Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

NASA Technical Reports Server (NTRS)

Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

2011-01-01

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Predicting bifurcation angle effect on blood flow in the microvasculature.

PubMed

Yang, Jiho; Pak, Y Eugene; Lee, Tae-Rin

2016-11-01

Since blood viscosity is a basic parameter for understanding hemodynamics in human physiology, great amount of research has been done in order to accurately predict this highly non-Newtonian flow property. However, previous works lacked in consideration of hemodynamic changes induced by heterogeneous vessel networks. In this paper, the effect of bifurcation on hemodynamics in a microvasculature is quantitatively predicted. The flow resistance in a single bifurcation microvessel was calculated by combining a new simple mathematical model with 3-dimensional flow simulation for varying bifurcation angles under physiological flow conditions. Interestingly, the results indicate that flow resistance induced by vessel bifurcation holds a constant value of approximately 0.44 over the whole single bifurcation model below diameter of 60μm regardless of geometric parameters including bifurcation angle. Flow solutions computed from this new model showed substantial decrement in flow velocity relative to other mathematical models, which do not include vessel bifurcation effects, while pressure remained the same. Furthermore, when applying the bifurcation angle effect to the entire microvascular network, the simulation results gave better agreements with recent in vivo experimental measurements. This finding suggests a new paradigm in microvascular blood flow properties, that vessel bifurcation itself, regardless of its angle, holds considerable influence on blood viscosity, and this phenomenon will help to develop new predictive tools in microvascular research. Copyright © 2016 Elsevier Inc. All rights reserved.

Performance of Reynolds Averaged Navier-Stokes Models in Predicting Separated Flows: Study of the Hump Flow Model Problem

NASA Technical Reports Server (NTRS)

Cappelli, Daniele; Mansour, Nagi N.

2012-01-01

Separation can be seen in most aerodynamic flows, but accurate prediction of separated flows is still a challenging problem for computational fluid dynamics (CFD) tools. The behavior of several Reynolds Averaged Navier-Stokes (RANS) models in predicting the separated ow over a wall-mounted hump is studied. The strengths and weaknesses of the most popular RANS models (Spalart-Allmaras, k-epsilon, k-omega, k-omega-SST) are evaluated using the open source software OpenFOAM. The hump ow modeled in this work has been documented in the 2004 CFD Validation Workshop on Synthetic Jets and Turbulent Separation Control. Only the baseline case is treated; the slot flow control cases are not considered in this paper. Particular attention is given to predicting the size of the recirculation bubble, the position of the reattachment point, and the velocity profiles downstream of the hump.

A new algebraic turbulence model for accurate description of airfoil flows

NASA Astrophysics Data System (ADS)

Xiao, Meng-Juan; She, Zhen-Su

2017-11-01

We report a new algebraic turbulence model (SED-SL) based on the SED theory, a symmetry-based approach to quantifying wall turbulence. The model specifies a multi-layer profile of a stress length (SL) function in both the streamwise and wall-normal directions, which thus define the eddy viscosity in the RANS equation (e.g. a zero-equation model). After a successful simulation of flat plate flow (APS meeting, 2016), we report here further applications of the model to the flow around airfoil, with significant improvement of the prediction accuracy of the lift (CL) and drag (CD) coefficients compared to other popular models (e.g. BL, SA, etc.). Two airfoils, namely RAE2822 airfoil and NACA0012 airfoil, are computed for over 50 cases. The results are compared to experimental data from AGARD report, which shows deviations of CL bounded within 2%, and CD within 2 counts (10-4) for RAE2822 and 6 counts for NACA0012 respectively (under a systematic adjustment of the flow conditions). In all these calculations, only one parameter (proportional to the Karmen constant) shows slight variation with Mach number. The most remarkable outcome is, for the first time, the accurate prediction of the drag coefficient. The other interesting outcome is the physical interpretation of the multi-layer parameters: they specify the corresponding multi-layer structure of turbulent boundary layer; when used together with simulation data, the SED-SL enables one to extract physical information from empirical data, and to understand the variation of the turbulent boundary layer.

Microgravity Geyser and Flow Field Prediction

NASA Technical Reports Server (NTRS)

Hochstein, J. I.; Marchetta, J. G.; Thornton, R. J.

2006-01-01

Modeling and prediction of flow fields and geyser formation in microgravity cryogenic propellant tanks was investigated. A computational simulation was used to reproduce the test matrix of experimental results performed by other investigators, as well as to model the flows in a larger tank. An underprediction of geyser height by the model led to a sensitivity study to determine if variations in surface tension coefficient, contact angle, or jet pipe turbulence significantly influence the simulations. It was determined that computational geyser height is not sensitive to slight variations in any of these items. An existing empirical correlation based on dimensionless parameters was re-examined in an effort to improve the accuracy of geyser prediction. This resulted in the proposal for a re-formulation of two dimensionless parameters used in the correlation; the non-dimensional geyser height and the Bond number. It was concluded that the new non-dimensional geyser height shows little promise. Although further data will be required to make a definite judgement, the reformulation of the Bond number provided correlations that are more accurate and appear to be more general than the previously established correlation.

Biomarker Surrogates Do Not Accurately Predict Sputum Eosinophils and Neutrophils in Asthma

PubMed Central

Hastie, Annette T.; Moore, Wendy C.; Li, Huashi; Rector, Brian M.; Ortega, Victor E.; Pascual, Rodolfo M.; Peters, Stephen P.; Meyers, Deborah A.; Bleecker, Eugene R.

2013-01-01

Background Sputum eosinophils (Eos) are a strong predictor of airway inflammation, exacerbations, and aid asthma management, whereas sputum neutrophils (Neu) indicate a different severe asthma phenotype, potentially less responsive to TH2-targeted therapy. Variables such as blood Eos, total IgE, fractional exhaled nitric oxide (FeNO) or FEV1% predicted, may predict airway Eos, while age, FEV1%predicted, or blood Neu may predict sputum Neu. Availability and ease of measurement are useful characteristics, but accuracy in predicting airway Eos and Neu, individually or combined, is not established. Objectives To determine whether blood Eos, FeNO, and IgE accurately predict sputum eosinophils, and age, FEV1% predicted, and blood Neu accurately predict sputum neutrophils (Neu). Methods Subjects in the Wake Forest Severe Asthma Research Program (N=328) were characterized by blood and sputum cells, healthcare utilization, lung function, FeNO, and IgE. Multiple analytical techniques were utilized. Results Despite significant association with sputum Eos, blood Eos, FeNO and total IgE did not accurately predict sputum Eos, and combinations of these variables failed to improve prediction. Age, FEV1%predicted and blood Neu were similarly unsatisfactory for prediction of sputum Neu. Factor analysis and stepwise selection found FeNO, IgE and FEV1% predicted, but not blood Eos, correctly predicted 69% of sputum Eospredicted 64% of sputum Neupredict both sputum Eos and Neu accurately assigned only 41% of samples. Conclusion Despite statistically significant associations FeNO, IgE, blood Eos and Neu, FEV1%predicted, and age are poor surrogates, separately and combined, for accurately predicting sputum eosinophils and neutrophils. PMID:23706399

Prediction of Flow Stress in Cadmium Using Constitutive Equation and Artificial Neural Network Approach

NASA Astrophysics Data System (ADS)

Sarkar, A.; Chakravartty, J. K.

2013-10-01

A model is developed to predict the constitutive flow behavior of cadmium during compression test using artificial neural network (ANN). The inputs of the neural network are strain, strain rate, and temperature, whereas flow stress is the output. Experimental data obtained from compression tests in the temperature range -30 to 70 °C, strain range 0.1 to 0.6, and strain rate range 10-3 to 1 s-1 are employed to develop the model. A three-layer feed-forward ANN is trained with Levenberg-Marquardt training algorithm. It has been shown that the developed ANN model can efficiently and accurately predict the deformation behavior of cadmium. This trained network could predict the flow stress better than a constitutive equation of the type.

A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

NASA Technical Reports Server (NTRS)

Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

1994-01-01

Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

PNS predictions for supersonic/hypersonic flows over finned missile configurations

NASA Technical Reports Server (NTRS)

Bhutta, Bilal A.; Lewis, Clark H.

1992-01-01

Finned missile design entails accurate and computationally fast numerical techniques for predicting viscous flows over complex lifting configurations at small to moderate angles of attack and over Mach 3 to 15; these flows are often characterized by strong embedded shocks, so that numerical algorithms are also required to capture embedded shocks. The recent real-gas Flux Vector Splitting technique is here extended to investigate the Mach 3 flow over a typical finned missile configuration with/without side fin deflections. Elliptic grid-generation techniques for Mach 15 flows are shown to be inadequate for Mach 3 flows over finned configurations and need to be modified. Fin-deflection studies indicate that even small amounts of missile fin deflection can substantially modify vehicle aerodynamics. This 3D parabolized Navier-Stokes scheme is also extended into an efficient embedded algorithm for studying small axially separated flow regions due to strong fin and control surface deflections.

Accurate Identification of Fear Facial Expressions Predicts Prosocial Behavior

PubMed Central

Marsh, Abigail A.; Kozak, Megan N.; Ambady, Nalini

2009-01-01

The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants’ ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale. PMID:17516803

Accurate identification of fear facial expressions predicts prosocial behavior.

PubMed

Marsh, Abigail A; Kozak, Megan N; Ambady, Nalini

2007-05-01

The fear facial expression is a distress cue that is associated with the provision of help and prosocial behavior. Prior psychiatric studies have found deficits in the recognition of this expression by individuals with antisocial tendencies. However, no prior study has shown accuracy for recognition of fear to predict actual prosocial or antisocial behavior in an experimental setting. In 3 studies, the authors tested the prediction that individuals who recognize fear more accurately will behave more prosocially. In Study 1, participants who identified fear more accurately also donated more money and time to a victim in a classic altruism paradigm. In Studies 2 and 3, participants' ability to identify the fear expression predicted prosocial behavior in a novel task designed to control for confounding variables. In Study 3, accuracy for recognizing fear proved a better predictor of prosocial behavior than gender, mood, or scores on an empathy scale.

An implicit higher-order spatially accurate scheme for solving time dependent flows on unstructured meshes

NASA Astrophysics Data System (ADS)

Tomaro, Robert F.

1998-07-01

The present research is aimed at developing a higher-order, spatially accurate scheme for both steady and unsteady flow simulations using unstructured meshes. The resulting scheme must work on a variety of general problems to ensure the creation of a flexible, reliable and accurate aerodynamic analysis tool. To calculate the flow around complex configurations, unstructured grids and the associated flow solvers have been developed. Efficient simulations require the minimum use of computer memory and computational times. Unstructured flow solvers typically require more computer memory than a structured flow solver due to the indirect addressing of the cells. The approach taken in the present research was to modify an existing three-dimensional unstructured flow solver to first decrease the computational time required for a solution and then to increase the spatial accuracy. The terms required to simulate flow involving non-stationary grids were also implemented. First, an implicit solution algorithm was implemented to replace the existing explicit procedure. Several test cases, including internal and external, inviscid and viscous, two-dimensional, three-dimensional and axi-symmetric problems, were simulated for comparison between the explicit and implicit solution procedures. The increased efficiency and robustness of modified code due to the implicit algorithm was demonstrated. Two unsteady test cases, a plunging airfoil and a wing undergoing bending and torsion, were simulated using the implicit algorithm modified to include the terms required for a moving and/or deforming grid. Secondly, a higher than second-order spatially accurate scheme was developed and implemented into the baseline code. Third- and fourth-order spatially accurate schemes were implemented and tested. The original dissipation was modified to include higher-order terms and modified near shock waves to limit pre- and post-shock oscillations. The unsteady cases were repeated using the higher

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Assessment of Geometry and In-Flow Effects on Contra-Rotating Open Rotor Broadband Noise Predictions

NASA Technical Reports Server (NTRS)

Zawodny, Nikolas S.; Nark, Douglas M.; Boyd, D. Douglas, Jr.

2015-01-01

Application of previously formulated semi-analytical models for the prediction of broadband noise due to turbulent rotor wake interactions and rotor blade trailing edges is performed on the historical baseline F31/A31 contra-rotating open rotor configuration. Simplified two-dimensional blade element analysis is performed on cambered NACA 4-digit airfoil profiles, which are meant to serve as substitutes for the actual rotor blade sectional geometries. Rotor in-flow effects such as induced axial and tangential velocities are incorporated into the noise prediction models based on supporting computational fluid dynamics (CFD) results and simplified in-flow velocity models. Emphasis is placed on the development of simplified rotor in-flow models for the purpose of performing accurate noise predictions independent of CFD information. The broadband predictions are found to compare favorably with experimental acoustic results.

Predicting the enhancement of mixing-driven reactions in nonuniform flows using measures of flow topology.

PubMed

Engdahl, Nicholas B; Benson, David A; Bolster, Diogo

2014-11-01

The ability for reactive constituents to mix is often the key limiting factor for the completion of reactions across a huge range of scales in a variety of media. In flowing systems, deformation and shear enhance mixing by bringing constituents into closer proximity, thus increasing reaction potential. Accurately quantifying this enhanced mixing is key to predicting reactions and typically is done by observing or simulating scalar transport. To eliminate this computationally expensive step, we use a Lagrangian stochastic framework to derive the enhancement to reaction potential by calculating the collocation probability of particle pairs in a heterogeneous flow field accounting for deformations. We relate the enhanced reaction potential to three well known flow topology metrics and demonstrate that it is best correlated to (and asymptotically linear with) one: the largest eigenvalue of the (right) Cauchy-Green tensor.

A conservative fully implicit algorithm for predicting slug flows

NASA Astrophysics Data System (ADS)

Krasnopolsky, Boris I.; Lukyanov, Alexander A.

2018-02-01

An accurate and predictive modelling of slug flows is required by many industries (e.g., oil and gas, nuclear engineering, chemical engineering) to prevent undesired events potentially leading to serious environmental accidents. For example, the hydrodynamic and terrain-induced slugging leads to unwanted unsteady flow conditions. This demands the development of fast and robust numerical techniques for predicting slug flows. The presented in this paper study proposes a multi-fluid model and its implementation method accounting for phase appearance and disappearance. The numerical modelling of phase appearance and disappearance presents a complex numerical challenge for all multi-component and multi-fluid models. Numerical challenges arise from the singular systems of equations when some phases are absent and from the solution discontinuity when some phases appear or disappear. This paper provides a flexible and robust solution to these issues. A fully implicit formulation described in this work enables to efficiently solve governing fluid flow equations. The proposed numerical method provides a modelling capability of phase appearance and disappearance processes, which is based on switching procedure between various sets of governing equations. These sets of equations are constructed using information about the number of phases present in the computational domain. The proposed scheme does not require an explicit truncation of solutions leading to a conservative scheme for mass and linear momentum. A transient two-fluid model is used to verify and validate the proposed algorithm for conditions of hydrodynamic and terrain-induced slug flow regimes. The developed modelling capabilities allow to predict all the major features of the experimental data, and are in a good quantitative agreement with them.

Coupling of rainfall-induced landslide triggering model with predictions of debris flow runout distances

NASA Astrophysics Data System (ADS)

Lehmann, Peter; von Ruette, Jonas; Fan, Linfeng; Or, Dani

2014-05-01

Rapid debris flows initiated by rainfall induced shallow landslides present a highly destructive natural hazard in steep terrain. The impact and run-out paths of debris flows depend on the volume, composition and initiation zone of released material and are requirements to make accurate debris flow predictions and hazard maps. For that purpose we couple the mechanistic 'Catchment-scale Hydro-mechanical Landslide Triggering (CHLT)' model to compute timing, location, and landslide volume with simple approaches to estimate debris flow runout distances. The runout models were tested using two landslide inventories obtained in the Swiss Alps following prolonged rainfall events. The predicted runout distances were in good agreement with observations, confirming the utility of such simple models for landscape scale estimates. In a next step debris flow paths were computed for landslides predicted with the CHLT model for a certain range of soil properties to explore its effect on runout distances. This combined approach offers a more complete spatial picture of shallow landslide and subsequent debris flow hazards. The additional information provided by CHLT model concerning location, shape, soil type and water content of the released mass may also be incorporated into more advanced models of runout to improve predictability and impact of such abruptly-released mass.

Can phenological models predict tree phenology accurately under climate change conditions?

NASA Astrophysics Data System (ADS)

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2014-05-01

The onset of the growing season of trees has been globally earlier by 2.3 days/decade during the last 50 years because of global warming and this trend is predicted to continue according to climate forecast. The effect of temperature on plant phenology is however not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud dormancy, and on the other hand higher temperatures are necessary to promote bud cells growth afterwards. Increasing phenological changes in temperate woody species have strong impacts on forest trees distribution and productivity, as well as crops cultivation areas. Accurate predictions of trees phenology are therefore a prerequisite to understand and foresee the impacts of climate change on forests and agrosystems. Different process-based models have been developed in the last two decades to predict the date of budburst or flowering of woody species. They are two main families: (1) one-phase models which consider only the ecodormancy phase and make the assumption that endodormancy is always broken before adequate climatic conditions for cell growth occur; and (2) two-phase models which consider both the endodormancy and ecodormancy phases and predict a date of dormancy break which varies from year to year. So far, one-phase models have been able to predict accurately tree bud break and flowering under historical climate. However, because they do not consider what happens prior to ecodormancy, and especially the possible negative effect of winter temperature warming on dormancy break, it seems unlikely that they can provide accurate predictions in future climate conditions. It is indeed well known that a lack of low temperature results in abnormal pattern of bud break and development in temperate fruit trees. An accurate modelling of the dormancy break date has thus become a major issue in phenology modelling. Two-phases phenological models predict that global warming should delay

Comparison of PIV with 4D-Flow in a physiological accurate flow phantom

NASA Astrophysics Data System (ADS)

Sansom, Kurt; Balu, Niranjan; Liu, Haining; Aliseda, Alberto; Yuan, Chun; Canton, Maria De Gador

2016-11-01

Validation of 4D MRI flow sequences with planar particle image velocimetry (PIV) is performed in a physiologically-accurate flow phantom. A patient-specific phantom of a carotid artery is connected to a pulsatile flow loop to simulate the 3D unsteady flow in the cardiovascular anatomy. Cardiac-cycle synchronized MRI provides time-resolved 3D blood velocity measurements in clinical tool that is promising but lacks a robust validation framework. PIV at three different Reynolds numbers (540, 680, and 815, chosen based on +/- 20 % of the average velocity from the patient-specific CCA waveform) and four different Womersley numbers (3.30, 3.68, 4.03, and 4.35, chosen to reflect a physiological range of heart rates) are compared to 4D-MRI measurements. An accuracy assessment of raw velocity measurements and a comparison of estimated and measureable flow parameters such as wall shear stress, fluctuating velocity rms, and Lagrangian particle residence time, will be presented, with justification for their biomechanics relevance to the pathophysiology of arterial disease: atherosclerosis and intimal hyperplasia. Lastly, the framework is applied to a new 4D-Flow MRI sequence and post processing techniques to provide a quantitative assessment with the benchmarked data. Department of Education GAANN Fellowship.

ASTRAL, DRAGON and SEDAN scores predict stroke outcome more accurately than physicians.

PubMed

Ntaios, G; Gioulekas, F; Papavasileiou, V; Strbian, D; Michel, P

2016-11-01

ASTRAL, SEDAN and DRAGON scores are three well-validated scores for stroke outcome prediction. Whether these scores predict stroke outcome more accurately compared with physicians interested in stroke was investigated. Physicians interested in stroke were invited to an online anonymous survey to provide outcome estimates in randomly allocated structured scenarios of recent real-life stroke patients. Their estimates were compared to scores' predictions in the same scenarios. An estimate was considered accurate if it was within 95% confidence intervals of actual outcome. In all, 244 participants from 32 different countries responded assessing 720 real scenarios and 2636 outcomes. The majority of physicians' estimates were inaccurate (1422/2636, 53.9%). 400 (56.8%) of physicians' estimates about the percentage probability of 3-month modified Rankin score (mRS) > 2 were accurate compared with 609 (86.5%) of ASTRAL score estimates (P < 0.0001). 394 (61.2%) of physicians' estimates about the percentage probability of post-thrombolysis symptomatic intracranial haemorrhage were accurate compared with 583 (90.5%) of SEDAN score estimates (P < 0.0001). 160 (24.8%) of physicians' estimates about post-thrombolysis 3-month percentage probability of mRS 0-2 were accurate compared with 240 (37.3%) DRAGON score estimates (P < 0.0001). 260 (40.4%) of physicians' estimates about the percentage probability of post-thrombolysis mRS 5-6 were accurate compared with 518 (80.4%) DRAGON score estimates (P < 0.0001). ASTRAL, DRAGON and SEDAN scores predict outcome of acute ischaemic stroke patients with higher accuracy compared to physicians interested in stroke. © 2016 EAN.

Field-scale Prediction of Enhanced DNAPL Dissolution Using Partitioning Tracers and Flow Pattern Effects

NASA Astrophysics Data System (ADS)

Wang, F.; Annable, M. D.; Jawitz, J. W.

2012-12-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a PCE-contaminated dry cleaner site, located in Jacksonville, Florida. The EST is an analytical solution with field-measurable input parameters. Here, measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ alcohol (ethanol) flood. In addition, a simulated partitioning tracer test from a calibrated spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The ethanol prediction based on both the field partitioning tracer test and the UTCHEM tracer test simulation closely matched the field data. The PCE EST prediction showed a peak shift to an earlier arrival time that was concluded to be caused by well screen interval differences between the field tracer test and alcohol flood. This observation was based on a modeling assessment of potential factors that may influence predictions by using UTCHEM simulations. The imposed injection and pumping flow pattern at this site for both the partitioning tracer test and alcohol flood was more complex than the natural gradient flow pattern (NGFP). Both the EST model and UTCHEM were also used to predict PCE dissolution under natural gradient conditions, with much simpler flow patterns than the forced-gradient double five spot of the alcohol flood. The NGFP predictions based on parameters determined from tracer tests conducted with complex flow patterns underestimated PCE concentrations and total mass removal. This suggests that the flow patterns influence aqueous dissolution and that the aqueous dissolution under the NGFP is more efficient than dissolution under complex flow patterns.

Accurate and efficient calculation of response times for groundwater flow

NASA Astrophysics Data System (ADS)

Carr, Elliot J.; Simpson, Matthew J.

2018-03-01

We study measures of the amount of time required for transient flow in heterogeneous porous media to effectively reach steady state, also known as the response time. Here, we develop a new approach that extends the concept of mean action time. Previous applications of the theory of mean action time to estimate the response time use the first two central moments of the probability density function associated with the transition from the initial condition, at t = 0, to the steady state condition that arises in the long time limit, as t → ∞ . This previous approach leads to a computationally convenient estimation of the response time, but the accuracy can be poor. Here, we outline a powerful extension using the first k raw moments, showing how to produce an extremely accurate estimate by making use of asymptotic properties of the cumulative distribution function. Results are validated using an existing laboratory-scale data set describing flow in a homogeneous porous medium. In addition, we demonstrate how the results also apply to flow in heterogeneous porous media. Overall, the new method is: (i) extremely accurate; and (ii) computationally inexpensive. In fact, the computational cost of the new method is orders of magnitude less than the computational effort required to study the response time by solving the transient flow equation. Furthermore, the approach provides a rigorous mathematical connection with the heuristic argument that the response time for flow in a homogeneous porous medium is proportional to L2 / D , where L is a relevant length scale, and D is the aquifer diffusivity. Here, we extend such heuristic arguments by providing a clear mathematical definition of the proportionality constant.

Calculations of steady and transient channel flows with a time-accurate L-U factorization scheme

NASA Technical Reports Server (NTRS)

Kim, S.-W.

1991-01-01

Calculations of steady and unsteady, transonic, turbulent channel flows with a time accurate, lower-upper (L-U) factorization scheme are presented. The L-U factorization scheme is formally second-order accurate in time and space, and it is an extension of the steady state flow solver (RPLUS) used extensively to solve compressible flows. A time discretization method and the implementation of a consistent boundary condition specific to the L-U factorization scheme are also presented. The turbulence is described by the Baldwin-Lomax algebraic turbulence model. The present L-U scheme yields stable numerical results with the use of much smaller artificial dissipations than those used in the previous steady flow solver for steady and unsteady channel flows. The capability to solve time dependent flows is shown by solving very weakly excited and strongly excited, forced oscillatory, channel flows.

Prediction of rarefied micro-nozzle flows using the SPARTA library

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Grot, Jonathan

2016-11-01

The accurate numerical prediction of gas flows within micro-nozzles can help evaluate the performance and enable the design of optimal configurations for micro-propulsion systems. Viscous effects within the large boundary layers can have a strong impact on the nozzle performance. Furthermore, the variation in collision length scales from continuum to rarefied preclude the use of continuum-based computational fluid dynamics. In this paper, we describe the application of a massively parallel direct simulation Monte Carlo (DSMC) library to predict the steady-state and transient flow through a micro-nozzle. The nozzle's geometric configuration is described in a highly flexible manner to allow for the modification of the geometry in a systematic fashion. The transient simulation highlights a strong shock structure that forms within the converging portion of the nozzle when the expanded gas interacts with the nozzle walls. This structure has a strong impact on the buildup of the gas in the nozzle and affects the boundary layer thickness beyond the throat in the diverging section of the nozzle. Future work will look to examine the transient thrust and integrate this simulation capability into a web-based rarefied gas dynamics prediction software, which is currently under development.

CUFID-query: accurate network querying through random walk based network flow estimation.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive

A time-accurate algorithm for chemical non-equilibrium viscous flows at all speeds

NASA Technical Reports Server (NTRS)

Shuen, J.-S.; Chen, K.-H.; Choi, Y.

1992-01-01

A time-accurate, coupled solution procedure is described for the chemical nonequilibrium Navier-Stokes equations over a wide range of Mach numbers. This method employs the strong conservation form of the governing equations, but uses primitive variables as unknowns. Real gas properties and equilibrium chemistry are considered. Numerical tests include steady convergent-divergent nozzle flows with air dissociation/recombination chemistry, dump combustor flows with n-pentane-air chemistry, nonreacting flow in a model double annular combustor, and nonreacting unsteady driven cavity flows. Numerical results for both the steady and unsteady flows demonstrate the efficiency and robustness of the present algorithm for Mach numbers ranging from the incompressible limit to supersonic speeds.

Predicting Peak Flows following Forest Fires

NASA Astrophysics Data System (ADS)

Elliot, William J.; Miller, Mary Ellen; Dobre, Mariana

2016-04-01

Following forest fires, peak flows in perennial and ephemeral streams often increase by a factor of 10 or more. This increase in peak flow rate may overwhelm existing downstream structures, such as road culverts, causing serious damage to road fills at stream crossings. In order to predict peak flow rates following wildfires, we have applied two different tools. One is based on the U.S.D.A Natural Resource Conservation Service Curve Number Method (CN), and the other is by applying the Water Erosion Prediction Project (WEPP) to the watershed. In our presentation, we will describe the science behind the two methods, and present the main variables for each model. We will then provide an example of a comparison of the two methods to a fire-prone watershed upstream of the City of Flagstaff, Arizona, USA, where a fire spread model was applied for current fuel loads, and for likely fuel loads following a fuel reduction treatment. When applying the curve number method, determining the time to peak flow can be problematic for low severity fires because the runoff flow paths are both surface and through shallow lateral flow. The WEPP watershed version incorporates shallow lateral flow into stream channels. However, the version of the WEPP model that was used for this study did not have channel routing capabilities, but rather relied on regression relationships to estimate peak flows from individual hillslope polygon peak runoff rates. We found that the two methods gave similar results if applied correctly, with the WEPP predictions somewhat greater than the CN predictions. Later releases of the WEPP model have incorporated alternative methods for routing peak flows that need to be evaluated.

Invited article: Time accurate mass flow measurements of solid-fueled systems.

PubMed

Olliges, Jordan D; Lilly, Taylor C; Joslyn, Thomas B; Ketsdever, Andrew D

2008-10-01

A novel diagnostic method is described that utilizes a thrust stand mass balance (TSMB) to directly measure time-accurate mass flow from a solid-fuel thruster. The accuracy of the TSMB mass flow measurement technique was demonstrated in three ways including the use of an idealized numerical simulation, verifying a fluid mass calibration with high-speed digital photography, and by measuring mass loss in more than 30 hybrid rocket motor firings. Dynamic response of the mass balance was assessed through weight calibration and used to derive spring, damping, and mass moment of inertia coefficients for the TSMB. These dynamic coefficients were used to determine the mass flow rate and total mass loss within an acrylic and gaseous oxygen hybrid rocket motor firing. Intentional variations in the oxygen flow rate resulted in corresponding variations in the total propellant mass flow as expected. The TSMB was optimized to determine mass losses of up to 2.5 g and measured total mass loss to within 2.5% of that calculated by a NIST-calibrated digital scale. Using this method, a mass flow resolution of 0.0011 g/s or 2% of the average mass flow in this study has been achieved.

Invited Article: Time accurate mass flow measurements of solid-fueled systems

NASA Astrophysics Data System (ADS)

Olliges, Jordan D.; Lilly, Taylor C.; Joslyn, Thomas B.; Ketsdever, Andrew D.

2008-10-01

A novel diagnostic method is described that utilizes a thrust stand mass balance (TSMB) to directly measure time-accurate mass flow from a solid-fuel thruster. The accuracy of the TSMB mass flow measurement technique was demonstrated in three ways including the use of an idealized numerical simulation, verifying a fluid mass calibration with high-speed digital photography, and by measuring mass loss in more than 30 hybrid rocket motor firings. Dynamic response of the mass balance was assessed through weight calibration and used to derive spring, damping, and mass moment of inertia coefficients for the TSMB. These dynamic coefficients were used to determine the mass flow rate and total mass loss within an acrylic and gaseous oxygen hybrid rocket motor firing. Intentional variations in the oxygen flow rate resulted in corresponding variations in the total propellant mass flow as expected. The TSMB was optimized to determine mass losses of up to 2.5 g and measured total mass loss to within 2.5% of that calculated by a NIST-calibrated digital scale. Using this method, a mass flow resolution of 0.0011 g/s or 2% of the average mass flow in this study has been achieved.

Accurate Prediction of Motor Failures by Application of Multi CBM Tools: A Case Study

NASA Astrophysics Data System (ADS)

Dutta, Rana; Singh, Veerendra Pratap; Dwivedi, Jai Prakash

2018-02-01

Motor failures are very difficult to predict accurately with a single condition-monitoring tool as both electrical and the mechanical systems are closely related. Electrical problem, like phase unbalance, stator winding insulation failures can, at times, lead to vibration problem and at the same time mechanical failures like bearing failure, leads to rotor eccentricity. In this case study of a 550 kW blower motor it has been shown that a rotor bar crack was detected by current signature analysis and vibration monitoring confirmed the same. In later months in a similar motor vibration monitoring predicted bearing failure and current signature analysis confirmed the same. In both the cases, after dismantling the motor, the predictions were found to be accurate. In this paper we will be discussing the accurate predictions of motor failures through use of multi condition monitoring tools with two case studies.

Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

PubMed

Nielsen, Karina; Cleal, Bryan

2010-04-01

Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work. Copyright 2010 APA, all rights reserved.

A Numerical Analysis on the Effects of Self-Excited Tip Flow Unsteadiness and Upstream Blade Row Interactions on the Performance Predictions of a Transonic Compressor

NASA Astrophysics Data System (ADS)

Heberling, Brian

Computational fluid dynamics (CFD) simulations can offer a detailed view of the complex flow fields within an axial compressor and greatly aid the design process. However, the desire for quick turnaround times raises the question of how exact the model must be. At design conditions, steady CFD simulating an isolated blade row can accurately predict the performance of a rotor. However, as a compressor is throttled and mass flow rate decreased, axial flow becomes weaker making the capturing of unsteadiness, wakes, or other flow features more important. The unsteadiness of the tip clearance flow and upstream blade wake can have a significant impact on a rotor. At off-design conditions, time-accurate simulations or modeling multiple blade rows can become necessary in order to receive accurate performance predictions. Unsteady and multi- bladerow simulations are computationally expensive, especially when used in conjunction. It is important to understand which features are important to model in order to accurately capture a compressor's performance. CFD simulations of a transonic axial compressor throttling from the design point to stall are presented. The importance of capturing the unsteadiness of the rotor tip clearance flow versus capturing upstream blade-row interactions is examined through steady and unsteady, single- and multi-bladerow computations. It is shown that there are significant differences at near stall conditions between the different types of simulations.

High resolution flow field prediction for tail rotor aeroacoustics

NASA Technical Reports Server (NTRS)

Quackenbush, Todd R.; Bliss, Donald B.

1989-01-01

The prediction of tail rotor noise due to the impingement of the main rotor wake poses a significant challenge to current analysis methods in rotorcraft aeroacoustics. This paper describes the development of a new treatment of the tail rotor aerodynamic environment that permits highly accurate resolution of the incident flow field with modest computational effort relative to alternative models. The new approach incorporates an advanced full-span free wake model of the main rotor in a scheme which reconstructs high-resolution flow solutions from preliminary, computationally inexpensive simulations with coarse resolution. The heart of the approach is a novel method for using local velocity correction terms to capture the steep velocity gradients characteristic of the vortex-dominated incident flow. Sample calculations have been undertaken to examine the principal types of interactions between the tail rotor and the main rotor wake and to examine the performance of the new method. The results of these sample problems confirm the success of this approach in capturing the high-resolution flows necessary for analysis of rotor-wake/rotor interactions with dramatically reduced computational cost. Computations of radiated sound are also carried out that explore the role of various portions of the main rotor wake in generating tail rotor noise.

Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer

NASA Astrophysics Data System (ADS)

Hadjiiski, Lubomir; Chan, Heang-Ping; Cha, Kenny H.; Srinivasan, Ashok; Wei, Jun; Zhou, Chuan; Prince, Mark; Papagerakis, Silvana

2017-03-01

Accurate tumor progression prediction for oropharyngeal cancers is crucial for identifying patients who would best be treated with optimized treatment and therefore minimize the risk of under- or over-treatment. An objective decision support system that can merge the available radiomics, histopathologic and molecular biomarkers in a predictive model based on statistical outcomes of previous cases and machine learning may assist clinicians in making more accurate assessment of oropharyngeal tumor progression. In this study, we evaluated the feasibility of developing individual and combined predictive models based on quantitative image analysis from radiomics, histopathology and molecular biomarkers for oropharyngeal tumor progression prediction. With IRB approval, 31, 84, and 127 patients with head and neck CT (CT-HN), tumor tissue microarrays (TMAs) and molecular biomarker expressions, respectively, were collected. For 8 of the patients all 3 types of biomarkers were available and they were sequestered in a test set. The CT-HN lesions were automatically segmented using our level sets based method. Morphological, texture and molecular based features were extracted from CT-HN and TMA images, and selected features were merged by a neural network. The classification accuracy was quantified using the area under the ROC curve (AUC). Test AUCs of 0.87, 0.74, and 0.71 were obtained with the individual predictive models based on radiomics, histopathologic, and molecular features, respectively. Combining the radiomics and molecular models increased the test AUC to 0.90. Combining all 3 models increased the test AUC further to 0.94. This preliminary study demonstrates that the individual domains of biomarkers are useful and the integrated multi-domain approach is most promising for tumor progression prediction.

Flow of variably fluidized granular masses across three-dimensional terrain 2. Numerical predictions and experimental tests

USGS Publications Warehouse

Denlinger, R.P.; Iverson, R.M.

2001-01-01

Numerical solutions of the equations describing flow of variably fluidized Coulomb mixtures predict key features of dry granular avalanches and water-saturated debris flows measured in physical experiments. These features include time-dependent speeds, depths, and widths of flows as well as the geometry of resulting deposits. Threedimensional (3-D) boundary surfaces strongly influence flow dynamics because transverse shearing and cross-stream momentum transport occur where topography obstructs or redirects motion. Consequent energy dissipation can cause local deceleration and deposition, even on steep slopes. Velocities of surge fronts and other discontinuities that develop as flows cross 3-D terrain are predicted accurately by using a Riemann solution algorithm. The algorithm employs a gravity wave speed that accounts for different intensities of lateral stress transfer in regions of extending and compressing flow and in regions with different degrees of fluidization. Field observations and experiments indicate that flows in which fluid plays a significant role typically have high-friction margins with weaker interiors partly fluidized by pore pressure. Interaction of the strong perimeter and weak interior produces relatively steep-sided, flat-topped deposits. To simulate these effects, we compute pore pressure distributions using an advection-diffusion model with enhanced diffusivity near flow margins. Although challenges remain in evaluating pore pressure distributions in diverse geophysical flows, Riemann solutions of the depthaveraged 3-D Coulomb mixture equations provide a powerful tool for interpreting and predicting flow behavior. They provide a means of modeling debris flows, rock avalanches, pyroclastic flows, and related phenomena without invoking and calibrating Theological parameters that have questionable physical significance.

Numerical prediction of turbulent oscillating flow and associated heat transfer

NASA Technical Reports Server (NTRS)

Koehler, W. J.; Patankar, S. V.; Ibele, W. E.

1991-01-01

A crucial point for further development of engines is the optimization of its heat exchangers which operate under oscillatory flow conditions. It has been found that the most important thermodynamic uncertainties in the Stirling engine designs for space power are in the heat transfer between gas and metal in all engine components and in the pressure drop across the heat exchanger components. So far, performance codes cannot predict the power output of a Stirling engine reasonably enough if used for a wide variety of engines. Thus, there is a strong need for better performance codes. However, a performance code is not concerned with the details of the flow. This information must be provided externally. While analytical relationships exist for laminar oscillating flow, there has been hardly any information about transitional and turbulent oscillating flow, which could be introduced into the performance codes. In 1986, a survey by Seume and Simon revealed that most Stirling engine heat exchangers operate in the transitional and turbulent regime. Consequently, research has since focused on the unresolved issue of transitional and turbulent oscillating flow and heat transfer. Since 1988, the University of Minnesota oscillating flow facility has obtained experimental data about transitional and turbulent oscillating flow. However, since the experiments in this field are extremely difficult, lengthy, and expensive, it is advantageous to numerically simulate the flow and heat transfer accurately from first principles. Work done at the University of Minnesota on the development of such a numerical simulation is summarized.

SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

PubMed

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-05-01

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

PubMed Central

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-01-01

Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of

Sensory prediction on a whiskered robot: a tactile analogy to "optical flow".

PubMed

Schroeder, Christopher L; Hartmann, Mitra J Z

2012-01-01

When an animal moves an array of sensors (e.g., the hand, the eye) through the environment, spatial and temporal gradients of sensory data are related by the velocity of the moving sensory array. In vision, the relationship between spatial and temporal brightness gradients is quantified in the "optical flow" equation. In the present work, we suggest an analog to optical flow for the rodent vibrissal (whisker) array, in which the perceptual intensity that "flows" over the array is bending moment. Changes in bending moment are directly related to radial object distance, defined as the distance between the base of a whisker and the point of contact with the object. Using both simulations and a 1×5 array (row) of artificial whiskers, we demonstrate that local object curvature can be estimated based on differences in radial distance across the array. We then develop two algorithms, both based on tactile flow, to predict the future contact points that will be obtained as the whisker array translates along the object. The translation of the robotic whisker array represents the rat's head velocity. The first algorithm uses a calculation of the local object slope, while the second uses a calculation of the local object curvature. Both algorithms successfully predict future contact points for simple surfaces. The algorithm based on curvature was found to more accurately predict future contact points as surfaces became more irregular. We quantify the inter-related effects of whisker spacing and the object's spatial frequencies, and examine the issues that arise in the presence of real-world noise, friction, and slip.

A Semi-implicit Method for Time Accurate Simulation of Compressible Flow

NASA Astrophysics Data System (ADS)

Wall, Clifton; Pierce, Charles D.; Moin, Parviz

2001-11-01

A semi-implicit method for time accurate simulation of compressible flow is presented. The method avoids the acoustic CFL limitation, allowing a time step restricted only by the convective velocity. Centered discretization in both time and space allows the method to achieve zero artificial attenuation of acoustic waves. The method is an extension of the standard low Mach number pressure correction method to the compressible Navier-Stokes equations, and the main feature of the method is the solution of a Helmholtz type pressure correction equation similar to that of Demirdžić et al. (Int. J. Num. Meth. Fluids, Vol. 16, pp. 1029-1050, 1993). The method is attractive for simulation of acoustic combustion instabilities in practical combustors. In these flows, the Mach number is low; therefore the time step allowed by the convective CFL limitation is significantly larger than that allowed by the acoustic CFL limitation, resulting in significant efficiency gains. Also, the method's property of zero artificial attenuation of acoustic waves is important for accurate simulation of the interaction between acoustic waves and the combustion process. The method has been implemented in a large eddy simulation code, and results from several test cases will be presented.

Improving a prediction system for oil spills in the Yellow Sea: effect of tides on subtidal flow.

PubMed

Kim, Chang-Sin; Cho, Yang-Ki; Choi, Byoung-Ju; Jung, Kyung Tae; You, Sung Hyup

2013-03-15

A multi-nested prediction system for the Yellow Sea using drifter trajectory simulations was developed to predict the movements of an oil spill after the MV Hebei Spirit accident. The speeds of the oil spill trajectories predicted by the model without tidal forcing were substantially faster than the observations; however, predictions taking into account the tides, including both tidal cycle and subtidal periods, were satisfactorily improved. Subtidal flow in the simulation without tides was stronger than in that with tides because of reduced frictional effects. Friction induced by tidal stress decelerated the southward subtidal flows driven by northwesterly winter winds along the Korean coast of the Yellow Sea. These results strongly suggest that in order to produce accurate predictions of oil spill trajectories, simulations must include tidal effects, such as variations within a tidal cycle and advections over longer time scales in tide-dominated areas. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Numerical flow simulation and efficiency prediction for axial turbines by advanced turbulence models

NASA Astrophysics Data System (ADS)

Jošt, D.; Škerlavaj, A.; Lipej, A.

2012-11-01

Numerical prediction of an efficiency of a 6-blade Kaplan turbine is presented. At first, the results of steady state analysis performed by different turbulence models for different operating regimes are compared to the measurements. For small and optimal angles of runner blades the efficiency was quite accurately predicted, but for maximal blade angle the discrepancy between calculated and measured values was quite large. By transient analysis, especially when the Scale Adaptive Simulation Shear Stress Transport (SAS SST) model with zonal Large Eddy Simulation (ZLES) in the draft tube was used, the efficiency was significantly improved. The improvement was at all operating points, but it was the largest for maximal discharge. The reason was better flow simulation in the draft tube. Details about turbulent structure in the draft tube obtained by SST, SAS SST and SAS SST with ZLES are illustrated in order to explain the reasons for differences in flow energy losses obtained by different turbulence models.

Assessment of an Unstructured-Grid Method for Predicting 3-D Turbulent Viscous Flows

NASA Technical Reports Server (NTRS)

Frink, Neal T.

1996-01-01

A method Is presented for solving turbulent flow problems on three-dimensional unstructured grids. Spatial discretization Is accomplished by a cell-centered finite-volume formulation using an accurate lin- ear reconstruction scheme and upwind flux differencing. Time is advanced by an implicit backward- Euler time-stepping scheme. Flow turbulence effects are modeled by the Spalart-Allmaras one-equation model, which is coupled with a wall function to reduce the number of cells in the sublayer region of the boundary layer. A systematic assessment of the method is presented to devise guidelines for more strategic application of the technology to complex problems. The assessment includes the accuracy In predictions of skin-friction coefficient, law-of-the-wall behavior, and surface pressure for a flat-plate turbulent boundary layer, and for the ONERA M6 wing under a high Reynolds number, transonic, separated flow condition.

Assessment of an Unstructured-Grid Method for Predicting 3-D Turbulent Viscous Flows

NASA Technical Reports Server (NTRS)

Frink, Neal T.

1996-01-01

A method is presented for solving turbulent flow problems on three-dimensional unstructured grids. Spatial discretization is accomplished by a cell-centered finite-volume formulation using an accurate linear reconstruction scheme and upwind flux differencing. Time is advanced by an implicit backward-Euler time-stepping scheme. Flow turbulence effects are modeled by the Spalart-Allmaras one-equation model, which is coupled with a wall function to reduce the number of cells in the sublayer region of the boundary layer. A systematic assessment of the method is presented to devise guidelines for more strategic application of the technology to complex problems. The assessment includes the accuracy in predictions of skin-friction coefficient, law-of-the-wall behavior, and surface pressure for a flat-plate turbulent boundary layer, and for the ONERA M6 wing under a high Reynolds number, transonic, separated flow condition.

PredictSNP: Robust and Accurate Consensus Classifier for Prediction of Disease-Related Mutations

PubMed Central

Bendl, Jaroslav; Stourac, Jan; Salanda, Ondrej; Pavelka, Antonin; Wieben, Eric D.; Zendulka, Jaroslav; Brezovsky, Jan; Damborsky, Jiri

2014-01-01

Single nucleotide variants represent a prevalent form of genetic variation. Mutations in the coding regions are frequently associated with the development of various genetic diseases. Computational tools for the prediction of the effects of mutations on protein function are very important for analysis of single nucleotide variants and their prioritization for experimental characterization. Many computational tools are already widely employed for this purpose. Unfortunately, their comparison and further improvement is hindered by large overlaps between the training datasets and benchmark datasets, which lead to biased and overly optimistic reported performances. In this study, we have constructed three independent datasets by removing all duplicities, inconsistencies and mutations previously used in the training of evaluated tools. The benchmark dataset containing over 43,000 mutations was employed for the unbiased evaluation of eight established prediction tools: MAPP, nsSNPAnalyzer, PANTHER, PhD-SNP, PolyPhen-1, PolyPhen-2, SIFT and SNAP. The six best performing tools were combined into a consensus classifier PredictSNP, resulting into significantly improved prediction performance, and at the same time returned results for all mutations, confirming that consensus prediction represents an accurate and robust alternative to the predictions delivered by individual tools. A user-friendly web interface enables easy access to all eight prediction tools, the consensus classifier PredictSNP and annotations from the Protein Mutant Database and the UniProt database. The web server and the datasets are freely available to the academic community at http://loschmidt.chemi.muni.cz/predictsnp. PMID:24453961

Free surface profiles in river flows: Can standard energy-based gradually-varied flow computations be pursued?

NASA Astrophysics Data System (ADS)

Cantero, Francisco; Castro-Orgaz, Oscar; Garcia-Marín, Amanda; Ayuso, José Luis; Dey, Subhasish

2015-10-01

Is the energy equation for gradually-varied flow the best approximation for the free surface profile computations in river flows? Determination of flood inundation in rivers and natural waterways is based on the hydraulic computation of flow profiles. This is usually done using energy-based gradually-varied flow models, like HEC-RAS, that adopts a vertical division method for discharge prediction in compound channel sections. However, this discharge prediction method is not so accurate in the context of advancements over the last three decades. This paper firstly presents a study of the impact of discharge prediction on the gradually-varied flow computations by comparing thirteen different methods for compound channels, where both energy and momentum equations are applied. The discharge, velocity distribution coefficients, specific energy, momentum and flow profiles are determined. After the study of gradually-varied flow predictions, a new theory is developed to produce higher-order energy and momentum equations for rapidly-varied flow in compound channels. These generalized equations enable to describe the flow profiles with more generality than the gradually-varied flow computations. As an outcome, results of gradually-varied flow provide realistic conclusions for computations of flow in compound channels, showing that momentum-based models are in general more accurate; whereas the new theory developed for rapidly-varied flow opens a new research direction, so far not investigated in flows through compound channels.

Heart rate during basketball game play and volleyball drills accurately predicts oxygen uptake and energy expenditure.

PubMed

Scribbans, T D; Berg, K; Narazaki, K; Janssen, I; Gurd, B J

2015-09-01

There is currently little information regarding the ability of metabolic prediction equations to accurately predict oxygen uptake and exercise intensity from heart rate (HR) during intermittent sport. The purpose of the present study was to develop and, cross-validate equations appropriate for accurately predicting oxygen cost (VO2) and energy expenditure from HR during intermittent sport participation. Eleven healthy adult males (19.9±1.1yrs) were recruited to establish the relationship between %VO2peak and %HRmax during low-intensity steady state endurance (END), moderate-intensity interval (MOD) and high intensity-interval exercise (HI), as performed on a cycle ergometer. Three equations (END, MOD, and HI) for predicting %VO2peak based on %HRmax were developed. HR and VO2 were directly measured during basketball games (6 male, 20.8±1.0 yrs; 6 female, 20.0±1.3yrs) and volleyball drills (12 female; 20.8±1.0yrs). Comparisons were made between measured and predicted VO2 and energy expenditure using the 3 equations developed and 2 previously published equations. The END and MOD equations accurately predicted VO2 and energy expenditure, while the HI equation underestimated, and the previously published equations systematically overestimated VO2 and energy expenditure. Intermittent sport VO2 and energy expenditure can be accurately predicted from heart rate data using either the END (%VO2peak=%HRmax x 1.008-17.17) or MOD (%VO2peak=%HRmax x 1.2-32) equations. These 2 simple equations provide an accessible and cost-effective method for accurate estimation of exercise intensity and energy expenditure during intermittent sport.

Assessment and prediction of debris-flow hazards

USGS Publications Warehouse

Wieczorek, Gerald F.; ,

1993-01-01

Study of debris-flow geomorphology and initiation mechanism has led to better understanding of debris-flow processes. This paper reviews how this understanding is used in current techniques for assessment and prediction of debris-flow hazards.

Flow prediction over a transport multi-element high-lift system and comparison with flight measurements

NASA Technical Reports Server (NTRS)

Vijgen, P. M. H. W.; Hardin, J. D.; Yip, L. P.

1992-01-01

Accurate prediction of surface-pressure distributions, merging boundary-layers, and separated-flow regions over multi-element high-lift airfoils is required to design advanced high-lift systems for efficient subsonic transport aircraft. The availability of detailed measurements of pressure distributions and both averaged and time-dependent boundary-layer flow parameters at flight Reynolds numbers is critical to evaluate computational methods and to model the turbulence structure for closure of the flow equations. Several detailed wind-tunnel measurements at subscale Reynolds numbers were conducted to obtain detailed flow information including the Reynolds-stress component. As part of a subsonic-transport high-lift research program, flight experiments are conducted using the NASA-Langley B737-100 research aircraft to obtain detailed flow characteristics for support of computational and wind-tunnel efforts. Planned flight measurements include pressure distributions at several spanwise locations, boundary-layer transition and separation locations, surface skin friction, as well as boundary-layer profiles and Reynolds stresses in adverse pressure-gradient flow.

Quasi-laminar stability and sensitivity analyses for turbulent flows: Prediction of low-frequency unsteadiness and passive control

NASA Astrophysics Data System (ADS)

Mettot, Clément; Sipp, Denis; Bézard, Hervé

2014-04-01

This article presents a quasi-laminar stability approach to identify in high-Reynolds number flows the dominant low-frequencies and to design passive control means to shift these frequencies. The approach is based on a global linear stability analysis of mean-flows, which correspond to the time-average of the unsteady flows. Contrary to the previous work by Meliga et al. ["Sensitivity of 2-D turbulent flow past a D-shaped cylinder using global stability," Phys. Fluids 24, 061701 (2012)], we use the linearized Navier-Stokes equations based solely on the molecular viscosity (leaving aside any turbulence model and any eddy viscosity) to extract the least stable direct and adjoint global modes of the flow. Then, we compute the frequency sensitivity maps of these modes, so as to predict before hand where a small control cylinder optimally shifts the frequency of the flow. In the case of the D-shaped cylinder studied by Parezanović and Cadot [J. Fluid Mech. 693, 115 (2012)], we show that the present approach well captures the frequency of the flow and recovers accurately the frequency control maps obtained experimentally. The results are close to those already obtained by Meliga et al., who used a more complex approach in which turbulence models played a central role. The present approach is simpler and may be applied to a broader range of flows since it is tractable as soon as mean-flows — which can be obtained either numerically from simulations (Direct Numerical Simulation (DNS), Large Eddy Simulation (LES), unsteady Reynolds-Averaged-Navier-Stokes (RANS), steady RANS) or from experimental measurements (Particle Image Velocimetry - PIV) — are available. We also discuss how the influence of the control cylinder on the mean-flow may be more accurately predicted by determining an eddy-viscosity from numerical simulations or experimental measurements. From a technical point of view, we finally show how an existing compressible numerical simulation code may be used in

Numerical Investigation on the Effects of Self-Excited Tip Flow Unsteadiness and Blade Row Interactions on the Performance Predictions of Low Speed and Transonic Compressor Rotors

NASA Astrophysics Data System (ADS)

Lee, Daniel H.

The impact blade row interactions can have on the performance of compressor rotors has been well documented. It is also well known that rotor tip clearance flows can have a large effect on compressor performance and stall margin and recent research has shown that tip leakage flows can exhibit self-excited unsteadiness at near stall conditions. However, the impact of tip leakage flow on the performance and operating range of a compressor rotor, relative to other important flow features such as upstream stator wakes or downstream potential effects, has not been explored. To this end, a numerical investigation has been conducted to determine the effects of self-excited tip flow unsteadiness, upstream stator wakes, and downstream blade row interactions on the performance prediction of low speed and transonic compressor rotors. Calculations included a single blade-row rotor configuration as well as two multi-blade row configurations: one where the rotor was modeled with an upstream stator and a second where the rotor was modeled with a downstream stator. Steady-state and time accurate calculations were performed using a RANS solver and the results were compared with detailed experimental data obtained in the GE Low Speed Research Compressor and the Notre Dame Transonic Rig at several operating conditions including near stall. Differences in the performance predictions between the three configurations were then used to determine the effect of the upstream stator wakes and the downstream blade row interactions. Results obtained show that for both the low speed and transonic research compressors used in this investigation time-accurate RANS analysis is necessary to accurately predict the stalling character of the rotor. Additionally, for the first time it is demonstrated that capturing the unsteady tip flow can have a larger impact on rotor performance predictions than adjacent blade row interactions.

Accurate prediction of protein–protein interactions from sequence alignments using a Bayesian method

PubMed Central

Burger, Lukas; van Nimwegen, Erik

2008-01-01

Accurate and large-scale prediction of protein–protein interactions directly from amino-acid sequences is one of the great challenges in computational biology. Here we present a new Bayesian network method that predicts interaction partners using only multiple alignments of amino-acid sequences of interacting protein domains, without tunable parameters, and without the need for any training examples. We first apply the method to bacterial two-component systems and comprehensively reconstruct two-component signaling networks across all sequenced bacteria. Comparisons of our predictions with known interactions show that our method infers interaction partners genome-wide with high accuracy. To demonstrate the general applicability of our method we show that it also accurately predicts interaction partners in a recent dataset of polyketide synthases. Analysis of the predicted genome-wide two-component signaling networks shows that cognates (interacting kinase/regulator pairs, which lie adjacent on the genome) and orphans (which lie isolated) form two relatively independent components of the signaling network in each genome. In addition, while most genes are predicted to have only a small number of interaction partners, we find that 10% of orphans form a separate class of ‘hub' nodes that distribute and integrate signals to and from up to tens of different interaction partners. PMID:18277381

A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes

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

Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.

2004-12-01

We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacterpylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, andmore » its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from sixphylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.« less

Development of Computational Aeroacoustics Code for Jet Noise and Flow Prediction

NASA Astrophysics Data System (ADS)

Keith, Theo G., Jr.; Hixon, Duane R.

2002-07-01

Accurate prediction of jet fan and exhaust plume flow and noise generation and propagation is very important in developing advanced aircraft engines that will pass current and future noise regulations. In jet fan flows as well as exhaust plumes, two major sources of noise are present: large-scale, coherent instabilities and small-scale turbulent eddies. In previous work for the NASA Glenn Research Center, three strategies have been explored in an effort to computationally predict the noise radiation from supersonic jet exhaust plumes. In order from the least expensive computationally to the most expensive computationally, these are: 1) Linearized Euler equations (LEE). 2) Very Large Eddy Simulations (VLES). 3) Large Eddy Simulations (LES). The first method solves the linearized Euler equations (LEE). These equations are obtained by linearizing about a given mean flow and the neglecting viscous effects. In this way, the noise from large-scale instabilities can be found for a given mean flow. The linearized Euler equations are computationally inexpensive, and have produced good noise results for supersonic jets where the large-scale instability noise dominates, as well as for the tone noise from a jet engine blade row. However, these linear equations do not predict the absolute magnitude of the noise; instead, only the relative magnitude is predicted. Also, the predicted disturbances do not modify the mean flow, removing a physical mechanism by which the amplitude of the disturbance may be controlled. Recent research for isolated airfoils' indicates that this may not affect the solution greatly at low frequencies. The second method addresses some of the concerns raised by the LEE method. In this approach, called Very Large Eddy Simulation (VLES), the unsteady Reynolds averaged Navier-Stokes equations are solved directly using a high-accuracy computational aeroacoustics numerical scheme. With the addition of a two-equation turbulence model and the use of a relatively

Predicting the natural flow regime: Models for assessing hydrological alteration in streams

USGS Publications Warehouse

Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

2009-01-01

Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also

A time-accurate implicit method for chemical non-equilibrium flows at all speeds

NASA Technical Reports Server (NTRS)

Shuen, Jian-Shun

1992-01-01

A new time accurate coupled solution procedure for solving the chemical non-equilibrium Navier-Stokes equations over a wide range of Mach numbers is described. The scheme is shown to be very efficient and robust for flows with velocities ranging from M less than or equal to 10(exp -10) to supersonic speeds.

Accurate prediction of energy expenditure using a shoe-based activity monitor.

PubMed

Sazonova, Nadezhda; Browning, Raymond C; Sazonov, Edward

2011-07-01

The aim of this study was to develop and validate a method for predicting energy expenditure (EE) using a footwear-based system with integrated accelerometer and pressure sensors. We developed a footwear-based device with an embedded accelerometer and insole pressure sensors for the prediction of EE. The data from the device can be used to perform accurate recognition of major postures and activities and to estimate EE using the acceleration, pressure, and posture/activity classification information in a branched algorithm without the need for individual calibration. We measured EE via indirect calorimetry as 16 adults (body mass index=19-39 kg·m) performed various low- to moderate-intensity activities and compared measured versus predicted EE using several models based on the acceleration and pressure signals. Inclusion of pressure data resulted in better accuracy of EE prediction during static postures such as sitting and standing. The activity-based branched model that included predictors from accelerometer and pressure sensors (BACC-PS) achieved the lowest error (e.g., root mean squared error (RMSE)=0.69 METs) compared with the accelerometer-only-based branched model BACC (RMSE=0.77 METs) and nonbranched model (RMSE=0.94-0.99 METs). Comparison of EE prediction models using data from both legs versus models using data from a single leg indicates that only one shoe needs to be equipped with sensors. These results suggest that foot acceleration combined with insole pressure measurement, when used in an activity-specific branched model, can accurately estimate the EE associated with common daily postures and activities. The accuracy and unobtrusiveness of a footwear-based device may make it an effective physical activity monitoring tool.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter.

PubMed

Müller, Martin; Seidenberg, Ruth; Schuh, Sabine K; Exadaktylos, Aristomenis K; Schechter, Clyde B; Leichtle, Alexander B; Hautz, Wolf E

2018-01-01

Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected.

The development and validation of different decision-making tools to predict urine culture growth out of urine flow cytometry parameter

PubMed Central

Seidenberg, Ruth; Schuh, Sabine K.; Exadaktylos, Aristomenis K.; Schechter, Clyde B.; Leichtle, Alexander B.; Hautz, Wolf E.

2018-01-01

Objective Patients presenting with suspected urinary tract infection are common in every day emergency practice. Urine flow cytometry has replaced microscopic urine evaluation in many emergency departments, but interpretation of the results remains challenging. The aim of this study was to develop and validate tools that predict urine culture growth out of urine flow cytometry parameter. Methods This retrospective study included all adult patients that presented in a large emergency department between January and July 2017 with a suspected urinary tract infection and had a urine flow cytometry as well as a urine culture obtained. The objective was to identify urine flow cytometry parameters that reliably predict urine culture growth and mixed flora growth. The data set was split into a training (70%) and a validation set (30%) and different decision-making approaches were developed and validated. Results Relevant urine culture growth (respectively mixed flora growth) was found in 40.2% (7.2% respectively) of the 613 patients included. The number of leukocytes and bacteria in flow cytometry were highly associated with urine culture growth, but mixed flora growth could not be sufficiently predicted from the urine flow cytometry parameters. A decision tree, predictive value figures, a nomogram, and a cut-off table to predict urine culture growth from bacteria and leukocyte count were developed, validated and compared. Conclusions Urine flow cytometry parameters are insufficient to predict mixed flora growth. However, the prediction of urine culture growth based on bacteria and leukocyte count is highly accurate and the developed tools should be used as part of the decision-making process of ordering a urine culture or starting an antibiotic therapy if a urogenital infection is suspected. PMID:29474463

Prediction of unsteady airfoil flows at large angles of incidence

NASA Technical Reports Server (NTRS)

Cebeci, Tuncer; Jang, H. M.; Chen, H. H.

1992-01-01

The effect of the unsteady motion of an airfoil on its stall behavior is of considerable interest to many practical applications including the blades of helicopter rotors and of axial compressors and turbines. Experiments with oscillating airfoils, for example, have shown that the flow can remain attached for angles of attack greater than those which would cause stall to occur in a stationary system. This result appears to stem from the formation of a vortex close to the surface of the airfoil which continues to provide lift. It is also evident that the onset of dynamic stall depends strongly on the airfoil section, and as a result, great care is required in the development of a calculation method which will accurately predict this behavior.

Are EMS call volume predictions based on demand pattern analysis accurate?

