Computations of Flow over a Hump Model Using Higher Order Method with Turbulence Modeling

NASA Technical Reports Server (NTRS)

Balakumar, P.

2005-01-01

Turbulent separated flow over a two-dimensional hump is computed by solving the RANS equations with k - omega (SST) turbulence model for the baseline, steady suction and oscillatory blowing/suction flow control cases. The flow equations and the turbulent model equations are solved using a fifth-order accurate weighted essentially. nonoscillatory (WENO) scheme for space discretization and a third order, total variation diminishing (TVD) Runge-Kutta scheme for time integration. Qualitatively the computed pressure distributions exhibit the same behavior as those observed in the experiments. The computed separation regions are much longer than those observed experimentally. However, the percentage reduction in the separation region in the steady suction case is closer to what was measured in the experiment. The computations did not predict the expected reduction in the separation length in the oscillatory case. The predicted turbulent quantities are two to three times smaller than the measured values pointing towards the deficiencies in the existing turbulent models when they are applied to strong steady/unsteady separated flows.

Neuronal pattern separation of motion-relevant input in LIP activity

PubMed Central

Berberian, Nareg; MacPherson, Amanda; Giraud, Eloïse; Richardson, Lydia

2016-01-01

In various regions of the brain, neurons discriminate sensory stimuli by decreasing the similarity between ambiguous input patterns. Here, we examine whether this process of pattern separation may drive the rapid discrimination of visual motion stimuli in the lateral intraparietal area (LIP). Starting with a simple mean-rate population model that captures neuronal activity in LIP, we show that overlapping input patterns can be reformatted dynamically to give rise to separated patterns of neuronal activity. The population model predicts that a key ingredient of pattern separation is the presence of heterogeneity in the response of individual units. Furthermore, the model proposes that pattern separation relies on heterogeneity in the temporal dynamics of neural activity and not merely in the mean firing rates of individual neurons over time. We confirm these predictions in recordings of macaque LIP neurons and show that the accuracy of pattern separation is a strong predictor of behavioral performance. Overall, results propose that LIP relies on neuronal pattern separation to facilitate decision-relevant discrimination of sensory stimuli. NEW & NOTEWORTHY A new hypothesis is proposed on the role of the lateral intraparietal (LIP) region of cortex during rapid decision making. This hypothesis suggests that LIP alters the representation of ambiguous inputs to reduce their overlap, thus improving sensory discrimination. A combination of computational modeling, theoretical analysis, and electrophysiological data shows that the pattern separation hypothesis links neural activity to behavior and offers novel predictions on the role of LIP during sensory discrimination. PMID:27881719

Rolling Process Modeling Report: Finite-Element Prediction of Roll Separating Force and Rolling Defects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.

2014-04-23

Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum (U-10Mo) alloy plate-type fuel for the U.S. high-performance research reactors. This work supports the Convert Program of the U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) Global Threat Reduction Initiative. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll separating forces and rolling defects. Simulations were performed using a finite-element model developed using the commercial code LS-Dyna. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel have been conducted following two different schedules. Model predictions ofmore » the roll-separation force and roll-pack thicknesses at different stages of the rolling process were compared with experimental measurements. This report discusses various attributes of the rolled coupons revealed by the model (e.g., dog-boning and thickness non-uniformity).« less

Prediction of Laminar and Turbulent Boundary Layer Flow Separation in V/STOL Engine Inlets

NASA Technical Reports Server (NTRS)

Chou, D. C.; Luidens, R. W.; Stockman, N. O.

1977-01-01

A description is presented of the development of the boundary layer on the lip and diffuser surface of a subsonic inlet at arbitrary operating conditions of mass flow rate, free stream velocity and incidence angle. Both laminar separation on the lip and turbulent separation in the diffuser are discussed. The agreement of the theoretical results with model experimental data illustrates the capability of the theory to predict separation. The effects of throat Mach number, inlet size, and surface roughness on boundary layer development and separation are illustrated.

Perspectives on multifield models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banerjee, S.

1997-07-01

Multifield models for prediction of nuclear reactor thermalhydraulics are reviewed from the viewpoint of their structure and requirements for closure relationships. Their strengths and weaknesses are illustrated with examples, indicating that they are effective in predicting separated and distributed flow regimes, but have problems for flows with large oscillations. Needs for multifield models are also discussed in the context of reactor operations and accident simulations. The highest priorities for future developments appear to relate to closure relationships for three-dimensional multifield models with emphasis on those needed for calculations of phase separation and entrainment/de-entrainment in complex geometries.

Predictions of Separated and Transitional Boundary Layers Under Low-Pressure Turbine Airfoil Conditions Using an Intermittency Transport Equation

NASA Technical Reports Server (NTRS)

Suzen, Y. Bora; Huang, P. G.; Hultgren, Lennart S.; Ashpis, David E.

2001-01-01

A new transport equation for the intermittency factor was proposed to predict separated and transitional boundary layers under low-pressure turbine airfoil conditions. The intermittent behavior of the transitional flows is taken into account and incorporated into computations by modifying the eddy viscosity, mu(sub t), with the intermittency factor, gamma. Turbulent quantities are predicted by using Menter's two-equation turbulence model (SST). The intermittency factor is obtained from a transport equation model, which not only can reproduce the experimentally observed streamwise variation of the intermittency in the transition zone, but also can provide a realistic cross-stream variation of the intermittency profile. In this paper, the intermittency model is used to predict a recent separated and transitional boundary layer experiment under low pressure turbine airfoil conditions. The experiment provides detailed measurements of velocity, turbulent kinetic energy and intermittency profiles for a number of Reynolds numbers and freestream turbulent intensity conditions and is suitable for validation purposes. Detailed comparisons of computational results with experimental data are presented and good agreements between the experiments and predictions are obtained.

Predictions of Separated and Transitional Boundary Layers Under Low-Pressure Turbine Airfoil Conditions Using an Intermittency Transport Equation

NASA Technical Reports Server (NTRS)

Suzen, Y. B.; Huang, P. G.; Hultgren, Lennart S.; Ashpis, David E.

2003-01-01

A new transport equation for the intermittency factor was proposed to predict separated and transitional boundary layers under low-pressure turbine airfoil conditions. The intermittent behavior of the transitional flows is taken into account and incorporated into computations by modifying the eddy viscosity, t , with the intermittency factor, y. Turbulent quantities are predicted by using Menter s two-equation turbulence model (SST). The intermittency factor is obtained from a transport equation model, which not only can reproduce the experimentally observed streamwise variation of the intermittency in the transition zone, but also can provide a realistic cross-stream variation of the intermittency profile. In this paper, the intermittency model is used to predict a recent separated and transitional boundary layer experiment under low pressure turbine airfoil conditions. The experiment provides detailed measurements of velocity, turbulent kinetic energy and intermittency profiles for a number of Reynolds numbers and freestream turbulent intensity conditions and is suitable for validation purposes. Detailed comparisons of computational results with experimental data are presented and good agreements between the experiments and predictions are obtained.

Rapid determination of thermodynamic parameters from one-dimensional programmed-temperature gas chromatography for use in retention time prediction in comprehensive multidimensional chromatography.

PubMed

McGinitie, Teague M; Ebrahimi-Najafabadi, Heshmatollah; Harynuk, James J

2014-01-17

A new method for estimating the thermodynamic parameters of ΔH(T0), ΔS(T0), and ΔCP for use in thermodynamic modeling of GC×GC separations has been developed. The method is an alternative to the traditional isothermal separations required to fit a three-parameter thermodynamic model to retention data. Herein, a non-linear optimization technique is used to estimate the parameters from a series of temperature-programmed separations using the Nelder-Mead simplex algorithm. With this method, the time required to obtain estimates of thermodynamic parameters a series of analytes is significantly reduced. This new method allows for precise predictions of retention time with the average error being only 0.2s for 1D separations. Predictions for GC×GC separations were also in agreement with experimental measurements; having an average relative error of 0.37% for (1)tr and 2.1% for (2)tr. Copyright © 2013 Elsevier B.V. All rights reserved.

Cell design concepts for aqueous lithium-oxygen batteries: A model-based assessment

NASA Astrophysics Data System (ADS)

Grübl, Daniel; Bessler, Wolfgang G.

2015-11-01

Seven cell design concepts for aqueous (alkaline) lithium-oxygen batteries are investigated using a multi-physics continuum model for predicting cell behavior and performance in terms of the specific energy and specific power. Two different silver-based cathode designs (a gas diffusion electrode and a flooded cathode) and three different separator designs (a porous separator, a stirred separator chamber, and a redox-flow separator) are compared. Cathode and separator thicknesses are varied over a wide range (50 μm-20 mm) in order to identify optimum configurations. All designs show a considerable capacity-rate effect due to spatiotemporally inhomogeneous precipitation of solid discharge product LiOH·H2O. In addition, a cell design with flooded cathode and redox-flow separator including oxygen uptake within the external tank is suggested. For this design, the model predicts specific power up to 33 W/kg and specific energy up to 570 Wh/kg (gravimetric values of discharged cell including all cell components and catholyte except housing and piping).

Biologically driven neural platform invoking parallel electrophoretic separation and urinary metabolite screening.

PubMed

Page, Tessa; Nguyen, Huong Thi Huynh; Hilts, Lindsey; Ramos, Lorena; Hanrahan, Grady

2012-06-01

This work reveals a computational framework for parallel electrophoretic separation of complex biological macromolecules and model urinary metabolites. More specifically, the implementation of a particle swarm optimization (PSO) algorithm on a neural network platform for multiparameter optimization of multiplexed 24-capillary electrophoresis technology with UV detection is highlighted. Two experimental systems were examined: (1) separation of purified rabbit metallothioneins and (2) separation of model toluene urinary metabolites and selected organic acids. Results proved superior to the use of neural networks employing standard back propagation when examining training error, fitting response, and predictive abilities. Simulation runs were obtained as a result of metaheuristic examination of the global search space with experimental responses in good agreement with predicted values. Full separation of selected analytes was realized after employing optimal model conditions. This framework provides guidance for the application of metaheuristic computational tools to aid in future studies involving parallel chemical separation and screening. Adaptable pseudo-code is provided to enable users of varied software packages and modeling framework to implement the PSO algorithm for their desired use.

Numerical Study Comparing RANS and LES Approaches on a Circulation Control Airfoil

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Nishino, Takafumi

2011-01-01

A numerical study over a nominally two-dimensional circulation control airfoil is performed using a large-eddy simulation code and two Reynolds-averaged Navier-Stokes codes. Different Coanda jet blowing conditions are investigated. In addition to investigating the influence of grid density, a comparison is made between incompressible and compressible flow solvers. The incompressible equations are found to yield negligible differences from the compressible equations up to at least a jet exit Mach number of 0.64. The effects of different turbulence models are also studied. Models that do not account for streamline curvature effects tend to predict jet separation from the Coanda surface too late, and can produce non-physical solutions at high blowing rates. Three different turbulence models that account for streamline curvature are compared with each other and with large eddy simulation solutions. All three models are found to predict the Coanda jet separation location reasonably well, but one of the models predicts specific flow field details near the Coanda surface prior to separation much better than the other two. All Reynolds-averaged Navier-Stokes computations produce higher circulation than large eddy simulation computations, with different stagnation point location and greater flow acceleration around the nose onto the upper surface. The precise reasons for the higher circulation are not clear, although it is not solely a function of predicting the jet separation location correctly.

Pattern Separation Deficits Following Damage to the Hippocampus

ERIC Educational Resources Information Center

Kirwan, C. Brock; Hartshorn, Andrew; Stark, Shauna M.; Goodrich-Hunsaker, Naomi J.; Hopkins, Ramona O.; Stark, Craig E. L.

2012-01-01

Computational models of hippocampal function propose that the hippocampus is capable of rapidly storing distinct representations through a process known as pattern separation. This prediction is supported by electrophysiological data from rodents and neuroimaging data from humans. Here, we test the prediction that damage to the hippocampus would…

Heat transfer optimization for air-mist cooling between a stack of parallel plates

NASA Astrophysics Data System (ADS)

Issa, Roy J.

2010-06-01

A theoretical model is developed to predict the upper limit heat transfer between a stack of parallel plates subject to multiphase cooling by air-mist flow. The model predicts the optimal separation distance between the plates based on the development of the boundary layers for small and large separation distances, and for dilute mist conditions. Simulation results show the optimal separation distance to be strongly dependent on the liquid-to-air mass flow rate loading ratio, and reach a limit for a critical loading. For these dilute spray conditions, complete evaporation of the droplets takes place. Simulation results also show the optimal separation distance decreases with the increase in the mist flow rate. The proposed theoretical model shall lead to a better understanding of the design of fins spacing in heat exchangers where multiphase spray cooling is used.

The lagRST Model: A Turbulence Model for Non-Equilibrium Flows

NASA Technical Reports Server (NTRS)

Lillard, Randolph P.; Oliver, A. Brandon; Olsen, Michael E.; Blaisdell, Gregory A.; Lyrintzis, Anastasios S.

2011-01-01

This study presents a new class of turbulence model designed for wall bounded, high Reynolds number flows with separation. The model addresses deficiencies seen in the modeling of nonequilibrium turbulent flows. These flows generally have variable adverse pressure gradients which cause the turbulent quantities to react at a finite rate to changes in the mean flow quantities. This "lag" in the response of the turbulent quantities can t be modeled by most standard turbulence models, which are designed to model equilibrium turbulent boundary layers. The model presented uses a standard 2-equation model as the baseline for turbulent equilibrium calculations, but adds transport equations to account directly for non-equilibrium effects in the Reynolds Stress Tensor (RST) that are seen in large pressure gradients involving shock waves and separation. Comparisons are made to several standard turbulence modeling validation cases, including an incompressible boundary layer (both neutral and adverse pressure gradients), an incompressible mixing layer and a transonic bump flow. In addition, a hypersonic Shock Wave Turbulent Boundary Layer Interaction with separation is assessed along with a transonic capsule flow. Results show a substantial improvement over the baseline models for transonic separated flows. The results are mixed for the SWTBLI flows assessed. Separation predictions are not as good as the baseline models, but the over prediction of the peak heat flux downstream of the reattachment shock that plagues many models is reduced.

Predictions of spray combustion interactions

NASA Technical Reports Server (NTRS)

Shuen, J. S.; Solomon, A. S. P.; Faeth, G. M.

1984-01-01

Mean and fluctuating phase velocities; mean particle mass flux; particle size; and mean gas-phase Reynolds stress, composition and temperature were measured in stationary, turbulent, axisymmetric, and flows which conform to the boundary layer approximations while having well-defined initial and boundary conditions in dilute particle-laden jets, nonevaporating sprays, and evaporating sprays injected into a still air environment. Three models of the processes, typical of current practice, were evaluated. The local homogeneous flow and deterministic separated flow models did not provide very satisfactory predictions over the present data base. In contrast, the stochastic separated flow model generally provided good predictions and appears to be an attractive approach for treating nonlinear interphase transport processes in turbulent flows containing particles (drops).

Predicting the chromatographic retention of polymers: poly(methyl methacrylate)s and polyacryate blends.

PubMed

Bashir, Mubasher A; Radke, Wolfgang

2007-09-07

The suitability of a retention model especially designed for polymers is investigated to describe and predict the chromatographic retention behavior of poly(methyl methacrylate)s as a function of mobile phase composition and gradient steepness. It is found that three simple yet rationally chosen chromatographic experiments suffice to extract the analyte specific model parameters necessary to calculate the retention volumes. This allows predicting accurate retention volumes based on a minimum number of initial experiments. Therefore, methods for polymer separations can be developed in relatively short time. The suitability of the virtual chromatography approach to predict the separation of polymer blend is demonstrated for the first time using a blend of different polyacrylates.

Comparison of Experimental Surface and Flow Field Measurements to Computational Results of the Juncture Flow Model

NASA Technical Reports Server (NTRS)

Roozeboom, Nettie H.; Lee, Henry C.; Simurda, Laura J.; Zilliac, Gregory G.; Pulliam, Thomas H.

2016-01-01

Wing-body juncture flow fields on commercial aircraft configurations are challenging to compute accurately. The NASA Advanced Air Vehicle Program's juncture flow committee is designing an experiment to provide data to improve Computational Fluid Dynamics (CFD) modeling in the juncture flow region. Preliminary design of the model was done using CFD, yet CFD tends to over-predict the separation in the juncture flow region. Risk reduction wind tunnel tests were requisitioned by the committee to obtain a better understanding of the flow characteristics of the designed models. NASA Ames Research Center's Fluid Mechanics Lab performed one of the risk reduction tests. The results of one case, accompanied by CFD simulations, are presented in this paper. Experimental results suggest the wall mounted wind tunnel model produces a thicker boundary layer on the fuselage than the CFD predictions, resulting in a larger wing horseshoe vortex suppressing the side of body separation in the juncture flow region. Compared to experimental results, CFD predicts a thinner boundary layer on the fuselage generates a weaker wing horseshoe vortex resulting in a larger side of body separation.

Kinetics of process of product separation in closed system with recirculation

NASA Astrophysics Data System (ADS)

Prokopenko, V. S.; Orekhova, T. N.; Goncharov, E. I.; Odobesko, I. A.

2018-03-01

The object of an article is the extrapolation of the process of classifying material while passing in a model with the separation of the products of milling in the cleaning system includes a separator, concentrator, cyclone and a recycle loop. The model allows for the given parameters to predict the coarseness of grading of the finished product.

Improving a two-equation eddy-viscosity turbulence model to predict the aerodynamic performance of thick wind turbine airfoils

NASA Astrophysics Data System (ADS)

Bangga, Galih; Kusumadewi, Tri; Hutomo, Go; Sabila, Ahmad; Syawitri, Taurista; Setiadi, Herlambang; Faisal, Muhamad; Wiranegara, Raditya; Hendranata, Yongki; Lastomo, Dwi; Putra, Louis; Kristiadi, Stefanus

2018-03-01

Numerical simulations for relatively thick airfoils are carried out in the present studies. An attempt to improve the accuracy of the numerical predictions is done by adjusting the turbulent viscosity of the eddy-viscosity Menter Shear-Stress-Transport (SST) model. The modification involves the addition of a damping factor on the wall-bounded flows incorporating the ratio of the turbulent kinetic energy to its specific dissipation rate for separation detection. The results are compared with available experimental data and CFD simulations using the original Menter SST model. The present model improves the lift polar prediction even though the stall angle is still overestimated. The improvement is caused by the better prediction of separated flow under a strong adverse pressure gradient. The results show that the Reynolds stresses are damped near the wall causing variation of the logarithmic velocity profiles.

Control of Systems With Slow Actuators Using Time Scale Separation

NASA Technical Reports Server (NTRS)

Stepanyan, Vehram; Nguyen, Nhan

2009-01-01

This paper addresses the problem of controlling a nonlinear plant with a slow actuator using singular perturbation method. For the known plant-actuator cascaded system the proposed scheme achieves tracking of a given reference model with considerably less control demand than would otherwise result when using conventional design techniques. This is the consequence of excluding the small parameter from the actuator dynamics via time scale separation. The resulting tracking error is within the order of this small parameter. For the unknown system the adaptive counterpart is developed based on the prediction model, which is driven towards the reference model by the control design. It is proven that the prediction model tracks the reference model with an error proportional to the small parameter, while the prediction error converges to zero. The resulting closed-loop system with all prediction models and adaptive laws remains stable. The benefits of the approach are demonstrated in simulation studies and compared to conventional control approaches.

The Lag Model, a Turbulence Model for Wall Bounded Flows Including Separation

NASA Technical Reports Server (NTRS)

Olsen, Michael E.; Coakley, Thomas J.; Kwak, Dochan (Technical Monitor)

2001-01-01

A new class of turbulence model is described for wall bounded, high Reynolds number flows. A specific turbulence model is demonstrated, with results for favorable and adverse pressure gradient flowfields. Separation predictions are as good or better than either Spalart Almaras or SST models, do not require specification of wall distance, and have similar or reduced computational effort compared with these models.

Thin-layer approximation and algebraic model for separated turbulent flows

NASA Technical Reports Server (NTRS)

Baldwin, B.; Lomax, H.

1978-01-01

An algebraic turbulence model for two- and three-dimensional separated flows is specified that avoids the necessity for finding the edge of the boundary layer. Properties of the model are determined and comparisons made with experiment for an incident shock on a flat plate, separated flow over a compression corner, and transonic flow over an airfoil. Separation and reattachment points from numerical Navier-Stokes solutions agree with experiment within one boundary-layer thickness. Use of law-of-the-wall boundary conditions does not alter the predictions significantly. Applications of the model to other cases are contained in companion papers.

Compression-recovery model of absorptive glass mat (AGM) separator guided by X-ray micro-computed tomography analysis

NASA Astrophysics Data System (ADS)

Kameswara Rao, P. V.; Rawal, Amit; Kumar, Vijay; Rajput, Krishn Gopal

2017-10-01

Absorptive glass mat (AGM) separators play a key role in enhancing the cycle life of the valve regulated lead acid (VRLA) batteries by maintaining the elastic characteristics under a defined level of compression force with the plates of the electrodes. Inevitably, there are inherent challenges to maintain the required level of compression characteristics of AGM separators during the charge and discharge of the battery. Herein, we report a three-dimensional (3D) analytical model for predicting the compression-recovery behavior of AGM separators by formulating a direct relationship with the constituent fiber and structural parameters. The analytical model of compression-recovery behavior of AGM separators has successfully included the fiber slippage criterion and internal friction losses. The presented work uses, for the first time, 3D data of fiber orientation from X-ray micro-computed tomography, for predicting the compression-recovery behavior of AGM separators. A comparison has been made between the theoretical and experimental results of compression-recovery behavior of AGM samples with defined fiber orientation characteristics. In general, the theory agreed reasonably well with the experimental results of AGM samples in both dry and wet states. Through theoretical modeling, fiber volume fraction was established as one of the key structural parameters that modulates the compression hysteresis of an AGM separator.

Computation of turbulent flows over backward and forward-facing steps using a near-wall Reynolds stress model

NASA Technical Reports Server (NTRS)

Ko, Sung HO

1993-01-01

Separation and reattachment of turbulent shear layers is observed in many important engineering applications, yet it is poorly understood. This has motivated many studies on understanding and predicting the processes of separation and reattachment of turbulent shear layers. Both of the situations in which separation is induced by adverse pressure gradient, or by discontinuities of geometry, have attracted attention of turbulence model developers. Formulation of turbulence closure models to describe the essential features of separated turbulent flows accurately is still a formidable task. Computations of separated flows associated with sharp-edged bluff bodies are described. For the past two decades, the backward-facing step flow, the simplest separated flow, has been a popular test case for turbulence models. Detailed studies on the performance of many turbulence models, including two equation turbulence models and Reynolds stress models, for flows over steps can be found in the papers by Thangam & Speziale and Lasher & Taulbee). These studies indicate that almost all the existing turbulence models fail to accurately predict many important features of back step flow such as reattachment length, recovery rate of the redeveloping boundary layers downstream of the reattachment point, streamlines near the reattachment point, and the skin friction coefficient. The main objectives are to calculate flows over backward and forward-facing steps using the NRSM and to make use of the newest DNS data for detailed comparison. This will give insights for possible improvements of the turbulence model.

Massive separation around bluff bodies: comparisons among different cfd solvers and turbulence models

NASA Astrophysics Data System (ADS)

Armenio, Vincenzo; Fakhari, Ahmad; Petronio, Andrea; Padovan, Roberta; Pittaluga, Chiara; Caprino, Giovanni

2015-11-01

Massive flow separation is ubiquitous in industrial applications, ruling drag and hydrodynamic noise. In spite of considerable efforts, its numerical prediction still represents a challenge for CFD models in use in engineering. Aside commercial software, over the latter years the opensource software OpenFOAMR (OF) has emerged as a valid tool for prediction of complex industrial flows. In the present work, we simulate two flows representative of a class of situations occurring in industrial problems: the flow around sphere and that around a wall-mounted square cylinder at Re = 10000 . We compare the performance two different tools, namely OF and ANSYS CFX 15.0 (CFX) using different unstructured grids and turbulence models. The grids have been generated using SNAPPYHEXMESH and ANSYS ICEM CFD 15.0 with different near wall resolutions. The codes have been run in a RANS mode using k - ɛ model (OF) and SST - k - ω (CFX) with and without wall-layer models. OF has been also used in LES, WMLES and DES mode. Regarding the sphere, RANS models were not able to catch separation, while good prediction of separation and distribution of stresses over the surface were obtained using LES, WMLES and DES. Results for the second test case are currently under analysis. Financial support from COSMO ``cfd open source per opera mortta'' PAR FSC 2007-2013, Friuli Venezia Giulia.

A fracture mechanics study of the phase separating planar electrodes: Phase field modeling and analytical results

NASA Astrophysics Data System (ADS)

Haftbaradaran, H.; Maddahian, A.; Mossaiby, F.

2017-05-01

It is well known that phase separation could severely intensify mechanical degradation and expedite capacity fading in lithium-ion battery electrodes during electrochemical cycling. Experiments have frequently revealed that such degradation effects could be substantially mitigated via reducing the electrode feature size to the nanoscale. The purpose of this work is to present a fracture mechanics study of the phase separating planar electrodes. To this end, a phase field model is utilized to predict how phase separation affects evolution of the solute distribution and stress profile in a planar electrode. Behavior of the preexisting flaws in the electrode in response to the diffusion induced stresses is then examined via computing the time dependent stress intensity factor arising at the tip of flaws during both the insertion and extraction half-cycles. Further, adopting a sharp-interphase approximation of the system, a critical electrode thickness is derived below which the phase separating electrode becomes flaw tolerant. Numerical results of the phase field model are also compared against analytical predictions of the sharp-interphase model. The results are further discussed with reference to the available experiments in the literature. Finally, some of the limitations of the model are cautioned.

Modeling stick-slip-separation dynamics in a bimodal standing wave ultrasonic motor

NASA Astrophysics Data System (ADS)

Li, Xiang; Yao, Zhiyuan; Lv, Qibao; Liu, Zhen

2016-11-01

Ultrasonic motor (USM) is an electromechanical coupling system with ultrasonic vibration, which is driven by the frictional contact force between the stator (vibrating body) and the rotor/slider (driven body). Stick-slip motion can occur at the contact interface when USM is operating, which may affect the performance of the motor. This paper develops a physically-based model to investigate the complex stick-slip-separation dynamics in a bimodal standing wave ultrasonic motor. The model includes both friction nonlinearity and intermittent separation nonlinearity of the system. Utilizing Hamilton's principle and assumed mode method, the dynamic equations of the stator are deduced. Based on the dynamics of the stator and the slider, sticking force during the stick phase is derived, which is used to examine the stick-to-slip transition. Furthermore, the stick-slip-separation kinematics is analyzed by establishing analytical criteria that predict the transition between stick, slip and separation of the interface. Stick-slip-separation motion is observed in the resulting model, and numerical simulations are performed to study the influence of parameters on the range of possible motions. Results show that stick-slip motion can occur with greater preload and smaller voltage amplitude. Furthermore, a dimensionless parameter is proposed to predict the occurrence of stick-slip versus slip-separation motions, and its role in designing ultrasonic motors is discussed. It is shown that slip-separation motion is favorable for the slider velocity.

Analysis of two-equation turbulence models for recirculating flows

NASA Technical Reports Server (NTRS)

Thangam, S.

1991-01-01

The two-equation kappa-epsilon model is used to analyze turbulent separated flow past a backward-facing step. It is shown that if the model constraints are modified to be consistent with the accepted energy decay rate for isotropic turbulence, the dominant features of the flow field, namely the size of the separation bubble and the streamwise component of the mean velocity, can be accurately predicted. In addition, except in the vicinity of the step, very good predictions for the turbulent shear stress, the wall pressure, and the wall shear stress are obtained. The model is also shown to provide good predictions for the turbulence intensity in the region downstream of the reattachment point. Estimated long time growth rates for the turbulent kinetic energy and dissipation rate of homogeneous shear flow are utilized to develop an optimal set of constants for the two equation kappa-epsilon model. The physical implications of the model performance are also discussed.

Development of a recursion RNG-based turbulence model

NASA Technical Reports Server (NTRS)

Zhou, YE; Vahala, George; Thangam, S.

1993-01-01

Reynolds stress closure models based on the recursion renormalization group theory are developed for the prediction of turbulent separated flows. The proposed model uses a finite wavenumber truncation scheme to account for the spectral distribution of energy. In particular, the model incorporates effects of both local and nonlocal interactions. The nonlocal interactions are shown to yield a contribution identical to that from the epsilon-renormalization group (RNG), while the local interactions introduce higher order dispersive effects. A formal analysis of the model is presented and its ability to accurately predict separated flows is analyzed from a combined theoretical and computational stand point. Turbulent flow past a backward facing step is chosen as a test case and the results obtained based on detailed computations demonstrate that the proposed recursion -RNG model with finite cut-off wavenumber can yield very good predictions for the backstep problem.

Application of a Full Reynolds Stress Model to High Lift Flows

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Rumsey, C. L.; Eisfeld, B.

2016-01-01

A recently developed second-moment Reynolds stress model was applied to two challenging high-lift flows: (1) transonic flow over the ONERA M6 wing, and (2) subsonic flow over the DLR-F11 wing-body configuration from the second AIAA High Lift Prediction Workshop. In this study, the Reynolds stress model results were contrasted with those obtained from one- and two{equation turbulence models, and were found to be competitive in terms of the prediction of shock location and separation. For an ONERA M6 case, results from multiple codes, grids, and models were compared, with the Reynolds stress model tending to yield a slightly smaller shock-induced separation bubble near the wing tip than the simpler models, but all models were fairly close to the limited experimental surface pressure data. For a series of high-lift DLR{F11 cases, the range of results was more limited, but there was indication that the Reynolds stress model yielded less-separated results than the one-equation model near maximum lift. These less-separated results were similar to results from the one-equation model with a quadratic constitutive relation. Additional computations need to be performed before a more definitive assessment of the Reynolds stress model can be made.

Flowfield dynamics in blunt fin-induced shock wave/turbulent boundary layer interactions

NASA Technical Reports Server (NTRS)

Dolling, David S.; Brusniak, Leon

1994-01-01

Fluctuating wall pressure measurements have been made on centerline upstream of a blunt fin in a Mach 5 turbulent boundary layer. By examining the ensemble averaged wall pressure distributions for different separation shock foot positions, it has been shown that local fluctuating wall pressure measurements are due to a distinct pressure distribution, Rho(sub i), which undergoes a stretching and flattening effect as its upstream boundary translates aperiodically between the upstream influence and separation lines. The locations of the maxima and minima in the wall pressure standard deviation can be accurately predicted using this distribution, providing quantitative confirmation of the model. This model also explains the observed cross-correlations and ensemble average measurements within the interaction. Using the Rho(sub i) model, wall pressure signals from under the separated flow region were used to reproduce the position-time history of the separation shock foot. Further, the negative time delay peak in the cross-correlation between the predicted and actual shock foot histories suggests that the separated region fluctuations precede shock foot motion. The unsteady behavior of the primary horseshoe vortex and its relation to the unsteady separation shock are described.

An Experimental and Computational Investigation of Oscillating Airfoil Unsteady Aerodynamics at Large Mean Incidence

NASA Technical Reports Server (NTRS)

Capece, Vincent R.; Platzer, Max F.

2003-01-01

A major challenge in the design and development of turbomachine airfoils for gas turbine engines is high cycle fatigue failures due to flutter and aerodynamically induced forced vibrations. In order to predict the aeroelastic response of gas turbine airfoils early in the design phase, accurate unsteady aerodynamic models are required. However, accurate predictions of flutter and forced vibration stress at all operating conditions have remained elusive. The overall objectives of this research program are to develop a transition model suitable for unsteady separated flow and quantify the effects of transition on airfoil steady and unsteady aerodynamics for attached and separated flow using this model. Furthermore, the capability of current state-of-the-art unsteady aerodynamic models to predict the oscillating airfoil response of compressor airfoils over a range of realistic reduced frequencies, Mach numbers, and loading levels will be evaluated through correlation with benchmark data. This comprehensive evaluation will assess the assumptions used in unsteady aerodynamic models. The results of this evaluation can be used to direct improvement of current models and the development of future models. The transition modeling effort will also make strides in improving predictions of steady flow performance of fan and compressor blades at off-design conditions. This report summarizes the progress and results obtained in the first year of this program. These include: installation and verification of the operation of the parallel version of TURBO; the grid generation and initiation of steady flow simulations of the NASA/Pratt&Whitney airfoil at a Mach number of 0.5 and chordal incidence angles of 0 and 10 deg.; and the investigation of the prediction of laminar separation bubbles on a NACA 0012 airfoil.

Separability of drag and thrust in undulatory animals and machines

NASA Astrophysics Data System (ADS)

Bale, Rahul; Shirgaonkar, Anup A.; Neveln, Izaak D.; Bhalla, Amneet Pal Singh; Maciver, Malcolm A.; Patankar, Neelesh A.

2014-12-01

For nearly a century, researchers have tried to understand the swimming of aquatic animals in terms of a balance between the forward thrust from swimming movements and drag on the body. Prior approaches have failed to provide a separation of these two forces for undulatory swimmers such as lamprey and eels, where most parts of the body are simultaneously generating drag and thrust. We nonetheless show that this separation is possible, and delineate its fundamental basis in undulatory swimmers. Our approach unifies a vast diversity of undulatory aquatic animals (anguilliform, sub-carangiform, gymnotiform, bal-istiform, rajiform) and provides design principles for highly agile bioinspired underwater vehicles. This approach has practical utility within biology as well as engineering. It is a predictive tool for use in understanding the role of the mechanics of movement in the evolutionary emergence of morphological features relating to locomotion. For example, we demonstrate that the drag-thrust separation framework helps to predict the observed height of the ribbon fin of electric knifefish, a diverse group of neotropical fish which are an important model system in sensory neurobiology. We also show how drag-thrust separation leads to models that can predict the swimming velocity of an organism or a robotic vehicle.

Prediction of the structure of fuel sprays in gas turbine combustors

NASA Technical Reports Server (NTRS)

Shuen, J. S.

1985-01-01

The structure of fuel sprays in a combustion chamber is theoretically investigated using computer models of current interest. Three representative spray models are considered: (1) a locally homogeneous flow (LHF) model, which assumes infinitely fast interphase transport rates; (2) a deterministic separated flow (DSF) model, which considers finite rates of interphase transport but ignores effects of droplet/turbulence interactions; and (3) a stochastic separated flow (SSF) model, which considers droplet/turbulence interactions using random sampling for turbulence properties in conjunction with random-walk computations for droplet motion and transport. Two flow conditions are studied to investigate the influence of swirl on droplet life histories and the effects of droplet/turbulence interactions on flow properties. Comparison of computed results with the experimental data show that general features of the flow structure can be predicted with reasonable accuracy using the two separated flow models. In contrast, the LHF model overpredicts the rate of development of the flow. While the SSF model provides better agreement with measurements than the DSF model, definitive evaluation of the significance of droplet/turbulence interaction is not achieved due to uncertainties in the spray initial conditions.

New mathematic model for predicting chiral separation using molecular docking: mechanism of chiral recognition of triadimenol analogues.

PubMed

Zhang, Guoqing; Sun, Qingyan; Hou, Ying; Hong, Zhanying; Zhang, Jun; Zhao, Liang; Zhang, Hai; Chai, Yifeng

2009-07-01

The purpose of this paper was to study the enantioseparation mechanism of triadimenol compounds by carboxymethylated (CM)-beta-CD mediated CE. All the enantiomers were separated under the same experimental conditions to study the chiral recognition mechanism using a 30 mM sodium dihydrogen phosphate buffer at pH 2.2 adjusted by phosphoric acid. The inclusion courses between CM-beta-CD and enantiomers were investigated by the means of molecular docking technique. It was found that there were at least three points (one hydrophobic bond and two hydrogen bonds) involved in the interaction of each enantiomer with the chiral selectors. A new mathematic model has been built up based on the results of molecular mechanics calculations, which could analyze the relationship between the resolution of enantioseparation and the interaction energy in the docking area. Comparing the results of the separation by CE, the established mathematic model demonstrated good capability to predict chiral separation of triadimenol enantiomers using CM-beta-CD mediated CE.

Turbulence Modeling for Shock Wave/Turbulent Boundary Layer Interactions

NASA Technical Reports Server (NTRS)

Lillard, Randolph P.

2011-01-01

Accurate aerodynamic computational predictions are essential for the safety of space vehicles, but these computations are of limited accuracy when large pressure gradients are present in the flow. The goal of the current project is to improve the state of compressible turbulence modeling for high speed flows with shock wave / turbulent boundary layer interactions (SWTBLI). Emphasis will be placed on models that can accurately predict the separated region caused by the SWTBLI. These flows are classified as nonequilibrium boundary layers because of the very large and variable adverse pressure gradients caused by the shock waves. The lag model was designed to model these nonequilibrium flows by incorporating history effects. Standard one- and two-equation models (Spalart Allmaras and SST) and the lag model will be run and compared to a new lag model. This new model, the Reynolds stress tensor lag model (lagRST), will be assessed against multiple wind tunnel tests and correlations. The basis of the lag and lagRST models are to preserve the accuracy of the standard turbulence models in equilibrium turbulence, when the Reynolds stresses are linearly related to the mean strain rates, but create a lag between mean strain rate effects and turbulence when nonequilibrium effects become important, such as in large pressure gradients. The affect this lag has on the results for SWBLI and massively separated flows will be determined. These computations will be done with a modified version of the OVERFLOW code. This code solves the RANS equations on overset grids. It was used for this study for its ability to input very complex geometries into the flow solver, such as the Space Shuttle in the full stack configuration. The model was successfully implemented within two versions of the OVERFLOW code. Results show a substantial improvement over the baseline models for transonic separated flows. The results are mixed for the SWBLI assessed. Separation predictions are not as good as the baseline models, but the over prediction of the peak heat flux downstream of the reattachment shock that plagues many models is reduced.

The effects of RPM and recycle on separation efficiency in a clinical blood cell centrifuge.

PubMed

Drumheller, P D; Van Wie, B J; Petersen, J N; Oxford, R J; Schneider, G W

1987-11-01

A COBE blood cell centrifuge, model 2997 with a single stage channel, was modified to allow computer controlled sampling, and to allow recycle of red blood cells (RBCs) and plasma streams using bovine whole blood. The effects of recycle of the packed RBC and plasma product streams, and of the centrifuge RPM on platelet and white blood cell (WBC) separation efficiencies were quantified using a central composite factorial experimental design. These data were then fit using second order models. Both the model for the WBC separation efficiency and the model for the platelet separation efficiency predict that RPM has the greatest effect on separation efficiency and that RBC and plasma recycle have detrimental effects at moderate to low RPM, but have negligible impact on separation efficiency at high RPM.

Investigation of the free flow electrophoretic process. Volume 2: Technical analysis

NASA Technical Reports Server (NTRS)

Weiss, R. A.; Lanham, J. W.; Richman, D. W.; Walker, C. D.

1979-01-01

The effect of gravity on the free flow electrophoretic process was investigated. The demonstrated effects were then compared with predictions made by mathematical models. Results show that the carrier buffer flow was affected by gravity induced thermal convection and that the movement of the separating particle streams was affected by gravity induced buoyant forces. It was determined that if gravity induced buoyant forces were included in the mathematical models, then effective predictions of electrophoresis chamber separation performance were possible. The results of tests performed using various methods of electrophoresis using supportive media show that the mobility and the ability to separate were essentially independent of concentration, providing promise of being able to perform electrophoresis with higher inlet concentrations in space.

A comparison with theory of peak to peak sound level for a model helicopter rotor generating blade slap at low tip speeds

NASA Technical Reports Server (NTRS)

Fontana, R. R.; Hubbard, J. E., Jr.

1983-01-01

Mini-tuft and smoke flow visualization techniques have been developed for the investigation of model helicopter rotor blade vortex interaction noise at low tip speeds. These techniques allow the parameters required for calculation of the blade vortex interaction noise using the Widnall/Wolf model to be determined. The measured acoustics are compared with the predicted acoustics for each test condition. Under the conditions tested it is determined that the dominating acoustic pulse results from the interaction of the blade with a vortex 1-1/4 revolutions old at an interaction angle of less than 8 deg. The Widnall/Wolf model predicts the peak sound pressure level within 3 dB for blade vortex separation distances greater than 1 semichord, but it generally over predicts the peak S.P.L. by over 10 dB for blade vortex separation distances of less than 1/4 semichord.

A computationally efficient modelling of laminar separation bubbles

NASA Technical Reports Server (NTRS)

Maughmer, Mark D.

1988-01-01

The goal of this research is to accurately predict the characteristics of the laminar separation bubble and its effects on airfoil performance. To this end, a model of the bubble is under development and will be incorporated in the analysis section of the Eppler and Somers program. As a first step in this direction, an existing bubble model was inserted into the program. It was decided to address the problem of the short bubble before attempting the prediction of the long bubble. In the second place, an integral boundary-layer method is believed more desirable than a finite difference approach. While these two methods achieve similar prediction accuracy, finite-difference methods tend to involve significantly longer computer run times than the integral methods. Finally, as the boundary-layer analysis in the Eppler and Somers program employs the momentum and kinetic energy integral equations, a short-bubble model compatible with these equations is most preferable.

A Family of Well-Clear Boundary Models for the Integration of UAS in the NAS

NASA Technical Reports Server (NTRS)

Munoz, Cesar A.; Narkawicz, Anthony; Chamberlain, James; Consiglio, Maria; Upchurch, Jason

2014-01-01

The FAA-sponsored Sense and Avoid Workshop for Unmanned Aircraft Systems (UAS) defines the concept of sense and avoid for remote pilots as "the capability of a UAS to remain well clear from and avoid collisions with other airborne traffic." Hence, a rigorous definition of well clear is fundamental to any separation assurance concept for the integration of UAS into civil airspace. This paper presents a family of well-clear boundary models based on the TCAS II Resolution Advisory logic. For these models, algorithms that predict well-clear violations along aircraft current trajectories are provided. These algorithms are analogous to conflict detection algorithms but instead of predicting loss of separation, they predict whether well-clear violations will occur during a given lookahead time interval. Analytical techniques are used to study the properties and relationships satisfied by the models.

Prediction of space shuttle fluctuating pressure environments, including rocket plume effects

NASA Technical Reports Server (NTRS)

Plotkin, K. J.; Robertson, J. E.

1973-01-01

Preliminary estimates of space shuttle fluctuating pressure environments have been made based on prediction techniques developed by Wyle Laboratories. Particular emphasis has been given to the transonic speed regime during launch of a parallel-burn space shuttle configuration. A baseline configuration consisting of a lightweight orbiter and monolithic SRB, together with a typical flight trajectory, have been used as models for the predictions. Critical fluctuating pressure environments are predicted at transonic Mach numbers. Comparisons between predicted environments and wind tunnel test results, in general, showed good agreement. Predicted one-third octave band spectra for the above environments were generally one of three types: (1) attached turbulent boundary layer spectra (typically high frequencies); (2) homogeneous separated flow and shock-free interference flow spectra (typically intermediate frequencies); and (3) shock-oscillation and shock-induced interference flow spectra (typically low frequencies). Predictions of plume induced separated flow environments were made. Only the SRB plumes are important, with fluctuating levels comparable to compression-corner induced separated flow shock oscillation.

Sequence-Specific Model for Peptide Retention Time Prediction in Strong Cation Exchange Chromatography.

PubMed

Gussakovsky, Daniel; Neustaeter, Haley; Spicer, Victor; Krokhin, Oleg V

2017-11-07

The development of a peptide retention prediction model for strong cation exchange (SCX) separation on a Polysulfoethyl A column is reported. Off-line 2D LC-MS/MS analysis (SCX-RPLC) of S. cerevisiae whole cell lysate was used to generate a retention dataset of ∼30 000 peptides, sufficient for identifying the major sequence-specific features of peptide retention mechanisms in SCX. In contrast to RPLC/hydrophilic interaction liquid chromatography (HILIC) separation modes, where retention is driven by hydrophobic/hydrophilic contributions of all individual residues, SCX interactions depend mainly on peptide charge (number of basic residues at acidic pH) and size. An additive model (incorporating the contributions of all 20 residues into the peptide retention) combined with a peptide length correction produces a 0.976 R 2 value prediction accuracy, significantly higher than the additive models for either HILIC or RPLC. Position-dependent effects on peptide retention for different residues were driven by the spatial orientation of tryptic peptides upon interaction with the negatively charged surface functional groups. The positively charged N-termini serve as a primary point of interaction. For example, basic residues (Arg, His, Lys) increase peptide retention when located closer to the N-terminus. We also found that hydrophobic interactions, which could lead to a mixed-mode separation mechanism, are largely suppressed at 20-30% of acetonitrile in the eluent. The accuracy of the final Sequence-Specific Retention Calculator (SSRCalc) SCX model (∼0.99 R 2 value) exceeds all previously reported predictors for peptide LC separations. This also provides a solid platform for method development in 2D LC-MS protocols in proteomics and peptide retention prediction filtering of false positive identifications.

Experimental and Model Studies on Continuous Separation of 2-Phenylpropionic Acid Enantiomers by Enantioselective Liquid-Liquid Extraction in Centrifugal Contactor Separators.

PubMed

Feng, Xiaofeng; Tang, Kewen; Zhang, Pangliang; Yin, Shuangfeng

2016-03-01

Multistage enantioselective liquid-liquid extraction (ELLE) of 2-phenylpropionic acid (2-PPA) enantiomers using hydroxypropyl-β-cyclodextrin (HP-β-CD) as extractant was studied experimentally in a counter-current cascade of centrifugal contactor separators (CCSs). Performance of the process was evaluated by purity (enantiomeric excess, ee) and yield (Y). A multistage equilibrium model was established on the basis of single-stage model for chiral extraction of 2-PPA enantiomers and the law of mass conservation. A series of experiments on the extract phase/washing phase ratio (W/O ratio), extractant concentration, the pH value of aqueous phase, and the number of stages was conducted to verify the multistage equilibrium model. It was found that model predictions were in good agreement with the experimental results. The model was applied to predict and optimize the symmetrical separation of 2-PPA enantiomers. The optimal conditions for symmetric separation involves a W/O ratio of 0.6, pH of 2.5, and HP-β-CD concentration of 0.1 mol L(-1) at a temperature of 278 K, where eeeq (equal enantiomeric excess) can reach up to 37% and Yeq (equal yield) to 69%. By simulation and optimization, the minimum number of stages was evaluated at 98 and 106 for eeeq > 95% and eeeq > 97%. © 2016 Wiley Periodicals, Inc.

The effects of streamline curvature and swirl on turbulent flows in curved ducts

NASA Technical Reports Server (NTRS)

Cheng, Chih-Hsiung; Farokhi, Saeed

1990-01-01

A technique for improving the numerical predictions of turbulent flows with the effect of streamline curvature is developed. Separated flows, the flow in a curved duct, and swirling flows are examples of flow fields where streamline curvature plays a dominant role. A comprehensive literature review on the effect of streamline curvature was conducted. New algebraic formulations for the eddy viscosity incorporating the kappa-epsilon turbulence model are proposed to account for various effects of streamline curvature. The loci of flow reversal of the separated flows over various backward-facing steps are employed to test the capability of the proposed turbulence model in capturing the effect of local curvature. The inclusion of the effect of longitudinal curvature in the proposed turbulence model is validated by predicting the distributions of the static pressure coefficients in an S-bend duct and in 180 degree turn-around ducts. The proposed turbulence model embedded with transverse curvature modification is substantiated by predicting the decay of the axial velocities in the confined swirling flows. The numerical predictions of different curvature effects by the proposed turbulence models are also reported.

Modeling phase separation in mixtures of intrinsically-disordered proteins

NASA Astrophysics Data System (ADS)

Gu, Chad; Zilman, Anton

Phase separation in a pure or mixed solution of intrinsically-disordered proteins (IDPs) and its role in various biological processes has generated interest from the theoretical biophysics community. Phase separation of IDPs has been implicated in the formation of membrane-less organelles such as nucleoli, as well as in a mechanism of selectivity in transport through the nuclear pore complex. Based on a lattice model of polymers, we study the phase diagram of IDPs in a mixture and describe the selective exclusion of soluble proteins from the dense-phase IDP aggregates. The model captures the essential behaviour of phase separation by a minimal set of coarse-grained parameters, corresponding to the average monomer-monomer and monomer-protein attraction strength, as well as the protein-to-monomer size ratio. Contrary to the intuition that strong monomer-monomer interaction increases exclusion of soluble proteins from the dense IDP aggregates, our model predicts that the concentration of soluble proteins in the aggregate phase as a function of monomer-monomer attraction is non-monotonic. We corroborate the predictions of the lattice model using Langevin dynamics simulations of grafted polymers in planar and cylindrical geometries, mimicking various in-vivo and in-vitro conditions.

Making Long-Term Separations Easier for Children and Families

ERIC Educational Resources Information Center

Kim, Amy M.; Yeary, Julia

2008-01-01

The authors explore the importance of early attachments; the effects of separation on infants, toddlers, and 3-year-olds; and ways teachers can support children and families during separations. They discuss the predictable stages of the Emotional Cycle of Deployment, a model used with military families, and strategies teachers can use to help…

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2016-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused 1 by model inputs from uncertainty due to model structural error. We extend this method with a large-sample approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

PubMed Central

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2018-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a “large-sample” approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances. PMID:29697706

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

PubMed

Nearing, Grey S; Mocko, David M; Peters-Lidard, Christa D; Kumar, Sujay V; Xia, Youlong

2016-03-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a "large-sample" approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Model identification using stochastic differential equation grey-box models in diabetes.

PubMed

Duun-Henriksen, Anne Katrine; Schmidt, Signe; Røge, Rikke Meldgaard; Møller, Jonas Bech; Nørgaard, Kirsten; Jørgensen, John Bagterp; Madsen, Henrik

2013-03-01

The acceptance of virtual preclinical testing of control algorithms is growing and thus also the need for robust and reliable models. Models based on ordinary differential equations (ODEs) can rarely be validated with standard statistical tools. Stochastic differential equations (SDEs) offer the possibility of building models that can be validated statistically and that are capable of predicting not only a realistic trajectory, but also the uncertainty of the prediction. In an SDE, the prediction error is split into two noise terms. This separation ensures that the errors are uncorrelated and provides the possibility to pinpoint model deficiencies. An identifiable model of the glucoregulatory system in a type 1 diabetes mellitus (T1DM) patient is used as the basis for development of a stochastic-differential-equation-based grey-box model (SDE-GB). The parameters are estimated on clinical data from four T1DM patients. The optimal SDE-GB is determined from likelihood-ratio tests. Finally, parameter tracking is used to track the variation in the "time to peak of meal response" parameter. We found that the transformation of the ODE model into an SDE-GB resulted in a significant improvement in the prediction and uncorrelated errors. Tracking of the "peak time of meal absorption" parameter showed that the absorption rate varied according to meal type. This study shows the potential of using SDE-GBs in diabetes modeling. Improved model predictions were obtained due to the separation of the prediction error. SDE-GBs offer a solid framework for using statistical tools for model validation and model development. © 2013 Diabetes Technology Society.

CFL3D, FUN3d, and NSU3D Contributions to the Fifth Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Laflin, Kelly R.; Chaffin, Mark S.; Powell, Nicholas; Levy, David W.

2013-01-01

Results presented at the Fifth Drag Prediction Workshop using CFL3D, FUN3D, and NSU3D are described. These are calculations on the workshop provided grids and drag adapted grids. The NSU3D results have been updated to reflect an improvement to skin friction calculation on skewed grids. FUN3D results generated after the workshop are included for custom participant generated grids and a grid from a previous workshop. Uniform grid refinement at the design condition shows a tight grouping in calculated drag, where the variation in the pressure component of drag is larger than the skin friction component. At this design condition, A fine-grid drag value was predicted with a smaller drag adjoint adapted grid via tetrahedral adaption to a metric and mixed-element subdivision. The buffet study produced larger variation than the design case, which is attributed to large differences in the predicted side-of-body separation extent. Various modeling and discretization approaches had a strong impact on predicted side-of-body separation. This large wing root separation bubble was not observed in wind tunnel tests indicating that more work is necessary in modeling wing root juncture flows to predict experiments.

Experimental designs for modeling retention patterns and separation efficiency in analysis of fatty acid methyl esters by gas chromatography-mass spectrometry.

PubMed

Skartland, Liv Kjersti; Mjøs, Svein A; Grung, Bjørn

2011-09-23

The retention behavior of components analyzed by chromatography varies with instrumental settings. Being able to predict how changes in these settings alter the elution pattern is useful, both with regards to component identification, as well as with regards to optimization of the chromatographic system. In this work, it is shown how experimental designs can be used for this purpose. Different experimental designs for response surface modeling of the separation of fatty acid methyl esters (FAME) as function of chromatographic conditions in GC have been evaluated. Full factorial, central composite, Doehlert and Box-Behnken designs were applied. A mixture of 38 FAMEs was separated on a polar cyanopropyl substituted polysilphenylene-siloxane phase capillary column. The temperature gradient, the start temperature of the gradient, and the carrier gas velocity were varied in the experiments. The modeled responses, as functions of chromatographic conditions, were retention time, retention indices, peak widths, separation efficiency and resolution between selected peak pairs. The designs that allowed inclusion of quadratic terms among the predictors performed significantly better than factorial design. Box-Behnken design provided the best results for prediction of retention, but the differences between the central composite, Doehlert and Box-Behnken designs were small. Retention indices could be modeled with much better accuracy than retention times. However, because the errors of predicted tR of closely eluting peaks were highly correlated, models of resolution (Rs) that were based on retention time had errors in the same range as corresponding models based on ECL. Copyright © 2011 Elsevier B.V. All rights reserved.

Analysis of transitional separation bubbles on infinite swept wings

NASA Technical Reports Server (NTRS)

Davis, R. L.; Carter, J. E.

1986-01-01

A previously developed two-dimensional local inviscid-viscous interaction technique for the analysis of airfoil transitional separation bubbles, ALESEP (Airfoil Leading Edge Separation), has been extended for the calculation of transitional separation bubbles over infinite swept wings. As part of this effort, Roberts' empirical correlation, which is interpreted as a separated flow empirical extension of Mack's stability theory for attached flows, has been incorporated into the ALESEP procedure for the prediction of the transition location within the separation bubble. In addition, the viscous procedure used in the ALESEP techniques has been modified to allow for wall suction. A series of two-dimensional calculations is presented as a verification of the prediction capability of the interaction techniques with the Roberts' transition model. Numerical tests have shown that this two-dimensional natural transition correlation may also be applied to transitional separation bubbles over infinite swept wings. Results of the interaction procedure are compared with Horton's detailed experimental data for separated flow over a swept plate which demonstrates the accuracy of the present technique. Wall suction has been applied to a similar interaction calculation to demonstrate its effect on the separation bubble. The principal conclusion of this paper is that the prediction of transitional separation bubbles over two-dimensional or infinite swept geometries is now possible using the present interacting boundary layer approach.

A New Approach to Predict the Fish Fillet Shelf-Life in Presence of Natural Preservative Agents.

PubMed

Giuffrida, Alessandro; Giarratana, Filippo; Valenti, Davide; Muscolino, Daniele; Parisi, Roberta; Parco, Alessio; Marotta, Stefania; Ziino, Graziella; Panebianco, Antonio

2017-04-13

Three data sets concerning the behaviour of spoilage flora of fillets treated with natural preservative substances (NPS) were used to construct a new kind of mathematical predictive model. This model, unlike other ones, allows expressing the antibacterial effect of the NPS separately from the prediction of the growth rate. This approach, based on the introduction of a parameter into the predictive primary model, produced a good fitting of observed data and allowed characterising quantitatively the increase of shelf-life of fillets.

Predicting streamflow regime metrics for ungauged streamsin Colorado, Washington, and Oregon

NASA Astrophysics Data System (ADS)

Sanborn, Stephen C.; Bledsoe, Brian P.

2006-06-01

Streamflow prediction in ungauged basins provides essential information for water resources planning and management and ecohydrological studies yet remains a fundamental challenge to the hydrological sciences. A methodology is presented for stratifying streamflow regimes of gauged locations, classifying the regimes of ungauged streams, and developing models for predicting a suite of ecologically pertinent streamflow metrics for these streams. Eighty-four streamflow metrics characterizing various flow regime attributes were computed along with physical and climatic drainage basin characteristics for 150 streams with little or no streamflow modification in Colorado, Washington, and Oregon. The diverse hydroclimatology of the study area necessitates flow regime stratification and geographically independent clusters were identified and used to develop separate predictive models for each flow regime type. Multiple regression models for flow magnitude, timing, and rate of change metrics were quite accurate with many adjusted R2 values exceeding 0.80, while models describing streamflow variability did not perform as well. Separate stratification schemes for high, low, and average flows did not considerably improve models for metrics describing those particular aspects of the regime over a scheme based on the entire flow regime. Models for streams identified as 'snowmelt' type were improved if sites in Colorado and the Pacific Northwest were separated to better stratify the processes driving streamflow in these regions thus revealing limitations of geographically independent streamflow clusters. This study demonstrates that a broad suite of ecologically relevant streamflow characteristics can be accurately modeled across large heterogeneous regions using this framework. Applications of the resulting models include stratifying biomonitoring sites and quantifying linkages between specific aspects of flow regimes and aquatic community structure. In particular, the results bode well for modeling ecological processes related to high-flow magnitude, timing, and rate of change such as the recruitment of fish and riparian vegetation across large regions.

Separability of drag and thrust in undulatory animals and machines

PubMed Central

Bale, Rahul; Shirgaonkar, Anup A.; Neveln, Izaak D.; Bhalla, Amneet Pal Singh; MacIver, Malcolm A.; Patankar, Neelesh A.

2014-01-01

For nearly a century, researchers have tried to understand the swimming of aquatic animals in terms of a balance between the forward thrust from swimming movements and drag on the body. Prior approaches have failed to provide a separation of these two forces for undulatory swimmers such as lamprey and eels, where most parts of the body are simultaneously generating drag and thrust. We nonetheless show that this separation is possible, and delineate its fundamental basis in undulatory swimmers. Our approach unifies a vast diversity of undulatory aquatic animals (anguilliform, sub-carangiform, gymnotiform, bal-istiform, rajiform) and provides design principles for highly agile bioinspired underwater vehicles. This approach has practical utility within biology as well as engineering. It is a predictive tool for use in understanding the role of the mechanics of movement in the evolutionary emergence of morphological features relating to locomotion. For example, we demonstrate that the drag-thrust separation framework helps to predict the observed height of the ribbon fin of electric knifefish, a diverse group of neotropical fish which are an important model system in sensory neurobiology. We also show how drag-thrust separation leads to models that can predict the swimming velocity of an organism or a robotic vehicle. PMID:25491270

A study of the second and third order closure models of turbulence for prediction of separated shear flows

NASA Technical Reports Server (NTRS)

Amano, R. S.

1985-01-01

The hybrid model of the Reynolds-stress turbulence closure is tested for the computation of the flows over a step and disk. Here it is attempted to improve the redistributive action of the turbulence energy among the Reynolds stresses. By evaluating the existing models for the pressure-strain correlation, better coefficients are obtained for the prediction of separating shear flows. Furthermore, the diffusion rate of the Reynolds stresses is reevaluated adopting several algebraic correlations for the triple-velocity products. The models of Cormack et al., Daly-Harlow, Hanjalic-Launder, and Shir were tested for the reattaching shear flows. It was generally observed that all these algebraic models give considerably low values of the triple-velocity products. This is attributed to the fact that none of the algebraic models can take the convective effect of the triple-velocity products into account in the separating shear flows, thus resulting in much lower diffusion rate than Reynolds stresses. In order to improve the evaluation of these quantities correction factors are introduced based on the comparison with some experimental data.

