FOCUS
Source apportionment (receptor) models are mathematical procedures for identifying and quantifying the sources of ambient air pollutants and their effects at a site (the receptor), primarily on the basis of species concentration measurements at the receptor, and generally without...
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 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.
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.
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. PMID:26802012
REVIEW OF INDOOR EMISSION SOURCE MODELS--PART 1. OVERVIEW
Indoor emission source models are mainly used as a component in indoor air quality (IAQ) and exposure modeling. They are also widely used to interpret the experimental data obtained from environmental chambers and buildings. This paper compiles 46 indoor emission source models fo...
NASA Astrophysics Data System (ADS)
Li, Yun-He; Zhang, Jing-Fei; Zhang, Xin
2014-12-01
Dark energy can modify the dynamics of dark matter if there exists a direct interaction between them. Thus, a measurement of the structure growth, e.g., redshift-space distortions (RSDs), can provide a powerful tool to constrain the interacting dark energy (IDE) models. For the widely studied Q =3 β H ρde model, previous works showed that only a very small coupling [β ˜O (10-3) ] can survive in current RSD data. However, all of these analyses had to assume w >-1 and β >0 due to the existence of the large-scale instability in the IDE scenario. In our recent work [Phys. Rev. D 90, 063005 (2014)], we successfully solved this large-scale instability problem by establishing a parametrized post-Friedmann framework for the IDE scenario. So we, for the first time, have the ability to explore the full parameter space of the IDE models. In this work, we re-examine the observational constraints on the Q =3 β H ρde model within the parametrized post-Friedmann framework. By using the Planck data, the baryon acoustic oscillation data, the JLA sample of supernovae, and the Hubble constant measurement, we get β =-0.01 0-0.033+0.037 (1 σ ). The fit result becomes β =-0.014 8-0.0089+0.0100 (1 σ ) once we further incorporate the RSD data in the analysis. The error of β is substantially reduced with the help of the RSD data. Compared with the previous results, our results show that a negative β is favored by current observations, and a relatively larger interaction rate is permitted by current RSD data.
Models for galactic X-ray sources
NASA Technical Reports Server (NTRS)
Joss, P. C.
1980-01-01
Attention is given to those compact galactic X-ray sources whose X-ray luminosities are considerably in excess of the solar luminosity. It is pointed out that the key breakthrough in the development of an understanding of compact galactic X-ray sources was the discovery of X-ray pulsars with the UHURU satellite. There is now overwhelming evidence that these objects are neutron stars in close binary stellar systems. The X-ray pulsations are thought to be thermal emission from the magnetic polar caps of a neutron star that is accreting matter from a companion star and whose magnetic field is misaligned with its rotation axis. Among the compact galactic X-ray sources that are not X-ray pulsars, some still show direct evidence of binary membership, such as X-ray eclipses. There is evidence that the galactic-bulge sources are, in fact, close binary stellar systems. It is concluded, that the great majority of bright galactic X-ray sources, with only a tiny handful of exceptions (such as the Crab and Vela pulsars), are likely to be binaries.
NASA Astrophysics Data System (ADS)
Durmaz, Murat; Karslioglu, Mahmut Onur
2015-04-01
There are various global and regional methods that have been proposed for the modeling of ionospheric vertical total electron content (VTEC). Global distribution of VTEC is usually modeled by spherical harmonic expansions, while tensor products of compactly supported univariate B-splines can be used for regional modeling. In these empirical parametric models, the coefficients of the basis functions as well as differential code biases (DCBs) of satellites and receivers can be treated as unknown parameters which can be estimated from geometry-free linear combinations of global positioning system observables. In this work we propose a new semi-parametric multivariate adaptive regression B-splines (SP-BMARS) method for the regional modeling of VTEC together with satellite and receiver DCBs, where the parametric part of the model is related to the DCBs as fixed parameters and the non-parametric part adaptively models the spatio-temporal distribution of VTEC. The latter is based on multivariate adaptive regression B-splines which is a non-parametric modeling technique making use of compactly supported B-spline basis functions that are generated from the observations automatically. This algorithm takes advantage of an adaptive scale-by-scale model building strategy that searches for best-fitting B-splines to the data at each scale. The VTEC maps generated from the proposed method are compared numerically and visually with the global ionosphere maps (GIMs) which are provided by the Center for Orbit Determination in Europe (CODE). The VTEC values from SP-BMARS and CODE GIMs are also compared with VTEC values obtained through calibration using local ionospheric model. The estimated satellite and receiver DCBs from the SP-BMARS model are compared with the CODE distributed DCBs. The results show that the SP-BMARS algorithm can be used to estimate satellite and receiver DCBs while adaptively and flexibly modeling the daily regional VTEC.
Discussion of Source Reconstruction Models Using 3D MCG Data
NASA Astrophysics Data System (ADS)
Melis, Massimo De; Uchikawa, Yoshinori
In this study we performed the source reconstruction of magnetocardiographic signals generated by the human heart activity to localize the site of origin of the heart activation. The localizations were performed in a four compartment model of the human volume conductor. The analyses were conducted on normal subjects and on a subject affected by the Wolff-Parkinson-White syndrome. Different models of the source activation were used to evaluate whether a general model of the current source can be applied in the study of the cardiac inverse problem. The data analyses were repeated using normal and vector component data of the MCG. The results show that a distributed source model has the better accuracy in performing the source reconstructions, and that 3D MCG data allow finding smaller differences between the different source models.
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.
On enhancement of vibration-based energy harvesting by a random parametric excitation
NASA Astrophysics Data System (ADS)
Bobryk, Roman V.; Yurchenko, Daniil
2016-03-01
An electromechanical linear oscillator with a random ambient excitation and telegraphic noise parametric excitation is considered as an energy harvester model. It is shown that a parametric colored excitation can have a dramatic effect on the enhancement of the energy harvesting. A close relation with mean-square stability of the oscillator is established. Four sources of the ambient excitation are considered: the white noise, the Ornstein-Uhlenbeck noise, the harmonic noise and the periodic function. Analytical expressions for stationary electrical net mean power are presented for all the considered cases, confirming the proposed approach.
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.
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...
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…
NASA Astrophysics Data System (ADS)
Baker, Kirk R.; Kelly, James T.
2014-10-01
Some sources may need to estimate ozone and secondarily formed PM2.5 as part of the permit application process under the Clean Air Act New Source Review program. Photochemical grid models represent state-of-the-science gas- and particle-phase chemistry and provide a realistic chemical and physical environment for assessing changes in air quality resulting from changes in emissions. When using these tools for single source impact assessments, it is important to differentiate a single source impact from other emissions sources and to understand how well contemporary grid model applications capture near-source transport and chemistry. Here for the first time, both source apportionment and source sensitivity approaches (brute-force changes and high-order direct decoupled method) are used in a photochemical grid model to isolate impacts of a specific facility. These single source impacts are compared with in-plume measurements made as part of a well-characterized 1999 TVA Cumberland aircraft plume transect field study. The techniques were able to isolate the impacts of the TVA plume in a manner consistent with observations. The model predicted in-plume concentrations well when the observations were averaged to the grid scale, although peak concentrations of primary pollutants were generally underestimated near the source, possibly due to dilution in the 4-km grid cell.
Receptor modeling application framework for particle source apportionment.
Watson, John G; Zhu, Tan; Chow, Judith C; Engelbrecht, Johann; Fujita, Eric M; Wilson, William E
2002-12-01
Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses. PMID:12492167
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.
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