PubMed

Brown, Lawrence H; Lerner, E Brooke; Larmon, Baxter; LeGassick, Todd; Taigman, Michael

2007-01-01

Most EMS systems determine the number of crews they will deploy in their communities and when those crews will be scheduled based on anticipated call volumes. Many systems use historical data to calculate their anticipated call volumes, a method of prediction known as demand pattern analysis. To evaluate the accuracy of call volume predictions calculated using demand pattern analysis. Seven EMS systems provided 73 consecutive weeks of hourly call volume data. The first 20 weeks of data were used to calculate three common demand pattern analysis constructs for call volume prediction: average peak demand (AP), smoothed average peak demand (SAP), and 90th percentile rank (90%R). The 21st week served as a buffer. Actual call volumes in the last 52 weeks were then compared to the predicted call volumes by using descriptive statistics. There were 61,152 hourly observations in the test period. All three constructs accurately predicted peaks and troughs in call volume but not exact call volume. Predictions were accurate (+/-1 call) 13% of the time using AP, 10% using SAP, and 19% using 90%R. Call volumes were overestimated 83% of the time using AP, 86% using SAP, and 74% using 90%R. When call volumes were overestimated, predictions exceeded actual call volume by a median (Interquartile range) of 4 (2-6) calls for AP, 4 (2-6) for SAP, and 3 (2-5) for 90%R. Call volumes were underestimated 4% of time using AP, 4% using SAP, and 7% using 90%R predictions. When call volumes were underestimated, call volumes exceeded predictions by a median (Interquartile range; maximum under estimation) of 1 (1-2; 18) call for AP, 1 (1-2; 18) for SAP, and 2 (1-3; 20) for 90%R. Results did not vary between systems. Generally, demand pattern analysis estimated or overestimated call volume, making it a reasonable predictor for ambulance staffing patterns. However, it did underestimate call volume between 4% and 7% of the time. Communities need to determine if these rates of over

Predicting Information Flows in Network Traffic.

ERIC Educational Resources Information Center

Hinich, Melvin J.; Molyneux, Robert E.

2003-01-01

Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

Unfitted Two-Phase Flow Simulations in Pore-Geometries with Accurate

NASA Astrophysics Data System (ADS)

Heimann, Felix; Engwer, Christian; Ippisch, Olaf; Bastian, Peter

2013-04-01

The development of better macro scale models for multi-phase flow in porous media is still impeded by the lack of suitable methods for the simulation of such flow regimes on the pore scale. The highly complicated geometry of natural porous media imposes requirements with regard to stability and computational efficiency which current numerical methods fail to meet. Therefore, current simulation environments are still unable to provide a thorough understanding of porous media in multi-phase regimes and still fail to reproduce well known effects like hysteresis or the more peculiar dynamics of the capillary fringe with satisfying accuracy. Although flow simulations in pore geometries were initially the domain of Lattice-Boltzmann and other particle methods, the development of Galerkin methods for such applications is important as they complement the range of feasible flow and parameter regimes. In the recent past, it has been shown that unfitted Galerkin methods can be applied efficiently to topologically demanding geometries. However, in the context of two-phase flows, the interface of the two immiscible fluids effectively separates the domain in two sub-domains. The exact representation of such setups with multiple independent and time depending geometries exceeds the functionality of common unfitted methods. We present a new approach to pore scale simulations with an unfitted discontinuous Galerkin (UDG) method. Utilizing a recursive sub-triangulation algorithm, we extent the UDG method to setups with multiple independent geometries. This approach allows an accurate representation of the moving contact line and the interface conditions, i.e. the pressure jump across the interface. Example simulations in two and three dimensions illustrate and verify the stability and accuracy of this approach.

Rapid and accurate prediction and scoring of water molecules in protein binding sites.

PubMed

Ross, Gregory A; Morris, Garrett M; Biggin, Philip C

2012-01-01

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

Cartesian Off-Body Grid Adaption for Viscous Time- Accurate Flow Simulation

NASA Technical Reports Server (NTRS)

Buning, Pieter G.; Pulliam, Thomas H.

2011-01-01

An improved solution adaption capability has been implemented in the OVERFLOW overset grid CFD code. Building on the Cartesian off-body approach inherent in OVERFLOW and the original adaptive refinement method developed by Meakin, the new scheme provides for automated creation of multiple levels of finer Cartesian grids. Refinement can be based on the undivided second-difference of the flow solution variables, or on a specific flow quantity such as vorticity. Coupled with load-balancing and an inmemory solution interpolation procedure, the adaption process provides very good performance for time-accurate simulations on parallel compute platforms. A method of using refined, thin body-fitted grids combined with adaption in the off-body grids is presented, which maximizes the part of the domain subject to adaption. Two- and three-dimensional examples are used to illustrate the effectiveness and performance of the adaption scheme.

Multi-fidelity uncertainty quantification in large-scale predictive simulations of turbulent flow

NASA Astrophysics Data System (ADS)

Geraci, Gianluca; Jofre-Cruanyes, Lluis; Iaccarino, Gianluca

2017-11-01

The performance characterization of complex engineering systems often relies on accurate, but computationally intensive numerical simulations. It is also well recognized that in order to obtain a reliable numerical prediction the propagation of uncertainties needs to be included. Therefore, Uncertainty Quantification (UQ) plays a fundamental role in building confidence in predictive science. Despite the great improvement in recent years, even the more advanced UQ algorithms are still limited to fairly simplified applications and only moderate parameter dimensionality. Moreover, in the case of extremely large dimensionality, sampling methods, i.e. Monte Carlo (MC) based approaches, appear to be the only viable alternative. In this talk we describe and compare a family of approaches which aim to accelerate the convergence of standard MC simulations. These methods are based on hierarchies of generalized numerical resolutions (multi-level) or model fidelities (multi-fidelity), and attempt to leverage the correlation between Low- and High-Fidelity (HF) models to obtain a more accurate statistical estimator without introducing additional HF realizations. The performance of these methods are assessed on an irradiated particle laden turbulent flow (PSAAP II solar energy receiver). This investigation was funded by the United States Department of Energy's (DoE) National Nuclear Security Administration (NNSA) under the Predicitive Science Academic Alliance Program (PSAAP) II at Stanford University.

Mean Flow and Noise Prediction for a Separate Flow Jet With Chevron Mixers

NASA Technical Reports Server (NTRS)

Koch, L. Danielle; Bridges, James; Khavaran, Abbas

2004-01-01

Experimental and numerical results are presented here for a separate flow nozzle employing chevrons arranged in an alternating pattern on the core nozzle. Comparisons of these results demonstrate that the combination of the WIND/MGBK suite of codes can predict the noise reduction trends measured between separate flow jets with and without chevrons on the core nozzle. Mean flow predictions were validated against Particle Image Velocimetry (PIV), pressure, and temperature data, and noise predictions were validated against acoustic measurements recorded in the NASA Glenn Aeroacoustic Propulsion Lab. Comparisons are also made to results from the CRAFT code. The work presented here is part of an on-going assessment of the WIND/MGBK suite for use in designing the next generation of quiet nozzles for turbofan engines.

Multi-fidelity machine learning models for accurate bandgap predictions of solids

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

Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

Multi-fidelity machine learning models for accurate bandgap predictions of solids

DOE PAGES

Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab

2016-12-28

Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less

Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool.

PubMed

Aqil, Muhammad; Kita, Ichiro; Yano, Akira; Nishiyama, Soichi

2007-10-01

Traditionally, the multiple linear regression technique has been one of the most widely used models in simulating hydrological time series. However, when the nonlinear phenomenon is significant, the multiple linear will fail to develop an appropriate predictive model. Recently, neuro-fuzzy systems have gained much popularity for calibrating the nonlinear relationships. This study evaluated the potential of a neuro-fuzzy system as an alternative to the traditional statistical regression technique for the purpose of predicting flow from a local source in a river basin. The effectiveness of the proposed identification technique was demonstrated through a simulation study of the river flow time series of the Citarum River in Indonesia. Furthermore, in order to provide the uncertainty associated with the estimation of river flow, a Monte Carlo simulation was performed. As a comparison, a multiple linear regression analysis that was being used by the Citarum River Authority was also examined using various statistical indices. The simulation results using 95% confidence intervals indicated that the neuro-fuzzy model consistently underestimated the magnitude of high flow while the low and medium flow magnitudes were estimated closer to the observed data. The comparison of the prediction accuracy of the neuro-fuzzy and linear regression methods indicated that the neuro-fuzzy approach was more accurate in predicting river flow dynamics. The neuro-fuzzy model was able to improve the root mean square error (RMSE) and mean absolute percentage error (MAPE) values of the multiple linear regression forecasts by about 13.52% and 10.73%, respectively. Considering its simplicity and efficiency, the neuro-fuzzy model is recommended as an alternative tool for modeling of flow dynamics in the study area.

Measuring the value of accurate link prediction for network seeding.

PubMed

Wei, Yijin; Spencer, Gwen

2017-01-01

The influence-maximization literature seeks small sets of individuals whose structural placement in the social network can drive large cascades of behavior. Optimization efforts to find the best seed set often assume perfect knowledge of the network topology. Unfortunately, social network links are rarely known in an exact way. When do seeding strategies based on less-than-accurate link prediction provide valuable insight? We introduce optimized-against-a-sample ([Formula: see text]) performance to measure the value of optimizing seeding based on a noisy observation of a network. Our computational study investigates [Formula: see text] under several threshold-spread models in synthetic and real-world networks. Our focus is on measuring the value of imprecise link information. The level of investment in link prediction that is strategic appears to depend closely on spread model: in some parameter ranges investments in improving link prediction can pay substantial premiums in cascade size. For other ranges, such investments would be wasted. Several trends were remarkably consistent across topologies.

Can numerical simulations accurately predict hydrodynamic instabilities in liquid films?

NASA Astrophysics Data System (ADS)

Denner, Fabian; Charogiannis, Alexandros; Pradas, Marc; van Wachem, Berend G. M.; Markides, Christos N.; Kalliadasis, Serafim

2014-11-01

Understanding the dynamics of hydrodynamic instabilities in liquid film flows is an active field of research in fluid dynamics and non-linear science in general. Numerical simulations offer a powerful tool to study hydrodynamic instabilities in film flows and can provide deep insights into the underlying physical phenomena. However, the direct comparison of numerical results and experimental results is often hampered by several reasons. For instance, in numerical simulations the interface representation is problematic and the governing equations and boundary conditions may be oversimplified, whereas in experiments it is often difficult to extract accurate information on the fluid and its behavior, e.g. determine the fluid properties when the liquid contains particles for PIV measurements. In this contribution we present the latest results of our on-going, extensive study on hydrodynamic instabilities in liquid film flows, which includes direct numerical simulations, low-dimensional modelling as well as experiments. The major focus is on wave regimes, wave height and wave celerity as a function of Reynolds number and forcing frequency of a falling liquid film. Specific attention is paid to the differences in numerical and experimental results and the reasons for these differences. The authors are grateful to the EPSRC for their financial support (Grant EP/K008595/1).

Accurate prediction of secondary metabolite gene clusters in filamentous fungi.

PubMed

Andersen, Mikael R; Nielsen, Jakob B; Klitgaard, Andreas; Petersen, Lene M; Zachariasen, Mia; Hansen, Tilde J; Blicher, Lene H; Gotfredsen, Charlotte H; Larsen, Thomas O; Nielsen, Kristian F; Mortensen, Uffe H

2013-01-02

Biosynthetic pathways of secondary metabolites from fungi are currently subject to an intense effort to elucidate the genetic basis for these compounds due to their large potential within pharmaceutics and synthetic biochemistry. The preferred method is methodical gene deletions to identify supporting enzymes for key synthases one cluster at a time. In this study, we design and apply a DNA expression array for Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium. We apply a guilt-by-association-based analysis to predict the extent of the biosynthetic clusters for the 58 synthases active in our set of experimental conditions. A comparison with legacy data shows the method to be accurate in 13 of 16 known clusters and nearly accurate for the remaining 3 clusters. Furthermore, we apply a data clustering approach, which identifies cross-chemistry between physically separate gene clusters (superclusters), and validate this both with legacy data and experimentally by prediction and verification of a supercluster consisting of the synthase AN1242 and the prenyltransferase AN11080, as well as identification of the product compound nidulanin A. We have used A. nidulans for our method development and validation due to the wealth of available biochemical data, but the method can be applied to any fungus with a sequenced and assembled genome, thus supporting further secondary metabolite pathway elucidation in the fungal kingdom.

Simple prediction scores predict good and devastating outcomes after stroke more accurately than physicians.

PubMed

Reid, John Michael; Dai, Dingwei; Delmonte, Susanna; Counsell, Carl; Phillips, Stephen J; MacLeod, Mary Joan

2017-05-01

physicians are often asked to prognosticate soon after a patient presents with stroke. This study aimed to compare two outcome prediction scores (Five Simple Variables [FSV] score and the PLAN [Preadmission comorbidities, Level of consciousness, Age, and focal Neurologic deficit]) with informal prediction by physicians. demographic and clinical variables were prospectively collected from consecutive patients hospitalised with acute ischaemic or haemorrhagic stroke (2012-13). In-person or telephone follow-up at 6 months established vital and functional status (modified Rankin score [mRS]). Area under the receiver operating curves (AUC) was used to establish prediction score performance. five hundred and seventy-five patients were included; 46% female, median age 76 years, 88% ischaemic stroke. Six months after stroke, 47% of patients had a good outcome (alive and independent, mRS 0-2) and 26% a devastating outcome (dead or severely dependent, mRS 5-6). The FSV and PLAN scores were superior to physician prediction (AUCs of 0.823-0.863 versus 0.773-0.805, P < 0.0001) for good and devastating outcomes. The FSV score was superior to the PLAN score for predicting good outcomes and vice versa for devastating outcomes (P < 0.001). Outcome prediction was more accurate for those with later presentations (>24 hours from onset). the FSV and PLAN scores are validated in this population for outcome prediction after both ischaemic and haemorrhagic stroke. The FSV score is the least complex of all developed scores and can assist outcome prediction by physicians. © The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

Accurate Prediction of Contact Numbers for Multi-Spanning Helical Membrane Proteins

PubMed Central

Li, Bian; Mendenhall, Jeffrey; Nguyen, Elizabeth Dong; Weiner, Brian E.; Fischer, Axel W.; Meiler, Jens

2017-01-01

Prediction of the three-dimensional (3D) structures of proteins by computational methods is acknowledged as an unsolved problem. Accurate prediction of important structural characteristics such as contact number is expected to accelerate the otherwise slow progress being made in the prediction of 3D structure of proteins. Here, we present a dropout neural network-based method, TMH-Expo, for predicting the contact number of transmembrane helix (TMH) residues from sequence. Neuronal dropout is a strategy where certain neurons of the network are excluded from back-propagation to prevent co-adaptation of hidden-layer neurons. By using neuronal dropout, overfitting was significantly reduced and performance was noticeably improved. For multi-spanning helical membrane proteins, TMH-Expo achieved a remarkable Pearson correlation coefficient of 0.69 between predicted and experimental values and a mean absolute error of only 1.68. In addition, among those membrane protein–membrane protein interface residues, 76.8% were correctly predicted. Mapping of predicted contact numbers onto structures indicates that contact numbers predicted by TMH-Expo reflect the exposure patterns of TMHs and reveal membrane protein–membrane protein interfaces, reinforcing the potential of predicted contact numbers to be used as restraints for 3D structure prediction and protein–protein docking. TMH-Expo can be accessed via a Web server at www.meilerlab.org. PMID:26804342

Prediction of induction time for methane hydrate formation in the presence or absence of THF in flow loop system by Natarajan model

NASA Astrophysics Data System (ADS)

Talaghat, Mohammad Reza; Jokar, Seyyed Mohammad

2018-03-01

The induction time is a time interval to detect the initial hydrate formation, which is counted from the moment when the stirrer is turned on until the first detection of hydrate formation. The main objective of the present work is to predict and measure the induction time of methane hydrate formation in the presence or absence of tetrahydrofuran (THF) as promoter in the flow loop system. A laboratory flow mini-loop apparatus was set up to measure the induction time of methane hydrate formation. The induction time is predicted using developed Kashchiev and Firoozabadi model and modified model of Natarajan for a flow loop system. Furthermore, the effects of volumetric flow rate of the fluid on the induction time were investigated. The results of the models were compared with experimental data. They show that the induction time of hydrate formation in the presence of THF is very short at high pressure and high volumetric flow rate of the fluid. It decreases with increasing pressure and liquid volumetric flow rate. It is also shown that the modified Natarajan model is more accurate than the Kashchiev and Firoozabadi ones in prediction of the induction time.

Prediction of flow duration curves for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, Maya; Taylor, Graham; M. A. Sattar, Ahmed; Gharabaghi, Bahram

2017-02-01

This study presents novel models for prediction of flow Duration Curves (FDCs) at ungauged basins using artificial neural networks (ANN) and Gene Expression Programming (GEP) trained and tested using historical flow records from 171 unregulated and 89 regulated basins across North America. For the 89 regulated basins, FDCs were generated for both before and after flow regulation. Topographic, climatic, and land use characteristics are used to develop relationships between these basin characteristics and FDC statistical distribution parameters: mean (m) and variance (ν). The two main hypotheses that flow regulation has negligible effect on the mean (m) while it the variance (ν) were confirmed. The novel GEP model that predicts the mean (GEP-m) performed very well with high R2 (0.9) and D (0.95) values and low RAE value of 0.25. The simple regression model that predicts the variance (REG-v) was developed as a function of the mean (m) and a flow regulation index (R). The measured performance and uncertainty analysis indicated that the ANN-m was the best performing model with R2 (0.97), RAE (0.21), D (0.93) and the lowest 95% confidence prediction error interval (+0.22 to +3.49). Both GEP and ANN models were most sensitive to drainage area followed by mean annual precipitation, apportionment entropy disorder index, and shape factor.

Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates

DOE PAGES

Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; ...

2013-03-07

In shotgun proteomics, database search algorithms rely on fragmentation models to predict fragment ions that should be observed for a given peptide sequence. The most widely used strategy (Naive model) is oversimplified, cleaving all peptide bonds with equal probability to produce fragments of all charges below that of the precursor ion. More accurate models, based on fragmentation simulation, are too computationally intensive for on-the-fly use in database search algorithms. We have created an ordinal-regression-based model called Basophile that takes fragment size and basic residue distribution into account when determining the charge retention during CID/higher-energy collision induced dissociation (HCD) of chargedmore » peptides. This model improves the accuracy of predictions by reducing the number of unnecessary fragments that are routinely predicted for highly-charged precursors. Basophile increased the identification rates by 26% (on average) over the Naive model, when analyzing triply-charged precursors from ion trap data. Basophile achieves simplicity and speed by solving the prediction problem with an ordinal regression equation, which can be incorporated into any database search software for shotgun proteomic identification.« less

Validating Whole-Airway CFD Predictions of DPI Aerosol Deposition at Multiple Flow Rates.

PubMed

Longest, P Worth; Tian, Geng; Khajeh-Hosseini-Dalasm, Navvab; Hindle, Michael

2016-12-01

The objective of this study was to compare aerosol deposition predictions of a new whole-airway CFD model with available in vivo data for a dry powder inhaler (DPI) considered across multiple inhalation waveforms, which affect both the particle size distribution (PSD) and particle deposition. The Novolizer DPI with a budesonide formulation was selected based on the availability of 2D gamma scintigraphy data in humans for three different well-defined inhalation waveforms. Initial in vitro cascade impaction experiments were conducted at multiple constant (square-wave) particle sizing flow rates to characterize PSDs. The whole-airway CFD modeling approach implemented the experimentally determined PSDs at the point of aerosol formation in the inhaler. Complete characteristic airway geometries for an adult were evaluated through the lobar bronchi, followed by stochastic individual pathway (SIP) approximations through the tracheobronchial region and new acinar moving wall models of the alveolar region. It was determined that the PSD used for each inhalation waveform should be based on a constant particle sizing flow rate equal to the average of the inhalation waveform's peak inspiratory flow rate (PIFR) and mean flow rate [i.e., AVG(PIFR, Mean)]. Using this technique, agreement with the in vivo data was acceptable with <15% relative differences averaged across the three regions considered for all inhalation waveforms. Defining a peripheral to central deposition ratio (P/C) based on alveolar and tracheobronchial compartments, respectively, large flow-rate-dependent differences were observed, which were not evident in the original 2D in vivo data. The agreement between the CFD predictions and in vivo data was dependent on accurate initial estimates of the PSD, emphasizing the need for a combination in vitro-in silico approach. Furthermore, use of the AVG(PIFR, Mean) value was identified as a potentially useful method for characterizing a DPI aerosol at a constant flow rate.

Confined Turbulent Swirling Recirculating Flow Predictions. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Abujelala, M. T.

1984-01-01

Turbulent swirling flow, the STARPIC computer code, turbulence modeling of turbulent flows, the k-xi turbulence model and extensions, turbulence parameters deduction from swirling confined flow measurements, extension of the k-xi to confined swirling recirculating flows, and general predictions for confined turbulent swirling flow are discussed.

Physical and Numerical Model Studies of Cross-flow Turbines Towards Accurate Parameterization in Array Simulations

NASA Astrophysics Data System (ADS)

Wosnik, M.; Bachant, P.

2014-12-01

Cross-flow turbines, often referred to as vertical-axis turbines, show potential for success in marine hydrokinetic (MHK) and wind energy applications, ranging from small- to utility-scale installations in tidal/ocean currents and offshore wind. As turbine designs mature, the research focus is shifting from individual devices to the optimization of turbine arrays. It would be expensive and time-consuming to conduct physical model studies of large arrays at large model scales (to achieve sufficiently high Reynolds numbers), and hence numerical techniques are generally better suited to explore the array design parameter space. However, since the computing power available today is not sufficient to conduct simulations of the flow in and around large arrays of turbines with fully resolved turbine geometries (e.g., grid resolution into the viscous sublayer on turbine blades), the turbines' interaction with the energy resource (water current or wind) needs to be parameterized, or modeled. Models used today--a common model is the actuator disk concept--are not able to predict the unique wake structure generated by cross-flow turbines. This wake structure has been shown to create "constructive" interference in some cases, improving turbine performance in array configurations, in contrast with axial-flow, or horizontal axis devices. Towards a more accurate parameterization of cross-flow turbines, an extensive experimental study was carried out using a high-resolution turbine test bed with wake measurement capability in a large cross-section tow tank. The experimental results were then "interpolated" using high-fidelity Navier--Stokes simulations, to gain insight into the turbine's near-wake. The study was designed to achieve sufficiently high Reynolds numbers for the results to be Reynolds number independent with respect to turbine performance and wake statistics, such that they can be reliably extrapolated to full scale and used for model validation. The end product of

An accurate model for predicting high frequency noise of nanoscale NMOS SOI transistors

NASA Astrophysics Data System (ADS)

Shen, Yanfei; Cui, Jie; Mohammadi, Saeed

2017-05-01

A nonlinear and scalable model suitable for predicting high frequency noise of N-type Metal Oxide Semiconductor (NMOS) transistors is presented. The model is developed for a commercial 45 nm CMOS SOI technology and its accuracy is validated through comparison with measured performance of a microwave low noise amplifier. The model employs the virtual source nonlinear core and adds parasitic elements to accurately simulate the RF behavior of multi-finger NMOS transistors up to 40 GHz. For the first time, the traditional long-channel thermal noise model is supplemented with an injection noise model to accurately represent the noise behavior of these short-channel transistors up to 26 GHz. The developed model is simple and easy to extract, yet very accurate.

Fast and Accurate Prediction of Stratified Steel Temperature During Holding Period of Ladle

NASA Astrophysics Data System (ADS)

Deodhar, Anirudh; Singh, Umesh; Shukla, Rishabh; Gautham, B. P.; Singh, Amarendra K.

2017-04-01

Thermal stratification of liquid steel in a ladle during the holding period and the teeming operation has a direct bearing on the superheat available at the caster and hence on the caster set points such as casting speed and cooling rates. The changes in the caster set points are typically carried out based on temperature measurements at the end of tundish outlet. Thermal prediction models provide advance knowledge of the influence of process and design parameters on the steel temperature at various stages. Therefore, they can be used in making accurate decisions about the caster set points in real time. However, this requires both fast and accurate thermal prediction models. In this work, we develop a surrogate model for the prediction of thermal stratification using data extracted from a set of computational fluid dynamics (CFD) simulations, pre-determined using design of experiments technique. Regression method is used for training the predictor. The model predicts the stratified temperature profile instantaneously, for a given set of process parameters such as initial steel temperature, refractory heat content, slag thickness, and holding time. More than 96 pct of the predicted values are within an error range of ±5 K (±5 °C), when compared against corresponding CFD results. Considering its accuracy and computational efficiency, the model can be extended for thermal control of casting operations. This work also sets a benchmark for developing similar thermal models for downstream processes such as tundish and caster.

On the prediction of turbulent secondary flows

NASA Technical Reports Server (NTRS)

Speziale, C. G.; So, R. M. C.; Younis, B. A.

1992-01-01

The prediction of turbulent secondary flows, with Reynolds stress models, in circular pipes and non-circular ducts is reviewed. Turbulence-driven secondary flows in straight non-circular ducts are considered along with turbulent secondary flows in pipes and ducts that arise from curvature or a system rotation. The physical mechanisms that generate these different kinds of secondary flows are outlined and the level of turbulence closure required to properly compute each type is discussed in detail. Illustrative computations of a variety of different secondary flows obtained from two-equation turbulence models and second-order closures are provided to amplify these points.

Competitive Abilities in Experimental Microcosms Are Accurately Predicted by a Demographic Index for R*

PubMed Central

Murrell, Ebony G.; Juliano, Steven A.

2012-01-01

Resource competition theory predicts that R*, the equilibrium resource amount yielding zero growth of a consumer population, should predict species' competitive abilities for that resource. This concept has been supported for unicellular organisms, but has not been well-tested for metazoans, probably due to the difficulty of raising experimental populations to equilibrium and measuring population growth rates for species with long or complex life cycles. We developed an index (Rindex) of R* based on demography of one insect cohort, growing from egg to adult in a non-equilibrium setting, and tested whether Rindex yielded accurate predictions of competitive abilities using mosquitoes as a model system. We estimated finite rate of increase (λ′) from demographic data for cohorts of three mosquito species raised with different detritus amounts, and estimated each species' Rindex using nonlinear regressions of λ′ vs. initial detritus amount. All three species' Rindex differed significantly, and accurately predicted competitive hierarchy of the species determined in simultaneous pairwise competition experiments. Our Rindex could provide estimates and rigorous statistical comparisons of competitive ability for organisms for which typical chemostat methods and equilibrium population conditions are impractical. PMID:22970128

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

PubMed Central

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

Improving urban wind flow predictions through data assimilation

NASA Astrophysics Data System (ADS)

Sousa, Jorge; Gorle, Catherine

2017-11-01

Computational fluid dynamic is fundamentally important to several aspects in the design of sustainable and resilient urban environments. The prediction of the flow pattern for example can help to determine pedestrian wind comfort, air quality, optimal building ventilation strategies, and wind loading on buildings. However, the significant variability and uncertainty in the boundary conditions poses a challenge when interpreting results as a basis for design decisions. To improve our understanding of the uncertainties in the models and develop better predictive tools, we started a pilot field measurement campaign on Stanford University's campus combined with a detailed numerical prediction of the wind flow. The experimental data is being used to investigate the potential use of data assimilation and inverse techniques to better characterize the uncertainty in the results and improve the confidence in current wind flow predictions. We consider the incoming wind direction and magnitude as unknown parameters and perform a set of Reynolds-averaged Navier-Stokes simulations to build a polynomial chaos expansion response surface at each sensor location. We subsequently use an inverse ensemble Kalman filter to retrieve an estimate for the probabilistic density function of the inflow parameters. Once these distributions are obtained, the forward analysis is repeated to obtain predictions for the flow field in the entire urban canopy and the results are compared with the experimental data. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR.

SIFTER search: a web server for accurate phylogeny-based protein function prediction

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

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

SIFTER search: a web server for accurate phylogeny-based protein function prediction

DOE PAGES

Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

2015-05-15

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks.

PubMed

Zaretzki, Jed; Matlock, Matthew; Swamidass, S Joshua

2013-12-23

Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these properties. The cytochrome P450s (CYPs) are proteins responsible for metabolizing 90% of drugs on the market, and many computational methods can predict which atomic sites of a molecule--sites of metabolism (SOMs)--are modified during CYP-mediated metabolism. This study improves on prior methods of predicting CYP-mediated SOMs by using new descriptors and machine learning based on neural networks. The new method, XenoSite, is faster to train and more accurate by as much as 4% or 5% for some isozymes. Furthermore, some "incorrect" predictions made by XenoSite were subsequently validated as correct predictions by revaluation of the source literature. Moreover, XenoSite output is interpretable as a probability, which reflects both the confidence of the model that a particular atom is metabolized and the statistical likelihood that its prediction for that atom is correct.

Predicting Fluid Flow in Stressed Fractures: A Quantitative Evaluation of Methods

NASA Astrophysics Data System (ADS)

Weihmann, S. A.; Healy, D.

2015-12-01

Reliable estimation of fracture stability in the subsurface is crucial to the success of exploration and production in the petroleum industry, and also for wider applications to earthquake mechanics, hydrogeology and waste disposal. Previous work suggests that fracture stability is related to fluid flow in crystalline basement rocks through shear or tensile instabilities of fractures. Our preliminary scoping analysis compares the fracture stability of 60 partly open (apertures 1.5-3 cm) and electrically conductive (low acoustic amplitudes relative to matrix) fractures from a 16 m section of a producing zone in a basement well in Bayoot field, Yemen, to a non-producing zone in the same well (also 16 m). We determine the Critically Stressed Fractures (CSF; Barton et al., 1995) and dilatation tendency (Td; Ferrill et al., 1999). We find that: 1. CSF (Fig. 1) is a poor predictor of high fluid flow in the inflow zone; 88% of the fractures are predicted to be NOT critically stressed and yet they all occur within a zone of high fluid flow rate 2. Td (Fig. 2) is also a poor predictor of high fluid flow in the inflow zone; 67% of the fractures have a LOW Td(< 0.6) 3. For the non-producing zone CSF is a very reliable predictor (100% are not critically stressed) whereas the values of Tdare consistent with their location in non-producing interval (81% are < 0.6) (Fig. 3 & 4). In summary, neither method correlates well with the observed abundance of hydraulically conductive fractures within the producing zone. Within the non-producing zone CSF and Td make reasonably accurate predictions. Fractures may be filled or partially filled with drilling mud or a lower density and electrically conductive fill such as clay in the producing zone and therefore appear (partly) open. In situ stress, fluid pressure, rock properties (friction, strength) and fracture orientation data used as inputs for the CSF and Td calculations are all subject to uncertainty. Our results suggest that scope

Predicting Rediated Noise With Power Flow Finite Element Analysis

DTIC Science & Technology

2007-02-01

Defence R&D Canada – Atlantic DEFENCE DÉFENSE & Predicting Rediated Noise With Power Flow Finite Element Analysis D. Brennan T.S. Koko L. Jiang J...PREDICTING RADIATED NOISE WITH POWER FLOW FINITE ELEMENT ANALYSIS D.P. Brennan T.S. Koko L. Jiang J.C. Wallace Martec Limited Martec Limited...model- or full-scale data before it is available for general use. Brennan, D.P., Koko , T.S., Jiang, L., Wallace, J.C. 2007. Predicting Radiated

MODFLOW equipped with a new method for the accurate simulation of axisymmetric flow

NASA Astrophysics Data System (ADS)

Samani, N.; Kompani-Zare, M.; Barry, D. A.