Action Unit Models of Facial Expression of Emotion in the Presence of Speech

PubMed Central

Shah, Miraj; Cooper, David G.; Cao, Houwei; Gur, Ruben C.; Nenkova, Ani; Verma, Ragini

2014-01-01

Automatic recognition of emotion using facial expressions in the presence of speech poses a unique challenge because talking reveals clues for the affective state of the speaker but distorts the canonical expression of emotion on the face. We introduce a corpus of acted emotion expression where speech is either present (talking) or absent (silent). The corpus is uniquely suited for analysis of the interplay between the two conditions. We use a multimodal decision level fusion classifier to combine models of emotion from talking and silent faces as well as from audio to recognize five basic emotions: anger, disgust, fear, happy and sad. Our results strongly indicate that emotion prediction in the presence of speech from action unit facial features is less accurate when the person is talking. Modeling talking and silent expressions separately and fusing the two models greatly improves accuracy of prediction in the talking setting. The advantages are most pronounced when silent and talking face models are fused with predictions from audio features. In this multi-modal prediction both the combination of modalities and the separate models of talking and silent facial expression of emotion contribute to the improvement. PMID:25525561

Investigation of Periodic Pitching through the Static Stall Angle of Attack.

DTIC Science & Technology

1987-03-01

been completed to characterize and predict the dynamic stall process. In 1968 Ham (Ref 11) completed a study to explain the torsional oscillation of...peak values of l.:t and moment could be predicted accurately, but the model did not predict when the peaks would occur. Another problem with the...model was that it required input from experimental results to tell when leading edge vortex separation occurred. The prediction of when vortex shedding

Discovery of optimal zeolites for challenging separations and chemical transformations using predictive materials modeling

NASA Astrophysics Data System (ADS)

Bai, Peng; Jeon, Mi Young; Ren, Limin; Knight, Chris; Deem, Michael W.; Tsapatsis, Michael; Siepmann, J. Ilja

2015-01-01

Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure. To date, 213 framework types have been synthesized and >330,000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modelling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds.

Coupled thermal-fluid-mechanics analysis of twin roll casting of A7075 aluminum alloy

NASA Astrophysics Data System (ADS)

Lee, Yun-Soo; Kim, Hyoung-Wook; Cho, Jae-Hyung; Chun, Se-Hwan

2017-09-01

Better understanding of temperature distribution and roll separation force during twin roll casting of aluminum alloys is critical to successfully fabricate good quality of aluminum strips. Therefore, the simulation techniques are widely applied to understand the twin roll casting process in a comprehensive way and to reduce the experimental time and cost of trial and error. However, most of the conventional approaches are considered thermally coupled flow, or thermally coupled mechanical behaviors. In this study, a fully coupled thermal-fluid-mechanical analysis of twin roll casting of A7075 aluminum strips was carried out using the finite element method. Temperature profile, liquid fraction and metal flow of aluminum strips with different thickness were predicted. Roll separation force and roll temperatures were experimentally obtained from a pilot-scale twin roll caster, and those results were compared with model predictions. Coupling the fluid of the liquid melt to the thermal and mechanical modeling reasonably predicted roll temperature distribution and roll separation force during twin roll casting.

Predicting University Performance in Psychology: The Role of Previous Performance and Discipline-Specific Knowledge

ERIC Educational Resources Information Center

Betts, Lucy R.; Elder, Tracey J.; Hartley, James; Blurton, Anthony

2008-01-01

Recent initiatives to enhance retention and widen participation ensure it is crucial to understand the factors that predict students' performance during their undergraduate degree. The present research used Structural Equation Modeling (SEM) to test three separate models that examined the extent to which British Psychology students' A-level entry…

Are Binary Separations related to their System Mass?

NASA Astrophysics Data System (ADS)

Sterzik, M. F.; Durisen, R. H.

2004-08-01

We compile most recent multiplicity fractions and binary separation distributions for different primary masses, including very low-mass and brown dwarf primaries, and compare them with dynamical decay models of small-N clusters. The model predictions are based on detailed numerical calculations of the internal cluster dynamics, as well as on Monte-Carlo methods. Both observations and models reflect the same trends: (1) The multiplicity fraction is an increasing function of the primary mass. (2) The mean binary separations are increasing with the system mass in the sense that very low-mass binaries have average separations around ≈ 4AU, while the binary separation distribution for solar-type primaries peaks at ≈ 40AU. M-type binary systems apparently preferentially populate intermediate separations. Similar specific energy at the time of cluster formation for all cluster masses can possibly explain this trend.

Use of DES in mildly separated internal flow: dimples in a turbulent channel

NASA Astrophysics Data System (ADS)

Tay, Chien Ming Jonathan; Khoo, Boo Cheong; Chew, Yong Tian

2017-12-01

Detached eddy simulation (DES) is investigated as a means to study an array of shallow dimples with depth to diameter ratios of 1.5% and 5% in a turbulent channel. The DES captures large-scale flow features relatively well, but is unable to predict skin friction accurately due to flow modelling near the wall. The current work instead relies on the accuracy of DES to predict large-scale flow features, as well as its well-documented reliability in predicting flow separation regions to support the proposed mechanism that dimples reduce drag by introducing spanwise flow components near the wall through the addition of streamwise vorticity. Profiles of the turbulent energy budget show the stabilising effect of the dimples on the flow. The presence of flow separation however modulates the net drag reduction. Increasing the Reynolds number can reduce the size of the separated region and experiments show that this increases the overall drag reduction.

Phase separation of self-propelled ballistic particles

NASA Astrophysics Data System (ADS)

Bruss, Isaac R.; Glotzer, Sharon C.

2018-04-01

Self-propelled particles phase-separate into coexisting dense and dilute regions above a critical density. The statistical nature of their stochastic motion lends itself to various theories that predict the onset of phase separation. However, these theories are ill-equipped to describe such behavior when noise becomes negligible. To overcome this limitation, we present a predictive model that relies on two density-dependent timescales: τF, the mean time particles spend between collisions; and τC, the mean lifetime of a collision. We show that only when τF<τC do collisions last long enough to develop a growing cluster and initiate phase separation. Using both analytical calculations and active particle simulations, we measure these timescales and determine the critical density for phase separation in both two and three dimensions.

A new model integrating short- and long-term aging of copper added to soils

PubMed Central

Zeng, Saiqi; Li, Jumei; Wei, Dongpu

2017-01-01

Aging refers to the processes by which the bioavailability/toxicity, isotopic exchangeability, and extractability of metals added to soils decline overtime. We studied the characteristics of the aging process in copper (Cu) added to soils and the factors that affect this process. Then we developed a semi-mechanistic model to predict the lability of Cu during the aging process with descriptions of the diffusion process using complementary error function. In the previous studies, two semi-mechanistic models to separately predict short-term and long-term aging of Cu added to soils were developed with individual descriptions of the diffusion process. In the short-term model, the diffusion process was linearly related to the square root of incubation time (t1/2), and in the long-term model, the diffusion process was linearly related to the natural logarithm of incubation time (lnt). Both models could predict short-term or long-term aging processes separately, but could not predict the short- and long-term aging processes by one model. By analyzing and combining the two models, we found that the short- and long-term behaviors of the diffusion process could be described adequately using the complementary error function. The effect of temperature on the diffusion process was obtained in this model as well. The model can predict the aging process continuously based on four factors—soil pH, incubation time, soil organic matter content and temperature. PMID:28820888

The Separate Spheres Model of Gendered Inequality.

PubMed

Miller, Andrea L; Borgida, Eugene

2016-01-01

Research on role congruity theory and descriptive and prescriptive stereotypes has established that when men and women violate gender stereotypes by crossing spheres, with women pursuing career success and men contributing to domestic labor, they face backlash and economic penalties. Less is known, however, about the types of individuals who are most likely to engage in these forms of discrimination and the types of situations in which this is most likely to occur. We propose that psychological research will benefit from supplementing existing research approaches with an individual differences model of support for separate spheres for men and women. This model allows psychologists to examine individual differences in support for separate spheres as they interact with situational and contextual forces. The separate spheres ideology (SSI) has existed as a cultural idea for many years but has not been operationalized or modeled in social psychology. The Separate Spheres Model presents the SSI as a new psychological construct characterized by individual differences and a motivated system-justifying function, operationalizes the ideology with a new scale measure, and models the ideology as a predictor of some important gendered outcomes in society. As a first step toward developing the Separate Spheres Model, we develop a new measure of individuals' endorsement of the SSI and demonstrate its reliability, convergent validity, and incremental predictive validity. We provide support for the novel hypotheses that the SSI predicts attitudes regarding workplace flexibility accommodations, income distribution within families between male and female partners, distribution of labor between work and family spheres, and discriminatory workplace behaviors. Finally, we provide experimental support for the hypothesis that the SSI is a motivated, system-justifying ideology.

The Separate Spheres Model of Gendered Inequality

PubMed Central

Miller, Andrea L.; Borgida, Eugene

2016-01-01

Research on role congruity theory and descriptive and prescriptive stereotypes has established that when men and women violate gender stereotypes by crossing spheres, with women pursuing career success and men contributing to domestic labor, they face backlash and economic penalties. Less is known, however, about the types of individuals who are most likely to engage in these forms of discrimination and the types of situations in which this is most likely to occur. We propose that psychological research will benefit from supplementing existing research approaches with an individual differences model of support for separate spheres for men and women. This model allows psychologists to examine individual differences in support for separate spheres as they interact with situational and contextual forces. The separate spheres ideology (SSI) has existed as a cultural idea for many years but has not been operationalized or modeled in social psychology. The Separate Spheres Model presents the SSI as a new psychological construct characterized by individual differences and a motivated system-justifying function, operationalizes the ideology with a new scale measure, and models the ideology as a predictor of some important gendered outcomes in society. As a first step toward developing the Separate Spheres Model, we develop a new measure of individuals’ endorsement of the SSI and demonstrate its reliability, convergent validity, and incremental predictive validity. We provide support for the novel hypotheses that the SSI predicts attitudes regarding workplace flexibility accommodations, income distribution within families between male and female partners, distribution of labor between work and family spheres, and discriminatory workplace behaviors. Finally, we provide experimental support for the hypothesis that the SSI is a motivated, system-justifying ideology. PMID:26800454

Application of linear regression analysis in accuracy assessment of rolling force calculations

NASA Astrophysics Data System (ADS)

Poliak, E. I.; Shim, M. K.; Kim, G. S.; Choo, W. Y.

1998-10-01

Efficient operation of the computational models employed in process control systems require periodical assessment of the accuracy of their predictions. Linear regression is proposed as a tool which allows separate systematic and random prediction errors from those related to measurements. A quantitative characteristic of the model predictive ability is introduced in addition to standard statistical tests for model adequacy. Rolling force calculations are considered as an example for the application. However, the outlined approach can be used to assess the performance of any computational model.

Rapid Method Development in Hydrophilic Interaction Liquid Chromatography for Pharmaceutical Analysis Using a Combination of Quantitative Structure-Retention Relationships and Design of Experiments.

PubMed

Taraji, Maryam; Haddad, Paul R; Amos, Ruth I J; Talebi, Mohammad; Szucs, Roman; Dolan, John W; Pohl, Chris A

2017-02-07

A design-of-experiment (DoE) model was developed, able to describe the retention times of a mixture of pharmaceutical compounds in hydrophilic interaction liquid chromatography (HILIC) under all possible combinations of acetonitrile content, salt concentration, and mobile-phase pH with R 2 > 0.95. Further, a quantitative structure-retention relationship (QSRR) model was developed to predict retention times for new analytes, based only on their chemical structures, with a root-mean-square error of prediction (RMSEP) as low as 0.81%. A compound classification based on the concept of similarity was applied prior to QSRR modeling. Finally, we utilized a combined QSRR-DoE approach to propose an optimal design space in a quality-by-design (QbD) workflow to facilitate the HILIC method development. The mathematical QSRR-DoE model was shown to be highly predictive when applied to an independent test set of unseen compounds in unseen conditions with a RMSEP value of 5.83%. The QSRR-DoE computed retention time of pharmaceutical test analytes and subsequently calculated separation selectivity was used to optimize the chromatographic conditions for efficient separation of targets. A Monte Carlo simulation was performed to evaluate the risk of uncertainty in the model's prediction, and to define the design space where the desired quality criterion was met. Experimental realization of peak selectivity between targets under the selected optimal working conditions confirmed the theoretical predictions. These results demonstrate how discovery of optimal conditions for the separation of new analytes can be accelerated by the use of appropriate theoretical tools.

Modeling of membrane processes for air revitalization and water recovery

NASA Technical Reports Server (NTRS)

Lange, Kevin E.; Foerg, Sandra L.; Dall-Bauman, Liese A.

1992-01-01

Gas-separation and reverse-osmosis membrane models are being developed in conjunction with membrane testing at NASA JSC. The completed gas-separation membrane model extracts effective component permeabilities from multicomponent test data, and predicts the effects of flow configuration, operating conditions, and membrane dimensions on module performance. Variable feed- and permeate-side pressures are considered. The model has been applied to test data for hollow-fiber membrane modules with simulated cabin-air feeds. Results are presented for a membrane designed for air drying applications. Extracted permeabilities are used to predict the effect of operating conditions on water enrichment in the permeate. A first-order reverse-osmosis model has been applied to test data for spiral wound membrane modules with a simulated hygiene water feed. The model estimates an effective local component rejection coefficient under pseudosteady-state conditions. Results are used to define requirements for a detailed reverse-osmosis model.

[Application of Kohonen Self-Organizing Feature Maps in QSAR of human ADMET and kinase data sets].

PubMed

Hegymegi-Barakonyi, Bálint; Orfi, László; Kéri, György; Kövesdi, István

2013-01-01

QSAR predictions have been proven very useful in a large number of studies for drug design, such as kinase inhibitor design as targets for cancer therapy, however the overall predictability often remains unsatisfactory. To improve predictability of ADMET features and kinase inhibitory data, we present a new method using Kohonen's Self-Organizing Feature Map (SOFM) to cluster molecules based on explanatory variables (X) and separate dissimilar ones. We calculated SOFM clusters for a large number of molecules with human ADMET and kinase inhibitory data, and we showed that chemically similar molecules were in the same SOFM cluster, and within such clusters the QSAR models had significantly better predictability. We used also target variables (Y, e.g. ADMET) jointly with X variables to create a novel type of clustering. With our method, cells of loosely coupled XY data could be identified and separated into different model building sets.

A general strategy for performing temperature-programming in high performance liquid chromatography--prediction of segmented temperature gradients.

PubMed

Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C

2011-09-28

In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed to predict retention times for segmented-temperature gradients based on temperature-gradient input data in liquid chromatography (LC) with high accuracy. The LES model assumes that retention times for isothermal separations can be predicted based on two temperature gradients and is employed to calculate the retention factor of an analyte when changing the start temperature of the temperature gradient. In this study it was investigated whether this approach can also be employed in LC. It was shown that this approximation cannot be transferred to temperature-programmed LC where a temperature range from 60°C up to 180°C is investigated. Major relative errors up to 169.6% were observed for isothermal retention factor predictions. In order to predict retention times for temperature gradients with different start temperatures in LC, another relationship is required to describe the influence of temperature on retention. Therefore, retention times for isothermal separations based on isothermal input runs were predicted using a plot of the natural logarithm of the retention factor vs. the inverse temperature and a plot of the natural logarithm of the retention factor vs. temperature. It could be shown that a plot of lnk vs. T yields more reliable isothermal/isocratic retention time predictions than a plot of lnk vs. 1/T which is usually employed. Hence, in order to predict retention times for temperature-gradients with different start temperatures in LC, two temperature gradient and two isothermal measurements have been employed. In this case, retention times can be predicted with a maximal relative error of 5.5% (average relative error: 2.9%). In comparison, if the start temperature of the simulated temperature gradient is equal to the start temperature of the input data, only two temperature-gradient measurements are required. Under these conditions, retention times can be predicted with a maximal relative error of 4.3% (average relative error: 2.2%). As an example, the systematic method development for an isothermal as well as a temperature gradient separation of selected sulfonamides by means of the adapted LES model is demonstrated using a pure water mobile phase. Both methods are compared and it is shown that the temperature-gradient separation provides some advantages over the isothermal separation in terms of limits of detection and analysis time. Copyright © 2011 Elsevier B.V. All rights reserved.

Neural network river forecasting through baseflow separation and binary-coded swarm optimization

NASA Astrophysics Data System (ADS)

Taormina, Riccardo; Chau, Kwok-Wing; Sivakumar, Bellie

2015-10-01

The inclusion of expert knowledge in data-driven streamflow modeling is expected to yield more accurate estimates of river quantities. Modular models (MMs) designed to work on different parts of the hydrograph are preferred ways to implement such approach. Previous studies have suggested that better predictions of total streamflow could be obtained via modular Artificial Neural Networks (ANNs) trained to perform an implicit baseflow separation. These MMs fit separately the baseflow and excess flow components as produced by a digital filter, and reconstruct the total flow by adding these two signals at the output. The optimization of the filter parameters and ANN architectures is carried out through global search techniques. Despite the favorable premises, the real effectiveness of such MMs has been tested only on a few case studies, and the quality of the baseflow separation they perform has never been thoroughly assessed. In this work, we compare the performance of MM against global models (GMs) for nine different gaging stations in the northern United States. Binary-coded swarm optimization is employed for the identification of filter parameters and model structure, while Extreme Learning Machines, instead of ANN, are used to drastically reduce the large computational times required to perform the experiments. The results show that there is no evidence that MM outperform global GM for predicting the total flow. In addition, the baseflow produced by the MM largely underestimates the actual baseflow component expected for most of the considered gages. This occurs because the values of the filter parameters maximizing overall accuracy do not reflect the geological characteristics of the river basins. The results indeed show that setting the filter parameters according to expert knowledge results in accurate baseflow separation but lower accuracy of total flow predictions, suggesting that these two objectives are intrinsically conflicting rather than compatible.

Classification Studies in an Advanced Air Classifier

NASA Astrophysics Data System (ADS)

Routray, Sunita; Bhima Rao, R.

2016-10-01

In the present paper, experiments are carried out using VSK separator which is an advanced air classifier to recover heavy minerals from beach sand. In classification experiments the cage wheel speed and the feed rate are set and the material is fed to the air cyclone and split into fine and coarse particles which are collected in separate bags. The size distribution of each fraction was measured by sieve analysis. A model is developed to predict the performance of the air classifier. The objective of the present model is to predict the grade efficiency curve for a given set of operating parameters such as cage wheel speed and feed rate. The overall experimental data with all variables studied in this investigation is fitted to several models. It is found that the present model is fitting good to the logistic model.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546

Prediction and optimization of the recovery rate in centrifugal separation of platelet-rich plasma (PRP)

NASA Astrophysics Data System (ADS)

Piao, Linfeng; Park, Hyungmin; Jo, Chris

2016-11-01

We present a theoretical model of the recovery rate of platelet and white blood cell in the process of centrifugal separation of platelet-rich plasma (PRP). For the practically used conditions in the field, the separation process is modeled as a one-dimensional particle sedimentation; a quasi-linear partial differential equation is derived based on the kinematic-wave theory. This is solved to determine the interface positions between supernatant-suspension and suspension-sediment, used to estimate the recovery rate of the plasma. While correcting the Brown's hypothesis (1989) claiming that the platelet recovery is linearly proportional to that of plasma, we propose a new correlation model for prediction of the platelet recovery, which is a function of the volume of whole blood, centrifugal acceleration and time. For a range of practical parameters, such as hematocrit, volume of whole blood and centrifugation (time and acceleration), the predicted recovery rate shows a good agreement with available clinical data. We propose that this model is further used to optimize the preparation method of PRP that satisfies the customized case. Supported by a Grant (MPSS-CG-2016-02) through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

STICK-SLIP-SEPARATION Analysis and Non-Linear Stiffness and Damping Characterization of Friction Contacts Having Variable Normal Load

NASA Astrophysics Data System (ADS)

Yang, B. D.; Chu, M. L.; Menq, C. H.

1998-03-01

Mechanical systems in which moving components are mutually constrained through contacts often lead to complex contact kinematics involving tangential and normal relative motions. A friction contact model is proposed to characterize this type of contact kinematics that imposes both friction non-linearity and intermittent separation non-linearity on the system. The stick-slip friction phenomenon is analyzed by establishing analytical criteria that predict the transition between stick, slip, and separation of the interface. The established analytical transition criteria are particularly important to the proposed friction contact model for the transition conditions of the contact kinematics are complicated by the effect of normal load variation and possible interface separation. With these transition criteria, the induced friction force on the contact plane and the variable normal load perpendicular to the contact plane, can be predicted for any given cyclic relative motions at the contact interface and hysteresis loops can be produced so as to characterize the equivalent damping and stiffness of the friction contact. These-non-linear damping and stiffness methods along with the harmonic balance method are then used to predict the resonant response of a frictionally constrained two-degree-of-freedom oscillator. The predicted results are compared with those of the time integration method and the damping effect, the resonant frequency shift, and the jump phenomenon are examined.

In situ Observations of Heliospheric Current Sheets Evolution

NASA Astrophysics Data System (ADS)

Liu, Yong; Peng, Jun; Huang, Jia; Klecker, Berndt

2017-04-01

We investigate the Heliospheric current sheet observation time difference of the spacecraft using the STEREO, ACE and WIND data. The observations are first compared to a simple theory in which the time difference is only determined by the radial and longitudinal separation between the spacecraft. The predictions fit well with the observations except for a few events. Then the time delay caused by the latitudinal separation is taken in consideration. The latitude of each spacecraft is calculated based on the PFSS model assuming that heliospheric current sheets propagate at the solar wind speed without changing their shapes from the origin to spacecraft near 1AU. However, including the latitudinal effects does not improve the prediction, possibly because that the PFSS model may not locate the current sheets accurately enough. A new latitudinal delay is predicted based on the time delay using the observations on ACE data. The new method improved the prediction on the time lag between spacecraft; however, further study is needed to predict the location of the heliospheric current sheet more accurately.

Comparison of Turbulence Models for Nozzle-Afterbody Flows with Propulsive Jets

NASA Technical Reports Server (NTRS)

Compton, William B., III

1996-01-01

A numerical investigation was conducted to assess the accuracy of two turbulence models when computing non-axisymmetric nozzle-afterbody flows with propulsive jets. Navier-Stokes solutions were obtained for a Convergent-divergent non-axisymmetric nozzle-afterbody and its associated jet exhaust plume at free-stream Mach numbers of 0.600 and 0.938 at an angle of attack of 0 deg. The Reynolds number based on model length was approximately 20 x 10(exp 6). Turbulent dissipation was modeled by the algebraic Baldwin-Lomax turbulence model with the Degani-Schiff modification and by the standard Jones-Launder kappa-epsilon turbulence model. At flow conditions without strong shocks and with little or no separation, both turbulence models predicted the pressures on the surfaces of the nozzle very well. When strong shocks and massive separation existed, both turbulence models were unable to predict the flow accurately. Mixing of the jet exhaust plume and the external flow was underpredicted. The differences in drag coefficients for the two turbulence models illustrate that substantial development is still required for computing very complex flows before nozzle performance can be predicted accurately for all external flow conditions.

Prediction and Analysis of the Nonsteady Transition and Separation Processes on an Oscillating Wind Turbine Airfoil using the \\gamma-Re_\\theta Transition Model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nandi, Taraj; Brasseur, James; Vijayakumar, Ganesh

2016-01-04

This study is aimed at gaining insight into the nonsteady transitional boundary layer dynamics of wind turbine blades and the predictive capabilities of URANS based transition and turbulence models for similar physics through the analysis of a controlled flow with similar nonsteady parameters.

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Extraction-Separation Performance and Dynamic Modeling of Orion Test Vehicles with Adams Simulation: 2nd Edition

NASA Technical Reports Server (NTRS)

Fraire, Usbaldo, Jr.; Anderson, Keith; Varela, Jose G.; Bernatovich, Michael A.

2015-01-01

NASA's Orion Capsule Parachute Assembly System (CPAS) project has advanced into the third generation of its parachute test campaign and requires technically comprehensive modeling capabilities to simulate multi-body dynamics (MBD) of test articles released from a C-17. Safely extracting a 30,000 lbm mated test article from a C-17 and performing stable mid-air separation maneuvers requires an understanding of the interaction between elements in the test configuration and how they are influenced by extraction parachute performance, aircraft dynamics, aerodynamics, separation dynamics, and kinetic energy experienced by the system. During the real-time extraction and deployment sequences, these influences can be highly unsteady and difficult to bound. An avionics logic window based on time, pitch, and pitch rate is used to account for these effects and target a favorable separation state in real time. The Adams simulation has been employed to fine-tune this window, as well as predict and reconstruct the coupled dynamics of the Parachute Test Vehicle (PTV) and Cradle Platform Separation System (CPSS) from aircraft extraction through the mid-air separation event. The test-technique for the extraction of CPAS test articles has evolved with increased complexity and requires new modeling concepts to ensure the test article is delivered to a stable test condition for the programmer phase. Prompted by unexpected dynamics and hardware malfunctions in drop tests, these modeling improvements provide a more accurate loads prediction by incorporating a spring-damper line-model derived from the material properties. The qualification phase of CPAS testing is on the horizon and modeling increasingly complex test-techniques with Adams is vital to successfully qualify the Orion parachute system for human spaceflight.

Downstream Effects on Orbiter Leeside Flow Separation for Hypersonic Flows

NASA Technical Reports Server (NTRS)

Buck, Gregory M.; Pulsonetti, Maria V.; Weilmuenster, K. James

2005-01-01

Discrepancies between experiment and computation for shuttle leeside flow separation, which came to light in the Columbia accident investigation, are resolved. Tests were run in the Langley Research Center 20-Inch Hypersonic CF4 Tunnel with a baseline orbiter model and two extended trailing edge models. The extended trailing edges altered the wing leeside separation lines, moving the lines toward the fuselage, proving that wing trailing edge modeling does affect the orbiter leeside flow. Computations were then made with a wake grid. These calculations more closely matched baseline experiments. Thus, the present findings demonstrate that it is imperative to include the wake flow domain in CFD calculations in order to accurately predict leeside flow separation for hypersonic vehicles at high angles of attack.

Multivariate Modelling of the Career Intent of Air Force Personnel.

DTIC Science & Technology

1980-09-01

index (HOPP) was used as a measure of current job satisfaction . As with the Vroom and Fishbein/Graen models, two separate validations were accom...34 Organizational Behavior and Human Performance , 23: 251-267, 1979. Lewis, Logan M. "Expectancy Theory as a Predictive Model of Career Intent, Job Satisfaction ...W. Albright. "Expectancy Theory Predictions of the Satisfaction , Effort, Performance , and Retention of Naval Aviation Officers," Organizational

An analysis method for multi-component airfoils in separated flow

NASA Technical Reports Server (NTRS)

Rao, B. M.; Duorak, F. A.; Maskew, B.

1980-01-01

The multi-component airfoil program (Langley-MCARF) for attached flow is modified to accept the free vortex sheet separation-flow model program (Analytical Methods, Inc.-CLMAX). The viscous effects are incorporated into the calculation by representing the boundary layer displacement thickness with an appropriate source distribution. The separation flow model incorporated into MCARF was applied to single component airfoils. Calculated pressure distributions for angles of attack up to the stall are in close agreement with experimental measurements. Even at higher angles of attack beyond the stall, correct trends of separation, decrease in lift coefficients, and increase in pitching moment coefficients are predicted.

Theoretical study of hull-rotor aerodynamic interference on semibuoyant vehicles

NASA Technical Reports Server (NTRS)

Spangler, S. B.; Smith, C. A.

1978-01-01

Analytical methods are developed to predict the pressure distribution and overall loads on the hulls of airships which have close coupled, relatively large and/or high disk loading propulsors for attitude control, station keeping, and partial support of total weight as well as provision of thrust in cruise. The methods comprise a surface-singularity, potential-flow model for the hull and lifting surfaces (such as tails) and a rotor model which calculates the velocity induced by the rotor and its wake at points adjacent to the wake. Use of these two models provides an inviscid pressure distribution on the hull with rotor interference. A boundary layer separation prediction method is used to locate separation on the hull, and a wake pressure is imposed on the separated region for purposes of calculating hull loads. Results of calculations are shown to illustrate various cases of rotor-hull interference and comparisons with small scale data are made to evaluate the method.

A computational efficient modelling of laminar separation bubbles

NASA Technical Reports Server (NTRS)

Dini, Paolo; Maughmer, Mark D.

1990-01-01

In predicting the aerodynamic characteristics of airfoils operating at low Reynolds numbers, it is often important to account for the effects of laminar (transitional) separation bubbles. Previous approaches to the modelling of this viscous phenomenon range from fast but sometimes unreliable empirical correlations for the length of the bubble and the associated increase in momentum thickness, to more accurate but significantly slower displacement-thickness iteration methods employing inverse boundary-layer formulations in the separated regions. Since the penalty in computational time associated with the more general methods is unacceptable for airfoil design applications, use of an accurate yet computationally efficient model is highly desirable. To this end, a semi-empirical bubble model was developed and incorporated into the Eppler and Somers airfoil design and analysis program. The generality and the efficiency was achieved by successfully approximating the local viscous/inviscid interaction, the transition location, and the turbulent reattachment process within the framework of an integral boundary-layer method. Comparisons of the predicted aerodynamic characteristics with experimental measurements for several airfoils show excellent and consistent agreement for Reynolds numbers from 2,000,000 down to 100,000.

Eigenspace perturbations for uncertainty estimation of single-point turbulence closures

NASA Astrophysics Data System (ADS)

Iaccarino, Gianluca; Mishra, Aashwin Ananda; Ghili, Saman

2017-02-01

Reynolds-averaged Navier-Stokes (RANS) models represent the workhorse for predicting turbulent flows in complex industrial applications. However, RANS closures introduce a significant degree of epistemic uncertainty in predictions due to the potential lack of validity of the assumptions utilized in model formulation. Estimating this uncertainty is a fundamental requirement for building confidence in such predictions. We outline a methodology to estimate this structural uncertainty, incorporating perturbations to the eigenvalues and the eigenvectors of the modeled Reynolds stress tensor. The mathematical foundations of this framework are derived and explicated. Thence, this framework is applied to a set of separated turbulent flows, while compared to numerical and experimental data and contrasted against the predictions of the eigenvalue-only perturbation methodology. It is exhibited that for separated flows, this framework is able to yield significant enhancement over the established eigenvalue perturbation methodology in explaining the discrepancy against experimental observations and high-fidelity simulations. Furthermore, uncertainty bounds of potential engineering utility can be estimated by performing five specific RANS simulations, reducing the computational expenditure on such an exercise.

A validated computational model for the design of surface textures in full-film lubricated sliding

NASA Astrophysics Data System (ADS)

Schuh, Jonathon; Lee, Yong Hoon; Allison, James; Ewoldt, Randy

2016-11-01

Our recent experimental work showed that asymmetry is needed for surface textures to decrease friction in full-film lubricated sliding (thrust bearings) with Newtonian fluids; textures reduce the shear load and produce a separating normal force. The sign of the separating normal force is not predicted by previous 1-D theories. Here we model the flow with the Reynolds equation in cylindrical coordinates, numerically implemented with a pseudo-spectral method. The model predictions match experiments, rationalize the sign of the normal force, and allow for design of surface texture geometry. To minimize sliding friction with angled cylindrical textures, an optimal angle of asymmetry β exists. The optimal angle depends on the film thickness but not the sliding velocity within the applicable range of the model. The model has also been used to optimize generalized surface texture topography while satisfying manufacturability constraints.

Numerical Calculations of 3-D High-Lift Flows and Comparison with Experiment

NASA Technical Reports Server (NTRS)

Compton, William B, III

2015-01-01

Solutions were obtained with the Navier-Stokes CFD code TLNS3D to predict the flow about the NASA Trapezoidal Wing, a high-lift wing composed of three elements: the main-wing element, a deployed leading-edge slat, and a deployed trailing-edge flap. Turbulence was modeled by the Spalart-Allmaras one-equation turbulence model. One case with massive separation was repeated using Menter's two-equation SST (Menter's Shear Stress Transport) k-omega turbulence model in an attempt to improve the agreement with experiment. The investigation was conducted at a free stream Mach number of 0.2, and at angles of attack ranging from 10.004 degrees to 34.858 degrees. The Reynolds number based on the mean aerodynamic chord of the wing was 4.3 x 10 (sup 6). Compared to experiment, the numerical procedure predicted the surface pressures very well at angles of attack in the linear range of the lift. However, computed maximum lift was 5% low. Drag was mainly under predicted. The procedure correctly predicted several well-known trends and features of high-lift flows, such as off-body separation. The two turbulence models yielded significantly different solutions for the repeated case.

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread among the ensemble members of individual model, strong teleconnection (correlation analysis) with SST, coefficient of variation, inter-annual variability, analysis of Taylor diagram, etc. suggest that there is a need to improve coupled model instead of uncoupled model for the development of a better dynamical seasonal forecast system.

Prediction of XV-15 tilt rotor discrete frequency aeroacoustic noise with WOPWOP

NASA Technical Reports Server (NTRS)

Coffen, Charles D.; George, Albert R.

1990-01-01

The results, methodology, and conclusions of noise prediction calculations carried out to study several possible discrete frequency harmonic noise mechanisms of the XV-15 Tilt Rotor Aircraft in hover and helicopter mode forward flight are presented. The mechanisms studied were thickness and loading noise. In particular, the loading noise caused by flow separation and the fountain/ground plane effect were predicted with calculations made using WOPWOP, a noise prediction program developed by NASA Langley. The methodology was to model the geometry and aerodynamics of the XV-15 rotor blades in hover and steady level flight and then create corresponding FORTRAN subroutines which were used an input for WOPWOP. The models are described and the simplifying assumptions made in creating them are evaluated, and the results of the computations are presented. The computations lead to the following conclusions: The fountain/ground plane effect is an important source of aerodynamic noise for the XV-15 in hover. Unsteady flow separation from the airfoil passing through the fountain at high angles of attack significantly affects the predicted sound spectra and may be an important noise mechanism for the XV-15 in hover mode. The various models developed did not predict the sound spectra in helicopter forward flight. The experimental spectra indicate the presence of blade vortex interactions which were not modeled in these calculations. A need for further study and development of more accurate aerodynamic models, including unsteady stall in hover and blade vortex interactions in forward flight.

Simultaneous fermentation and separation in an immobilized cell trickle bed reactor: Acetone-butanol-ethane (ABE) and ethanol fermentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, C.H.

1989-01-01

A novel process employing immobilized cells and in-situ product removal was studied for acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum and ethanol fermentation by Saccharomyces cerevisiae. Experimental studies of ABE fermentation in a trickle bed reactor without product separation showed that solvent production could be improved by one order of magnitude compared to conventional batch fermentation. Control of effluent pH near 4.3 and feed glucose concentrations higher than 10 g/L were the necessary conditions for cell growth and solvent production. A mathematical model using an equilibrium staged model predicted efficient separation of butanol from the fermentation broth. Activity coefficients of multicomponentmore » system were estimated by Wilson's equation or the ASOG method. Inhibition by butanol and organic acids was incorporated into the kinetic expression. Experimental performance of simultaneous fermentation and separation in an immobilized cell trickle bed reactor showed that glucose conversion was improved as predicted by mathematical modeling and analysis. The effect of pH and temperature on ethanol fermentation by Saccharomyces cerevisiae was studied in free and immobilized cell reactors. Conditions for the highest glucose conversion, cell viability and least glycerol yield were determined.« less

Detection of Subsurface Material Separation in Shuttle Orbiter Slip-Side Joggle Region of the Wing Leading Edge using Infrared Imaging Data from Arc Jet Tests

NASA Technical Reports Server (NTRS)

Daryabeigi, Kamran; Walker, Sandra P.

2009-01-01

The objective of the present study was to determine whether infrared imaging (IR) surface temperature data obtained during arc-jet tests of Space Shuttle Orbiter s reinforced carbon-carbon (RCC) wing leading edge panel slip-side joggle region could be used to detect presence of subsurface material separation, and if so, to determine when separation occurs during the simulated entry profile. Recent thermostructural studies have indicated thermally induced interlaminar normal stress concentrations at the substrate/coating interface in the curved joggle region can result in local subsurface material separation, with the separation predicted to occur during approach to peak heating during reentry. The present study was an attempt to determine experimentally when subsurface material separations occur. A simplified thermal model of a flat RCC panel with subsurface material separation was developed and used to infer general surface temperature trends due to the presence of subsurface material separation. IR data from previously conducted arc-jet tests on three test specimens were analyzed: one without subsurface material separation either pre or post test, one with pre test separation, and one with separation developing during test. The simplified thermal model trend predictions along with comparison of experimental IR data of the three test specimens were used to successfully infer material separation from the arc-jet test data. Furthermore, for the test specimen that had developed subsurface material separation during the arc-jet tests, the initiation of separation appeared to occur during the ramp up to the peak heating condition, where test specimen temperature went from 2500 to 2800 F.

Analysis of airfoil transitional separation bubbles

NASA Technical Reports Server (NTRS)

Davis, R. L.; Carter, J. E.

1984-01-01

A previously developed local inviscid-viscous interaction technique for the analysis of airfoil transitional separation bubbles, ALESEP (Airfoil Leading Edge Separation) has been modified to utilize a more accurate windward finite difference procedure in the reversed flow region, and a natural transition/turbulence model has been incorporated for the prediction of transition within the separation bubble. Numerous calculations and experimental comparisons are presented to demonstrate the effects of the windward differencing scheme and the natural transition/turbulence model. Grid sensitivity and convergence capabilities of this inviscid-viscous interaction technique are briefly addressed. A major contribution of this report is that with the use of windward differencing, a second, counter-rotating eddy has been found to exist in the wall layer of the primary separation bubble.

MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation.

PubMed

Degroeve, Sven; Maddelein, Davy; Martens, Lennart

2015-07-01

We present an MS(2) peak intensity prediction server that computes MS(2) charge 2+ and 3+ spectra from peptide sequences for the most common fragment ions. The server integrates the Unimod public domain post-translational modification database for modified peptides. The prediction model is an improvement of the previously published MS(2)PIP model for Orbitrap-LTQ CID spectra. Predicted MS(2) spectra can be downloaded as a spectrum file and can be visualized in the browser for comparisons with observations. In addition, we added prediction models for HCD fragmentation (Q-Exactive Orbitrap) and show that these models compute accurate intensity predictions on par with CID performance. We also show that training prediction models for CID and HCD separately improves the accuracy for each fragmentation method. The MS(2)PIP prediction server is accessible from http://iomics.ugent.be/ms2pip. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Discovery of optimal zeolites for challenging separations and chemical conversions through predictive materials modeling

NASA Astrophysics Data System (ADS)

Siepmann, J. Ilja; Bai, Peng; Tsapatsis, Michael; Knight, Chris; Deem, Michael W.

2015-03-01

Zeolites play numerous important roles in modern petroleum refineries and have the potential to advance the production of fuels and chemical feedstocks from renewable resources. The performance of a zeolite as separation medium and catalyst depends on its framework structure and the type or location of active sites. To date, 213 framework types have been synthesized and >330000 thermodynamically accessible zeolite structures have been predicted. Hence, identification of optimal zeolites for a given application from the large pool of candidate structures is attractive for accelerating the pace of materials discovery. Here we identify, through a large-scale, multi-step computational screening process, promising zeolite structures for two energy-related applications: the purification of ethanol beyond the ethanol/water azeotropic concentration in a single separation step from fermentation broths and the hydroisomerization of alkanes with 18-30 carbon atoms encountered in petroleum refining. These results demonstrate that predictive modeling and data-driven science can now be applied to solve some of the most challenging separation problems involving highly non-ideal mixtures and highly articulated compounds. Financial support from the Department of Energy Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences under Award DE-FG02-12ER16362 is gratefully acknowledged.

Moisture Separator Reheater for NPP Turbines

NASA Astrophysics Data System (ADS)

Manabe, Jun; Kasahara, Jiro

This paper introduces the development of the current model Moisture Separator Reheater (MSR) for nuclear power plant (NPP) turbines, commercially placed in service in the period 1984-1997, focusing on the mist separation performance of the MSR along with drainage from heat exchanger tubes. A method of predicting the mist separation performance was devised first based on the observation of mist separation behaviors under an air-water test. Then the method was developed for the application to predict under the steam conditions, followed by the verification in comparison with the actual results of a steam condition test. The instability of tube drainage associated with both sub-cooling and temperature oscillation might adversely affect the seal welding of tubes to tube sheet due to thermal fatigue. The instability was measured on an existing unit to clarify behaviors and the development of a method to suppress them. Both methods were applied to newly constructed units and the effectiveness of the methods was demonstrated.

Numerical Analysis of Incipient Separation on 53 Deg Swept Diamond Wing

NASA Technical Reports Server (NTRS)

Frink, Neal T.

2015-01-01

A systematic analysis of incipient separation and subsequent vortex formation from moderately swept blunt leading edges is presented for a 53 deg swept diamond wing. This work contributes to a collective body of knowledge generated within the NATO/STO AVT-183 Task Group titled 'Reliable Prediction of Separated Flow Onset and Progression for Air and Sea Vehicles'. The objective is to extract insights from the experimentally measured and numerically computed flow fields that might enable turbulence experts to further improve their models for predicting swept blunt leading-edge flow separation. Details of vortex formation are inferred from numerical solutions after establishing a good correlation of the global flow field and surface pressure distributions between wind tunnel measurements and computed flow solutions. From this, significant and sometimes surprising insights into the nature of incipient separation and part-span vortex formation are derived from the wealth of information available in the computational solutions.

Model-based influences on humans’ choices and striatal prediction errors

PubMed Central

Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

2011-01-01

Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

The discomfort produced by noise and whole-body vertical vibration presented separately and in combination.

PubMed

Huang, Yu; Griffin, Michael J

2014-01-01

This study investigated the prediction of the discomfort caused by simultaneous noise and vibration from the discomfort caused by noise and the discomfort caused by vibration when they are presented separately. A total of 24 subjects used absolute magnitude estimation to report their discomfort caused by seven levels of noise (70-88 dBA SEL), 7 magnitudes of vibration (0.146-2.318 ms(- 1.75)) and all 49 possible combinations of these noise and vibration stimuli. Vibration did not significantly influence judgements of noise discomfort, but noise reduced vibration discomfort by an amount that increased with increasing noise level, consistent with a 'masking effect' of noise on judgements of vibration discomfort. A multiple linear regression model or a root-sums-of-squares model predicted the discomfort caused by combined noise and vibration, but the root-sums-of-squares model is more convenient and provided a more accurate prediction of the discomfort produced by combined noise and vibration.

A proposed metabolic strategy for monitoring disease progression in Alzheimer's disease.

PubMed

Greenberg, Nicola; Grassano, Antonio; Thambisetty, Madhav; Lovestone, Simon; Legido-Quigley, Cristina

2009-04-01

A specific, sensitive and essentially non-invasive assay to diagnose and monitor Alzheimer's disease (AD) would be valuable to both clinicians and medical researchers. The aim of this study was to perform a metabonomic statistical analysis on plasma fingerprints. Objectives were to investigate novel biomarkers indicative of AD, to consider the role of bile acids as AD biomarkers and to consider whether mild cognitive impairment (MCI) is a separate disease from AD. Samples were analysed by ultraperformance liquid chromatography-MS and resulting data sets were interpreted using soft-independent modelling of class analogy statistical analysis methods. PCA models did not show any grouping of subjects by disease state. Partial least-squares discriminant analysis (PLS-DS) models yielded class separation for AD. However, as with earlier studies, model validation revealed a predictive power of Q(2)<0.5 and indicating their unsuitability for predicting disease state. Three bile acids were extracted from the data and quantified, up-regulation was observed for MCI and AD patients. PLS-DA did not support MCI being considered as a separate disease from AD with MCI patient metabolic profiles being significantly closer to AD patients than controls. This study suggested that further investigation into the lipid fraction of the metabolome may yield useful biomarkers for AD and metabolomic profiles could be used to predict disease state in a clinical setting.

Evaluation of transition-sensitive eddy-viscosity turbulence models for separated flow in OpenFOAM

NASA Astrophysics Data System (ADS)

Fadhila, H.; Medina, H.; Beechook, A.; Aleksandrova, S.; Benjamin, S.

2017-07-01

A recently published transition-sensitive turbulence model, k-kL-ω-υ2 [1], is implemented in the open-source CFD package OpenFOAM, and its performance is evaluated in comparison with k-kL-ω [2] and υ2- f [3] models. On T3A and T3B flat plate cases, the k-kL-ω-υ2 model gives accurate transitional predictions. On a flapped NACA 23012 aerofoil, it is found to give only a small improvement over the k-kL-ω model (under 5% reduction in error for lift coefficient) compared with experimental results obtained at the Coventry University wind tunnel, showing limited effects of the extra transport equation which was added to sensitise the model to rotation and curvature effects. Assessment of fluctuating kinetic energy and the new wall-normal turbulent velocity scale shows overprediction near the wall compared to the υ2- f model which indicates a delayed prediction of separation.

Prediction of gradient retention data for hydrophilic interaction liquid chromatographic separation of native and fluorescently labeled oligosaccharides.

PubMed

Vaňková, Nikola; Česla, Petr

2017-02-17

In this work, we have investigated the predictive properties of mixed-mode retention model and oligomeric mixed-mode model, taking into account the contribution of monomeric units to the retention, in hydrophilic interaction liquid chromatography. The gradient retention times of native maltooligosaccharides and their fluorescent derivatives were predicted in the oligomeric series with number of monomeric glucose units in the range from two to seven. The maltooligosaccharides were separated on a packed column with carbamoyl-bonded silica stationary phase and 15 gradient profiles with different initial and final mobile phase composition were used with the gradient times 5; 7.5 and 10min. The predicted gradient retention times were compared for calculations based on isocratic retention data and gradient retention data, which provided better accuracy of the results. By comparing two different mobile phase additives, the more accurate retention times were predicted in mobile phases containing ammonium acetate. The acidic derivatives, prepared by reaction of an oligosaccharide with 2-aminobenzoic acid or 8-aminonaphthalene-1,3,6-trisulfonic acid, provided more accurate predictions of the retention data in comparison to native oligosaccharides or their neutral derivatives. The oligomeric mixed-mode model allowed prediction of gradient retention times using only one gradient profile, which significantly speeded-up the method development. Copyright © 2017 Elsevier B.V. All rights reserved.

Introduction to statistical modelling 2: categorical variables and interactions in linear regression.

PubMed

Lunt, Mark

2015-07-01

In the first article in this series we explored the use of linear regression to predict an outcome variable from a number of predictive factors. It assumed that the predictive factors were measured on an interval scale. However, this article shows how categorical variables can also be included in a linear regression model, enabling predictions to be made separately for different groups and allowing for testing the hypothesis that the outcome differs between groups. The use of interaction terms to measure whether the effect of a particular predictor variable differs between groups is also explained. An alternative approach to testing the difference between groups of the effect of a given predictor, which consists of measuring the effect in each group separately and seeing whether the statistical significance differs between the groups, is shown to be misleading. © The Author 2013. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Relationship between Quantitative CT Metrics and Health Status and Bode in COPD

PubMed Central

Martinez, Carlos H.; Chen, Ya-Hong; Westgate, Phillip M.; Liu, Lyrica X.; Murray, Susan; Curtis, Jeffrey L.; Make, Barry J.; Kazerooni, Ella A.; Lynch, David A.; Marchetti, Nathaniel; Washko, George R.; Martinez, Fernando J.; Han, MeiLan K.

2013-01-01

Background The value of quantitative computed tomography (QCT) to identify chronic obstructive pulmonary disease (COPD) phenotypes is increasingly appreciated. We hypothesized that QCT-defined emphysema and airway abnormalities relate to St. George's Respiratory Questionnaire (SGRQ) and BODE. Methods 1,200 COPDGene subjects meeting GOLD criteria for COPD with QCT analysis were included. Total lung emphysema was measured using density mask technique with a -950 HU threshold. An automated program measured mean wall thickness (WT), wall area percent (WA%) and pi10 in six segmental bronchi. Separate multivariate analyses examined the relative influence of airway measures and emphysema on SGRQ and BODE. Results In separate models predicting SGRQ score, a one unit standard deviation (SD) increase in each airway measure predicted higher SGRQ scores (for WT, 1.90 points higher, p=0.002; for WA%, 1.52 points higher, p=0.02; for pi10, 2.83 points higher p<0.001). The comparable increase in SGRQ for a one unit SD increase in percent emphysema in these models was relatively weaker, significant only in the pi10 model (for percent emphysema, 1.45 points higher, p=0.01). In separate models predicting BODE, a one unit SD increase in each airway measure predicted higher BODE scores (for WT, 1.07 fold increase, p<0.001; for WA%, 1.20 fold increase, p<0.001; for pi10, 1.16 fold increase, p<0.001). In these models, emphysema more strongly influenced BODE (range 1.24-1.26 fold increase, p<0.001). Conclusion Emphysema and airway disease both relate to clinically important parameters. The relative influence of airway disease is greater for SGRQ; the relative influence of emphysema is greater for BODE. PMID:22514236

Non-destructive and rapid prediction of moisture content in red pepper (Capsicum annuum L.) powder using near-infrared spectroscopy and a partial least squares regression model

USDA-ARS?s Scientific Manuscript database

Purpose: The aim of this study was to develop a technique for the non-destructive and rapid prediction of the moisture content in red pepper powder using near-infrared (NIR) spectroscopy and a partial least squares regression (PLSR) model. Methods: Three red pepper powder products were separated in...

Kinetic rate constant prediction supports the conformational selection mechanism of protein binding.

PubMed

Moal, Iain H; Bates, Paul A

2012-01-01

The prediction of protein-protein kinetic rate constants provides a fundamental test of our understanding of molecular recognition, and will play an important role in the modeling of complex biological systems. In this paper, a feature selection and regression algorithm is applied to mine a large set of molecular descriptors and construct simple models for association and dissociation rate constants using empirical data. Using separate test data for validation, the predicted rate constants can be combined to calculate binding affinity with accuracy matching that of state of the art empirical free energy functions. The models show that the rate of association is linearly related to the proportion of unbound proteins in the bound conformational ensemble relative to the unbound conformational ensemble, indicating that the binding partners must adopt a geometry near to that of the bound prior to binding. Mirroring the conformational selection and population shift mechanism of protein binding, the models provide a strong separate line of evidence for the preponderance of this mechanism in protein-protein binding, complementing structural and theoretical studies.

Systematic Interpolation Method Predicts Antibody Monomer-Dimer Separation by Gradient Elution Chromatography at High Protein Loads.

PubMed

Creasy, Arch; Reck, Jason; Pabst, Timothy; Hunter, Alan; Barker, Gregory; Carta, Giorgio

2018-05-29

A previously developed empirical interpolation (EI) method is extended to predict highly overloaded multicomponent elution behavior on a cation exchange (CEX) column based on batch isotherm data. Instead of a fully mechanistic model, the EI method employs an empirically modified multicomponent Langmuir equation to correlate two-component adsorption isotherm data at different salt concentrations. Piecewise cubic interpolating polynomials are then used to predict competitive binding at intermediate salt concentrations. The approach is tested for the separation of monoclonal antibody monomer and dimer mixtures by gradient elution on the cation exchange resin Nuvia HR-S. Adsorption isotherms are obtained over a range of salt concentrations with varying monomer and dimer concentrations. Coupled with a lumped kinetic model, the interpolated isotherms predict the column behavior for highly overloaded conditions. Predictions based on the EI method showed good agreement with experimental elution curves for protein loads up to 40 mg/mL column or about 50% of the column binding capacity. The approach can be extended to other chromatographic modalities and to more than two components. This article is protected by copyright. All rights reserved.

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments

PubMed Central

Colburn, H. Steven

2016-01-01

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. PMID:27698261

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments.

PubMed

Mi, Jing; Colburn, H Steven

2016-10-03

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. © The Author(s) 2016.

Predictions of Cockpit Simulator Experimental Outcome Using System Models

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Goka, T.

1984-01-01

This study involved predicting the outcome of a cockpit simulator experiment where pilots used cockpit displays of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. The experiments were run on the NASA Ames Research Center multicab cockpit simulator facility. Prior to the experiments, a mathematical model of the pilot/aircraft/CDTI flight system was developed which included relative in-trail and vertical dynamics between aircraft in the approach string. This model was used to construct a digital simulation of the string dynamics including response to initial position errors. The model was then used to predict the outcome of the in-trail following cockpit simulator experiments. Outcome included performance and sensitivity to different separation criteria. The experimental results were then used to evaluate the model and its prediction accuracy. Lessons learned in this modeling and prediction study are noted.

Genomic prediction based on data from three layer lines using non-linear regression models.

PubMed

Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L

2014-11-06

Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional occurrence of large negative accuracies when the evaluated line was not included in the training dataset. Furthermore, when using a multi-line training dataset, non-linear models provided information on the genotype data that was complementary to the linear models, which indicates that the underlying data distributions of the three studied lines were indeed heterogeneous.

Experimental, Theoretical, and Computational Investigation of Separated Nozzle Flows

NASA Technical Reports Server (NTRS)

Hunter, Craig A.

2004-01-01

A detailed experimental, theoretical, and computational study of separated nozzle flows has been conducted. Experimental testing was performed at the NASA Langley 16-Foot Transonic Tunnel Complex. As part of a comprehensive static performance investigation, force, moment, and pressure measurements were made and schlieren flow visualization was obtained for a sub-scale, non-axisymmetric, two-dimensional, convergent- divergent nozzle. In addition, two-dimensional numerical simulations were run using the computational fluid dynamics code PAB3D with two-equation turbulence closure and algebraic Reynolds stress modeling. For reference, experimental and computational results were compared with theoretical predictions based on one-dimensional gas dynamics and an approximate integral momentum boundary layer method. Experimental results from this study indicate that off-design overexpanded nozzle flow was dominated by shock induced boundary layer separation, which was divided into two distinct flow regimes; three- dimensional separation with partial reattachment, and fully detached two-dimensional separation. The test nozzle was observed to go through a marked transition in passing from one regime to the other. In all cases, separation provided a significant increase in static thrust efficiency compared to the ideal prediction. Results indicate that with controlled separation, the entire overexpanded range of nozzle performance would be within 10% of the peak thrust efficiency. By offering savings in weight and complexity over a conventional mechanical exhaust system, this may allow a fixed geometry nozzle to cover an entire flight envelope. The computational simulation was in excellent agreement with experimental data over most of the test range, and did a good job of modeling internal flow and thrust performance. An exception occurred at low nozzle pressure ratios, where the two-dimensional computational model was inconsistent with the three-dimensional separation observed in the experiment. In general, the computation captured the physics of the shock boundary layer interaction and shock induced boundary layer separation in the nozzle, though there were some differences in shock structure compared to experiment. Though minor, these differences could be important for studies involving flow control or thrust vectoring of separated nozzles. Combined with other observations, this indicates that more detailed, three-dimensional computational modeling needs to be conducted to more realistically simulate shock-separated nozzle flows.

Comparison of measured ozone in southeastern Virginia with computer predictions from a photochemical model

NASA Technical Reports Server (NTRS)

Wakelyn, N. T.; Gregory, G. L.

1980-01-01

Data for one day of the 1977 southeastern Virginia urban plume study are compared with computer predictions from a traveling air parcel model using a contemporary photochemical mechanism with a minimal description of nonmethane hydrocarbon (NMHC) constitution and chemistry. With measured initial NOx and O3 concentrations and a current separate estimate of urban source loading input to the model, and for a variation of initial NMHC over a reasonable range, an ozone increase over the day is predicted from the photochemical simulation which is consistent with the flight path averaged airborne data.

Mathematical and experimental modelling of the dynamic bubble processes occurring in a two-phase cyclonic separation device

NASA Astrophysics Data System (ADS)

Schrage, Dean Stewart

1998-11-01

This dissertation presents a combined mathematical and experimental analysis of the fluid dynamics of a gas- liquid, dispersed-phase cyclonic separation device. The global objective of this research is to develop a simulation model of separation process in order to predict the void fraction field within a cyclonic separation device. The separation process is approximated by analyzing the dynamic motion of many single-bubbles, moving under the influence of the far-field, interacting with physical boundaries and other bubbles. The dynamic motion of the bubble is described by treating the bubble as a point-mass and writing an inertial force balance, equating the force applied to the bubble-point-location to the inertial acceleration of the bubble mass (also applied to the point-location). The forces which are applied to the bubble are determined by an integration of the surface pressure over the bubble. The surface pressure is coupled to the intrinsic motion of the bubble, and is very difficult to obtain exactly. However, under moderate Reynolds number, the wake trailing a bubble is small and the near-field flow field can be approximated as an inviscid flow field. Unconventional potential flow techniques are employed to solve for the surface pressure; the hydrodyamic forces are described as a hydrodynamic mass tensor operating on the bubble acceleration vector. The inviscid flow model is augmented with adjunct forces which describe: drag forces, dynamic lift, far-field pressure forces. The dynamic equations of motion are solved both analytically and numerically for the bubble trajectory in specific flow field examples. A validation of these equations is performed by comparing to an experimentally-derived trajectory of a single- bubble, which is released into a cylindrical Couette flow field (inner cylinder rotating) at varying positions. Finally, a simulation of a cyclonic separation device is performed by extending the single-bubble dynamic model to a multi-bubble ensemble. A simplified model is developed to predict the effects of bubble-interaction. The simulation qualitatively depicts the separation physics encountered in an actual cyclonic separation device, supporting the original tenet that the separation process can be approximated by the collective motions of single- bubbles.

An improved model for computing the trajectories of conductive particles in roll-type electrostatic separator for recycling metals from WEEE.

PubMed

Wu, Jiang; Li, Jia; Xu, Zhenming

2009-08-15

Electrostatic separation presents an effective and environmentally friendly way for recycling metals and nonmetals from ground waste electrical and electronic equipment (WEEE). For this process, the trajectory of conductive particle is significant and some models have been established. However, the results of previous researches are limited by some simplifying assumptions and lead to a notable discrepancy between the model prediction and the experimental results. In the present research, a roll-type corona-electrostatic separator and ground printed circuit board (PCB) wastes were used to investigate the trajectory of the conductive particle. Two factors, the air drag force and the different charging situation, were introduced into the improved model. Their effects were analyzed and an improved model for the theoretical trajectory of conductive particle was established. Compared with the previous one, the improved model shows a good agreement with the experimental results. It provides a positive guidance for designing of separator and makes a progress for recycling the metals and nonmetals from WEEE.

Parametric Study of Flow Control Over a Hump Model Using an Unsteady Reynolds- Averaged Navier-Stokes Code

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Greenblatt, David

2007-01-01

This is an expanded version of a limited-length paper that appeared at the 5th International Symposium on Turbulence and Shear Flow Phenomena by the same authors. A computational study was performed for steady and oscillatory flow control over a hump model with flow separation to assess how well the steady and unsteady Reynolds-averaged Navier-Stokes equations predict trends due to Reynolds number, control magnitude, and control frequency. As demonstrated in earlier studies, the hump model case is useful because it clearly demonstrates a failing in all known turbulence models: they under-predict the turbulent shear stress in the separated region and consequently reattachment occurs too far downstream. In spite of this known failing, three different turbulence models were employed to determine if trends can be captured even though absolute levels are not. Overall the three turbulence models showed very similar trends as experiment for steady suction, but only agreed qualitatively with some of the trends for oscillatory control.