2004-01-01

Axisymmetric flow to a well is an important topic of groundwater hydraulics, the simulation of which depends on accurate computation of head gradients. Groundwater numerical models with conventional rectilinear grid geometry such as MODFLOW (in contrast to analytical models) generally have not been used to simulate aquifer test results at a pumping well because they are not designed or expected to closely simulate the head gradient near the well. A scaling method is proposed based on mapping the governing flow equation from cylindrical to Cartesian coordinates, and vice versa. A set of relationships and scales is derived to implement the conversion. The proposed scaling method is then embedded in MODFLOW 2000. To verify the accuracy of the method steady and unsteady flows in confined and unconfined aquifers with fully or partially penetrating pumping wells are simulated and compared with the corresponding analytical solutions. In all cases a high degree of accuracy is achieved.

Turbulence Model Predictions of Strongly Curved Flow in a U-Duct

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Gatski, Thomas B.; Morrison, Joseph H.

2000-01-01

The ability of three types of turbulence models to accurately predict the effects of curvature on the flow in a U-duct is studied. An explicit algebraic stress model performs slightly better than one- or two-equation linear eddy viscosity models, although it is necessary to fully account for the variation of the production-to-dissipation-rate ratio in the algebraic stress model formulation. In their original formulations, none of these turbulence models fully captures the suppressed turbulence near the convex wall, whereas a full Reynolds stress model does. Some of the underlying assumptions used in the development of algebraic stress models are investigated and compared with the computed flowfield from the full Reynolds stress model. Through this analysis, the assumption of Reynolds stress anisotropy equilibrium used in the algebraic stress model formulation is found to be incorrect in regions of strong curvature. By the accounting for the local variation of the principal axes of the strain rate tensor, the explicit algebraic stress model correctly predicts the suppressed turbulence in the outer part of the boundary layer near the convex wall.

Recommendations for Achieving Accurate Numerical Simulation of Tip Clearance Flows in Transonic Compressor Rotors

NASA Technical Reports Server (NTRS)

VanZante, Dale E.; Strazisar, Anthony J.; Wood, Jerry R,; Hathaway, Michael D.; Okiishi, Theodore H.

2000-01-01

The tip clearance flows of transonic compressor rotors are important because they have a significant impact on rotor and stage performance. While numerical simulations of these flows are quite sophisticated. they are seldom verified through rigorous comparisons of numerical and measured data because these kinds of measurements are rare in the detail necessary to be useful in high-speed machines. In this paper we compare measured tip clearance flow details (e.g. trajectory and radial extent) with corresponding data obtained from a numerical simulation. Recommendations for achieving accurate numerical simulation of tip clearance flows are presented based on this comparison. Laser Doppler Velocimeter (LDV) measurements acquired in a transonic compressor rotor, NASA Rotor 35, are used. The tip clearance flow field of this transonic rotor was simulated using a Navier-Stokes turbomachinery solver that incorporates an advanced k-epsilon turbulence model derived for flows that are not in local equilibrium. Comparison between measured and simulated results indicates that simulation accuracy is primarily dependent upon the ability of the numerical code to resolve important details of a wall-bounded shear layer formed by the relative motion between the over-tip leakage flow and the shroud wall. A simple method is presented for determining the strength of this shear layer.

Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features.

PubMed

Li, Hongyang; Panwar, Bharat; Omenn, Gilbert S; Guan, Yuanfang

2018-02-01

The olfactory stimulus-percept problem has been studied for more than a century, yet it is still hard to precisely predict the odor given the large-scale chemoinformatic features of an odorant molecule. A major challenge is that the perceived qualities vary greatly among individuals due to different genetic and cultural backgrounds. Moreover, the combinatorial interactions between multiple odorant receptors and diverse molecules significantly complicate the olfaction prediction. Many attempts have been made to establish structure-odor relationships for intensity and pleasantness, but no models are available to predict the personalized multi-odor attributes of molecules. In this study, we describe our winning algorithm for predicting individual and population perceptual responses to various odorants in the DREAM Olfaction Prediction Challenge. We find that random forest model consisting of multiple decision trees is well suited to this prediction problem, given the large feature spaces and high variability of perceptual ratings among individuals. Integrating both population and individual perceptions into our model effectively reduces the influence of noise and outliers. By analyzing the importance of each chemical feature, we find that a small set of low- and nondegenerative features is sufficient for accurate prediction. Our random forest model successfully predicts personalized odor attributes of structurally diverse molecules. This model together with the top discriminative features has the potential to extend our understanding of olfactory perception mechanisms and provide an alternative for rational odorant design.

A comparison of predicted and measured inlet distortion flows in a subsonic axial inlet flow compressor rotor

NASA Technical Reports Server (NTRS)

Owen, Albert K.

1992-01-01

Detailed flow measurements were taken inside an isolated axial compressor rotor operating subsonically near peak efficiency. These Laser Anemometer measurements were made with two inlet velocity profiles. One profile consisted of an unmodified baseline flow, and the second profile was distorted by placing axisymmetric screens on the hub and shroud well upstream of the rotor. A detailed comparison in the rotor relative reference frame between a Navier-Stokes solver and the measured experimental results showed good agreement between the predicted and measured flows. A primary flow is defined in the rotor and deviations and the computed predictions is made to assess the development of a passage vortex due to the distortion of the inlet flow. Computer predictions indicate that a distorted inlet profile has a minimal effect on the development of the flow in the rotor passage and the resulting passage vortex.

A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care.

PubMed

Alanazi, Hamdan O; Abdullah, Abdul Hanan; Qureshi, Kashif Naseer

2017-04-01

Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.

Implicit time accurate simulation of unsteady flow

NASA Astrophysics Data System (ADS)

van Buuren, René; Kuerten, Hans; Geurts, Bernard J.

2001-03-01

Implicit time integration was studied in the context of unsteady shock-boundary layer interaction flow. With an explicit second-order Runge-Kutta scheme, a reference solution to compare with the implicit second-order Crank-Nicolson scheme was determined. The time step in the explicit scheme is restricted by both temporal accuracy as well as stability requirements, whereas in the A-stable implicit scheme, the time step has to obey temporal resolution requirements and numerical convergence conditions. The non-linear discrete equations for each time step are solved iteratively by adding a pseudo-time derivative. The quasi-Newton approach is adopted and the linear systems that arise are approximately solved with a symmetric block Gauss-Seidel solver. As a guiding principle for properly setting numerical time integration parameters that yield an efficient time accurate capturing of the solution, the global error caused by the temporal integration is compared with the error resulting from the spatial discretization. Focus is on the sensitivity of properties of the solution in relation to the time step. Numerical simulations show that the time step needed for acceptable accuracy can be considerably larger than the explicit stability time step; typical ratios range from 20 to 80. At large time steps, convergence problems that are closely related to a highly complex structure of the basins of attraction of the iterative method may occur. Copyright

Prediction of High-Lift Flows using Turbulent Closure Models

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.; Gatski, Thomas B.; Ying, Susan X.; Bertelrud, Arild

1997-01-01

The flow over two different multi-element airfoil configurations is computed using linear eddy viscosity turbulence models and a nonlinear explicit algebraic stress model. A subset of recently-measured transition locations using hot film on a McDonnell Douglas configuration is presented, and the effect of transition location on the computed solutions is explored. Deficiencies in wake profile computations are found to be attributable in large part to poor boundary layer prediction on the generating element, and not necessarily inadequate turbulence modeling in the wake. Using measured transition locations for the main element improves the prediction of its boundary layer thickness, skin friction, and wake profile shape. However, using measured transition locations on the slat still yields poor slat wake predictions. The computation of the slat flow field represents a key roadblock to successful predictions of multi-element flows. In general, the nonlinear explicit algebraic stress turbulence model gives very similar results to the linear eddy viscosity models.

Characterization of 3-Dimensional PET Systems for Accurate Quantification of Myocardial Blood Flow.

PubMed

Renaud, Jennifer M; Yip, Kathy; Guimond, Jean; Trottier, Mikaël; Pibarot, Philippe; Turcotte, Eric; Maguire, Conor; Lalonde, Lucille; Gulenchyn, Karen; Farncombe, Troy; Wisenberg, Gerald; Moody, Jonathan; Lee, Benjamin; Port, Steven C; Turkington, Timothy G; Beanlands, Rob S; deKemp, Robert A

2017-01-01

Three-dimensional (3D) mode imaging is the current standard for PET/CT systems. Dynamic imaging for quantification of myocardial blood flow with short-lived tracers, such as 82 Rb-chloride, requires accuracy to be maintained over a wide range of isotope activities and scanner counting rates. We proposed new performance standard measurements to characterize the dynamic range of PET systems for accurate quantitative imaging. 82 Rb or 13 N-ammonia (1,100-3,000 MBq) was injected into the heart wall insert of an anthropomorphic torso phantom. A decaying isotope scan was obtained over 5 half-lives on 9 different 3D PET/CT systems and 1 3D/2-dimensional PET-only system. Dynamic images (28 × 15 s) were reconstructed using iterative algorithms with all corrections enabled. Dynamic range was defined as the maximum activity in the myocardial wall with less than 10% bias, from which corresponding dead-time, counting rates, and/or injected activity limits were established for each scanner. Scatter correction residual bias was estimated as the maximum cavity blood-to-myocardium activity ratio. Image quality was assessed via the coefficient of variation measuring nonuniformity of the left ventricular myocardium activity distribution. Maximum recommended injected activity/body weight, peak dead-time correction factor, counting rates, and residual scatter bias for accurate cardiac myocardial blood flow imaging were 3-14 MBq/kg, 1.5-4.0, 22-64 Mcps singles and 4-14 Mcps prompt coincidence counting rates, and 2%-10% on the investigated scanners. Nonuniformity of the myocardial activity distribution varied from 3% to 16%. Accurate dynamic imaging is possible on the 10 3D PET systems if the maximum injected MBq/kg values are respected to limit peak dead-time losses during the bolus first-pass transit. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Predicting the occurrence of channelized debris flow by an integrated cascading model: A case study of a small debris flow-prone catchment in Zhejiang Province, China

NASA Astrophysics Data System (ADS)

Wei, Zhen-lei; Xu, Yue-Ping; Sun, Hong-yue; Xie, Wei; Wu, Gang

2018-05-01

Excessive water in a channel is an important factor that triggers channelized debris flows. Floods and debris flows often occur in a cascading manner, and thus, calculating the amount of runoff accurately is important for predicting the occurrence of debris flows. In order to explore the runoff-rainfall relationship, we placed two measuring facilities at the outlet of a small, debris flow-prone headwater catchment to explore the hydrological response of the catchment. The runoff responses generally consisted of a rapid increase in runoff followed by a slower decrease. The peak runoff often occurred after the rainfall ended. The runoff discharge data were simulated by two different modeling approaches, i.e., the NAM model and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. The results showed that the NAM model performed better than the HEC-HMS model. The NAM model provided acceptable simulations, while the HEC-HMS model did not. Then, we coupled the calculated results of the NAM model with an empirically based debris flow initiation model to obtain a new integrated cascading disaster modeling system to provide improved disaster preparedness and hazard management. In this case study, we found that the coupled model could correctly predict the occurrence of debris flows. Furthermore, we evaluated the effect of the range of input parameter values on the hydrographical shape of the runoff. We also used the grey relational analysis to conduct a sensitivity analysis of the parameters of the model. This study highlighted the important connections between rainfall, hydrological processes, and debris flow, and it provides a useful prototype model system for operational forecasting of debris flows.

Validating Whole-Airway CFD Predictions of DPI Aerosol Deposition at Multiple Flow Rates

PubMed Central

Tian, Geng; Khajeh-Hosseini-Dalasm, Navvab; Hindle, Michael

2016-01-01

Abstract Background: The objective of this study was to compare aerosol deposition predictions of a new whole-airway CFD model with available in vivo data for a dry powder inhaler (DPI) considered across multiple inhalation waveforms, which affect both the particle size distribution (PSD) and particle deposition. Methods: The Novolizer DPI with a budesonide formulation was selected based on the availability of 2D gamma scintigraphy data in humans for three different well-defined inhalation waveforms. Initial in vitro cascade impaction experiments were conducted at multiple constant (square-wave) particle sizing flow rates to characterize PSDs. The whole-airway CFD modeling approach implemented the experimentally determined PSDs at the point of aerosol formation in the inhaler. Complete characteristic airway geometries for an adult were evaluated through the lobar bronchi, followed by stochastic individual pathway (SIP) approximations through the tracheobronchial region and new acinar moving wall models of the alveolar region. Results: It was determined that the PSD used for each inhalation waveform should be based on a constant particle sizing flow rate equal to the average of the inhalation waveform's peak inspiratory flow rate (PIFR) and mean flow rate [i.e., AVG(PIFR, Mean)]. Using this technique, agreement with the in vivo data was acceptable with <15% relative differences averaged across the three regions considered for all inhalation waveforms. Defining a peripheral to central deposition ratio (P/C) based on alveolar and tracheobronchial compartments, respectively, large flow-rate-dependent differences were observed, which were not evident in the original 2D in vivo data. Conclusions: The agreement between the CFD predictions and in vivo data was dependent on accurate initial estimates of the PSD, emphasizing the need for a combination in vitro–in silico approach. Furthermore, use of the AVG(PIFR, Mean) value was identified as a potentially useful method

Prediction of Transitional Flows in the Low Pressure Turbine

NASA Technical Reports Server (NTRS)

Huang, George; Xiong, Guohua

1998-01-01

Current turbulence models tend to give too early and too short a length of flow transition to turbulence, and hence fail to predict flow separation induced by the adverse pressure gradients and streamline flow curvatures. Our discussion will focus on the development and validation of transition models. The baseline data for model comparisons are the T3 series, which include a range of free-stream turbulence intensity and cover zero-pressure gradient to aft-loaded turbine pressure gradient flows. The method will be based on the conditioned N-S equations and a transport equation for the intermittency factor. First, several of the most popular 2-equation models in predicting flow transition are examined: k-e [Launder-Sharina], k-w [Wilcox], Lien-Leschiziner and SST [Menter] models. All models fail to predict the onset and the length of transition, even for the simplest flat plate with zero-pressure gradient(T3A). Although the predicted onset position of transition can be varied by providing different inlet turbulent energy dissipation rates, the appropriate inlet conditions for turbulence quantities should be adjusted to match the decay of the free-stream turbulence. Arguably, one may adjust the low-Reynolds-number part of the model to predict transition. This approach has so far not been very successful. However, we have found that the low-Reynolds-number model of Launder and Sharma [1974], which is an improved version of Jones and Launder [1972] gave the best overall performance. The Launder and Sharma model was designed to capture flow re-laminarization (a reverse of flow transition), but tends to give rise to a too early and too fast transition in comparison with the physical transition. The three test cases were for flows with zero pressure gradient but with different free-stream turbulent intensities. The same can be said about the model when considering flows subject to pressure gradient(T3C1). To capture the effects of transition using existing turbulence

Predicting debris-flow initiation and run-out with a depth-averaged two-phase model and adaptive numerical methods

NASA Astrophysics Data System (ADS)

George, D. L.; Iverson, R. M.

2012-12-01

Numerically simulating debris-flow motion presents many challenges due to the complicated physics of flowing granular-fluid mixtures, the diversity of spatial scales (ranging from a characteristic particle size to the extent of the debris flow deposit), and the unpredictability of the flow domain prior to a simulation. Accurately predicting debris-flows requires models that are complex enough to represent the dominant effects of granular-fluid interaction, while remaining mathematically and computationally tractable. We have developed a two-phase depth-averaged mathematical model for debris-flow initiation and subsequent motion. Additionally, we have developed software that numerically solves the model equations efficiently on large domains. A unique feature of the mathematical model is that it includes the feedback between pore-fluid pressure and the evolution of the solid grain volume fraction, a process that regulates flow resistance. This feature endows the model with the ability to represent the transition from a stationary mass to a dynamic flow. With traditional approaches, slope stability analysis and flow simulation are treated separately, and the latter models are often initialized with force balances that are unrealistically far from equilibrium. Additionally, our new model relies on relatively few dimensionless parameters that are functions of well-known material properties constrained by physical data (eg. hydraulic permeability, pore-fluid viscosity, debris compressibility, Coulomb friction coefficient, etc.). We have developed numerical methods and software for accurately solving the model equations. By employing adaptive mesh refinement (AMR), the software can efficiently resolve an evolving debris flow as it advances through irregular topography, without needing terrain-fit computational meshes. The AMR algorithms utilize multiple levels of grid resolutions, so that computationally inexpensive coarse grids can be used where the flow is absent, and

Ensemble predictive model for more accurate soil organic carbon spectroscopic estimation

NASA Astrophysics Data System (ADS)

Vašát, Radim; Kodešová, Radka; Borůvka, Luboš

2017-07-01

A myriad of signal pre-processing strategies and multivariate calibration techniques has been explored in attempt to improve the spectroscopic prediction of soil organic carbon (SOC) over the last few decades. Therefore, to come up with a novel, more powerful, and accurate predictive approach to beat the rank becomes a challenging task. However, there may be a way, so that combine several individual predictions into a single final one (according to ensemble learning theory). As this approach performs best when combining in nature different predictive algorithms that are calibrated with structurally different predictor variables, we tested predictors of two different kinds: 1) reflectance values (or transforms) at each wavelength and 2) absorption feature parameters. Consequently we applied four different calibration techniques, two per each type of predictors: a) partial least squares regression and support vector machines for type 1, and b) multiple linear regression and random forest for type 2. The weights to be assigned to individual predictions within the ensemble model (constructed as a weighted average) were determined by an automated procedure that ensured the best solution among all possible was selected. The approach was tested at soil samples taken from surface horizon of four sites differing in the prevailing soil units. By employing the ensemble predictive model the prediction accuracy of SOC improved at all four sites. The coefficient of determination in cross-validation (R2cv) increased from 0.849, 0.611, 0.811 and 0.644 (the best individual predictions) to 0.864, 0.650, 0.824 and 0.698 for Site 1, 2, 3 and 4, respectively. Generally, the ensemble model affected the final prediction so that the maximal deviations of predicted vs. observed values of the individual predictions were reduced, and thus the correlation cloud became thinner as desired.

Towards First Principles-Based Prediction of Highly Accurate Electrochemical Pourbaix Diagrams

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

Zeng, Zhenhua; Chan, Maria K. Y.; Zhao, Zhi-Jian

2015-08-13

Electrochemical potential/pH (Pourbaix) diagrams underpin many aqueous electrochemical processes and are central to the identification of stable phases of metals for processes ranging from electrocatalysis to corrosion. Even though standard DFT calculations are potentially powerful tools for the prediction of such diagrams, inherent errors in the description of transition metal (hydroxy)oxides, together with neglect of van der Waals interactions, have limited the reliability of such predictions for even the simplest pure metal bulk compounds, and corresponding predictions for more complex alloy or surface structures are even more challenging. In the present work, through synergistic use of a Hubbard U correction,more » a state-of-the-art dispersion correction, and a water-based bulk reference state for the calculations, these errors are systematically corrected. The approach describes the weak binding that occurs between hydroxyl-containing functional groups in certain compounds in Pourbaix diagrams, corrects for self-interaction errors in transition metal compounds, and reduces residual errors on oxygen atoms by preserving a consistent oxidation state between the reference state, water, and the relevant bulk phases. The strong performance is illustrated on a series of bulk transition metal (Mn, Fe, Co and Ni) hydroxides, oxyhydroxides, binary, and ternary oxides, where the corresponding thermodynamics of redox and (de)hydration are described with standard errors of 0.04 eV per (reaction) formula unit. The approach further preserves accurate descriptions of the overall thermodynamics of electrochemically-relevant bulk reactions, such as water formation, which is an essential condition for facilitating accurate analysis of reaction energies for electrochemical processes on surfaces. The overall generality and transferability of the scheme suggests that it may find useful application in the construction of a broad array of electrochemical phase diagrams, including

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.

Transonic cascade flow prediction using the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Arnone, A.; Stecco, S. S.

1991-01-01

This paper presents results which summarize the work carried out during the last three years to improve the efficiency and accuracy of numerical predictions in turbomachinery flow calculations. A new kind of nonperiodic c-type grid is presented and a Runge-Kutta scheme with accelerating strategies is used as a flow solver. The code capability is presented by testing four different blades at different exit Mach numbers in transonic regimes. Comparison with experiments shows the very good reliability of the numerical prediction. In particular, the loss coefficient seems to be correctly predicted by using the well-known Baldwin-Lomax turbulence model.

Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals.

PubMed

Doré, Bruce P; Meksin, Robert; Mather, Mara; Hirst, William; Ochsner, Kevin N

2016-06-01

In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting (a) the overall intensity of their future negative emotion, and (b) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals

PubMed Central

Doré, B.P.; Meksin, R.; Mather, M.; Hirst, W.; Ochsner, K.N

2016-01-01

In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting 1) the overall intensity of their future negative emotion, and 2) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. PMID:27100309

High Order Schemes in Bats-R-US for Faster and More Accurate Predictions

NASA Astrophysics Data System (ADS)

Chen, Y.; Toth, G.; Gombosi, T. I.

2014-12-01

BATS-R-US is a widely used global magnetohydrodynamics model that originally employed second order accurate TVD schemes combined with block based Adaptive Mesh Refinement (AMR) to achieve high resolution in the regions of interest. In the last years we have implemented fifth order accurate finite difference schemes CWENO5 and MP5 for uniform Cartesian grids. Now the high order schemes have been extended to generalized coordinates, including spherical grids and also to the non-uniform AMR grids including dynamic regridding. We present numerical tests that verify the preservation of free-stream solution and high-order accuracy as well as robust oscillation-free behavior near discontinuities. We apply the new high order accurate schemes to both heliospheric and magnetospheric simulations and show that it is robust and can achieve the same accuracy as the second order scheme with much less computational resources. This is especially important for space weather prediction that requires faster than real time code execution.

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

NASA Astrophysics Data System (ADS)

Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán

2014-11-01

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.

Debris-flow runout predictions based on the average channel slope (ACS)

USGS Publications Warehouse

Prochaska, A.B.; Santi, P.M.; Higgins, J.D.; Cannon, S.H.

2008-01-01

Prediction of the runout distance of a debris flow is an important element in the delineation of potentially hazardous areas on alluvial fans and for the siting of mitigation structures. Existing runout estimation methods rely on input parameters that are often difficult to estimate, including volume, velocity, and frictional factors. In order to provide a simple method for preliminary estimates of debris-flow runout distances, we developed a model that provides runout predictions based on the average channel slope (ACS model) for non-volcanic debris flows that emanate from confined channels and deposit on well-defined alluvial fans. This model was developed from 20 debris-flow events in the western United States and British Columbia. Based on a runout estimation method developed for snow avalanches, this model predicts debris-flow runout as an angle of reach from a fixed point in the drainage channel to the end of the runout zone. The best fixed point was found to be the mid-point elevation of the drainage channel, measured from the apex of the alluvial fan to the top of the drainage basin. Predicted runout lengths were more consistent than those obtained from existing angle-of-reach estimation methods. Results of the model compared well with those of laboratory flume tests performed using the same range of channel slopes. The robustness of this model was tested by applying it to three debris-flow events not used in its development: predicted runout ranged from 82 to 131% of the actual runout for these three events. Prediction interval multipliers were also developed so that the user may calculate predicted runout within specified confidence limits. ?? 2008 Elsevier B.V. All rights reserved.

The Space-Time Conservative Schemes for Large-Scale, Time-Accurate Flow Simulations with Tetrahedral Meshes

NASA Technical Reports Server (NTRS)

Venkatachari, Balaji Shankar; Streett, Craig L.; Chang, Chau-Lyan; Friedlander, David J.; Wang, Xiao-Yen; Chang, Sin-Chung

2016-01-01

Despite decades of development of unstructured mesh methods, high-fidelity time-accurate simulations are still predominantly carried out on structured, or unstructured hexahedral meshes by using high-order finite-difference, weighted essentially non-oscillatory (WENO), or hybrid schemes formed by their combinations. In this work, the space-time conservation element solution element (CESE) method is used to simulate several flow problems including supersonic jet/shock interaction and its impact on launch vehicle acoustics, and direct numerical simulations of turbulent flows using tetrahedral meshes. This paper provides a status report for the continuing development of the space-time conservation element solution element (CESE) numerical and software framework under the Revolutionary Computational Aerosciences (RCA) project. Solution accuracy and large-scale parallel performance of the numerical framework is assessed with the goal of providing a viable paradigm for future high-fidelity flow physics simulations.

Accurate high-throughput structure mapping and prediction with transition metal ion FRET

PubMed Central

Yu, Xiaozhen; Wu, Xiongwu; Bermejo, Guillermo A.; Brooks, Bernard R.; Taraska, Justin W.

2013-01-01

Mapping the landscape of a protein’s conformational space is essential to understanding its functions and regulation. The limitations of many structural methods have made this process challenging for most proteins. Here, we report that transition metal ion FRET (tmFRET) can be used in a rapid, highly parallel screen, to determine distances from multiple locations within a protein at extremely low concentrations. The distances generated through this screen for the protein Maltose Binding Protein (MBP) match distances from the crystal structure to within a few angstroms. Furthermore, energy transfer accurately detects structural changes during ligand binding. Finally, fluorescence-derived distances can be used to guide molecular simulations to find low energy states. Our results open the door to rapid, accurate mapping and prediction of protein structures at low concentrations, in large complex systems, and in living cells. PMID:23273426

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.

A Time-Accurate Upwind Unstructured Finite Volume Method for Compressible Flow with Cure of Pathological Behaviors

NASA Technical Reports Server (NTRS)

Loh, Ching Y.; Jorgenson, Philip C. E.

2007-01-01

A time-accurate, upwind, finite volume method for computing compressible flows on unstructured grids is presented. The method is second order accurate in space and time and yields high resolution in the presence of discontinuities. For efficiency, the Roe approximate Riemann solver with an entropy correction is employed. In the basic Euler/Navier-Stokes scheme, many concepts of high order upwind schemes are adopted: the surface flux integrals are carefully treated, a Cauchy-Kowalewski time-stepping scheme is used in the time-marching stage, and a multidimensional limiter is applied in the reconstruction stage. However even with these up-to-date improvements, the basic upwind scheme is still plagued by the so-called "pathological behaviors," e.g., the carbuncle phenomenon, the expansion shock, etc. A solution to these limitations is presented which uses a very simple dissipation model while still preserving second order accuracy. This scheme is referred to as the enhanced time-accurate upwind (ETAU) scheme in this paper. The unstructured grid capability renders flexibility for use in complex geometry; and the present ETAU Euler/Navier-Stokes scheme is capable of handling a broad spectrum of flow regimes from high supersonic to subsonic at very low Mach number, appropriate for both CFD (computational fluid dynamics) and CAA (computational aeroacoustics). Numerous examples are included to demonstrate the robustness of the methods.

Numerical prediction of 3-D ejector flows

NASA Technical Reports Server (NTRS)

Roberts, D. W.; Paynter, G. C.

1979-01-01

The use of parametric flow analysis, rather than parametric scale testing, to support the design of an ejector system offers a number of potential advantages. The application of available 3-D flow analyses to the design ejectors can be subdivided into several key elements. These are numerics, turbulence modeling, data handling and display, and testing in support of analysis development. Experimental and predicted jet exhaust for the Boeing 727 aircraft are examined.

Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers.

PubMed

Lundegaard, Claus; Lund, Ole; Nielsen, Morten

2008-06-01

Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate binding affinity prediction of peptides of length 8, 10 and 11. The method gives the opportunity to predict peptides with a different length than nine for MHC alleles where no such peptides have been measured. As validation, the performance of this approach is compared to predictors trained on peptides of the peptide length in question. In this validation, the approximation method has an accuracy that is comparable to or better than methods trained on a peptide length identical to the predicted peptides. The algorithm has been implemented in the web-accessible servers NetMHC-3.0: http://www.cbs.dtu.dk/services/NetMHC-3.0, and NetMHCpan-1.1: http://www.cbs.dtu.dk/services/NetMHCpan-1.1

On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow

NASA Astrophysics Data System (ADS)

Xu, M.; van Overloop, P. J.; van de Giesen, N. C.

2011-02-01

Model predictive control (MPC) of open channel flow is becoming an important tool in water management. The complexity of the prediction model has a large influence on the MPC application in terms of control effectiveness and computational efficiency. The Saint-Venant equations, called SV model in this paper, and the Integrator Delay (ID) model are either accurate but computationally costly, or simple but restricted to allowed flow changes. In this paper, a reduced Saint-Venant (RSV) model is developed through a model reduction technique, Proper Orthogonal Decomposition (POD), on the SV equations. The RSV model keeps the main flow dynamics and functions over a large flow range but is easier to implement in MPC. In the test case of a modeled canal reach, the number of states and disturbances in the RSV model is about 45 and 16 times less than the SV model, respectively. The computational time of MPC with the RSV model is significantly reduced, while the controller remains effective. Thus, the RSV model is a promising means to balance the control effectiveness and computational efficiency.

Spatial adaption procedures on unstructured meshes for accurate unsteady aerodynamic flow computation

NASA Technical Reports Server (NTRS)

Rausch, Russ D.; Batina, John T.; Yang, Henry T. Y.

1991-01-01

Spatial adaption procedures for the accurate and efficient solution of steady and unsteady inviscid flow problems are described. The adaption procedures were developed and implemented within a two-dimensional unstructured-grid upwind-type Euler code. These procedures involve mesh enrichment and mesh coarsening to either add points in a high gradient region or the flow or remove points where they are not needed, respectively, to produce solutions of high spatial accuracy at minimal computational costs. A detailed description is given of the enrichment and coarsening procedures and comparisons with alternative results and experimental data are presented to provide an assessment of the accuracy and efficiency of the capability. Steady and unsteady transonic results, obtained using spatial adaption for the NACA 0012 airfoil, are shown to be of high spatial accuracy, primarily in that the shock waves are very sharply captured. The results were obtained with a computational savings of a factor of approximately fifty-three for a steady case and as much as twenty-five for the unsteady cases.

Spatial adaption procedures on unstructured meshes for accurate unsteady aerodynamic flow computation

NASA Technical Reports Server (NTRS)

Rausch, Russ D.; Yang, Henry T. Y.; Batina, John T.

1991-01-01

Spatial adaption procedures for the accurate and efficient solution of steady and unsteady inviscid flow problems are described. The adaption procedures were developed and implemented within a two-dimensional unstructured-grid upwind-type Euler code. These procedures involve mesh enrichment and mesh coarsening to either add points in high gradient regions of the flow or remove points where they are not needed, respectively, to produce solutions of high spatial accuracy at minimal computational cost. The paper gives a detailed description of the enrichment and coarsening procedures and presents comparisons with alternative results and experimental data to provide an assessment of the accuracy and efficiency of the capability. Steady and unsteady transonic results, obtained using spatial adaption for the NACA 0012 airfoil, are shown to be of high spatial accuracy, primarily in that the shock waves are very sharply captured. The results were obtained with a computational savings of a factor of approximately fifty-three for a steady case and as much as twenty-five for the unsteady cases.

Capabilities of current wildfire models when simulating topographical flow

NASA Astrophysics Data System (ADS)

Kochanski, A.; Jenkins, M.; Krueger, S. K.; McDermott, R.; Mell, W.

2009-12-01

Accurate predictions of the growth, spread and suppression of wild fires rely heavily on the correct prediction of the local wind conditions and the interactions between the fire and the local ambient airflow. Resolving local flows, often strongly affected by topographical features like hills, canyons and ridges, is a prerequisite for accurate simulation and prediction of fire behaviors. In this study, we present the results of high-resolution numerical simulations of the flow over a smooth hill, performed using (1) the NIST WFDS (WUI or Wildland-Urban-Interface version of the FDS or Fire Dynamic Simulator), and (2) the LES version of the NCAR Weather Research and Forecasting (WRF-LES) model. The WFDS model is in the initial stages of development for application to wind flow and fire spread over complex terrain. The focus of the talk is to assess how well simple topographical flow is represented by WRF-LES and the current version of WFDS. If sufficient progress has been made prior to the meeting then the importance of the discrepancies between the predicted and measured winds, in terms of simulated fire behavior, will be examined.

A highly accurate symmetric optical flow based high-dimensional nonlinear spatial normalization of brain images.

PubMed

Wen, Ying; Hou, Lili; He, Lianghua; Peterson, Bradley S; Xu, Dongrong

2015-05-01

Spatial normalization plays a key role in voxel-based analyses of brain images. We propose a highly accurate algorithm for high-dimensional spatial normalization of brain images based on the technique of symmetric optical flow. We first construct a three dimension optical model with the consistency assumption of intensity and consistency of the gradient of intensity under a constraint of discontinuity-preserving spatio-temporal smoothness. Then, an efficient inverse consistency optical flow is proposed with aims of higher registration accuracy, where the flow is naturally symmetric. By employing a hierarchical strategy ranging from coarse to fine scales of resolution and a method of Euler-Lagrange numerical analysis, our algorithm is capable of registering brain images data. Experiments using both simulated and real datasets demonstrated that the accuracy of our algorithm is not only better than that of those traditional optical flow algorithms, but also comparable to other registration methods used extensively in the medical imaging community. Moreover, our registration algorithm is fully automated, requiring a very limited number of parameters and no manual intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

Can phenological models predict tree phenology accurately in the future? The unrevealed hurdle of endodormancy break.

PubMed

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2016-10-01

The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.

How accurate is our clinical prediction of "minimal prostate cancer"?

PubMed

Leibovici, Dan; Shikanov, Sergey; Gofrit, Ofer N; Zagaja, Gregory P; Shilo, Yaniv; Shalhav, Arieh L

2013-07-01

Recommendations for active surveillance versus immediate treatment for low risk prostate cancer are based on biopsy and clinical data, assuming that a low volume of well-differentiated carcinoma will be associated with a low progression risk. However, the accuracy of clinical prediction of minimal prostate cancer (MPC) is unclear. To define preoperative predictors for MPC in prostatectomy specimens and to examine the accuracy of such prediction. Data collected on 1526 consecutive radical prostatectomy patients operated in a single center between 2003 and 2008 included: age, body mass index, preoperative prostate-specific antigen level, biopsy Gleason score, clinical stage, percentage of positive biopsy cores, and maximal core length (MCL) involvement. MPC was defined as < 5% of prostate volume involvement with organ-confined Gleason score < or = 6. Univariate and multivariate logistic regression analyses were used to define independent predictors of minimal disease. Classification and Regression Tree (CART) analysis was used to define cutoff values for the predictors and measure the accuracy of prediction. MPC was found in 241 patients (15.8%). Clinical stage, biopsy Gleason's score, percent of positive biopsy cores, and maximal involved core length were associated with minimal disease (OR 0.42, 0.1, 0.92, and 0.9, respectively). Independent predictors of MPC included: biopsy Gleason score, percent of positive cores and MCL (OR 0.21, 095 and 0.95, respectively). CART showed that when the MCL exceeded 11.5%, the likelihood of MPC was 3.8%. Conversely, when applying the most favorable preoperative conditions (Gleason < or = 6, < 20% positive cores, MCL < or = 11.5%) the chance of minimal disease was 41%. Biopsy Gleason score, the percent of positive cores and MCL are independently associated with MPC. While preoperative prediction of significant prostate cancer was accurate, clinical prediction of MPC was incorrect 59% of the time. Caution is necessary when

Confined turbulent swirling recirculating flow predictions. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Abujelala, M. T.; Lilley, D. G.

1985-01-01

The capability and the accuracy of the STARPIC computer code in predicting confined turbulent swirling recirculating flows is presented. Inlet flow boundary conditions were demonstrated to be extremely important in simulating a flowfield via numerical calculations. The degree of swirl strength and expansion ratio have strong effects on the characteristics of swirling flow. In a nonswirling flow, a large corner recirculation zone exists in the flowfield with an expansion ratio greater than one. However, as the degree of inlet swirl increases, the size of this zone decreases and a central recirculation zone appears near the inlet. Generally, the size of the central zone increased with swirl strength and expansion ratio. Neither the standard k-epsilon turbulence mode nor its previous extensions show effective capability for predicting confined turbulent swirling recirculating flows. However, either reduced optimum values of three parameters in the mode or the empirical C sub mu formulation obtained via careful analysis of available turbulence measurements, can provide more acceptable accuracy in the prediction of these swirling flows.

Prediction of vortex shedding from circular and noncircular bodies in supersonic flow

NASA Technical Reports Server (NTRS)

Mendenhall, M. R.; Perkins, S. C., Jr.

1984-01-01

An engineering prediction method and associated computer code NOZVTX to predict nose vortex shedding from circular and noncircular bodies in supersonic flow at angles of attack and roll are presented. The body is represented by either a supersonic panel method for noncircular cross sections or line sources and doublets for circular cross sections, and the lee side vortex wake is modeled by discrete vortices in crossflow planes. The three-dimensional steady flow problem is reduced to a two-dimensional, unsteady, separated flow problem for solution. Comparison of measured and predicted surface pressure distributions, flow field surveys, and aerodynamic characteristics is presented for bodies with circular and noncircular cross-sectional shapes.

Accurate Descriptions of Hot Flow Behaviors Across β Transus of Ti-6Al-4V Alloy by Intelligence Algorithm GA-SVR

NASA Astrophysics Data System (ADS)

Wang, Li-yong; Li, Le; Zhang, Zhi-hua

2016-09-01

Hot compression tests of Ti-6Al-4V alloy in a wide temperature range of 1023-1323 K and strain rate range of 0.01-10 s-1 were conducted by a servo-hydraulic and computer-controlled Gleeble-3500 machine. In order to accurately and effectively characterize the highly nonlinear flow behaviors, support vector regression (SVR) which is a machine learning method was combined with genetic algorithm (GA) for characterizing the flow behaviors, namely, the GA-SVR. The prominent character of GA-SVR is that it with identical training parameters will keep training accuracy and prediction accuracy at a stable level in different attempts for a certain dataset. The learning abilities, generalization abilities, and modeling efficiencies of the mathematical regression model, ANN, and GA-SVR for Ti-6Al-4V alloy were detailedly compared. Comparison results show that the learning ability of the GA-SVR is stronger than the mathematical regression model. The generalization abilities and modeling efficiencies of these models were shown as follows in ascending order: the mathematical regression model < ANN < GA-SVR. The stress-strain data outside experimental conditions were predicted by the well-trained GA-SVR, which improved simulation accuracy of the load-stroke curve and can further improve the related research fields where stress-strain data play important roles, such as speculating work hardening and dynamic recovery, characterizing dynamic recrystallization evolution, and improving processing maps.

Improving catchment discharge predictions by inferring flow route contributions from a nested-scale monitoring and model setup

NASA Astrophysics Data System (ADS)

van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.; van Geer, F. C.; Torfs, P. J. J. F.; de Louw, P. G. B.

2011-03-01

Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for the estimation of flow route volumes and for predictions of catchment discharge. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km2) and simple process descriptions were applied to relate groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from the hydrographs of two nested catchments (0.4 and 6.5 km2). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% and 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements improves simulations of nitrate loads and predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.

Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space

DOE PAGES

Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; ...

2015-06-04

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstratemore » prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.« less

Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

PubMed Central

2015-01-01

Simultaneously accurate and efficient prediction of molecular properties throughout chemical compound space is a critical ingredient toward rational compound design in chemical and pharmaceutical industries. Aiming toward this goal, we develop and apply a systematic hierarchy of efficient empirical methods to estimate atomization and total energies of molecules. These methods range from a simple sum over atoms, to addition of bond energies, to pairwise interatomic force fields, reaching to the more sophisticated machine learning approaches that are capable of describing collective interactions between many atoms or bonds. In the case of equilibrium molecular geometries, even simple pairwise force fields demonstrate prediction accuracy comparable to benchmark energies calculated using density functional theory with hybrid exchange-correlation functionals; however, accounting for the collective many-body interactions proves to be essential for approaching the “holy grail” of chemical accuracy of 1 kcal/mol for both equilibrium and out-of-equilibrium geometries. This remarkable accuracy is achieved by a vectorized representation of molecules (so-called Bag of Bonds model) that exhibits strong nonlocality in chemical space. In addition, the same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies. PMID:26113956

Debris flow hazards mitigation--Mechanics, prediction, and assessment

USGS Publications Warehouse

Chen, C.-L.; Major, J.J.

2007-01-01

These proceedings contain papers presented at the Fourth International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment held in Chengdu, China, September 10-13, 2007. The papers cover a wide range of topics on debris-flow science and engineering, including the factors triggering debris flows, geomorphic effects, mechanics of debris flows (e.g., rheology, fluvial mechanisms, erosion and deposition processes), numerical modeling, various debris-flow experiments, landslide-induced debris flows, assessment of debris-flow hazards and risk, field observations and measurements, monitoring and alert systems, structural and non-structural countermeasures against debris-flow hazards and case studies. The papers reflect the latest devel-opments and advances in debris-flow research. Several studies discuss the development and appli-cation of Geographic Information System (GIS) and Remote Sensing (RS) technologies in debris-flow hazard/risk assessment. Timely topics presented in a few papers also include the development of new or innovative techniques for debris-flow monitoring and alert systems, especially an infra-sound acoustic sensor for detecting debris flows. Many case studies illustrate a wide variety of debris-flow hazards and related phenomena as well as their hazardous effects on human activities and settlements.

Prediction of Ablation Rates from Solid Surfaces Exposed to High Temperature Gas Flow

NASA Technical Reports Server (NTRS)

Akyuzlu, Kazim M.; Coote, David

2013-01-01

A mathematical model and a solution algorithm is developed to study the physics of high temperature heat transfer and material ablation and identify the problems associated with the flow of hydrogen gas at very high temperatures and velocities through pipes and various components of Nuclear Thermal Rocket (NTR) motors. Ablation and melting can be experienced when the inner solid surface of the cooling channels and the diverging-converging nozzle of a Nuclear Thermal Rocket (NTR) motor is exposed to hydrogen gas flow at temperatures around 2500 degrees Kelvin and pressures around 3.4 MPa. In the experiments conducted on typical NTR motors developed in 1960s, degradation of the cooling channel material (cracking in the nuclear fuel element cladding) and in some instances melting of the core was observed. This paper presents the results of a preliminary study based on two types of physics based mathematical models that were developed to simulate the thermal-hydrodynamic conditions that lead to ablation of the solid surface of a stainless steel pipe exposed to high temperature hydrogen gas near sonic velocities. One of the proposed models is one-dimensional and assumes the gas flow to be unsteady, compressible and viscous. An in-house computer code was developed to solve the conservations equations of this model using a second-order accurate finite-difference technique. The second model assumes the flow to be three-dimensional, unsteady, compressible and viscous. A commercial CFD code (Fluent) was used to solve the later model equations. Both models assume the thermodynamic and transport properties of the hydrogen gas to be temperature dependent. In the solution algorithm developed for this study, the unsteady temperature of the pipe is determined from the heat equation for the solid. The solid-gas interface temperature is determined from an energy balance at the interface which includes heat transfer from or to the interface by conduction, convection, radiation, and

Predicting the Agglomeration of Cohesive Particles in a Gas-Solid Flow and its Effect on the Solids Flow

NASA Astrophysics Data System (ADS)

Kellogg, Kevin; Liu, Peiyuan; Lamarche, Casey; Hrenya, Christine

2017-11-01

In flows of cohesive particles, agglomerates will readily form and break. These agglomerates are expected to complicate how particles interact with the surrounding fluid in multiphase flows, and consequently how the solids flow. In this work, a dilute flow of particles driven by gas against gravity is studied. A continuum framework, composed of a population balance to predict the formation of agglomerates, and kinetic-theory-based balances, is used to predict the flow of particles. The closures utilized for the birth and death rates due to aggregation and breakage in the population balance take into account how the impact velocity (the granular temperature) affects the outcome of a collision as aggregation, rebound, or breakage. The agglomerate size distribution and solids velocity predicted by the continuum framework are compared to discrete element method (DEM) simulations, as well to experimental results of particles being entrained from the riser of a fluidized bed. Dow Corning Corporation.

How accurate are resting energy expenditure prediction equations in obese trauma and burn patients?

PubMed

Stucky, Chee-Chee H; Moncure, Michael; Hise, Mary; Gossage, Clint M; Northrop, David

2008-01-01

While the prevalence of obesity continues to increase in our society, outdated resting energy expenditure (REE) prediction equations may overpredict energy requirements in obese patients. Accurate feeding is essential since overfeeding has been demonstrated to adversely affect outcomes. The first objective was to compare REE calculated by prediction equations to the measured REE in obese trauma and burn patients. Our hypothesis was that an equation using fat-free mass would give a more accurate prediction. The second objective was to consider the effect of a commonly used injury factor on the predicted REE. A retrospective chart review was performed on 28 patients. REE was measured using indirect calorimetry and compared with the Harris-Benedict and Cunningham equations, and an equation using type II diabetes as a factor. Statistical analyses used were paired t test, +/-95% confidence interval, and the Bland-Altman method. Measured average REE in trauma and burn patients was 21.37 +/- 5.26 and 21.81 +/- 3.35 kcal/kg/d, respectively. Harris-Benedict underpredicted REE in trauma and burn patients to the least extent, while the Cunningham equation underpredicted REE in both populations to the greatest extent. Using an injury factor of 1.2, Cunningham continued to underestimate REE in both populations, while the Harris-Benedict and Diabetic equations overpredicted REE in both populations. The measured average REE is significantly less than current guidelines. This finding suggests that a hypocaloric regimen is worth considering for ICU patients. Also, if an injury factor of 1.2 is incorporated in certain equations, patients may be given too many calories.

Prediction of Complex Aerodynamic Flows with Explicit Algebraic Stress Models

NASA Technical Reports Server (NTRS)

Abid, Ridha; Morrison, Joseph H.; Gatski, Thomas B.; Speziale, Charles G.

1996-01-01

An explicit algebraic stress equation, developed by Gatski and Speziale, is used in the framework of K-epsilon formulation to predict complex aerodynamic turbulent flows. The nonequilibrium effects are modeled through coefficients that depend nonlinearly on both rotational and irrotational strains. The proposed model was implemented in the ISAAC Navier-Stokes code. Comparisons with the experimental data are presented which clearly demonstrate that explicit algebraic stress models can predict the correct response to nonequilibrium flow.

ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers

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

Visel, Axel; Blow, Matthew J.; Li, Zirong

2009-02-01

A major yet unresolved quest in decoding the human genome is the identification of the regulatory sequences that control the spatial and temporal expression of genes. Distant-acting transcriptional enhancers are particularly challenging to uncover since they are scattered amongst the vast non-coding portion of the genome. Evolutionary sequence constraint can facilitate the discovery of enhancers, but fails to predict when and where they are active in vivo. Here, we performed chromatin immunoprecipitation with the enhancer-associated protein p300, followed by massively-parallel sequencing, to map several thousand in vivo binding sites of p300 in mouse embryonic forebrain, midbrain, and limb tissue. Wemore » tested 86 of these sequences in a transgenic mouse assay, which in nearly all cases revealed reproducible enhancer activity in those tissues predicted by p300 binding. Our results indicate that in vivo mapping of p300 binding is a highly accurate means for identifying enhancers and their associated activities and suggest that such datasets will be useful to study the role of tissue-specific enhancers in human biology and disease on a genome-wide scale.« less

Wave Current Interactions and Wave-blocking Predictions Using NHWAVE Model

DTIC Science & Technology

2013-03-01

Navier-Stokes equation. In this approach, as with previous modeling techniques, there is difficulty in simulating the free surface that inhibits accurate...hydrostatic, free - surface , rotational flows in multiple dimensions. It is useful in predicting transformations of surface waves and rapidly varied...Stelling, G., and M. Zijlema, 2003: An accurate and efficient finite-differencing algorithm for non-hydrostatic free surface flow with application to

Using magma flow indicators to infer flow dynamics in sills

NASA Astrophysics Data System (ADS)

Hoyer, Lauren; Watkeys, Michael K.

2017-03-01

Fabrics from Anisotropy of Magnetic Susceptibility (AMS) analyses and Shape Preferred Orientation (SPO) of plagioclase are compared with field structures (such as bridge structures, intrusive steps and magma lobes) formed during magma intrusion in Jurassic sills. This is to constrain magma flow directions in the sills of the Karoo Igneous Province along the KwaZulu-Natal North Coast and to show how accurately certain structures predict a magma flow sense, thus improving the understanding of the Karoo sub-volcanic dynamics. The AMS fabrics are derived from magnetite grains and are well constrained, however the SPO results are commonly steeply inclined, poorly constrained and differ to the AMS fabrics. Both techniques resulted in asymmetrical fabrics. Successful relationships were established between the AMS fabric and the long axes of the magma flow indicators, implying adequate magma flow prediction. However, where numerous sill segments merge, either in the form of magma lobes or bridge structures, the coalescence process creates a new fabric between the segments preserving late-stage magma migration between the merged segments, overprinting the initial magma flow direction.

A numerical simulation of the NFAC (National Full-scale Aerodynamics Complex) open-return wind tunnel inlet flow

NASA Technical Reports Server (NTRS)

Kaul, U. K.; Ross, J. C.; Jacocks, J. L.

1985-01-01

The flow into an open return wind tunnel inlet was simulated using Euler equations. An explicit predictor-corrector method was employed to solve the system. The calculation is time-accurate and was performed to achieve a steady-state solution. The predictions are in reasonable agreement with the experimental data. Wall pressures are accurately predicted except in a region of recirculating flow. Flow-field surveys agree qualitatively with laser velocimeter measurements. The method can be used in the design process for open return wind tunnels.

Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

PubMed Central

Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

2015-01-01

Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results

Predicted and experimental steady and unsteady transonic flows about a biconvex airfoil

NASA Technical Reports Server (NTRS)

Levy, L. L., Jr.

1981-01-01

Results of computer code time dependent solutions of the two dimensional compressible Navier-Stokes equations and the results of independent experiments are compared to verify the Mach number range for instabilities in the transonic flow field about a 14 percent thick biconvex airfoil at an angle of attack of 0 deg and a Reynolds number of 7 million. The experiments were conducted in a transonic, slotted wall wind tunnel. The computer code included an algebraic eddy viscosity turbulence model developed for steady flows, and all computations were made using free flight boundary conditions. All of the features documented experimentally for both steady and unsteady flows were predicted qualitatively; even with the above simplifications, the predictions were, on the whole, in good quantitative agreement with experiment. In particular, predicted time histories of shock wave position, surface pressures, lift, and pitching moment were found to be in very good agreement with experiment for an unsteady flow. Depending upon the free stream Mach number for steady flows, the surface pressure downstream of the shock wave or the shock wave location was not well predicted.

Improving medical decisions for incapacitated persons: does focusing on "accurate predictions" lead to an inaccurate picture?

PubMed

Kim, Scott Y H

2014-04-01

The Patient Preference Predictor (PPP) proposal places a high priority on the accuracy of predicting patients' preferences and finds the performance of surrogates inadequate. However, the quest to develop a highly accurate, individualized statistical model has significant obstacles. First, it will be impossible to validate the PPP beyond the limit imposed by 60%-80% reliability of people's preferences for future medical decisions--a figure no better than the known average accuracy of surrogates. Second, evidence supports the view that a sizable minority of persons may not even have preferences to predict. Third, many, perhaps most, people express their autonomy just as much by entrusting their loved ones to exercise their judgment than by desiring to specifically control future decisions. Surrogate decision making faces none of these issues and, in fact, it may be more efficient, accurate, and authoritative than is commonly assumed.

Predicting equilibrium states with Reynolds stress closures in channel flow and homogeneous shear flow

NASA Technical Reports Server (NTRS)

Abid, R.; Speziale, C. G.

1993-01-01

Turbulent channel flow and homogeneous shear flow have served as basic building block flows for the testing and calibration of Reynolds stress models. A direct theoretical connection is made between homogeneous shear flow in equilibrium and the log-layer of fully-developed turbulent channel flow. It is shown that if a second-order closure model is calibrated to yield good equilibrium values for homogeneous shear flow it will also yield good results for the log-layer of channel flow provided that the Rotta coefficient is not too far removed from one. Most of the commonly used second-order closure models introduce an ad hoc wall reflection term in order to mask deficient predictions for the log-layer of channel flow that arise either from an inaccurate calibration of homogeneous shear flow or from the use of a Rotta coefficient that is too large. Illustrative model calculations are presented to demonstrate this point which has important implications for turbulence modeling.

Predicting equilibrium states with Reynolds stress closures in channel flow and homogeneous shear flow

NASA Technical Reports Server (NTRS)

Abid, R.; Speziale, C. G.

1992-01-01

Turbulent channel flow and homogeneous shear flow have served as basic building block flows for the testing and calibration of Reynolds stress models. A direct theoretical connection is made between homogeneous shear flow in equilibrium and the log-layer of fully-developed turbulent channel flow. It is shown that if a second-order closure model is calibrated to yield good equilibrium values for homogeneous shear flow it will also yield good results for the log-layer of channel flow provided that the Rotta coefficient is not too far removed from one. Most of the commonly used second-order closure models introduce an ad hoc wall reflection term in order to mask deficient predictions for the log-layer of channel flow that arise either from an inaccurate calibration of homogeneous shear flow or from the use of a Rotta coefficient that is too large. Illustrative model calculations are presented to demonstrate this point which has important implications for turbulence modeling.

Rapid and accurate prediction of degradant formation rates in pharmaceutical formulations using high-performance liquid chromatography-mass spectrometry.

PubMed

Darrington, Richard T; Jiao, Jim

2004-04-01

Rapid and accurate stability prediction is essential to pharmaceutical formulation development. Commonly used stability prediction methods include monitoring parent drug loss at intended storage conditions or initial rate determination of degradants under accelerated conditions. Monitoring parent drug loss at the intended storage condition does not provide a rapid and accurate stability assessment because often <0.5% drug loss is all that can be observed in a realistic time frame, while the accelerated initial rate method in conjunction with extrapolation of rate constants using the Arrhenius or Eyring equations often introduces large errors in shelf-life prediction. In this study, the shelf life prediction of a model pharmaceutical preparation utilizing sensitive high-performance liquid chromatography-mass spectrometry (LC/MS) to directly quantitate degradant formation rates at the intended storage condition is proposed. This method was compared to traditional shelf life prediction approaches in terms of time required to predict shelf life and associated error in shelf life estimation. Results demonstrated that the proposed LC/MS method using initial rates analysis provided significantly improved confidence intervals for the predicted shelf life and required less overall time and effort to obtain the stability estimation compared to the other methods evaluated. Copyright 2004 Wiley-Liss, Inc. and the American Pharmacists Association.

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.

Effectiveness of evaluating tumor vascularization using 3D power Doppler ultrasound with high-definition flow technology in the prediction of the response to neoadjuvant chemotherapy for T2 breast cancer: a preliminary report

NASA Astrophysics Data System (ADS)

Shia, Wei-Chung; Chen, Dar-Ren; Huang, Yu-Len; Wu, Hwa-Koon; Kuo, Shou-Jen

2015-10-01

The aim of this study was to evaluate the effectiveness of advanced ultrasound (US) imaging of vascular flow and morphological features in the prediction of a pathologic complete response (pCR) and a partial response (PR) to neoadjuvant chemotherapy for T2 breast cancer. Twenty-nine consecutive patients with T2 breast cancer treated with six courses of anthracycline-based neoadjuvant chemotherapy were enrolled. Three-dimensional (3D) power Doppler US with high-definition flow (HDF) technology was used to investigate the blood flow in and morphological features of the tumors. Six vascularity quantization features, three morphological features, and two vascular direction features were selected and extracted from the US images. A support vector machine was used to evaluate the changes in vascularity after neoadjuvant chemotherapy, and pCR and PR were predicted on the basis of these changes. The most accurate prediction of pCR was achieved after the first chemotherapy cycle, with an accuracy of 93.1% and a specificity of 85.5%, while that of a PR was achieved after the second cycle, with an accuracy of 79.31% and a specificity of 72.22%. Vascularity data can be useful to predict the effects of neoadjuvant chemotherapy. Determination of changes in vascularity after neoadjuvant chemotherapy using 3D power Doppler US with HDF can generate accurate predictions of the patient response, facilitating early decision-making.

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.

Nested-scale discharge and groundwater level monitoring to improve predictions of flow route discharges and nitrate loads

NASA Astrophysics Data System (ADS)

van der Velde, Y.; Rozemeijer, J. C.; de Rooij, G. H.; van Geer, F. C.; Torfs, P. J. J. F.; de Louw, P. G. B.

2010-10-01

Identifying effective measures to reduce nutrient loads of headwaters in lowland catchments requires a thorough understanding of flow routes of water and nutrients. In this paper we assess the value of nested-scale discharge and groundwater level measurements for predictions of catchment-scale discharge and nitrate loads. In order to relate field-site measurements to the catchment-scale an upscaling approach is introduced that assumes that scale differences in flow route fluxes originate from differences in the relationship between groundwater storage and the spatial structure of the groundwater table. This relationship is characterized by the Groundwater Depth Distribution (GDD) curve that relates spatial variation in groundwater depths to the average groundwater depth. The GDD-curve was measured for a single field site (0.009 km2) and simple process descriptions were applied to relate the groundwater levels to flow route discharges. This parsimonious model could accurately describe observed storage, tube drain discharge, overland flow and groundwater flow simultaneously with Nash-Sutcliff coefficients exceeding 0.8. A probabilistic Monte Carlo approach was applied to upscale field-site measurements to catchment scales by inferring scale-specific GDD-curves from hydrographs of two nested catchments (0.4 and 6.5 km2). The estimated contribution of tube drain effluent (a dominant source for nitrates) decreased with increasing scale from 76-79% at the field-site to 34-61% and 25-50% for both catchment scales. These results were validated by demonstrating that a model conditioned on nested-scale measurements simulates better nitrate loads and better predictions of extreme discharges during validation periods compared to a model that was conditioned on catchment discharge only.

A Comprehensive Prediction Model of Hydraulic Extended-Reach Limit Considering the Allowable Range of Drilling Fluid Flow Rate in Horizontal Drilling.

PubMed

Li, Xin; Gao, Deli; Chen, Xuyue

2017-06-08

Hydraulic extended-reach limit (HERL) model of horizontal extended-reach well (ERW) can predict the maximum measured depth (MMD) of the horizontal ERW. The HERL refers to the well's MMD when drilling fluid cannot be normally circulated by drilling pump. Previous model analyzed the following two constraint conditions, drilling pump rated pressure and rated power. However, effects of the allowable range of drilling fluid flow rate (Q min  ≤ Q ≤ Q max ) were not considered. In this study, three cases of HERL model are proposed according to the relationship between allowable range of drilling fluid flow rate and rated flow rate of drilling pump (Q r ). A horizontal ERW is analyzed to predict its HERL, especially its horizontal-section limit (L h ). Results show that when Q min  ≤ Q r  ≤ Q max (Case I), L h depends both on horizontal-section limit based on rated pump pressure (L h1 ) and horizontal-section limit based on rated pump power (L h2 ); when Q min  < Q max  < Q r (Case II), L h is exclusively controlled by L h1 ; while L h is only determined by L h2 when Q r  < Q min  < Q max (Case III). Furthermore, L h1 first increases and then decreases with the increase in drilling fluid flow rate, while L h2 keeps decreasing as the drilling fluid flow rate increases. The comprehensive model provides a more accurate prediction on HERL.

Kinetic approach to degradation mechanisms in polymer solar cells and their accurate lifetime predictions

NASA Astrophysics Data System (ADS)

Arshad, Muhammad Azeem; Maaroufi, AbdelKrim

2018-07-01

A beginning has been made in the present study regarding the accurate lifetime predictions of polymer solar cells. Certain reservations about the conventionally employed temperature accelerated lifetime measurements test for its unworthiness of predicting reliable lifetimes of polymer solar cells are brought into light. Critical issues concerning the accelerated lifetime testing include, assuming reaction mechanism instead of determining it, and relying solely on the temperature acceleration of a single property of material. An advanced approach comprising a set of theoretical models to estimate the accurate lifetimes of polymer solar cells is therefore suggested in order to suitably alternate the accelerated lifetime testing. This approach takes into account systematic kinetic modeling of various possible polymer degradation mechanisms under natural weathering conditions. The proposed kinetic approach is substantiated by its applications on experimental aging data-sets of polymer solar materials/solar cells including, P3HT polymer film, bulk heterojunction (MDMO-PPV:PCBM) and dye-sensitized solar cells. Based on the suggested approach, an efficacious lifetime determination formula for polymer solar cells is derived and tested on dye-sensitized solar cells. Some important merits of the proposed method are also pointed out and its prospective applications are discussed.

Predicting sediment delivery from debris flows after wildfire

NASA Astrophysics Data System (ADS)

Nyman, Petter; Smith, Hugh G.; Sherwin, Christopher B.; Langhans, Christoph; Lane, Patrick N. J.; Sheridan, Gary J.