High-Lift OVERFLOW Analysis of the DLR-F11 Wind Tunnel Model

NASA Technical Reports Server (NTRS)

Pulliam, Thomas H.; Sclafani, Anthony J.

2014-01-01

In response to the 2nd AIAA CFD High Lift Prediction Workshop, the DLR-F11 wind tunnel model is analyzed using the Reynolds-averaged Navier-Stokes flow solver OVERFLOW. A series of overset grids for a bracket-off landing configuration is constructed and analyzed as part of a general grid refinement study. This high Reynolds number (15.1 million) analysis is done at multiple angles-of-attack to evaluate grid resolution effects at operational lift levels as well as near stall. A quadratic constitutive relation recently added to OVERFLOW for improved solution accuracy is utilized for side-of-body separation issues at low angles-of-attack and outboard wing separation at stall angles. The outboard wing separation occurs when the slat brackets are added to the landing configuration and is a source of discrepancy between the predictions and experimental data. A detailed flow field analysis is performed at low Reynolds number (1.35 million) after pressure tube bundles are added to the bracket-on medium grid system with the intent of better understanding bracket/bundle wake interaction with the wing's boundary layer. Localized grid refinement behind each slat bracket and pressure tube bundle coupled with a time accurate analysis are exercised in an attempt to improve stall prediction capability. The results are inconclusive and suggest the simulation is missing a key element such as boundary layer transition. The computed lift curve is under-predicted through the linear range and over-predicted near stall, and the solution from the most complete configuration analyzed shows outboard wing separation occurring behind slat bracket 6 where the experiment shows it behind bracket 5. These results are consistent with most other participants of this workshop.

Predicting the kinetics of Listeria monocytogenes and Yersinia enterocolitica under dynamic growth/death-inducing conditions, in Italian style fresh sausage.

PubMed

Iannetti, Luigi; Salini, Romolo; Sperandii, Anna Franca; Santarelli, Gino Angelo; Neri, Diana; Di Marzio, Violeta; Romantini, Romina; Migliorati, Giacomo; Baranyi, József

2017-01-02

Traditional Italian pork products can be consumed after variable drying periods, where the temporal decrease of water activity spans from optimal to inactivating values. This makes it necessary to A) consider the bias factor when applying culture-medium-based predictive models to sausage; B) apply the dynamic version (described by differential equations) of those models; C) combine growth and death models in a continuous way, including the highly uncertain growth/no growth range separating the two regions. This paper tests the applicability of published predictive models on the responses of Listeria monocytogenes and Yersinia enterocolitica to dynamic conditions in traditional Italian pork sausage, where the environment changes from growth-supporting to inhibitory conditions, so the growth and death models need to be combined. The effect of indigenous lactic acid bacteria was also taken into account in the predictions. Challenge tests were carried out using such sausages, inoculated separately with L. monocytogenes and Y. enterocolitica, stored for 480h at 8, 12, 18 and 20°C. The pH was fairly constant, while the water activity changed dynamically. The effects of the environment on the specific growth and death rate of the studied organisms were predicted using previously published predictive models and parameters. Microbial kinetics in many products with a long shelf-life and dynamic internal environment, could result in both growth and inactivation, making it difficult to estimate the bacterial concentration at the time of consumption by means of commonly available predictive software tools. Our prediction of the effect of the storage environment, where the water activity gradually decreases during a drying period, is designed to overcome these difficulties. The methodology can be used generally to predict and visualise bacterial kinetics under temporal variation of environments, which is vital when assessing the safety of many similar products. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction of the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient-elution conditions.

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna; Ruggieri, Fabrizio

2014-08-01

In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs. Predictive performance of this model is evaluated on six external triazines and four unseen separation conditions. For comparison, retention of triazines is modelled by both quantitative structure-retention relationships and response surface methodology, which describe separately the effect of molecular structure and gradient parameters on the retention. Although applied to a wider variable domain, the network provides a performance comparable to that of the above "local" models and retention times of triazines are modelled with accuracy generally better than 7%. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comparative study of full Navier-Stokes and Reduced Navier-Stokes analyses for separating flows within a diffusing inlet S-duct

NASA Technical Reports Server (NTRS)

Anderson, B. H.; Reddy, D. R.; Kapoor, K.

1993-01-01

A three-dimensional implicit Full Navier-Stokes (FNS) analysis and a 3D Reduced Navier-Stokes (RNS) initial value space marching solution technique has been applied to a class of separate flow problems within a diffusing S-duct configuration characterized as vortex-liftoff. Both Full Navier-Stokes and Reduced Navier-Stokes solution techniques were able to capture the overall flow physics of vortex lift-off, however more consideration must be given to the development of turbulence models for the prediction of the locations of separation and reattachment. This accounts for some of the discrepancies in the prediction of the relevant inlet distortion descriptors, particularly circumferential distortion. The 3D RNS solution technique adequately described the topological structure of flow separation associated with vortex lift-off.

Structure of Monopropellant Spray Flames at Elevated Pressures

DTIC Science & Technology

1990-01-15

process were developed , both ignoring and considering effects of separated flow, and evaluated using the new measurements. Supercritical combustion...McliJUTV CL*.S’a»’ iCAr ’ON 0’ Igj iadf REPORT DOCUMENTATION PAGE i*. Kiwwr Jicjmry CLASSiFiCATtow unclsssified i*. sicumrr cuusiwcAnoN AUTHORITY...separated flow. Deterministic and stochastic separated flow models were developed which yielded predictions that were similar to each other and were

Model-based learning and the contribution of the orbitofrontal cortex to the model-free world

PubMed Central

McDannald, Michael A.; Takahashi, Yuji K.; Lopatina, Nina; Pietras, Brad W.; Jones, Josh L.; Schoenbaum, Geoffrey

2012-01-01

Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. PMID:22487030

Energy and time modelling of kerbside waste collection: Changes incurred when adding source separated food waste.

PubMed

Edwards, Joel; Othman, Maazuza; Burn, Stewart; Crossin, Enda

2016-10-01

The collection of source separated kerbside municipal FW (SSFW) is being incentivised in Australia, however such a collection is likely to increase the fuel and time a collection truck fleet requires. Therefore, waste managers need to determine whether the incentives outweigh the cost. With literature scarcely describing the magnitude of increase, and local parameters playing a crucial role in accurately modelling kerbside collection; this paper develops a new general mathematical model that predicts the energy and time requirements of a collection regime whilst incorporating the unique variables of different jurisdictions. The model, Municipal solid waste collect (MSW-Collect), is validated and shown to be more accurate at predicting fuel consumption and trucks required than other common collection models. When predicting changes incurred for five different SSFW collection scenarios, results show that SSFW scenarios require an increase in fuel ranging from 1.38% to 57.59%. There is also a need for additional trucks across most SSFW scenarios tested. All SSFW scenarios are ranked and analysed in regards to fuel consumption; sensitivity analysis is conducted to test key assumptions. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Efficiency and Accuracy of Time-Accurate Turbulent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Sanetrik, Mark D.; Biedron, Robert T.; Melson, N. Duane; Parlette, Edward B.

1995-01-01

The accuracy and efficiency of two types of subiterations in both explicit and implicit Navier-Stokes codes are explored for unsteady laminar circular-cylinder flow and unsteady turbulent flow over an 18-percent-thick circular-arc (biconvex) airfoil. Grid and time-step studies are used to assess the numerical accuracy of the methods. Nonsubiterative time-stepping schemes and schemes with physical time subiterations are subject to time-step limitations in practice that are removed by pseudo time sub-iterations. Computations for the circular-arc airfoil indicate that a one-equation turbulence model predicts the unsteady separated flow better than an algebraic turbulence model; also, the hysteresis with Mach number of the self-excited unsteadiness due to shock and boundary-layer separation is well predicted.

The Role of Separation Bubbles on the Aerodynamic Characteristics of Airfoils, Including Stall and Post-Stall, at Low Reynolds Numbers

NASA Technical Reports Server (NTRS)

Chen, Hsun H.; Cebeci, Tuncer

2007-01-01

Airfoils at high Reynolds numbers, in general, have small separation bubbles that are usually confined to the leading edge. Since the Reynolds number is large, the turbulence model for the transition region between the laminar and turbulent flow is not important. Furthermore, the onset of transition occurs either at separation or prior to separation and can be predicted satisfactorily by empirical correlations when the incident angle is small and can be assumed to correspond to laminar separation when the correlations do not apply, i.e., at high incidence angles.

A generalized predictive model for direct gain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Givoni, B.

In the correlational model for direct gain developed by the Los Alamos National Laboratory, a list of constants applicable to different types of buildings or passive solar systems was specified separately for each type. In its original form, the model was applicable only to buildings similar in their heat capacity, type of glazing, or night insulation to the types specified by the model. While maintaining the general form of the predictive equations, the new model, the predictive model for direct gain (PMDG), replaces the constants with functions dependent upon the thermal properties of the building, or the components of themore » solar system, or both. By this transformation, the LANL model for direct gain becomes a generalized one. The new model predicts the performance of buildings heated by direct gain with any heat capacity, glazing, and night insulation as functions of their thermophysical properties and climatic conditions.« less

Predicting Market Impact Costs Using Nonparametric Machine Learning Models.

PubMed

Park, Saerom; Lee, Jaewook; Son, Youngdoo

2016-01-01

Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance.

Evolution of the Radial Abundance Gradient and Cold Gas along the Milky Way Disk

NASA Astrophysics Data System (ADS)

Chen, Q. S.; Chang, R. X.; Yin, J.

2014-03-01

We have constructed a phenomenological model of the chemical evolution of the Milky Way disk, and treated the molecular and atomic gas separately. Using this model, we explore the radial profiles of oxygen abundance, the surface density of cold gas, and their time evolutions. It is shown that the model predictions are very sensitive to the adopted infall time-scale. By comparing the model predictions with the observations, we find that the model adopting the star formation law based on H_2 can properly predict the observed radial distributions of cold gas and oxygen abundance gradient along the disk. We also compare the model results with the predictions of the model which adopts the instantaneous recycling approximation (IRA), and find that the IRA assumption has little influence on the model results, especially in the low-density gas region.

Predicting Market Impact Costs Using Nonparametric Machine Learning Models

PubMed Central

Park, Saerom; Lee, Jaewook; Son, Youngdoo

2016-01-01

Market impact cost is the most significant portion of implicit transaction costs that can reduce the overall transaction cost, although it cannot be measured directly. In this paper, we employed the state-of-the-art nonparametric machine learning models: neural networks, Bayesian neural network, Gaussian process, and support vector regression, to predict market impact cost accurately and to provide the predictive model that is versatile in the number of variables. We collected a large amount of real single transaction data of US stock market from Bloomberg Terminal and generated three independent input variables. As a result, most nonparametric machine learning models outperformed a-state-of-the-art benchmark parametric model such as I-star model in four error measures. Although these models encounter certain difficulties in separating the permanent and temporary cost directly, nonparametric machine learning models can be good alternatives in reducing transaction costs by considerably improving in prediction performance. PMID:26926235

Numerical solution of turbulent flow past a backward facing step using a nonlinear K-epsilon model

NASA Technical Reports Server (NTRS)

Speziale, C. G.; Ngo, Tuan

1987-01-01

The problem of turbulent flow past a backward facing step is important in many technological applications and has been used as a standard test case to evaluate the performance of turbulence models in the prediction of separated flows. It is well known that the commonly used kappa-epsilon (and K-l) models of turbulence yield inaccurate predictions for the reattachment points in this problem. By an analysis of the mean vorticity transport equation, it will be argued that the intrinsically inaccurate prediction of normal Reynolds stress differences by the Kappa-epsilon and K-l models is a major contributor to this problem. Computations using a new nonlinear kappa-epsilon model (which alleviates this deficiency) are made with the TEACH program. Comparisons are made between the improved results predicted by this nonlinear kappa-epsilon model and those obtained from the linear kappa-epsilon model as well as from second-order closure models.

Data integration of structured and unstructured sources for assigning clinical codes to patient stays

PubMed Central

Luyckx, Kim; Luyten, Léon; Daelemans, Walter; Van den Bulcke, Tim

2016-01-01

Objective Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation. Methods Two separate data integration approaches were evaluated. Early data integration combines features of several sources within a single model, and late data integration learns a separate model per data source and combines these predictions with a meta-learner. This is evaluated on data sources and clinical codes from a broad set of medical specialties. Results When compared with the best individual prediction source, late data integration leads to improvements in predictive power (eg, overall F-measure increased from 30.6% to 38.3% for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes), while early data integration is less consistent. The predictive strength strongly differs between medical specialties, both for ICD-9-CM diagnostic and procedural codes. Discussion Structured data provides complementary information to unstructured data (and vice versa) for predicting ICD-9-CM codes. This can be captured most effectively by the proposed late data integration approach. Conclusions We demonstrated that models using multiple electronic health record data sources systematically outperform models using data sources in isolation in the task of predicting ICD-9-CM codes over a broad range of medical specialties. PMID:26316458

Prediction of the effect of formulation on the toxicity of chemicals.

PubMed

Mistry, Pritesh; Neagu, Daniel; Sanchez-Ruiz, Antonio; Trundle, Paul R; Vessey, Jonathan D; Gosling, John Paul

2017-01-01

Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.

A Three-Dimensional Solution of Flows over Wings with Leading-Edge Vortex Separation. Part 1: Engineering Document

NASA Technical Reports Server (NTRS)

Brune, G. W.; Weber, J. A.; Johnson, F. T.; Lu, P.; Rubbert, P. E.

1975-01-01

A method of predicting forces, moments, and detailed surface pressures on thin, sharp-edged wings with leading-edge vortex separation in incompressible flow is presented. The method employs an inviscid flow model in which the wing and the rolled-up vortex sheets are represented by piecewise, continuous quadratic doublet sheet distributions. The Kutta condition is imposed on all wing edges. Computed results are compared with experimental data and with the predictions of the leading-edge suction analogy for a selected number of wing planforms over a wide range of angle of attack. These comparisons show the method to be very promising, capable of producing not only force predictions, but also accurate predictions of detailed surface pressure distributions, loads, and moments.

Genetic interactions for heat stress and production level: predicting foreign from domestic data

USDA-ARS?s Scientific Manuscript database

Genetic by environmental interactions were estimated from U.S. national data by separately adding random regressions for heat stress (HS) and herd production level (HL) to the all-breed animal model to improve predictions of future records and rankings in other climate and production situations. Yie...

A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model

PubMed Central

Niu, Jian; Zhao, Jun; Xu, Zuhua; Qian, Jixin

2009-01-01

A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. PMID:19834542

Application of Navier-Stokes code PAB3D with kappa-epsilon turbulence model to attached and separated flows

NASA Technical Reports Server (NTRS)

Abdol-Hamid, Khaled S.; Lakshmanan, B.; Carlson, John R.

1995-01-01

A three-dimensional Navier-Stokes solver was used to determine how accurately computations can predict local and average skin friction coefficients for attached and separated flows for simple experimental geometries. Algebraic and transport equation closures were used to model turbulence. To simulate anisotropic turbulence, the standard two-equation turbulence model was modified by adding nonlinear terms. The effects of both grid density and the turbulence model on the computed flow fields were also investigated and compared with available experimental data for subsonic and supersonic free-stream conditions.

Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Gaussian Processes Mixture

PubMed Central

Li, Lingling; Wang, Pengchong; Chao, Kuei-Hsiang; Zhou, Yatong; Xie, Yang

2016-01-01

The remaining useful life (RUL) prediction of Lithium-ion batteries is closely related to the capacity degeneration trajectories. Due to the self-charging and the capacity regeneration, the trajectories have the property of multimodality. Traditional prediction models such as the support vector machines (SVM) or the Gaussian Process regression (GPR) cannot accurately characterize this multimodality. This paper proposes a novel RUL prediction method based on the Gaussian Process Mixture (GPM). It can process multimodality by fitting different segments of trajectories with different GPR models separately, such that the tiny differences among these segments can be revealed. The method is demonstrated to be effective for prediction by the excellent predictive result of the experiments on the two commercial and chargeable Type 1850 Lithium-ion batteries, provided by NASA. The performance comparison among the models illustrates that the GPM is more accurate than the SVM and the GPR. In addition, GPM can yield the predictive confidence interval, which makes the prediction more reliable than that of traditional models. PMID:27632176

Fractional reactive extraction for symmetrical separation of 4-nitro-D,L-phenylalanine in centrifugal contactor separators: experiments and modeling.

PubMed

Tang, Kewen; Wen, Ping; Zhang, Panliang; Huang, Yan

2015-01-01

The enantioselective liquid-liquid extraction of 4-nitro-D,L-phenylalanine (D,L-Nphy) using PdCl2 {(s)-BINAP} as extractant in dichloroethane was studied experimentally in a countercurrent cascade of 10 centrifugal contactor separators (CCSs) at 5°C, involving flow ratio, extractant concentration, and Cl(-) concentration. The steady-state enantiomeric excess (ee) in both stream exits was 90.86% at a 93.29% yield. The predicted value was modeled using an equilibrium stage approach. The correlation between model and experiment was satisfactory. The model was applied to optimize the production of both enantiomers in >97% ee and >99% ee. 14 stages and 16 stages are required for 97% ee and 99% ee for both enantiomers, respectively. © 2014 Wiley Periodicals, Inc.

An experimental and numerical investigation of shock-wave induced turbulent boundary-layer separation at hypersonic speeds

NASA Technical Reports Server (NTRS)

Marvin, J. G.; Horstman, C. C.; Rubesin, M. W.; Coakley, T. J.; Kussoy, M. I.

1975-01-01

An experiment designed to test and guide computations of the interaction of an impinging shock wave with a turbulent boundary layer is described. Detailed mean flow-field and surface data are presented for two shock strengths which resulted in attached and separated flows, respectively. Numerical computations, employing the complete time-averaged Navier-Stokes equations along with algebraic eddy-viscosity and turbulent Prandtl number models to describe shear stress and heat flux, are used to illustrate the dependence of the computations on the particulars of the turbulence models. Models appropriate for zero-pressure-gradient flows predicted the overall features of the flow fields, but were deficient in predicting many of the details of the interaction regions. Improvements to the turbulence model parameters were sought through a combination of detailed data analysis and computer simulations which tested the sensitivity of the solutions to model parameter changes. Computer simulations using these improvements are presented and discussed.

Measurements in a Transitional Boundary Layer Under Low-Pressure Turbine Airfoil Conditions

NASA Technical Reports Server (NTRS)

Simon, Terrence W.; Qiu, Songgang; Yuan, Kebiao; Ashpis, David (Technical Monitor); Simon, Fred (Technical Monitor)

2000-01-01

This report presents the results of an experimental study of transition from laminar to turbulent flow in boundary layers or in shear layers over separation zones on a convex-curved surface which simulates the suction surface of a low-pressure turbine airfoil. Flows with various free-stream turbulence intensity (FSTI) values (0.5%, 2.5% and 10%), and various Reynolds numbers (50,000, 100,000 200,000 and 300,000) are investigated. Reynold numbers in the present study are based on suction surface length and passage exit mean velocity. Flow separation followed by transition within the separated flow region is observed for the lower-Re cases at each of the FSTI levels. At the highest Reynolds numbers and at elevated FSn, transition of the attached boundary layer begins before separation, and the separation zone is small. Transition proceeds in the shear layer over the separation bubble. For both the transitional boundary layer and the transitional shear layer, mean velocity, turbulence intensity and intermittency (the fraction of the time the flow is turbulent) distributions are presented. The present data are compared to published distribution models for bypass transition, intermittency distribution through transition, transition start position, and transition length. A model developed for transition of separated flows is shown to adequately predict the location of the beginning of transition, for these cases, and a model developed for transitional boundary layer flows seems to adequately predict the path of intermittency through transition when the transition start and end are known. These results are useful for the design of low-pressure turbine stages which are known to operate under conditions replicated by these tests.

Prediction of Phase Separation of Immiscible Ga-Tl Alloys

NASA Astrophysics Data System (ADS)

Kim, Yunkyum; Kim, Han Gyeol; Kang, Youn-Bae; Kaptay, George; Lee, Joonho

2017-06-01

Phase separation temperature of Ga-Tl liquid alloys was investigated using the constrained drop method. With this method, density and surface tension were investigated together. Despite strong repulsive interactions, molar volume showed ideal mixing behavior, whereas surface tension of the alloy was close to that of pure Tl due to preferential adsorption of Tl. Phase separation temperatures and surface tension values obtained with this method were close to the theoretically calculated values using three different thermodynamic models.

An efficient approach to understanding and predicting the effects of multiple task characteristics on performance.

PubMed

Richardson, Miles

2017-04-01

In ergonomics there is often a need to identify and predict the separate effects of multiple factors on performance. A cost-effective fractional factorial approach to understanding the relationship between task characteristics and task performance is presented. The method has been shown to provide sufficient independent variability to reveal and predict the effects of task characteristics on performance in two domains. The five steps outlined are: selection of performance measure, task characteristic identification, task design for user trials, data collection, regression model development and task characteristic analysis. The approach can be used for furthering knowledge of task performance, theoretical understanding, experimental control and prediction of task performance. Practitioner Summary: A cost-effective method to identify and predict the separate effects of multiple factors on performance is presented. The five steps allow a better understanding of task factors during the design process.

Model-based influences on humans' choices and striatal prediction errors.

PubMed

Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

2011-03-24

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

Stress granule formation via ATP depletion-triggered phase separation

NASA Astrophysics Data System (ADS)

Wurtz, Jean David; Lee, Chiu Fan

2018-04-01

Stress granules (SG) are droplets of proteins and RNA that form in the cell cytoplasm during stress conditions. We consider minimal models of stress granule formation based on the mechanism of phase separation regulated by ATP-driven chemical reactions. Motivated by experimental observations, we identify a minimal model of SG formation triggered by ATP depletion. Our analysis indicates that ATP is continuously hydrolysed to deter SG formation under normal conditions, and we provide specific predictions that can be tested experimentally.

The rheology and phase separation kinetics of mixed-matrix membrane dopes

NASA Astrophysics Data System (ADS)

Olanrewaju, Kayode Olaseni

Mixed-matrix hollow fiber membranes are being developed to offer more efficient gas separations applications than what the current technologies allow. Mixed-matrix membranes (MMMs) are membranes in which molecular sieves incorporated in a polymer matrix enhance separation of gas mixtures based on the molecular size difference and/or adsorption properties of the component gases in the molecular sieve. The major challenges encountered in the efficient development of MMMs are associated with some of the paradigm shifts involved in their processing, as compared to pure polymer membranes. For instance, mixed-matrix hollow fiber membranes are prepared by a dry-wet jet spinning method. Efficient large scale processing of hollow fibers by this method requires knowledge of two key process variables: the rheology and kinetics of phase separation of the MMM dopes. Predicting the rheological properties of MMM dopes is not trivial; the presence of particles significantly affects neat polymer membrane dopes. Therefore, the need exists to characterize and develop predictive capabilities for the rheology of MMM dopes. Furthermore, the kinetics of phase separation of polymer solutions is not well understood. In the case of MMM dopes, the kinetics of phase separation are further complicated by the presence of porous particles in a polymer solution. Thus, studies on the phase separation kinetics of polymer solutions and suspensions of zeolite particles in polymer solutions are essential. Therefore, this research thesis aims to study the rheology and phase separation kinetics of mixed-matrix membrane dopes. In our research efforts to develop predictive models for the shear rheology of suspensions of zeolite particles in polymer solutions, it was found that MFI zeolite suspensions have relative viscosities that dramatically exceed the Krieger-Dougherty predictions for hard sphere suspensions. Our investigations showed that the major origin of this discrepancy is the selective absorption of solvent molecules from the suspending polymer solution into the zeolite pores. Consequently, both the viscosity of the polymer solution and the particle contribution to the suspension viscosity are greatly increased. A predictive model for the viscosity of porous zeolite suspensions incorporating a solvent absorption parameter, alpha, into the Krieger-Dougherty model was developed. We experimentally determined the solvent absorption parameter and our results are in good agreement with the theoretical pore volume of MFI particles. In addition, fundamental studies were conducted with spherical nonporous silica suspensions to elucidate the role of colloidal and hydrodynamic forces on the rheology of mixed-matrix membrane dopes. Also in this thesis, details of a novel microfluidic device for measuring the phase separation kinetics of membrane dopes are presented. We have used this device to quantify the phase separation kinetics (PSK) of polymer solutions and MMM dopes upon contact with an array of relevant nonsolvent. For the polymer solution, we found that PSK is governed by the micro-rheological and thermodynamic properties of the polymer solution and nonsolvent. For the MMM dopes, we found that the PSK may increase with increase in particles surface area due to surface diffusion enhancement. In addition, it was found that the dispersed particles alter the thermodynamic properties of the dope based on the hydrophilicity and porosity of the particle.

Cognitive control predicts use of model-based reinforcement learning.

PubMed

Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

2015-02-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

On the frequency of close binary systems among very low-mass stars and brown dwarfs

NASA Astrophysics Data System (ADS)

Maxted, P. F. L.; Jeffries, R. D.

2005-09-01

We have used Monte Carlo simulation techniques and published radial velocity surveys to constrain the frequency of very low-mass star (VLMS) and brown dwarf (BD) binary systems and their separation (a) distribution. Gaussian models for the separation distribution with a peak at a= 4au and 0.6 <=σlog(a/au)<= 1.0, correctly predict the number of observed binaries, yielding a close (a < 2.6au) binary frequency of 17-30 per cent and an overall VLMS/BD binary frequency of 32-45 per cent. We find that the available N-body models of VLMS/BD formation from dynamically decaying protostellar multiple systems are excluded at >99 per cent confidence because they predict too few close binary VLMS/BDs. The large number of close binaries and high overall binary frequency are also very inconsistent with recent smoothed particle hydrodynamical modelling and argue against a dynamical origin for VLMS/BDs.

Definition and classification of evaluation units for tertiary structure prediction in CASP12 facilitated through semi-automated metrics.

PubMed

Abriata, Luciano A; Kinch, Lisa N; Tamò, Giorgio E; Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Dal Peraro, Matteo

2018-03-01

For assessment purposes, CASP targets are split into evaluation units. We herein present the official definition of CASP12 evaluation units (EUs) and their classification into difficulty categories. Each target can be evaluated as one EU (the whole target) or/and several EUs (separate structural domains or groups of structural domains). The specific scenario for a target split is determined by the domain organization of available templates, the difference in server performance on separate domains versus combination of the domains, and visual inspection. In the end, 71 targets were split into 96 EUs. Classification of the EUs into difficulty categories was done semi-automatically with the assistance of metrics provided by the Prediction Center. These metrics account for sequence and structural similarities of the EUs to potential structural templates from the Protein Data Bank, and for the baseline performance of automated server predictions. The metrics readily separate the 96 EUs into 38 EUs that should be straightforward for template-based modeling (TBM) and 39 that are expected to be hard for homology modeling and are thus left for free modeling (FM). The remaining 19 borderline evaluation units were dubbed FM/TBM, and were inspected case by case. The article also overviews structural and evolutionary features of selected targets relevant to our accompanying article presenting the assessment of FM and FM/TBM predictions, and overviews structural features of the hardest evaluation units from the FM category. We finally suggest improvements for the EU definition and classification procedures. © 2017 Wiley Periodicals, Inc.

Data assimilation for groundwater flow modelling using Unbiased Ensemble Square Root Filter: Case study in Guantao, North China Plain

NASA Astrophysics Data System (ADS)

Li, N.; Kinzelbach, W.; Li, H.; Li, W.; Chen, F.; Wang, L.

2017-12-01

Data assimilation techniques are widely used in hydrology to improve the reliability of hydrological models and to reduce model predictive uncertainties. This provides critical information for decision makers in water resources management. This study aims to evaluate a data assimilation system for the Guantao groundwater flow model coupled with a one-dimensional soil column simulation (Hydrus 1D) using an Unbiased Ensemble Square Root Filter (UnEnSRF) originating from the Ensemble Kalman Filter (EnKF) to update parameters and states, separately or simultaneously. To simplify the coupling between unsaturated and saturated zone, a linear relationship obtained from analyzing inputs to and outputs from Hydrus 1D is applied in the data assimilation process. Unlike EnKF, the UnEnSRF updates parameter ensemble mean and ensemble perturbations separately. In order to keep the ensemble filter working well during the data assimilation, two factors are introduced in the study. One is called damping factor to dampen the update amplitude of the posterior ensemble mean to avoid nonrealistic values. The other is called inflation factor to relax the posterior ensemble perturbations close to prior to avoid filter inbreeding problems. The sensitivities of the two factors are studied and their favorable values for the Guantao model are determined. The appropriate observation error and ensemble size were also determined to facilitate the further analysis. This study demonstrated that the data assimilation of both model parameters and states gives a smaller model prediction error but with larger uncertainty while the data assimilation of only model states provides a smaller predictive uncertainty but with a larger model prediction error. Data assimilation in a groundwater flow model will improve model prediction and at the same time make the model converge to the true parameters, which provides a successful base for applications in real time modelling or real time controlling strategies in groundwater resources management.

Supersonic Pitch Damping Predictions of Blunt Entry Vehicles from Static CFD Solutions

NASA Technical Reports Server (NTRS)

Schoenenberger, Mark

2013-01-01

A technique for predicting supersonic pitch damping of blunt axisymmetric bodies from static CFD data is presented. The contributions to static pitching moment due to forebody and aftbody pressure distributions are broken out and considered separately. The one-dimension moment equation is cast to model the separate contributions from forebody and aftbody pressures with no traditional damping term included. The aftbody contribution to pitching moment is lagged by a phase angle of the natural oscillation period. This lag represents the time for aftbody wake structures to equilibrate while the body is oscillation. The characteristic equation of this formulation indicates that the lagged backshell moment adds a damping moment equivalent in form to a constant pitch damping term. CFD calculations of the backshell's contribution to the static pitching moment for a range of angles-of-attack is used to predict pitch damping coefficients. These predictions are compared with ballistic range data taken of the Mars Exploration Rover (MER) capsule and forced oscillation data of the Mars Viking capsule. The lag model appears to capture dynamic stability variation due to backshell geometry as well as Mach number.

Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity

PubMed Central

Chavlis, Spyridon; Petrantonakis, Panagiotis C.

2016-01-01

ABSTRACT The hippocampus plays a key role in pattern separation, the process of transforming similar incoming information to highly dissimilar, nonverlapping representations. Sparse firing granule cells (GCs) in the dentate gyrus (DG) have been proposed to undertake this computation, but little is known about which of their properties influence pattern separation. Dendritic atrophy has been reported in diseases associated with pattern separation deficits, suggesting a possible role for dendrites in this phenomenon. To investigate whether and how the dendrites of GCs contribute to pattern separation, we build a simplified, biologically relevant, computational model of the DG. Our model suggests that the presence of GC dendrites is associated with high pattern separation efficiency while their atrophy leads to increased excitability and performance impairments. These impairments can be rescued by restoring GC sparsity to control levels through various manipulations. We predict that dendrites contribute to pattern separation as a mechanism for controlling sparsity. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27784124

Cosmological velocity correlations - Observations and model predictions

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.; Davis, Marc; Strauss, Michael A.; White, Simon D. M.; Yahil, Amos

1989-01-01

By applying the present simple statistics for two-point cosmological peculiar velocity-correlation measurements to the actual data sets of the Local Supercluster spiral galaxy of Aaronson et al. (1982) and the elliptical galaxy sample of Burstein et al. (1987), as well as to the velocity field predicted by the distribution of IRAS galaxies, a coherence length of 1100-1600 km/sec is obtained. Coherence length is defined as that separation at which the correlations drop to half their zero-lag value. These results are compared with predictions from two models of large-scale structure formation: that of cold dark matter and that of baryon isocurvature proposed by Peebles (1980). N-body simulations of these models are performed to check the linear theory predictions and measure sampling fluctuations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, H.L.; Spronsen, G. van; Klaus, E.H.

A simulation model of the dynamics of a by-pass pig and related two-phase flow behavior along with field trials of the pig in a dry-gas pipeline have revealed significant gains in use of a by-pass pig in modifying gas and liquid production rates. The method can widen the possibility of applying two-phase flow pipeline transportation to cases in which separator or slug-catcher capacity is limited by practicality or cost. Pigging two-phase pipelines normally generates large liquid slug volumes in front of the pig. These require large separators or slug catchers. Using a high by-pass pig to disperse the liquid andmore » reduce the maximum liquid production rate before pig arrival has been investigated by Shell Exploration and Production companies. A simulation model of the dynamics of the pig and related two-phase flow behavior in the pipeline was used to predict the performance of by-pass pigs. Field trials in a dry-gas pipeline were carried out to provide friction data and to validate the model. The predicted mobility of the high by-pass pig in the pipeline and risers was verified and the beneficial effects due to the by-pass concept exceeded the prediction of the simplified model.« less

Automated red blood cells extraction from holographic images using fully convolutional neural networks.

PubMed

Yi, Faliu; Moon, Inkyu; Javidi, Bahram

2017-10-01

In this paper, we present two models for automatically extracting red blood cells (RBCs) from RBCs holographic images based on a deep learning fully convolutional neural network (FCN) algorithm. The first model, called FCN-1, only uses the FCN algorithm to carry out RBCs prediction, whereas the second model, called FCN-2, combines the FCN approach with the marker-controlled watershed transform segmentation scheme to achieve RBCs extraction. Both models achieve good segmentation accuracy. In addition, the second model has much better performance in terms of cell separation than traditional segmentation methods. In the proposed methods, the RBCs phase images are first numerically reconstructed from RBCs holograms recorded with off-axis digital holographic microscopy. Then, some RBCs phase images are manually segmented and used as training data to fine-tune the FCN. Finally, each pixel in new input RBCs phase images is predicted into either foreground or background using the trained FCN models. The RBCs prediction result from the first model is the final segmentation result, whereas the result from the second model is used as the internal markers of the marker-controlled transform algorithm for further segmentation. Experimental results show that the given schemes can automatically extract RBCs from RBCs phase images and much better RBCs separation results are obtained when the FCN technique is combined with the marker-controlled watershed segmentation algorithm.

A Volume-Fraction Based Two-Phase Constitutive Model for Blood

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Rui; Massoudi, Mehrdad; Hund, S.J.

2008-06-01

Mechanically-induced blood trauma such as hemolysis and thrombosis often occurs at microscopic channels, steps and crevices within cardiovascular devices. A predictive mathematical model based on a broad understanding of hemodynamics at micro scale is needed to mitigate these effects, and is the motivation of this research project. Platelet transport and surface deposition is important in thrombosis. Microfluidic experiments have previously revealed a significant impact of red blood cell (RBC)-plasma phase separation on platelet transport [5], whereby platelet localized concentration can be enhanced due to a non-uniform distribution of RBCs of blood flow in a capillary tube and sudden expansion. However,more » current platelet deposition models either totally ignored RBCs in the fluid by assuming a zero sample hematocrit or treated them as being evenly distributed. As a result, those models often underestimated platelet advection and deposition to certain areas [2]. The current study aims to develop a two-phase blood constitutive model that can predict phase separation in a RBC-plasma mixture at the micro scale. The model is based on a sophisticated theory known as theory of interacting continua, i.e., mixture theory. The volume fraction is treated as a field variable in this model, which allows the prediction of concentration as well as velocity profiles of both RBC and plasma phases. The results will be used as the input of successive platelet deposition models.« less

Automated red blood cells extraction from holographic images using fully convolutional neural networks

PubMed Central

Yi, Faliu; Moon, Inkyu; Javidi, Bahram

2017-01-01

In this paper, we present two models for automatically extracting red blood cells (RBCs) from RBCs holographic images based on a deep learning fully convolutional neural network (FCN) algorithm. The first model, called FCN-1, only uses the FCN algorithm to carry out RBCs prediction, whereas the second model, called FCN-2, combines the FCN approach with the marker-controlled watershed transform segmentation scheme to achieve RBCs extraction. Both models achieve good segmentation accuracy. In addition, the second model has much better performance in terms of cell separation than traditional segmentation methods. In the proposed methods, the RBCs phase images are first numerically reconstructed from RBCs holograms recorded with off-axis digital holographic microscopy. Then, some RBCs phase images are manually segmented and used as training data to fine-tune the FCN. Finally, each pixel in new input RBCs phase images is predicted into either foreground or background using the trained FCN models. The RBCs prediction result from the first model is the final segmentation result, whereas the result from the second model is used as the internal markers of the marker-controlled transform algorithm for further segmentation. Experimental results show that the given schemes can automatically extract RBCs from RBCs phase images and much better RBCs separation results are obtained when the FCN technique is combined with the marker-controlled watershed segmentation algorithm. PMID:29082078

Tropical forecasting - Predictability perspective

NASA Technical Reports Server (NTRS)

Shukla, J.

1989-01-01

Results are presented of classical predictability studies and forecast experiments with observed initial conditions to show the nature of initial error growth and final error equilibration for the tropics and midlatitudes, separately. It is found that the theoretical upper limit of tropical circulation predictability is far less than for midlatitudes. The error growth for a complete general circulation model is compared to a dry version of the same model in which there is no prognostic equation for moisture, and diabatic heat sources are prescribed. It is found that the growth rate of synoptic-scale errors for the dry model is significantly smaller than for the moist model, suggesting that the interactions between dynamics and moist processes are among the important causes of atmospheric flow predictability degradation. Results are then presented of numerical experiments showing that correct specification of the slowly varying boundary condition of SST produces significant improvement in the prediction of time-averaged circulation and rainfall over the tropics.

New utility for an old tool: can a simple gait speed test predict ambulatory surgical discharge outcomes?

PubMed

Odonkor, Charles A; Schonberger, Robert B; Dai, Feng; Shelley, Kirk H; Silverman, David G; Barash, Paul G

2013-10-01

The primary aims of this study were to design prediction models based on a functional marker (preoperative gait speed) to predict readiness for home discharge time of 90 mins or less and to identify those at risk for unplanned admissions after elective ambulatory surgery. This prospective observational cohort study evaluated all patients scheduled for elective ambulatory surgery. Home discharge readiness and unplanned admissions were the primary outcomes. Independent variables included preoperative gait speed, heart rate, and total anesthesia time. The relationship between all predictors and each primary outcome was determined in separate multivariable logistic regression models. After adjustment for covariates, gait speed with adjusted odds ratio of 3.71 (95% confidence interval, 1.21-11.26), P = 0.02, was independently associated with early home discharge readiness of 90 mins or less. Importantly, gait speed dichotomized as greater or less than 1 m/sec predicted unplanned admissions, with odds ratio of 0.35 (95% confidence interval, 0.16-0.76, P = 0.008) for those with speeds 1 m/sec or greater in comparison with those with speeds less than 1 m/sec. In a separate model, history of cardiac surgery with adjusted odds ratio of 7.5 (95% confidence interval, 2.34-24.41; P = 0.001) was independently associated with unplanned admissions after elective ambulatory surgery, when other covariates were held constant. This study demonstrates the use of novel prediction models based on gait speed testing to predict early home discharge and to identify those patients at risk for unplanned admissions after elective ambulatory surgery.

Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

NASA Technical Reports Server (NTRS)

Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette

2009-01-01

Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

New Utility for an Old Tool

PubMed Central

Odonkor, Charles A.; Schonberger, Robert B.; Dai, Feng; Shelley, Kirk H.; Silverman, David G.; Barash, Paul G.

2013-01-01

Objective The primary aim of this study was to design prediction models based on a functional marker (preoperative gait-speed) to predict readiness for home discharge time of ≤ 90 minutes, and to identify those at risk for unplanned admissions, after elective ambulatory surgery. Design This prospective observational cohort study evaluated all patients scheduled for elective ambulatory surgery. Home discharge readiness and unplanned admissions were the primary outcomes. Independent variables included preoperative gait speed, heart rate, and total anesthesia time. The relationship between all predictors and each primary outcome was determined in separate multivariable logistic regression models. Results After adjustment for covariates, gait speed with adjusted odds ratio = 3.71 (95% CI: 1.21-11.26), p=0.02; was independently associated with early home discharge readiness ≤90 minutes. Importantly, gait speed dichotomized as greater or less than 1 m/s predicted unplanned admissions with odds ratio = 0.35 (95% CI: 0.16 to 0.76, p=0.008) for those with speeds ≥ 1 m/s in comparison to those with speed < 1 m/s. In a separate model, prior history of cardiac surgery with adjusted odds ratio =7.5 (95% CI: 2.34-24.41)(p=0.001) was independently associated with unplanned admissions after elective ambulatory surgery, when other covariates were held constant. Conclusions This study demonstrates use of novel prediction models based on gait speed testing to predict early home discharge and to identify those patients at risk for unplanned admissions, after elective ambulatory surgery. PMID:24051992

Intercalation Dynamics in Lithium-Ion Batteries

DTIC Science & Technology

2009-09-01

When applied to strongly phase-separating, highly anisotropic materials such as LiFePO4 , this model predicts phase-transformation waves between the...new findings relevant to batteries: Defect Interactions: When applied to strongly phase-separating, highly anisotropic mate- rials such as LiFePO4 ...93 6.3.5 Relevance to LiFePO4 . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.3.6 Wave propagation

Investigation of Dispersed and Dispersed Annular (rivulet or Thin Film) Flow Phase Separation in Tees.

NASA Astrophysics Data System (ADS)

McCreery, Glenn Ernest

An experimental and analytical investigation of dispersed and dispersed-annular (rivulet or thin film) flow phase separation in tees has been successfully completed. The research was directed at, but is not specific to, determining flow conditions, following a loss of coolant accident, in the large rectangular passageways leading to vacuum buildings in the containment envelope of some CANDU nuclear reactors. The primary objectives of the research were to: (1) obtain experimental data to help formulate and test mechanistic analytical models of phase separation, and (2) develop the analytical models in computer programs which predict phase separation from upstream flow and pressure conditions and downstream and side branch pressure boundary conditions. To meet these objectives an air-water experimental apparatus was constructed, and consists of large air blowers attached to a long rectangular duct leading to a tee in the horizontal plane. A variety of phenomena was investigated including, for comparison with computer predictions, air streamlines and eddy boundary geometry, drop size spectra, macroscopic mass balances, liquid rivulet pathlines, and trajectories of drops of known size and velocity. Four separate computer programs were developed to analyze phase separation. Three of the programs are used sequentially to calculate dispersed mist phase separation in a tee. The fourth is used to calculate rivulet or thin film pathlines. Macroscopic mass balances are calculated from a summation of mass balances for drops with representative sizes (and masses) spaced across the drop size spectrum. The programs are tested against experimental data, and accurately predict gas flow fields, drop trajectories, rivulet pathlines and macroscopic mass balances. In addition to development of the computer programs, analysis was performed to specify the scaling of dispersed mist and rivulet or thin film flow, to investigate pressure losses in tees, and the inter-relationship of loss coefficients, contraction coefficients, and eddy geometry. The important transient effects of liquid storage in eddies were also analyzed.

PredictABEL: an R package for the assessment of risk prediction models.

PubMed

Kundu, Suman; Aulchenko, Yurii S; van Duijn, Cornelia M; Janssens, A Cecile J W

2011-04-01

The rapid identification of genetic markers for multifactorial diseases from genome-wide association studies is fuelling interest in investigating the predictive ability and health care utility of genetic risk models. Various measures are available for the assessment of risk prediction models, each addressing a different aspect of performance and utility. We developed PredictABEL, a package in R that covers descriptive tables, measures and figures that are used in the analysis of risk prediction studies such as measures of model fit, predictive ability and clinical utility, and risk distributions, calibration plot and the receiver operating characteristic plot. Tables and figures are saved as separate files in a user-specified format, which include publication-quality EPS and TIFF formats. All figures are available in a ready-made layout, but they can be customized to the preferences of the user. The package has been developed for the analysis of genetic risk prediction studies, but can also be used for studies that only include non-genetic risk factors. PredictABEL is freely available at the websites of GenABEL ( http://www.genabel.org ) and CRAN ( http://cran.r-project.org/).

Boundary-layer computational model for predicting the flow and heat transfer in sudden expansions

NASA Technical Reports Server (NTRS)

Lewis, J. P.; Pletcher, R. H.

1986-01-01

Fully developed turbulent and laminar flows through symmetric planar and axisymmetric expansions with heat transfer were modeled using a finite-difference discretization of the boundary-layer equations. By using the boundary-layer equations to model separated flow in place of the Navier-Stokes equations, computational effort was reduced permitting turbulence modelling studies to be economically carried out. For laminar flow, the reattachment length was well predicted for Reynolds numbers as low as 20 and the details of the trapped eddy were well predicted for Reynolds numbers above 200. For turbulent flows, the Boussinesq assumption was used to express the Reynolds stresses in terms of a turbulent viscosity. Near-wall algebraic turbulence models based on Prandtl's-mixing-length model and the maximum Reynolds shear stress were compared.

Separating foliar physiology from morphology reveals the relative roles of vertically structured transpiration factors within red maple crowns and limitations of larger scale models

PubMed Central

Bauerle, William L.; Bowden, Joseph D.

2011-01-01

A spatially explicit mechanistic model, MAESTRA, was used to separate key parameters affecting transpiration to provide insights into the most influential parameters for accurate predictions of within-crown and within-canopy transpiration. Once validated among Acer rubrum L. genotypes, model responses to different parameterization scenarios were scaled up to stand transpiration (expressed per unit leaf area) to assess how transpiration might be affected by the spatial distribution of foliage properties. For example, when physiological differences were accounted for, differences in leaf width among A. rubrum L. genotypes resulted in a 25% difference in transpiration. An in silico within-canopy sensitivity analysis was conducted over the range of genotype parameter variation observed and under different climate forcing conditions. The analysis revealed that seven of 16 leaf traits had a ≥5% impact on transpiration predictions. Under sparse foliage conditions, comparisons of the present findings with previous studies were in agreement that parameters such as the maximum Rubisco-limited rate of photosynthesis can explain ∼20% of the variability in predicted transpiration. However, the spatial analysis shows how such parameters can decrease or change in importance below the uppermost canopy layer. Alternatively, model sensitivity to leaf width and minimum stomatal conductance was continuous along a vertical canopy depth profile. Foremost, transpiration sensitivity to an observed range of morphological and physiological parameters is examined and the spatial sensitivity of transpiration model predictions to vertical variations in microclimate and foliage density is identified to reduce the uncertainty of current transpiration predictions. PMID:21617246

Comparison of experimental surface pressures with theoretical predictions on twin two-dimensional convergent-divergent nozzles

NASA Technical Reports Server (NTRS)

Carlson, J. R.; Pendergraft, O. C., Jr.; Burley, J. R., II

1986-01-01

A three-dimensional subsonic aerodynamic panel code (VSAERO) was used to predict the effects of upper and lower external nozzle flap geometry on the external afterbody/nozzle pressure coefficient distributions and external nozzle drag of nonaxisymmetric convergent-divergent exhaust nozzles having parallel external sidewalls installed on a generic twin-engine high performance aircraft model. Nozzle static pressure coefficient distributions along the upper and lower surfaces near the model centerline and near the outer edges (corner) of the two surfaces were calculated, and nozzle drag was predicted using these surface pressure distributions. A comparison between the theoretical predictions and experimental wind tunnel data is made to evaluate the utility of the code in calculating the flow about these types of non-axisymmetric afterbody configurations. For free-stream Mach numbers of 0.60 and 0.90, the conditions where the flows were attached on the boattails yielded the best comparison between the theoretical predictions and the experimental data. For the Boattail terminal angles of greater than 15 deg., the experimental data for M = 0.60 and 0.90 indicated areas of separated flow, so the theoretical predictions failed to match the experimental data. Even though calculations of regions of separated flows are within the capabilities of the theoretical method, acceptable solutions were not obtained.

Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

PubMed Central

Nilsaz-Dezfouli, Hamid; Abu-Bakar, Mohd Rizam; Arasan, Jayanthi; Adam, Mohd Bakri; Pourhoseingholi, Mohamad Amin

2017-01-01

In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve. PMID:28469384

A simple transferable adaptive potential to study phase separation in large-scale xMgO-(1-x)SiO2 binary glasses.

PubMed

Bidault, Xavier; Chaussedent, Stéphane; Blanc, Wilfried

2015-10-21

A simple transferable adaptive model is developed and it allows for the first time to simulate by molecular dynamics the separation of large phases in the MgO-SiO2 binary system, as experimentally observed and as predicted by the phase diagram, meaning that separated phases have various compositions. This is a real improvement over fixed-charge models, which are often limited to an interpretation involving the formation of pure clusters, or involving the modified random network model. Our adaptive model, efficient to reproduce known crystalline and glassy structures, allows us to track the formation of large amorphous Mg-rich Si-poor nanoparticles in an Mg-poor Si-rich matrix from a 0.1MgO-0.9SiO2 melt.

Bubbles in Sediments

DTIC Science & Technology

1998-09-30

model (simplest) to a fluid saturated poroelastic model (most complex). Based on the results of the theoretical treatment, a laboratory experiment has...are widely separated for each model . Finally, if a sediment is modeled by Biot theory, which describes wave propagation in a saturated poroelastic ...application of Biot theory to sediment acoustics . The predicted resonance behavior under each model is distinct, so an optical extinction measurement may

Comparative Study on the Prediction of Aerodynamic Characteristics of Aircraft with Turbulence Models

NASA Astrophysics Data System (ADS)

Jang, Yujin; Huh, Jinbum; Lee, Namhun; Lee, Seungsoo; Park, Youngmin

2018-04-01

The RANS equations are widely used to analyze complex flows over aircraft. The equations require a turbulence model for turbulent flow analyses. A suitable turbulence must be selected for accurate predictions of aircraft aerodynamic characteristics. In this study, numerical analyses of three-dimensional aircraft are performed to compare the results of various turbulence models for the prediction of aircraft aerodynamic characteristics. A 3-D RANS solver, MSAPv, is used for the aerodynamic analysis. The four turbulence models compared are the Sparlart-Allmaras (SA) model, Coakley's q-ω model, Huang and Coakley's k-ɛ model, and Menter's k-ω SST model. Four aircrafts are considered: an ARA-M100, DLR-F6 wing-body, DLR-F6 wing-body-nacelle-pylon from the second drag prediction workshop, and a high wing aircraft with nacelles. The CFD results are compared with experimental data and other published computational results. The details of separation patterns, shock positions, and Cp distributions are discussed to find the characteristics of the turbulence models.

Linear separability in superordinate natural language concepts.

PubMed

Ruts, Wim; Storms, Gert; Hampton, James

2004-01-01

Two experiments are reported in which linear separability was investigated in superordinate natural language concept pairs (e.g., toiletry-sewing gear). Representations of the exemplars of semantically related concept pairs were derived in two to five dimensions using multidimensional scaling (MDS) of similarities based on possession of the concept features. Next, category membership, obtained from an exemplar generation study (in Experiment 1) and from a forced-choice classification task (in Experiment 2) was predicted from the coordinates of the MDS representation using log linear analysis. The results showed that all natural kind concept pairs were perfectly linearly separable, whereas artifact concept pairs showed several violations. Clear linear separability of natural language concept pairs is in line with independent cue models. The violations in the artifact pairs, however, yield clear evidence against the independent cue models.

Predicting age groups of Twitter users based on language and metadata features

PubMed Central

Morgan-Lopez, Antonio A.; Chew, Robert F.; Ruddle, Paul

2017-01-01

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of social media education campaigns. The main objective of this study was to examine the separate and joint predictive validity of linguistic and metadata features in predicting the age of Twitter users. We created a labeled dataset of Twitter users across different age groups (youth, young adults, adults) by collecting publicly available birthday announcement tweets using the Twitter Search application programming interface. We manually reviewed results and, for each age-labeled handle, collected the 200 most recent publicly available tweets and user handles’ metadata. The labeled data were split into training and test datasets. We created separate models to examine the predictive validity of language features only, metadata features only, language and metadata features, and words/phrases from another age-validated dataset. We estimated accuracy, precision, recall, and F1 metrics for each model. An L1-regularized logistic regression model was conducted for each age group, and predicted probabilities between the training and test sets were compared for each age group. Cohen’s d effect sizes were calculated to examine the relative importance of significant features. Models containing both Tweet language features and metadata features performed the best (74% precision, 74% recall, 74% F1) while the model containing only Twitter metadata features were least accurate (58% precision, 60% recall, and 57% F1 score). Top predictive features included use of terms such as “school” for youth and “college” for young adults. Overall, it was more challenging to predict older adults accurately. These results suggest that examining linguistic and Twitter metadata features to predict youth and young adult Twitter users may be helpful for informing public health surveillance and evaluation research. PMID:28850620

Predicting age groups of Twitter users based on language and metadata features.

PubMed

Morgan-Lopez, Antonio A; Kim, Annice E; Chew, Robert F; Ruddle, Paul

2017-01-01

Health organizations are increasingly using social media, such as Twitter, to disseminate health messages to target audiences. Determining the extent to which the target audience (e.g., age groups) was reached is critical to evaluating the impact of social media education campaigns. The main objective of this study was to examine the separate and joint predictive validity of linguistic and metadata features in predicting the age of Twitter users. We created a labeled dataset of Twitter users across different age groups (youth, young adults, adults) by collecting publicly available birthday announcement tweets using the Twitter Search application programming interface. We manually reviewed results and, for each age-labeled handle, collected the 200 most recent publicly available tweets and user handles' metadata. The labeled data were split into training and test datasets. We created separate models to examine the predictive validity of language features only, metadata features only, language and metadata features, and words/phrases from another age-validated dataset. We estimated accuracy, precision, recall, and F1 metrics for each model. An L1-regularized logistic regression model was conducted for each age group, and predicted probabilities between the training and test sets were compared for each age group. Cohen's d effect sizes were calculated to examine the relative importance of significant features. Models containing both Tweet language features and metadata features performed the best (74% precision, 74% recall, 74% F1) while the model containing only Twitter metadata features were least accurate (58% precision, 60% recall, and 57% F1 score). Top predictive features included use of terms such as "school" for youth and "college" for young adults. Overall, it was more challenging to predict older adults accurately. These results suggest that examining linguistic and Twitter metadata features to predict youth and young adult Twitter users may be helpful for informing public health surveillance and evaluation research.

A theory and model of conflict detection in air traffic control: incorporating environmental constraints.

PubMed

Loft, Shayne; Bolland, Scott; Humphreys, Michael S; Neal, Andrew

2009-06-01

A performance theory for conflict detection in air traffic control is presented that specifies how controllers adapt decisions to compensate for environmental constraints. This theory is then used as a framework for a model that can fit controller intervention decisions. The performance theory proposes that controllers apply safety margins to ensure separation between aircraft. These safety margins are formed through experience and reflect the biasing of decisions to favor safety over accuracy, as well as expectations regarding uncertainty in aircraft trajectory. In 2 experiments, controllers indicated whether they would intervene to ensure separation between pairs of aircraft. The model closely predicted the probability of controller intervention across the geometry of problems and as a function of controller experience. When controller safety margins were manipulated via task instructions, the parameters of the model changed in the predicted direction. The strength of the model over existing and alternative models is that it better captures the uncertainty and decision biases involved in the process of conflict detection. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Configuration and validation of an analytical model predicting secondary neutron radiation in proton therapy using Monte Carlo simulations and experimental measurements.

PubMed

Farah, J; Bonfrate, A; De Marzi, L; De Oliveira, A; Delacroix, S; Martinetti, F; Trompier, F; Clairand, I

2015-05-01

This study focuses on the configuration and validation of an analytical model predicting leakage neutron doses in proton therapy. Using Monte Carlo (MC) calculations, a facility-specific analytical model was built to reproduce out-of-field neutron doses while separately accounting for the contribution of intra-nuclear cascade, evaporation, epithermal and thermal neutrons. This model was first trained to reproduce in-water neutron absorbed doses and in-air neutron ambient dose equivalents, H*(10), calculated using MCNPX. Its capacity in predicting out-of-field doses at any position not involved in the training phase was also checked. The model was next expanded to enable a full 3D mapping of H*(10) inside the treatment room, tested in a clinically relevant configuration and finally consolidated with experimental measurements. Following the literature approach, the work first proved that it is possible to build a facility-specific analytical model that efficiently reproduces in-water neutron doses and in-air H*(10) values with a maximum difference less than 25%. In addition, the analytical model succeeded in predicting out-of-field neutron doses in the lateral and vertical direction. Testing the analytical model in clinical configurations proved the need to separate the contribution of internal and external neutrons. The impact of modulation width on stray neutrons was found to be easily adjustable while beam collimation remains a challenging issue. Finally, the model performance agreed with experimental measurements with satisfactory results considering measurement and simulation uncertainties. Analytical models represent a promising solution that substitutes for time-consuming MC calculations when assessing doses to healthy organs. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

QSAR models for thiophene and imidazopyridine derivatives inhibitors of the Polo-Like Kinase 1.

PubMed

Comelli, Nieves C; Duchowicz, Pablo R; Castro, Eduardo A

2014-10-01

The inhibitory activity of 103 thiophene and 33 imidazopyridine derivatives against Polo-Like Kinase 1 (PLK1) expressed as pIC50 (-logIC50) was predicted by QSAR modeling. Multivariate linear regression (MLR) was employed to model the relationship between 0D and 3D molecular descriptors and biological activities of molecules using the replacement method (MR) as variable selection tool. The 136 compounds were separated into several training and test sets. Two splitting approaches, distribution of biological data and structural diversity, and the statistical experimental design procedure D-optimal distance were applied to the dataset. The significance of the training set models was confirmed by statistically higher values of the internal leave one out cross-validated coefficient of determination (Q2) and external predictive coefficient of determination for the test set (Rtest2). The model developed from a training set, obtained with the D-optimal distance protocol and using 3D descriptor space along with activity values, separated chemical features that allowed to distinguish high and low pIC50 values reasonably well. Then, we verified that such model was sufficient to reliably and accurately predict the activity of external diverse structures. The model robustness was properly characterized by means of standard procedures and their applicability domain (AD) was analyzed by leverage method. Copyright © 2014 Elsevier B.V. All rights reserved.

Several examples where turbulence models fail in inlet flow field analysis

NASA Technical Reports Server (NTRS)

Anderson, Bernhard H.

1993-01-01

Computational uncertainties in turbulence modeling for three dimensional inlet flow fields include flows approaching separation, strength of secondary flow field, three dimensional flow predictions of vortex liftoff, and influence of vortex-boundary layer interactions; computational uncertainties in vortex generator modeling include representation of generator vorticity field and the relationship between generator and vorticity field. The objectives of the inlet flow field studies presented in this document are to advance the understanding, prediction, and control of intake distortion and to study the basic interactions that influence this design problem.

Quantitative structure-retention relationships applied to development of liquid chromatography gradient-elution method for the separation of sartans.

PubMed

Golubović, Jelena; Protić, Ana; Otašević, Biljana; Zečević, Mira

2016-04-01

QSRR are mathematically derived relationships between the chromatographic parameters determined for a representative series of analytes in given separation systems and the molecular descriptors accounting for the structural differences among the investigated analytes. Artificial neural network is a technique of data analysis, which sets out to emulate the human brain's way of working. The aim of the present work was to optimize separation of six angiotensin receptor antagonists, so-called sartans: losartan, valsartan, irbesartan, telmisartan, candesartan cilexetil and eprosartan in a gradient-elution HPLC method. For this purpose, ANN as a mathematical tool was used for establishing a QSRR model based on molecular descriptors of sartans and varied instrumental conditions. The optimized model can be further used for prediction of an external congener of sartans and analysis of the influence of the analyte structure, represented through molecular descriptors, on retention behaviour. Molecular descriptors included in modelling were electrostatic, geometrical and quantum-chemical descriptors: connolly solvent excluded volume non-1,4 van der Waals energy, octanol/water distribution coefficient, polarizability, number of proton-donor sites and number of proton-acceptor sites. Varied instrumental conditions were gradient time, buffer pH and buffer molarity. High prediction ability of the optimized network enabled complete separation of the analytes within the run time of 15.5 min under following conditions: gradient time of 12.5 min, buffer pH of 3.95 and buffer molarity of 25 mM. Applied methodology showed the potential to predict retention behaviour of an external analyte with the properties within the training space. Connolly solvent excluded volume, polarizability and number of proton-acceptor sites appeared to be most influential paramateres on retention behaviour of the sartans. Copyright © 2015 Elsevier B.V. All rights reserved.