2015-12-01

Debris flows are an important erosion process in wildfire-prone landscapes. Predicting their frequency and magnitude can therefore be critical for quantifying risk to infrastructure, people and water resources. However, the factors contributing to the frequency and magnitude of events remain poorly understood, particularly in regions outside western USA. Against this background, the objectives of this study were to i) quantify sediment yields from post-fire debris flows in southeast Australian highlands and ii) model the effects of landscape attributes on debris flow susceptibility. Sediment yields from post-fire debris flows (113-294 t ha- 1) are 2-3 orders of magnitude higher than annual background erosion rates from undisturbed forests. Debris flow volumes ranged from 539 to 33,040 m3 with hillslope contributions of 18-62%. The distribution of erosion and deposition above the fan were related to a stream power index, which could be used to model changes in yield along the drainage network. Debris flow susceptibility was quantified with a logistic regression and an inventory of 315 debris flow fans deposited in the first year after two large wildfires (total burned area = 2919 km2). The differenced normalised burn ratio (dNBR or burn severity), local slope, radiative index of dryness (AI) and rainfall intensity (from rainfall radar) were significant predictors in a susceptibility model, which produced excellent results in terms identifying channels that were eroded by debris flows (Area Under Curve, AUC = 0.91). Burn severity was the strongest predictor in the model (AUC = 0.87 when dNBR is used as single predictor) suggesting that fire regimes are an important control on sediment delivery from these forests. The analysis showed a positive effect of AI on debris flow probability in landscapes where differences in moisture regimes due to climate are associated with large variation in soil hydraulic properties. Overall, the results from this study based in the

Modeling methodology for the accurate and prompt prediction of symptomatic events in chronic diseases.

PubMed

Pagán, Josué; Risco-Martín, José L; Moya, José M; Ayala, José L

2016-08-01

Prediction of symptomatic crises in chronic diseases allows to take decisions before the symptoms occur, such as the intake of drugs to avoid the symptoms or the activation of medical alarms. The prediction horizon is in this case an important parameter in order to fulfill the pharmacokinetics of medications, or the time response of medical services. This paper presents a study about the prediction limits of a chronic disease with symptomatic crises: the migraine. For that purpose, this work develops a methodology to build predictive migraine models and to improve these predictions beyond the limits of the initial models. The maximum prediction horizon is analyzed, and its dependency on the selected features is studied. A strategy for model selection is proposed to tackle the trade off between conservative but robust predictive models, with respect to less accurate predictions with higher horizons. The obtained results show a prediction horizon close to 40min, which is in the time range of the drug pharmacokinetics. Experiments have been performed in a realistic scenario where input data have been acquired in an ambulatory clinical study by the deployment of a non-intrusive Wireless Body Sensor Network. Our results provide an effective methodology for the selection of the future horizon in the development of prediction algorithms for diseases experiencing symptomatic crises. Copyright © 2016 Elsevier Inc. All rights reserved.

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: implications for three-dimensional modeling.

PubMed

Bhaskara, Ramachandra M; Padhi, Amrita; Srinivasan, Narayanaswamy

2014-07-01

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naïve Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (∼85%) and specific (∼95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. © 2013 Wiley Periodicals, Inc.

Effect of energy equation in one control-volume bulk-flow model for the prediction of labyrinth seal dynamic coefficients

NASA Astrophysics Data System (ADS)

Cangioli, Filippo; Pennacchi, Paolo; Vannini, Giuseppe; Ciuchicchi, Lorenzo

2018-01-01

The influence of sealing components on the rotordynamic stability of turbomachinery has become a key topic because the oil and gas market is increasingly demanding high rotational speeds and high efficiency. This leads the turbomachinery manufacturers to design higher flexibility ratios and to reduce the clearance of the seals. Accurate prediction of the effective damping of seals is critical to avoid instability problems; in recent years, "negative-swirl" swirl brakes have been used to reverse the circumferential direction of the inlet flow, which changes the sign of the cross-coupled stiffness coefficients and generates stabilizing forces. Experimental tests for a teeth-on-stator labyrinth seal were performed by manufacturers with positive and negative pre-swirl values to investigate the pre-swirl effect on the cross-coupled stiffness coefficient. Those results are used as a benchmark in this paper. To analyse the rotor-fluid interaction in the seals, the bulk-flow numeric approach is more time efficient than computational fluid dynamics (CFD). Although the accuracy of the coefficients prediction in bulk-flow models is satisfactory for liquid phase application, the accuracy of the results strongly depends on the operating conditions in the case of the gas phase. In this paper, the authors propose an improvement in the state-of-the-art bulk-flow model by introducing the effect of the energy equation in the zeroth-order solution to better characterize real gas properties due to the enthalpy variation along the seal cavities. The consideration of the energy equation allows for a better estimation of the coefficients in the case of a negative pre-swirl ratio, therefore, it extend the prediction fidelity over a wide range of operating conditions. The numeric results are also compared to the state-of-the-art bulk-flow model, which highlights the improvement in the model.

Prediction of Undsteady Flows in Turbomachinery Using the Linearized Euler Equations on Deforming Grids

NASA Technical Reports Server (NTRS)

Clark, William S.; Hall, Kenneth C.

1994-01-01

A linearized Euler solver for calculating unsteady flows in turbomachinery blade rows due to both incident gusts and blade motion is presented. The model accounts for blade loading, blade geometry, shock motion, and wake motion. Assuming that the unsteadiness in the flow is small relative to the nonlinear mean solution, the unsteady Euler equations can be linearized about the mean flow. This yields a set of linear variable coefficient equations that describe the small amplitude harmonic motion of the fluid. These linear equations are then discretized on a computational grid and solved using standard numerical techniques. For transonic flows, however, one must use a linear discretization which is a conservative linearization of the non-linear discretized Euler equations to ensure that shock impulse loads are accurately captured. Other important features of this analysis include a continuously deforming grid which eliminates extrapolation errors and hence, increases accuracy, and a new numerically exact, nonreflecting far-field boundary condition treatment based on an eigenanalysis of the discretized equations. Computational results are presented which demonstrate the computational accuracy and efficiency of the method and demonstrate the effectiveness of the deforming grid, far-field nonreflecting boundary conditions, and shock capturing techniques. A comparison of the present unsteady flow predictions to other numerical, semi-analytical, and experimental methods shows excellent agreement. In addition, the linearized Euler method presented requires one or two orders-of-magnitude less computational time than traditional time marching techniques making the present method a viable design tool for aeroelastic analyses.

Prediction of unsteady transonic flow around missile configurations

NASA Technical Reports Server (NTRS)

Nixon, D.; Reisenthel, P. H.; Torres, T. O.; Klopfer, G. H.

1990-01-01

This paper describes the preliminary development of a method for predicting the unsteady transonic flow around missiles at transonic and supersonic speeds, with the final goal of developing a computer code for use in aeroelastic calculations or during maneuvers. The basic equations derived for this method are an extension of those derived by Klopfer and Nixon (1989) for steady flow and are a subset of the Euler equations. In this approach, the five Euler equations are reduced to an equation similar to the three-dimensional unsteady potential equation, and a two-dimensional Poisson equation. In addition, one of the equations in this method is almost identical to the potential equation for which there are well tested computer codes, allowing the development of a prediction method based in part on proved technology.

Development of an accurate portable recording peak-flow meter for the diagnosis of asthma.

PubMed

Hitchings, D J; Dickinson, S A; Miller, M R; Fairfax, A J

1993-05-01

This article describes the systematic design of an electronic recording peak expiratory flow (PEF) meter to provide accurate data for the diagnosis of occupational asthma. Traditional diagnosis of asthma relies on accurate data of PEF tests performed by the patients in their own homes and places of work. Unfortunately there are high error rates in data produced and recorded by the patient, most of these are transcription errors and some patients falsify their records. The PEF measurement itself is not effort independent, the data produced depending on the way in which the patient performs the test. Patients are taught how to perform the test giving maximal effort to the expiration being measured. If the measurement is performed incorrectly then errors will occur. Accurate data can be produced if an electronically recording PEF instrument is developed, thus freeing the patient from the task of recording the test data. It should also be capable of determining whether the PEF measurement has been correctly performed. A requirement specification for a recording PEF meter was produced. A commercially available electronic PEF meter was modified to provide the functions required for accurate serial recording of the measurements produced by the patients. This is now being used in three hospitals in the West Midlands for investigations into the diagnosis of occupational asthma. In investigating current methods of measuring PEF and other pulmonary quantities a greater understanding was obtained of the limitations of current methods of measurement, and quantities being measured.(ABSTRACT TRUNCATED AT 250 WORDS)

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.

Prediction of gas-liquid two-phase flow regime in microgravity

NASA Technical Reports Server (NTRS)

Lee, Jinho; Platt, Jonathan A.

1993-01-01

An attempt is made to predict gas-liquid two-phase flow regime in a pipe in a microgravity environment through scaling analysis based on dominant physical mechanisms. Simple inlet geometry is adopted in the analysis to see the effect of inlet configuration on flow regime transitions. Comparison of the prediction with the existing experimental data shows good agreement, though more work is required to better define some physical parameters. The analysis clarifies much of the physics involved in this problem and can be applied to other configurations.

Evaluation of Turbulence-Model Performance as Applied to Jet-Noise Prediction

NASA Technical Reports Server (NTRS)

Woodruff, S. L.; Seiner, J. M.; Hussaini, M. Y.; Erlebacher, G.

1998-01-01

The accurate prediction of jet noise is possible only if the jet flow field can be predicted accurately. Predictions for the mean velocity and turbulence quantities in the jet flowfield are typically the product of a Reynolds-averaged Navier-Stokes solver coupled with a turbulence model. To evaluate the effectiveness of solvers and turbulence models in predicting those quantities most important to jet noise prediction, two CFD codes and several turbulence models were applied to a jet configuration over a range of jet temperatures for which experimental data is available.

Evaluation of a method of estimating low-flow frequencies from base-flow measurements at Indiana streams

USGS Publications Warehouse

Wilson, John Thomas

2000-01-01

A mathematical technique of estimating low-flow frequencies from base-flow measurements was evaluated by using data for streams in Indiana. Low-flow frequencies at low- flow partial-record stations were estimated by relating base-flow measurements to concurrent daily flows at nearby streamflow-gaging stations (index stations) for which low-flowfrequency curves had been developed. A network of long-term streamflow-gaging stations in Indiana provided a sample of sites with observed low-flow frequencies. Observed values of 7-day, 10-year low flow and 7-day, 2-year low flow were compared to predicted values to evaluate the accuracy of the method. Five test cases were used to evaluate the method under a variety of conditions in which the location of the index station and its drainage area varied relative to the partial-record station. A total of 141 pairs of streamflow-gaging stations were used in the five test cases. Four of the test cases used one index station, the fifth test case used two index stations. The number of base-flow measurements was varied for each test case to see if the accuracy of the method was affected by the number of measurements used. The most accurate and least variable results were produced when two index stations on the same stream or tributaries of the partial-record station were used. All but one value of the predicted 7-day, 10-year low flow were within 15 percent of the values observed for the long-term continuous record, and all of the predicted values of the 7-day, 2-year lowflow were within 15 percent of the observed values. This apparent accuracy, to some extent, may be a result of the small sample set of 15. Of the four test cases that used one index station, the most accurate and least variable results were produced in the test case where the index station and partial-record station were on the same stream or on streams tributary to each other and where the index station had a larger drainage area than the partial-record station. In

Do dual-route models accurately predict reading and spelling performance in individuals with acquired alexia and agraphia?

PubMed

Rapcsak, Steven Z; Henry, Maya L; Teague, Sommer L; Carnahan, Susan D; Beeson, Pélagie M

2007-06-18

Coltheart and co-workers [Castles, A., Bates, T. C., & Coltheart, M. (2006). John Marshall and the developmental dyslexias. Aphasiology, 20, 871-892; Coltheart, M., Rastle, K., Perry, C., Langdon, R., & Ziegler, J. (2001). DRC: A dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108, 204-256] have demonstrated that an equation derived from dual-route theory accurately predicts reading performance in young normal readers and in children with reading impairment due to developmental dyslexia or stroke. In this paper, we present evidence that the dual-route equation and a related multiple regression model also accurately predict both reading and spelling performance in adult neurological patients with acquired alexia and agraphia. These findings provide empirical support for dual-route theories of written language processing.

Development of a coupled level set and immersed boundary method for predicting dam break flows

NASA Astrophysics Data System (ADS)

Yu, C. H.; Sheu, Tony W. H.

2017-12-01

Dam-break flow over an immersed stationary object is investigated using a coupled level set (LS)/immersed boundary (IB) method developed in Cartesian grids. This approach adopts an improved interface preserving level set method which includes three solution steps and the differential-based interpolation immersed boundary method to treat fluid-fluid and solid-fluid interfaces, respectively. In the first step of this level set method, the level set function ϕ is advected by a pure advection equation. The intermediate step is performed to obtain a new level set value through a new smoothed Heaviside function. In the final solution step, a mass correction term is added to the re-initialization equation to ensure the new level set is a distance function and to conserve the mass bounded by the interface. For accurately calculating the level set value, the four-point upwinding combined compact difference (UCCD) scheme with three-point boundary combined compact difference scheme is applied to approximate the first-order derivative term shown in the level set equation. For the immersed boundary method, application of the artificial momentum forcing term at points in cells consisting of both fluid and solid allows an imposition of velocity condition to account for the presence of solid object. The incompressible Navier-Stokes solutions are calculated using the projection method. Numerical results show that the coupled LS/IB method can not only predict interface accurately but also preserve the mass conservation excellently for the dam-break flow.

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Sturdza, Peter (Inventor); Rajnarayan, Dev (Inventor)

2013-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of boundary-layer properties at the point are obtained from a steady-state solution of a fluid flow in a region adjacent to the point. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For each instability mode in the plurality of instability modes, a covariance vector is determined, which is the covariance of a predicted local growth rate with the known instability growth rates. Each covariance vector is used with the vector of regressor weights to determine a predicted local growth rate at the point. Based on the predicted local growth rates, an n-factor envelope at the point is determined.

Intermolecular potentials and the accurate prediction of the thermodynamic properties of water

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

Shvab, I.; Sadus, Richard J., E-mail: rsadus@swin.edu.au

2013-11-21

The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm{sup 3} for a wide range of temperatures (298–650 K) and pressures (0.1–700 MPa) is investigated. Molecular dynamics simulations are reported for the pressure, thermal pressure coefficient, thermal expansion coefficient, isothermal and adiabatic compressibilities, isobaric and isochoric heat capacities, and Joule-Thomson coefficient of liquid water using the non-polarizable SPC/E and TIP4P/2005 potentials. The results are compared with both experiment data and results obtained from the ab initio-based Matsuoka-Clementi-Yoshimine non-additive (MCYna) [J. Li, Z. Zhou, and R. J. Sadus, J. Chem. Phys.more » 127, 154509 (2007)] potential, which includes polarization contributions. The data clearly indicate that both the SPC/E and TIP4P/2005 potentials are only in qualitative agreement with experiment, whereas the polarizable MCYna potential predicts some properties within experimental uncertainty. This highlights the importance of polarizability for the accurate prediction of the thermodynamic properties of water, particularly at temperatures beyond 298 K.« less

ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

NASA Astrophysics Data System (ADS)

Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

2016-05-01

At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.

PubMed

Wang, Sheng; Sun, Siqi; Li, Zhen; Zhang, Renyu; Xu, Jinbo

2017-01-01

Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact-assisted models also have

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

PubMed Central

Li, Zhen; Zhang, Renyu

2017-01-01

Motivation Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. Method This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks. The first residual network conducts a series of 1-dimensional convolutional transformation of sequential features; the second residual network conducts a series of 2-dimensional convolutional transformation of pairwise information including output of the first residual network, EC information and pairwise potential. By using very deep residual networks, we can accurately model contact occurrence patterns and complex sequence-structure relationship and thus, obtain higher-quality contact prediction regardless of how many sequence homologs are available for proteins in question. Results Our method greatly outperforms existing methods and leads to much more accurate contact-assisted folding. Tested on 105 CASP11 targets, 76 past CAMEO hard targets, and 398 membrane proteins, the average top L long-range prediction accuracy obtained by our method, one representative EC method CCMpred and the CASP11 winner MetaPSICOV is 0.47, 0.21 and 0.30, respectively; the average top L/10 long-range accuracy of our method, CCMpred and MetaPSICOV is 0.77, 0.47 and 0.59, respectively. Ab initio folding using our predicted contacts as restraints but without any force fields can yield correct folds (i.e., TMscore>0.6) for 203 of the 579 test proteins, while that using MetaPSICOV- and CCMpred-predicted contacts can do so for only 79 and 62 of them, respectively. Our contact

Obtaining Accurate Probabilities Using Classifier Calibration

ERIC Educational Resources Information Center

Pakdaman Naeini, Mahdi

2016-01-01

Learning probabilistic classification and prediction models that generate accurate probabilities is essential in many prediction and decision-making tasks in machine learning and data mining. One way to achieve this goal is to post-process the output of classification models to obtain more accurate probabilities. These post-processing methods are…

The wire-mesh sensor as a two-phase flow meter

NASA Astrophysics Data System (ADS)

Shaban, H.; Tavoularis, S.

2015-01-01

A novel gas and liquid flow rate measurement method is proposed for use in vertical upward and downward gas-liquid pipe flows. This method is based on the analysis of the time history of area-averaged void fraction that is measured using a conductivity wire-mesh sensor (WMS). WMS measurements were collected in vertical upward and downward air-water flows in a pipe with an internal diameter of 32.5 mm at nearly atmospheric pressure. The relative frequencies and the power spectral density of area-averaged void fraction were calculated and used as representative properties. Independent features, extracted from these properties using Principal Component Analysis and Independent Component Analysis, were used as inputs to artificial neural networks, which were trained to give the gas and liquid flow rates as outputs. The present method was shown to be accurate for all four encountered flow regimes and for a wide range of flow conditions. Besides providing accurate predictions for steady flows, the method was also tested successfully in three flows with transient liquid flow rates. The method was augmented by the use of the cross-correlation function of area-averaged void fraction determined from the output of a dual WMS unit as an additional representative property, which was found to improve the accuracy of flow rate prediction.

Prediction of vortex shedding from circular and noncircular bodies in subsonic flow

NASA Technical Reports Server (NTRS)

Mendenhall, Michael R.; Lesieutre, Daniel J.

1987-01-01

An engineering prediction method and associated computer code VTXCLD are presented which predict nose vortex shedding from circular and noncircular bodies in subsonic flow at angles of attack and roll. The axisymmetric body is represented by point sources and doublets, and noncircular cross sections are transformed to a circle by either analytical or numerical conformal transformations. The leeward vortices are modeled by discrete vortices in crossflow planes along the body; thus, the three-dimensional steady flow problem is reduced to a two-dimensional, unsteady, separated flow problem for solution. Comparison of measured and predicted surface pressure distributions, flowfield surveys, and aerodynamic characteristics are presented for bodies with circular and noncircular cross sectional shapes.

An integrated Navier-Stokes - full potential - free wake method for rotor flows

NASA Astrophysics Data System (ADS)

Berkman, Mert Enis

1998-12-01

The strong wake shed from rotary wings interacts with almost all components of the aircraft, and alters the flow field thus causing performance and noise problems. Understanding and modeling the behavior of this wake, and its effect on the aerodynamics and acoustics of helicopters have remained as challenges. This vortex wake and its effect should be accurately accounted for in any technique that aims to predict rotor flow field and performance. In this study, an advanced and efficient computational technique for predicting three-dimensional unsteady viscous flows over isolated helicopter rotors in hover and in forward flight is developed. In this hybrid technique, the advantages of various existing methods have been combined to accurately and efficiently study rotor flows with a single numerical method. The flow field is viewed in three parts: (i) an inner zone surrounding each blade where the wake and viscous effects are numerically captured, (ii) an outer zone away from the blades where wake is modeled, and (iii) a Lagrangean wake which induces wake effects in the outer zone. This technique was coded in a flow solver and compared with experimental data for hovering and advancing rotors including a two-bladed rotor, the UH-60A rotor and a tapered tip rotor. Detailed surface pressure, integrated thrust and torque, sectional thrust, and tip vortex position predictions compared favorably against experimental data. Results indicated that the hybrid solver provided accurate flow details and performance information typically in one-half to one-eighth cost of complete Navier-Stokes methods.

CFD Validation Studies for Hypersonic Flow Prediction

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2001-01-01

A series of experiments to measure pressure and heating for code validation involving hypersonic, laminar, separated flows was conducted at the Calspan-University at Buffalo Research Center (CUBRC) in the Large Energy National Shock (LENS) tunnel. The experimental data serves as a focus for a code validation session but are not available to the authors until the conclusion of this session. The first set of experiments considered here involve Mach 9.5 and Mach 11.3 N2 flow over a hollow cylinder-flare with 30 degree flare angle at several Reynolds numbers sustaining laminar, separated flow. Truncated and extended flare configurations are considered. The second set of experiments, at similar conditions, involves flow over a sharp, double cone with fore-cone angle of 25 degrees and aft-cone angle of 55 degrees. Both sets of experiments involve 30 degree compressions. Location of the separation point in the numerical simulation is extremely sensitive to the level of grid refinement in the numerical predictions. The numerical simulations also show a significant influence of Reynolds number on extent of separation. Flow unsteadiness was easily introduced into the double cone simulations using aggressive relaxation parameters that normally promote convergence.

CFD Validation Studies for Hypersonic Flow Prediction

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2001-01-01

A series of experiments to measure pressure and heating for code validation involving hypersonic, laminar, separated flows was conducted at the Calspan-University at Buffalo Research Center (CUBRC) in the Large Energy National Shock (LENS) tunnel. The experimental data serves as a focus for a code validation session but are not available to the authors until the conclusion of this session. The first set of experiments considered here involve Mach 9.5 and Mach 11.3 N, flow over a hollow cylinder-flare with 30 deg flare angle at several Reynolds numbers sustaining laminar, separated flow. Truncated and extended flare configurations are considered. The second set of experiments, at similar conditions, involves flow over a sharp, double cone with fore-cone angle of 25 deg and aft-cone angle of 55 deg. Both sets of experiments involve 30 deg compressions. Location of the separation point in the numerical simulation is extremely sensitive to the level of grid refinement in the numerical predictions. The numerical simulations also show a significant influence of Reynolds number on extent of separation. Flow unsteadiness was easily introduced into the double cone simulations using aggressive relaxation parameters that normally promote convergence.

Dynamic Modeling Strategy for Flow Regime Transition in Gas-Liquid Two-Phase Flows

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

Xia Wang; Xiaodong Sun; Benjamin Doup

In modeling gas-liquid two-phase flows, the concept of flow regimes has been widely used to characterize the global interfacial structure of the flows. Nearly all constitutive relations that provide closures to the interfacial transfers in two-phase flow models, such as the two-fluid model, are flow regime dependent. Current nuclear reactor safety analysis codes, such as RELAP5, classify flow regimes using flow regime maps or transition criteria that were developed for steady-state, fully-developed flows. As twophase flows are dynamic in nature, it is important to model the flow regime transitions dynamically to more accurately predict the two-phase flows. The present workmore » aims to develop a dynamic modeling strategy to determine flow regimes in gas-liquid two-phase flows through introduction of interfacial area transport equations (IATEs) within the framework of a two-fluid model. The IATE is a transport equation that models the interfacial area concentration by considering the creation of the interfacial area, fluid particle (bubble or liquid droplet) disintegration, boiling and evaporation, and the destruction of the interfacial area, fluid particle coalescence and condensation. For flow regimes beyond bubbly flows, a two-group IATE has been proposed, in which bubbles are divided into two groups based on their size and shapes, namely group-1 and group-2 bubbles. A preliminary approach to dynamically identify the flow regimes is discussed, in which discriminator s are based on the predicted information, such as the void fraction and interfacial area concentration. The flow regime predicted with this method shows good agreement with the experimental observations.« less

Tectonic predictions with mantle convection models

NASA Astrophysics Data System (ADS)

Coltice, Nicolas; Shephard, Grace E.

2018-04-01

Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough

TAS: A Transonic Aircraft/Store flow field prediction code

NASA Technical Reports Server (NTRS)

Thompson, D. S.

1983-01-01

A numerical procedure has been developed that has the capability to predict the transonic flow field around an aircraft with an arbitrarily located, separated store. The TAS code, the product of a joint General Dynamics/NASA ARC/AFWAL research and development program, will serve as the basis for a comprehensive predictive method for aircraft with arbitrary store loadings. This report described the numerical procedures employed to simulate the flow field around a configuration of this type. The validity of TAS code predictions is established by comparison with existing experimental data. In addition, future areas of development of the code are outlined. A brief description of code utilization is also given in the Appendix. The aircraft/store configuration is simulated using a mesh embedding approach. The computational domain is discretized by three meshes: (1) a planform-oriented wing/body fine mesh, (2) a cylindrical store mesh, and (3) a global Cartesian crude mesh. This embedded mesh scheme enables simulation of stores with fins of arbitrary angular orientation.

Predictive model for convective flows induced by surface reactivity contrast

NASA Astrophysics Data System (ADS)

Davidson, Scott M.; Lammertink, Rob G. H.; Mani, Ali

2018-05-01

Concentration gradients in a fluid adjacent to a reactive surface due to contrast in surface reactivity generate convective flows. These flows result from contributions by electro- and diffusio-osmotic phenomena. In this study, we have analyzed reactive patterns that release and consume protons, analogous to bimetallic catalytic conversion of peroxide. Similar systems have typically been studied using either scaling analysis to predict trends or costly numerical simulation. Here, we present a simple analytical model, bridging the gap in quantitative understanding between scaling relations and simulations, to predict the induced potentials and consequent velocities in such systems without the use of any fitting parameters. Our model is tested against direct numerical solutions to the coupled Poisson, Nernst-Planck, and Stokes equations. Predicted slip velocities from the model and simulations agree to within a factor of ≈2 over a multiple order-of-magnitude change in the input parameters. Our analysis can be used to predict enhancement of mass transport and the resulting impact on overall catalytic conversion, and is also applicable to predicting the speed of catalytic nanomotors.

Limb-Enhancer Genie: An accessible resource of accurate enhancer predictions in the developing limb

DOE PAGES

Monti, Remo; Barozzi, Iros; Osterwalder, Marco; ...

2017-08-21

Epigenomic mapping of enhancer-associated chromatin modifications facilitates the genome-wide discovery of tissue-specific enhancers in vivo. However, reliance on single chromatin marks leads to high rates of false-positive predictions. More sophisticated, integrative methods have been described, but commonly suffer from limited accessibility to the resulting predictions and reduced biological interpretability. Here we present the Limb-Enhancer Genie (LEG), a collection of highly accurate, genome-wide predictions of enhancers in the developing limb, available through a user-friendly online interface. We predict limb enhancers using a combination of > 50 published limb-specific datasets and clusters of evolutionarily conserved transcription factor binding sites, taking advantage ofmore » the patterns observed at previously in vivo validated elements. By combining different statistical models, our approach outperforms current state-of-the-art methods and provides interpretable measures of feature importance. Our results indicate that including a previously unappreciated score that quantifies tissue-specific nuclease accessibility significantly improves prediction performance. We demonstrate the utility of our approach through in vivo validation of newly predicted elements. Moreover, we describe general features that can guide the type of datasets to include when predicting tissue-specific enhancers genome-wide, while providing an accessible resource to the general biological community and facilitating the functional interpretation of genetic studies of limb malformations.« less

Detecting Human Hydrologic Alteration from Diversion Hydropower Requires Universal Flow Prediction Tools: A Proposed Framework for Flow Prediction in Poorly-gauged, Regulated Rivers

NASA Astrophysics Data System (ADS)

Kibler, K. M.; Alipour, M.

2016-12-01

Achieving the universal energy access Sustainable Development Goal will require great investment in renewable energy infrastructure in the developing world. Much growth in the renewable sector will come from new hydropower projects, including small and diversion hydropower in remote and mountainous regions. Yet, human impacts to hydrological systems from diversion hydropower are poorly described. Diversion hydropower is often implemented in ungauged rivers, thus detection of impact requires flow analysis tools suited to prediction in poorly-gauged and human-altered catchments. We conduct a comprehensive analysis of hydrologic alteration in 32 rivers developed with diversion hydropower in southwestern China. As flow data are sparse, we devise an approach for estimating streamflow during pre- and post-development periods, drawing upon a decade of research into prediction in ungauged basins. We apply a rainfall-runoff model, parameterized and forced exclusively with global-scale data, in hydrologically-similar gauged and ungauged catchments. Uncertain "soft" data are incorporated through fuzzy numbers and confidence-based weighting, and a multi-criteria objective function is applied to evaluate model performance. Testing indicates that the proposed framework returns superior performance (NSE = 0.77) as compared to models parameterized by rote calibration (NSE = 0.62). Confident that the models are providing `the right answer for the right reasons', our analysis of hydrologic alteration based on simulated flows indicates statistically significant hydrologic effects of diversion hydropower across many rivers. Mean annual flows, 7-day minimum and 7-day maximum flows decreased. Frequency and duration of flow exceeding Q25 decreased while duration of flows sustained below the Q75 increased substantially. Hydrograph rise and fall rates and flow constancy increased. The proposed methodology may be applied to improve diversion hydropower design in data-limited regions.

Analysis of methods to estimate spring flows in a karst aquifer.

PubMed

Sepúlveda, Nicasio

2009-01-01

Hydraulically and statistically based methods were analyzed to identify the most reliable method to predict spring flows in a karst aquifer. Measured water levels at nearby observation wells, measured spring pool altitudes, and the distance between observation wells and the spring pool were the parameters used to match measured spring flows. Measured spring flows at six Upper Floridan aquifer springs in central Florida were used to assess the reliability of these methods to predict spring flows. Hydraulically based methods involved the application of the Theis, Hantush-Jacob, and Darcy-Weisbach equations, whereas the statistically based methods were the multiple linear regressions and the technology of artificial neural networks (ANNs). Root mean square errors between measured and predicted spring flows using the Darcy-Weisbach method ranged between 5% and 15% of the measured flows, lower than the 7% to 27% range for the Theis or Hantush-Jacob methods. Flows at all springs were estimated to be turbulent based on the Reynolds number derived from the Darcy-Weisbach equation for conduit flow. The multiple linear regression and the Darcy-Weisbach methods had similar spring flow prediction capabilities. The ANNs provided the lowest residuals between measured and predicted spring flows, ranging from 1.6% to 5.3% of the measured flows. The model prediction efficiency criteria also indicated that the ANNs were the most accurate method predicting spring flows in a karst aquifer.

Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

PubMed Central

Garcia Lopez, Sebastian; Kim, Philip M.

2014-01-01

Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

A physical-based gas-surface interaction model for rarefied gas flow simulation

NASA Astrophysics Data System (ADS)

Liang, Tengfei; Li, Qi; Ye, Wenjing

2018-01-01

Empirical gas-surface interaction models, such as the Maxwell model and the Cercignani-Lampis model, are widely used as the boundary condition in rarefied gas flow simulations. The accuracy of these models in the prediction of macroscopic behavior of rarefied gas flows is less satisfactory in some cases especially the highly non-equilibrium ones. Molecular dynamics simulation can accurately resolve the gas-surface interaction process at atomic scale, and hence can predict accurate macroscopic behavior. They are however too computationally expensive to be applied in real problems. In this work, a statistical physical-based gas-surface interaction model, which complies with the basic relations of boundary condition, is developed based on the framework of the washboard model. In virtue of its physical basis, this new model is capable of capturing some important relations/trends for which the classic empirical models fail to model correctly. As such, the new model is much more accurate than the classic models, and in the meantime is more efficient than MD simulations. Therefore, it can serve as a more accurate and efficient boundary condition for rarefied gas flow simulations.

Toward accurate prediction of pKa values for internal protein residues: the importance of conformational relaxation and desolvation energy.

PubMed

Wallace, Jason A; Wang, Yuhang; Shi, Chuanyin; Pastoor, Kevin J; Nguyen, Bao-Linh; Xia, Kai; Shen, Jana K

2011-12-01

Proton uptake or release controls many important biological processes, such as energy transduction, virus replication, and catalysis. Accurate pK(a) prediction informs about proton pathways, thereby revealing detailed acid-base mechanisms. Physics-based methods in the framework of molecular dynamics simulations not only offer pK(a) predictions but also inform about the physical origins of pK(a) shifts and provide details of ionization-induced conformational relaxation and large-scale transitions. One such method is the recently developed continuous constant pH molecular dynamics (CPHMD) method, which has been shown to be an accurate and robust pK(a) prediction tool for naturally occurring titratable residues. To further examine the accuracy and limitations of CPHMD, we blindly predicted the pK(a) values for 87 titratable residues introduced in various hydrophobic regions of staphylococcal nuclease and variants. The predictions gave a root-mean-square deviation of 1.69 pK units from experiment, and there were only two pK(a)'s with errors greater than 3.5 pK units. Analysis of the conformational fluctuation of titrating side-chains in the context of the errors of calculated pK(a) values indicate that explicit treatment of conformational flexibility and the associated dielectric relaxation gives CPHMD a distinct advantage. Analysis of the sources of errors suggests that more accurate pK(a) predictions can be obtained for the most deeply buried residues by improving the accuracy in calculating desolvation energies. Furthermore, it is found that the generalized Born implicit-solvent model underlying the current CPHMD implementation slightly distorts the local conformational environment such that the inclusion of an explicit-solvent representation may offer improvement of accuracy. Copyright © 2011 Wiley-Liss, Inc.

A prediction of 3-D viscous flow and performance of the NASA Low-Speed Centrifugal Compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1990-01-01

A prediction of the three-dimensional turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation of high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modeling. Recommendations are made for future flow studies in the NASA impeller.

A prediction of 3-D viscous flow and performance of the NASA low-speed centrifugal compressor

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1989-01-01

A prediction of the 3-D turbulent flow in the NASA Low-Speed Centrifugal Compressor Impeller has been made. The calculation was made for the compressor design conditions with the specified uniform tip clearance gap. The predicted performance is significantly worse than that predicted in the NASA design study. This is explained by the high tip leakage flow in the present calculation and by the different model adopted for tip leakage flow mixing. The calculation gives an accumulation for high losses in the shroud/pressure-side quadrant near the exit of the impeller. It also predicts a region of meridional backflow near the shroud wall. Both of these flow features should be extensive enough in the NASA impeller to allow detailed flow measurements, leading to improved flow modelling. Recommendations are made for future flow studies in the NASA impeller.

Prognostic breast cancer signature identified from 3D culture model accurately predicts clinical outcome across independent datasets

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

Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.

2008-10-20

One of the major tenets in breast cancer research is that early detection is vital for patient survival by increasing treatment options. To that end, we have previously used a novel unsupervised approach to identify a set of genes whose expression predicts prognosis of breast cancer patients. The predictive genes were selected in a well-defined three dimensional (3D) cell culture model of non-malignant human mammary epithelial cell morphogenesis as down-regulated during breast epithelial cell acinar formation and cell cycle arrest. Here we examine the ability of this gene signature (3D-signature) to predict prognosis in three independent breast cancer microarray datasetsmore » having 295, 286, and 118 samples, respectively. Our results show that the 3D-signature accurately predicts prognosis in three unrelated patient datasets. At 10 years, the probability of positive outcome was 52, 51, and 47 percent in the group with a poor-prognosis signature and 91, 75, and 71 percent in the group with a good-prognosis signature for the three datasets, respectively (Kaplan-Meier survival analysis, p<0.05). Hazard ratios for poor outcome were 5.5 (95% CI 3.0 to 12.2, p<0.0001), 2.4 (95% CI 1.6 to 3.6, p<0.0001) and 1.9 (95% CI 1.1 to 3.2, p = 0.016) and remained significant for the two larger datasets when corrected for estrogen receptor (ER) status. Hence the 3D-signature accurately predicts breast cancer outcome in both ER-positive and ER-negative tumors, though individual genes differed in their prognostic ability in the two subtypes. Genes that were prognostic in ER+ patients are AURKA, CEP55, RRM2, EPHA2, FGFBP1, and VRK1, while genes prognostic in ER patients include ACTB, FOXM1 and SERPINE2 (Kaplan-Meier p<0.05). Multivariable Cox regression analysis in the largest dataset showed that the 3D-signature was a strong independent factor in predicting breast cancer outcome. The 3D-signature accurately predicts breast cancer outcome across multiple datasets and holds

Flow of two immiscible fluids in a periodically constricted tube: Transitions to stratified, segmented, churn, spray or segregated flow

NASA Astrophysics Data System (ADS)

Tsamopoulos, John; Fraggedakis, Dimitris; Dimakopoulos, Yiannis

2015-11-01

We study the flow of two immiscible, Newtonian fluids in a periodically constricted tube driven by a constant pressure gradient. Our Volume-of-Fluid algorithm is used to solve the governing equations. First the code is validated by comparing its predictions to previously reported results for stratified and pulsing flow. Then it is used to capture accurately all the significant topological changes that take place. Initially, the fluids have a core-annular arrangement, which is found to either remain the same or change to a different arrangement depending on the fluid properties, the pressure driving the flow or the flow geometry. The flow-patterns that appear are the core-annular, segmented, churn, spray and segregated flow. The predicted scalings near pinching of the core fluid concur with similarity predictions and earlier numerical results (Cohen et al. (1999)). Flow-pattern maps are constructed in terms of the Reynolds and Weber numbers. Our results provide deeper insights in the mechanism of the pattern transitions and are in agreement with previous studies on core-annular flow (Kouris & Tsamopoulos (2001 & 2002)), segmented flow (Lac & Sherwood (2009)) and churn flow (Bai et al. (1992)). GSRT of Greece through the program ``Excellence'' (Grant No. 1918, entitled ``FilCoMicrA'').

New results in gravity dependent two-phase flow regime mapping

NASA Astrophysics Data System (ADS)

Kurwitz, Cable; Best, Frederick

2002-01-01

Accurate prediction of thermal-hydraulic parameters, such as the spatial gas/liquid orientation or flow regime, is required for implementation of two-phase systems. Although many flow regime transition models exist, accurate determination of both annular and slug regime boundaries is not well defined especially at lower flow rates. Furthermore, models typically indicate the regime as a sharp transition where data may indicate a transition space. Texas A&M has flown in excess of 35 flights aboard the NASA KC-135 aircraft with a unique two-phase package. These flights have produced a significant database of gravity dependent two-phase data including visual observations for flow regime identification. Two-phase flow tests conducted during recent zero-g flights have added to the flow regime database and are shown in this paper with comparisons to selected transition models. .

MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins.

PubMed

Jones, David T; Singh, Tanya; Kosciolek, Tomasz; Tetchner, Stuart

2015-04-01

Recent developments of statistical techniques to infer direct evolutionary couplings between residue pairs have rendered covariation-based contact prediction a viable means for accurate 3D modelling of proteins, with no information other than the sequence required. To extend the usefulness of contact prediction, we have designed a new meta-predictor (MetaPSICOV) which combines three distinct approaches for inferring covariation signals from multiple sequence alignments, considers a broad range of other sequence-derived features and, uniquely, a range of metrics which describe both the local and global quality of the input multiple sequence alignment. Finally, we use a two-stage predictor, where the second stage filters the output of the first stage. This two-stage predictor is additionally evaluated on its ability to accurately predict the long range network of hydrogen bonds, including correctly assigning the donor and acceptor residues. Using the original PSICOV benchmark set of 150 protein families, MetaPSICOV achieves a mean precision of 0.54 for top-L predicted long range contacts-around 60% higher than PSICOV, and around 40% better than CCMpred. In de novo protein structure prediction using FRAGFOLD, MetaPSICOV is able to improve the TM-scores of models by a median of 0.05 compared with PSICOV. Lastly, for predicting long range hydrogen bonding, MetaPSICOV-HB achieves a precision of 0.69 for the top-L/10 hydrogen bonds compared with just 0.26 for the baseline MetaPSICOV. MetaPSICOV is available as a freely available web server at http://bioinf.cs.ucl.ac.uk/MetaPSICOV. Raw data (predicted contact lists and 3D models) and source code can be downloaded from http://bioinf.cs.ucl.ac.uk/downloads/MetaPSICOV. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Current Trends in Modeling Research for Turbulent Aerodynamic Flows

NASA Technical Reports Server (NTRS)

Gatski, Thomas B.; Rumsey, Christopher L.; Manceau, Remi

2007-01-01

The engineering tools of choice for the computation of practical engineering flows have begun to migrate from those based on the traditional Reynolds-averaged Navier-Stokes approach to methodologies capable, in theory if not in practice, of accurately predicting some instantaneous scales of motion in the flow. The migration has largely been driven by both the success of Reynolds-averaged methods over a wide variety of flows as well as the inherent limitations of the method itself. Practitioners, emboldened by their ability to predict a wide-variety of statistically steady, equilibrium turbulent flows, have now turned their attention to flow control and non-equilibrium flows, that is, separation control. This review gives some current priorities in traditional Reynolds-averaged modeling research as well as some methodologies being applied to a new class of turbulent flow control problems.

Bedform response to flow variability

USGS Publications Warehouse

Nelson, J.M.; Logan, B.L.; Kinzel, P.J.; Shimizu, Y.; Giri, S.; Shreve, R.L.; McLean, S.R.

2011-01-01

Laboratory observations and computational results for the response of bedform fields to rapid variations in discharge are compared and discussed. The simple case considered here begins with a relatively low discharge over a flat bed on which bedforms are initiated, followed by a short high-flow period with double the original discharge, during which the morphology of the bedforms adjusts, followed in turn by a relatively long period of the original low discharge. For the grain size and hydraulic conditions selected, the Froude number remains subcritical during the experiment, and sediment moves predominantly as bedload. Observations show rapid development of quasi-two-dimensional bedforms during the initial period of low flow with increasing wavelength and height over the initial low-flow period. When the flow increases, the bedforms rapidly increase in wavelength and height, as expected from other empirical results. When the flow decreases back to the original discharge, the height of the bedforms quickly decreases in response, but the wavelength decreases much more slowly. Computational results using an unsteady two-dimensional flow model coupled to a disequilibrium bedload transport model for the same conditions simulate the formation and initial growth of the bedforms fairly accurately and also predict an increase in dimensions during the high-flow period. However, the computational model predicts a much slower rate of wavelength increase, and also performs less accurately during the final low-flow period, where the wavelength remains essentially constant, rather than decreasing. In addition, the numerical results show less variability in bedform wavelength and height than the measured values; the bedform shape is also somewhat different. Based on observations, these discrepancies may result from the simplified model for sediment particle step lengths used in the computational approach. Experiments show that the particle step length varies spatially and

KIVA-hpFE. Predictive turbulent reactive and multiphase flow in engines - An Overview

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

Carrington, David Bradley

2016-05-23

Research and development of KIVA-hpFE for turbulent reactive and multiphase flow particularly as related to engine modeling program has relevance to National energy security and climate change. Climate change is a source problem, and energy national security is consumption of petroleum products problem. Accurately predicting engine processes leads to, lower greenhouse gas (GHG) emission, where engines in the transportation sector currently account for 26% of the U.S. GHG emissions. Less dependence on petroleum products leads to greater energy security. By Environmental Protection Agency standards, some vehicles are now reaching 42 to the 50 mpg mark. These are conventional gasoline engines.more » Continued investment and research into new technical innovations, the potential exists to save more than 4 million barrels of oil per day or approximately $200 to $400 million per day. This would be a significant decrease in emission and use of petroleum and a very large economic stimulus too! It is estimated with further advancements in combustion, the current emissions can be reduced up to 40%. Enabling better understanding of fuel injection and fuel-air mixing, thermodynamic combustion losses, and combustion/emission formation processes enhances our ability to help solve both problems. To provide adequate capability for accurately simulating these processes, minimize time and labor for development of engine technology, are the goals of our KIVA development program.« less

Quasi-closed phase forward-backward linear prediction analysis of speech for accurate formant detection and estimation.

PubMed

Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo

2017-09-01

Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.

WegoLoc: accurate prediction of protein subcellular localization using weighted Gene Ontology terms.

PubMed

Chi, Sang-Mun; Nam, Dougu

2012-04-01

We present an accurate and fast web server, WegoLoc for predicting subcellular localization of proteins based on sequence similarity and weighted Gene Ontology (GO) information. A term weighting method in the text categorization process is applied to GO terms for a support vector machine classifier. As a result, WegoLoc surpasses the state-of-the-art methods for previously used test datasets. WegoLoc supports three eukaryotic kingdoms (animals, fungi and plants) and provides human-specific analysis, and covers several sets of cellular locations. In addition, WegoLoc provides (i) multiple possible localizations of input protein(s) as well as their corresponding probability scores, (ii) weights of GO terms representing the contribution of each GO term in the prediction, and (iii) a BLAST E-value for the best hit with GO terms. If the similarity score does not meet a given threshold, an amino acid composition-based prediction is applied as a backup method. WegoLoc and User's guide are freely available at the website http://www.btool.org/WegoLoc smchiks@ks.ac.kr; dougnam@unist.ac.kr Supplementary data is available at http://www.btool.org/WegoLoc.

Sex-specific lean body mass predictive equations are accurate in the obese paediatric population

PubMed Central

Jackson, Lanier B.; Henshaw, Melissa H.; Carter, Janet; Chowdhury, Shahryar M.

2015-01-01

Background The clinical assessment of lean body mass (LBM) is challenging in obese children. A sex-specific predictive equation for LBM derived from anthropometric data was recently validated in children. Aim The purpose of this study was to independently validate these predictive equations in the obese paediatric population. Subjects and methods Obese subjects aged 4–21 were analysed retrospectively. Predicted LBM (LBMp) was calculated using equations previously developed in children. Measured LBM (LBMm) was derived from dual-energy x-ray absorptiometry. Agreement was expressed as [(LBMm-LBMp)/LBMm] with 95% limits of agreement. Results Of 310 enrolled patients, 195 (63%) were females. The mean age was 11.8 ± 3.4 years and mean BMI Z-score was 2.3 ± 0.4. The average difference between LBMm and LBMp was −0.6% (−17.0%, 15.8%). Pearson’s correlation revealed a strong linear relationship between LBMm and LBMp (r=0.97, p<0.01). Conclusion This study validates the use of these clinically-derived sex-specific LBM predictive equations in the obese paediatric population. Future studies should use these equations to improve the ability to accurately classify LBM in obese children. PMID:26287383

Accurate prediction of cation-π interaction energy using substituent effects.

PubMed

Sayyed, Fareed Bhasha; Suresh, Cherumuttathu H

2012-06-14

(M(+))' and ΔV(min). All the Φ-X···M(+) systems showed good agreement between the calculated and predicted E(M(+))() values, suggesting that the ΔV(min) approach to substituent effect is accurate and useful for predicting the interactive behavior of substituted π-systems with cations.

Comparison of the PLTEMP code flow instability predictions with measurements made with electrically heated channels for the advanced test reactor.

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

Feldman, E.

of the fuel element burnout is due to a form of flow instability. Whittle and Forgan provide a formula that predicts when this flow instability will occur. This formula is included in the PLTEMP/ANL code.Error! Reference source not found. Olson has shown that the PLTEMP/ANL code accurately predicts the powers at which flow instability occurs in the Whittle and Forgan experiments. He also considered the electrically heated tests performed in the ANS Thermal-Hydraulic Test Loop at ORNL and report by M. Siman-Tov et al. The purpose of this memorandum is to demonstrate that the PLTEMP/ANL code accurately predicts the Croft and the Waters tests. This demonstration should provide sufficient confidence that the PLTEMP/ANL code can adequately predict the onset of flow instability for the converted MURR. The MURR core uses light water as a coolant, has a 24-inch active fuel length, downward flow in the core, and an average core velocity of about 7 m/s. The inlet temperature is about 50 C and the peak outlet is about 20 C higher than the inlet for reactor operation at 10 MW. The core pressures range from about 4 to about 5 bar. The peak heat flux is about 110 W/cm{sup 2}. Section 2 describes the mechanism that causes flow instability. Section 3 describes the Whittle and Forgan formula for flow instability. Section 4 briefly describes both the Croft and the Waters experiments. Section 5 describes the PLTEMP/ANL models. Section 6 compares the PLTEMP/ANL predictions based on the Whittle and Forgan formula with the Croft measurements. Section 7 does the same for the Waters measurements. Section 8 provides the range of parameters for the Whittle and Forgan tests. Section 9 discusses the results and provides conclusions. In conclusion, although there is no single test that by itself closely matches the limiting conditions in the MURR, the preponderance of measured data and the ability of the Whittle and Forgan correlation, as implemented in PLTEMP/ANL, to predict the onset of flow

Modeling study of rarefied gas effects on hypersonic reacting stagnation flows

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Bao, Lin

2014-12-01

Recent development of the near space hypersonic sharp leading vehicles has raised a necessity to fast and accurately predict the aeroheating in hypersonic rarefied flows, which challenges our understanding of the aerothermodynamics and aerothermochemistry. The present flow and heat transfer problem involves complex rarefied gas effects and nonequilibrium real gas effects which are beyond the scope of the traditional prediction theory based on the continuum hypothesis and equilibrium assumption. As a typical example, it has been found that the classical Fay-Riddell equation fails to predict the stagnation point heat flux, when the flow is either rarefied or chemical nonequilibrium. In order to design a more general theory covering the rarefied reacting flow cases, an intuitive model is proposed in this paper to describe the nonequilibrium dissociation-recombination flow along the stagnation streamline towards a slightly blunted nose in hypersonic rarefied flows. Some characteristic flow parameters are introduced, and based on these parameters, an explicitly analytical bridging function is established to correct the traditional theory to accurately predict the actual aeroheating performance. It is shown that for a small size nose in medium density flows, the flow at the outer edge of the stagnation point boundary layer could be highly nonequilibrium, and the aeroheating performance is distinguished from that of the big blunt body reentry flows at high altitudes. As a result, when the rarefied gas effects and the nonequilibrium real gas effects are both significant, the classical similarity law could be questionable, and it is inadequate to directly analogize results from the classical blunt body reentry problems to the present new generation sharp-leading vehicles. In addition, the direct simulation Monte Carlo method is also employed to validate the conclusion.

Numerical Simulation of a High Mach Number Jet Flow

NASA Technical Reports Server (NTRS)

Hayder, M. Ehtesham; Turkel, Eli; Mankbadi, Reda R.

1993-01-01

The recent efforts to develop accurate numerical schemes for transition and turbulent flows are motivated, among other factors, by the need for accurate prediction of flow noise. The success of developing high speed civil transport plane (HSCT) is contingent upon our understanding and suppression of the jet exhaust noise. The radiated sound can be directly obtained by solving the full (time-dependent) compressible Navier-Stokes equations. However, this requires computational storage that is beyond currently available machines. This difficulty can be overcome by limiting the solution domain to the near field where the jet is nonlinear and then use acoustic analogy (e.g., Lighthill) to relate the far-field noise to the near-field sources. The later requires obtaining the time-dependent flow field. The other difficulty in aeroacoustics computations is that at high Reynolds numbers the turbulent flow has a large range of scales. Direct numerical simulations (DNS) cannot obtain all the scales of motion at high Reynolds number of technological interest. However, it is believed that the large scale structure is more efficient than the small-scale structure in radiating noise. Thus, one can model the small scales and calculate the acoustically active scales. The large scale structure in the noise-producing initial region of the jet can be viewed as a wavelike nature, the net radiated sound is the net cancellation after integration over space. As such, aeroacoustics computations are highly sensitive to errors in computing the sound sources. It is therefore essential to use a high-order numerical scheme to predict the flow field. The present paper presents the first step in a ongoing effort to predict jet noise. The emphasis here is in accurate prediction of the unsteady flow field. We solve the full time-dependent Navier-Stokes equations by a high order finite difference method. Time accurate spatial simulations of both plane and axisymmetric jet are presented. Jet Mach

Prediction of unsteady separated flows on oscillating airfoils

NASA Technical Reports Server (NTRS)

Mccroskey, W. J.

1978-01-01

Techniques for calculating high Reynolds number flow around an airfoil undergoing dynamic stall are reviewed. Emphasis is placed on predicting the values of lift, drag, and pitching moments. Methods discussed include: the discrete potential vortex method; thin boundary layer method; strong interaction between inviscid and viscous flows; and solutions to the Navier-Stokes equations. Empirical methods for estimating unsteady airloads on oscillating airfoils are also described. These methods correlate force and moment data from wind tunnel tests to indicate the effects of various parameters, such as airfoil shape, Mach number, amplitude and frequency of sinosoidal oscillations, mean angle, and type of motion.

Analysis of methods to estimate spring flows in a karst aquifer

USGS Publications Warehouse

Sepulveda, N.

2009-01-01

Hydraulically and statistically based methods were analyzed to identify the most reliable method to predict spring flows in a karst aquifer. Measured water levels at nearby observation wells, measured spring pool altitudes, and the distance between observation wells and the spring pool were the parameters used to match measured spring flows. Measured spring flows at six Upper Floridan aquifer springs in central Florida were used to assess the reliability of these methods to predict spring flows. Hydraulically based methods involved the application of the Theis, Hantush-Jacob, and Darcy-Weisbach equations, whereas the statistically based methods were the multiple linear regressions and the technology of artificial neural networks (ANNs). Root mean square errors between measured and predicted spring flows using the Darcy-Weisbach method ranged between 5% and 15% of the measured flows, lower than the 7% to 27% range for the Theis or Hantush-Jacob methods. Flows at all springs were estimated to be turbulent based on the Reynolds number derived from the Darcy-Weisbach equation for conduit flow. The multiple linear regression and the Darcy-Weisbach methods had similar spring flow prediction capabilities. The ANNs provided the lowest residuals between measured and predicted spring flows, ranging from 1.6% to 5.3% of the measured flows. The model prediction efficiency criteria also indicated that the ANNs were the most accurate method predicting spring flows in a karst aquifer. ?? 2008 National Ground Water Association.

Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2001-01-01

A computational fluid dynamics (CFD) method has been employed to compute vortical flows around slender wing/body configurations. The emphasis of the paper is on the effectiveness of an adaptive grid procedure in "capturing" concentrated vortices generated at sharp edges or flow separation lines of lifting surfaces flying at high angles of attack. The method is based on a tetrahedral unstructured grid technology developed at the NASA Langley Research Center. Two steady-state, subsonic, inviscid and Navier-Stokes flow test cases are presented to demonstrate the applicability of the method for solving practical vortical flow problems. The first test case concerns vortex flow over a simple 65deg delta wing with different values of leading-edge bluntness, and the second case is that of a more complex fighter configuration. The superiority of the adapted solutions in capturing the vortex flow structure over the conventional unadapted results is demonstrated by comparisons with the windtunnel experimental data. The study shows that numerical prediction of vortical flows is highly sensitive to the local grid resolution and that the implementation of grid adaptation is essential when applying CFD methods to such complicated flow problems.

The application of intraoperative transit time flow measurement to accurately assess anastomotic quality in sequential vein grafting

PubMed Central

Yu, Yang; Zhang, Fan; Gao, Ming-Xin; Li, Hai-Tao; Li, Jing-Xing; Song, Wei; Huang, Xin-Sheng; Gu, Cheng-Xiong

2013-01-01

OBJECTIVES Intraoperative transit time flow measurement (TTFM) is widely used to assess anastomotic quality in coronary artery bypass grafting (CABG). However, in sequential vein grafting, the flow characteristics collected by the conventional TTFM method are usually associated with total graft flow and might not accurately indicate the quality of every distal anastomosis in a sequential graft. The purpose of our study was to examine a new TTFM method that could assess the quality of each distal anastomosis in a sequential graft more reliably than the conventional TTFM approach. METHODS Two TTFM methods were tested in 84 patients who underwent sequential saphenous off-pump CABG in Beijing An Zhen Hospital between April and August 2012. In the conventional TTFM method, normal blood flow in the sequential graft was maintained during the measurement, and the flow probe was placed a few centimetres above the anastomosis to be evaluated. In the new method, blood flow in the sequential graft was temporarily reduced during the measurement by placing an atraumatic bulldog clamp at the graft a few centimetres distal to the anastomosis to be evaluated, while the position of the flow probe remained the same as in the conventional method. This new TTFM method was named the flow reduction TTFM. Graft flow parameters measured by both methods were compared. RESULTS Compared with the conventional TTFM, the flow reduction TTFM resulted in significantly lower mean graft blood flow (P < 0.05); in contrast, yielded significantly higher pulsatility index (P < 0.05). Diastolic filling was not significantly different between the two methods and was >50% in both cases. Interestingly, the flow reduction TTFM identified two defective middle distal anastomoses that the conventional TTFM failed to detect. Graft flows near the defective distal anastomoses were improved substantially after revision. CONCLUSIONS In this study, we found that temporary reduction of graft flow during TTFM seemed to

Prediction and control of vortex-dominated and vortex-wake flows

NASA Technical Reports Server (NTRS)

Kandil, Osama

1993-01-01

This progress report documents the accomplishments achieved in the period from December 1, 1992 until November 30, 1993. These accomplishments include publications, national and international presentations, NASA presentations, and the research group supported under this grant. Topics covered by documents incorporated into this progress report include: active control of asymmetric conical flow using spinning and rotary oscillation; supersonic vortex breakdown over a delta wing in transonic flow; shock-vortex interaction over a 65-degree delta wing in transonic flow; three dimensional supersonic vortex breakdown; numerical simulation and physical aspects of supersonic vortex breakdown; and prediction of asymmetric vortical flows around slender bodies using Navier-Stokes equations.

Accurate predictions of iron redox state in silicate glasses: A multivariate approach using X-ray absorption spectroscopy

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

Dyar, M. Darby; McCanta, Molly; Breves, Elly

2016-03-01

Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yield accurate resultsmore » from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.« less

Accurate predictions of iron redox state in silicate glasses: A multivariate approach using X-ray absorption spectroscopy

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

Dyar, M. Darby; McCanta, Molly; Breves, Elly

2016-03-01

Pre-edge features in the K absorption edge of X-ray absorption spectra are commonly used to predict Fe 3+ valence state in silicate glasses. However, this study shows that using the entire spectral region from the pre-edge into the extended X-ray absorption fine-structure region provides more accurate results when combined with multivariate analysis techniques. The least absolute shrinkage and selection operator (lasso) regression technique yields %Fe 3+ values that are accurate to ±3.6% absolute when the full spectral region is employed. This method can be used across a broad range of glass compositions, is easily automated, and is demonstrated to yieldmore » accurate results from different synchrotrons. It will enable future studies involving X-ray mapping of redox gradients on standard thin sections at 1 × 1 μm pixel sizes.« less

Turbulent flow separation in three-dimensional asymmetric diffusers

NASA Astrophysics Data System (ADS)

Jeyapaul, Elbert

2011-12-01

separation is due to effects of lateral straining, streamline curvature, secondary flow of second kind, transverse pressure gradient on turbulence. Resolving these effects is possible with anisotropy turbulence models as the Explicit Algebraic Reynolds stress model (EARSM). This model has provided accurate prediction of streamwise and transverse velocity, however the wall pressure is under predicted. An improved EARSM model is developed by correcting the coefficients, which predicts a more accurate wall pressure. There exists scope for improvement of this model, by including convective effects and dynamics of velocity gradient invariants.

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis; Negri, Jacquelyn; Kean, Jason

2016-04-01

burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

The value of assessing pulmonary venous flow velocity for predicting severity of mitral regurgitation: A quantitative assessment integrating left ventricular function

NASA Technical Reports Server (NTRS)

Pu, M.; Griffin, B. P.; Vandervoort, P. M.; Stewart, W. J.; Fan, X.; Cosgrove, D. M.; Thomas, J. D.

1999-01-01

%) for detecting ROA of greater than 0.3 cm(2) with significant overlap with the reversed and normal patterns. Among patients with the blunted pattern, the correlation between the systolic to diastolic velocity ratio was worse in those with LV dysfunction (ejection fraction <50%, r = 0.23, P >.05) than in those with normal LV function (r = -0.57, P <.05). Stepwise linear regression analysis showed that the peak systolic to diastolic velocity ratio was independently correlated with RF (P <.001) and effective stroke volume (P <.01), with a multiple correlation coefficient of 0.71 (P <.001). In conclusion, reversed pulmonary venous flow in systole is a highly specific and reliable marker of moderately severe or severe MR with an ROA greater than 0.3 cm(2), whereas the normal pattern accurately predicts mild to moderate MR. Blunted pulmonary venous flow can be seen in all grades of MR with low predictive value for severity of MR, especially in the presence of LV dysfunction. The blunted pulmonary venous flow pattern must therefore be interpreted cautiously in clinical practice as a marker for severity of MR.

Predictive onboard flow control for packet switching satellites

NASA Technical Reports Server (NTRS)

Bobinsky, Eric A.

1992-01-01

We outline two alternate approaches to predicting the onset of congestion in a packet switching satellite, and argue that predictive, rather than reactive, flow control is necessary for the efficient operation of such a system. The first method discussed is based on standard, statistical techniques which are used to periodically calculate a probability of near-term congestion based on arrival rate statistics. If this probability exceeds a present threshold, the satellite would transmit a rate-reduction signal to all active ground stations. The second method discussed would utilize a neural network to periodically predict the occurrence of buffer overflow based on input data which would include, in addition to arrival rates, the distributions of packet lengths, source addresses, and destination addresses.

Accurate indel prediction using paired-end short reads

PubMed Central

2013-01-01

Background One of the major open challenges in next generation sequencing (NGS) is the accurate identification of structural variants such as insertions and deletions (indels). Current methods for indel calling assign scores to different types of evidence or counter-evidence for the presence of an indel, such as the number of split read alignments spanning the boundaries of a deletion candidate or reads that map within a putative deletion. Candidates with a score above a manually defined threshold are then predicted to be true indels. As a consequence, structural variants detected in this manner contain many false positives. Results Here, we present a machine learning based method which is able to discover and distinguish true from false indel candidates in order to reduce the false positive rate. Our method identifies indel candidates using a discriminative classifier based on features of split read alignment profiles and trained on true and false indel candidates that were validated by Sanger sequencing. We demonstrate the usefulness of our method with paired-end Illumina reads from 80 genomes of the first phase of the 1001 Genomes Project ( http://www.1001genomes.org) in Arabidopsis thaliana. Conclusion In this work we show that indel classification is a necessary step to reduce the number of false positive candidates. We demonstrate that missing classification may lead to spurious biological interpretations. The software is available at: http://agkb.is.tuebingen.mpg.de/Forschung/SV-M/. PMID:23442375

Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

Multi-scale modeling of tsunami flows and tsunami-induced forces

NASA Astrophysics Data System (ADS)

Qin, X.; Motley, M. R.; LeVeque, R. J.; Gonzalez, F. I.