Evidence of common and separate eye and hand accumulators underlying flexible eye-hand coordination

PubMed Central

Jana, Sumitash; Gopal, Atul

2016-01-01

Eye and hand movements are initiated by anatomically separate regions in the brain, and yet these movements can be flexibly coupled and decoupled, depending on the need. The computational architecture that enables this flexible coupling of independent effectors is not understood. Here, we studied the computational architecture that enables flexible eye-hand coordination using a drift diffusion framework, which predicts that the variability of the reaction time (RT) distribution scales with its mean. We show that a common stochastic accumulator to threshold, followed by a noisy effector-dependent delay, explains eye-hand RT distributions and their correlation in a visual search task that required decision-making, while an interactive eye and hand accumulator model did not. In contrast, in an eye-hand dual task, an interactive model better predicted the observed correlations and RT distributions than a common accumulator model. Notably, these two models could only be distinguished on the basis of the variability and not the means of the predicted RT distributions. Additionally, signatures of separate initiation signals were also observed in a small fraction of trials in the visual search task, implying that these distinct computational architectures were not a manifestation of the task design per se. Taken together, our results suggest two unique computational architectures for eye-hand coordination, with task context biasing the brain toward instantiating one of the two architectures. NEW & NOTEWORTHY Previous studies on eye-hand coordination have considered mainly the means of eye and hand reaction time (RT) distributions. Here, we leverage the approximately linear relationship between the mean and standard deviation of RT distributions, as predicted by the drift-diffusion model, to propose the existence of two distinct computational architectures underlying coordinated eye-hand movements. These architectures, for the first time, provide a computational basis for the flexible coupling between eye and hand movements. PMID:27784809

CFD Sensitivity Analysis of a Modern Civil Transport Near Buffet-Onset Conditions

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Allison, Dennis O.; Biedron, Robert T.; Buning, Pieter G.; Gainer, Thomas G.; Morrison, Joseph H.; Rivers, S. Melissa; Mysko, Stephen J.; Witkowski, David P.

2001-01-01

A computational fluid dynamics (CFD) sensitivity analysis is conducted for a modern civil transport at several conditions ranging from mostly attached flow to flow with substantial separation. Two different Navier-Stokes computer codes and four different turbulence models are utilized, and results are compared both to wind tunnel data at flight Reynolds number and flight data. In-depth CFD sensitivities to grid, code, spatial differencing method, aeroelastic shape, and turbulence model are described for conditions near buffet onset (a condition at which significant separation exists). In summary, given a grid of sufficient density for a given aeroelastic wing shape, the combined approximate error band in CFD at conditions near buffet onset due to code, spatial differencing method, and turbulence model is: 6% in lift, 7% in drag, and 16% in moment. The biggest two contributers to this uncertainty are turbulence model and code. Computed results agree well with wind tunnel surface pressure measurements both for an overspeed 'cruise' case as well as a case with small trailing edge separation. At and beyond buffet onset, computed results agree well over the inner half of the wing, but shock location is predicted too far aft at some of the outboard stations. Lift, drag, and moment curves are predicted in good agreement with experimental results from the wind tunnel.

Firmness prediction in Prunus persica 'Calrico' peaches by visible/short-wave near infrared spectroscopy and acoustic measurements using optimised linear and non-linear chemometric models.

PubMed

Lafuente, Victoria; Herrera, Luis J; Pérez, María del Mar; Val, Jesús; Negueruela, Ignacio

2015-08-15

In this work, near infrared spectroscopy (NIR) and an acoustic measure (AWETA) (two non-destructive methods) were applied in Prunus persica fruit 'Calrico' (n = 260) to predict Magness-Taylor (MT) firmness. Separate and combined use of these measures was evaluated and compared using partial least squares (PLS) and least squares support vector machine (LS-SVM) regression methods. Also, a mutual-information-based variable selection method, seeking to find the most significant variables to produce optimal accuracy of the regression models, was applied to a joint set of variables (NIR wavelengths and AWETA measure). The newly proposed combined NIR-AWETA model gave good values of the determination coefficient (R(2)) for PLS and LS-SVM methods (0.77 and 0.78, respectively), improving the reliability of MT firmness prediction in comparison with separate NIR and AWETA predictions. The three variables selected by the variable selection method (AWETA measure plus NIR wavelengths 675 and 697 nm) achieved R(2) values 0.76 and 0.77, PLS and LS-SVM. These results indicated that the proposed mutual-information-based variable selection algorithm was a powerful tool for the selection of the most relevant variables. © 2014 Society of Chemical Industry.

Statistical Models for Predicting Automobile Driving Postures for Men and Women Including Effects of Age.

PubMed

Park, Jangwoon; Ebert, Sheila M; Reed, Matthew P; Hallman, Jason J

2016-03-01

Previously published statistical models of driving posture have been effective for vehicle design but have not taken into account the effects of age. The present study developed new statistical models for predicting driving posture. Driving postures of 90 U.S. drivers with a wide range of age and body size were measured in laboratory mockup in nine package conditions. Posture-prediction models for female and male drivers were separately developed by employing a stepwise regression technique using age, body dimensions, vehicle package conditions, and two-way interactions, among other variables. Driving posture was significantly associated with age, and the effects of other variables depended on age. A set of posture-prediction models is presented for women and men. The results are compared with a previously developed model. The present study is the first study of driver posture to include a large cohort of older drivers and the first to report a significant effect of age. The posture-prediction models can be used to position computational human models or crash-test dummies for vehicle design and assessment. © 2015, Human Factors and Ergonomics Society.

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra.

PubMed

Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

2015-01-01

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l'Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the 'upland model' was able to more accurately predict SOC compared with the 'upland & wetland model'. However, the separately calibrated 'upland and wetland model' did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM).

Investigation of spray characteristics for flashing injection of fuels containing dissolved air and superheated fuels

NASA Technical Reports Server (NTRS)

Solomon, A. S. P.; Chen, L. D.; Faeth, G. M.

1982-01-01

The flow, atomization and spreading of flashing injector flowing liquids containing dissolved gases (jet/air) as well as superheated liquids (Freon II) were considered. The use of a two stage expansion process separated by an expansion chamber, ws found to be beneficial for flashing injection particularly for dissolved gas systems. Both locally homogeneous and separated flow models provided good predictions of injector flow properties. Conventional correlations for drop sizes from pressure atomized and airblast injectors were successfully modified, using the separated flow model to prescribe injector exit conditions, to correlate drop size measurements. Additional experimental results are provided for spray angle and combustion properties of sprays from flashing injectors.

Simulations of a Liquid Hydrogen Inducer at Low-Flow Off-Design Flow Conditions

NASA Technical Reports Server (NTRS)

Hosangadi, A.; Ahuja, V.; Ungewitter, R. J.

2005-01-01

The ability to accurately model details of inlet back flow for inducers operating a t low-flow, off-design conditions is evaluated. A sub-scale version of a three-bladed liquid hydrogen inducer tested in water with detailed velocity and pressure measurements is used as a numerical test bed. Under low-flow, off-design conditions the length of the separation zone as well as the swirl velocity magnitude was under predicted with a standard k-E model. When the turbulent viscosity coefficient was reduced good comparison was obtained a t all the flow conditions examined with both the magnitude and shape of the profile matching well with the experimental data taken half a diameter upstream of the leading edge. The velocity profiles and incidence angles a t the leading edge itself were less sensitive to the back flow length predictions indicating that single-phase performance predictions may be well predicted even if the details of flow separation modeled are incorrect. However, for cavitating flow situations the prediction of the correct swirl in the back flow and the pressure depression in the core becomes critical since it leads to vapor formation. The simulations have been performed using the CRUNCH CFD(Registered Trademark) code that has a generalized multi-element unstructured framework and a n advanced multi-phase formulation for cryogenic fluids. The framework has been validated rigorously for predictions of temperature and pressure depression in cryogenic fluid cavities and has also been shown to predict the cavitation breakdown point for inducers a t design conditions.

Person-Environment Congruence and Personality Domains in the Prediction of Job Performance and Work Quality

ERIC Educational Resources Information Center

Kieffer, Kevin M.; Schinka, John A.; Curtiss, Glenn

2004-01-01

This study examined the contributions of the 5-Factor Model (FFM; P. T. Costa & R. R. McCrae, 1992) and RIASEC (J. L. Holland, 1994) constructs of consistency, differentiation, and person-environment congruence in predicting job performance ratings in a large sample (N = 514) of employees. Hierarchical regression analyses conducted separately by…

Predicting Binge Drinking in College Students: Rational Beliefs, Stress, or Loneliness?

ERIC Educational Resources Information Center

Chen, Yixin; Feeley, Thomas Hugh

2015-01-01

We proposed a conceptual model to predict binge-drinking behavior among college students, based on the theory of planned behavior and the stress-coping hypothesis. A two-wave online survey was conducted with predictors and drinking behavior measured separately over 2 weeks' time. In the Wave 1 survey, 279 students at a public university in the…

DSMC computations of hypersonic flow separation and re-attachment in the transition to continuum regime

NASA Astrophysics Data System (ADS)

Prakash, Ram; Gai, Sudhir L.; O'Byrne, Sean; Brown, Melrose

2016-11-01

The flow over a `tick' shaped configuration is performed using two Direct Simulation Monte Carlo codes: the DS2V code of Bird and the code from Sandia National Laboratory, called SPARTA. The configuration creates a flow field, where the flow is expanded initially but then is affected by the adverse pressure gradient induced by a compression surface. The flow field is challenging in the sense that the full flow domain is comprised of localized areas spanning continuum and transitional regimes. The present work focuses on the capability of SPARTA to model such flow conditions and also towards a comparative evaluation with results from DS2V. An extensive grid adaptation study is performed using both the codes on a model with a sharp leading edge and the converged results are then compared. The computational predictions are evaluated in terms of surface parameters such as heat flux, shear stress, pressure and velocity slip. SPARTA consistently predicts higher values for these surface properties. The skin friction predictions of both the codes don't give any indication of separation but the velocity slip plots indicate an incipient separation behavior at the corner. The differences in the results are attributed towards the flow resolution at the leading edge that dictates the downstream flow characteristics.

Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds

USGS Publications Warehouse

O'Connell, Allan F.; Gardner, Beth; Oppel, Steffen; Meirinho, Ana; Ramírez, Iván; Miller, Peter I.; Louzao, Maite

2012-01-01

Knowledge about the spatial distribution of seabirds at sea is important for conservation. During marine conservation planning, logistical constraints preclude seabird surveys covering the complete area of interest and spatial distribution of seabirds is frequently inferred from predictive statistical models. Increasingly complex models are available to relate the distribution and abundance of pelagic seabirds to environmental variables, but a comparison of their usefulness for delineating protected areas for seabirds is lacking. Here we compare the performance of five modelling techniques (generalised linear models, generalised additive models, Random Forest, boosted regression trees, and maximum entropy) to predict the distribution of Balearic Shearwaters (Puffinus mauretanicus) along the coast of the western Iberian Peninsula. We used ship transect data from 2004 to 2009 and 13 environmental variables to predict occurrence and density, and evaluated predictive performance of all models using spatially segregated test data. Predicted distribution varied among the different models, although predictive performance varied little. An ensemble prediction that combined results from all five techniques was robust and confirmed the existence of marine important bird areas for Balearic Shearwaters in Portugal and Spain. Our predictions suggested additional areas that would be of high priority for conservation and could be proposed as protected areas. Abundance data were extremely difficult to predict, and none of five modelling techniques provided a reliable prediction of spatial patterns. We advocate the use of ensemble modelling that combines the output of several methods to predict the spatial distribution of seabirds, and use these predictions to target separate surveys assessing the abundance of seabirds in areas of regular use.

Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming.

PubMed

Li, Yuqin; You, Guirong; Jia, Baoxiu; Si, Hongzong; Yao, Xiaojun

2014-01-01

Quantitative structure-activity relationships (QSAR) were developed to predict the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase via heuristic method (HM) and gene expression programming (GEP). The descriptors of 33 pyrrolidine derivatives were calculated by the software CODESSA, which can calculate quantum chemical, topological, geometrical, constitutional, and electrostatic descriptors. HM was also used for the preselection of 5 appropriate molecular descriptors. Linear and nonlinear QSAR models were developed based on the HM and GEP separately and two prediction models lead to a good correlation coefficient (R (2)) of 0.93 and 0.94. The two QSAR models are useful in predicting the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase during the discovery of new anticancer drugs and providing theory information for studying the new drugs.

Childhood Epilepsy and Asthma: A Test of an Extension of the Double ABCX Model.

ERIC Educational Resources Information Center

Austin, Joan Kessner

The Double ABCX Model of Family Adjustment and Adaptation, a model that predicts adaptation to chronic stressors on the family, was extended by dividing it into attitudes, coping, and adaptation of parents and child separately, and by including variables relevant to child adaptation to epilepsy or asthma. The extended model was tested on 246…

Bubbles in Sediments

DTIC Science & Technology

1997-09-30

modeled as either an effective fluid, effective viscoelastic solid, or a saturated poroelastic medium. The analysis included only the breathing mode...separated for each model . Finally, if a sediment is modeled by Biot theory, which describes wave propagation in a saturated poroelastic medium, then two...theory to sediment acoustics . The predicted resonance behavior under each model is distinct, so an optical extinction measurement may provide an

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

PubMed

Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

2018-02-01

To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

On turbulent flows dominated by curvature effects

NASA Technical Reports Server (NTRS)

Cheng, G. C.; Farokhi, S.

1992-01-01

A technique for improving the numerical predictions of turbulent flows with the effect of streamline curvature is developed. Separated flows and the flow in a curved duct are examples of flowfields where streamline curvature plays a dominant role. New algebraic formulations for the eddy viscosity incorporating the k-epsilon turbulence model are proposed to account for various effects of streamline curvature. The loci of flow reversal of the separated flows over various backward-facing steps are employed to test the capability of the proposed turbulence model in capturing the effect of local curvature.

Condensation model for the ESBWR passive condensers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Revankar, S. T.; Zhou, W.; Wolf, B.

2012-07-01

In the General Electric's Economic simplified boiling water reactor (GE-ESBWR) the passive containment cooling system (PCCS) plays a major role in containment pressure control in case of an loss of coolant accident. The PCCS condenser must be able to remove sufficient energy from the reactor containment to prevent containment from exceeding its design pressure following a design basis accident. There are three PCCS condensation modes depending on the containment pressurization due to coolant discharge; complete condensation, cyclic venting and flow through mode. The present work reviews the models and presents model predictive capability along with comparison with existing data frommore » separate effects test. The condensation models in thermal hydraulics code RELAP5 are also assessed to examine its application to various flow modes of condensation. The default model in the code predicts complete condensation well, and basically is Nusselt solution. The UCB model predicts through flow well. None of condensation model in RELAP5 predict complete condensation, cyclic venting, and through flow condensation consistently. New condensation correlations are given that accurately predict all three modes of PCCS condensation. (authors)« less

Partial least squares for efficient models of fecal indicator bacteria on Great Lakes beaches

USGS Publications Warehouse

Brooks, Wesley R.; Fienen, Michael N.; Corsi, Steven R.

2013-01-01

At public beaches, it is now common to mitigate the impact of water-borne pathogens by posting a swimmer's advisory when the concentration of fecal indicator bacteria (FIB) exceeds an action threshold. Since culturing the bacteria delays public notification when dangerous conditions exist, regression models are sometimes used to predict the FIB concentration based on readily-available environmental measurements. It is hard to know which environmental parameters are relevant to predicting FIB concentration, and the parameters are usually correlated, which can hurt the predictive power of a regression model. Here the method of partial least squares (PLS) is introduced to automate the regression modeling process. Model selection is reduced to the process of setting a tuning parameter to control the decision threshold that separates predicted exceedances of the standard from predicted non-exceedances. The method is validated by application to four Great Lakes beaches during the summer of 2010. Performance of the PLS models compares favorably to that of the existing state-of-the-art regression models at these four sites.

Wall-Resolved Large-Eddy Simulation of Flow Separation Over NASA Wall-Mounted Hump

NASA Technical Reports Server (NTRS)

Uzun, Ali; Malik, Mujeeb R.

2017-01-01

This paper reports the findings from a study that applies wall-resolved large-eddy simulation to investigate flow separation over the NASA wall-mounted hump geometry. Despite its conceptually simple flow configuration, this benchmark problem has proven to be a challenging test case for various turbulence simulation methods that have attempted to predict flow separation arising from the adverse pressure gradient on the aft region of the hump. The momentum-thickness Reynolds number of the incoming boundary layer has a value that is near the upper limit achieved by recent direct numerical simulation and large-eddy simulation of incompressible turbulent boundary layers. The high Reynolds number of the problem necessitates a significant number of grid points for wall-resolved calculations. The present simulations show a significant improvement in the separation-bubble length prediction compared to Reynolds-Averaged Navier-Stokes calculations. The current simulations also provide good overall prediction of the skin-friction distribution, including the relaminarization observed over the front portion of the hump due to the strong favorable pressure gradient. We discuss a number of problems that were encountered during the course of this work and present possible solutions. A systematic study regarding the effect of domain span, subgrid-scale model, tunnel back pressure, upstream boundary layer conditions and grid refinement is performed. The predicted separation-bubble length is found to be sensitive to the span of the domain. Despite the large number of grid points used in the simulations, some differences between the predictions and experimental observations still exist (particularly for Reynolds stresses) in the case of the wide-span simulation, suggesting that additional grid resolution may be required.

Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volkova, Svitlana; Shaffer, Kyle J.; Jang, Jin Yea

Pew research polls report 62 percent of U.S. adults get news on social media (Gottfried and Shearer, 2016). In a December poll, 64 percent of U.S. adults said that “made-up news” has caused a “great deal of confusion” about the facts of current events (Barthel et al., 2016). Fabricated stories spread in social media, ranging from deliberate propaganda to hoaxes and satire, contributes to this confusion in addition to having serious effects on global stability. In this work we build predictive models to classify 130 thousand news tweets as suspicious or verified, and predict four subtypes of suspicious news –more » satire, hoaxes, clickbait and propaganda. We demonstrate that neural network models trained on tweet content and social network interactions outperform lexical models. Unlike previous work on deception detection, we find that adding syntax and grammar features to our models decreases performance. Incorporating linguistic features, including bias and subjectivity, improves classification results, however social interaction features are most informative for finer-grained separation between our four types of suspicious news posts.« less

The Separation and Quantitation of Peptides with and without Oxidation of Methionine and Deamidation of Asparagine Using Hydrophilic Interaction Liquid Chromatography with Mass Spectrometry (HILIC-MS)

NASA Astrophysics Data System (ADS)

Badgett, Majors J.; Boyes, Barry; Orlando, Ron

2017-05-01

Peptides with deamidated asparagine residues and oxidized methionine residues are often not resolved sufficiently to allow quantitation of their native and modified forms using reversed phase (RP) chromatography. The accurate quantitation of these modifications is vital in protein biotherapeutic analysis because they can affect a protein's function, activity, and stability. We demonstrate here that hydrophilic interaction liquid chromatography (HILIC) adequately and predictably separates peptides with these modifications from their native counterparts. Furthermore, coefficients describing the extent of the hydrophilicity of these modifications have been derived and were incorporated into a previously made peptide retention prediction model that is capable of predicting the retention times of peptides with and without these modifications.

Exclusive quasi-free proton knockout from oxygen isotopes at intermediate energies

NASA Astrophysics Data System (ADS)

Kawase, Shoichiro; Uesaka, Tomohiro; Tang, Tsz Leung; Beaumel, Didier; Dozono, Masanori; Fukunaga, Taku; Fujii, Toshihiko; Fukuda, Naoki; Galindo-Uribarri, Alfredo; Hwang, Sanghoon; Inabe, Naoto; Kawabata, Takahiro; Kawahara, Tomomi; Kim, Wooyoung; Kisamori, Keiichi; Kobayashi, Motoki; Kubo, Toshiyuki; Kubota, Yuki; Kusaka, Kensuke; Lee, Cheongsoo; Maeda, Yukie; Matsubara, Hiroaki; Michimasa, Shin'ichiro; Miya, Hiroyuki; Noro, Tetsuo; Nozawa, Yuki; Obertelli, Alexandre; Ogata, Kazuyuki; Ota, Shinsuke; Padilla-Rodal, Elizabeth; Sakaguchi, Satoshi; Sakai, Hideyuki; Sasano, Masaki; Shimoura, Susumu; Stepanyan, Samvel; Suzuki, Hiroshi; Suzuki, Tomokazu; Takaki, Motonobu; Takeda, Hiroyuki; Tamii, Atsushi; Tokieda, Hiroshi; Wakasa, Tomotsugu; Wakui, Takashi; Yako, Kentaro; Yasuda, Jumpei; Yanagisawa, Yoshiyuki; Yokoyama, Rin; Yoshida, Kazuki; Yoshida, Koichi; Zenihiro, Juzo

2018-02-01

The dependence of the single-particle strength on the difference between proton and neutron separation energies is studied for oxygen isotopes in a wide range of isospins. The cross sections of the quasi-free (p,2p) reaction on ^{14,16,18,22,24}O were measured at intermediate energies. The measured cross sections are compared to predictions based on the distorted wave impulse approximation and shell-model psd valence-space spectroscopic factors. The reduction factors, which are the ratio of the experimental cross sections to the theoretical predictions, show no apparent dependence on the proton-neutron separation energy difference. The result is compatible with the result of the (e,e^'p) reaction on stable targets and with the predictions of recent ab initio calculations.

The Separation and Quantitation of Peptides with and without Oxidation of Methionine and Deamidation of Asparagine Using Hydrophilic Interaction Liquid Chromatography with Mass Spectrometry (HILIC-MS).

PubMed

Badgett, Majors J; Boyes, Barry; Orlando, Ron

2017-05-01

Peptides with deamidated asparagine residues and oxidized methionine residues are often not resolved sufficiently to allow quantitation of their native and modified forms using reversed phase (RP) chromatography. The accurate quantitation of these modifications is vital in protein biotherapeutic analysis because they can affect a protein's function, activity, and stability. We demonstrate here that hydrophilic interaction liquid chromatography (HILIC) adequately and predictably separates peptides with these modifications from their native counterparts. Furthermore, coefficients describing the extent of the hydrophilicity of these modifications have been derived and were incorporated into a previously made peptide retention prediction model that is capable of predicting the retention times of peptides with and without these modifications. Graphical Abstract ᅟ.

A New Methodology for Turbulence Modelers Using DNS Database Analysis

NASA Technical Reports Server (NTRS)

Parneix, S.; Durbin, P.

1996-01-01

Many industrial applications in such fields as aeronautical, mechanical, thermal, and environmental engineering involve complex turbulent flows containing global separations and subsequent reattachment zones. Accurate prediction of this phenomena is very important because separations influence the whole fluid flow and may have an even bigger impact on surface heat transfer. In particular, reattaching flows are known to be responsible for large local variations of the local wall heat transfer coefficient as well as modifying the overall heat transfer. For incompressible, non-buoyant situations, the fluid mechanics have to be accurately predicted in order to have a good resolution of the temperature field.

A computational approach to predicting ligand selectivity for the size-based separation of trivalent lanthanides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, Alexander S.; Bryantsev, Vyacheslav S.

An accurate description of solvation effects for trivalent lanthanide ions is a main stumbling block to the qualitative prediction of selectivity trends along the lanthanide series. In this work, we propose a simple model to describe the differential effect of solvation in the competitive binding of a ligand by lanthanide ions by including weakly co-ordinated counterions in the complexes of more than a +1 charge. The success of the approach to quantitatively reproduce selectivities obtained from aqueous phase complexation studies demonstrates its potential for the design and screening of new ligands for efficient size-based separation.

A computational approach to predicting ligand selectivity for the size-based separation of trivalent lanthanides

DOE PAGES

Ivanov, Alexander S.; Bryantsev, Vyacheslav S.

2016-06-20

An accurate description of solvation effects for trivalent lanthanide ions is a main stumbling block to the qualitative prediction of selectivity trends along the lanthanide series. In this work, we propose a simple model to describe the differential effect of solvation in the competitive binding of a ligand by lanthanide ions by including weakly co-ordinated counterions in the complexes of more than a +1 charge. The success of the approach to quantitatively reproduce selectivities obtained from aqueous phase complexation studies demonstrates its potential for the design and screening of new ligands for efficient size-based separation.

Numerical solutions of the complete Navier-Strokes equations. no. 27

NASA Technical Reports Server (NTRS)

Hassan, H. A.

1996-01-01

This report describes the development of an enstrophy model capable of predicting turbulence separation and its application to two airfoils at various angles of attack and Mach numbers. In addition, a two equation kappa-xi model with a tensor eddy viscosity was developed. Plans call for this model to be used in calculating three dimensional turbulent flows.

Models and parameters for environmental radiological assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, C W

1984-01-01

This book presents a unified compilation of models and parameters appropriate for assessing the impact of radioactive discharges to the environment. Models examined include those developed for the prediction of atmospheric and hydrologic transport and deposition, for terrestrial and aquatic food-chain bioaccumulation, and for internal and external dosimetry. Chapters have been entered separately into the data base. (ACR)

Predicting use of ineffective responsive, structure and control vegetable parenting practices with the Model of Goal Directed Behavior

USDA-ARS?s Scientific Manuscript database

This study reports the modeling of three categories of ineffective vegetable parenting practices (IVPP) separately (responsive, structure, and control vegetable parenting practices). An internet survey was employed for a cross sectional assessment of parenting practices and cognitive-emotional varia...

Dynamics of the antibody-T.cruzi competition during Chagas infection: Prognostic relevance of intracellular replication

NASA Astrophysics Data System (ADS)

Sibona, G. J.; Condat, C. A.; Isasi, S. Cossy

2005-02-01

A recently proposed model for the competitive parasite-antibody interactions in Chagas disease is extended by separately describing the parasitic intracellular and extracellular phases. The model solutions faithfully reproduce available population data and yield predictions for parasite-induced cardiac cell damage.

Bayesian component separation: The Planck experience

NASA Astrophysics Data System (ADS)

Wehus, Ingunn Kathrine; Eriksen, Hans Kristian

2018-05-01

Bayesian component separation techniques have played a central role in the data reduction process of Planck. The most important strength of this approach is its global nature, in which a parametric and physical model is fitted to the data. Such physical modeling allows the user to constrain very general data models, and jointly probe cosmological, astrophysical and instrumental parameters. This approach also supports statistically robust goodness-of-fit tests in terms of data-minus-model residual maps, which are essential for identifying residual systematic effects in the data. The main challenges are high code complexity and computational cost. Whether or not these costs are justified for a given experiment depends on its final uncertainty budget. We therefore predict that the importance of Bayesian component separation techniques is likely to increase with time for intensity mapping experiments, similar to what has happened in the CMB field, as observational techniques mature, and their overall sensitivity improves.

Limitation of predictive 2-D liquid chromatography in reducing the database search space in shotgun proteomics: in silico studies.

PubMed

Moskovets, Eugene; Goloborodko, Anton A; Gorshkov, Alexander V; Gorshkov, Mikhail V

2012-07-01

A two-dimensional (2-D) liquid chromatography (LC) separation of complex peptide mixtures that combines a normal phase utilizing hydrophilic interactions and a reversed phase offers reportedly the highest level of 2-D LC orthogonality by providing an even spread of peptides across multiple LC fractions. Matching experimental peptide retention times to those predicted by empirical models describing chromatographic separation in each LC dimension leads to a significant reduction in a database search space. In this work, we calculated the retention times of tryptic peptides separated in the C18 reversed phase at different separation conditions (pH 2 and pH 10) and in TSK gel Amide-80 normal phase. We show that retention times calculated for different 2-D LC separation schemes utilizing these phases start to correlate once the mass range of peptides under analysis becomes progressively narrow. This effect is explained by high degree of correlation between retention coefficients in the considered phases. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model-based learning and the contribution of the orbitofrontal cortex to the model-free world.

PubMed

McDannald, Michael A; Takahashi, Yuji K; Lopatina, Nina; Pietras, Brad W; Jones, Josh L; Schoenbaum, Geoffrey

2012-04-01

Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Predicting students' physical activity and health-related well-being: a prospective cross-domain investigation of motivation across school physical education and exercise settings.

PubMed

Standage, Martyn; Gillison, Fiona B; Ntoumanis, Nikos; Treasure, Darren C

2012-02-01

A three-wave prospective design was used to assess a model of motivation guided by self-determination theory (Ryan & Deci, 2008) spanning the contexts of school physical education (PE) and exercise. The outcome variables examined were health-related quality of life (HRQoL), physical self-concept (PSC), and 4 days of objectively assessed estimates of activity. Secondary school students (n = 494) completed questionnaires at three separate time points and were familiarized with how to use a sealed pedometer. Results of structural equation modeling supported a model in which perceptions of autonomy support from a PE teacher positively predicted PE-related need satisfaction (autonomy, competence, and relatedness). Competence predicted PSC, whereas relatedness predicted HRQoL. Autonomy and competence positively predicted autonomous motivation toward PE, which in turn positively predicted autonomous motivation toward exercise (i.e., 4-day pedometer step count). Autonomous motivation toward exercise positively predicted step count, HRQoL, and PSC. Results of multisample structural equation modeling supported gender invariance. Suggestions for future work are discussed.

Target/error overlap in jargonaphasia: The case for a one-source model, lexical and non-lexical summation, and the special status of correct responses.

PubMed

Olson, Andrew; Halloran, Elizabeth; Romani, Cristina

2015-12-01

We present three jargonaphasic patients who made phonological errors in naming, repetition and reading. We analyse target/response overlap using statistical models to answer three questions: 1) Is there a single phonological source for errors or two sources, one for target-related errors and a separate source for abstruse errors? 2) Can correct responses be predicted by the same distribution used to predict errors or do they show a completion boost (CB)? 3) Is non-lexical and lexical information summed during reading and repetition? The answers were clear. 1) Abstruse errors did not require a separate distribution created by failure to access word forms. Abstruse and target-related errors were the endpoints of a single overlap distribution. 2) Correct responses required a special factor, e.g., a CB or lexical/phonological feedback, to preserve their integrity. 3) Reading and repetition required separate lexical and non-lexical contributions that were combined at output. Copyright © 2015 Elsevier Ltd. All rights reserved.

Separator Reconnection at Earth's Dayside Magnetopause and the Tail: MMS Observations Compared to Global 3D Simulations

NASA Astrophysics Data System (ADS)

Buzulukova, N.; Dorelli, J.; Glocer, A.

2017-12-01

We present the results of global high resolution resistive magnetohydrodynamics (MHD BATS-R-US) simulations of Earth's magnetosphere. We extract location of magnetic separators with RECONX tool and compare the results with observations from the Magnetospheric Multiscale (MMS). A few cases are analysed including a southward IMF magnetopause crossing during October 16, 2015 that was previously identified as an electron diffusion region (EDR) event. The simulation predicts a complex time-dependent magnetic topology consisting of multiple separators and flux ropes. Despite the topological complexity, the predicted distance between MMS and the primary separator is less than 0.5 Earth radii. The simulation shows that the existence of IMF Bx results in a duskward shift of the location of the topological separator. The results are explained by a combined effect of solar wind draping and pile-up effect that modify the current density across the magnetopause and affect the location of the separator. The RECONX tool also is used to extract the separator location in the geomagnetic tail, and relate transient tail structures (bursty bulk flows) to the location of separator. These results suggest that global magnetic topology, rather than local magnetic geometry alone, determines the location of the separator reconnection both at the dayside magnetopause and in the tail. We show that the resistive MHD model helps to understand the global context of local MMS observations.

Interkinetic nuclear migration and basal tethering facilitates post-mitotic daughter separation in intestinal organoids

PubMed Central

Carroll, Thomas D.; Langlands, Alistair J.; Osborne, James M.; Newton, Ian P.; Appleton, Paul L.

2017-01-01

ABSTRACT Homeostasis of renewing tissues requires balanced proliferation, differentiation and movement. This is particularly important in the intestinal epithelium where lineage tracing suggests that stochastic differentiation choices are intricately coupled to the position of a cell relative to a niche. To determine how position is achieved, we followed proliferating cells in intestinal organoids and discovered that the behaviour of mitotic sisters predicted long-term positioning. We found that, normally, 70% of sisters remain neighbours, while 30% lose contact and separate after cytokinesis. These post-mitotic placements predict longer term differences in positions assumed by sisters: adjacent sisters reach similar positions over time; in a pair of separating sisters, one remains close to its birthplace while the other is displaced upward. Computationally modelling crypt dynamics confirmed that post-mitotic separation leads to sisters reaching different compartments. We show that interkinetic nuclear migration, cell size and asymmetric tethering by a process extending from the basal side of cells contribute to separations. These processes are altered in adenomatous polyposis coli (Apc) mutant epithelia where separation is lost. We conclude that post-mitotic placement contributes to stochastic niche exit and, when defective, supports the clonal expansion of Apc mutant cells. PMID:28982714

A two-stage storage routing model for green roof runoff detention.

PubMed

Vesuviano, Gianni; Sonnenwald, Fred; Stovin, Virginia

2014-01-01

Green roofs have been adopted in urban drainage systems to control the total quantity and volumetric flow rate of runoff. Modern green roof designs are multi-layered, their main components being vegetation, substrate and, in almost all cases, a separate drainage layer. Most current hydrological models of green roofs combine the modelling of the separate layers into a single process; these models have limited predictive capability for roofs not sharing the same design. An adaptable, generic, two-stage model for a system consisting of a granular substrate over a hard plastic 'egg box'-style drainage layer and fibrous protection mat is presented. The substrate and drainage layer/protection mat are modelled separately by previously verified sub-models. Controlled storm events are applied to a green roof system in a rainfall simulator. The time-series modelled runoff is compared to the monitored runoff for each storm event. The modelled runoff profiles are accurate (mean Rt(2) = 0.971), but further characterization of the substrate component is required for the model to be generically applicable to other roof configurations with different substrate.

Particle-laden weakly swirling free jets: Measurements and predictions. Ph.D. Thesis - Pennsylvania State Univ.

NASA Technical Reports Server (NTRS)

Bulzan, Daniel L.

1988-01-01

A theoretical and experimental investigation of particle-laden, weakly swirling, turbulent free jets was conducted. Glass particles, having a Sauter mean diameter of 39 microns, with a standard deviation of 15 microns, were used. A single loading ratio (the mass flow rate of particles per unit mass flow rate of air) of 0.2 was used in the experiments. Measurements are reported for three swirl numbers, ranging from 0 to 0.33. The measurements included mean and fluctuating velocities of both phases, and particle mass flux distributions. Measurements were also completed for single-phase non-swirling and swirling jets, as baselines. Measurements were compared with predictions from three types of multiphase flow analysis, as follows: (1) locally homogeneous flow (LHF) where slip between the phases was neglected; (2) deterministic separated flow (DSF), where slip was considered but effects of turbulence/particle interactions were neglected; and (3) stochastic separated flow (SSF), where effects of both interphase slip and turbulence/particle interactions were considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. Single-phase weakly swirling jets were considered first. Predictions using a standard k-epsilon turbulence model, as well as two versions modified to account for effects of streamline curvature, were compared with measurements. Predictions using a streamline curvature modification based on the flux Richardson number gave better agreement with measurements for the single-phase swirling jets than the standard k-epsilon model. For the particle-laden jets, the LHF and DSF models did not provide very satisfactory predictions. The LHF model generally overestimated the rate of decay of particle mean axial and angular velocities with streamwise distance, and predicted particle mass fluxes also showed poor agreement with measurements, due to the assumption of no-slip between phases. The DSF model also performed quite poorly for predictions of particle mass flux because turbulent dispersion of the particles was neglected. The SSF model, which accounts for both particle inertia and turbulent dispersion of the particles, yielded reasonably good predictions throughout the flow field for the particle-laden jets.

Cognitive Control Predicts Use of Model-Based Reinforcement-Learning

PubMed Central

Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

2015-01-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information—in the service of overcoming habitual, stimulus-driven responses—in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

Differential coactivation in a redundant signals task with weak and strong go/no-go stimuli.

PubMed

Minakata, Katsumi; Gondan, Matthias

2018-05-01

When participants respond to stimuli of two sources, response times (RTs) are often faster when both stimuli are presented together relative to the RTs obtained when presented separately (redundant signals effect [RSE]). Race models and coactivation models can explain the RSE. In race models, separate channels process the two stimulus components, and the faster processing time determines the overall RT. In audiovisual experiments, the RSE is often higher than predicted by race models, and coactivation models have been proposed that assume integrated processing of the two stimuli. Where does coactivation occur? We implemented a go/no-go task with randomly intermixed weak and strong auditory, visual, and audiovisual stimuli. In one experimental session, participants had to respond to strong stimuli and withhold their response to weak stimuli. In the other session, these roles were reversed. Interestingly, coactivation was only observed in the experimental session in which participants had to respond to strong stimuli. If weak stimuli served as targets, results were widely consistent with the race model prediction. The pattern of results contradicts the inverse effectiveness law. We present two models that explain the result in terms of absolute and relative thresholds.

Investigation of transient cavitating flow in viscoelastic pipes

NASA Astrophysics Data System (ADS)

Keramat, A.; Tijsseling, A. S.; Ahmadi, A.

2010-08-01

A study on water hammer in viscoelastic pipes when the fluid pressure drops to liquid vapour pressure is performed. Two important concepts including column separation and the effects of retarded strains in the pipe wall on the fluid response have been investigated separately in recent works, but there is some curiosity as to how the results for pressure and discharge are when column separation occurs in a viscoelastic pipe. For pipes made of plastic such as polyethylene (PE) and polyvinyl chloride (PVC), viscoelasticity is a crucial mechanical property which changes the hydraulic and structural transient responses. Based on previous developments in the analysis of water hammer, a model which is capable of analysing column separation in viscoelastic pipes is presented and used for solving the selected case studies. For the column-separation modelling the Discrete Vapour Cavity Model (DVCM) is utilised and the viscoelasticity property of the pipe wall is modelled by Kelvin-Voigt elements. The effects of viscoelasticity play an important role in the column separation phenomenon because it changes the water hammer fundamental frequency and so affects the time of opening or collapse of the cavities. Verification of the implemented computer code is performed for the effects of viscoelasticity and column separation - separately and simultaneously - using experimental results from the literature. In the provided examples the focus is placed on the simultaneous effect of viscoelasticity and column separation on the hydraulic transient response. The final conclusions drawn are that if rectangular grids are utilised the DVCM gives acceptable predictions of the phenomenon and that the pipe wall material's retarded behaviour strongly dampens the pressure spikes caused by column separation.

Theoretical study of hull-rotor aerodynamic interference on semibuoyant vehicles

NASA Technical Reports Server (NTRS)

Spangler, S. B.; Smith, C. A.; Mendenhall, M. R.

1977-01-01

Theoretical methods are being developed to predict the mutual interference between rotor wakes and the hull for semibuoyant vehicles. The objective of the investigation is to predict the pressure distribution and overall loads on the hull in the presence of rotors whose locations, tilt angles, and disk loading are arbitrarily specified. The methods involve development of potential flow models for the hull alone in a nonuniform onset flow, a rotor wake which has the proper features to predict induced flow outside the wake, and a wake centerline specification technique which accounts for the reactions of the wake to a nonuniform crossflow. The flow models are used in sequence to solve for the mutual influence of the hull and rotor(s) on each other and the resulting loads. A flow separation model is included to estimate the influence of separation on hull loads at high sideslip angles. Only limited results have been obtained to date. These were obtained on a configuration which was tested in the Ames Research Center 7- by 10-Foot Low Speed Tunnel under Goodyear Aircraft Corporation sponsorship and indicate the nature of the interference pressure distribution on a configuration in hover.

An evaluation of three two-dimensional computational fluid dynamics codes including low Reynolds numbers and transonic Mach numbers

NASA Technical Reports Server (NTRS)

Hicks, Raymond M.; Cliff, Susan E.

1991-01-01

Full-potential, Euler, and Navier-Stokes computational fluid dynamics (CFD) codes were evaluated for use in analyzing the flow field about airfoils sections operating at Mach numbers from 0.20 to 0.60 and Reynolds numbers from 500,000 to 2,000,000. The potential code (LBAUER) includes weakly coupled integral boundary layer equations for laminar and turbulent flow with simple transition and separation models. The Navier-Stokes code (ARC2D) uses the thin-layer formulation of the Reynolds-averaged equations with an algebraic turbulence model. The Euler code (ISES) includes strongly coupled integral boundary layer equations and advanced transition and separation calculations with the capability to model laminar separation bubbles and limited zones of turbulent separation. The best experiment/CFD correlation was obtained with the Euler code because its boundary layer equations model the physics of the flow better than the other two codes. An unusual reversal of boundary layer separation with increasing angle of attack, following initial shock formation on the upper surface of the airfoil, was found in the experiment data. This phenomenon was not predicted by the CFD codes evaluated.

Prediction of the backflow and recovery regions in the backward facing step at various Reynolds numbers

NASA Technical Reports Server (NTRS)

Michelassi, V.; Durbin, P. A.; Mansour, N. N.

1996-01-01

A four-equation model of turbulence is applied to the numerical simulation of flows with massive separation induced by a sudden expansion. The model constants are a function of the flow parameters, and two different formulations for these functions are tested. The results are compared with experimental data for a high Reynolds-number case and with experimental and DNS data for a low Reynolds-number case. The computations prove that the recovery region downstream of the massive separation is properly modeled only for the high Re case. The problems in this case stem from the gradient diffusion hypothesis, which underestimates the turbulent diffusion.

Numerical modeling of on-orbit propellant motion resulting from an impulsive acceleration

NASA Technical Reports Server (NTRS)

Aydelott, John C.; Mjolsness, Raymond C.; Torrey, Martin D.; Hochstein, John I.

1987-01-01

In-space docking and separation maneuvers of spacecraft that have large fluid mass fractions may cause undesirable spacecraft motion in response to the impulsive-acceleration-induced fluid motion. An example of this potential low gravity fluid management problem arose during the development of the shuttle/Centaur vehicle. Experimentally verified numerical modeling techniques were developed to establish the propellant dynamics, and subsequent vehicle motion, associated with the separation of the Centaur vehicle from the shuttle orbiter cargo bay. Although the shuttle/Centaur development activity was suspended, the numerical modeling techniques are available to predict on-orbit liquid motion resulting from impulsive accelerations for other missions and spacecraft.

Empirical models to predict the volumes of debris flows generated by recently burned basins in the western U.S.

USGS Publications Warehouse

Gartner, J.E.; Cannon, S.H.; Santi, P.M.; deWolfe, V.G.

2008-01-01

Recently burned basins frequently produce debris flows in response to moderate-to-severe rainfall. Post-fire hazard assessments of debris flows are most useful when they predict the volume of material that may flow out of a burned basin. This study develops a set of empirically-based models that predict potential volumes of wildfire-related debris flows in different regions and geologic settings. The models were developed using data from 53 recently burned basins in Colorado, Utah and California. The volumes of debris flows in these basins were determined by either measuring the volume of material eroded from the channels, or by estimating the amount of material removed from debris retention basins. For each basin, independent variables thought to affect the volume of the debris flow were determined. These variables include measures of basin morphology, basin areas burned at different severities, soil material properties, rock type, and rainfall amounts and intensities for storms triggering debris flows. Using these data, multiple regression analyses were used to create separate predictive models for volumes of debris flows generated by burned basins in six separate regions or settings, including the western U.S., southern California, the Rocky Mountain region, and basins underlain by sedimentary, metamorphic and granitic rocks. An evaluation of these models indicated that the best model (the Western U.S. model) explains 83% of the variability in the volumes of the debris flows, and includes variables that describe the basin area with slopes greater than or equal to 30%, the basin area burned at moderate and high severity, and total storm rainfall. This model was independently validated by comparing volumes of debris flows reported in the literature, to volumes estimated using the model. Eighty-seven percent of the reported volumes were within two residual standard errors of the volumes predicted using the model. This model is an improvement over previous models in that it includes a measure of burn severity and an estimate of modeling errors. The application of this model, in conjunction with models for the probability of debris flows, will enable more complete and rapid assessments of debris flow hazards following wildfire.

Conservative Exposure Predictions for Rapid Risk Assessment of Phase-Separated Additives in Medical Device Polymers.

PubMed

Chandrasekar, Vaishnavi; Janes, Dustin W; Saylor, David M; Hood, Alan; Bajaj, Akhil; Duncan, Timothy V; Zheng, Jiwen; Isayeva, Irada S; Forrey, Christopher; Casey, Brendan J

2018-01-01

A novel approach for rapid risk assessment of targeted leachables in medical device polymers is proposed and validated. Risk evaluation involves understanding the potential of these additives to migrate out of the polymer, and comparing their exposure to a toxicological threshold value. In this study, we propose that a simple diffusive transport model can be used to provide conservative exposure estimates for phase separated color additives in device polymers. This model has been illustrated using a representative phthalocyanine color additive (manganese phthalocyanine, MnPC) and polymer (PEBAX 2533) system. Sorption experiments of MnPC into PEBAX were conducted in order to experimentally determine the diffusion coefficient, D = (1.6 ± 0.5) × 10 -11  cm 2 /s, and matrix solubility limit, C s  = 0.089 wt.%, and model predicted exposure values were validated by extraction experiments. Exposure values for the color additive were compared to a toxicological threshold for a sample risk assessment. Results from this study indicate that a diffusion model-based approach to predict exposure has considerable potential for use as a rapid, screening-level tool to assess the risk of color additives and other small molecule additives in medical device polymers.

Constrained positive matrix factorization: Elemental ratios, spatial distinction, and chemical transport model source contributions

NASA Astrophysics Data System (ADS)

Sturtz, Timothy M.

Source apportionment models attempt to untangle the relationship between pollution sources and the impacts at downwind receptors. Two frameworks of source apportionment models exist: source-oriented and receptor-oriented. Source based apportionment models use presumed emissions and atmospheric processes to estimate the downwind source contributions. Conversely, receptor based models leverage speciated concentration data from downwind receptors and apply statistical methods to predict source contributions. Integration of both source-oriented and receptor-oriented models could lead to a better understanding of the implications sources have on the environment and society. The research presented here investigated three different types of constraints applied to the Positive Matrix Factorization (PMF) receptor model within the framework of the Multilinear Engine (ME-2): element ratio constraints, spatial separation constraints, and chemical transport model (CTM) source attribution constraints. PM10-2.5 mass and trace element concentrations were measured in Winston-Salem, Chicago, and St. Paul at up to 60 sites per city during two different seasons in 2010. PMF was used to explore the underlying sources of variability. Information on previously reported PM10-2.5 tire and brake wear profiles were used to constrain these features in PMF by prior specification of selected species ratios. We also modified PMF to allow for combining the measurements from all three cities into a single model while preserving city-specific soil features. Relatively minor differences were observed between model predictions with and without the prior ratio constraints, increasing confidence in our ability to identify separate brake wear and tire wear features. Using separate data, source contributions to total fine particle carbon predicted by a CTM were incorporated into the PMF receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was varied using a weighting parameter applied to an object function as implemented in ME-2. The resulting hybrid model was used to quantify the contributions of total carbon from both wildfires and biogenic sources at two Interagency Monitoring of Protected Visual Environment monitoring sites, Monture and Sula Peak, Montana, from 2006 through 2008.

Microscopic prediction of speech intelligibility in spatially distributed speech-shaped noise for normal-hearing listeners.

PubMed

Geravanchizadeh, Masoud; Fallah, Ali

2015-12-01

A binaural and psychoacoustically motivated intelligibility model, based on a well-known monaural microscopic model is proposed. This model simulates a phoneme recognition task in the presence of spatially distributed speech-shaped noise in anechoic scenarios. In the proposed model, binaural advantage effects are considered by generating a feature vector for a dynamic-time-warping speech recognizer. This vector consists of three subvectors incorporating two monaural subvectors to model the better-ear hearing, and a binaural subvector to simulate the binaural unmasking effect. The binaural unit of the model is based on equalization-cancellation theory. This model operates blindly, which means separate recordings of speech and noise are not required for the predictions. Speech intelligibility tests were conducted with 12 normal hearing listeners by collecting speech reception thresholds (SRTs) in the presence of single and multiple sources of speech-shaped noise. The comparison of the model predictions with the measured binaural SRTs, and with the predictions of a macroscopic binaural model called extended equalization-cancellation, shows that this approach predicts the intelligibility in anechoic scenarios with good precision. The square of the correlation coefficient (r(2)) and the mean-absolute error between the model predictions and the measurements are 0.98 and 0.62 dB, respectively.

Second-Moment RANS Model Verification and Validation Using the Turbulence Modeling Resource Website (Invited)

NASA Technical Reports Server (NTRS)

Eisfeld, Bernhard; Rumsey, Chris; Togiti, Vamshi

2015-01-01

The implementation of the SSG/LRR-omega differential Reynolds stress model into the NASA flow solvers CFL3D and FUN3D and the DLR flow solver TAU is verified by studying the grid convergence of the solution of three different test cases from the Turbulence Modeling Resource Website. The model's predictive capabilities are assessed based on four basic and four extended validation cases also provided on this website, involving attached and separated boundary layer flows, effects of streamline curvature and secondary flow. Simulation results are compared against experimental data and predictions by the eddy-viscosity models of Spalart-Allmaras (SA) and Menter's Shear Stress Transport (SST).

What's Next: Recruitment of a Grounded Predictive Body Model for Planning a Robot's Actions.

PubMed

Schilling, Malte; Cruse, Holk

2012-01-01

Even comparatively simple, reactive systems are able to control complex motor tasks, such as hexapod walking on unpredictable substrate. The capability of such a controller can be improved by introducing internal models of the body and of parts of the environment. Such internal models can be applied as inverse models, as forward models or to solve the problem of sensor fusion. Usually, separate models are used for these functions. Furthermore, separate models are used to solve different tasks. Here we concentrate on internal models of the body as the brain considers its own body the most important part of the world. The model proposed is formed by a recurrent neural network with the property of pattern completion. The model shows a hierarchical structure but nonetheless comprises a holistic system. One and the same model can be used as a forward model, as an inverse model, for sensor fusion, and, with a simple expansion, as a model to internally simulate (new) behaviors to be used for prediction. The model embraces the geometrical constraints of a complex body with many redundant degrees of freedom, and allows finding geometrically possible solutions. To control behavior such as walking, climbing, or reaching, this body model is complemented by a number of simple reactive procedures together forming a procedural memory. In this article, we illustrate the functioning of this network. To this end we present examples for solutions of the forward function and the inverse function, and explain how the complete network might be used for predictive purposes. The model is assumed to be "innate," so learning the parameters of the model is not (yet) considered.

Correlation-based Transition Modeling for External Aerodynamic Flows

NASA Astrophysics Data System (ADS)

Medida, Shivaji

Conventional turbulence models calibrated for fully turbulent boundary layers often over-predict drag and heat transfer on aerodynamic surfaces with partially laminar boundary layers. A robust correlation-based model is developed for use in Reynolds-Averaged Navier-Stokes simulations to predict laminar-to-turbulent transition onset of boundary layers on external aerodynamic surfaces. The new model is derived from an existing transition model for the two-equation k-omega Shear Stress Transport (SST) turbulence model, and is coupled with the one-equation Spalart-Allmaras (SA) turbulence model. The transition model solves two transport equations for intermittency and transition momentum thickness Reynolds number. Experimental correlations and local mean flow quantities are used in the model to account for effects of freestream turbulence level and pressure gradients on transition onset location. Transition onset is triggered by activating intermittency production using a vorticity Reynolds number criterion. In the new model, production and destruction terms of the intermittency equation are modified to improve consistency in the fully turbulent boundary layer post-transition onset, as well as ensure insensitivity to freestream eddy viscosity value specified in the SA model. In the original model, intermittency was used to control production and destruction of turbulent kinetic energy. Whereas, in the new model, only the production of eddy viscosity in SA model is controlled, and the destruction term is not altered. Unlike the original model, the new model does not use an additional correction to intermittency for separation-induced transition. Accuracy of drag predictions are improved significantly with the use of the transition model for several two-dimensional single- and multi-element airfoil cases over a wide range of Reynolds numbers. The new model is able to predict the formation of stable and long laminar separation bubbles on low-Reynolds number airfoils that is not captured with conventional turbulence models. The validated transition model is successfully applied to rotating blade configurations in axial flow conditions to study the effects of transitional boundary layers on rotor thrust and torque. In helicopter rotors, inclusion of transition effects increased thrust prediction by 2% and decreased torque by as much as 8% at lower collective angles, due to reduced airfoil profile drag. In wind turbine rotors, transition model predicted a 7%--70% increase in generated shaft torque at lower wind speeds, due to lower viscous drag. This has important implications for CFD analysis of small wind turbines operating at low values of rated power. Transition onset locations along upper and lower surfaces of rotor blades are analyzed in detail. A new crossflow transition onset criterion is developed to account for crossflow instability effects in three-dimensional boundary layers. Preliminary results for swept wing and rotating blade flows demonstrate the need to account for crossflow transition in three-dimensional simulations of wings, rotating blades, and airframes. Inclusion of crossflow effects resulted in accelerated transition in the presence of favorable pressure gradients and yawed flow. Finally, a new correction to the wall damping function in the Spalart-Allmaras turbulence model is proposed to improve sensitivity of the model to strong adverse pressure gradients (APG). The correction reduces turbulence production in the boundary layer when the ratio of magnitudes of local turbulent stress to the wall shear stress exceeds a threshold value, therefore enabling earlier separation of boundary layer. Improved prediction of static and dynamic stall on two-dimensional airfoils is demonstrated with the APG correction.

A high-resolution model of the planetary boundary layer - Sensitivity tests and comparisons with SESAME-79 data

NASA Technical Reports Server (NTRS)

Zhang, D.; Anthes, R. A.

1982-01-01

A one-dimensional, planetary boundary layer (PBL) model is presented and verified using April 10, 1979 SESAME data. The model contains two modules to account for two different regimes of turbulent mixing. Separate parameterizations are made for stable and unstable conditions, with a predictive slab model for surface temperature. Atmospheric variables in the surface layer are calculated with a prognostic model, with moisture included in the coupled surface/PBL modeling. Sensitivity tests are performed for factors such as moisture availability, albedo, surface roughness, and thermal capacity, and a 24 hr simulation is summarized for day and night conditions. The comparison with the SESAME data comprises three hour intervals, using a time-dependent geostrophic wind. Close correlations were found with daytime conditions, but not in nighttime thermal structure, while the turbulence was faithfully predicted. Both geostrophic flow and surface characteristics were shown to have significant effects on the model predictions

Effect of added mass on the interaction of bubbles in a low-Reynolds-number shear flow.

PubMed

Lavrenteva, Olga; Prakash, Jai; Nir, Avinoam

2016-02-01

Equal size air bubbles that are entrapped by a Taylor vortex of the secondary flow in a Couette device, thereby defying buoyancy, slowly form a stable ordered ring with equal separation distances between all neighbors. We present two models of the process dynamics based on force balance on a bubble in the presence of other bubbles positioned on the same streamline in a simple shear flow. The forces taken into account are the viscous resistance, the added mass force, and the inertia-induced repulsing force between two bubbles in a low-Reynolds-number shear flow obtained in Prakash et al. [J. Prakash et al., Phys. Rev. E 87, 043002 (2013)]. The first model of the process assumes that each bubble interacts solely with its nearest neighbors. The second model takes into account pairwise interactions among all the bubbles in the ring. The performed dynamic simulations were compared to the experimental results reported in Prakash et al. [J. Prakash et al., Phys. Rev. E 87, 043002 (2013)] and to the results of quasistationary models (ignoring the added mass effect) suggested in that paper. It is demonstrated that taking into account the effect of added mass, the models describe the major effect of the bubbles' ordering, provide good estimation of the relaxation time, and also predict nonmonotonic behavior of the separation distance between the bubbles, which exhibit over- and undershooting of equilibrium separations. The latter effects were observed in experiments, but are not predicted by the quasistationary models.

A novel validated model for the prediction of insulin therapy initiation and adverse perinatal outcomes in women with gestational diabetes mellitus.

PubMed

Barnes, Robyn A; Wong, Tang; Ross, Glynis P; Jalaludin, Bin B; Wong, Vincent W; Smart, Carmel E; Collins, Clare E; MacDonald-Wicks, Lesley; Flack, Jeff R

2016-11-01

Identifying women with gestational diabetes mellitus who are more likely to require insulin therapy vs medical nutrition therapy (MNT) alone would allow risk stratification and early triage to be incorporated into risk-based models of care. The aim of this study was to develop and validate a model to predict therapy type (MNT or MNT plus insulin [MNT+I]) for women with gestational diabetes mellitus (GDM). Analysis was performed of de-identified prospectively collected data (1992-2015) from women diagnosed with GDM by criteria in place since 1991 and formally adopted and promulgated as part of the more detailed 1998 Australasian Diabetes in Pregnancy Society management guidelines. Clinically relevant variables predictive of insulin therapy by univariate analysis were dichotomised and included in a multivariable regression model. The model was tested in a separate clinic population. In 3317 women, seven dichotomised significant independent predictors of insulin therapy were maternal age >30 years, family history of diabetes, pre-pregnancy obesity (BMI ≥30 kg/m(2)), prior GDM, early diagnosis of GDM (<24 weeks gestation), fasting venous blood glucose level (≥5.3 mmol/l) and HbA1c at GDM diagnosis ≥5.5% (≥37 mmol/mol). The requirement for MNT+I could be estimated according to the number of predictors present: 85.7-93.1% of women with 6-7 predictors required MNT+I compared with 9.3-14.7% of women with 0-1 predictors. This model predicted the likelihood of several adverse outcomes, including Caesarean delivery, early delivery, large for gestational age and an abnormal postpartum OGTT. The model was validated in a separate clinic population. This validated model has been shown to predict therapy type and the likelihood of several adverse perinatal outcomes in women with GDM.

Simple, empirical approach to predict neutron capture cross sections from nuclear masses

NASA Astrophysics Data System (ADS)

Couture, A.; Casten, R. F.; Cakirli, R. B.

2017-12-01

Background: Neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40 % , and has limited predictive power, with predictions from different models rapidly differing by an order of magnitude a few nucleons from the last measurement. Purpose: To develop a new approach to predicting neutron capture cross sections over broad ranges of nuclei that accounts for their values where known and which has reliable predictive power with small uncertainties for many nuclei where they are unknown. Methods: Experimental neutron capture cross sections were compared to empirical mass observables in regions of similar structure. Results: We present an extremely simple method, based solely on empirical mass observables, that correlates neutron capture cross sections in the critical energy range from a few keV to a couple hundred keV. We show that regional cross sections are compactly correlated in medium and heavy mass nuclei with the two-neutron separation energy. These correlations are easily amenable to predict unknown cross sections, often converting the usual extrapolations to more reliable interpolations. It almost always reproduces existing data to within 25 % and estimated uncertainties are below about 40 % up to 10 nucleons beyond known data. Conclusions: Neutron capture cross sections display a surprisingly strong connection to the two-neutron separation energy, a nuclear structure property. The simple, empirical correlations uncovered provide model-independent predictions of neutron capture cross sections, extending far from stability, including for nuclei of the highest sensitivity to r -process nucleosynthesis.

Prediction versus aetiology: common pitfalls and how to avoid them.

PubMed

van Diepen, Merel; Ramspek, Chava L; Jager, Kitty J; Zoccali, Carmine; Dekker, Friedo W

2017-04-01

Prediction research is a distinct field of epidemiologic research, which should be clearly separated from aetiological research. Both prediction and aetiology make use of multivariable modelling, but the underlying research aim and interpretation of results are very different. Aetiology aims at uncovering the causal effect of a specific risk factor on an outcome, adjusting for confounding factors that are selected based on pre-existing knowledge of causal relations. In contrast, prediction aims at accurately predicting the risk of an outcome using multiple predictors collectively, where the final prediction model is usually based on statistically significant, but not necessarily causal, associations in the data at hand.In both scientific and clinical practice, however, the two are often confused, resulting in poor-quality publications with limited interpretability and applicability. A major problem is the frequently encountered aetiological interpretation of prediction results, where individual variables in a prediction model are attributed causal meaning. This article stresses the differences in use and interpretation of aetiological and prediction studies, and gives examples of common pitfalls. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials

DOE PAGES

Witman, Matthew; Ling, Sanliang; Jawahery, Sudi; ...

2017-03-30

For applications of metal–organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation, we develop a simple analytical model that predicts a material’s Henry regime adsorption and selectivity as a function of flexibility. We elucidate the complex dependence of selectivity on a framework’s intrinsic flexibility whereby performance is either improved or reduced with increasingmore » flexibility, depending on the material’s pore size characteristics. However, the selectivity of a material with the pore size and chemistry that already maximizes selectivity in the rigid approximation is continuously diminished with increasing flexibility, demonstrating that the globally optimal separation exists within an entirely rigid pore. Molecular simulations show that our simple model predicts performance trends that are observed when screening the adsorption behavior of flexible MOFs. These flexible simulations provide better agreement with experimental adsorption data in a high-performance material that is not captured when modeling this framework as rigid, an approximation typically made in high-throughput screening studies. We conclude that, for shape selective adsorption applications, the globally optimal material will have the optimal pore size/chemistry and minimal intrinsic flexibility even though other nonoptimal materials’ selectivity can actually be improved by flexibility. In conclusion, equally important, we find that flexible simulations can be critical for correctly modeling adsorption in these types of systems.« less

The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Witman, Matthew; Ling, Sanliang; Jawahery, Sudi

For applications of metal–organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation, we develop a simple analytical model that predicts a material’s Henry regime adsorption and selectivity as a function of flexibility. We elucidate the complex dependence of selectivity on a framework’s intrinsic flexibility whereby performance is either improved or reduced with increasingmore » flexibility, depending on the material’s pore size characteristics. However, the selectivity of a material with the pore size and chemistry that already maximizes selectivity in the rigid approximation is continuously diminished with increasing flexibility, demonstrating that the globally optimal separation exists within an entirely rigid pore. Molecular simulations show that our simple model predicts performance trends that are observed when screening the adsorption behavior of flexible MOFs. These flexible simulations provide better agreement with experimental adsorption data in a high-performance material that is not captured when modeling this framework as rigid, an approximation typically made in high-throughput screening studies. We conclude that, for shape selective adsorption applications, the globally optimal material will have the optimal pore size/chemistry and minimal intrinsic flexibility even though other nonoptimal materials’ selectivity can actually be improved by flexibility. In conclusion, equally important, we find that flexible simulations can be critical for correctly modeling adsorption in these types of systems.« less

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

PubMed Central

Peng, Yi; Xiong, Xiong; Adhikari, Kabindra; Knadel, Maria; Grunwald, Sabine; Greve, Mogens Humlekrog

2015-01-01

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R2 (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R2: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the ‘upland model’ was able to more accurately predict SOC compared with the ‘upland & wetland model’. However, the separately calibrated ‘upland and wetland model’ did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM). PMID:26555071

Alcohol-Approach Inclinations and Drinking Identity as Predictors of Behavioral Economic Demand for Alcohol

PubMed Central

Ramirez, Jason J.; Dennhardt, Ashley A.; Baldwin, Scott A.; Murphy, James G.; Lindgren, Kristen P.

2016-01-01

Behavioral economic demand curve indices of alcohol consumption reflect decisions to consume alcohol at varying costs. Although these indices predict alcohol-related problems beyond established predictors, little is known about the determinants of elevated demand. Two cognitive constructs that may underlie alcohol demand are alcohol-approach inclinations and drinking identity. The aim of this study was to evaluate implicit and explicit measures of these constructs as predictors of alcohol demand curve indices. College student drinkers (N = 223, 59% female) completed implicit and explicit measures of drinking identity and alcohol-approach inclinations at three timepoints separated by three-month intervals, and completed the Alcohol Purchase Task to assess demand at Time 3. Given no change in our alcohol-approach inclinations and drinking identity measures over time, random intercept-only models were used to predict two demand indices: Amplitude, which represents maximum hypothetical alcohol consumption and expenditures, and Persistence, which represents sensitivity to increasing prices. When modeled separately, implicit and explicit measures of drinking identity and alcohol-approach inclinations positively predicted demand indices. When implicit and explicit measures were included in the same model, both measures of drinking identity predicted Amplitude, but only explicit drinking identity predicted Persistence. In contrast, explicit measures of alcohol-approach inclinations, but not implicit measures, predicted both demand indices. Therefore, there was more support for explicit, versus implicit, measures as unique predictors of alcohol demand. Overall, drinking identity and alcohol-approach inclinations both exhibit positive associations with alcohol demand and represent potentially modifiable cognitive constructs that may underlie elevated demand in college student drinkers. PMID:27379444

Interfacial separation of a mature biofilm from a glass surface - A combined experimental and cohesive zone modelling approach.

PubMed

Safari, Ashkan; Tukovic, Zeljko; Cardiff, Philip; Walter, Maik; Casey, Eoin; Ivankovic, Alojz

2016-02-01

A good understanding of the mechanical stability of biofilms is essential for biofouling management, particularly when mechanical forces are used. Previous biofilm studies lack a damage-based theoretical model to describe the biofilm separation from a surface. The purpose of the current study was to investigate the interfacial separation of a mature biofilm from a rigid glass substrate using a combined experimental and numerical modelling approach. In the current work, the biofilm-glass interfacial separation process was investigated under tensile and shear stresses at the macroscale level, known as modes I and II failure mechanisms respectively. The numerical simulations were performed using a Finite Volume (FV)-based simulation package (OpenFOAM®) to predict the separation initiation using the cohesive zone model (CZM). Atomic force microscopy (AFM)-based retraction curve was used to obtain the separation properties between the biofilm and glass colloid at microscale level, where the CZM parameters were estimated using the Johnson-Kendall-Roberts (JKR) model. In this study CZM is introduced as a reliable method for the investigation of interfacial separation between a biofilm and rigid substrate, in which a high local stress at the interface edge acts as an ultimate stress at the crack tip.This study demonstrated that the total interfacial failure energy measured at the macroscale, was significantly higher than the pure interfacial separation energy obtained by AFM at the microscale, indicating a highly ductile deformation behaviour within the bulk biofilm matrix. The results of this study can significantly contribute to the understanding of biofilm detachments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

A TCAS-II Resolution Advisory Detection Algorithm

NASA Technical Reports Server (NTRS)

Munoz, Cesar; Narkawicz, Anthony; Chamberlain, James

2013-01-01

The Traffic Alert and Collision Avoidance System (TCAS) is a family of airborne systems designed to reduce the risk of mid-air collisions between aircraft. TCASII, the current generation of TCAS devices, provides resolution advisories that direct pilots to maintain or increase vertical separation when aircraft distance and time parameters are beyond designed system thresholds. This paper presents a mathematical model of the TCASII Resolution Advisory (RA) logic that assumes accurate aircraft state information. Based on this model, an algorithm for RA detection is also presented. This algorithm is analogous to a conflict detection algorithm, but instead of predicting loss of separation, it predicts resolution advisories. It has been formally verified that for a kinematic model of aircraft trajectories, this algorithm completely and correctly characterizes all encounter geometries between two aircraft that lead to a resolution advisory within a given lookahead time interval. The RA detection algorithm proposed in this paper is a fundamental component of a NASA sense and avoid concept for the integration of Unmanned Aircraft Systems in civil airspace.

Multi-fidelity Gaussian process regression for prediction of random fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parussini, L.; Venturi, D., E-mail: venturi@ucsc.edu; Perdikaris, P.

We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgersmore » equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.« less

Material Characterization for the Analysis of Skin/Stiffener Separation

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Leone, Frank A.; Song, Kyongchan; Ratcliffe, James G.; Rose, Cheryl A.

2017-01-01

Test results show that separation failure in co-cured skin/stiffener interfaces is characterized by dense networks of interacting cracks and crack path migrations that are not present in standard characterization tests for delamination. These crack networks result in measurable large-scale and sub-ply-scale R curve toughening mechanisms, such as fiber bridging, crack migration, and crack delving. Consequently, a number of unknown issues exist regarding the level of analysis detail that is required for sufficient predictive fidelity. The objective of the present paper is to examine some of the difficulties associated with modeling separation failure in stiffened composite structures. A procedure to characterize the interfacial material properties is proposed and the use of simplified models based on empirical interface properties is evaluated.

Accommodating subject and instrument variations in spectroscopic determinations

DOEpatents

Haas, Michael J [Albuquerque, NM; Rowe, Robert K [Corrales, NM; Thomas, Edward V [Albuquerque, NM

2006-08-29

A method and apparatus for measuring a biological attribute, such as the concentration of an analyte, particularly a blood analyte in tissue such as glucose. The method utilizes spectrographic techniques in conjunction with an improved instrument-tailored or subject-tailored calibration model. In a calibration phase, calibration model data is modified to reduce or eliminate instrument-specific attributes, resulting in a calibration data set modeling intra-instrument or intra-subject variation. In a prediction phase, the prediction process is tailored for each target instrument separately using a minimal number of spectral measurements from each instrument or subject.

Reynolds-averaged Navier-Stokes investigation of high-lift low-pressure turbine blade aerodynamics at low Reynolds number

NASA Astrophysics Data System (ADS)

Arko, Bryan M.

Design trends for the low-pressure turbine (LPT) section of modern gas turbine engines include increasing the loading per airfoil, which promises a decreased airfoil count resulting in reduced manufacturing and operating costs. Accurate Reynolds-Averaged Navier-Stokes predictions of separated boundary layers and transition to turbulence are needed, as the lack of an economical and reliable computational model has contributed to this high-lift concept not reaching its full potential. Presented here for what is believed to be the first time applied to low-Re computations of high-lift linear cascade simulations is the Abe-Kondoh-Nagano (AKN) linear low-Re two-equation turbulence model which utilizes the Kolmogorov velocity scale for improved predictions of separated boundary layers. A second turbulence model investigated is the Kato-Launder modified version of the AKN, denoted MPAKN, which damps turbulent production in highly strained regions of flow. Fully Laminar solutions have also been calculated in an effort to elucidate the transitional quality of the turbulence model solutions. Time accurate simulations of three modern high-lift blades at a Reynolds number of 25,000 are compared to experimental data and higher-order computations in order to judge the accuracy of the results, where it is shown that the RANS simulations with highly refined grids can produce both quantitatively and qualitatively similar separation behavior as found in experiments. In particular, the MPAKN model is shown to predict the correct boundary layer behavior for all three blades, and evidence of transition is found through inspection of the components of the Reynolds Stress Tensor, spectral analysis, and the turbulence production parameter. Unfortunately, definitively stating that transition is occurring becomes an uncertain task, as similar evidence of the transition process is found in the Laminar predictions. This reveals that boundary layer reattachment may be a result of laminar vortex shedding interaction with the blade surface, or that application of Laminar solvers with highly refined grids may be valid for investigations of transitional flow. It is recommended that this be studied in the future along with further studies of the turbulence models presented, which have proved to be worthy of additional study in the present application.

Fundamental Mechanisms, Predictive Modeling, and Novel Aerospace Applications of Plasma Assisted Combustion. Overview of OSU Research Plan

DTIC Science & Technology

2009-11-04

air, low-temperature plasma chemistry kinetic model Nonequilibrium Thermodynamics Laboratories The Ohio State University • Air plasma model...problems require separate analysis: • Nsec pulse plasma / sheath models cannot incorporate detailed reactive plasma chemistry : too many species ( 100...and reactions ( 1 000)~ ~ , • Detailed plasma chemistry models (quasi-neutral) cannot incorporate repetitive, nsec time scale sheath dynamics and plasma

Real-time monitoring of high-gravity corn mash fermentation using in situ raman spectroscopy.

PubMed

Gray, Steven R; Peretti, Steven W; Lamb, H Henry

2013-06-01

In situ Raman spectroscopy was employed for real-time monitoring of simultaneous saccharification and fermentation (SSF) of corn mash by an industrial strain of Saccharomyces cerevisiae. An accurate univariate calibration model for ethanol was developed based on the very strong 883 cm(-1) C-C stretching band. Multivariate partial least squares (PLS) calibration models for total starch, dextrins, maltotriose, maltose, glucose, and ethanol were developed using data from eight batch fermentations and validated using predictions for a separate batch. The starch, ethanol, and dextrins models showed significant prediction improvement when the calibration data were divided into separate high- and low-concentration sets. Collinearity between the ethanol and starch models was avoided by excluding regions containing strong ethanol peaks from the starch model and, conversely, excluding regions containing strong saccharide peaks from the ethanol model. The two-set calibration models for starch (R(2)  = 0.998, percent error = 2.5%) and ethanol (R(2)  = 0.999, percent error = 2.1%) provide more accurate predictions than any previously published spectroscopic models. Glucose, maltose, and maltotriose are modeled to accuracy comparable to previous work on less complex fermentation processes. Our results demonstrate that Raman spectroscopy is capable of real time in situ monitoring of a complex industrial biomass fermentation. To our knowledge, this is the first PLS-based chemometric modeling of corn mash fermentation under typical industrial conditions, and the first Raman-based monitoring of a fermentation process with glucose, oligosaccharides and polysaccharides present. Copyright © 2013 Wiley Periodicals, Inc.

A comparison between theoretical prediction and experimental measurement of the dynamic behavior of spur gears

NASA Technical Reports Server (NTRS)

Rebbechi, Brian; Forrester, B. David; Oswald, Fred B.; Townsend, Dennis P.

1992-01-01

A comparison was made between computer model predictions of gear dynamics behavior and experimental results. The experimental data were derived from the NASA gear noise rig, which was used to record dynamic tooth loads and vibration. The experimental results were compared with predictions from the DSTO Aeronautical Research Laboratory's gear dynamics code for a matrix of 28 load speed points. At high torque the peak dynamic load predictions agree with the experimental results with an average error of 5 percent in the speed range 800 to 6000 rpm. Tooth separation (or bounce), which was observed in the experimental data for light torque, high speed conditions, was simulated by the computer model. The model was also successful in simulating the degree of load sharing between gear teeth in the multiple tooth contact region.

Rapid Prediction of Hematologic Acute Radiation Syndrome in Radiation Injury Patients Using Peripheral Blood Cell Counts.

PubMed

Port, M; Pieper, B; Knie, T; Dörr, H; Ganser, A; Graessle, D; Meineke, V; Abend, M

2017-08-01

Rapid clinical triage of radiation injury patients is essential for determining appropriate diagnostic and therapeutic interventions. We examined the utility of blood cell counts (BCCs) in the first three days postirradiation to predict clinical outcome, specifically for hematologic acute radiation syndrome (HARS). We analyzed BCC test samples from radiation accident victims (n = 135) along with their clinical outcome HARS severity scores (H1-4) using the System for Evaluation and Archiving of Radiation Accidents based on Case Histories (SEARCH) database. Data from nonirradiated individuals (H0, n = 132) were collected from an outpatient facility. We created binary categories for severity scores, i.e., 1 (H0 vs. H1-4), 2 (H0-1 vs. H2-4) and 3 (H0-2 vs. H3-4), to assess the discrimination ability of BCCs using unconditional logistic regression analysis. The test sample contained 454 BCCs from 267 individuals. We validated the discrimination ability on a second independent group comprised of 275 BCCs from 252 individuals originating from SEARCH (HARS 1-4), an outpatient facility (H0) and hospitals (e.g., leukemia patients, H4). Individuals with a score of H0 were easily separated from exposed individuals based on developing lymphopenia and granulocytosis. The separation of H0 and H1-4 became more prominent with increasing hematologic severity scores and time. On day 1, lymphocyte counts were most predictive for discriminating binary categories, followed by granulocytes and thrombocytes. For days 2 and 3, an almost complete separation was achieved when BCCs from different days were combined, supporting the measurement of sequential BCC. We found an almost complete discrimination of H0 vs. irradiated individuals during model validation (negative predictive value, NPV > 94%) for all three days, while the correct prediction of exposed individuals increased from day 1 (positive predictive value, PPV 78-89%) to day 3 (PPV > 90%). The models were unable to provide predictions for 10.9% of the test samples, because the PPVs or NPVs did not reach a 95% likelihood defined as the lower limit for a prediction. We developed a prediction model spreadsheet to provide early and prompt diagnostic predictions and therapeutic recommendations including identification of the worried well, requirement of hospitalization or development of severe hematopoietic syndrome. These results improve the provisional classification of HARS. For the final diagnosis, further procedures (sequential diagnosis, retrospective dosimetry, clinical follow-up, etc.) must be taken into account. Clinical outcome of radiation injury patients can be rapidly predicted within the first three days postirradiation using peripheral BCC.

Model for the separate collection of packaging waste in Portuguese low-performing recycling regions.

PubMed

Oliveira, V; Sousa, V; Vaz, J M; Dias-Ferreira, C

2018-06-15

Separate collection of packaging waste (glass; plastic/metals; paper/cardboard), is currently a widespread practice throughout Europe. It enables the recovery of good quality recyclable materials. However, separate collection performance are quite heterogeneous, with some countries reaching higher levels than others. In the present work, separate collection of packaging waste has been evaluated in a low-performance recycling region in Portugal in order to investigate which factors are most affecting the performance in bring-bank collection system. The variability of separate collection yields (kg per inhabitant per year) among 42 municipalities was scrutinized for the year 2015 against possible explanatory factors. A total of 14 possible explanatory factors were analysed, falling into two groups: socio-economic/demographic and waste collection service related. Regression models were built in an attempt to evaluate the individual effect of each factor on separate collection yields and predict changes on the collection yields by acting on those factors. The best model obtained is capable to explain 73% of the variation found in the separate collection yields. The model includes the following statistically significant indicators affecting the success of separate collection yields: i) inhabitants per bring-bank; ii) relative accessibility to bring-banks; iii) degree of urbanization; iv) number of school years attended; and v) area. The model presented in this work was developed specifically for the bring-bank system, has an explanatory power and quantifies the impact of each factor on separate collection yields. It can therefore be used as a support tool by local and regional waste management authorities in the definition of future strategies to increase collection of recyclables of good quality and to achieve national and regional targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

“Dynamic evaluation of the CMAQv5.0 modeling system: Assessing the model’s ability to simulate ozone changes due to NOx emission reductions”

EPA Science Inventory

Dynamic evaluation of the CMAQv5.0 modeling system during the NOx SIP Call time period indicates that the model underestimates the observed ozone decrease in eastern U.S. Utilizing novel cross simulations we are able to separately quantify the impact on ozone predictions stemmin...

Slave to the Rhythm: Experimental Tests of a Model for Verbal Short-Term Memory and Long-Term Sequence Learning

ERIC Educational Resources Information Center

Hitch, Graham J.; Flude, Brenda; Burgess, Neil

2009-01-01

Three experiments tested predictions of a neural network model of phonological short-term memory that assumes separate representations for order and item information, order being coded via a context-timing signal [Burgess, N., & Hitch, G. J. (1999). Memory for serial order: A network model of the phonological loop and its timing. "Psychological…

Calibration of a γ- Re θ transition model and its application in low-speed flows

NASA Astrophysics Data System (ADS)

Wang, YunTao; Zhang, YuLun; Meng, DeHong; Wang, GunXue; Li, Song

2014-12-01

The prediction of laminar-turbulent transition in boundary layer is very important for obtaining accurate aerodynamic characteristics with computational fluid dynamic (CFD) tools, because laminar-turbulent transition is directly related to complex flow phenomena in boundary layer and separated flow in space. Unfortunately, the transition effect isn't included in today's major CFD tools because of non-local calculations in transition modeling. In this paper, Menter's γ- Re θ transition model is calibrated and incorporated into a Reynolds-Averaged Navier-Stokes (RANS) code — Trisonic Platform (TRIP) developed in China Aerodynamic Research and Development Center (CARDC). Based on the experimental data of flat plate from the literature, the empirical correlations involved in the transition model are modified and calibrated numerically. Numerical simulation for low-speed flow of Trapezoidal Wing (Trap Wing) is performed and compared with the corresponding experimental data. It is indicated that the γ- Re θ transition model can accurately predict the location of separation-induced transition and natural transition in the flow region with moderate pressure gradient. The transition model effectively imporves the simulation accuracy of the boundary layer and aerodynamic characteristics.

Separation of very hydrophobic analytes by micellar electrokinetic chromatography IV. Modeling of the effective electrophoretic mobility from carbon number equivalents and octanol-water partition coefficients.

PubMed

Huhn, Carolin; Pyell, Ute

2008-07-11

It is investigated whether those relationships derived within an optimization scheme developed previously to optimize separations in micellar electrokinetic chromatography can be used to model effective electrophoretic mobilities of analytes strongly differing in their properties (polarity and type of interaction with the pseudostationary phase). The modeling is based on two parameter sets: (i) carbon number equivalents or octanol-water partition coefficients as analyte descriptors and (ii) four coefficients describing properties of the separation electrolyte (based on retention data for a homologous series of alkyl phenyl ketones used as reference analytes). The applicability of the proposed model is validated comparing experimental and calculated effective electrophoretic mobilities. The results demonstrate that the model can effectively be used to predict effective electrophoretic mobilities of neutral analytes from the determined carbon number equivalents or from octanol-water partition coefficients provided that the solvation parameters of the analytes of interest are similar to those of the reference analytes.

Predictive modeling of infrared radiative heating in tomato dry-peeling process: Part I. Model development

USDA-ARS?s Scientific Manuscript database

Infrared (IR) dry-peeling has emerged as an effective non-chemical alternative to conventional lye and steam methods of peeling tomatoes. Successful peel separation induced by IR radiation requires the delivery of a sufficient amount of thermal energy onto tomato surface in a very short duration. Th...

A Four-Part Model of Autonomy during Emerging Adulthood: Associations with Adjustment

ERIC Educational Resources Information Center

Lamborn, Susie D.; Groh, Kelly

2009-01-01

We found support for a four-part model of autonomy that links connectedness, separation, detachment, and agency to adjustment during emerging adulthood. Based on self-report surveys of 285 American college students, expected associations among the autonomy variables were found. In addition, agency, as measured by self-reliance, predicted lower…

Patterns of Interaction in Family Relationships and the Development of Identity Exploration in Adolescence.

ERIC Educational Resources Information Center

Grotevant, Harold D.; Cooper, Catherine R.

1985-01-01

Developed a model of individuation in family relationships focused on communicative processes. Expressions of four dimensions of the model (self-esteem, separateness, permeability, and mutuality) were predicted to be positively associated with identity exploration in adolescents. Analysis of observations of families in a Family Interaction Task…

Automated use of mutagenesis data in structure prediction.

PubMed

Nanda, Vikas; DeGrado, William F

2005-05-15

In the absence of experimental structural determination, numerous methods are available to indirectly predict or probe the structure of a target molecule. Genetic modification of a protein sequence is a powerful tool for identifying key residues involved in binding reactions or protein stability. Mutagenesis data is usually incorporated into the modeling process either through manual inspection of model compatibility with empirical data, or through the generation of geometric constraints linking sensitive residues to a binding interface. We present an approach derived from statistical studies of lattice models for introducing mutation information directly into the fitness score. The approach takes into account the phenotype of mutation (neutral or disruptive) and calculates the energy for a given structure over an ensemble of sequences. The structure prediction procedure searches for the optimal conformation where neutral sequences either have no impact or improve stability and disruptive sequences reduce stability relative to wild type. We examine three types of sequence ensembles: information from saturation mutagenesis, scanning mutagenesis, and homologous proteins. Incorporating multiple sequences into a statistical ensemble serves to energetically separate the native state and misfolded structures. As a result, the prediction of structure with a poor force field is sufficiently enhanced by mutational information to improve accuracy. Furthermore, by separating misfolded conformations from the target score, the ensemble energy serves to speed up conformational search algorithms such as Monte Carlo-based methods. Copyright 2005 Wiley-Liss, Inc.

Potential-based and non-potential-based cohesive zone formulations under mixed-mode separation and over-closure-Part II: Finite element applications

NASA Astrophysics Data System (ADS)

Máirtín, Éamonn Ó.; Parry, Guillaume; Beltz, Glenn E.; McGarry, J. Patrick

2014-02-01

This paper, the second of two parts, presents three novel finite element case studies to demonstrate the importance of normal-tangential coupling in cohesive zone models (CZMs) for the prediction of mixed-mode interface debonding. Specifically, four new CZMs proposed in Part I of this study are implemented, namely the potential-based MP model and the non-potential-based NP1, NP2 and SMC models. For comparison, simulations are also performed for the well established potential-based Xu-Needleman (XN) model and the non-potential-based model of van den Bosch, Schreurs and Geers (BSG model). Case study 1: Debonding and rebonding of a biological cell from a cyclically deforming silicone substrate is simulated when the mode II work of separation is higher than the mode I work of separation at the cell-substrate interface. An active formulation for the contractility and remodelling of the cell cytoskeleton is implemented. It is demonstrated that when the XN potential function is used at the cell-substrate interface repulsive normal tractions are computed, preventing rebonding of significant regions of the cell to the substrate. In contrast, the proposed MP potential function at the cell-substrate interface results in negligible repulsive normal tractions, allowing for the prediction of experimentally observed patterns of cell cytoskeletal remodelling. Case study 2: Buckling of a coating from the compressive surface of a stent is simulated. It is demonstrated that during expansion of the stent the coating is initially compressed into the stent surface, while simultaneously undergoing tangential (shear) tractions at the coating-stent interface. It is demonstrated that when either the proposed NP1 or NP2 model is implemented at the stent-coating interface mixed-mode over-closure is correctly penalised. Further expansion of the stent results in the prediction of significant buckling of the coating from the stent surface, as observed experimentally. In contrast, the BSG model does not correctly penalise mixed-mode over-closure at the stent-coating interface, significantly altering the stress state in the coating and preventing the prediction of buckling. Case study 3: Application of a displacement to the base of a bi-layered composite arch results in a symmetric sinusoidal distribution of normal and tangential traction at the arch interface. The traction defined mode mixity at the interface ranges from pure mode II at the base of the arch to pure mode I at the top of the arch. It is demonstrated that predicted debonding patterns are highly sensitive to normal-tangential coupling terms in a CZM. The NP2, XN, and BSG models exhibit a strong bias towards mode I separation at the top of the arch, while the NP1 model exhibits a bias towards mode II debonding at the base of the arch. Only the SMC model provides mode-independent behaviour in the early stages of debonding. This case study provides a practical example of the importance of the behaviour of CZMs under conditions of traction controlled mode mixity, following from the theoretical analysis presented in Part I of this study.

Numerical Prediction of SERN Performance using WIND code

NASA Technical Reports Server (NTRS)

Engblom, W. A.

2003-01-01

Computational results are presented for the performance and flow behavior of single-expansion ramp nozzles (SERNs) during overexpanded operation and transonic flight. Three-dimensional Reynolds-Averaged Navier Stokes (RANS) results are obtained for two vehicle configurations, including the NASP Model 5B and ISTAR RBCC (a variant of X-43B) using the WIND code. Numerical predictions for nozzle integrated forces and pitch moments are directly compared to experimental data for the NASP Model 5B, and adequate-to-excellent agreement is found. The sensitivity of SERN performance and separation phenomena to freestream static pressure and Mach number is demonstrated via a matrix of cases for both vehicles. 3-D separation regions are shown to be induced by either lateral (e.g., sidewall) shocks or vertical (e.g., cowl trailing edge) shocks. Finally, the implications of this work to future preliminary design efforts involving SERNs are discussed.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Effects of turbulence modelling on prediction of flow characteristics in a bench-scale anaerobic gas-lift digester.

PubMed

Coughtrie, A R; Borman, D J; Sleigh, P A

2013-06-01

Flow in a gas-lift digester with a central draft-tube was investigated using computational fluid dynamics (CFD) and different turbulence closure models. The k-ω Shear-Stress-Transport (SST), Renormalization-Group (RNG) k-∊, Linear Reynolds-Stress-Model (RSM) and Transition-SST models were tested for a gas-lift loop reactor under Newtonian flow conditions validated against published experimental work. The results identify that flow predictions within the reactor (where flow is transitional) are particularly sensitive to the turbulence model implemented; the Transition-SST model was found to be the most robust for capturing mixing behaviour and predicting separation reliably. Therefore, Transition-SST is recommended over k-∊ models for use in comparable mixing problems. A comparison of results obtained using multiphase Euler-Lagrange and singlephase approaches are presented. The results support the validity of the singlephase modelling assumptions in obtaining reliable predictions of the reactor flow. Solver independence of results was verified by comparing two independent finite-volume solvers (Fluent-13.0sp2 and OpenFOAM-2.0.1). Copyright © 2013 Elsevier Ltd. All rights reserved.

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

NASA Technical Reports Server (NTRS)

Karr, David A.; Vivona, Robert A.; Woods, Sharon E.; Wing, David J.

2017-01-01

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

Male-initiated partner abuse during marital separation prior to divorce.

PubMed

Toews, Michelle L; McKenry, Patrick C; Catlett, Beth S

2003-08-01

The purpose of this study was to assess predictors of male-initiated psychological and physical partner abuse during the separation process prior to divorce among a sample of 80 divorced fathers who reported no physical violence during their marriages. The predictor variables examined were male gender-role identity, female-initiated divorces, dependence on one's former wife, depression, anxiety, and coparental conflict. Through ordinary least square (OLS) regression techniques, it was found that male gender-role identity was positively related to male-initiated psychological abuse during separation. Logistic regression analyses revealed that male-initiated psychological abuse, anxiety level, coparental conflict, and dependence on one's former spouse increased the odds of a man engaging in physical abuse. However, depression decreased the odds of separation physical abuse. The models predicting both male-initiated psychological abuse (F = 2.20, p < .05, R2 = .15) and physical violence during the separation process were significant (Model chi2 = 35.00, df= 7, p < .001).

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

PubMed

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

New test techniques to evaluate near field effects for supersonic store carriage and separation

NASA Technical Reports Server (NTRS)

Sawyer, Wallace C.; Stallings, Robert L., Jr.; Wilcox, Floyd J., Jr.; Blair, A. B., Jr.; Monta, William J.; Plentovich, Elizabeth B.

1989-01-01

Store separation and store carriage drag studies were conducted. A primary purpose is to develop new experimental methods to evaluate near field effects of store separation and levels of store carriage drag associated with a variety of carriage techniques for different store shapes and arrangements. Flow field measurements consisting of surface pressure distributions and vapor screen photographs are used to analyze the variations of the store separation characteristics with cavity geometry. Store carriage drag measurements representative of tangent, semi-submerged, and internal carriage installations are presented and discussed. Results are included from both fully metric models and models with only metric segments (metric pallets) and the relative merits of the two are discussed. Carriage drag measurements for store installations on an aircraft parent body are compared both with prediction methods and with installations on a generic parent body.

Line active hybrid lipids determine domain size in phase separation of saturated and unsaturated lipids.

PubMed

Brewster, Robert; Safran, Samuel A

2010-03-17

A simple model of the line activity of a hybrid lipid (e.g., POPC) with one fully saturated chain and one partially unsaturated chain demonstrates that these lipids preferentially pack at curved interfaces between phase-separated saturated and unsaturated domains. We predict that the domain sizes typically range from tens to hundreds of nm, depending on molecular interactions and parameters such as molecular volume and area per headgroup in the bulk fluid phase. The role of cholesterol is taken into account by an effective change in the headgroup areas and the domain sizes are predicted to increase with cholesterol concentration. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

VORCOR: A computer program for calculating characteristics of wings with edge vortex separation by using a vortex-filament and-core model

NASA Technical Reports Server (NTRS)

Pao, J. L.; Mehrotra, S. C.; Lan, C. E.

1982-01-01

A computer code base on an improved vortex filament/vortex core method for predicting aerodynamic characteristics of slender wings with edge vortex separations is developed. The code is applicable to camber wings, straked wings or wings with leading edge vortex flaps at subsonic speeds. The prediction of lifting pressure distribution and the computer time are improved by using a pair of concentrated vortex cores above the wing surface. The main features of this computer program are: (1) arbitrary camber shape may be defined and an option for exactly defining leading edge flap geometry is also provided; (2) the side edge vortex system is incorporated.

A three-dimensional turbulent separated flow and related mesurements

NASA Technical Reports Server (NTRS)

Pierce, F. J.

1985-01-01

The applicability of and the limits on the applicability of 11 near wall similarity laws characterizing three-dimensional turbulent boundary layer flows were determined. A direct force sensing local wall shear stress meter was used in both pressure-driven and shear-driven three-dimensional turbulent boundary layers, together with extensive mean velocity field and wall pressure field data. This resulted in a relatively large number of graphical comparisons of the predictive ability of 10 of these 11 similarity models relative to measured data over a wide range of flow conditions. Documentation of a complex, separated three-dimensional turbulent flow as a standard test case for evaluating the predictive ability of numerical codes solving such flows is presented.

Investigation of rotor blade element airloads for a teetering rotor in the blade stall regime

NASA Technical Reports Server (NTRS)

Dadone, L. U.; Fukushima, T.

1974-01-01

A model of a teetering rotor was tested in a low speed wind tunnel. Blade element airloads measured on an articulated model rotor were compared with the teetering rotor and showed that the teetering rotor is subjected to less extensive flow separation. Retreating blade stall was studied. Results show that stall, under the influence of unsteady aerodynamic effects, consists of four separate stall events, each associated with a vortex shed from the leading edge and sweeping over the upper surface of the rotor blade. Current rotor performance prediction methodology was evaluated through computer simulation.

Northward migration under a changing climate: a case study of blackgum (Nyssa Sylvatica)

Treesearch

Johanna Desprez; Basil V. Iannone III; Peilin Yang; Christopher M. Oswalt; Songlin Fei

2014-01-01

Species are predicted to shift their distribution ranges in response to climate change. Region-wide, empirically-based studies, however, are still limited to support these predictions. We used a model tree species, blackgum (Nyssa sylvatica), to study climate-induced range shift. Data collected from two separate sampling periods (1980s and 2007) by the USDA’s Forestry...

Ares I-X Flight Evaluation Tasks in Support of Ares I Development

NASA Technical Reports Server (NTRS)

Huebner, Lawrence D.; Richards, James S.; Coates, Ralph H., III; Cruit, Wendy D.; Ramsey, Matthew N.

2010-01-01

NASA s Constellation Program successfully launched the Ares I-X Flight Test Vehicle on October 28, 2009. The Ares I-X flight was a development flight test that offered a unique opportunity for early engineering data to impact the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office established a set of 33 flight evaluation tasks to correlate fight results with prospective design assumptions and models. Included within these tasks were direct comparisons of flight data with pre-flight predictions and post-flight assessments utilizing models and modeling techniques being applied to design and develop Ares I. A discussion of the similarities and differences in those comparisons and the need for discipline-level model updates based upon those comparisons form the substance of this paper. The benefits of development flight testing were made evident by implementing these tasks that used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. The areas in which partial validation from the flight test was most significant included flight control system algorithms to predict liftoff clearance, ascent, and stage separation; structural models from rollout to separation; thermal models that have been updated based on these data; pyroshock attenuation; and the ability to predict complex flow fields during time-varying conditions including plume interactions.

Computation of Separated and Unsteady Flows with One- and Two-Equation Turbulence Models

NASA Technical Reports Server (NTRS)

Ekaterinaris, John A.; Menter, Florian R.

1994-01-01

The ability of one- and two-equation turbulence models to predict unsteady separated flows over airfoils is evaluated. An implicit, factorized, upwind-biased numerical scheme is used for the integration of the compressible, Reynolds averaged Navier-Stokes equations. The turbulent eddy viscosity is obtained from the computed mean flowfield by integration of the turbulent field equations. The two-equation turbulence models are discretized in space with an upwind-biased, second order accurate total variation diminishing scheme. One and two-equation turbulence models are first tested for a separated airfoil flow at fixed angle of incidence. The same models are then applied to compute the unsteady flowfields about airfoils undergoing oscillatory motion at low subsonic Mach numbers. Experimental cases where the flow has been tripped at the leading edge and where natural transition was allowed to occur naturally are considered. The more recently developed field-equation turbulence models capture the physics of unsteady separated flow significantly better than the standard kappa-epsilon and kappa-omega models. However, certain differences in the hysteresis effects are obtained. For an untripped high-Reynolds-number flow, it was found necessary to take into account the leading edge transitional flow region in order to capture the correct physical mechanism that leads to dynamic stall.

Probabilistic Modeling of Aircraft Trajectories for Dynamic Separation Volumes

NASA Technical Reports Server (NTRS)

Lewis, Timothy A.

2016-01-01

With a proliferation of new and unconventional vehicles and operations expected in the future, the ab initio airspace design will require new approaches to trajectory prediction for separation assurance and other air traffic management functions. This paper presents an approach to probabilistic modeling of the trajectory of an aircraft when its intent is unknown. The approach uses a set of feature functions to constrain a maximum entropy probability distribution based on a set of observed aircraft trajectories. This model can be used to sample new aircraft trajectories to form an ensemble reflecting the variability in an aircraft's intent. The model learning process ensures that the variability in this ensemble reflects the behavior observed in the original data set. Computational examples are presented.

A gravitationally lensed quasar with quadruple images separated by 14.62 arcseconds.

PubMed

Inada, Naohisa; Oguri, Masamune; Pindor, Bartosz; Hennawi, Joseph F; Chiu, Kuenley; Zheng, Wei; Ichikawa, Shin-Ichi; Gregg, Michael D; Becker, Robert H; Suto, Yasushi; Strauss, Michael A; Turner, Edwin L; Keeton, Charles R; Annis, James; Castander, Francisco J; Eisenstein, Daniel J; Frieman, Joshua A; Fukugita, Masataka; Gunn, James E; Johnston, David E; Kent, Stephen M; Nichol, Robert C; Richards, Gordon T; Rix, Hans-Walter; Sheldon, Erin Scott; Bahcall, Neta A; Brinkmann, J; Ivezić, Zeljko; Lamb, Don Q; McKay, Timothy A; Schneider, Donald P; York, Donald G

2003-12-18

Gravitational lensing is a powerful tool for the study of the distribution of dark matter in the Universe. The cold-dark-matter model of the formation of large-scale structures (that is, clusters of galaxies and even larger assemblies) predicts the existence of quasars gravitationally lensed by concentrations of dark matter so massive that the quasar images would be split by over 7 arcsec. Numerous searches for large-separation lensed quasars have, however, been unsuccessful. All of the roughly 70 lensed quasars known, including the first lensed quasar discovered, have smaller separations that can be explained in terms of galaxy-scale concentrations of baryonic matter. Although gravitationally lensed galaxies with large separations are known, quasars are more useful cosmological probes because of the simplicity of the resulting lens systems. Here we report the discovery of a lensed quasar, SDSS J1004 + 4112, which has a maximum separation between the components of 14.62 arcsec. Such a large separation means that the lensing object must be dominated by dark matter. Our results are fully consistent with theoretical expectations based on the cold-dark-matter model.

Separation of m-cresol from neutral oils with liquid-liquid extraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Venter, D.L.; Nieuwoudt

Coal pyrolysis liquors are a major source of valuable phenolic compounds. In this study, the separation of m-cresol from neutral oils by means of liquid-liquid extraction is investigated. Liquid-liquid equilibria for the systems m-cresol + o-toluonitrile + hexane + water + tetraethylene glycol + undecane + dodecane and m-cresol + o-toluonitrile + hexane + water + tetraethylene glycol have bee determined at 313.15 K in order to evaluate the suitability of tetraethylene glycol as a high-boiling solvent for the separation of m-cresol from neutral oils. The effect of parameters such as solvent ratios on the desired separation were investigated. Thesemore » are illustrated on the basis of separation factors, percentage of feed o-toluonitrile remaining in the solvent phase, and percentage recovery of m-cresol. From the experimental results it was concluded that tetraethylene glycol is suitable for the proposed separation. The nonrandom two-liquid model fitted the experimental data satisfactorily. The model was used in the simulation of a multistage extraction column. m-Cresol recoveries of greater than 97% and m-cresol purity of greater than 99.5% were predicted.« less

Optimal SVM parameter selection for non-separable and unbalanced datasets.

PubMed

Jiang, Peng; Missoum, Samy; Chen, Zhao

2014-10-01

This article presents a study of three validation metrics used for the selection of optimal parameters of a support vector machine (SVM) classifier in the case of non-separable and unbalanced datasets. This situation is often encountered when the data is obtained experimentally or clinically. The three metrics selected in this work are the area under the ROC curve (AUC), accuracy, and balanced accuracy. These validation metrics are tested using computational data only, which enables the creation of fully separable sets of data. This way, non-separable datasets, representative of a real-world problem, can be created by projection onto a lower dimensional sub-space. The knowledge of the separable dataset, unknown in real-world problems, provides a reference to compare the three validation metrics using a quantity referred to as the "weighted likelihood". As an application example, the study investigates a classification model for hip fracture prediction. The data is obtained from a parameterized finite element model of a femur. The performance of the various validation metrics is studied for several levels of separability, ratios of unbalance, and training set sizes.

Sound transmission through stiffened double-panel structures lined with elastic porous materials

NASA Astrophysics Data System (ADS)

Mathur, Gopal P.; Tran, Boi N.; Bolton, J. S.; Shiau, Nae-Ming

This paper presents transmission loss prediction models for a periodically stiffened panel and stiffened double-panel structures using the periodic structure theory. The inter-panel cavity in the double-panels structures can be modeled as being separated by an airspace or filled with an elastic porous layer in various configurations. The acoustic behavior of elastic porous layer is described by a theory capable of accounting fully for multi-dimensional wave propagation in such materials. The predicted transmission loss of a single stiffened panel is compared with the measured data.

Changes at work and employee reactions: organizational elements, job insecurity, and short-term stress as predictors for employee health and safety.

PubMed

Størseth, Fred

2006-12-01

The objective was to identify focus areas for possible reduction of job insecurity and its outcomes. A model was specified and tested as a prediction model for health and safety. First, a parsimonious model was specified. The model consisted of perceived job insecurity (as a stressor), organizational factors (information quality, leadership style, work task administration), and short-term stress reactions (job dissatisfaction, reduced work motivation). Second, the model was tested as a prediction model in three separate path analyses, in order to examine the model's contribution in explaining (1) physical health complaints, (2) mental health complaints, and (3) risk taking behavior. A quota sample of Norwegian employees (N= 1,002) was obtained by means of a self-completion questionnaire survey. The results of the structural equation modeling (path analyses) supported the hypothesized model. Mental health complaints and employee risk taking behavior were significantly predicted (not physical health complaints).

A semiparametric spatio-temporal model for solar irradiance data

DOE PAGES

Patrick, Joshua D.; Harvill, Jane L.; Hansen, Clifford W.

2016-03-01

Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance atmore » high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.« less

External validation of EPIWIN biodegradation models.

PubMed

Posthumus, R; Traas, T P; Peijnenburg, W J G M; Hulzebos, E M

2005-01-01

The BIOWIN biodegradation models were evaluated for their suitability for regulatory purposes. BIOWIN includes the linear and non-linear BIODEG and MITI models for estimating the probability of rapid aerobic biodegradation and an expert survey model for primary and ultimate biodegradation estimation. Experimental biodegradation data for 110 newly notified substances were compared with the estimations of the different models. The models were applied separately and in combinations to determine which model(s) showed the best performance. The results of this study were compared with the results of other validation studies and other biodegradation models. The BIOWIN models predict not-readily biodegradable substances with high accuracy in contrast to ready biodegradability. In view of the high environmental concern of persistent chemicals and in view of the large number of not-readily biodegradable chemicals compared to the readily ones, a model is preferred that gives a minimum of false positives without a corresponding high percentage false negatives. A combination of the BIOWIN models (BIOWIN2 or BIOWIN6) showed the highest predictive value for not-readily biodegradability. However, the highest score for overall predictivity with lowest percentage false predictions was achieved by applying BIOWIN3 (pass level 2.75) and BIOWIN6.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Cliff

2015-01-01

Empirical models for the shielding and refection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and rejection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Empirical Models for the Shielding and Reflection of Jet Mixing Noise by a Surface

NASA Technical Reports Server (NTRS)

Brown, Clifford A.

2016-01-01

Empirical models for the shielding and reflection of jet mixing noise by a nearby surface are described and the resulting models evaluated. The flow variables are used to non-dimensionalize the surface position variables, reducing the variable space and producing models that are linear function of non-dimensional surface position and logarithmic in Strouhal frequency. A separate set of coefficients are determined at each observer angle in the dataset and linear interpolation is used to for the intermediate observer angles. The shielding and reflection models are then combined with existing empirical models for the jet mixing and jet-surface interaction noise sources to produce predicted spectra for a jet operating near a surface. These predictions are then evaluated against experimental data.

Defining Aggressive Prostate Cancer Using a 12-Gene Model1

PubMed Central

Riva, Alberto; Kim, Robert; Varambally, Sooryanarayana; He, Le; Kutok, Jeff; Aster, Jonathan C; Tang, Jeffery; Kuefer, Rainer; Hofer, Matthias D; Febbo, Phillip G; Chinnaiyan, Arul M; Rubin, Mark A

2006-01-01

Abstract The critical clinical question in prostate cancer research is: How do we develop means of distinguishing aggressive disease from indolent disease? Using a combination of proteomic and expression array data, we identified a set of 36 genes with concordant dysregulation of protein products that could be evaluated in situ by quantitative immunohistochemistry. Another five prostate cancer biomarkers were included using linear discriminant analysis, we determined that the optimal model used to predict prostate cancer progression consisted of 12 proteins. Using a separate patient population, transcriptional levels of the 12 genes encoding for these proteins predicted prostate-specific antigen failure in 79 men following surgery for clinically localized prostate cancer (P = .0015). This study demonstrates that cross-platform models can lead to predictive models with the possible advantage of being more robust through this selection process. PMID:16533427

A drift-diffusion checkpoint model predicts a highly variable and growth-factor-sensitive portion of the cell cycle G1 phase.

PubMed

Jones, Zack W; Leander, Rachel; Quaranta, Vito; Harris, Leonard A; Tyson, Darren R

2018-01-01

Even among isogenic cells, the time to progress through the cell cycle, or the intermitotic time (IMT), is highly variable. This variability has been a topic of research for several decades and numerous mathematical models have been proposed to explain it. Previously, we developed a top-down, stochastic drift-diffusion+threshold (DDT) model of a cell cycle checkpoint and showed that it can accurately describe experimentally-derived IMT distributions [Leander R, Allen EJ, Garbett SP, Tyson DR, Quaranta V. Derivation and experimental comparison of cell-division probability densities. J. Theor. Biol. 2014;358:129-135]. Here, we use the DDT modeling approach for both descriptive and predictive data analysis. We develop a custom numerical method for the reliable maximum likelihood estimation of model parameters in the absence of a priori knowledge about the number of detectable checkpoints. We employ this method to fit different variants of the DDT model (with one, two, and three checkpoints) to IMT data from multiple cell lines under different growth conditions and drug treatments. We find that a two-checkpoint model best describes the data, consistent with the notion that the cell cycle can be broadly separated into two steps: the commitment to divide and the process of cell division. The model predicts one part of the cell cycle to be highly variable and growth factor sensitive while the other is less variable and relatively refractory to growth factor signaling. Using experimental data that separates IMT into G1 vs. S, G2, and M phases, we show that the model-predicted growth-factor-sensitive part of the cell cycle corresponds to a portion of G1, consistent with previous studies suggesting that the commitment step is the primary source of IMT variability. These results demonstrate that a simple stochastic model, with just a handful of parameters, can provide fundamental insights into the biological underpinnings of cell cycle progression.

Modeling of the interfacial separation work in relation to impurity concentration in adjoining materials

NASA Astrophysics Data System (ADS)

Alekseev, Ilia M.; Makhviladze, Tariel M.; Minushev, Airat Kh.; Sarychev, Mikhail E.

2009-10-01

On the basis of the general thermodynamic approach developed in a model describing the influence of point defects on the separation work at an interface of solid materials is developed. The kinetic equations describing the defect exchange between the interface and the material bulks are formulated. The model have been applied to the case when joined materials contain such point defects as impurity atoms (interstitial and substitutional), concretized the main characteristic parameters required for a numerical modeling as well as clarified their domains of variability. The results of the numerical modeling concerning the dependences on impurity concentrations and the temperature dependences are obtained and analyzed. Particularly, the effects of interfacial strengthening and adhesion incompatibility predicted analytically for the case of impurity atoms are verified and analyzed.

Modeling of the interfacial separation work in relation to impurity concentration in adjoining materials

NASA Astrophysics Data System (ADS)

Alekseev, Ilia M.; Makhviladze, Tariel M.; Minushev, Airat Kh.; Sarychev, Mikhail E.

2010-02-01

On the basis of the general thermodynamic approach developed in a model describing the influence of point defects on the separation work at an interface of solid materials is developed. The kinetic equations describing the defect exchange between the interface and the material bulks are formulated. The model have been applied to the case when joined materials contain such point defects as impurity atoms (interstitial and substitutional), concretized the main characteristic parameters required for a numerical modeling as well as clarified their domains of variability. The results of the numerical modeling concerning the dependences on impurity concentrations and the temperature dependences are obtained and analyzed. Particularly, the effects of interfacial strengthening and adhesion incompatibility predicted analytically for the case of impurity atoms are verified and analyzed.

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

PubMed

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

A novel method for landslide displacement prediction by integrating advanced computational intelligence algorithms.

PubMed

Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Fu, Xiaolin

2018-05-08

Landslide displacement prediction is considered as an essential component for developing early warning systems. The modelling of conventional forecast methods requires enormous monitoring data that limit its application. To conduct accurate displacement prediction with limited data, a novel method is proposed and applied by integrating three computational intelligence algorithms namely: the wavelet transform (WT), the artificial bees colony (ABC), and the kernel-based extreme learning machine (KELM). At first, the total displacement was decomposed into several sub-sequences with different frequencies using the WT. Next each sub-sequence was predicted separately by the KELM whose parameters were optimized by the ABC. Finally the predicted total displacement was obtained by adding all the predicted sub-sequences. The Shuping landslide in the Three Gorges Reservoir area in China was taken as a case study. The performance of the new method was compared with the WT-ELM, ABC-KELM, ELM, and the support vector machine (SVM) methods. Results show that the prediction accuracy can be improved by decomposing the total displacement into sub-sequences with various frequencies and by predicting them separately. The ABC-KELM algorithm shows the highest prediction capacity followed by the ELM and SVM. Overall, the proposed method achieved excellent performance both in terms of accuracy and stability.

How uncertain is model-based prediction of copper loads in stormwater runoff?

PubMed

Lindblom, E; Ahlman, S; Mikkelsen, P S

2007-01-01

In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.

Notes on the Prediction of Shock-induced Boundary-layer Separation

NASA Technical Reports Server (NTRS)

Lange, Roy H.

1953-01-01

The present status of available information relative to the prediction of shock-induced boundary-layer separation is discussed. Experimental results showing the effects of Reynolds number and Mach number on the separation of both laminar and turbulent boundary layer are given and compared with available methods for predicting separation. The flow phenomena associated with separation caused by forward-facing steps, wedges, and incident shock waves are discussed. Applications of the flat-plate data to problems of separation on spoilers, diffusers, and scoop inlets are indicated for turbulent boundary layers.

Computational methods for unsteady transonic flows

NASA Technical Reports Server (NTRS)

Edwards, John W.; Thomas, J. L.

1987-01-01

Computational methods for unsteady transonic flows are surveyed with emphasis on prediction. Computational difficulty is discussed with respect to type of unsteady flow; attached, mixed (attached/separated) and separated. Significant early computations of shock motions, aileron buzz and periodic oscillations are discussed. The maturation of computational methods towards the capability of treating complete vehicles with reasonable computational resources is noted and a survey of recent comparisons with experimental results is compiled. The importance of mixed attached and separated flow modeling for aeroelastic analysis is discussed, and recent calculations of periodic aerodynamic oscillations for an 18 percent thick circular arc airfoil are given.

The prediction of zenith range refraction from surface measurements of meteorological parameters. [mathematical models of atmospheric refraction used to improve spacecraft tracking space navigation

NASA Technical Reports Server (NTRS)

Berman, A. L.

1976-01-01

In the last two decades, increasingly sophisticated deep space missions have placed correspondingly stringent requirements on navigational accuracy. As part of the effort to increase navigational accuracy, and hence the quality of radiometric data, much effort has been expended in an attempt to understand and compute the tropospheric effect on range (and hence range rate) data. The general approach adopted has been that of computing a zenith range refraction, and then mapping this refraction to any arbitrary elevation angle via an empirically derived function of elevation. The prediction of zenith range refraction derived from surface measurements of meteorological parameters is presented. Refractivity is separated into wet (water vapor pressure) and dry (atmospheric pressure) components. The integration of dry refractivity is shown to be exact. Attempts to integrate wet refractivity directly prove ineffective; however, several empirical models developed by the author and other researchers at JPL are discussed. The best current wet refraction model is here considered to be a separate day/night model, which is proportional to surface water vapor pressure and inversely proportional to surface temperature. Methods are suggested that might improve the accuracy of the wet range refraction model.

A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities

NASA Astrophysics Data System (ADS)

Vallières, M.; Freeman, C. R.; Skamene, S. R.; El Naqa, I.

2015-07-01

This study aims at developing a joint FDG-PET and MRI texture-based model for the early evaluation of lung metastasis risk in soft-tissue sarcomas (STSs). We investigate if the creation of new composite textures from the combination of FDG-PET and MR imaging information could better identify aggressive tumours. Towards this goal, a cohort of 51 patients with histologically proven STSs of the extremities was retrospectively evaluated. All patients had pre-treatment FDG-PET and MRI scans comprised of T1-weighted and T2-weighted fat-suppression sequences (T2FS). Nine non-texture features (SUV metrics and shape features) and forty-one texture features were extracted from the tumour region of separate (FDG-PET, T1 and T2FS) and fused (FDG-PET/T1 and FDG-PET/T2FS) scans. Volume fusion of the FDG-PET and MRI scans was implemented using the wavelet transform. The influence of six different extraction parameters on the predictive value of textures was investigated. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. Univariate analysis showed that the isotropic voxel size at which texture features were extracted had the most impact on predictive value. In multivariable analysis, texture features extracted from fused scans significantly outperformed those from separate scans in terms of lung metastases prediction estimates. The best performance was obtained using a combination of four texture features extracted from FDG-PET/T1 and FDG-PET/T2FS scans. This model reached an area under the receiver-operating characteristic curve of 0.984 ± 0.002, a sensitivity of 0.955 ± 0.006, and a specificity of 0.926 ± 0.004 in bootstrapping evaluations. Ultimately, lung metastasis risk assessment at diagnosis of STSs could improve patient outcomes by allowing better treatment adaptation.

Accurate Theoretical Predictions of the Properties of Energetic Materials

DTIC Science & Technology

2008-09-18

decomposition, Monte Carlo, molecular dynamics, supercritical fluids, solvation and separation, quantum Monte Carlo, potential energy surfaces, RDX , TNAZ...labs, who are contributing to the theoretical efforts, providing data for testing of the models, or aiding in the transition of the methods, models...and results to DoD applications. The major goals of the project are: • Models that describe phase transitions and chemical reactions in

Modification of the MML turbulence model for adverse pressure gradient flows. M.S. Thesis - Akron Univ., 1993

NASA Technical Reports Server (NTRS)

Conley, Julianne M.

1994-01-01

Computational fluid dynamics is being used increasingly to predict flows for aerospace propulsion applications, yet there is still a need for an easy to use, computationally inexpensive turbulence model capable of accurately predicting a wide range of turbulent flows. The Baldwin-Lomax model is the most widely used algebraic model, even though it has known difficulties calculating flows with strong adverse pressure gradients and large regions of separation. The modified mixing length model (MML) was developed specifically to handle the separation which occurs on airfoils and has given significantly better results than the Baldwin-Lomax model. The success of these calculations warrants further evaluation and development of MML. The objective of this work was to evaluate the performance of MML for zero and adverse pressure gradient flows, and modify it as needed. The Proteus Navier-Stokes code was used for this study and all results were compared with experimental data and with calculations made using the Baldwin-Lomax algebraic model, which is currently available in Proteus. The MML model was first evaluated for zero pressure gradient flow over a flat plate, then modified to produce the proper boundary layer growth. Additional modifications, based on experimental data for three adverse pressure gradient flows, were also implemented. The adapted model, called MMLPG (modified mixing length model for pressure gradient flows), was then evaluated for a typical propulsion flow problem, flow through a transonic diffuser. Three cases were examined: flow with no shock, a weak shock and a strong shock. The results of these calculations indicate that the objectives of this study have been met. Overall, MMLPG is capable of accurately predicting the adverse pressure gradient flows examined in this study, giving generally better agreement with experimental data than the Baldwin-Lomax model.

Relating Cohesive Zone Model to Linear Elastic Fracture Mechanics

NASA Technical Reports Server (NTRS)

Wang, John T.

2010-01-01

The conditions required for a cohesive zone model (CZM) to predict a failure load of a cracked structure similar to that obtained by a linear elastic fracture mechanics (LEFM) analysis are investigated in this paper. This study clarifies why many different phenomenological cohesive laws can produce similar fracture predictions. Analytical results for five cohesive zone models are obtained, using five different cohesive laws that have the same cohesive work rate (CWR-area under the traction-separation curve) but different maximum tractions. The effect of the maximum traction on the predicted cohesive zone length and the remote applied load at fracture is presented. Similar to the small scale yielding condition for an LEFM analysis to be valid. the cohesive zone length also needs to be much smaller than the crack length. This is a necessary condition for a CZM to obtain a fracture prediction equivalent to an LEFM result.

Maltodextrins as chiral selectors in CE: molecular structure effect of basic chiral compounds on the enantioseparation.

PubMed

Tabani, Hadi; Fakhari, Ali Reza; Nojavan, Saeed

2014-10-01

Prediction of chiral separation for a compound using a chiral selector is an interesting and debatable work. For this purpose, in this study 23 chiral basic drugs with different chemical structures were selected as model solutes and the influence of their chemical structures on the enantioseparation in the presence of maltodextrin (MD) as chiral selector was investigated. For chiral separation, a 100-mM phosphate buffer solution (pH 3.0) containing 10% (w/v) MD with dextrose equivalent (DE) of 4-7 as chiral selector at the temperature of 25°C and voltage of 20 kV was used. Under this condition, baseline separation was achieved for nine chiral compounds and partial separation was obtained for another six chiral compounds while no enantioseparation was obtained for the remaining eight compounds. The results showed that the existence of at least two aromatic rings or cycloalkanes and an oxygen or nitrogen atom or -CN group directly bonded to the chiral center are necessary for baseline separation. With the obtained results in this study, chiral separation of a chiral compound can be estimated with MD-modified capillary electrophoresis before analysis. This prediction will minimize the number of preliminary experiments required to resolve enantiomers and will save time and cost. © 2014 Wiley Periodicals, Inc.

Management of Vortices Trailing Flapped Wings via Separation Control

NASA Technical Reports Server (NTRS)

Greenblatt, David

2005-01-01

A pilot study was conducted on a flapped semi-span model to investigate the concept and viability of near-wake vortex management via separation control. Passive control was achieved by means of a simple fairing and active control was achieved via zero mass-flux blowing slots. Vortex sheet strength, estimated by integrating surface pressure ports, was used to predict vortex characteristics by means of inviscid rollup relations. Furthermore, vortices trailing the flaps were mapped using a seven-hole probe. Separation control was found to have a marked effect on vortex location, strength, tangential velocity, axial velocity and size over a wide range of angles of attack and control conditions. In general, the vortex trends were well predicted by the inviscid rollup relations. Manipulation of the separated flow near the flap edges exerted significant control over both outboard and inboard edge vortices while producing negligible lift excursions. Dynamic separation and attachment control was found to be an effective means for dynamically perturbing the vortex from arbitrarily long wavelengths down to wavelengths less than a typical wingspan. In summary, separation control has the potential for application to time-independent or time-dependent wake alleviation schemes, where the latter can be deployed to minimize adverse effects on ride-quality and dynamic structural loading.

Determination of Extrapolation Distance With Pressure Signatures Measured at Two to Twenty Span Lengths From Two Low-Boom Models

NASA Technical Reports Server (NTRS)

Mack, Robert J.; Kuhn, Neil S.

2006-01-01

A study was performed to determine a limiting separation distance for the extrapolation of pressure signatures from cruise altitude to the ground. The study was performed at two wind-tunnel facilities with two research low-boom wind-tunnel models designed to generate ground pressure signatures with "flattop" shapes. Data acquired at the first wind-tunnel facility showed that pressure signatures had not achieved the desired low-boom features for extrapolation purposes at separation distances of 2 to 5 span lengths. However, data acquired at the second wind-tunnel facility at separation distances of 5 to 20 span lengths indicated the "limiting extrapolation distance" had been achieved so pressure signatures could be extrapolated with existing codes to obtain credible predictions of ground overpressures.

Age-class separation of blue-winged ducks

USGS Publications Warehouse

Hohman, W.L.; Moore, J.L.; Twedt, D.J.; Mensik, John G.; Logerwell, E.

1995-01-01

Accurate determination of age is of fundamental importance to population and life history studies of waterfowl and their management. Therefore, we developed quantitative methods that separate adult and immature blue-winged teal (Anas discors), cinnamon teal (A. cyanoptera), and northern shovelers (A. clypeata) during spring and summer. To assess suitability of discriminant models using 9 remigial measurements, we compared model performance (% agreement between predicted age and age assigned to birds on the basis of definitive cloacal or rectral feather characteristics) in different flyways (Mississippi and Pacific) and between years (1990-91 and 1991-92). We also applied age-classification models to wings obtained from U.S. Fish and Wildlife Service harvest surveys in the Mississippi and Central-Pacific flyways (wing-bees) for which age had been determined using qualitative characteristics (i.e., remigial markings, shape, or wear). Except for male northern shovelers, models correctly aged lt 90% (range 70-86%) of blue-winged ducks. Model performance varied among species and differed between sexes and years. Proportions of individuals that were correctly aged were greater for males (range 63-86%) than females (range 39-69%). Models for northern shovelers performed better in flyway comparisons within year (1991-92, La. model applied to Calif. birds, and Calif. model applied to La. birds: 90 and 94% for M, and 89 and 76% for F, respectively) than in annual comparisons within the Mississippi Flyway (1991-92 model applied to 1990-91 data: 79% for M, 50% for F). Exclusion of measurements that varied by flyway or year did not improve model performance. Quantitative methods appear to be of limited value for age separation of female blue-winged ducks. Close agreement between predicted age and age assigned to wings from the wing-bees suggests that qualitative and quantitative methods may be equally accurate for age separation of male blue-winged ducks. We interpret annual and flyway differences in remigial measurements and reduced performance of age classification models as evidence of high variability in size of blue-winged ducks' remiges. Variability in remigial size of these and other small-bodied waterfowl may be related to nutrition during molt.

Characterization of Nanofluidic Entropic Trap Array for DNA Separation

NASA Astrophysics Data System (ADS)

Han, Jongyoon

2003-03-01

Micromachined nanoscale fluidic structures can provide new opportunities in biomolecule manipulation and sorting, because their chemical and physical properties can be controlled easily unlike random nanoporous materials. As an example of regular nanostructures used for biomolecule manipulation and sorting, a nanofluidic entropic trap array for DNA separation is presented. Nanofluidic channels as thin as 75nm were used as a molecular sieve instead of agarose gel for DNA separation. The interaction between DNA molecules and the nanofluidic structure determines the DNA migration speed, which was used to separate DNA molecules in a dc electrophoresis. Separation of long DNA (up to 200kbp) has been achieved within 30 minutes, using less than a picogram quantities of DNA, with only 1.5cm long channels.[1] In addition to the efficiency improvement, nanofluidic DNA entropic traps have a regular structure that can be easily modeled theoretically. The theoretical model could be the basis for improving the system performance for further optimization in separation size range and resolution. The process of DNA moving out of the entropic trap was theoretically modeled, and the prediction of the theoretical model was compared with the experimental data.[2] The selectivity, resolution, and the separation range of DNA for a given entropic trap separation system was discussed in terms of the number of entropic traps, various structural parameters of the system, and the electric field. It is expected that this system could be used for analyzing a small amount of ultra-long DNA molecules. (1) Han, J.; Craighead, H. G. Science 2000, 288, 1026-1029. (2) Han, J.; Craighead, H. G. Anal. Chem. 2002, 74, 394-401.

Combining inventories of land cover and forest resources with prediction models and remotely sensed data

Treesearch

Raymond L. Czaplewski

1989-01-01

It is difficult to design systems for national and global resource inventory and analysis that efficiently satisfy changing, and increasingly complex objectives. It is proposed that individual inventory, monitoring, modeling, and remote sensing systems be specialized to achieve portions of the objectives. These separate systems can be statistically linked to accomplish...

Modeling of mass transfer of Phospholipids in separation process with supercritical CO2 fluid by RBF artificial neural networks

USDA-ARS?s Scientific Manuscript database

An artificial Radial Basis Function (RBF) neural network model was developed for the prediction of mass transfer of the phospholipids from canola meal in supercritical CO2 fluid. The RBF kind of artificial neural networks (ANN) with orthogonal least squares (OLS) learning algorithm were used for mod...

Unsteady flow through in-vitro models of the glottis

NASA Astrophysics Data System (ADS)

Hofmans, G. C. J.; Groot, G.; Ranucci, M.; Graziani, G.; Hirschberg, A.

2003-03-01

The unsteady two-dimensional flow through fixed rigid in vitro models of the glottis is studied in some detail to validate a more accurate model based on the prediction of boundary-layer separation. The study is restricted to the flow phenomena occurring within the glottis and does not include effects of vocal-fold movement on the flow. Pressure measurements have been carried out for a transient flow through a rigid scale model of the glottis. The rigid model with a fixed geometry driven by an unsteady pressure is used in order to achieve a high accuracy in the specification of the geometry of the glottis. The experimental study is focused on flow phenomena as they might occur in the glottis, such as the asymmetry of the flow due to the Coanda effect and the transition to turbulent flow. It was found that both effects need a relatively long time to establish themselves and are therefore unlikely to occur during the production of normal voiced speech when the glottis closes completely during part of the oscillation cycle. It is shown that when the flow is still laminar and symmetric the prediction of the boundary-layer model and the measurement of the pressure drop from the throat of the glottis to the exit of the glottis agree within 40%. Results of the boundary-layer model are compared with a two-dimensional vortex-blob method for viscous flow. The difference between the results of the simpiflied boundary-layer model and the experimental results is explained by an additional pressure difference between the separation point and the far field within the jet downstream of the separation point. The influence of the movement of the vocal folds on our conclusions is still unclear.

Modifications of the law of the wall and algebraic turbulence modelling for separated boundary layers

NASA Technical Reports Server (NTRS)

Baldwin, B. S.; Maccormack, R. W.

1976-01-01

Various modifications of the conventional algebraic eddy viscosity turbulence model are investigated for application to separated flows. Friction velocity is defined in a way that avoids singular behavior at separation and reattachment but reverts to the conventional definition for flows with small pressure gradients. This leads to a modified law of the wall for separated flows. The effect on the calculated flow field of changes in the model that affect the eddy viscosity at various distances from the wall are determined by (1) switching from Prandtl's form to an inner layer formula due to Clauser at various distances from the wall, (2) varying the constant in the Van Driest damping factor, (3) using Clauser's inner layer formula all the way to the wall, and (4) applying a relaxation procedure in the evaluation of the constant in Clauser's inner layer formula. Numerical solutions of the compressible Navier-Stokes equations are used to determine the effects of the modifications. Experimental results from shock-induced separated flows at Mach numbers 2.93 and 8.45 are used for comparison. For these cases improved predictions of wall pressure distribution and positions of separation and reattachment are obtained from the relaxation version of the Clauser inner layer eddy viscosity formula.

Model Prediction Results for 2007 Ultrasonic Benchmark Problems

NASA Astrophysics Data System (ADS)

Kim, Hak-Joon; Song, Sung-Jin

2008-02-01

The World Federation of NDE Centers (WFNDEC) has addressed two types of problems for the 2007 ultrasonic benchmark problems: prediction of side-drilled hole responses with 45° and 60° refracted shear waves, and effects of surface curvatures on the ultrasonic responses of flat-bottomed hole. To solve this year's ultrasonic benchmark problems, we applied multi-Gaussian beam models for calculation of ultrasonic beam fields and the Kirchhoff approximation and the separation of variables method for calculation of far-field scattering amplitudes of flat-bottomed holes and side-drilled holes respectively In this paper, we present comparison results of model predictions to experiments for side-drilled holes and discuss effect of interface curvatures on ultrasonic responses by comparison of peak-to-peak amplitudes of flat-bottomed hole responses with different sizes and interface curvatures.

VTOL in ground effect flows for closely spaced jets. [to predict pressure and upwash forces on aircraft structures

NASA Technical Reports Server (NTRS)

Migdal, D.; Hill, W. G., Jr.; Jenkins, R. C.

1979-01-01

Results of a series of in ground effect twin jet tests are presented along with flow models for closely spaced jets to help predict pressure and upwash forces on simulated aircraft surfaces. The isolated twin jet tests revealed unstable fountains over a range of spacings and jet heights, regions of below ambient pressure on the ground, and negative pressure differential in the upwash flow field. A separate computer code was developed for vertically oriented, incompressible jets. This model more accurately reflects fountain behavior without fully formed wall jets, and adequately predicts ground isobars, upwash dynamic pressure decay, and fountain lift force variation with height above ground.

Computation of oscillating airfoil flows with one- and two-equation turbulence models

NASA Technical Reports Server (NTRS)

Ekaterinaris, J. A.; Menter, F. R.

1994-01-01

The ability of one- and two-equation turbulence models to predict unsteady separated flows over airfoils is evaluated. An implicit, factorized, upwind-biased numerical scheme is used for the integration of the compressible, Reynolds-averaged Navier-Stokes equations. The turbulent eddy viscosity is obtained from the computed mean flowfield by integration of the turbulent field equations. One- and two-equation turbulence models are first tested for a separated airfoil flow at fixed angle of incidence. The same models are then applied to compute the unsteady flowfields about airfoils undergoing oscillatory motion at low subsonic Mach numbers. Experimental cases where the flow has been tripped at the leading-edge and where natural transition was allowed to occur naturally are considered. The more recently developed turbulence models capture the physics of unsteady separated flow significantly better than the standard kappa-epsilon and kappa-omega models. However, certain differences in the hysteresis effects are observed. For an untripped high-Reynolds-number flow, it was found necessary to take into account the leading-edge transitional flow region to capture the correct physical mechanism that leads to dynamic stall.

Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks.

PubMed

Coiera, Enrico; Wang, Ying; Magrabi, Farah; Concha, Oscar Perez; Gallego, Blanca; Runciman, William

2014-05-21

Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model performance was evaluated alone, and in combination with simple disease-specific models. Patients admitted between 2000 and 2006 from 501 public and private hospitals in NSW, Australia were used for training and 2007 data for evaluation. The impact of hospital care delivered over different days of the week and or times of the day was modeled by separating hospitalization risk into 21 separate time periods (morning, day, night across the days of the week). Three models were developed to predict death up to 7-days post-discharge: 1/a simple background risk model using age, gender; 2/a time-varying risk model for exposure to hospitalization (admission time, days in hospital); 3/disease specific models (Charlson co-morbidity index, DRG). Combining these three generated a full model. Models were evaluated by accuracy, AUC, Akaike and Bayesian information criteria. There was a clear diurnal rhythm to hospital mortality in the data set, peaking in the evening, as well as the well-known 'weekend-effect' where mortality peaks with weekend admissions. Individual models had modest performance on the test data set (AUC 0.71, 0.79 and 0.79 respectively). The combined model which included time-varying risk however yielded an average AUC of 0.92. This model performed best for stays up to 7-days (93% of admissions), peaking at days 3 to 5 (AUC 0.94). Risks of hospitalization vary not just with the day of the week but also time of the day, and can be used to make predictions about the cumulative risk of death associated with an individual's hospitalization. Combining disease specific models with such time varying- estimates appears to result in robust predictive performance. Such risk exposure models should find utility both in enhancing standard prognostic models as well as estimating the risk of continuation of hospitalization.

Influence of collision on the flow through in-vitro rigid models of the vocal folds

NASA Astrophysics Data System (ADS)

Deverge, M.; Pelorson, X.; Vilain, C.; Lagrée, P.-Y.; Chentouf, F.; Willems, J.; Hirschberg, A.

2003-12-01

Measurements of pressure in oscillating rigid replicas of vocal folds are presented. The pressure upstream of the replica is used as input to various theoretical approximations to predict the pressure within the glottis. As the vocal folds collide the classical quasisteady boundary layer theory fails. It appears however that for physiologically reasonable shapes of the replicas, viscous effects are more important than the influence of the flow unsteadiness due to the wall movement. A simple model based on a quasisteady Bernoulli equation corrected for viscous effect, combined with a simple boundary layer separation model does globally predict the observed pressure behavior.

Enhancing BEM simulations of a stalled wind turbine using a 3D correction model

NASA Astrophysics Data System (ADS)

Bangga, Galih; Hutomo, Go; Syawitri, Taurista; Kusumadewi, Tri; Oktavia, Winda; Sabila, Ahmad; Setiadi, Herlambang; Faisal, Muhamad; Hendranata, Yongki; Lastomo, Dwi; Putra, Louis; Kristiadi, Stefanus; Bumi, Ilmi

2018-03-01

Nowadays wind turbine rotors are usually employed with pitch control mechanisms to avoid deep stall conditions. Despite that, wind turbines often operate under pitch fault situation causing massive flow separation to occur. Pure Blade Element Momentum (BEM) approaches are not designed for this situation and inaccurate load predictions are already expected. In the present studies, BEM predictions are improved through the inclusion of a stall delay model for a wind turbine rotor operating under pitch fault situation of -2.3° towards stall. The accuracy of the stall delay model is assessed by comparing the results with available Computational Fluid Dynamics (CFD) simulations data.

In Silico Modelling of Transdermal and Systemic Kinetics of Topically Applied Solutes: Model Development and Initial Validation for Transdermal Nicotine.

PubMed

Chen, Tao; Lian, Guoping; Kattou, Panayiotis

2016-07-01

The purpose was to develop a mechanistic mathematical model for predicting the pharmacokinetics of topically applied solutes penetrating through the skin and into the blood circulation. The model could be used to support the design of transdermal drug delivery systems and skin care products, and risk assessment of occupational or consumer exposure. A recently reported skin penetration model [Pharm Res 32 (2015) 1779] was integrated with the kinetic equations for dermis-to-capillary transport and systemic circulation. All model parameters were determined separately from the molecular, microscopic and physiological bases, without fitting to the in vivo data to be predicted. Published clinical studies of nicotine were used for model demonstration. The predicted plasma kinetics is in good agreement with observed clinical data. The simulated two-dimensional concentration profile in the stratum corneum vividly illustrates the local sub-cellular disposition kinetics, including tortuous lipid pathway for diffusion and the "reservoir" effect of the corneocytes. A mechanistic model for predicting transdermal and systemic kinetics was developed and demonstrated with published clinical data. The integrated mechanistic approach has significantly extended the applicability of a recently reported microscopic skin penetration model by providing prediction of solute concentration in the blood.

Load application for the contact mechanics analysis and wear prediction of total knee replacement.

PubMed

Zhang, Jing; Chen, Zhenxian; Wang, Ling; Li, Dichen; Jin, Zhongmin

2017-05-01

Tibiofemoral contact forces in total knee replacement have been measured at the medial and lateral sites respectively using an instrumented prosthesis, and predicted from musculoskeletal multibody dynamics models with a reasonable accuracy. However, it is uncommon that the medial and lateral forces are applied separately to replace a total axial load according to the ISO standard in the majority of current finite element analyses. In this study, we quantified the different effects of applying the medial and lateral loads separately versus the traditional total axial load application on contact mechanics and wear prediction of a patient-specific knee prosthesis. The load application position played an important role under the medial-lateral load application. The loading set which produced the closest load distribution to the multibody dynamics model was used to predict the contact mechanics and wear for the prosthesis and compared with the total axial load application. The medial-lateral load distribution using the present method was found to be closer to the multibody dynamics prediction than the traditional total axial load application, and the maximum contact pressure and contact area were consistent with the corresponding load variation. The predicted total volumetric wear rate and area were similar between the two load applications. However, the split of the predicted wear volumes on the medial and the lateral sides was different. The lateral volumetric wear rate was 31.46% smaller than the medial from the traditional load application prediction, while from the medial-lateral load application, the lateral side was only 11.8% smaller than the medial. The medial-lateral load application could provide a new and more accurate method of load application for patient-specific preclinical contact mechanics and wear prediction of knee implants.

Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

NASA Astrophysics Data System (ADS)

Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

2016-02-01

Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

Modeling the Endogenous Sunlight Inactivation Rates of Laboratory Strain and Wastewater E. coli and Enterococci Using Biological Weighting Functions.

PubMed

Silverman, Andrea I; Nelson, Kara L

2016-11-15

Models that predict sunlight inactivation rates of bacteria are valuable tools for predicting the fate of pathogens in recreational waters and designing natural wastewater treatment systems to meet disinfection goals. We developed biological weighting function (BWF)-based numerical models to estimate the endogenous sunlight inactivation rates of E. coli and enterococci. BWF-based models allow the prediction of inactivation rates under a range of environmental conditions that shift the magnitude or spectral distribution of sunlight irradiance (e.g., different times, latitudes, water absorbances, depth). Separate models were developed for laboratory strain bacteria cultured in the laboratory and indigenous organisms concentrated directly from wastewater. Wastewater bacteria were found to be 5-7 times less susceptible to full-spectrum simulated sunlight than the laboratory bacteria, highlighting the importance of conducting experiments with bacteria sourced directly from wastewater. The inactivation rate models fit experimental data well and were successful in predicting the inactivation rates of wastewater E. coli and enterococci measured in clear marine water by researchers from a different laboratory. Additional research is recommended to develop strategies to account for the effects of elevated water pH on predicted inactivation rates.

Consolidated Human Activity Database (CHAD) for use in human exposure and health studies and predictive models

EPA Pesticide Factsheets

EPA scientists have compiled detailed data on human behavior from 22 separate exposure and time-use studies into CHAD. The database includes more than 54,000 individual study days of detailed human behavior.

Impaired neurogenesis of the dentate gyrus is associated with pattern separation deficits: A computational study.

PubMed

Faghihi, Faramarz; Moustafa, Ahmed A

2016-09-01

The separation of input patterns received from the entorhinal cortex (EC) by the dentate gyrus (DG) is a well-known critical step of information processing in the hippocampus. Although the role of interneurons in separation pattern efficiency of the DG has been theoretically known, the balance of neurogenesis of excitatory neurons and interneurons as well as its potential role in information processing in the DG is not fully understood. In this work, we study separation efficiency of the DG for different rates of neurogenesis of interneurons and excitatory neurons using a novel computational model in which we assume an increase in the synaptic efficacy between excitatory neurons and interneurons and then its decay over time. Information processing in the EC and DG was simulated as information flow in a two layer feed-forward neural network. The neurogenesis rate was modeled as the percentage of new born neurons added to the neuronal population in each time bin. The results show an important role of an optimal neurogenesis rate of interneurons and excitatory neurons in the DG in efficient separation of inputs from the EC in pattern separation tasks. The model predicts that any deviation of the optimal values of neurogenesis rates leads to different decreased levels of the separation deficits of the DG which influences its function to encode memory.

Predicting Risk for Suicide: A Preliminary Examination of Non-Suicidal Self-Injury and the Acquired Capability Construct in a College Sample.

PubMed

Brackman, Emily H; Morris, Blair W; Andover, Margaret S

2016-01-01

The interpersonal psychological theory of suicide provides a useful framework for considering the relationship between non-suicidal self-injury and suicide. Researchers propose that NSSI increases acquired capability for suicide. We predicted that both NSSI frequency and the IPTS acquired capability construct (decreased fear of death and increased pain tolerance) would separately interact with suicidal ideation to predict suicide attempts. Undergraduate students (N = 113) completed self-report questionnaires, and a subsample (n = 66) also completed a pain sensitivity task. NSSI frequency significantly moderated the association between suicidal ideation and suicide attempts. However, in a separate model, acquired capability did not moderate this relationship. Our understanding of the relationship between suicidal ideation and suicidal behavior can be enhanced by factors associated with NSSI that are distinct from the acquired capability construct.

A vortex-filament and core model for wings with edge vortex separation

NASA Technical Reports Server (NTRS)

Pao, J. L.; Lan, C. E.

1981-01-01

A method for predicting aerodynamic characteristics of slender wings with edge vortex separation was developed. Semiempirical but simple methods were used to determine the initial positions of the free sheet and vortex core. Comparison with available data indicates that: the present method is generally accurate in predicting the lift and induced drag coefficients but the predicted pitching moment is too positive; the spanwise lifting pressure distributions estimated by the one vortex core solution of the present method are significantly better than the results of Mehrotra's method relative to the pressure peak values for the flat delta; the two vortex core system applied to the double delta and strake wing produce overall aerodynamic characteristics which have good agreement with data except for the pitching moment; and the computer time for the present method is about two thirds of that of Mehrotra's method.

Spatial patterns of phylogenetic diversity.

PubMed

Morlon, Hélène; Schwilk, Dylan W; Bryant, Jessica A; Marquet, Pablo A; Rebelo, Anthony G; Tauss, Catherine; Bohannan, Brendan J M; Green, Jessica L

2011-02-01

Ecologists and conservation biologists have historically used species-area and distance-decay relationships as tools to predict the spatial distribution of biodiversity and the impact of habitat loss on biodiversity. These tools treat each species as evolutionarily equivalent, yet the importance of species' evolutionary history in their ecology and conservation is becoming increasingly evident. Here, we provide theoretical predictions for phylogenetic analogues of the species-area and distance-decay relationships. We use a random model of community assembly and a spatially explicit flora dataset collected in four Mediterranean-type regions to provide theoretical predictions for the increase in phylogenetic diversity - the total phylogenetic branch-length separating a set of species - with increasing area and the decay in phylogenetic similarity with geographic separation. These developments may ultimately provide insights into the evolution and assembly of biological communities, and guide the selection of protected areas. © 2010 Blackwell Publishing Ltd/CNRS.

A vortex-filament and core model for wings with edge vortex separation

NASA Technical Reports Server (NTRS)

Pao, J. L.; Lan, C. E.

1982-01-01

A vortex filament-vortex core method for predicting aerodynamic characteristics of slender wings with edge vortex separation was developed. Semi-empirical but simple methods were used to determine the initial positions of the free sheet and vortex core. Comparison with available data indicates that: (1) the present method is generally accurate in predicting the lift and induced drag coefficients but the predicted pitching moment is too positive; (2) the spanwise lifting pressure distributions estimated by the one vortex core solution of the present method are significantly better than the results of Mehrotra's method relative to the pressure peak values for the flat delta; (3) the two vortex core system applied to the double delta and strake wings produce overall aerodynamic characteristics which have good agreement with data except for the pitching moment; and (4) the computer time for the present method is about two thirds of that of Mehrotra's method.

Foam flotation as a separation process

NASA Technical Reports Server (NTRS)

Currin, B. L.

1986-01-01

The basic principles of foam separation techniques are discussed. A review of the research concerning bubble-particle interaction and its role in the kinetics of the flotation process is given. Most of the research in this area deals with the use of theoretical models to predict the effects of bubble and particle sizes, of liquid flow, and of various forces on the aperture and retention of particles by bubbles. A discussion of fluid mechanical aspects of particle flotation is given.

A computational model of pattern separation efficiency in the dentate gyrus with implications in schizophrenia

PubMed Central

Faghihi, Faramarz; Moustafa, Ahmed A.

2015-01-01

Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189

Ringin' the water bell: dynamic modes of curved fluid sheets

NASA Astrophysics Data System (ADS)

Kolinski, John; Aharoni, Hillel; Fineberg, Jay; Sharon, Eran

2015-11-01

A water bell is formed by fluid flowing in a thin, coherent sheet in the shape of a bell. Experimentally, a water bell is created via the impact of a cylindrical jet on a flat surface. Its shape is set by the splash angle (the separation angle) of the resulting cylindrically symmetric water sheet. The separation angle is altered by adjusting the height of a lip surrounding the impact point, as in a water sprinkler. We drive the lip's height sinusoidally, altering the separation angle, and ringin' the water bell. This forcing generates disturbances on the steady-state water bell that propagate forward and backward in the fluid's reference frame at well-defined velocities, and interact, resulting in the emergence of an interference pattern unique to each steady-state geometry. We analytically model these dynamics by linearizing the amplitude of the bell's response about the underlying curved geometry. This simple model predicts the nodal structure over a wide range of steady-state water bell configurations and driving frequencies. Due to the curved water bell geometry, the nodal structure is quite complex; nevertheless, the predicted nodal structure agrees extremely well with the experimental data. When we drive the bell beyond perturbative separation angles, the nodal locations surprisingly persist, despite the strikingly altered underlying water bell shape. At extreme driving amplitudes the water sheet assumes a rich variety of tortuous, non-convex shapes; nevertheless, the fluid sheet remains intact.

Spatial working memory capacity predicts bias in estimates of location.

PubMed

Crawford, L Elizabeth; Landy, David; Salthouse, Timothy A

2016-09-01

Spatial memory research has attributed systematic bias in location estimates to a combination of a noisy memory trace with a prior structure that people impose on the space. Little is known about intraindividual stability and interindividual variation in these patterns of bias. In the current work, we align recent empirical and theoretical work on working memory capacity limits and spatial memory bias to generate the prediction that those with lower working memory capacity will show greater bias in memory of the location of a single item. Reanalyzing data from a large study of cognitive aging, we find support for this prediction. Fitting separate models to individuals' data revealed a surprising variety of strategies. Some were consistent with Bayesian models of spatial category use, however roughly half of participants biased estimates outward in a way not predicted by current models and others seemed to combine these strategies. These analyses highlight the importance of studying individuals when developing general models of cognition. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Spatial Working Memory Capacity Predicts Bias in Estimates of Location

PubMed Central

Crawford, L. Elizabeth; Landy, David H.; Salthouse, Timothy A.

2016-01-01

Spatial memory research has attributed systematic bias in location estimates to a combination of a noisy memory trace with a prior structure that people impose on the space. Little is known about intra-individual stability and inter-individual variation in these patterns of bias. In the current work we align recent empirical and theoretical work on working memory capacity limits and spatial memory bias to generate the prediction that those with lower working memory capacity will show greater bias in memory of the location of a single item. Reanalyzing data from a large study of cognitive aging, we find support for this prediction. Fitting separate models to individuals’ data revealed a surprising variety of strategies. Some were consistent with Bayesian models of spatial category use, however roughly half of participants biased estimates outward in a way not predicted by current models and others seemed to combine these strategies. These analyses highlight the importance of studying individuals when developing general models of cognition. PMID:26900708

FUN3D and CFL3D Computations for the First High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Park, Michael A.; Lee-Rausch, Elizabeth M.; Rumsey, Christopher L.

2011-01-01

Two Reynolds-averaged Navier-Stokes codes were used to compute flow over the NASA Trapezoidal Wing at high lift conditions for the 1st AIAA CFD High Lift Prediction Workshop, held in Chicago in June 2010. The unstructured-grid code FUN3D and the structured-grid code CFL3D were applied to several different grid systems. The effects of code, grid system, turbulence model, viscous term treatment, and brackets were studied. The SST model on this configuration predicted lower lift than the Spalart-Allmaras model at high angles of attack; the Spalart-Allmaras model agreed better with experiment. Neglecting viscous cross-derivative terms caused poorer prediction in the wing tip vortex region. Output-based grid adaptation was applied to the unstructured-grid solutions. The adapted grids better resolved wake structures and reduced flap flow separation, which was also observed in uniform grid refinement studies. Limitations of the adaptation method as well as areas for future improvement were identified.

A Task-Optimized Neural Network Replicates Human Auditory Behavior, Predicts Brain Responses, and Reveals a Cortical Processing Hierarchy.

PubMed

Kell, Alexander J E; Yamins, Daniel L K; Shook, Erica N; Norman-Haignere, Sam V; McDermott, Josh H

2018-05-02

A core goal of auditory neuroscience is to build quantitative models that predict cortical responses to natural sounds. Reasoning that a complete model of auditory cortex must solve ecologically relevant tasks, we optimized hierarchical neural networks for speech and music recognition. The best-performing network contained separate music and speech pathways following early shared processing, potentially replicating human cortical organization. The network performed both tasks as well as humans and exhibited human-like errors despite not being optimized to do so, suggesting common constraints on network and human performance. The network predicted fMRI voxel responses substantially better than traditional spectrotemporal filter models throughout auditory cortex. It also provided a quantitative signature of cortical representational hierarchy-primary and non-primary responses were best predicted by intermediate and late network layers, respectively. The results suggest that task optimization provides a powerful set of tools for modeling sensory systems. Copyright © 2018 Elsevier Inc. All rights reserved.

Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

NASA Technical Reports Server (NTRS)

He, Yuning

2015-01-01

Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

Investigating Some Technical Issues on Cohesive Zone Modeling of Fracture

NASA Technical Reports Server (NTRS)

Wang, John T.

2011-01-01

This study investigates some technical issues related to the use of cohesive zone models (CZMs) in modeling fracture processes. These issues include: why cohesive laws of different shapes can produce similar fracture predictions; under what conditions CZM predictions have a high degree of agreement with linear elastic fracture mechanics (LEFM) analysis results; when the shape of cohesive laws becomes important in the fracture predictions; and why the opening profile along the cohesive zone length needs to be accurately predicted. Two cohesive models were used in this study to address these technical issues. They are the linear softening cohesive model and the Dugdale perfectly plastic cohesive model. Each cohesive model constitutes five cohesive laws of different maximum tractions. All cohesive laws have the same cohesive work rate (CWR) which is defined by the area under the traction-separation curve. The effects of the maximum traction on the cohesive zone length and the critical remote applied stress are investigated for both models. For a CZM to predict a fracture load similar to that obtained by an LEFM analysis, the cohesive zone length needs to be much smaller than the crack length, which reflects the small scale yielding condition requirement for LEFM analysis to be valid. For large-scale cohesive zone cases, the predicted critical remote applied stresses depend on the shape of cohesive models used and can significantly deviate from LEFM results. Furthermore, this study also reveals the importance of accurately predicting the cohesive zone profile in determining the critical remote applied load.

Features in visual search combine linearly

PubMed Central

Pramod, R. T.; Arun, S. P.

2014-01-01

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328

Flow processes in overexpanded chemical rocket nozzles. Part 1: Flow separation

NASA Technical Reports Server (NTRS)

Schmucker, R. H.

1984-01-01

An investigation was made of published nozzle flow separation data in order to determine the parameters which affect the separation conditions. A comparison of experimental data with empirical and theoretical separation prediction methods leads to the selection of suitable equations for the separation criterion. The results were used to predict flow separation of the main space shuttle engine.

Flow processes in overexpanded chemical rocket nozzles. Part 1: Flow separation

NASA Technical Reports Server (NTRS)

Schmucker, R. H.

1973-01-01

An investigation was made of published nozzle flow separation data in order to determine the parameters which affect the separation condition. A comparison of experimental data with empirical and theoretical separation prediction methods leads to the selection of suitable equations for the separation criterion. The results were used to predict flow separation of the main space shuttle engine.

Optimizing the separation performance of a gas centrifuge

NASA Astrophysics Data System (ADS)

Wood, H. G.

1997-11-01

Gas centrifuges were originally developed for the enrichment of U^235 from naturally occurring uranium for the purpose of providing fuel for nuclear power reactors and material for nuclear weapons. This required the separation of a binary mixture composed of U^235 and U^238. Since the end of the cold war, a surplus of enriched uranium exists on the world market, but many centrifuge plants exist in numerous countries. These circumstances together with the growing demand for stable isotopes for chemical and physical research and in medical science has led to the exploration of alternate applications of gas centrifuge technology. In order to acieve these multi-component separations, existing centrifuges must be modified or new centrifuges must be designed. In either case, it is important to have models of the internal flow fields to predict the separation performance and algorithms to seek the optimal operating conditions of the centrifuges. Here, we use the Onsager pancake model of the internal flow field, and we present an optimization strategy which exploits a similarity parameter in the pancake model. Numerical examples will be presented.

Experimental design for a basic mixture on a fluorinated packing. The effect of composition of the mobile phase.

PubMed

Wang, Y; Harrison, M; Clark, B J

2006-02-10

An optimization methodology is introduced for investigating the separation and the retention behavior of analytes on a new fluorinated reversed-phase packing. Ten basic compounds were selected as test probes to study the predictive models developed by using SPSS and MATLAB software. A two-level orthogonal array design (OAD) was used to extract significant parameters. The significant factors were optimised using a central composite design to obtain the quadratic relationship between the dependent and the independent variables. Using this strategy, response surfaces were derived as the 3D and contour plots, and mathematical models were defined for the separation. The models had a satisfactory coefficient (R(2) > 0.97, n = 16). For the test compounds, the best separation condition was: MeCN/30 mM phosphate buffer pH 7.1(55.5:44.5, v/v) and 10 basic solutes were resolved in 22 min. The significant influence of the concentration of buffer shows that different mechanisms of separation for basic compounds on the fluorinated packing exist compared with a common ODS stationary phase.

Genomic Prediction of Gene Bank Wheat Landraces.

PubMed

Crossa, José; Jarquín, Diego; Franco, Jorge; Pérez-Rodríguez, Paulino; Burgueño, Juan; Saint-Pierre, Carolina; Vikram, Prashant; Sansaloni, Carolina; Petroli, Cesar; Akdemir, Deniz; Sneller, Clay; Reynolds, Matthew; Tattaris, Maria; Payne, Thomas; Guzman, Carlos; Peña, Roberto J; Wenzl, Peter; Singh, Sukhwinder

2016-07-07

This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, "diversity" and "prediction", including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15-20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials. Copyright © 2016 Crossa et al.

Options as information: rational reversals of evaluation and preference.

PubMed

Sher, Shlomi; McKenzie, Craig R M

2014-06-01

This article develops a rational analysis of an important class of apparent preference reversals-joint-separate reversals traditionally explained by the evaluability hypothesis. The "options-as-information" model considers a hypothetical rational actor with limited knowledge about the market distribution of a stimulus attribute. The actor's evaluations are formed via a 2-stage process-an inferential stage in which beliefs are updated on the basis of the sample of options received, followed by an assessment stage in which options are evaluated in light of these updated beliefs. This process generates joint-separate reversals in standard experimental designs. The normative model explains why the evaluability hypothesis works when it does, identifies boundary conditions for the hypothesis, and clarifies some common misconceptions about these effects. In particular, it implies that joint-separate reversals are not irrational; in fact, they are not preference reversals. However, in expanded designs where more than 2 options are jointly evaluated, the model predicts that genuine (and rational) preference reversals will sometimes emerge. Results of 3 experiments suggest an excellent fit between the rational actor model and the judgments of human actors in joint-separate experiments. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A computational study of incipient leading-edge separation on a 65-deg delta wing at M = 1.60

NASA Technical Reports Server (NTRS)

Mcmillin, S. Naomi; Pittman, James L.; Thomas, James L.

1990-01-01

A computational study on a 65-deg delta wing at a freestream Mach number of 1.60 has been conducted by obtaining conical Reynolds-averaged Navier-Stokes solutions on a parametric series of geometries which varied in leading-edge radius and/or circular-arc camber. The computational results showed that increasing leading-edge radius or camber can delay the onset of leading-edge separation on the leeside of a delta wing at a specific angle of attack. Reynolds number was varied from 1 x 10 to the 6th to 5 x 10 to the 6th for a turbulent boundary-layer and was shown to have a minor effect on the effectiveness of leading-edge radius and/or camber in delaying the onset of leading-edge separation. Both laminar and turbulent boundary-layer models were investigated at a Reynolds number of 1 x 10 to the 6th, and the predicted flow pattern was found to change from attached flow for the turbulent boundary-layer model to separated flow for the laminar boundary-layer model. Based upon these results, three wind-tunnel models have been designed to be tested in the Langley Unitary Plan Wind Tunnel.

Using modelling to predict impacts of sea level rise and increased turbidity on seagrass distributions in estuarine embayments

NASA Astrophysics Data System (ADS)

Davis, Tom R.; Harasti, David; Smith, Stephen D. A.; Kelaher, Brendan P.

2016-11-01

Climate change induced sea level rise will affect shallow estuarine habitats, which are already under threat from multiple anthropogenic stressors. Here, we present the results of modelling to predict potential impacts of climate change associated processes on seagrass distributions. We use a novel application of relative environmental suitability (RES) modelling to examine relationships between variables of physiological importance to seagrasses (light availability, wave exposure, and current flow) and seagrass distributions within 5 estuarine embayments. Models were constructed separately for Posidonia australis and Zostera muelleri subsp. capricorni using seagrass data from Port Stephens estuary, New South Wales, Australia. Subsequent testing of models used independent datasets from four other estuarine embayments (Wallis Lake, Lake Illawarra, Merimbula Lake, and Pambula Lake) distributed along 570 km of the east Australian coast. Relative environmental suitability models provided adequate predictions for seagrass distributions within Port Stephens and the other estuarine embayments, indicating that they may have broad regional application. Under the predictions of RES models, both sea level rise and increased turbidity are predicted to cause substantial seagrass losses in deeper estuarine areas, resulting in a net shoreward movement of seagrass beds. Seagrass species distribution models developed in this study provide a valuable tool to predict future shifts in estuarine seagrass distributions, allowing identification of areas for protection, monitoring and rehabilitation.

Investigation of pressure drop in capillary tube for mixed refrigerant Joule-Thomson cryocooler

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ardhapurkar, P. M.; Sridharan, Arunkumar; Atrey, M. D.

2014-01-29

A capillary tube is commonly used in small capacity refrigeration and air-conditioning systems. It is also a preferred expansion device in mixed refrigerant Joule-Thomson (MR J-T) cryocoolers, since it is inexpensive and simple in configuration. However, the flow inside a capillary tube is complex, since flashing process that occurs in case of refrigeration and air-conditioning systems is metastable. A mixture of refrigerants such as nitrogen, methane, ethane, propane and iso-butane expands below its inversion temperature in the capillary tube of MR J-T cryocooler and reaches cryogenic temperature. The mass flow rate of refrigerant mixture circulating through capillary tube depends onmore » the pressure difference across it. There are many empirical correlations which predict pressure drop across the capillary tube. However, they have not been tested for refrigerant mixtures and for operating conditions of the cryocooler. The present paper assesses the existing empirical correlations for predicting overall pressure drop across the capillary tube for the MR J-T cryocooler. The empirical correlations refer to homogeneous as well as separated flow models. Experiments are carried out to measure the overall pressure drop across the capillary tube for the cooler. Three different compositions of refrigerant mixture are used to study the pressure drop variations. The predicted overall pressure drop across the capillary tube is compared with the experimentally obtained value. The predictions obtained using homogeneous model show better match with the experimental results compared to separated flow models.« less

A path analysis of gender differences in adolescent onset of alcohol, tobacco and other drug use (ATOD), reported ATOD use and adverse consequences of ATOD use.

PubMed

Thomas, B S

1996-01-01

Gender differences in the ways a risk factor approach explains onset of using alcohol, tobacco and other drugs (ATOD), reported use of ATOD and adverse consequences from ATOD use were investigated by means of separate path analyses for male and female adolescents. A fully recursive model was specified in which alienation, trait anger, interaction anxiety and cognitive motivation for ATOD use comprised the first column variables which were used to predict earliness of onset. For the second step, column one variables plus onset were used to predict ATOD use. In the final step, column one variables plus onset and ATOD use were used to predict adverse consequences of ATOD use. An ex post facto design was used in surveying 796 high school students in a single Midwestern community. The data from this sample supported the predictive validity of the theoretical model. In addition to the expected indirect or mediated effects of the risk factors via onset of ATOD use on ATOD use and via onset and ATOD use on adverse consequences of ATOD use, there were direct effects of column on risk factors on both ATOD use and on adverse consequences of ATOD use for both males and females, lending support to the concept of multiple pathway risk factors. The three gender differences that emerged in the separate path analyses were entirely consistent with the gendered deviance model.

Modeling RP-1 fuel advanced distillation data using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and partial least squares analysis.

PubMed

Kehimkar, Benjamin; Parsons, Brendon A; Hoggard, Jamin C; Billingsley, Matthew C; Bruno, Thomas J; Synovec, Robert E

2015-01-01

Recent efforts in predicting rocket propulsion (RP-1) fuel performance through modeling put greater emphasis on obtaining detailed and accurate fuel properties, as well as elucidating the relationships between fuel compositions and their properties. Herein, we study multidimensional chromatographic data obtained by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC-TOFMS) to analyze RP-1 fuels. For GC × GC separations, RTX-Wax (polar stationary phase) and RTX-1 (non-polar stationary phase) columns were implemented for the primary and secondary dimensions, respectively, to separate the chemical compound classes (alkanes, cycloalkanes, aromatics, etc.), providing a significant level of chemical compositional information. The GC × GC-TOFMS data were analyzed using partial least squares regression (PLS) chemometric analysis to model and predict advanced distillation curve (ADC) data for ten RP-1 fuels that were previously analyzed using the ADC method. The PLS modeling provides insight into the chemical species that impact the ADC data. The PLS modeling correlates compositional information found in the GC × GC-TOFMS chromatograms of each RP-1 fuel, and their respective ADC, and allows prediction of the ADC for each RP-1 fuel with good precision and accuracy. The root-mean-square error of calibration (RMSEC) ranged from 0.1 to 0.5 °C, and was typically below ∼0.2 °C, for the PLS calibration of the ADC modeling with GC × GC-TOFMS data, indicating a good fit of the model to the calibration data. Likewise, the predictive power of the overall method via PLS modeling was assessed using leave-one-out cross-validation (LOOCV) yielding root-mean-square error of cross-validation (RMSECV) ranging from 1.4 to 2.6 °C, and was typically below ∼2.0 °C, at each % distilled measurement point during the ADC analysis.

The structure of evaporating and combusting sprays: Measurements and predictions

NASA Technical Reports Server (NTRS)

Shuen, J. S.; Solomon, A. S. P.; Faeth, F. M.

1983-01-01

The structure of particle-laden jets and nonevaporating and evaporating sprays was measured in order to evaluate models of these processes. Three models are being evaluated: (1) a locally homogeneous flow model, where slip between the phases is neglected and the flow is assumed to be in local thermodynamic equilibrium; (2) a deterministic separated flow model, where slip and finite interphase transport rates are considered but effects of particle/drop dispersion by turbulence and effects of turbulence on interphase transport rates are ignored; and (3) a stochastic separated flow model, where effects of interphase slip, turbulent dispersion and turbulent fluctuations are considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. All three models use a k-e-g turbulence model. All testing and data reduction are completed for the particle laden jets. Mean and fluctuating velocities of the continuous phase and mean mixture fraction were measured in the evaporating sprays.

Thermal loading of natural streams

USGS Publications Warehouse

Jackman, Alan P.; Yotsukura, Nobuhiro

1977-01-01

The impact of thermal loading on the temperature regime of natural streams is investigated by mathematical models, which describe both transport (convection-diffusion) and decay (surface dissipation) of waste heat over 1-hour or shorter time intervals. The models are derived from the principle of conservation of thermal energy for application to one- and two-dimensional spaces. The basic concept in these models is to separate water temperature into two parts, (1) excess temperature due to thermal loading and (2) natural (ambient) temperature. This separation allows excess temperature to be calculated from the models without incoming radiation data. Natural temperature may either be measured in prototypes or calculated from the model. If use is made of the model, however, incoming radiation is required as input data. Comparison of observed and calculated temperatures in seven natural streams shows that the models are capable of predicting transient temperature regimes satisfactorily in most cases. (Woodard-USGS)

Advanced Waveform Simulation for Seismic Monitoring

DTIC Science & Technology

2008-09-01

velocity model. The method separates the main arrivals of the regional waveform into 5 windows: Pnl (vertical and radial components), Rayleigh (vertical and...ranges out to 10°, including extensive observations of crustal thinning and thickening and various Pnl complexities. Broadband modeling in 1D, 2D...existing models perform in predicting the various regional phases, Rayleigh waves, Love waves, and Pnl waves. Previous events from this Basin-and-Range

Improvement of the Reynolds-stress model by a new pressure-strain correlation

NASA Technical Reports Server (NTRS)

Amano, Ryoichi S.; Chai, John C.

1988-01-01

A study is made to improve the predictions of Reynolds stresses in backward facing step flows, through modifications of the pressure-strain correlation. The mean-strain term of the pressure-strain correlation is formulated only in terms of nonisotropic turbulence in order to take the severe nonisotropic effect caused by a separating flow. This model is compared with other models and results are verified with experimental results.

Separation of antibody drug conjugate species by RPLC: A generic method development approach.

PubMed

Fekete, Szabolcs; Molnár, Imre; Guillarme, Davy

2017-04-15

This study reports the use of modelling software for the successful method development of IgG1 cysteine conjugated antibody drug conjugate (ADC) in RPLC. The goal of such a method is to be able to calculate the average drug to antibody ratio (DAR) of and ADC product. A generic method development strategy was proposed including the optimization of mobile phase temperature, gradient profile and mobile phase ternary composition. For the first time, a 3D retention modelling was presented for large therapeutic protein. Based on a limited number of preliminary experiments, a fast and efficient separation of the DAR species of a commercial ADC sample, namely brentuximab vedotin, was achieved. The prediction offered by the retention model was found to be highly reliable, with an average error of retention time prediction always lower than 0.5% using a 2D or 3D retention models. For routine purpose, four to six initial experiments were required to build the 2D retention models, while 12 experiments were recommended to create the 3D model. At the end, RPLC can therefore be considered as a good method for estimating the average DAR of an ADC, based on the observed peak area ratios of RPLC chromatogram of the reduced ADC sample. Copyright © 2017 Elsevier B.V. All rights reserved.

Rolling Process Modeling Report. Finite-Element Model Validation and Parametric Study on various Rolling Process parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soulami, Ayoub; Lavender, Curt A.; Paxton, Dean M.

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 validationmore » 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.« less

Jonathan J. Stickel | NREL

Science.gov Websites

research interests in fluid mechanics, rheology, separation science, reaction engineering, mathematical -established Newtonian fluid mechanics and solution reaction kinetics do not apply to these biomass slurries , and reaction kinetics of the biomass slurries in order to develop predictive modeling capabilities

Self-harm risk between adolescence and midlife in people who experienced separation from one or both parents during childhood.

PubMed

Astrup, Aske; Pedersen, Carsten B; Mok, Pearl L H; Carr, Matthew J; Webb, Roger T

2017-01-15

Experience of child-parent separation predicts adverse outcomes in later life. We conducted a detailed epidemiological examination of this complex relationship by modelling an array of separation scenarios and trajectories and subsequent risk of self-harm. This cohort study examined persons born in Denmark during 1971-1997. We measured child-parent separations each year from birth to 15th birthday via complete residential address records in the Civil Registration System. Self-harm episodes between 15th birthday and early middle age were ascertained through linkage to psychiatric and general hospital registers. Incidence rate ratios (IRRs) from Poisson regression models were estimated against a reference category of individuals not separated from their parents. All exposure models examined indicated an association with raised self-harm risk. For example, large elevations in risk were observed in relation to separation from both parents at 15th birthday (IRR 5.50, 95% CI 5.25-5.77), experiencing five or more changes in child-parent separation status (IRR 5.24, CI 4.88-5.63), and having a shorter duration of familial cohesion during upbringing. There was no significant evidence for varying strength of association according to child's gender. Measuring child-parent separation according to differential residential addresses took no account of the reason for or circumstances of these separations. These novel findings suggest that self-harm prevention initiatives should be tailored toward exposed persons who remain psychologically distressed into adulthood. These high-risk subgroups include individuals with little experience of familial cohesion during their upbringing, those with the most complicated trajectories who lived through multiple child-parent separation transitions, and those separated from both parents during early adolescence. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Computational modeling of in vitro biological responses on polymethacrylate surfaces

PubMed Central

Ghosh, Jayeeta; Lewitus, Dan Y; Chandra, Prafulla; Joy, Abraham; Bushman, Jared; Knight, Doyle; Kohn, Joachim

2011-01-01

The objective of this research was to examine the capabilities of QSPR (Quantitative Structure Property Relationship) modeling to predict specific biological responses (fibrinogen adsorption, cell attachment and cell proliferation index) on thin films of different polymethacrylates. Using 33 commercially available monomers it is theoretically possible to construct a library of over 40,000 distinct polymer compositions. A subset of these polymers were synthesized and solvent cast surfaces were prepared in 96 well plates for the measurement of fibrinogen adsorption. NIH 3T3 cell attachment and proliferation index were measured on spin coated thin films of these polymers. Based on the experimental results of these polymers, separate models were built for homo-, co-, and terpolymers in the library with good correlation between experiment and predicted values. The ability to predict biological responses by simple QSPR models for large numbers of polymers has important implications in designing biomaterials for specific biological or medical applications. PMID:21779132

Associations of Sexual Victimization, Depression, and Sexual Assertiveness with Unprotected Sex: A Test of the Multifaceted Model of HIV Risk Across Gender

PubMed Central

Morokoff, Patricia J.; Redding, Colleen A.; Harlow, Lisa L.; Cho, Sookhyun; Rossi, Joseph S.; Meier, Kathryn S.; Mayer, Kenneth H.; Koblin, Beryl; Brown-Peterside, Pamela

2014-01-01

This study examined whether the Multifaceted Model of HIV Risk (MMOHR) would predict unprotected sex based on predictors including gender, childhood sexual abuse (CSA), sexual victimization (SV), depression, and sexual assertiveness for condom use. A community-based sample of 473 heterosexually active men and women, aged 18–46 years completed survey measures of model variables. Gender predicted several variables significantly. A separate model for women demonstrated excellent fit, while the model for men demonstrated reasonable fit. Multiple sample model testing supported the use of MMOHR in both men and women, while simultaneously highlighting areas of gender difference. Prevention interventions should focus on sexual assertiveness, especially for CSA and SV survivors, as well as targeting depression, especially among men. PMID:25018617

PconsFold: improved contact predictions improve protein models.

PubMed

Michel, Mirco; Hayat, Sikander; Skwark, Marcin J; Sander, Chris; Marks, Debora S; Elofsson, Arne

2014-09-01

Recently it has been shown that the quality of protein contact prediction from evolutionary information can be improved significantly if direct and indirect information is separated. Given sufficiently large protein families, the contact predictions contain sufficient information to predict the structure of many protein families. However, since the first studies contact prediction methods have improved. Here, we ask how much the final models are improved if improved contact predictions are used. In a small benchmark of 15 proteins, we show that the TM-scores of top-ranked models are improved by on average 33% using PconsFold compared with the original version of EVfold. In a larger benchmark, we find that the quality is improved with 15-30% when using PconsC in comparison with earlier contact prediction methods. Further, using Rosetta instead of CNS does not significantly improve global model accuracy, but the chemistry of models generated with Rosetta is improved. PconsFold is a fully automated pipeline for ab initio protein structure prediction based on evolutionary information. PconsFold is based on PconsC contact prediction and uses the Rosetta folding protocol. Due to its modularity, the contact prediction tool can be easily exchanged. The source code of PconsFold is available on GitHub at https://www.github.com/ElofssonLab/pcons-fold under the MIT license. PconsC is available from http://c.pcons.net/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Reynolds-Averaged Turbulence Model Assessment for a Highly Back-Pressured Isolator Flowfield

NASA Technical Reports Server (NTRS)

Baurle, Robert A.; Middleton, Troy F.; Wilson, L. G.

2012-01-01

The use of computational fluid dynamics in scramjet engine component development is widespread in the existing literature. Unfortunately, the quantification of model-form uncertainties is rarely addressed with anything other than sensitivity studies, requiring that the computational results be intimately tied to and calibrated against existing test data. This practice must be replaced with a formal uncertainty quantification process for computational fluid dynamics to play an expanded role in the system design, development, and flight certification process. Due to ground test facility limitations, this expanded role is believed to be a requirement by some in the test and evaluation community if scramjet engines are to be given serious consideration as a viable propulsion device. An effort has been initiated at the NASA Langley Research Center to validate several turbulence closure models used for Reynolds-averaged simulations of scramjet isolator flows. The turbulence models considered were the Menter BSL, Menter SST, Wilcox 1998, Wilcox 2006, and the Gatski-Speziale explicit algebraic Reynolds stress models. The simulations were carried out using the VULCAN computational fluid dynamics package developed at the NASA Langley Research Center. A procedure to quantify the numerical errors was developed to account for discretization errors in the validation process. This procedure utilized the grid convergence index defined by Roache as a bounding estimate for the numerical error. The validation data was collected from a mechanically back-pressured constant area (1 2 inch) isolator model with an isolator entrance Mach number of 2.5. As expected, the model-form uncertainty was substantial for the shock-dominated, massively separated flowfield within the isolator as evidenced by a 6 duct height variation in shock train length depending on the turbulence model employed. Generally speaking, the turbulence models that did not include an explicit stress limiter more closely matched the measured surface pressures. This observation is somewhat surprising, given that stress-limiting models have generally been developed to better predict shock-separated flows. All of the models considered also failed to properly predict the shape and extent of the separated flow region caused by the shock boundary layer interactions. However, the best performing models were able to predict the isolator shock train length (an important metric for isolator operability margin) to within 1 isolator duct height.

Testing process predictions of models of risky choice: a quantitative model comparison approach

PubMed Central

Pachur, Thorsten; Hertwig, Ralph; Gigerenzer, Gerd; Brandstätter, Eduard

2013-01-01

This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called “similarity.” In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies. PMID:24151472

Mechanistic simulation of batch acetone-butanol-ethanol (ABE) fermentation with in situ gas stripping using Aspen Plus™.

PubMed

Darkwah, Kwabena; Nokes, Sue E; Seay, Jeffrey R; Knutson, Barbara L

2018-05-22

Process simulations of batch fermentations with in situ product separation traditionally decouple these interdependent steps by simulating a separate "steady state" continuous fermentation and separation units. In this study, an integrated batch fermentation and separation process was simulated for a model system of acetone-butanol-ethanol (ABE) fermentation with in situ gas stripping, such that the fermentation kinetics are linked in real-time to the gas stripping process. A time-dependent cell growth, substrate utilization, and product production is translated to an Aspen Plus batch reactor. This approach capitalizes on the phase equilibria calculations of Aspen Plus to predict the effect of stripping on the ABE fermentation kinetics. The product profiles of the integrated fermentation and separation are shown to be sensitive to gas flow rate, unlike separate steady state fermentation and separation simulations. This study demonstrates the importance of coupled fermentation and separation simulation approaches for the systematic analyses of unsteady state processes.

Dynamic evaluation of CMAQ part I: Separating the effects of changing emissions and changing meteorology on ozone levels between 2002 and 2005 in the eastern US

EPA Science Inventory

A dynamic evaluation of the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.1 was conducted to evaluate the model's ability to predict changes in ozone levels between 2002 and 2005, a time period characterized by emission reductions associated with the EPA's N...

Mathematical modeling of a primary zinc/air battery

NASA Technical Reports Server (NTRS)

Mao, Z.; White, R. E.

1992-01-01

The mathematical model developed by Sunu and Bennion has been extended to include the separator, precipitation of both solid ZnO and K2Zn(OH)4, and the air electrode, and has been used to investigate the behavior of a primary Zn-Air battery with respect to battery design features. Predictions obtained from the model indicate that anode material utilization is predominantly limited by depletion of the concentration of hydroxide ions. The effect of electrode thickness on anode material utilization is insignificant, whereas material loading per unit volume has a great effect on anode material utilization; a higher loading lowers both the anode material utilization and delivered capacity. Use of a thick separator will increase the anode material utilization, but may reduce the cell voltage.

Genomic Prediction of Gene Bank Wheat Landraces

PubMed Central

Crossa, José; Jarquín, Diego; Franco, Jorge; Pérez-Rodríguez, Paulino; Burgueño, Juan; Saint-Pierre, Carolina; Vikram, Prashant; Sansaloni, Carolina; Petroli, Cesar; Akdemir, Deniz; Sneller, Clay; Reynolds, Matthew; Tattaris, Maria; Payne, Thomas; Guzman, Carlos; Peña, Roberto J.; Wenzl, Peter; Singh, Sukhwinder

2016-01-01

This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials. PMID:27172218

Rapid prototyping and parametric optimization of plastic acoustofluidic devices for blood-bacteria separation.

PubMed

Silva, R; Dow, P; Dubay, R; Lissandrello, C; Holder, J; Densmore, D; Fiering, J

2017-09-01

Acoustic manipulation has emerged as a versatile method for microfluidic separation and concentration of particles and cells. Most recent demonstrations of the technology use piezoelectric actuators to excite resonant modes in silicon or glass microchannels. Here, we focus on acoustic manipulation in disposable, plastic microchannels in order to enable a low-cost processing tool for point-of-care diagnostics. Unfortunately, the performance of resonant acoustofluidic devices in plastic is hampered by a lack of a predictive model. In this paper, we build and test a plastic blood-bacteria separation device informed by a design of experiments approach, parametric rapid prototyping, and screening by image-processing. We demonstrate that the new device geometry can separate bacteria from blood while operating at 275% greater flow rate as well as reduce the power requirement by 82%, while maintaining equivalent separation performance and resolution when compared to the previously published plastic acoustofluidic separation device.

NASA Trapezoidal Wing Computations Including Transition and Advanced Turbulence Modeling

NASA Technical Reports Server (NTRS)

Rumsey, C. L.; Lee-Rausch, E. M.

2012-01-01

Flow about the NASA Trapezoidal Wing is computed with several turbulence models by using grids from the first High Lift Prediction Workshop in an effort to advance understanding of computational fluid dynamics modeling for this type of flowfield. Transition is accounted for in many of the computations. In particular, a recently-developed 4-equation transition model is utilized and works well overall. Accounting for transition tends to increase lift and decrease moment, which improves the agreement with experiment. Upper surface flap separation is reduced, and agreement with experimental surface pressures and velocity profiles is improved. The predicted shape of wakes from upstream elements is strongly influenced by grid resolution in regions above the main and flap elements. Turbulence model enhancements to account for rotation and curvature have the general effect of increasing lift and improving the resolution of the wing tip vortex as it convects downstream. However, none of the models improve the prediction of surface pressures near the wing tip, where more grid resolution is needed.

Tail Separation and Density Effects on the Underwater Trajectory of the JDAM

DTIC Science & Technology

2009-12-01

countermeasure technologies that fulfills this criteria—the use of the Joint Direct Attack Munition (JDAM) to clear a minefield. It updates the general...physics-based, six degrees of freedom model, STRIKE35, to predict the three-dimensional, free-fall trajectory and orientation of a MK-84 bomb...simulating the JDAM) through a water column. It accurately predicts the final detonation position relative to an underwater mine in the very shallow

Dusty plasma ring model

NASA Astrophysics Data System (ADS)

Sheridan, T. E.

2009-12-01

A model of a dusty plasma (Yukawa) ring is presented. We consider n identical particles confined in a two-dimensional (2D) annular potential well and interacting through a Debye (i.e. Yukawa or screened Coulomb) potential. Equilibrium configurations are computed versus n, the Debye shielding parameter and the trap radius. When the particle separation exceeds a critical value the particles form a 1D chain with a ring topology. Below the critical separation the zigzag instability gives a 2D configuration. Computed critical separations are shown to agree well with a theoretical prediction for the zigzag threshold. Normal mode spectra for 1D rings are computed and found to be in excellent agreement with the longitudinal and transverse dispersion relations for unbounded straight chains. When the longitudinal and transverse dispersion relations intersect we observe a resonance due to the finite curvature of the ring.

Deep Ensemble Learning for Monaural Speech Separation

DTIC Science & Technology

2015-02-01

cse.ohio- state.edu). typically predict the ideal binary mask (IBM) or ideal ratio mask ( IRM ). For the IBM [21], a T-F unit is assigned 1, if the signal...dominance. For the IRM [17], a T- F unit is assigned some ratio of target energy and mixture energy. Kim et al. [15] used Gaussian mixture models (GMM...significantly outperforms earlier separation methods. Subsequently, Wang et al. [23] examined a number of training targets and suggested that the IRM should be

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry.

PubMed

Dodds, James N; May, Jody C; McLean, John A

2017-11-21

Here we examine the relationship among resolving power (R p ), resolution (R pp ), and collision cross section (CCS) for compounds analyzed in previous ion mobility (IM) experiments representing a wide variety of instrument platforms and IM techniques. Our previous work indicated these three variables effectively describe and predict separation efficiency for drift tube ion mobility spectrometry experiments. In this work, we seek to determine if our previous findings are a general reflection of IM behavior that can be applied to various instrument platforms and mobility techniques. Results suggest IM distributions are well characterized by a Gaussian model and separation efficiency can be predicted on the basis of the empirical difference in the gas-phase CCS and a CCS-based resolving power definition (CCS/ΔCCS). Notably traveling wave (TWIMS) was found to operate at resolutions substantially higher than a single-peak resolving power suggested. When a CCS-based R p definition was utilized, TWIMS was found to operate at a resolving power between 40 and 50, confirming the previous observations by Giles and co-workers. After the separation axis (and corresponding resolving power) is converted to cross section space, it is possible to effectively predict separation behavior for all mobility techniques evaluated (i.e., uniform field, trapped ion mobility, traveling wave, cyclic, and overtone instruments) using the equations described in this work. Finally, we are able to establish for the first time that the current state-of-the-art ion mobility separations benchmark at a CCS-based resolving power of >300 that is sufficient to differentiate analyte ions with CCS differences as small as 0.5%.

Innovative high-performance liquid chromatography method development for the screening of 19 antimalarial drugs based on a generic approach, using design of experiments, independent component analysis and design space.

PubMed

Debrus, B; Lebrun, P; Kindenge, J Mbinze; Lecomte, F; Ceccato, A; Caliaro, G; Mbay, J Mavar Tayey; Boulanger, B; Marini, R D; Rozet, E; Hubert, Ph

2011-08-05

An innovative methodology based on design of experiments (DoE), independent component analysis (ICA) and design space (DS) was developed in previous works and was tested out with a mixture of 19 antimalarial drugs. This global LC method development methodology (i.e. DoE-ICA-DS) was used to optimize the separation of 19 antimalarial drugs to obtain a screening method. DoE-ICA-DS methodology is fully compliant with the current trend of quality by design. DoE was used to define the set of experiments to model the retention times at the beginning, the apex and the end of each peak. Furthermore, ICA was used to numerically separate coeluting peaks and estimate their unbiased retention times. Gradient time, temperature and pH were selected as the factors of a full factorial design. These retention times were modelled by stepwise multiple linear regressions. A recently introduced critical quality attribute, namely the separation criterion (S), was also used to assess the quality of separations rather than using the resolution. Furthermore, the resulting mathematical models were also studied from a chromatographic point of view to understand and investigate the chromatographic behaviour of each compound. Good adequacies were found between the mathematical models and the expected chromatographic behaviours predicted by chromatographic theory. Finally, focusing at quality risk management, the DS was computed as the multidimensional subspace where the probability for the separation criterion to lie in acceptance limits was higher than a defined quality level. The DS was computed propagating the prediction error from the modelled responses to the quality criterion using Monte Carlo simulations. DoE-ICA-DS allowed encountering optimal operating conditions to obtain a robust screening method for the 19 considered antimalarial drugs in the framework of the fight against counterfeit medicines. Moreover and only on the basis of the same data set, a dedicated method for the determination of three antimalarial compounds in a pharmaceutical formulation was optimized to demonstrate both the efficiency and flexibility of the methodology proposed in the present study. Copyright © 2011 Elsevier B.V. All rights reserved.

Cognitive models of risky choice: parameter stability and predictive accuracy of prospect theory.

PubMed

Glöckner, Andreas; Pachur, Thorsten

2012-04-01

In the behavioral sciences, a popular approach to describe and predict behavior is cognitive modeling with adjustable parameters (i.e., which can be fitted to data). Modeling with adjustable parameters allows, among other things, measuring differences between people. At the same time, parameter estimation also bears the risk of overfitting. Are individual differences as measured by model parameters stable enough to improve the ability to predict behavior as compared to modeling without adjustable parameters? We examined this issue in cumulative prospect theory (CPT), arguably the most widely used framework to model decisions under risk. Specifically, we examined (a) the temporal stability of CPT's parameters; and (b) how well different implementations of CPT, varying in the number of adjustable parameters, predict individual choice relative to models with no adjustable parameters (such as CPT with fixed parameters, expected value theory, and various heuristics). We presented participants with risky choice problems and fitted CPT to each individual's choices in two separate sessions (which were 1 week apart). All parameters were correlated across time, in particular when using a simple implementation of CPT. CPT allowing for individual variability in parameter values predicted individual choice better than CPT with fixed parameters, expected value theory, and the heuristics. CPT's parameters thus seem to pick up stable individual differences that need to be considered when predicting risky choice. Copyright © 2011 Elsevier B.V. All rights reserved.

Phase separation and the formation of cellular bodies

NASA Astrophysics Data System (ADS)

Xu, Bin; Broedersz, Chase P.; Meir, Yigal; Wingreen, Ned S.

Cellular bodies in eukaryotic cells spontaneously assemble to form cellular compartments. Among other functions, these bodies carry out essential biochemical reactions. Cellular bodies form micron-sized structures, which, unlike canonical cell organelles, are not surrounded by membranes. A recent in vitro experiment has shown that phase separation of polymers in solution can explain the formation of cellular bodies. We constructed a lattice-polymer model to capture the essential mechanism leading to this phase separation. We used both analytical and numerical tools to predict the phase diagram of a system of two interacting polymers, including the concentration of each polymer type in the condensed and dilute phase.

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

Modeling of an integrated fermentation/membrane extraction process for the production of 2-phenylethanol and 2-phenylethylacetate.

PubMed

Adler, Philipp; Hugen, Thorsten; Wiewiora, Marzena; Kunz, Benno

2011-03-07

An unstructured model for an integrated fermentation/membrane extraction process for the production of the aroma compounds 2-phenylethanol and 2-phenylethylacetate by Kluyveromyces marxianus CBS 600 was developed. The extent to which this model, based only on data from the conventional fermentation and separation processes, provided an estimation of the integrated process was evaluated. The effect of product inhibition on specific growth rate and on biomass yield by both aroma compounds was approximated by multivariate regression. Simulations of the respective submodels for fermentation and the separation process matched well with experimental results. With respect to the in situ product removal (ISPR) process, the effect of reduced product inhibition due to product removal on specific growth rate and biomass yield was predicted adequately by the model simulations. Overall product yields were increased considerably in this process (4.0 g/L 2-PE+2-PEA vs. 1.4 g/L in conventional fermentation) and were even higher than predicted by the model. To describe the effect of product concentration on product formation itself, the model was extended using results from the conventional and the ISPR process, thus agreement between model and experimental data improved notably. Therefore, this model can be a useful tool for the development and optimization of an efficient integrated bioprocess. Copyright © 2010 Elsevier Inc. All rights reserved.

Lagrangian predictability characteristics of an Ocean Model

NASA Astrophysics Data System (ADS)

Lacorata, Guglielmo; Palatella, Luigi; Santoleri, Rosalia

2014-11-01

The Mediterranean Forecasting System (MFS) Ocean Model, provided by INGV, has been chosen as case study to analyze Lagrangian trajectory predictability by means of a dynamical systems approach. To this regard, numerical trajectories are tested against a large amount of Mediterranean drifter data, used as sample of the actual tracer dynamics across the sea. The separation rate of a trajectory pair is measured by computing the Finite-Scale Lyapunov Exponent (FSLE) of first and second kind. An additional kinematic Lagrangian model (KLM), suitably treated to avoid "sweeping"-related problems, has been nested into the MFS in order to recover, in a statistical sense, the velocity field contributions to pair particle dispersion, at mesoscale level, smoothed out by finite resolution effects. Some of the results emerging from this work are: (a) drifter pair dispersion displays Richardson's turbulent diffusion inside the [10-100] km range, while numerical simulations of MFS alone (i.e., without subgrid model) indicate exponential separation; (b) adding the subgrid model, model pair dispersion gets very close to observed data, indicating that KLM is effective in filling the energy "mesoscale gap" present in MFS velocity fields; (c) there exists a threshold size beyond which pair dispersion becomes weakly sensitive to the difference between model and "real" dynamics; (d) the whole methodology here presented can be used to quantify model errors and validate numerical current fields, as far as forecasts of Lagrangian dispersion are concerned.

A statistical model including age to predict passenger postures in the rear seats of automobiles.

PubMed

Park, Jangwoon; Ebert, Sheila M; Reed, Matthew P; Hallman, Jason J

2016-06-01

Few statistical models of rear seat passenger posture have been published, and none has taken into account the effects of occupant age. This study developed new statistical models for predicting passenger postures in the rear seats of automobiles. Postures of 89 adults with a wide range of age and body size were measured in a laboratory mock-up in seven seat configurations. Posture-prediction models for female and male passengers were separately developed by stepwise regression using age, body dimensions, seat configurations and two-way interactions as potential predictors. Passenger posture was significantly associated with age and the effects of other two-way interaction variables depended on age. A set of posture-prediction models are presented for women and men, and the prediction results are compared with previously published models. This study is the first study of passenger posture to include a large cohort of older passengers and the first to report a significant effect of age for adults. The presented models can be used to position computational and physical human models for vehicle design and assessment. Practitioner Summary: The significant effects of age, body dimensions and seat configuration on rear seat passenger posture were identified. The models can be used to accurately position computational human models or crash test dummies for older passengers in known rear seat configurations.

Enzyme clustering accelerates processing of intermediates through metabolic channeling

PubMed Central

Castellana, Michele; Wilson, Maxwell Z.; Xu, Yifan; Joshi, Preeti; Cristea, Ileana M.; Rabinowitz, Joshua D.; Gitai, Zemer; Wingreen, Ned S.

2015-01-01

We present a quantitative model to demonstrate that coclustering multiple enzymes into compact agglomerates accelerates the processing of intermediates, yielding the same efficiency benefits as direct channeling, a well-known mechanism in which enzymes are funneled between enzyme active sites through a physical tunnel. The model predicts the separation and size of coclusters that maximize metabolic efficiency, and this prediction is in agreement with previously reported spacings between coclusters in mammalian cells. For direct validation, we study a metabolic branch point in Escherichia coli and experimentally confirm the model prediction that enzyme agglomerates can accelerate the processing of a shared intermediate by one branch, and thus regulate steady-state flux division. Our studies establish a quantitative framework to understand coclustering-mediated metabolic channeling and its application to both efficiency improvement and metabolic regulation. PMID:25262299

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahedo, Eduardo; Merino, Mario

A previous axisymmetric model of the supersonic expansion of a collisionless, hot plasma in a divergent magnetic nozzle is extended here in order to include electron-inertia effects. Up to dominant order on all components of the electron velocity, electron momentum equations still reduce to three conservation laws. Electron inertia leads to outward electron separation from the magnetic streamtubes. The progressive plasma filling of the adjacent vacuum region is consistent with electron-inertia being part of finite electron Larmor radius effects, which increase downstream and eventually demagnetize the plasma. Current ambipolarity is not fulfilled and ion separation can be either outwards ormore » inwards of magnetic streamtubes, depending on their magnetization. Electron separation penalizes slightly the plume efficiency and is larger for plasma beams injected with large pressure gradients. An alternative nonzero electron-inertia model [E. Hooper, J. Propul. Power 9, 757 (1993)] based on cold plasmas and current ambipolarity, which predicts inwards electron separation, is discussed critically. A possible competition of the gyroviscous force with electron-inertia effects is commented briefly.« less

Predicting mixed-gas adsorption equilibria on activated carbon for precombustion CO2 capture.

PubMed

García, S; Pis, J J; Rubiera, F; Pevida, C

2013-05-21

We present experimentally measured adsorption isotherms of CO2, H2, and N2 on a phenol-formaldehyde resin-based activated carbon, which had been previously synthesized for the separation of CO2 in a precombustion capture process. The single component adsorption isotherms were measured in a magnetic suspension balance at three different temperatures (298, 318, and 338 K) and over a large range of pressures (from 0 to 3000-4000 kPa). These values cover the temperature and pressure conditions likely to be found in a precombustion capture scenario, where CO2 needs to be separated from a CO2/H2/N2 gas stream at high pressure (~1000-1500 kPa) and with a high CO2 concentration (~20-40 vol %). Data on the pure component isotherms were correlated using the Langmuir, Sips, and dual-site Langmuir (DSL) models, i.e., a two-, three-, and four-parameter model, respectively. By using the pure component isotherm fitting parameters, adsorption equilibrium was then predicted for multicomponent gas mixtures by the extended models. The DSL model was formulated considering the energetic site-matching concept, recently addressed in the literature. Experimental gas-mixture adsorption equilibrium data were calculated from breakthrough experiments conducted in a lab-scale fixed-bed reactor and compared with the predictions from the models. Breakthrough experiments were carried out at a temperature of 318 K and five different pressures (300, 500, 1000, 1500, and 2000 kPa) where two different CO2/H2/N2 gas mixtures were used as the feed gas in the adsorption step. The DSL model was found to be the one that most accurately predicted the CO2 adsorption equilibrium in the multicomponent mixture. The results presented in this work highlight the importance of performing experimental measurements of mixture adsorption equilibria, as they are of utmost importance to discriminate between models and to correctly select the one that most closely reflects the actual process.

Integrating uniform design and response surface methodology to optimize thiacloprid suspension

PubMed Central

Li, Bei-xing; Wang, Wei-chang; Zhang, Xian-peng; Zhang, Da-xia; Mu, Wei; Liu, Feng

2017-01-01

A model 25% suspension concentrate (SC) of thiacloprid was adopted to evaluate an integrative approach of uniform design and response surface methodology. Tersperse2700, PE1601, xanthan gum and veegum were the four experimental factors, and the aqueous separation ratio and viscosity were the two dependent variables. Linear and quadratic polynomial models of stepwise regression and partial least squares were adopted to test the fit of the experimental data. Verification tests revealed satisfactory agreement between the experimental and predicted data. The measured values for the aqueous separation ratio and viscosity were 3.45% and 278.8 mPa·s, respectively, and the relative errors of the predicted values were 9.57% and 2.65%, respectively (prepared under the proposed conditions). Comprehensive benefits could also be obtained by appropriately adjusting the amount of certain adjuvants based on practical requirements. Integrating uniform design and response surface methodology is an effective strategy for optimizing SC formulas. PMID:28383036

Fostering marginalized youths' political participation: longitudinal roles of parental political socialization and youth sociopolitical development.

PubMed

Diemer, Matthew A

2012-09-01

This study examines the roles of parental political socialization and the moral commitment to change social inequalities in predicting marginalized youths' (defined here as lower-SES youth of color) political participation. These issues are examined by applying structural equation modeling to a longitudinal panel of youth. Because tests of measurement invariance suggested racial/ethnic heterogeneity, the structural model was fit separately for three racial/ethnic groups. For each group, parental political socialization: discussion predicted youths' commitment to produce social change and for two groups, longitudinally predicted political participation. This study contributes to the literature by examining civic/political participation among disparate racial/ethnic groups, addresses an open scholarly question (whether youths' commitment to create social change predicts their "traditional" participation), and emphasizes parents' role in fostering marginalized youths' civic and political participation.

NASA AVOSS Fast-Time Wake Prediction Models: User's Guide

NASA Technical Reports Server (NTRS)

Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew

2014-01-01

The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.

Work-Related Biomechanical Exposure and Job Strain as Separate and Joint Predictors of Musculoskeletal Diseases: A 28-Year Prospective Follow-up Study.

PubMed

Prakash, K C; Neupane, Subas; Leino-Arjas, Päivi; von Bonsdorff, Mikaela B; Rantanen, Taina; von Bonsdorff, Monika E; Seitsamo, Jorma; Ilmarinen, Juhani; Nygård, Clas-Håkan

2017-12-01

We investigated how work-related biomechanical exposure and job strain in midlife separately and jointly predicted back and degenerative musculoskeletal diseases (MSDs). A total of 6,257 employees participated in the Finnish Longitudinal Study on Aging Municipal Employees (FLAME) in 1981 and were followed up for 28 years. Risk ratios and the relative excessive risk due to interaction and 95% confidence intervals were modeled for separate and joint prediction estimates, respectively. After adjustment for confounders, job strain predicted degenerative MSDs among women after 4 and 11 years of follow-up. After 11 years, both exposures predicted both types of MSDs among men. Joint exposure predicted both types of MSDs after 4 years among women (for back MSDs, risk ratio (RR) = 1.58, 95% confidence interval (CI): 1.15, 2.18; for degenerative MSDs, RR = 1.59, 95% CI: 1.21, 2.07) and men (for back MSDs, RR = 1.50, 95% CI: 1.05, 2.15; for degenerative MSDs, RR = 1.61, 95% CI: 1.16, 2.22) and both types of MSDs after 11 years (for back MSDs, RR = 1.72, 95% CI: 1.21, 2.43; for degenerative MSDs, RR = 1.68, 95% CI: 1.25, 2.46) among men only, but the relative excessive risk due to interaction was not significant throughout. However, after 28 years, the separate and joint exposures did not predict MSDs. Workplace interventions should be focused on reducing job strain along with biomechanical exposure for possible prevention of MSDs in working life and around the time of retirement, but there may be other pathways of onset of MSDs in old age. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Benchmarking the Performance of Exchange-Correlation Functionals for Predicting Two-Photon Absorption Strengths.

PubMed

Beerepoot, Maarten T P; Alam, Md Mehboob; Bednarska, Joanna; Bartkowiak, Wojciech; Ruud, Kenneth; Zaleśny, Robert

2018-06-15

The present work investigates the performance of exchange-correlation functionals in the prediction of two-photon absorption (2PA) strengths. For this purpose, we considered six common functionals used for studying 2PA processes and tested these on six organoboron chelates. The set consisted of two semilocal (PBE and BLYP), two hybrid (B3LYP and PBE0), and two range-separated (LC-BLYP and CAM-B3LYP) functionals. The RI-CC2 method was chosen as a reference level and was found to give results consistent with the experimental data that are available for three of the molecules considered. Of the six exchange-correlation functionals studied, only the range-separated functionals predict an ordering of the 2PA strengths that is consistent with experimental and RI-CC2 results. Even though the range-separated functionals predict correct relative trends, the absolute values for the 2PA strengths are underestimated by a factor of 2-6 for the molecules considered. An in-depth analysis, on the basis of the derived generalized few-state model expression for the 2PA strength for a coupled-cluster wave function, reveals that the problem with these functionals can be linked to underestimated excited-state dipole moments and, to a lesser extent, overestimated excitation energies. The semilocal and hybrid functionals exhibit less predictable errors and a variation in the 2PA strengths in disagreement with the reference results. The semilocal and hybrid functionals show smaller average errors than the range-separated functionals, but our analysis reveals that this is due to fortuitous error cancellation between excitation energies and the transition dipole moments. Our results constitute a warning against using currently available exchange-correlation functionals in the prediction of 2PA strengths and highlight the need for functionals that correctly describe the electron density of excited electronic states.

Combined electrochemical, heat generation, and thermal model for large prismatic lithium-ion batteries in real-time applications

NASA Astrophysics Data System (ADS)

Farag, Mohammed; Sweity, Haitham; Fleckenstein, Matthias; Habibi, Saeid

2017-08-01

Real-time prediction of the battery's core temperature and terminal voltage is very crucial for an accurate battery management system. In this paper, a combined electrochemical, heat generation, and thermal model is developed for large prismatic cells. The proposed model consists of three sub-models, an electrochemical model, heat generation model, and thermal model which are coupled together in an iterative fashion through physicochemical temperature dependent parameters. The proposed parameterization cycles identify the sub-models' parameters separately by exciting the battery under isothermal and non-isothermal operating conditions. The proposed combined model structure shows accurate terminal voltage and core temperature prediction at various operating conditions while maintaining a simple mathematical structure, making it ideal for real-time BMS applications. Finally, the model is validated against both isothermal and non-isothermal drive cycles, covering a broad range of C-rates, and temperature ranges [-25 °C to 45 °C].

Minnowbrook IV: 2003 Workshop on Transition and Unsteady Aspects of Turbomachinery Flows

NASA Technical Reports Server (NTRS)

LaGraff, John E. (Editor); Ashpis, David E.

2004-01-01

This Minnowbrook IV 2003 workshop on Transition and Unsteady Aspects of Turbomachinery Flows includes the following topics: 1) Current Issues in Unsteady Turbomachinery Flows; 2) Global Instability and Control of Low-Pressure Turbine Flows; 3) Influence of End Wall Leakage on Secondary Flow Development in Axial Turbines; 4) Active and Passive Flow Control on Low Pressure Turbine Airfoils; 5) Experimental and Numerical Investigation of Transitional Flows as Affected by Passing Wakes; 6) Effects of Freestream Turbulence on Turbine Blade Heat Transfer; 7) Bypass Transition Via Continuous Modes and Unsteady Effects on Film Cooling; 8) High Frequency Surface Heat Flux Imaging of Bypass Transition; 9) Skin Friction and Heat Flux Oscillations in Upstream Moving Wave Packets; 10) Transition Mechanisms and Use of Surface Roughness to Enhance the Benefits of Wake Passing in LP Turbines; 11) Transient Growth Approach to Roughness-Induced Transition; 12) Roughness- and Freestream-Turbulence-Induced Transient Growth as a Bypass Transition Mechanism; 13) Receptivity Calculations as a Means to Predicting Transition; 14) On Streamwise Vortices in a Curved Wall Jet and Their Effect on the Mean Flow; 15) Plasma Actuators for Separation Control of Low Pressure Turbine Blades; 16) Boundary-Layer Separation Control Under Low-Pressure-Turbine Conditions Using Glow-Discharge Plasma Actuators; 17) Control of Separation for Low Pressure Turbine Blades: Numerical Simulation; 18) Effects of Elevated Free-Stream Turbulence on Active Control of a Separation Bubble; 19) Wakes, Calming and Transition Under Strong Adverse Pressure Gradients; 20) Transitional Bubble in Periodic Flow Phase Shift; 21) Modelling Spots: The Calmed Region, Pressure Gradient Effects and Background; 22) Modeling of Unsteady Transitional Flow on Axial Compressor Blades; 23) Challenges in Predicting Component Efficiencies in Turbomachines With Low Reynolds Number Blading; 24) Observations on the Causal Relationship Between Blade Count and Developing Rotating Stall in a Four Stage Axial Compressor; 25) Experimental and Numerical Study of Non-Linear Interactions in Transonic Nozzle Flow; 26) Clocking Effects on a Modern Stage and One-Half Transonic Turbine; 27) DNS and LES of Transition on Turbine Blades; 28) The Use of Cellular Automata in Modeling the Transition; 29) Predicting Unsteady Buffet Onset Using RANS Solutions; 30) Transition Modelling With the SST Turbulence Model and an Intermittency Transport; and 31) Equation Workshop Summary Transcript

Particle drift model for Z-pinch-driven magneto-Rayleigh-Taylor instability

NASA Astrophysics Data System (ADS)

Dan, Jia Kun; Xu, Qiang; Wang, Kun Lun; Ren, Xiao Dong; Huang, Xian Bin

2016-09-01

A theoretical model of Z-pinch driven magneto-Rayleigh-Taylor instability is proposed based on the particle drift point of view, which can explain the helical instability structure observed in premagnetized imploding liner experiments. It is demonstrated that all possible drift motions, including polarization drift, gradient drift, and curvature drift, which can lead to charge separations, each will attribute to an effective gravity acceleration. Theoretical predictions given by this model are dramatically different from those given by previous theories which have been readily recovered in the theory presented here as a limiting case. The theory shows qualitative agreement with available experimental data of the pitch angle and provides certain predictions to be verified.

Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

PubMed

Hassanpour, Saeed; Langlotz, Curtis P

2016-01-01

Imaging utilization has significantly increased over the last two decades, and is only recently showing signs of moderating. To help healthcare providers identify patients at risk for high imaging utilization, we developed a prediction model to recognize high imaging utilizers based on their initial imaging reports. The prediction model uses a machine learning text classification framework. In this study, we used radiology reports from 18,384 patients with at least one abdomen computed tomography study in their imaging record at Stanford Health Care as the training set. We modeled the radiology reports in a vector space and trained a support vector machine classifier for this prediction task. We evaluated our model on a separate test set of 4791 patients. In addition to high prediction accuracy, in our method, we aimed at achieving high specificity to identify patients at high risk for high imaging utilization. Our results (accuracy: 94.0%, sensitivity: 74.4%, specificity: 97.9%, positive predictive value: 87.3%, negative predictive value: 95.1%) show that a prediction model can enable healthcare providers to identify in advance patients who are likely to be high utilizers of imaging services. Machine learning classifiers developed from narrative radiology reports are feasible methods to predict imaging utilization. Such systems can be used to identify high utilizers, inform future image ordering behavior, and encourage judicious use of imaging. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Does Parsonnet scoring model predict mortality following adult cardiac surgery in India?

PubMed

Srilata, Moningi; Padhy, Narmada; Padmaja, Durga; Gopinath, Ramachandran

2015-01-01

To validate the Parsonnet scoring model to predict mortality following adult cardiac surgery in Indian scenario. A total of 889 consecutive patients undergoing adult cardiac surgery between January 2010 and April 2011 were included in the study. The Parsonnet score was determined for each patient and its predictive ability for in-hospital mortality was evaluated. The validation of Parsonnet score was performed for the total data and separately for the sub-groups coronary artery bypass grafting (CABG), valve surgery and combined procedures (CABG with valve surgery). The model calibration was performed using Hosmer-Lemeshow goodness of fit test and receiver operating characteristics (ROC) analysis for discrimination. Independent predictors of mortality were assessed from the variables used in the Parsonnet score by multivariate regression analysis. The overall mortality was 6.3% (56 patients), 7.1% (34 patients) for CABG, 4.3% (16 patients) for valve surgery and 16.2% (6 patients) for combined procedures. The Hosmer-Lemeshow statistic was <0.05 for the total data and also within the sub-groups suggesting that the predicted outcome using Parsonnet score did not match the observed outcome. The area under the ROC curve for the total data was 0.699 (95% confidence interval 0.62-0.77) and when tested separately, it was 0.73 (0.64-0.81) for CABG, 0.79 (0.63-0.92) for valve surgery (good discriminatory ability) and only 0.55 (0.26-0.83) for combined procedures. The independent predictors of mortality determined for the total data were low ejection fraction (odds ratio [OR] - 1.7), preoperative intra-aortic balloon pump (OR - 10.7), combined procedures (OR - 5.1), dialysis dependency (OR - 23.4), and re-operation (OR - 9.4). The Parsonnet score yielded a good predictive value for valve surgeries, moderate predictive value for the total data and for CABG and poor predictive value for combined procedures.

Predictive Computational Modeling of Chromatin Folding

NASA Astrophysics Data System (ADS)

di Pierro, Miichele; Zhang, Bin; Wolynes, Peter J.; Onuchic, Jose N.

In vivo, the human genome folds into well-determined and conserved three-dimensional structures. The mechanism driving the folding process remains unknown. We report a theoretical model (MiChroM) for chromatin derived by using the maximum entropy principle. The proposed model allows Molecular Dynamics simulations of the genome using as input the classification of loci into chromatin types and the presence of binding sites of loop forming protein CTCF. The model was trained to reproduce the Hi-C map of chromosome 10 of human lymphoblastoid cells. With no additional tuning the model was able to predict accurately the Hi-C maps of chromosomes 1-22 for the same cell line. Simulations show unknotted chromosomes, phase separation of chromatin types and a preference of chromatin of type A to sit at the periphery of the chromosomes.

Can spatial statistical river temperature models be transferred between catchments?

NASA Astrophysics Data System (ADS)

Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.

2017-09-01

There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across multiple catchments and larger spatial scales.

Pattern separation in the hippocampus: distinct circuits under different conditions.

PubMed

Kassab, Randa; Alexandre, Frédéric

2018-04-11

Pattern separation is a fundamental hippocampal process thought to be critical for distinguishing similar episodic memories, and has long been recognized as a natural function of the dentate gyrus (DG), supporting autoassociative learning in CA3. Understanding how neural circuits within the DG-CA3 network mediate this process has received much interest, yet the exact mechanisms behind remain elusive. Here, we argue for the case that sparse coding is necessary but not sufficient to ensure efficient separation and, alternatively, propose a possible interaction of distinct circuits which, nevertheless, act in synergy to produce a unitary function of pattern separation. The proposed circuits involve different functional granule-cell populations, a primary population mediates sparsification and provides recurrent excitation to the other populations which are related to additional pattern separation mechanisms with higher degrees of robustness against interference in CA3. A variety of top-down and bottom-up factors, such as motivation, emotion, and pattern similarity, control the selection of circuitry depending on circumstances. According to this framework, a computational model is implemented and tested against model variants in a series of numerical simulations and biological experiments. The results demonstrate that the model combines fast learning, robust pattern separation and high storage capacity. It also accounts for the controversy around the involvement of the DG during memory recall, explains other puzzling findings, and makes predictions that can inform future investigations.

Extended charge banking model of dual path shocks for implantable cardioverter defibrillators

PubMed Central

Dosdall, Derek J; Sweeney, James D

2008-01-01

Background Single path defibrillation shock methods have been improved through the use of the Charge Banking Model of defibrillation, which predicts the response of the heart to shocks as a simple resistor-capacitor (RC) circuit. While dual path defibrillation configurations have significantly reduced defibrillation thresholds, improvements to dual path defibrillation techniques have been limited to experimental observations without a practical model to aid in improving dual path defibrillation techniques. Methods The Charge Banking Model has been extended into a new Extended Charge Banking Model of defibrillation that represents small sections of the heart as separate RC circuits, uses a weighting factor based on published defibrillation shock field gradient measures, and implements a critical mass criteria to predict the relative efficacy of single and dual path defibrillation shocks. Results The new model reproduced the results from several published experimental protocols that demonstrated the relative efficacy of dual path defibrillation shocks. The model predicts that time between phases or pulses of dual path defibrillation shock configurations should be minimized to maximize shock efficacy. Discussion Through this approach the Extended Charge Banking Model predictions may be used to improve dual path and multi-pulse defibrillation techniques, which have been shown experimentally to lower defibrillation thresholds substantially. The new model may be a useful tool to help in further improving dual path and multiple pulse defibrillation techniques by predicting optimal pulse durations and shock timing parameters. PMID:18673561

Assessing the capacity of social determinants of health data to augment predictive models identifying patients in need of wraparound social services.

PubMed

Kasthurirathne, Suranga N; Vest, Joshua R; Menachemi, Nir; Halverson, Paul K; Grannis, Shaun J

2018-01-01

A growing variety of diverse data sources is emerging to better inform health care delivery and health outcomes. We sought to evaluate the capacity for clinical, socioeconomic, and public health data sources to predict the need for various social service referrals among patients at a safety-net hospital. We integrated patient clinical data and community-level data representing patients' social determinants of health (SDH) obtained from multiple sources to build random forest decision models to predict the need for any, mental health, dietitian, social work, or other SDH service referrals. To assess the impact of SDH on improving performance, we built separate decision models using clinical and SDH determinants and clinical data only. Decision models predicting the need for any, mental health, and dietitian referrals yielded sensitivity, specificity, and accuracy measures ranging between 60% and 75%. Specificity and accuracy scores for social work and other SDH services ranged between 67% and 77%, while sensitivity scores were between 50% and 63%. Area under the receiver operating characteristic curve values for the decision models ranged between 70% and 78%. Models for predicting the need for any services reported positive predictive values between 65% and 73%. Positive predictive values for predicting individual outcomes were below 40%. The need for various social service referrals can be predicted with considerable accuracy using a wide range of readily available clinical and community data that measure socioeconomic and public health conditions. While the use of SDH did not result in significant performance improvements, our approach represents a novel and important application of risk predictive modeling. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Seismoelectric data processing for surface surveys of shallow targets

USGS Publications Warehouse

Haines, S.S.; Guitton, A.; Biondi, B.

2007-01-01

The utility of the seismoelectric method relies on the development of methods to extract the signal of interest from background and source-generated coherent noise that may be several orders-of-magnitude stronger. We compare data processing approaches to develop a sequence of preprocessing and signal/noise separation and to quantify the noise level from which we can extract signal events. Our preferred sequence begins with the removal of power line harmonic noise and the use of frequency filters to minimize random and source-generated noise. Mapping to the linear Radon domain with an inverse process incorporating a sparseness constraint provides good separation of signal from noise, though it is ineffective on noise that shows the same dip as the signal. Similarly, the seismoelectric signal and noise do not separate cleanly in the Fourier domain, so f-k filtering can not remove all of the source-generated noise and it also disrupts signal amplitude patterns. We find that prediction-error filters provide the most effective method to separate signal and noise, while also preserving amplitude information, assuming that adequate pattern models can be determined for the signal and noise. These Radon-domain and prediction-error-filter methods successfully separate signal from <33 dB stronger noise in our test data. ?? 2007 Society of Exploration Geophysicists.

Certainties and Uncertainties in CFD Prediction of the End of the Vortex Behaviour in Centrifugal Separators

NASA Astrophysics Data System (ADS)

Pisarev, Gleb I.; Hoffmann, Alex C.

2011-09-01

This paper compares CFD simulations of the `end of the vortex' (EoV) behaviour in centrifugal separators with experiment. The EoV was studied in `swirl tubes', cylindrical cyclone separators with swirl vanes. We refer to the EoV as the phenomenon whereby the core of the vortex does not reach the bottom of the separator, but deviates from the swirl tube axis and attaches to the wall, where it rotates at some level above the bottom. The crucial parameters governing the EoV are geometrical, specifically the ratio of the separator length to its diameter (L/D), and operational, specifically the fluid flowrate. Swirl tubes with varying body lengths have been studied experimentally and numerically. CFD simulations were carried out using the commercial package Star-CD. The 3-D Navier-Stokes equations were solved using the finite volume method based on the SIMPLE pressure-correction algorithm and the LES turbulence model. The vortex behaviour was very similar between the experiments and the numerical simulations, this agreement being both qualitative and quantitative. However, there were some cases where the CFD predictions showed only qualitative agreement with experiments, with some of the parameter-values delimiting given types of flows being somewhat different between experiment and simulations.

Army Active Duty Members’ Linkage to Veterans Health Administration Services After Deployments to Iraq or Afghanistan and Following Separation

PubMed Central

Vanneman, Megan E.; Harris, Alex H. S.; Chen, Cheng; Mohr, Beth A.; Adams, Rachel Sayko; Williams, Thomas V.; Larson, Mary Jo

2015-01-01

This study described the rate and predictors of Operation Enduring Freedom/Operation Iraqi Freedom active duty Army members’ enrollment in and use of Veterans Health Administration (VHA) services (linkage), as well as variation in linkage rates by VHA facility. We used a multivariate mixed effect regression model to predict linkage to VHA, and also calculated linkage rates in the catchment areas of each facility (n = 158). The sample included 151,122 active duty members who deployed to Iraq or Afghanistan and then separated from the Army between fiscal years 2008 and 2012. Approximately 48% of the active duty members separating utilized VHA as an enrollee within one year. There was significant variation in linkage rates by VHA facilities (31–72%). The most notable variables associated with greater linkage included probable serious injury during index deployment (odds ratio = 1.81), separation because of disability (odds ratio = 2.86), and various measures of receipt of VHA care before and after separation. Information about the individual characteristics that predict greater or lesser linkage to VHA services can be used to improve delivery of health care services at VHA as well as outreach efforts to active duty Army members. PMID:26444467

De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

PubMed

Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N

2017-11-14

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.

Coupling chemical transport model source attributions with positive matrix factorization: application to two IMPROVE sites impacted by wildfires.

PubMed

Sturtz, Timothy M; Schichtel, Bret A; Larson, Timothy V

2014-10-07

Source contributions to total fine particle carbon predicted by a chemical transport model (CTM) were incorporated into the positive matrix factorization (PMF) receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was varied using a weighting parameter applied to an object function as implemented in the Multilinear Engine (ME-2). The methodology provides the ability to separate features that would not be identified using PMF alone, without sacrificing fit to observations. The hybrid model was applied to IMPROVE data taken from 2006 through 2008 at Monture and Sula Peak, Montana. It was able to separately identify major contributions of total carbon (TC) from wildfires and minor contributions from biogenic sources. The predictions of TC had a lower cross-validated RMSE than those from either PMF or CTM alone. Two unconstrained, minor features were identified at each site, a soil derived feature with elevated summer impacts and a feature enriched in sulfate and nitrate with significant, but sporadic contributions across the sampling period. The respective mean TC contributions from wildfires, biogenic emissions, and other sources were 1.18, 0.12, and 0.12 ugC/m(3) at Monture and 1.60, 0.44, and 0.06 ugC/m(3) at Sula Peak.

Purification of complex samples: Implementation of a modular and reconfigurable droplet-based microfluidic platform with cascaded deterministic lateral displacement separation modules

PubMed Central

Pudda, Catherine; Boizot, François; Verplanck, Nicolas; Revol-Cavalier, Frédéric; Berthier, Jean; Thuaire, Aurélie

2018-01-01

Particle separation in microfluidic devices is a common problematic for sample preparation in biology. Deterministic lateral displacement (DLD) is efficiently implemented as a size-based fractionation technique to separate two populations of particles around a specific size. However, real biological samples contain components of many different sizes and a single DLD separation step is not sufficient to purify these complex samples. When connecting several DLD modules in series, pressure balancing at the DLD outlets of each step becomes critical to ensure an optimal separation efficiency. A generic microfluidic platform is presented in this paper to optimize pressure balancing, when DLD separation is connected either to another DLD module or to a different microfluidic function. This is made possible by generating droplets at T-junctions connected to the DLD outlets. Droplets act as pressure controllers, which perform at the same time the encapsulation of DLD sorted particles and the balance of output pressures. The optimized pressures to apply on DLD modules and on T-junctions are determined by a general model that ensures the equilibrium of the entire platform. The proposed separation platform is completely modular and reconfigurable since the same predictive model applies to any cascaded DLD modules of the droplet-based cartridge. PMID:29768490

Modeling Nonstationarity in Space and Time

PubMed Central

2017-01-01

Summary We propose to model a spatio-temporal random field that has nonstationary covariance structure in both space and time domains by applying the concept of the dimension expansion method in Bornn et al. (2012). Simulations are conducted for both separable and nonseparable space-time covariance models, and the model is also illustrated with a streamflow dataset. Both simulation and data analyses show that modeling nonstationarity in both space and time can improve the predictive performance over stationary covariance models or models that are nonstationary in space but stationary in time. PMID:28134977

Modeling nonstationarity in space and time.

PubMed

Shand, Lyndsay; Li, Bo

2017-09-01

We propose to model a spatio-temporal random field that has nonstationary covariance structure in both space and time domains by applying the concept of the dimension expansion method in Bornn et al. (2012). Simulations are conducted for both separable and nonseparable space-time covariance models, and the model is also illustrated with a streamflow dataset. Both simulation and data analyses show that modeling nonstationarity in both space and time can improve the predictive performance over stationary covariance models or models that are nonstationary in space but stationary in time. © 2017, The International Biometric Society.

Numerical modeling of separated flows at moderate Reynolds numbers appropriate for turbine blades and unmanned aero vehicles

NASA Astrophysics Data System (ADS)

Castiglioni, Giacomo

Flows over airfoils and blades in rotating machinery, for unmanned and micro-aerial vehicles, wind turbines, and propellers consist of a laminar boundary layer near the leading edge that is often followed by a laminar separation bubble and transition to turbulence further downstream. Typical Reynolds averaged Navier-Stokes turbulence models are inadequate for such flows. Direct numerical simulation is the most reliable, but is also the most computationally expensive alternative. This work assesses the capability of immersed boundary methods and large eddy simulations to reduce the computational requirements for such flows and still provide high quality results. Two-dimensional and three-dimensional simulations of a laminar separation bubble on a NACA-0012 airfoil at Rec = 5x104 and at 5° of incidence have been performed with an immersed boundary code and a commercial code using body fitted grids. Several sub-grid scale models have been implemented in both codes and their performance evaluated. For the two-dimensional simulations with the immersed boundary method the results show good agreement with the direct numerical simulation benchmark data for the pressure coefficient Cp and the friction coefficient Cf, but only when using dissipative numerical schemes. There is evidence that this behavior can be attributed to the ability of dissipative schemes to damp numerical noise coming from the immersed boundary. For the three-dimensional simulations the results show a good prediction of the separation point, but an inaccurate prediction of the reattachment point unless full direct numerical simulation resolution is used. The commercial code shows good agreement with the direct numerical simulation benchmark data in both two and three-dimensional simulations, but the presence of significant, unquantified numerical dissipation prevents a conclusive assessment of the actual prediction capabilities of very coarse large eddy simulations with low order schemes in general cases. Additionally, a two-dimensional sweep of angles of attack from 0° to 5° is performed showing a qualitative prediction of the jump in lift and drag coefficients due to the appearance of the laminar separation bubble. The numerical dissipation inhibits the predictive capabilities of large eddy simulations whenever it is of the same order of magnitude or larger than the sub-grid scale dissipation. The need to estimate the numerical dissipation is most pressing for low-order methods employed by commercial computational fluid dynamics codes. Following the recent work of Schranner et al., the equations and procedure for estimating the numerical dissipation rate and the numerical viscosity in a commercial code are presented. The method allows for the computation of the numerical dissipation rate and numerical viscosity in the physical space for arbitrary sub-domains in a self-consistent way, using only information provided by the code in question. The method is first tested for a three-dimensional Taylor-Green vortex flow in a simple cubic domain and compared with benchmark results obtained using an accurate, incompressible spectral solver. Afterwards the same procedure is applied for the first time to a realistic flow configuration, specifically to the above discussed laminar separation bubble flow over a NACA 0012 airfoil. The method appears to be quite robust and its application reveals that for the code and the flow in question the numerical dissipation can be significantly larger than the viscous dissipation or the dissipation of the classical Smagorinsky sub-grid scale model, confirming the previously qualitative finding.

Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

PubMed

James, Katherine A; Meliker, Jaymie R; Buttenfield, Barbara E; Byers, Tim; Zerbe, Gary O; Hokanson, John E; Marshall, Julie A

2014-08-01

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

Exploring unobserved heterogeneity in bicyclists' red-light running behaviors at different crossing facilities.

PubMed

Guo, Yanyong; Li, Zhibin; Wu, Yao; Xu, Chengcheng

2018-06-01

Bicyclists running the red light at crossing facilities increase the potential of colliding with motor vehicles. Exploring the contributing factors could improve the prediction of running red-light probability and develop countermeasures to reduce such behaviors. However, individuals could have unobserved heterogeneities in running a red light, which make the accurate prediction more challenging. Traditional models assume that factor parameters are fixed and cannot capture the varying impacts on red-light running behaviors. In this study, we employed the full Bayesian random parameters logistic regression approach to account for the unobserved heterogeneous effects. Two types of crossing facilities were considered which were the signalized intersection crosswalks and the road segment crosswalks. Electric and conventional bikes were distinguished in the modeling. Data were collected from 16 crosswalks in urban area of Nanjing, China. Factors such as individual characteristics, road geometric design, environmental features, and traffic variables were examined. Model comparison indicates that the full Bayesian random parameters logistic regression approach is statistically superior to the standard logistic regression model. More red-light runners are predicted at signalized intersection crosswalks than at road segment crosswalks. Factors affecting red-light running behaviors are gender, age, bike type, road width, presence of raised median, separation width, signal type, green ratio, bike and vehicle volume, and average vehicle speed. Factors associated with the unobserved heterogeneity are gender, bike type, signal type, separation width, and bike volume. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development and Validation of a qRT-PCR Classifier for Lung Cancer Prognosis

PubMed Central

Chen, Guoan; Kim, Sinae; Taylor, Jeremy MG; Wang, Zhuwen; Lee, Oliver; Ramnath, Nithya; Reddy, Rishindra M; Lin, Jules; Chang, Andrew C; Orringer, Mark B; Beer, David G

2011-01-01

Purpose This prospective study aimed to develop a robust and clinically-applicable method to identify high-risk early stage lung cancer patients and then to validate this method for use in future translational studies. Patients and Methods Three published Affymetrix microarray data sets representing 680 primary tumors were used in the survival-related gene selection procedure using clustering, Cox model and random survival forest (RSF) analysis. A final set of 91 genes was selected and tested as a predictor of survival using a qRT-PCR-based assay utilizing an independent cohort of 101 lung adenocarcinomas. Results The RSF model built from 91 genes in the training set predicted patient survival in an independent cohort of 101 lung adenocarcinomas, with a prediction error rate of 26.6%. The mortality risk index (MRI) was significantly related to survival (Cox model p < 0.00001) and separated all patients into low, medium, and high-risk groups (HR = 1.00, 2.82, 4.42). The MRI was also related to survival in stage 1 patients (Cox model p = 0.001), separating patients into low, medium, and high-risk groups (HR = 1.00, 3.29, 3.77). Conclusions The development and validation of this robust qRT-PCR platform allows prediction of patient survival with early stage lung cancer. Utilization will now allow investigators to evaluate it prospectively by incorporation into new clinical trials with the goal of personalized treatment of lung cancer patients and improving patient survival. PMID:21792073

Investigation to advance prediction techniques of the low-speed aerodynamics of V/STOL aircraft

NASA Technical Reports Server (NTRS)

Maskew, B.; Strash, D.; Nathman, J.; Dvorak, F. A.

1985-01-01

A computer program, VSAERO, has been applied to a number of V/STOL configurations with a view to advancing prediction techniques for the low-speed aerodynamic characteristics. The program couples a low-order panel method with surface streamline calculation and integral boundary layer procedures. The panel method--which uses piecewise constant source and doublet panels-includes an iterative procedure for wake shape and models boundary layer displacement effect using the source transpiration technique. Certain improvements to a basic vortex tube jet model were installed in the code prior to evaluation. Very promising results were obtained for surface pressures near a jet issuing at 90 deg from a flat plate. A solid core model was used in the initial part of the jet with a simple entrainment model. Preliminary representation of the downstream separation zone significantly improve the correlation. The program accurately predicted the pressure distribution inside the inlet on the Grumman 698-411 design at a range of flight conditions. Furthermore, coupled viscous/potential flow calculations gave very close correlation with experimentally determined operational boundaries dictated by the onset of separation inside the inlet. Experimentally observed degradation of these operational boundaries between nacelle-alone tests and tests on the full configuration were also indicated by the calculation. Application of the program to the General Dynamics STOL fighter design were equally encouraging. Very close agreement was observed between experiment and calculation for the effects of power on pressure distribution, lift and lift curve slope.

Status of flow separation prediction in liquid propellant rocket nozzles

NASA Technical Reports Server (NTRS)

Schmucker, R. H.

1974-01-01

Flow separation which plays an important role in the design of a rocket engine nozzle is discussed. For a given ambient pressure, the condition of no flow separation limits the area ratio and, therefore, the vacuum performance. Avoidance of performance loss due to area ratio limitation requires a correct prediction of the flow separation conditions. To provide a better understanding of the flow separation process, the principal behavior of flow separation in a supersonic overexpanded rocket nozzle is described. The hot firing separation tests from various sources are summarized, and the applicability and accuracy of the measurements are described. A comparison of the different data points allows an evaluation of the parameters that affect flow separation. The pertinent flow separation predicting methods, which are divided into theoretical and empirical correlations, are summarized and the numerical results are compared with the experimental points.

Modeling of near wall turbulence and modeling of bypass transition

NASA Technical Reports Server (NTRS)

Yang, Z.

1992-01-01

The objectives for this project are as follows: (1) Modeling of the near wall turbulence: We aim to develop a second order closure for the near wall turbulence. As a first step of this project, we try to develop a kappa-epsilon model for near wall turbulence. We require the resulting model to be able to handle both near wall turbulence and turbulent flows away from the wall, computationally robust, and applicable for complex flow situations, flow with separation, for example, and (2) Modeling of the bypass transition: We aim to develop a bypass transition model which contains the effect of intermittency. Thus, the model can be used for both the transitional boundary layers and the turbulent boundary layers. We require the resulting model to give a good prediction of momentum and heat transfer within the transitional boundary and a good prediction of the effect of freestream turbulence on transitional boundary layers.

Goal striving within agentic and communal roles: separate but functionally similar pathways to enhanced well-being.

PubMed

Sheldon, Kennon M; Cooper, M Lynne

2008-06-01

Do agency and communion strivings provide functionally similar but predictively independent pathways to enhanced well-being? We tested this idea via a year-long study of 493 diverse community adults. Our process model, based on self-determination and motive disposition theories, fit the data well. First, the need for achievement predicted initial autonomous motivation for agentic (work and school) role-goals and the need for intimacy predicted felt autonomy for communal (relationship and parenting) goals. For both agentic and communal goals, autonomous motivation predicted corresponding initial expectancies that predicted later goal attainment. Finally, each type of attainment predicted improved adjustment or role-satisfaction over the year. Besides being similar across agency and communion, the model was also similar across race and gender, except that the beneficial effects of communal goal attainment were stronger for high need for intimacy women and Blacks. Implications for agency/communion theories, motivation theories, and theories of well-being are discussed.

Automatic Prediction of Conversion from Mild Cognitive Impairment to Probable Alzheimer’s Disease using Structural Magnetic Resonance Imaging

PubMed Central

Nho, Kwangsik; Shen, Li; Kim, Sungeun; Risacher, Shannon L.; West, John D.; Foroud, Tatiana; Jack, Clifford R.; Weiner, Michael W.; Saykin, Andrew J.

2010-01-01

Mild Cognitive Impairment (MCI) is thought to be a precursor to the development of early Alzheimer’s disease (AD). For early diagnosis of AD, the development of a model that is able to predict the conversion of amnestic MCI to AD is challenging. Using automatic whole-brain MRI analysis techniques and pattern classification methods, we developed a model to differentiate AD from healthy controls (HC), and then applied it to the prediction of MCI conversion to AD. Classification was performed using support vector machines (SVMs) together with a SVM-based feature selection method, which selected a set of most discriminating predictors for optimizing prediction accuracy. We obtained 90.5% cross-validation accuracy for classifying AD and HC, and 72.3% accuracy for predicting MCI conversion to AD. These analyses suggest that a classifier trained to separate HC vs. AD has substantial potential for predicting MCI conversion to AD. PMID:21347037

Deconstructing three-dimensional (3D) structure of absorptive glass mat (AGM) separator to tailor pore dimensions and amplify electrolyte uptake

NASA Astrophysics Data System (ADS)

Rawal, Amit; Rao, P. V. Kameswara; Kumar, Vijay

2018-04-01

Absorptive glass mat (AGM) separator is a vital technical component in valve regulated lead acid (VRLA) batteries that can be tailored for a desired application. To selectively design and tailor the AGM separator, the intricate three-dimensional (3D) structure needs to be unraveled. Herein, a toolkit of 3D analytical models of pore size distribution and electrolyte uptake expressed via wicking characteristics of AGM separators under unconfined and confined states is presented. 3D data of fiber orientation distributions obtained previously through X-ray micro-computed tomography (microCT) analysis are used as key set of input parameters. The predictive ability of pore size distribution model is assessed through the commonly used experimental set-up that usually apply high level of compressive stresses. Further, the existing analytical model of wicking characteristics of AGM separators has been extended to account for 3D characteristics, and subsequently, compared with the experimental results. A good agreement between the theory and experiments pave the way to simulate the realistic charge-discharge modes of the battery by applying cyclic loading condition. A threshold criterion describing the invariant behavior of pore size and wicking characteristics in terms of maximum permissible limit of key structural parameters during charge-discharge mode of the battery has also been proposed.

Development of a High-Order Space-Time Matrix-Free Adjoint Solver

NASA Technical Reports Server (NTRS)

Ceze, Marco A.; Diosady, Laslo T.; Murman, Scott M.

2016-01-01

The growth in computational power and algorithm development in the past few decades has granted the science and engineering community the ability to simulate flows over complex geometries, thus making Computational Fluid Dynamics (CFD) tools indispensable in analysis and design. Currently, one of the pacing items limiting the utility of CFD for general problems is the prediction of unsteady turbulent ows.1{3 Reynolds-averaged Navier-Stokes (RANS) methods, which predict a time-invariant mean flowfield, struggle to provide consistent predictions when encountering even mild separation, such as the side-of-body separation at a wing-body junction. NASA's Transformative Tools and Technologies project is developing both numerical methods and physical modeling approaches to improve the prediction of separated flows. A major focus of this e ort is efficient methods for resolving the unsteady fluctuations occurring in these flows to provide valuable engineering data of the time-accurate flow field for buffet analysis, vortex shedding, etc. This approach encompasses unsteady RANS (URANS), large-eddy simulations (LES), and hybrid LES-RANS approaches such as Detached Eddy Simulations (DES). These unsteady approaches are inherently more expensive than traditional engineering RANS approaches, hence every e ort to mitigate this cost must be leveraged. Arguably, the most cost-effective approach to improve the efficiency of unsteady methods is the optimal placement of the spatial and temporal degrees of freedom (DOF) using solution-adaptive methods.

Finite-element model to predict roll-separation force and defects during rolling of U-10Mo alloys

NASA Astrophysics Data System (ADS)

Soulami, Ayoub; Burkes, Douglas E.; Joshi, Vineet V.; Lavender, Curt A.; Paxton, Dean

2017-10-01

A major goal of the Convert Program of the U.S. Department of Energy's National Nuclear Security Administration (DOE/NNSA) is to enable high-performance research reactors to operate with low-enriched uranium rather than the high-enriched uranium currently used. To this end, uranium alloyed with 10 wt% molybdenum (U-10Mo) represents an ideal candidate because of its stable gamma phase, low neutron caption cross section, acceptable swelling response, and predictable irradiation behavior. However, because of the complexities of the fuel design and the need for rolled monolithic U-10Mo foils, new developments in processing and fabrication are necessary. This study used a finite-element code, LS-DYNA, as a predictive tool to optimize the rolling process. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel were conducted following two different schedules. Model predictions of the roll-separation force and roll pack thicknesses at different stages of the rolling process were compared with experimental measurements. The study reported here discussed various attributes of the rolled coupons revealed by the model (e.g., waviness and thickness non-uniformity like dog-boning). To investigate the influence of the cladding material on these rolling defects, other cases were simulated: hot rolling with alternative can materials, namely, 304 stainless steel and Zircaloy-2, and bare-rolling. Simulation results demonstrated that reducing the mismatch in strength between the coupon and can material improves the quality of the rolled sheet. Bare-rolling simulation results showed a defect-free rolled coupon. The finite-element model developed and presented in this study can be used to conduct parametric studies of several process parameters (e.g., rolling speed, roll diameter, can material, and reduction).

RACER a Coarse-Grained RNA Model for Capturing Folding Free Energy in Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Cheng, Sara; Bell, David; Ren, Pengyu

RACER is a coarse-grained RNA model that can be used in molecular dynamics simulations to predict native structures and sequence-specific variation of free energy of various RNA structures. RACER is capable of accurate prediction of native structures of duplexes and hairpins (average RMSD of 4.15 angstroms), and RACER can capture sequence-specific variation of free energy in excellent agreement with experimentally measured stabilities (r-squared =0.98). The RACER model implements a new effective non-bonded potential and re-parameterization of hydrogen bond and Debye-Huckel potentials. Insights from the RACER model include the importance of treating pairing and stacking interactions separately in order to distinguish folded an unfolded states and identification of hydrogen-bonding, base stacking, and electrostatic interactions as essential driving forces for RNA folding. Future applications of the RACER model include predicting free energy landscapes of more complex RNA structures and use of RACER for multiscale simulations.

Modelling ADHD: A review of ADHD theories through their predictions for computational models of decision-making and reinforcement learning.

PubMed

Ziegler, Sigurd; Pedersen, Mads L; Mowinckel, Athanasia M; Biele, Guido

2016-12-01

Attention deficit hyperactivity disorder (ADHD) is characterized by altered decision-making (DM) and reinforcement learning (RL), for which competing theories propose alternative explanations. Computational modelling contributes to understanding DM and RL by integrating behavioural and neurobiological findings, and could elucidate pathogenic mechanisms behind ADHD. This review of neurobiological theories of ADHD describes predictions for the effect of ADHD on DM and RL as described by the drift-diffusion model of DM (DDM) and a basic RL model. Empirical studies employing these models are also reviewed. While theories often agree on how ADHD should be reflected in model parameters, each theory implies a unique combination of predictions. Empirical studies agree with the theories' assumptions of a lowered DDM drift rate in ADHD, while findings are less conclusive for boundary separation. The few studies employing RL models support a lower choice sensitivity in ADHD, but not an altered learning rate. The discussion outlines research areas for further theoretical refinement in the ADHD field. Copyright © 2016 Elsevier Ltd. All rights reserved.

The accuracy of matrix population model projections for coniferous trees in the Sierra Nevada, California

USGS Publications Warehouse

van Mantgem, P.J.; Stephenson, N.L.

2005-01-01

1 We assess the use of simple, size-based matrix population models for projecting population trends for six coniferous tree species in the Sierra Nevada, California. We used demographic data from 16 673 trees in 15 permanent plots to create 17 separate time-invariant, density-independent population projection models, and determined differences between trends projected from initial surveys with a 5-year interval and observed data during two subsequent 5-year time steps. 2 We detected departures from the assumptions of the matrix modelling approach in terms of strong growth autocorrelations. We also found evidence of observation errors for measurements of tree growth and, to a more limited degree, recruitment. Loglinear analysis provided evidence of significant temporal variation in demographic rates for only two of the 17 populations. 3 Total population sizes were strongly predicted by model projections, although population dynamics were dominated by carryover from the previous 5-year time step (i.e. there were few cases of recruitment or death). Fractional changes to overall population sizes were less well predicted. Compared with a null model and a simple demographic model lacking size structure, matrix model projections were better able to predict total population sizes, although the differences were not statistically significant. Matrix model projections were also able to predict short-term rates of survival, growth and recruitment. Mortality frequencies were not well predicted. 4 Our results suggest that simple size-structured models can accurately project future short-term changes for some tree populations. However, not all populations were well predicted and these simple models would probably become more inaccurate over longer projection intervals. The predictive ability of these models would also be limited by disturbance or other events that destabilize demographic rates. ?? 2005 British Ecological Society.

Mathematical modeling of sample stacking methods in microfluidic systems

NASA Astrophysics Data System (ADS)

Horek, Jon

Gradient focusing methods are a general class of experimental techniques used to simultaneously separate and increase the cross-sectionally averaged concentration of charged particle mixtures. In comparison, Field Amplified Sample Stacking (FASS) techniques first concentrate the collection of molecules before separating them. Together, we denote gradient focusing and FASS methods "sample stacking" and study the dynamics of a specific method, Temperature Gradient Focusing (TGF), in which an axial temperature gradient is applied along a channel filled with weak buffer. Gradients in electroosmotic fluid flow and electrophoretic species velocity create the simultaneous separating and concentrating mechanism mentioned above. In this thesis, we begin with the observation that very little has been done to model the dynamics of gradient focusing, and proceed to solve the fundamental equations of fluid mechanics and scalar transport, assuming the existence of slow axial variations and the Taylor-Aris dispersion coefficient. In doing so, asymptotic methods reduce the equations from 3D to 1D, and we arrive at a simple 1D model which can be used to predict the transient evolution of the cross-sectionally averaged analyte concentration. In the second half of this thesis, we run several numerical focusing experiments with a 3D finite volume code. Comparison of the 1D theory and 3D simulations illustrates not only that the asymptotic theory converges as a certain parameter tends to zero, but also that fairly large axial slip velocity gradients lead to quite small errors in predicted steady variance. Additionally, we observe that the axial asymmetry of the electrophoretic velocity model leads to asymmetric peak shapes, a violation of the symmetric Gaussians predicted by the 1D theory. We conclude with some observations on the effect of Peclet number and gradient strength on the performance of focusing experiments, and describe a method for experimental optimization. Such knowledge is useful for design of lab-on-a-chip devices.

Effects of children's working memory capacity and processing speed on their sentence imitation performance.

PubMed

Poll, Gerard H; Miller, Carol A; Mainela-Arnold, Elina; Adams, Katharine Donnelly; Misra, Maya; Park, Ji Sook

2013-01-01

More limited working memory capacity and slower processing for language and cognitive tasks are characteristics of many children with language difficulties. Individual differences in processing speed have not consistently been found to predict language ability or severity of language impairment. There are conflicting views on whether working memory and processing speed are integrated or separable abilities. To evaluate four models for the relations of individual differences in children's processing speed and working memory capacity in sentence imitation. The models considered whether working memory and processing speed are integrated or separable, as well as the effect of the number of operations required per sentence. The role of working memory as a mediator of the effect of processing speed on sentence imitation was also evaluated. Forty-six children with varied language and reading abilities imitated sentences. Working memory was measured with the Competing Language Processing Task (CLPT), and processing speed was measured with a composite of truth-value judgment and rapid automatized naming tasks. Mixed-effects ordinal regression models evaluated the CLPT and processing speed as predictors of sentence imitation item scores. A single mediator model evaluated working memory as a mediator of the effect of processing speed on sentence imitation total scores. Working memory was a reliable predictor of sentence imitation accuracy, but processing speed predicted sentence imitation only as a component of a processing speed by number of operations interaction. Processing speed predicted working memory capacity, and there was evidence that working memory acted as a mediator of the effect of processing speed on sentence imitation accuracy. The findings support a refined view of working memory and processing speed as separable factors in children's sentence imitation performance. Processing speed does not independently explain sentence imitation accuracy for all sentence types, but contributes when the task requires more mental operations. Processing speed also has an indirect effect on sentence imitation by contributing to working memory capacity. © 2013 Royal College of Speech and Language Therapists.

Mass-Gathering Medical Care in Electronic Dance Music Festivals.

PubMed

FitzGibbon, Kathleen M; Nable, Jose V; Ayd, Benjamin; Lawner, Benjamin J; Comer, Angela C; Lichenstein, Richard; Levy, Matthew J; Seaman, Kevin G; Bussey, Ian

2017-10-01

Introduction Electronic dance music (EDM) festivals represent a unique subset of mass-gathering events with limited guidance through literature or legislation to guide mass-gathering medical care at these events. Hypothesis/Problem Electronic dance music festivals pose unique challenges with increased patient encounters and heightened patient acuity under-estimated by current validated casualty predication models. This was a retrospective review of three separate EDM festivals with analysis of patient encounters and patient transport rates. Data obtained were inserted into the predictive Arbon and Hartman models to determine estimated patient presentation rate and patient transport rates. The Arbon model under-predicted the number of patient encounters and the number of patient transports for all three festivals, while the Hartman model under-predicted the number of patient encounters at one festival and over-predicted the number of encounters at the other two festivals. The Hartman model over-predicted patient transport rates for two of the three festivals. Electronic dance music festivals often involve distinct challenges and current predictive models are inaccurate for planning these events. The formation of a cohesive incident action plan will assist in addressing these challenges and lead to the collection of more uniform data metrics. FitzGibbon KM , Nable JV , Ayd B , Lawner BJ , Comer AC , Lichenstein R , Levy MJ , Seaman KG , Bussey I . Mass-gathering medical care in electronic dance music festivals. Prehosp Disaster Med. 2017;32(5):563-567.

Statistical Analysis of CFD Solutions from the Third AIAA Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.; Hemsch, Michael J.

2007-01-01

The first AIAA Drag Prediction Workshop, held in June 2001, evaluated the results from an extensive N-version test of a collection of Reynolds-Averaged Navier-Stokes CFD codes. The code-to-code scatter was more than an order of magnitude larger than desired for design and experimental validation of cruise conditions for a subsonic transport configuration. The second AIAA Drag Prediction Workshop, held in June 2003, emphasized the determination of installed pylon-nacelle drag increments and grid refinement studies. The code-to-code scatter was significantly reduced compared to the first DPW, but still larger than desired. However, grid refinement studies showed no significant improvement in code-to-code scatter with increasing grid refinement. The third Drag Prediction Workshop focused on the determination of installed side-of-body fairing drag increments and grid refinement studies for clean attached flow on wing alone configurations and for separated flow on the DLR-F6 subsonic transport model. This work evaluated the effect of grid refinement on the code-to-code scatter for the clean attached flow test cases and the separated flow test cases.

Space weather at planet Venus during the forthcoming BepiColombo flybys

NASA Astrophysics Data System (ADS)

McKenna-Lawlor, S.; Jackson, B.; Odstrcil, D.

2018-03-01

The BepiColombo (BC) Mission which will be launched in 2018, will include during its Cruise Phase two flybys of Venus and five Mercury flybys. It will then enter a one Earth year orbit about Mercury (with a possible one-year extension) during which two spacecraft, one provided by ESA (MPO) and one provided by JAXA (MMO), will perform both autonomous and coordinated observations of the Hermean environment at various separations. The measurements will take place during the minimum of solar cycle 24 and the rise of solar cycle 25. At the start of the minimum of solar cycle 23, four major flares, each associated with the production of MeV particle radiation and CME activity occurred. Predictions of the HAFv.2 model of the arrival of particle radiation and a travelling shock at Venus on 6 December 2006 were verified by in-situ measurements made aboard Venus Express (VEX) by the ASPERA 4 instrument. Interplanetary scintillation observations, as well as the ENLIL 3-D MHD model when employed separately or in combination, enable the making of predictions of the solar wind density and speed at various locations in the inner heliosphere. Both methods, which outdate HAFv.2, are utilized in the present paper to predict (retrospectively) the arrival of the flare related, interplanetary propagating shock recorded at Venus on 6 December 2006 aboard VEX with a view to putting in place the facility to make very reliable space weather predictions for BC during both its Cruise Phase and when in the Hermean environment itself. The successful matching of the December 2006 predictions with in-situ signatures recorded aboard Venus Express provide confidence that the predictive methodology to be adopted will be appropriate to provide space weather predictions for BepiColombo during its Venus flybys and throughout the mission.

Finite-element model to predict roll-separation force and defects during rolling of U-10Mo alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Soulami, Ayoub; Burkes, Douglas E.; Joshi, Vineet V.

This study used a finite element code, LSDYNA, as a predictive tool to optimize the rolling process. Simulations of the hot rolling of U-10Mo coupons encapsulated in low-carbon steel were conducted following two different schedules. Model predictions of the roll-separation force and roll pack thicknesses at different stages of the rolling process were compared with experimental measurements. The study reported here discussed various attributes of the rolled coupons revealed by the model (e.g., waviness and thickness non-uniformity like dog boning). To investigate the influence of the cladding material on these rolling defects, other cases were simulated:  hot rolling with alternative can materials, namely, 304 stainless steel and Zircaloy-2, and bare-rolling.

The Shock and Vibration Digest. Volume 18, Number 8

DTIC Science & Technology

1986-08-01

the swash plate . This is an active that vibration can be reduced by separation of control system...element program model . ture-borne sound intensity has been tried earlier The agreement is shown to be very good. A on thin- plate constructions in ...predicting the response of two displacement controlled laboratory tests that were used for the determination of the model parameters. 86-1532

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

NASA Technical Reports Server (NTRS)

Diallo, Ousmane H.

2012-01-01

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors.

PubMed

Thipphavong, David P

2016-09-01

The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%.

Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors

PubMed Central

Thipphavong, David P.

2017-01-01

The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%. PMID:28684883

Top-of-Climb Matching Method for Reducing Aircraft Trajectory Prediction Errors

NASA Technical Reports Server (NTRS)

Thipphavong, David P.

2016-01-01

The inaccuracies of the aircraft performance models utilized by trajectory predictors with regard to takeoff weight, thrust, climb profile, and other parameters result in altitude errors during the climb phase that often exceed the vertical separation standard of 1000 feet. This study investigates the potential reduction in altitude trajectory prediction errors that could be achieved for climbing flights if just one additional parameter is made available: top-of-climb (TOC) time. The TOC-matching method developed and evaluated in this paper is straightforward: a set of candidate trajectory predictions is generated using different aircraft weight parameters, and the one that most closely matches TOC in terms of time is selected. This algorithm was tested using more than 1000 climbing flights in Fort Worth Center. Compared to the baseline trajectory predictions of a real-time research prototype (Center/TRACON Automation System), the TOC-matching method reduced the altitude root mean square error (RMSE) for a 5-minute prediction time by 38%. It also decreased the percentage of flights with absolute altitude error greater than the vertical separation standard of 1000 ft for the same look-ahead time from 55% to 30%.

Computational Investigations on the Aerodynamics of a Generic Car Model in Proximity to a Side Wall

NASA Astrophysics Data System (ADS)

Mallapragada, Srivatsa

A moving road vehicle is subjected to many fluid interferences caused by a number of external agents apart from the vehicle itself. Vehicles moving in proximity to a side wall is an interesting aspect that has been little investigated in the literature. This is of great interest in motorsports, more specifically in NASCAR racing. The aim of this thesis is to develop a Computational Fluid Dynamics (CFD) model that can simulate the motion of a race car moving close to a side wall with an objective of understanding the influence of this side barrier on the overall aerodynamic characteristics of the vehicle, like the force and moment coefficients. Additionally, flow visualization tools are used to gain insights into the flow field and to explain the causes of the observed aerodynamic characteristics of the vehicle. This is accomplished by using a generic car model, a 25-degree slant angle Ahmed Body, in proximity to a side wall in a virtual wind tunnel where the vehicle body is allowed to move at constant velocity. This methodology is different from the traditional CFD approach where the air is blown over a stationary vehicle. The simulation process used in this thesis requires the use of a recently developed meshing methodology called the Overset mesh. All simulations were run using a commercial finite volume CFD code called StarCCM+ where the Unsteady Reynolds Averaged Navier-Stokes URANS fluid flow solver was used to model turbulence. However, the existing literature suggests that no URANS model can correctly predict the flow field around a 25-degree slant Ahmed body model; all models under-predict turbulence in the initial separated shear layer and over-predict the separation region. Subsequently, the first phase of this thesis involved the determination of a modeling methodology that can accurately predict the flow-field over a 25-degree Ahmed body. Two two-equation eddy-viscosity turbulence models, the AKN and SST preferred by many researchers for CFD simulations of massively separated flows, were tested. It turned out that only the latter with modified model coefficients was capable of reproducing the experimental results with a reasonable accuracy. Compared to the eddy viscosity CFD simulations of an isolated 25-degree slant angle Ahmed body seen in existing literature, the results presented in this thesis show significantly better correlations with experiments. The wall proximity studies show a strong influence of the presence of the wall on the overall aerodynamic characteristics of the vehicle body. When compared with the experimental studies, although both show similar trends, however, there exists a significant difference between the experimental and CFD predicted results which tend to worsen as one approaches the wall. These differences can be attributed to fact that the CFD emulation of the flow around the side-wall is more realistic compared to the experimental implementation.

Interaction between polymer constituents and the structure of biopolymers

NASA Technical Reports Server (NTRS)

Rein, R.

1974-01-01

The paper reviews the current status of methods for calculating intermolecular interactions between biopolymer units. The nature of forces contributing to the various domains of intermolecular separations is investigated, and various approximations applicable in the respective regions are examined. The predictive value of current theory is tested by establishing a connection with macroscopic properties and comparing the theoretical predicted values with those derived from experimental data. This has led to the introduction of a statistical model describing DNA.

Hydrodynamic models for slurry bubble column reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gidaspow, D.

1995-12-31

The objective of this investigation is to convert a {open_quotes}learning gas-solid-liquid{close_quotes} fluidization model into a predictive design model. This model is capable of predicting local gas, liquid and solids hold-ups and the basic flow regimes: the uniform bubbling, the industrially practical churn-turbulent (bubble coalescence) and the slugging regimes. Current reactor models incorrectly assume that the gas and the particle hold-ups (volume fractions) are uniform in the reactor. They must be given in terms of empirical correlations determined under conditions that radically differ from reactor operation. In the proposed hydrodynamic approach these hold-ups are computed from separate phase momentum balances. Furthermore,more » the kinetic theory approach computes the high slurry viscosities from collisions of the catalyst particles. Thus particle rheology is not an input into the model.« less

What Parents Don’t Know: Disclosure and Secrecy in a Sample of Urban Adolescents

PubMed Central

Jäggi, Lena; Drazdowski, Tess K.; Kliewer, Wendy

2016-01-01

Research with two-parent European households has suggested that secrecy, and not disclosure of information per se, predicts adolescent adjustment difficulties. The present study attempted to replicate this finding using data from a 4-wave study of 358 poor, urban adolescents (47% male; M age = 12 yrs) in the United States, most of whom (> 92%) were African American. Adolescents self-reported secrecy, disclosure, depressive symptoms, and delinquency at each wave. Confirmatory factor analyses revealed that a two-factor model with secrecy and disclosure as separate, but correlated, factors was a better fit than a one-factor model. However, predictive models differed from previous research. Secrecy did not predict depressive symptoms, rather depressive symptoms predicted secrecy. For delinquency, there were significant paths from both secrecy to delinquency and delinquency to secrecy, as well as from delinquency to disclosure. These results did not differ by age or sex. Comparisons with previous findings are discussed. PMID:27639590

Prediction of failure in notched carbon-fibre-reinforced-polymer laminates under multi-axial loading.

PubMed

Tan, J L Y; Deshpande, V S; Fleck, N A

2016-07-13

A damage-based finite-element model is used to predict the fracture behaviour of centre-notched quasi-isotropic carbon-fibre-reinforced-polymer laminates under multi-axial loading. Damage within each ply is associated with fibre tension, fibre compression, matrix tension and matrix compression. Inter-ply delamination is modelled by cohesive interfaces using a traction-separation law. Failure envelopes for a notch and a circular hole are predicted for in-plane multi-axial loading and are in good agreement with the observed failure envelopes from a parallel experimental study. The ply-by-ply (and inter-ply) damage evolution and the critical mechanisms of ultimate failure also agree with the observed damage evolution. It is demonstrated that accurate predictions of notched compressive strength are obtained upon employing the band broadening stress for microbuckling, highlighting the importance of this damage mode in compression. This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

[Theoretical modeling and experimental research on direct compaction characteristics of multi-component pharmaceutical powders based on the Kawakita equation].

PubMed

Si, Guo-Ning; Chen, Lan; Li, Bao-Guo

2014-04-01

Base on the Kawakita powder compression equation, a general theoretical model for predicting the compression characteristics of multi-components pharmaceutical powders with different mass ratios was developed. The uniaxial flat-face compression tests of powder lactose, starch and microcrystalline cellulose were carried out, separately. Therefore, the Kawakita equation parameters of the powder materials were obtained. The uniaxial flat-face compression tests of the powder mixtures of lactose, starch, microcrystalline cellulose and sodium stearyl fumarate with five mass ratios were conducted, through which, the correlation between mixture density and loading pressure and the Kawakita equation curves were obtained. Finally, the theoretical prediction values were compared with experimental results. The analysis showed that the errors in predicting mixture densities were less than 5.0% and the errors of Kawakita vertical coordinate were within 4.6%, which indicated that the theoretical model could be used to predict the direct compaction characteristics of multi-component pharmaceutical powders.

Sugar and acid content of Citrus prediction modeling using FT-IR fingerprinting in combination with multivariate statistical analysis.

PubMed

Song, Seung Yeob; Lee, Young Koung; Kim, In-Jung

2016-01-01

A high-throughput screening system for Citrus lines were established with higher sugar and acid contents using Fourier transform infrared (FT-IR) spectroscopy in combination with multivariate analysis. FT-IR spectra confirmed typical spectral differences between the frequency regions of 950-1100 cm(-1), 1300-1500 cm(-1), and 1500-1700 cm(-1). Principal component analysis (PCA) and subsequent partial least square-discriminant analysis (PLS-DA) were able to discriminate five Citrus lines into three separate clusters corresponding to their taxonomic relationships. The quantitative predictive modeling of sugar and acid contents from Citrus fruits was established using partial least square regression algorithms from FT-IR spectra. The regression coefficients (R(2)) between predicted values and estimated sugar and acid content values were 0.99. These results demonstrate that by using FT-IR spectra and applying quantitative prediction modeling to Citrus sugar and acid contents, excellent Citrus lines can be early detected with greater accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

PubMed

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

New reversed phase-high performance liquid chromatographic method for selective separation of yttrium from all rare earth elements employing nitrilotriacetate complexes in anion exchange mode.

PubMed

Dybczyński, Rajmund S; Kulisa, Krzysztof; Pyszynska, Marta; Bojanowska-Czajka, Anna

2015-03-20

Separation of Y from other rare earth elements (REE) is difficult because of similarity of its ionic radius to ionic radii of Tb, Dy and Ho. In the new RP-HPLC system with C18 column, tetra-n-butyl ammonium hydroxide (TBAOH) as an ion interaction reagent (IIR), nitrilotriacetic acid (NTA) as a complexing agent at pH=2.8-3.5, and post column derivatization with Arsenazo III, yttrium is eluted in the region of light REE, between Nd and Sm and is base line separated from Nd and Sm and even from promethium. Simple model employing literature data on complex formation of REE with NTA and based on anion exchange mechanism was developed to foresee the order of elution of individual REE. The model correctly predicted that lanthanides up to Tb will be eluted in the order of increasing Atomic Number (At.No.) but all heavier REE will show smaller retention factors than Tb. Concurrent UV/VIS detection at 658nm and the use of radioactive tracers together with γ-ray spectrometric measurements made possible to establish an unique elution order of elution of REE: La, Ce, Pr, Nd, Pm, Y, Sm, Er, Ho, Tm, Yb, Eu, Lu, Dy+Gd, Tb, Sc. The real place of Y however, in this elution series differs from that predicted by the model (Y between Sm and Eu). The method described in this work enables selective separation of Y from La, Ce, Pr, Nd, Pm, Sm and all heavier REE treated as a group. Copyright © 2015 Elsevier B.V. All rights reserved.

Cortical dynamics of feature binding and reset: control of visual persistence.

PubMed

Francis, G; Grossberg, S; Mingolla, E

1994-04-01

An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset mechanisms prevent massive smearing of visual percepts in response to rapidly moving images. The model simulates relationships among psychophysical data showing inverse relations of persistence to flash luminance and duration, greater persistence of illusory contours than real contours, a U-shaped temporal function for persistence of illusory contours, a reduction of persistence due to adaptation with a stimulus of like orientation, an increase of persistence with spatial separation of a masking stimulus. The model suggests that a combination of habituative, opponent, and endstopping mechanisms prevent smearing and limit persistence. Earlier work with the model has analyzed data about boundary formation, texture segregation, shape-from-shading, and figure-ground separation. Thus, several types of data support each model mechanism and new predictions are made.

Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine.

PubMed

Du, Hongying; Wang, Jie; Yao, Xiaojun; Hu, Zhide

2009-01-01

The heuristic method (HM) and support vector machine (SVM) were used to construct quantitative structure-retention relationship models by a series of compounds to predict the gradient retention times of reversed-phase high-performance liquid chromatography (HPLC) in three different columns. The aims of this investigation were to predict the retention times of multifarious compounds, to find the main properties of the three columns, and to indicate the theory of separation procedures. In our method, we correlated the retention times of many diverse structural analytes in three columns (Symmetry C18, Chromolith, and SG-MIX) with their representative molecular descriptors, calculated from the molecular structures alone. HM was used to select the most important molecular descriptors and build linear regression models. Furthermore, non-linear regression models were built using the SVM method; the performance of the SVM models were better than that of the HM models, and the prediction results were in good agreement with the experimental values. This paper could give some insights into the factors that were likely to govern the gradient retention process of the three investigated HPLC columns, which could theoretically supervise the practical experiment.

Using spatio-temporal modeling to predict long-term exposure to black smoke at fine spatial and temporal scale

NASA Astrophysics Data System (ADS)

Dadvand, Payam; Rushton, Stephen; Diggle, Peter J.; Goffe, Louis; Rankin, Judith; Pless-Mulloli, Tanja

2011-01-01

Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055 km 2) over a 12 year period (1985-1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology. The first stage separates the temporal trend in BS for the region as a whole from within-region spatial variation and the second stage is a linear model which predicts BS levels at all locations in the region using spatially referenced covariate data as predictors and the regional predicted temporal trend as an offset. Traffic and land cover predictors were included in the final model, which predicted 70% of the spatio-temporal variation in BS across the study region over the study period. This modeling approach appears to provide a robust way of estimating exposure to BS at an inter-urban scale.

ABodyBuilder: Automated antibody structure prediction with data–driven accuracy estimation

PubMed Central

Leem, Jinwoo; Dunbar, James; Georges, Guy; Shi, Jiye; Deane, Charlotte M.

2016-01-01

ABSTRACT Computational modeling of antibody structures plays a critical role in therapeutic antibody design. Several antibody modeling pipelines exist, but no freely available methods currently model nanobodies, provide estimates of expected model accuracy, or highlight potential issues with the antibody's experimental development. Here, we describe our automated antibody modeling pipeline, ABodyBuilder, designed to overcome these issues. The algorithm itself follows the standard 4 steps of template selection, orientation prediction, complementarity-determining region (CDR) loop modeling, and side chain prediction. ABodyBuilder then annotates the ‘confidence’ of the model as a probability that a component of the antibody (e.g., CDRL3 loop) will be modeled within a root–mean square deviation threshold. It also flags structural motifs on the model that are known to cause issues during in vitro development. ABodyBuilder was tested on 4 separate datasets, including the 11 antibodies from the Antibody Modeling Assessment–II competition. ABodyBuilder builds models that are of similar quality to other methodologies, with sub–Angstrom predictions for the ‘canonical’ CDR loops. Its ability to model nanobodies, and rapidly generate models (∼30 seconds per model) widens its potential usage. ABodyBuilder can also help users in decision–making for the development of novel antibodies because it provides model confidence and potential sequence liabilities. ABodyBuilder is freely available at http://opig.stats.ox.ac.uk/webapps/abodybuilder. PMID:27392298

Using prior information to separate the temperature response to greenhouse gas forcing from that of aerosols - Estimating the transient climate response

NASA Astrophysics Data System (ADS)

Schurer, Andrew; Hegerl, Gabriele

2016-04-01

The evaluation of the transient climate response (TCR) is of critical importance to policy makers as it can be used to calculate a simple estimate of the expected warming given predicted greenhouse gas emissions. Previous studies using optimal detection techniques have been able to estimate a TCR value from the historic record using simulations from some of the models which took part in the Coupled Model Intercomparison Project Phase 5 (CMIP5) but have found that others give unconstrained results. At least partly this is due to degeneracy between the greenhouse gas and aerosol signals which makes separation of the temperature response to these forcings problematic. Here we re-visit this important topic by using an adapted optimal detection analysis within a Bayesian framework. We account for observational uncertainty by the use of an ensemble of instrumental observations, and model uncertainty by combining the results from several different models. This framework allows the use of prior information which is found to help separate the response to the different forcings leading to a more constrained estimate of TCR.

Macroscopic balance model for wave rotors

NASA Technical Reports Server (NTRS)

Welch, Gerard E.

1996-01-01

A mathematical model for multi-port wave rotors is described. The wave processes that effect energy exchange within the rotor passage are modeled using one-dimensional gas dynamics. Macroscopic mass and energy balances relate volume-averaged thermodynamic properties in the rotor passage control volume to the mass, momentum, and energy fluxes at the ports. Loss models account for entropy production in boundary layers and in separating flows caused by blade-blockage, incidence, and gradual opening and closing of rotor passages. The mathematical model provides a basis for predicting design-point wave rotor performance, port timing, and machine size. Model predictions are evaluated through comparisons with CFD calculations and three-port wave rotor experimental data. A four-port wave rotor design example is provided to demonstrate model applicability. The modeling approach is amenable to wave rotor optimization studies and rapid assessment of the trade-offs associated with integrating wave rotors into gas turbine engine systems.

Towards a framework for business model innovation in health care delivery in developing countries.

PubMed

Castano, Ramon

2014-12-02

Uncertainty and information asymmetries in health care are the basis for a supply-sided mindset in the health care industry and for a business model for hospitals and doctor's practices; these two models have to be challenged with business model innovation. The three elements which ensure this are standardizability, separability, and patient-centeredness. As scientific evidence advances and outcomes are more predictable, standardization is more feasible. If a standardized process can also be separated from the hospital and doctor's practice, it is more likely that innovative business models emerge. Regarding patient centeredness, it has to go beyond the oversimplifying approach to patient satisfaction with amenities and interpersonal skills of staff, to include the design of structure and processes starting from patients' needs, expectations, and preferences. Six business models are proposed in this article, including those of hospitals and doctor's practices. Unravelling standardized and separable processes from the traditional hospital setting will increase hospital expenditure, however, the new business models would reduce expenses. The net effect on efficiency could be argued to be positive. Regarding equity in access to high-quality care, most of the innovations described along these business models have emerged in developing countries; it is therefore reasonable to be optimistic regarding their impact on access by the poor. These models provide a promising route to achieve sustainable universal access to high quality care by the poor. Business model innovation is a necessary step to guarantee sustainability of health care systems; standardizability, separability, and patient-centeredness are key elements underlying the six business model innovations proposed in this article.

Ensemble method for dengue prediction.

PubMed

Buczak, Anna L; Baugher, Benjamin; Moniz, Linda J; Bagley, Thomas; Babin, Steven M; Guven, Erhan

2018-01-01

In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru.

Ensemble method for dengue prediction

PubMed Central

Baugher, Benjamin; Moniz, Linda J.; Bagley, Thomas; Babin, Steven M.; Guven, Erhan

2018-01-01

Background In the 2015 NOAA Dengue Challenge, participants made three dengue target predictions for two locations (Iquitos, Peru, and San Juan, Puerto Rico) during four dengue seasons: 1) peak height (i.e., maximum weekly number of cases during a transmission season; 2) peak week (i.e., week in which the maximum weekly number of cases occurred); and 3) total number of cases reported during a transmission season. A dengue transmission season is the 12-month period commencing with the location-specific, historical week with the lowest number of cases. At the beginning of the Dengue Challenge, participants were provided with the same input data for developing the models, with the prediction testing data provided at a later date. Methods Our approach used ensemble models created by combining three disparate types of component models: 1) two-dimensional Method of Analogues models incorporating both dengue and climate data; 2) additive seasonal Holt-Winters models with and without wavelet smoothing; and 3) simple historical models. Of the individual component models created, those with the best performance on the prior four years of data were incorporated into the ensemble models. There were separate ensembles for predicting each of the three targets at each of the two locations. Principal findings Our ensemble models scored higher for peak height and total dengue case counts reported in a transmission season for Iquitos than all other models submitted to the Dengue Challenge. However, the ensemble models did not do nearly as well when predicting the peak week. Conclusions The Dengue Challenge organizers scored the dengue predictions of the Challenge participant groups. Our ensemble approach was the best in predicting the total number of dengue cases reported for transmission season and peak height for Iquitos, Peru. PMID:29298320

Growth and nonlinear response of driven water bells

NASA Astrophysics Data System (ADS)

Kolinski, John M.; Aharoni, Hillel; Fineberg, Jay; Sharon, Eran

2017-04-01

A water bell forms when a fluid jet impacts upon a target and separates into a two-dimensional sheet. Depending on the angle of separation from the target, the sheet can curve into a variety of different geometries. We show analytically that harmonic perturbations of water bells have linear wave solutions with geometry-dependent growth. We test the predictions of this model experimentally with a custom target system, and observe growth in agreement with the model below a critical forcing amplitude. Once the critical forcing amplitude is exceeded, a nonlinear transcritical bifurcation occurs; the response amplitude increases linearly with increasing forcing amplitude, albeit with a fundamentally different spatial form, and distinct nodes appear in the amplitude envelope.

The predictability of a lake phytoplankton community, over time-scales of hours to years.

PubMed

Thomas, Mridul K; Fontana, Simone; Reyes, Marta; Kehoe, Michael; Pomati, Francesco

2018-05-01

Forecasting changes to ecological communities is one of the central challenges in ecology. However, nonlinear dependencies, biotic interactions and data limitations have limited our ability to assess how predictable communities are. Here, we used a machine learning approach and environmental monitoring data (biological, physical and chemical) to assess the predictability of phytoplankton cell density in one lake across an unprecedented range of time-scales. Communities were highly predictable over hours to months: model R 2 decreased from 0.89 at 4 hours to 0.74 at 1 month, and in a long-term dataset lacking fine spatial resolution, from 0.46 at 1 month to 0.32 at 10 years. When cyanobacterial and eukaryotic algal cell densities were examined separately, model-inferred environmental growth dependencies matched laboratory studies, and suggested novel trade-offs governing their competition. High-frequency monitoring and machine learning can set prediction targets for process-based models and help elucidate the mechanisms underlying ecological dynamics. © 2018 John Wiley & Sons Ltd/CNRS.

Contact Prediction for Beta and Alpha-Beta Proteins Using Integer Linear Optimization and its Impact on the First Principles 3D Structure Prediction Method ASTRO-FOLD

PubMed Central

Rajgaria, R.; Wei, Y.; Floudas, C. A.

2010-01-01

An integer linear optimization model is presented to predict residue contacts in β, α + β, and α/β proteins. The total energy of a protein is expressed as sum of a Cα – Cα distance dependent contact energy contribution and a hydrophobic contribution. The model selects contacts that assign lowest energy to the protein structure while satisfying a set of constraints that are included to enforce certain physically observed topological information. A new method based on hydrophobicity is proposed to find the β-sheet alignments. These β-sheet alignments are used as constraints for contacts between residues of β-sheets. This model was tested on three independent protein test sets and CASP8 test proteins consisting of β, α + β, α/β proteins and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) was approximately 61%. The average true positive and false positive distances were also calculated for each of the test sets and they are 7.58 Å and 15.88 Å, respectively. Residue contact prediction can be directly used to facilitate the protein tertiary structure prediction. This proposed residue contact prediction model is incorporated into the first principles protein tertiary structure prediction approach, ASTRO-FOLD. The effectiveness of the contact prediction model was further demonstrated by the improvement in the quality of the protein structure ensemble generated using the predicted residue contacts for a test set of 10 proteins. PMID:20225257

An Operational Wake Vortex Sensor Using Pulsed Coherent Lidar

NASA Technical Reports Server (NTRS)

Barker, Ben C., Jr.; Koch, Grady J.; Nguyen, D. Chi

1998-01-01

NASA and FAA initiated a program in 1994 to develop methods of setting spacings for landing aircraft by incorporating information on the real-time behavior of aircraft wake vortices. The current wake separation standards were developed in the 1970's when there was relatively light airport traffic and a logical break point by which to categorize aircraft. Today's continuum of aircraft sizes and increased airport packing densities have created a need for re-evaluation of wake separation standards. The goals of this effort are to ensure that separation standards are adequate for safety and to reduce aircraft spacing for higher airport capacity. Of particular interest are the different requirements for landing under visual flight conditions and instrument flight conditions. Over the years, greater spacings have been established for instrument flight than are allowed for visual flight conditions. Preliminary studies indicate that the airline industry would save considerable money and incur fewer passenger delays if a dynamic spacing system could reduce separations at major hubs during inclement weather to the levels routinely achieved under visual flight conditions. The sensor described herein may become part of this dynamic spacing system known as the "Aircraft VOrtex Spacing System" (AVOSS) that will interface with a future air traffic control system. AVOSS will use vortex behavioral models and short-term weather prediction models in order to predict vortex behavior sufficiently into the future to allow dynamic separation standards to be generated. The wake vortex sensor will periodically provide data to validate AVOSS predictions. Feasibility of measuring wake vortices using a lidar was first demonstrated using a continuous wave (CW) system from NASA Marshall Space Flight Sensor and tested at the Volpe National Transportation Systems Center's wake vortex test site at JFK International Airport. Other applications of CW lidar for wake vortex measurement have been made more recently, including a system developed by the MIT Lincoln Laboratory. This lidar has been used for detailed measurements of wake vortex velocities in support of wake vortex model validation. The first measurements of wake vortices using a pulsed, lidar were made by Coherent Technologies, Inc. (CTI) using a 2 micron solid-state, flashlamp-pumped system operating at 5 Hz. This system was first deployed at Denver's Stapleton Airport. Pulsed lidar has been selected as the baseline technology for an operational sensor due to its longer range capability.

Residents’ Waste Separation Behaviors at the Source: Using SEM with the Theory of Planned Behavior in Guangzhou, China

PubMed Central

Zhang, Dongliang; Huang, Guangqing; Yin, Xiaoling; Gong, Qinghua

2015-01-01

Understanding the factors that affect residents’ waste separation behaviors helps in constructing effective environmental campaigns for a community. Using the theory of planned behavior (TPB), this study examines factors associated with waste separation behaviors by analyzing responses to questionnaires distributed in Guangzhou, China. Data drawn from 208 of 1000-field questionnaires were used to assess socio-demographic factors and the TPB constructs (i.e., attitudes, subjective norms, perceived behavioral control, intentions, and situational factors). The questionnaire data revealed that attitudes, subjective norms, perceived behavioral control, intentions, and situational factors significantly predicted household waste behaviors in Guangzhou, China. Through a structural equation modeling analysis, we concluded that campaigns targeting moral obligations may be particularly effective for increasing the participation rate in waste separation behaviors. PMID:26274969

Streamflow Prediction based on Chaos Theory

NASA Astrophysics Data System (ADS)

Li, X.; Wang, X.; Babovic, V. M.

2015-12-01

Chaos theory is a popular method in hydrologic time series prediction. Local model (LM) based on this theory utilizes time-delay embedding to reconstruct the phase-space diagram. For this method, its efficacy is dependent on the embedding parameters, i.e. embedding dimension, time lag, and nearest neighbor number. The optimal estimation of these parameters is thus critical to the application of Local model. However, these embedding parameters are conventionally estimated using Average Mutual Information (AMI) and False Nearest Neighbors (FNN) separately. This may leads to local optimization and thus has limitation to its prediction accuracy. Considering about these limitation, this paper applies a local model combined with simulated annealing (SA) to find the global optimization of embedding parameters. It is also compared with another global optimization approach of Genetic Algorithm (GA). These proposed hybrid methods are applied in daily and monthly streamflow time series for examination. The results show that global optimization can contribute to the local model to provide more accurate prediction results compared with local optimization. The LM combined with SA shows more advantages in terms of its computational efficiency. The proposed scheme here can also be applied to other fields such as prediction of hydro-climatic time series, error correction, etc.

Retention modeling under organic modifier gradient conditions in ion-pair reversed-phase chromatography. Application to the separation of a set of underivatized amino acids.

PubMed

Pappa-Louisi, A; Agrafiotou, P; Papachristos, K

2010-07-01

The combined effect of the ion-pairing reagent concentration, C(ipr), and organic modifier content, phi, on the retention under phi-gradient conditions at different constant C(ipr) was treated in this study by using two approaches. In the first approach, the prediction of the retention time of a sample solute is based on a direct fitting procedure of a proper retention model to 3-D phi-gradient retention data obtained under the same phi-linear variation but with different slope and time duration of the initial isocratic part and in the presence of various constant C(ipr) values in the eluent. The second approach is based on a retention model describing the combined effect of C(ipr) and phi on the retention of solutes in isocratic mode and consequently analyzes isocratic data obtained in mobile phases containing different C(ipr) values. The effectiveness of the above approaches was tested in the retention prediction of a mixture of 16 underivatized amino acids using mobile phases containing acetonitrile as organic modifier and sodium dodecyl sulfate as ion-pairing reagent. From these approaches, only the first one gives satisfactory predictions and can be successfully used in optimization of ion-pair chromatographic separations under gradient conditions. The failure of the second approach to predict the retention of solutes in the gradient elution mode in the presence of different C(ipr) values was attributed to slow changes in the distribution equilibrium of ion-pairing reagents caused by phi-variation.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Evaluating Air-Quality Models: Review and Outlook.

NASA Astrophysics Data System (ADS)

Weil, J. C.; Sykes, R. I.; Venkatram, A.

1992-10-01

Over the past decade, much attention has been devoted to the evaluation of air-quality models with emphasis on model performance in predicting the high concentrations that are important in air-quality regulations. This paper stems from our belief that this practice needs to be expanded to 1) evaluate model physics and 2) deal with the large natural or stochastic variability in concentration. The variability is represented by the root-mean- square fluctuating concentration (c about the mean concentration (C) over an ensemble-a given set of meteorological, source, etc. conditions. Most air-quality models used in applications predict C, whereas observations are individual realizations drawn from an ensemble. For cC large residuals exist between predicted and observed concentrations, which confuse model evaluations.This paper addresses ways of evaluating model physics in light of the large c the focus is on elevated point-source models. Evaluation of model physics requires the separation of the mean model error-the difference between the predicted and observed C-from the natural variability. A residual analysis is shown to be an elective way of doing this. Several examples demonstrate the usefulness of residuals as well as correlation analyses and laboratory data in judging model physics.In general, c models and predictions of the probability distribution of the fluctuating concentration (c), (c, are in the developmental stage, with laboratory data playing an important role. Laboratory data from point-source plumes in a convection tank show that (c approximates a self-similar distribution along the plume center plane, a useful result in a residual analysis. At pmsent,there is one model-ARAP-that predicts C, c, and (c for point-source plumes. This model is more computationally demanding than other dispersion models (for C only) and must be demonstrated as a practical tool. However, it predicts an important quantity for applications- the uncertainty in the very high and infrequent concentrations. The uncertainty is large and is needed in evaluating operational performance and in predicting the attainment of air-quality standards.

Computational Study of Separating Flow in a Planar Subsonic Diffuser

NASA Technical Reports Server (NTRS)

DalBello, Teryn; Dippold, Vance, III; Georgiadis, Nicholas J.

2005-01-01

A computational study of the separated flow through a 2-D asymmetric subsonic diffuser has been performed. The Wind Computational Fluid Dynamics code is used to predict the separation and reattachment behavior for an incompressible diffuser flow. The diffuser inlet flow is a two-dimensional, turbulent, and fully-developed channel flow with a Reynolds number of 20,000 based on the centerline velocity and the channel height. Wind solutions computed with the Menter SST, Chien k-epsilon, Spalart-Allmaras and Explicit Algebraic Reynolds Stress turbulence models are compared with experimentally measured velocity profiles and skin friction along the upper and lower walls. In addition to the turbulence model study, the effects of grid resolution and use of wall functions were investigated. The grid studies varied the number of grid points across the diffuser and varied the initial wall spacing from y(sup +) = 0.2 to 60. The wall function study assessed the applicability of wall functions for analysis of separated flow. The SST and Explicit Algebraic Stress models provide the best agreement with experimental data, and it is recommended wall functions should only be used with a high level of caution.

Noise and diffusion of a vibrated self-propelled granular particle

NASA Astrophysics Data System (ADS)

Walsh, Lee; Wagner, Caleb G.; Schlossberg, Sarah; Olson, Christopher; Baskaran, Aparna; Menon, Narayanan

Granular materials are an important physical realization of active matter. In vibration-fluidized granular matter, both diffusion and self-propulsion derive from the same collisional forcing, unlike many other active systems where there is a clean separation between the origin of single-particle mobility and the coupling to noise. Here we present experimental studies of single-particle motion in a vibrated granular monolayer, along with theoretical analysis that compares grain motion at short and long time scales to the assumptions and predictions, respectively, of the active Brownian particle (ABP) model. The results demonstrate that despite the unique relation between noise and propulsion, granular media do show the generic features predicted by the ABP model and indicate that this is a valid framework to predict collective phenomena. Additionally, our scheme of analysis for validating the inputs and outputs of the model can be applied to other granular and non-granular systems.

Application of Molecular Interaction Volume Model for Phase Equilibrium of Sn-Based Binary System in Vacuum Distillation

NASA Astrophysics Data System (ADS)

Kong, Lingxin; Yang, Bin; Xu, Baoqiang; Li, Yifu

2014-09-01

Based on the molecular interaction volume model (MIVM), the activities of components of Sn-Sb, Sb-Bi, Sn-Zn, Sn-Cu, and Sn-Ag alloys were predicted. The predicted values are in good agreement with the experimental data, which indicate that the MIVM is of better stability and reliability due to its good physical basis. A significant advantage of the MIVM lies in its ability to predict the thermodynamic properties of liquid alloys using only two parameters. The phase equilibria of Sn-Sb and Sn-Bi alloys were calculated based on the properties of pure components and the activity coefficients, which indicates that Sn-Sb and Sn-Bi alloys can be separated thoroughly by vacuum distillation. This study extends previous investigations and provides an effective and convenient model on which to base refining simulations for Sn-based alloys.

Anxiety, social skills, friendship quality, and peer victimization: an integrated model.

PubMed

Crawford, A Melissa; Manassis, Katharina

2011-10-01

This cross-sectional study investigated whether anxiety and social functioning interact in their prediction of peer victimization. A structural equation model linking anxiety, social skills, and friendship quality to victimization was tested separately for children with anxiety disorders and normal comparison children to explore whether the processes involved in victimization differ for these groups. Participants were 8-14 year old children: 55 (34 boys, 21 girls) diagnosed with an anxiety disorder and 85 (37 boys, 48 girls) normal comparison children. The final models for both groups yielded two independent pathways to victimization: (a) anxiety independently predicted being victimized; and (b) poor social skills predicted lower friendship quality, which in turn, placed a child at risk for victimization. These findings have important implications for the treatment of childhood anxiety disorders and for school-based anti-bullying interventions, but replication with larger samples is indicated. Copyright © 2011 Elsevier Ltd. All rights reserved.

Thermodynamic model effects on the design and optimization of natural gas plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diaz, S.; Zabaloy, M.; Brignole, E.A.

1999-07-01

The design and optimization of natural gas plants is carried out on the basis of process simulators. The physical property package is generally based on cubic equations of state. By rigorous thermodynamics phase equilibrium conditions, thermodynamic functions, equilibrium phase separations, work and heat are computed. The aim of this work is to analyze the NGL turboexpansion process and identify possible process computations that are more sensitive to model predictions accuracy. Three equations of state, PR, SRK and Peneloux modification, are used to study the effect of property predictions on process calculations and plant optimization. It is shown that turboexpander plantsmore » have moderate sensitivity with respect to phase equilibrium computations, but higher accuracy is required for the prediction of enthalpy and turboexpansion work. The effect of modeling CO{sub 2} solubility is also critical in mixtures with high CO{sub 2} content in the feed.« less

Fast-multivariate optimization of chiral separations in capillary electrophoresis: anticipative strategies.

PubMed

Escuder-Gilabert, L; Martín-Biosca, Y; Sagrado, S; Medina-Hernández, M J

2014-10-10

The design of experiments (DOE) is a good option for rationally limiting the number of experiments required to achieve the enantioresolution (Rs) of a chiral compound in capillary electrophoresis. In some cases, the modeled Rs after DOE analysis can be unsatisfactory, maybe because the range of the explored factors (DOE domain) was not the adequate. In these cases, anticipative strategies can be an alternative to the repetition of the process (e.g. a new DOE), to save time and money. In this work, multiple linear regression (MLR)-steepest ascent and a new anticipative strategy based on a multiple response-partial least squares model (called PLS2-prediction) are examined as post-DOE strategies to anticipate new experimental conditions providing satisfactory Rs values. The new anticipative strategy allows to include the analysis time (At) and uncertainty limits into the decision making process. To demonstrate their efficiency, the chiral separation of hexaconazole and penconazole, as model compounds, is studied using highly sulfated-β-cyclodextrin (HS-β-CD) in electrokinetic chromatography (EKC). Box-Behnken DOE for three factors (background electrolyte pH, separation temperature and HS-β-CD concentration) and two responses (Rs and At) is used. Using commercially available software, the whole modeling and anticipative process is automatic, simple and requires minimal skills from the researcher. Both strategies studied have proven to successfully anticipate Rs values close to the experimental ones for EKC conditions outside the DOE domain for the two model compounds. The results in this work suggest that PLS2-prediction approach could be the strategy of choice to obtain secure anticipations in EKC. Copyright © 2014 Elsevier B.V. All rights reserved.

Development and numerical analysis of low specific speed mixed-flow pump

NASA Astrophysics Data System (ADS)

Li, H. F.; Huo, Y. W.; Pan, Z. B.; Zhou, W. C.; He, M. H.

2012-11-01

With the development of the city, the market of the mixed flow pump with large flux and high head is prospect. The KSB Shanghai Pump Co., LTD decided to develop low speed specific speed mixed flow pump to meet the market requirements. Based on the centrifugal pump and axial flow pump model, aiming at the characteristics of large flux and high head, a new type of guide vane mixed flow pump was designed. The computational fluid dynamics method was adopted to analyze the internal flow of the new type model and predict its performances. The time-averaged Navier-Stokes equations were closed by SST k-ω turbulent model to adapt internal flow of guide vane with larger curvatures. The multi-reference frame(MRF) method was used to deal with the coupling of rotating impeller and static guide vane, and the SIMPLEC method was adopted to achieve the coupling solution of velocity and pressure. The computational results shows that there is great flow impact on the head of vanes at different working conditions, and there is great flow separation at the tailing of the guide vanes at different working conditions, and all will affect the performance of pump. Based on the computational results, optimizations were carried out to decrease the impact on the head of vanes and flow separation at the tailing of the guide vanes. The optimized model was simulated and its performance was predicted. The computational results show that the impact on the head of vanes and the separation at the tailing of the guide vanes disappeared. The high efficiency of the optimized pump is wide, and it fit the original design destination. The newly designed mixed flow pump is now in modeling and its experimental performance will be getting soon.

Testing for ontological errors in probabilistic forecasting models of natural systems

PubMed Central

Marzocchi, Warner; Jordan, Thomas H.

2014-01-01

Probabilistic forecasting models describe the aleatory variability of natural systems as well as our epistemic uncertainty about how the systems work. Testing a model against observations exposes ontological errors in the representation of a system and its uncertainties. We clarify several conceptual issues regarding the testing of probabilistic forecasting models for ontological errors: the ambiguity of the aleatory/epistemic dichotomy, the quantification of uncertainties as degrees of belief, the interplay between Bayesian and frequentist methods, and the scientific pathway for capturing predictability. We show that testability of the ontological null hypothesis derives from an experimental concept, external to the model, that identifies collections of data, observed and not yet observed, that are judged to be exchangeable when conditioned on a set of explanatory variables. These conditional exchangeability judgments specify observations with well-defined frequencies. Any model predicting these behaviors can thus be tested for ontological error by frequentist methods; e.g., using P values. In the forecasting problem, prior predictive model checking, rather than posterior predictive checking, is desirable because it provides more severe tests. We illustrate experimental concepts using examples from probabilistic seismic hazard analysis. Severe testing of a model under an appropriate set of experimental concepts is the key to model validation, in which we seek to know whether a model replicates the data-generating process well enough to be sufficiently reliable for some useful purpose, such as long-term seismic forecasting. Pessimistic views of system predictability fail to recognize the power of this methodology in separating predictable behaviors from those that are not. PMID:25097265

Nurses' short-term prediction of violence in acute psychiatric intensive care.

PubMed

Björkdahl, A; Olsson, D; Palmstierna, T

2006-03-01

To evaluate the short-term predictive capacity of the Brøset Violence Checklist (BVC) when used by nurses in a psychiatric intensive care unit. Seventy-three patients were assessed according to the BVC three times daily. Violent incidents were recorded with the Staff Observation Aggression Scale, revised version. An extended Cox proportional hazards model with multiple events and time-dependent covariates was estimated to evaluate how the highest BVC sum of the last 24 h and its separate items affect the risk for severe violence within the next 24 h. With a BVC sum of one or more, hazard for severe violence was six times higher than if the sum was zero. Four of the six separate items significantly increased the risk for severe violence with hazard ratios between 3.0 and 6.3. Risk for in-patient violence in a short-term perspective can to a high degree be predicted by nurses using the BVC.

Predicting Multicomponent Adsorption Isotherms in Open-Metal Site Materials Using Force Field Calculations Based on Energy Decomposed Density Functional Theory.

PubMed

Heinen, Jurn; Burtch, Nicholas C; Walton, Krista S; Fonseca Guerra, Célia; Dubbeldam, David

2016-12-12

For the design of adsorptive-separation units, knowledge is required of the multicomponent adsorption behavior. Ideal adsorbed solution theory (IAST) breaks down for olefin adsorption in open-metal site (OMS) materials due to non-ideal donor-acceptor interactions. Using a density-function-theory-based energy decomposition scheme, we develop a physically justifiable classical force field that incorporates the missing orbital interactions using an appropriate functional form. Our first-principles derived force field shows greatly improved quantitative agreement with the inflection points, initial uptake, saturation capacity, and enthalpies of adsorption obtained from our in-house adsorption experiments. While IAST fails to make accurate predictions, our improved force field model is able to correctly predict the multicomponent behavior. Our approach is also transferable to other OMS structures, allowing the accurate study of their separation performances for olefins/paraffins and further mixtures involving complex donor-acceptor interactions. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Review on DTU-parton model for hadron-hadron and hadron-nucleus collisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chiu, C.B.

1980-08-01

The parton picture of color separation of dual string and its subsequent breakup is used to motivate the DTU-parton model for high energy small p/sub T/ multiparticle productions in hadron-hadron and hadron-nucleus collisions. A brief survey on phenomenological applications of the model: such as the inclusive spectra for various hh processes and central plateau heights predicted, hA inclusive spectra and the approximate anti v-universalities is presented.

Planck intermediate results. XLII. Large-scale Galactic magnetic fields

NASA Astrophysics Data System (ADS)

Planck Collaboration; Adam, R.; Ade, P. A. R.; Alves, M. I. R.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Chiang, H. C.; Christensen, P. R.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dolag, K.; Doré, O.; Ducout, A.; Dupac, X.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Ferrière, K.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Galeotta, S.; Ganga, K.; Ghosh, T.; Giard, M.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Harrison, D. L.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hobson, M.; Hornstrup, A.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leahy, J. P.; Leonardi, R.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Melchiorri, A.; Mennella, A.; Migliaccio, M.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Nørgaard-Nielsen, H. U.; Oppermann, N.; Orlando, E.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Pasian, F.; Perotto, L.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Pratt, G. W.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Scott, D.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Strong, A. W.; Sudiwala, R.; Sunyaev, R.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Valenziano, L.; Valiviita, J.; Van Tent, F.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-12-01

Recent models for the large-scale Galactic magnetic fields in the literature have been largely constrained by synchrotron emission and Faraday rotation measures. We use three different but representative models to compare their predicted polarized synchrotron and dust emission with that measured by the Planck satellite. We first update these models to match the Planck synchrotron products using a common model for the cosmic-ray leptons. We discuss the impact on this analysis of the ongoing problems of component separation in the Planck microwave bands and of the uncertain cosmic-ray spectrum. In particular, the inferred degree of ordering in the magnetic fields is sensitive to these systematic uncertainties, and we further show the importance of considering the expected variations in the observables in addition to their mean morphology. We then compare the resulting simulated emission to the observed dust polarization and find that the dust predictions do not match the morphology in the Planck data but underpredict the dust polarization away from the plane. We modify one of the models to roughly match both observables at high latitudes by increasing the field ordering in the thin disc near the observer. Though this specific analysis is dependent on the component separation issues, we present the improved model as a proof of concept for how these studies can be advanced in future using complementary information from ongoing and planned observational projects.

GOBF-ARMA based model predictive control for an ideal reactive distillation column.

PubMed

Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K

2015-11-01

This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. Copyright © 2015 Elsevier Inc. All rights reserved.

Right Lateral Cerebellum Represents Linguistic Predictability.

PubMed

Lesage, Elise; Hansen, Peter C; Miall, R Chris

2017-06-28

Mounting evidence indicates that posterolateral portions of the cerebellum (right Crus I/II) contribute to language processing, but the nature of this role remains unclear. Based on a well-supported theory of cerebellar motor function, which ascribes to the cerebellum a role in short-term prediction through internal modeling, we hypothesize that right cerebellar Crus I/II supports prediction of upcoming sentence content. We tested this hypothesis using event-related fMRI in male and female human subjects by manipulating the predictability of written sentences. Our design controlled for motor planning and execution, as well as for linguistic features and working memory load; it also allowed separation of the prediction interval from the presentation of the final sentence item. In addition, three further fMRI tasks captured semantic, phonological, and orthographic processing to shed light on the nature of the information processed. As hypothesized, activity in right posterolateral cerebellum correlated with the predictability of the upcoming target word. This cerebellar region also responded to prediction error during the outcome of the trial. Further, this region was engaged in phonological, but not semantic or orthographic, processing. This is the first imaging study to demonstrate a right cerebellar contribution in language comprehension independently from motor, cognitive, and linguistic confounds. These results complement our work using other methodologies showing cerebellar engagement in linguistic prediction and suggest that internal modeling of phonological representations aids language production and comprehension. SIGNIFICANCE STATEMENT The cerebellum is traditionally seen as a motor structure that allows for smooth movement by predicting upcoming signals. However, the cerebellum is also consistently implicated in nonmotor functions such as language and working memory. Using fMRI, we identify a cerebellar area that is active when words are predicted and when these predictions are violated. This area is active in a separate task that requires phonological processing, but not in tasks that require semantic or visuospatial processing. Our results support the idea of prediction as a unifying cerebellar function in motor and nonmotor domains. We provide new insights by linking the cerebellar role in prediction to its role in verbal working memory, suggesting that these predictions involve phonological processing. Copyright © 2017 Lesage et al.

Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions

USGS Publications Warehouse

Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.

2009-01-01

This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non-stationarity of the climate series and possible cross-correlations between models. Crown Copyright ?? 2008.

The structure of evaporating and combusting sprays: Measurements and predictions

NASA Technical Reports Server (NTRS)

Shuen, J. S.; Solomon, A. S. P.; Faeth, G. M.

1982-01-01

An apparatus was constructed to provide measurements in open sprays with no zones of recirculation, in order to provide well-defined conditions for use in evaluating spray models. Measurements were completed in a gas jet, in order to test experimental methods, and are currently in progress for nonevaporating sprays. A locally homogeneous flow (LHF) model where interphase transport rates are assumed to be infinitely fast; a separated flow (SF) model which allows for finite interphase transport rates but neglects effects of turbulent fluctuations on drop motion; and a stochastic SF model which considers effects of turbulent fluctuations on drop motion were evaluated using existing data on particle-laden jets. The LHF model generally overestimates rates of particle dispersion while the SF model underestimates dispersion rates. The stochastic SF flow yield satisfactory predictions except at high particle mass loadings where effects of turbulence modulation may have caused the model to overestimate turbulence levels.

Selective interference with image retention and generation: evidence for the workspace model.

PubMed

van der Meulen, Marian; Logie, Robert H; Della Sala, Sergio

2009-08-01

We address three types of model of the relationship between working memory (WM) and long-term memory (LTM): (a) the gateway model, in which WM acts as a gateway between perceptual input and LTM; (b) the unitary model, in which WM is seen as the currently activated areas of LTM; and (c) the workspace model, in which perceptual input activates LTM, and WM acts as a separate workspace for processing and temporary retention of these activated traces. Predictions of these models were tested, focusing on visuospatial working memory and using dual-task methodology to combine two main tasks (visual short-term retention and image generation) with two interference tasks (irrelevant pictures and spatial tapping). The pictures selectively disrupted performance on the generation task, whereas the tapping selectively interfered with the retention task. Results are consistent with the predictions of the workspace model.

Lattice modeling and calibration with turn-by-turn orbit data

NASA Astrophysics Data System (ADS)

Huang, Xiaobiao; Sebek, Jim; Martin, Don

2010-11-01

A new method that explores turn-by-turn beam position monitor (BPM) data to calibrate lattice models of accelerators is proposed. The turn-by-turn phase space coordinates at one location of the ring are first established using data from two BPMs separated by a simple section with a known transfer matrix, such as a drift space. The phase space coordinates are then tracked with the model to predict positions at other BPMs, which can be compared to measurements. The model is adjusted to minimize the difference between the measured and predicted orbit data. BPM gains and rolls are included as fitting variables. This technique can be applied to either the entire or a section of the ring. We have tested the method experimentally on a part of the SPEAR3 ring.

Romantic Partner Monitoring After Breakups: Attachment, Dependence, Distress, and Post-Dissolution Online Surveillance via Social Networking Sites.

PubMed

Fox, Jesse; Tokunaga, Robert S

2015-09-01

Romantic relationship dissolution can be stressful, and social networking sites make it difficult to separate from a romantic partner online as well as offline. An online survey (N = 431) tested a model synthesizing attachment, investment model variables, and post-dissolution emotional distress as predictors of interpersonal surveillance (i.e., "Facebook stalking") of one's ex-partner on Facebook after a breakup. Results indicated that anxious attachment predicted relational investment but also seeking relationship alternatives; avoidant attachment was negatively related to investment but positively related to seeking alternatives. Investment predicted commitment, whereas seeking alternatives was negatively related to commitment. Commitment predicted emotional distress after the breakup. Distress predicted partner monitoring immediately following the breakup, particularly for those who did not initiate the breakup, as well as current partner monitoring. Given their affordances, social media are discussed as potentially unhealthy enablers for online surveillance after relationship termination.

Advanced Computational Modeling Approaches for Shock Response Prediction

NASA Technical Reports Server (NTRS)

Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee

2015-01-01

Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.