2016-12-01

The modeling of tsunami flows and tsunami-induced forces in coastal communities with the incorporation of the constructed environment is challenging for many numerical modelers because of the scale and complexity of the physical problem. A two-dimensional (2D) depth-averaged model can be efficient for modeling of waves offshore but may not be accurate enough to predict the complex flow with transient variance in vertical direction around constructed environments on land. On the other hand, using a more complex three-dimensional model is much more computational expensive and can become impractical due to the size of the problem and the meshing requirements near the built environment. In this study, a 2D depth-integrated model and a 3D Reynolds Averaged Navier-Stokes (RANS) model are built to model a 1:50 model-scale, idealized community, representative of Seaside, OR, USA, for which existing experimental data is available for comparison. Numerical results from the two numerical models are compared with each other as well as experimental measurement. Both models predict the flow parameters (water level, velocity, and momentum flux in the vicinity of the buildings) accurately, in general, except for time period near the initial impact, where the depth-averaged models can fail to capture the complexities in the flow. Forces predicted using direct integration of predicted pressure on structural surfaces from the 3D model and using momentum flux from the 2D model with constructed environment are compared, which indicates that force prediction from the 2D model is not always reliable in such a complicated case. Force predictions from integration of the pressure are also compared with forces predicted from bare earth momentum flux calculations to reveal the importance of incorporating the constructed environment in force prediction models.

Accurate and robust genomic prediction of celiac disease using statistical learning.

PubMed

Abraham, Gad; Tye-Din, Jason A; Bhalala, Oneil G; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2014-02-01

Practical application of genomic-based risk stratification to clinical diagnosis is appealing yet performance varies widely depending on the disease and genomic risk score (GRS) method. Celiac disease (CD), a common immune-mediated illness, is strongly genetically determined and requires specific HLA haplotypes. HLA testing can exclude diagnosis but has low specificity, providing little information suitable for clinical risk stratification. Using six European cohorts, we provide a proof-of-concept that statistical learning approaches which simultaneously model all SNPs can generate robust and highly accurate predictive models of CD based on genome-wide SNP profiles. The high predictive capacity replicated both in cross-validation within each cohort (AUC of 0.87-0.89) and in independent replication across cohorts (AUC of 0.86-0.9), despite differences in ethnicity. The models explained 30-35% of disease variance and up to ∼43% of heritability. The GRS's utility was assessed in different clinically relevant settings. Comparable to HLA typing, the GRS can be used to identify individuals without CD with ≥99.6% negative predictive value however, unlike HLA typing, fine-scale stratification of individuals into categories of higher-risk for CD can identify those that would benefit from more invasive and costly definitive testing. The GRS is flexible and its performance can be adapted to the clinical situation by adjusting the threshold cut-off. Despite explaining a minority of disease heritability, our findings indicate a genomic risk score provides clinically relevant information to improve upon current diagnostic pathways for CD and support further studies evaluating the clinical utility of this approach in CD and other complex diseases.

Accurate viscosity measurements of flowing aqueous glucose solutions with suspended scatterers using a dynamic light scattering approach with optical coherence tomography.

PubMed

Weatherbee, Andrew; Popov, Ivan; Vitkin, Alex

2017-08-01

The viscosity of turbid colloidal glucose solutions has been accurately determined from spectral domain optical coherence tomography (OCT) M-mode measurements and our recently developed OCT dynamic light scattering model. Results for various glucose concentrations, flow speeds, and flow angles are reported. The relative "combined standard uncertainty" uc(η) on the viscosity measurements was ±1% for the no-flow case and ±5% for the flow cases, a significant improvement in measurement robustness over previously published reports. The available literature data for the viscosity of pure water and our measurements differ by 1% (stagnant case) and 1.5% (flow cases), demonstrating good accuracy; similar agreement is seen across the measured glucose concentration range when compared to interpolated literature values. The developed technique may contribute toward eventual noninvasive glucose measurements in medicine. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Estimating Flow-Duration and Low-Flow Frequency Statistics for Unregulated Streams in Oregon

USGS Publications Warehouse

Risley, John; Stonewall, Adam J.; Haluska, Tana

2008-01-01

Flow statistical datasets, basin-characteristic datasets, and regression equations were developed to provide decision makers with surface-water information needed for activities such as water-quality regulation, water-rights adjudication, biological habitat assessment, infrastructure design, and water-supply planning and management. The flow statistics, which included annual and monthly period of record flow durations (5th, 10th, 25th, 50th, and 95th percent exceedances) and annual and monthly 7-day, 10-year (7Q10) and 7-day, 2-year (7Q2) low flows, were computed at 466 streamflow-gaging stations at sites with unregulated flow conditions throughout Oregon and adjacent areas of neighboring States. Regression equations, created from the flow statistics and basin characteristics of the stations, can be used to estimate flow statistics at ungaged stream sites in Oregon. The study area was divided into 10 regression modeling regions based on ecological, topographic, geologic, hydrologic, and climatic criteria. In total, 910 annual and monthly regression equations were created to predict the 7 flow statistics in the 10 regions. Equations to predict the five flow-duration exceedance percentages and the two low-flow frequency statistics were created with Ordinary Least Squares and Generalized Least Squares regression, respectively. The standard errors of estimate of the equations created to predict the 5th and 95th percent exceedances had medians of 42.4 and 64.4 percent, respectively. The standard errors of prediction of the equations created to predict the 7Q2 and 7Q10 low-flow statistics had medians of 51.7 and 61.2 percent, respectively. Standard errors for regression equations for sites in western Oregon were smaller than those in eastern Oregon partly because of a greater density of available streamflow-gaging stations in western Oregon than eastern Oregon. High-flow regression equations (such as the 5th and 10th percent exceedances) also generally were more accurate

A Multiscale Red Blood Cell Model with Accurate Mechanics, Rheology, and Dynamics

PubMed Central

Fedosov, Dmitry A.; Caswell, Bruce; Karniadakis, George Em

2010-01-01

Abstract Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. PMID:20483330

A narrow-band k-distribution model with single mixture gas assumption for radiative flows

NASA Astrophysics Data System (ADS)

Jo, Sung Min; Kim, Jae Won; Kwon, Oh Joon

2018-06-01

In the present study, the narrow-band k-distribution (NBK) model parameters for mixtures of H2O, CO2, and CO are proposed by utilizing the line-by-line (LBL) calculations with a single mixture gas assumption. For the application of the NBK model to radiative flows, a radiative transfer equation (RTE) solver based on a finite-volume method on unstructured meshes was developed. The NBK model and the RTE solver were verified by solving two benchmark problems including the spectral radiance distribution emitted from one-dimensional slabs and the radiative heat transfer in a truncated conical enclosure. It was shown that the results are accurate and physically reliable by comparing with available data. To examine the applicability of the methods to realistic multi-dimensional problems in non-isothermal and non-homogeneous conditions, radiation in an axisymmetric combustion chamber was analyzed, and then the infrared signature emitted from an aircraft exhaust plume was predicted. For modeling the plume flow involving radiative cooling, a flow-radiation coupled procedure was devised in a loosely coupled manner by adopting a Navier-Stokes flow solver based on unstructured meshes. It was shown that the predicted radiative cooling for the combustion chamber is physically more accurate than other predictions, and is as accurate as that by the LBL calculations. It was found that the infrared signature of aircraft exhaust plume can also be obtained accurately, equivalent to the LBL calculations, by using the present narrow-band approach with a much improved numerical efficiency.

Predicting the Performance of an Axial-Flow Compressor

NASA Technical Reports Server (NTRS)

Steinke, R. J.

1986-01-01

Stage-stacking computer code (STGSTK) developed for predicting off-design performance of multi-stage axial-flow compressors. Code uses meanline stagestacking method. Stage and cumulative compressor performance calculated from representative meanline velocity diagrams located at rotor inlet and outlet meanline radii. Numerous options available within code. Code developed so user modify correlations to suit their needs.

Vegetation-Induced Roughness in Low-Reynold's Number Flows

NASA Astrophysics Data System (ADS)

Piercy, C. D.; Wynn, T. M.

2008-12-01

Wetlands are important ecosystems, providing habitat for wildlife and fish and shellfish production, water storage, erosion control, and water quality improvement and preservation. Models to estimate hydraulic resistance due to vegetation in emergent wetlands are crucial to good wetland design and analysis. The goal of this project is to improve modeling of emergent wetlands by linking properties of the vegetation to flow. Existing resistance equations such as Hoffmann (2004), Kadlec (1990), Moghadam and Kouwen (1997), Nepf (1999), and Stone and Shen (2002) were evaluated. A large outdoor vegetated flume was constructed at the Price's Fork Research Center near Blacksburg, Virginia to measure flow and water surface slope through woolgrass (Scirpus cyperinus), a common native emergent wetland plant. Measurements of clump and stem density, diameter, and volume, blockage factor, and stiffness were made after each set of flume runs. Flow rates through the flume were low (3-4 L/s) resulting in very low stem-Reynold's numbers (15-102). Since experimental flow conditions were in the laminar to transitional range, most of the models considered did not predict velocity or stage accurately except for conditions in which the stem-Reynold's number approached 100. At low stem-Reynold's numbers (<100), the drag coefficient is inversely proportional to the Reynold's number and can vary greatly with flow conditions. Most of the models considered assumed a stem-Reynold's number in the 100-105 range in which the drag coefficient is relatively constant and as a result did not predict velocity or stage accurately except for conditions in which the stem-Reynold's number approached 100. The only model that accurately predicted stem layer velocity was the Kadlec (1990) model since it does not make assumptions about flow regime; instead, the parameters are adjusted according to the site conditions. Future work includes relating the parameters used to fit the Kadlec (1990) model to measured

Hot Deformation Behavior and Flow Stress Prediction of TC4-DT Alloy in Single-Phase Region and Dual-Phase Regions

NASA Astrophysics Data System (ADS)

Liu, Jianglin; Zeng, Weidong; Zhu, Yanchun; Yu, Hanqing; Zhao, Yongqing

2015-05-01

Isothermal compression tests of TC4-DT titanium alloy at the deformation temperature ranging from 1181 to 1341 K covering α + β phase field and β-phase field, the strain rate ranging from 0.01 to 10.0 s-1 and the height reduction of 70% were conducted on a Gleeble-3500 thermo-mechanical simulator. The experimental true stress-true strain data were employed to develop the strain-compensated Arrhenius-type flow stress model and artificial neural network (ANN) model; the predictability of two models was quantified in terms of correlation coefficient ( R) and average absolute relative error (AARE). The R and AARE for the Arrhenius-type flow stress model were 0.9952 and 5.78%, which were poorer linear relation and more deviation than 0.9997 and 1.04% for the feed-forward back-propagation ANN model, respectively. The results indicated that the trained ANN model was more efficient and accurate in predicting the flow behavior for TC4-DT titanium alloy at elevated temperature deformation than the strain-compensated Arrhenius-type constitutive equations. The constitutive relationship compensating strain could track the experimental data across the whole hot working domain other than that at high strain rates (≥1 s-1). The microstructure analysis illustrated that the deformation mechanisms existed at low strain rates (≤0.1 s-1), where dynamic recrystallization occurred, were far different from that at high strain rates (≥1 s-1) that presented bands of flow localization and cracking along grain boundary.

DYNAMIC MODELING STRATEGY FOR FLOW REGIME TRANSITION IN GAS-LIQUID TWO-PHASE FLOWS

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

X. Wang; X. Sun; H. Zhao

In modeling gas-liquid two-phase flows, the concept of flow regime has been used to characterize the global interfacial structure of the flows. Nearly all constitutive relations that provide closures to the interfacial transfers in two-phase flow models, such as the two-fluid model, are often flow regime dependent. Currently, the determination of the flow regimes is primarily based on flow regime maps or transition criteria, which are developed for steady-state, fully-developed flows and widely applied in nuclear reactor system safety analysis codes, such as RELAP5. As two-phase flows are observed to be dynamic in nature (fully-developed two-phase flows generally do notmore » exist in real applications), it is of importance to model the flow regime transition dynamically for more accurate predictions of two-phase flows. The present work aims to develop a dynamic modeling strategy for determining flow regimes in gas-liquid two-phase flows through the introduction of interfacial area transport equations (IATEs) within the framework of a two-fluid model. The IATE is a transport equation that models the interfacial area concentration by considering the creation and destruction of the interfacial area, such as the fluid particle (bubble or liquid droplet) disintegration, boiling and evaporation; and fluid particle coalescence and condensation, respectively. For the flow regimes beyond bubbly flows, a two-group IATE has been proposed, in which bubbles are divided into two groups based on their size and shape (which are correlated), namely small bubbles and large bubbles. A preliminary approach to dynamically identifying the flow regimes is provided, in which discriminators are based on the predicted information, such as the void fraction and interfacial area concentration of small bubble and large bubble groups. This method is expected to be applied to computer codes to improve their predictive capabilities of gas-liquid two-phase flows, in particular for the

Chemical reacting flows

NASA Technical Reports Server (NTRS)

Mularz, Edward J.; Sockol, Peter M.

1987-01-01

Future aerospace propulsion concepts involve the combination of liquid or gaseous fuels in a highly turbulent internal air stream. Accurate predictive computer codes which can simulate the fluid mechanics, chemistry, and turbulence combustion interaction of these chemical reacting flows will be a new tool that is needed in the design of these future propulsion concepts. Experimental and code development research is being performed at Lewis to better understand chemical reacting flows with the long term goal of establishing these reliable computer codes. The approach to understanding chemical reacting flows is to look at separate simple parts of this complex phenomena as well as to study the full turbulent reacting flow process. As a result research on the fluid mechanics associated with chemical reacting flows was initiated. The chemistry of fuel-air combustion is also being studied. Finally, the phenomena of turbulence-combustion interaction is being investigated. This presentation will highlight research, both experimental and analytical, in each of these three major areas.

Chemical reacting flows

NASA Technical Reports Server (NTRS)

Mularz, Edward J.; Sockol, Peter M.

1990-01-01

Future aerospace propulsion concepts involve the combustion of liquid or gaseous fuels in a highly turbulent internal airstream. Accurate predictive computer codes which can simulate the fluid mechanics, chemistry, and turbulence-combustion interaction of these chemical reacting flows will be a new tool that is needed in the design of these future propulsion concepts. Experimental and code development research is being performed at LeRC to better understand chemical reacting flows with the long-term goal of establishing these reliable computer codes. Our approach to understand chemical reacting flows is to look at separate, more simple parts of this complex phenomenon as well as to study the full turbulent reacting flow process. As a result, we are engaged in research on the fluid mechanics associated with chemical reacting flows. We are also studying the chemistry of fuel-air combustion. Finally, we are investigating the phenomenon of turbulence-combustion interaction. Research, both experimental and analytical, is highlighted in each of these three major areas.

Can a numerically stable subgrid-scale model for turbulent flow computation be ideally accurate?: a preliminary theoretical study for the Gaussian filtered Navier-Stokes equations.

PubMed

Ida, Masato; Taniguchi, Nobuyuki

2003-09-01

This paper introduces a candidate for the origin of the numerical instabilities in large eddy simulation repeatedly observed in academic and practical industrial flow computations. Without resorting to any subgrid-scale modeling, but based on a simple assumption regarding the streamwise component of flow velocity, it is shown theoretically that in a channel-flow computation, the application of the Gaussian filtering to the incompressible Navier-Stokes equations yields a numerically unstable term, a cross-derivative term, which is similar to one appearing in the Gaussian filtered Vlasov equation derived by Klimas [J. Comput. Phys. 68, 202 (1987)] and also to one derived recently by Kobayashi and Shimomura [Phys. Fluids 15, L29 (2003)] from the tensor-diffusivity subgrid-scale term in a dynamic mixed model. The present result predicts that not only the numerical methods and the subgrid-scale models employed but also only the applied filtering process can be a seed of this numerical instability. An investigation concerning the relationship between the turbulent energy scattering and the unstable term shows that the instability of the term does not necessarily represent the backscatter of kinetic energy which has been considered a possible origin of numerical instabilities in large eddy simulation. The present findings raise the question whether a numerically stable subgrid-scale model can be ideally accurate.

Accurate Size and Size-Distribution Determination of Polystyrene Latex Nanoparticles in Aqueous Medium Using Dynamic Light Scattering and Asymmetrical Flow Field Flow Fractionation with Multi-Angle Light Scattering

PubMed Central

Kato, Haruhisa; Nakamura, Ayako; Takahashi, Kayori; Kinugasa, Shinichi

2012-01-01

Accurate determination of the intensity-average diameter of polystyrene latex (PS-latex) by dynamic light scattering (DLS) was carried out through extrapolation of both the concentration of PS-latex and the observed scattering angle. Intensity-average diameter and size distribution were reliably determined by asymmetric flow field flow fractionation (AFFFF) using multi-angle light scattering (MALS) with consideration of band broadening in AFFFF separation. The intensity-average diameter determined by DLS and AFFFF-MALS agreed well within the estimated uncertainties, although the size distribution of PS-latex determined by DLS was less reliable in comparison with that determined by AFFFF-MALS. PMID:28348293

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

2016-01-01

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Predicting dynamics and rheology of blood flow: A comparative study of multiscale and low-dimensional models of red blood cells

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

Pan, Wenxiao; Fedosov, Dmitry A.; Caswell, Bruce

In this work we compare the predictive capability of two mathematical models for red blood cells (RBCs) focusing on blood flow in capillaries and arterioles. Both RBC models as well as their corresponding blood flows are based on the dissipative particle dynamics (DPD) method, a coarse-grained molecular dynamics approach. The first model employs a multiscale description of the RBC (MS-RBC), with its membrane represented by hundreds or even thousands of DPD-particles connected by springs into a triangular network in combination with out-of-plane elastic bending resistance. Extra dissipation within the network accounts for membrane viscosity, while the characteristic biconcave RBC shapemore » is achieved by imposition of constraints for constant membrane area and constant cell volume. The second model is based on a low-dimensional description (LD-RBC) constructed as a closed torus-like ring of only 10 large DPD colloidal particles. They are connected into a ring by worm-like chain (WLC) springs combined with bending resistance. The LD-RBC model can be fitted to represent the entire range of nonlinear elastic deformations as measured by optical-tweezers for healthy and for infected RBCs in malaria. MS-RBCs suspensions model the dynamics and rheology of blood flow accurately for any size vessel but this approach is computationally expensive above 100 microns. Surprisingly, the much more economical suspensions of LD-RBCs also capture the blood flow dynamics and rheology accurately except for vessels with sizes comparable to RBC diameter. In particular, the LD-RBC suspensions are shown to properly capture the experimental data for the apparent viscosity of blood and its cell-free layer (CFL) in tube flow. Taken together, these findings suggest a hierarchical approach in modeling blood flow in the arterial tree, whereby the MS-RBC model should be employed for capillaries and arterioles below 100 microns, the LD-RBC model for arterioles, and the continuum description for

Automatic intraaortic balloon pump timing using an intrabeat dicrotic notch prediction algorithm.

PubMed

Schreuder, Jan J; Castiglioni, Alessandro; Donelli, Andrea; Maisano, Francesco; Jansen, Jos R C; Hanania, Ramzi; Hanlon, Pat; Bovelander, Jan; Alfieri, Ottavio

2005-03-01

The efficacy of intraaortic balloon counterpulsation (IABP) during arrhythmic episodes is questionable. A novel algorithm for intrabeat prediction of the dicrotic notch was used for real time IABP inflation timing control. A windkessel model algorithm was used to calculate real-time aortic flow from aortic pressure. The dicrotic notch was predicted using a percentage of calculated peak flow. Automatic inflation timing was set at intrabeat predicted dicrotic notch and was combined with automatic IAB deflation. Prophylactic IABP was applied in 27 patients with low ejection fraction (< 35%) undergoing cardiac surgery. Analysis of IABP at a 1:4 ratio revealed that IAB inflation occurred at a mean of 0.6 +/- 5 ms from the dicrotic notch. In all patients accurate automatic timing at a 1:1 assist ratio was performed. Seventeen patients had episodes of severe arrhythmia, the novel IABP inflation algorithm accurately assisted 318 of 320 arrhythmic beats at a 1:1 ratio. The novel real-time intrabeat IABP inflation timing algorithm performed accurately in all patients during both regular rhythms and severe arrhythmia, allowing fully automatic intrabeat IABP timing.

Feedback about More Accurate versus Less Accurate Trials: Differential Effects on Self-Confidence and Activation

ERIC Educational Resources Information Center

Badami, Rokhsareh; VaezMousavi, Mohammad; Wulf, Gabriele; Namazizadeh, Mahdi

2012-01-01

One purpose of the present study was to examine whether self-confidence or anxiety would be differentially affected by feedback from more accurate rather than less accurate trials. The second purpose was to determine whether arousal variations (activation) would predict performance. On Day 1, participants performed a golf putting task under one of…

Modified unified kinetic scheme for all flow regimes.

PubMed

Liu, Sha; Zhong, Chengwen

2012-06-01

A modified unified kinetic scheme for the prediction of fluid flow behaviors in all flow regimes is described. The time evolution of macrovariables at the cell interface is calculated with the idea that both free transport and collision mechanisms should be considered. The time evolution of macrovariables is obtained through the conservation constraints. The time evolution of local Maxwellian distribution is obtained directly through the one-to-one mapping from the evolution of macrovariables. These improvements provide more physical realities in flow behaviors and more accurate numerical results in all flow regimes especially in the complex transition flow regime. In addition, the improvement steps introduce no extra computational complexity.

Two-dimensional flow nanometry of biological nanoparticles for accurate determination of their size and emission intensity

NASA Astrophysics Data System (ADS)

Block, Stephan; Fast, Björn Johansson; Lundgren, Anders; Zhdanov, Vladimir P.; Höök, Fredrik

2016-09-01

Biological nanoparticles (BNPs) are of high interest due to their key role in various biological processes and use as biomarkers. BNP size and composition are decisive for their functions, but simultaneous determination of both properties with high accuracy remains challenging. Optical microscopy allows precise determination of fluorescence/scattering intensity, but not the size of individual BNPs. The latter is better determined by tracking their random motion in bulk, but the limited illumination volume for tracking this motion impedes reliable intensity determination. Here, we show that by attaching BNPs to a supported lipid bilayer, subjecting them to hydrodynamic flows and tracking their motion via surface-sensitive optical imaging enable determination of their diffusion coefficients and flow-induced drifts, from which accurate quantification of both BNP size and emission intensity can be made. For vesicles, the accuracy of this approach is demonstrated by resolving the expected radius-squared dependence of their fluorescence intensity for radii down to 15 nm.

Improvement of operational prediction system applied to the oil spill prediction in the Yellow Sea

NASA Astrophysics Data System (ADS)

Kim, C.; Cho, Y.; Choi, B.; Jung, K.

2012-12-01

Multi-nested operational prediction system for the Yellow Sea (YS) has been developed to predict the movement of oil spill. Drifter trajectory simulations were performed to predict the path of the oil spill of the MV Hebei Spirit accident occurred on 7 December 2007. The oil spill trajectories at the surface predicted by numerical model without tidal forcing were remarkably faster than the observation. However the speed of drifters predicted by model considering tide was satisfactorily improved not only for the motion with tidal cycle but also for the motion with subtidal period. The subtidal flow of the simulation with tide was weaker than that without tide due to tidal stress. Tidal stress decelerated the southward subtidal flows driven by northwesterly wind along the Korean coast of the YS in winter. This result provides a substantial implication that tide must be included for accurate prediction of oil spill trajectory not only for variation within a tidal cycle but also for longer time scale advection in tide dominant area.

An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

PubMed

Nemati, Shamim; Holder, Andre; Razmi, Fereshteh; Stanley, Matthew D; Clifford, Gari D; Buchman, Timothy G

2018-04-01

Sepsis is among the leading causes of morbidity, mortality, and cost overruns in critically ill patients. Early intervention with antibiotics improves survival in septic patients. However, no clinically validated system exists for real-time prediction of sepsis onset. We aimed to develop and validate an Artificial Intelligence Sepsis Expert algorithm for early prediction of sepsis. Observational cohort study. Academic medical center from January 2013 to December 2015. Over 31,000 admissions to the ICUs at two Emory University hospitals (development cohort), in addition to over 52,000 ICU patients from the publicly available Medical Information Mart for Intensive Care-III ICU database (validation cohort). Patients who met the Third International Consensus Definitions for Sepsis (Sepsis-3) prior to or within 4 hours of their ICU admission were excluded, resulting in roughly 27,000 and 42,000 patients within our development and validation cohorts, respectively. None. High-resolution vital signs time series and electronic medical record data were extracted. A set of 65 features (variables) were calculated on hourly basis and passed to the Artificial Intelligence Sepsis Expert algorithm to predict onset of sepsis in the proceeding T hours (where T = 12, 8, 6, or 4). Artificial Intelligence Sepsis Expert was used to predict onset of sepsis in the proceeding T hours and to produce a list of the most significant contributing factors. For the 12-, 8-, 6-, and 4-hour ahead prediction of sepsis, Artificial Intelligence Sepsis Expert achieved area under the receiver operating characteristic in the range of 0.83-0.85. Performance of the Artificial Intelligence Sepsis Expert on the development and validation cohorts was indistinguishable. Using data available in the ICU in real-time, Artificial Intelligence Sepsis Expert can accurately predict the onset of sepsis in an ICU patient 4-12 hours prior to clinical recognition. A prospective study is necessary to determine the

Evaluation of particle-based flow characteristics using novel Eulerian indices

NASA Astrophysics Data System (ADS)

Cho, Youngmoon; Kang, Seongwon

2017-11-01

The main objective of this study is to evaluate flow characteristics in complex particle-laden flows efficiently using novel Eulerian indices. For flows with a large number of particles, a Lagrangian approach leads to accurate yet inefficient prediction in many engineering problems. We propose a technique based on Eulerian transport equation and ensemble-averaged particle properties, which enables efficient evaluation of various particle-based flow characteristics such as the residence time, accumulated travel distance, mean radial force, etc. As a verification study, we compare the developed Eulerian indices with those using Lagrangian approaches for laminar flows with and without a swirling motion and density ratio. The results show satisfactory agreement between two approaches. The accumulated travel distance is modified to analyze flow motions inside IC engines and, when applied to flow bench cases, it can predict swirling and tumbling motions successfully. For flows inside a cyclone separator, the mean radial force is applied to predict the separation of particles and is shown to have a high correlation to the separation efficiency for various working conditions. In conclusion, the proposed Eulerian indices are shown to be useful tools to analyze complex particle-based flow characteristics. Corresponding author.

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

Rajnarayan, Dev (Inventor); Sturdza, Peter (Inventor)

2016-01-01

A prediction of whether a point on a computer-generated surface is adjacent to laminar or turbulent flow is made using a transition prediction technique. A plurality of instability modes are obtained, each defined by one or more mode parameters. A vector of regressor weights is obtained for the known instability growth rates in a training dataset. For an instability mode in the plurality of instability modes, a covariance vector is determined. A predicted local instability growth rate at the point is determined using the covariance vector and the vector of regressor weights. Based on the predicted local instability growth rate, an n-factor envelope at the point is determined.

Bed Morphology and Sediment Transport under Oscillatory Flow

ERIC Educational Resources Information Center

Pedocchi Miljan, Francisco

2009-01-01

Recent laboratory and field experiments have shown the inability of existing oscillatory flow ripple predictors to accurately predict both ripple size and planform geometry. However, at this time, only partial adaptations of these predictors have been proposed in the literature to account for the observed discrepancies with experimental data…

Control surface hinge moment prediction using computational fluid dynamics

NASA Astrophysics Data System (ADS)

Simpson, Christopher David

The following research determines the feasibility of predicting control surface hinge moments using various computational methods. A detailed analysis is conducted using a 2D GA(W)-1 airfoil with a 20% plain flap. Simple hinge moment prediction methods are tested, including empirical Datcom relations and XFOIL. Steady-state and time-accurate turbulent, viscous, Navier-Stokes solutions are computed using Fun3D. Hinge moment coefficients are computed. Mesh construction techniques are discussed. An adjoint-based mesh adaptation case is also evaluated. An NACA 0012 45-degree swept horizontal stabilizer with a 25% elevator is also evaluated using Fun3D. Results are compared with experimental wind-tunnel data obtained from references. Finally, the costs of various solution methods are estimated. Results indicate that while a steady-state Navier-Stokes solution can accurately predict control surface hinge moments for small angles of attack and deflection angles, a time-accurate solution is necessary to accurately predict hinge moments in the presence of flow separation. The ability to capture the unsteady vortex shedding behavior present in moderate to large control surface deflections is found to be critical to hinge moment prediction accuracy. Adjoint-based mesh adaptation is shown to give hinge moment predictions similar to a globally-refined mesh for a steady-state 2D simulation.

A Simplified Micromechanical Modeling Approach to Predict the Tensile Flow Curve Behavior of Dual-Phase Steels

NASA Astrophysics Data System (ADS)

Nanda, Tarun; Kumar, B. Ravi; Singh, Vishal

2017-11-01

Micromechanical modeling is used to predict material's tensile flow curve behavior based on microstructural characteristics. This research develops a simplified micromechanical modeling approach for predicting flow curve behavior of dual-phase steels. The existing literature reports on two broad approaches for determining tensile flow curve of these steels. The modeling approach developed in this work attempts to overcome specific limitations of the existing two approaches. This approach combines dislocation-based strain-hardening method with rule of mixtures. In the first step of modeling, `dislocation-based strain-hardening method' was employed to predict tensile behavior of individual phases of ferrite and martensite. In the second step, the individual flow curves were combined using `rule of mixtures,' to obtain the composite dual-phase flow behavior. To check accuracy of proposed model, four distinct dual-phase microstructures comprising of different ferrite grain size, martensite fraction, and carbon content in martensite were processed by annealing experiments. The true stress-strain curves for various microstructures were predicted with the newly developed micromechanical model. The results of micromechanical model matched closely with those of actual tensile tests. Thus, this micromechanical modeling approach can be used to predict and optimize the tensile flow behavior of dual-phase steels.

Dry patches in a flowing film : Predicting rewetting and the effects of inertia

NASA Astrophysics Data System (ADS)

Lebon, Luc; Sebilleau, Julien; Limat, Laurent

2016-11-01

We study the effects of inertia on the shape and stability of dry patches using liquids of decreasing viscosities. These dry patches are formed when a liquid film flows down along a substrate under partial wetting conditions. They become stationary and exhibit an "arch" shape well described by a simple viscous model developed long ago by Podgorski. Surprisingly, this "arch" shape appears to be robust when one decreases the fluid viscosity which increases inertial effects, but the evolution of the apex curvature upon flow rate is strongly affected. We here proposed an improved description of the dry patch evolution taking into account several physical effects as the hydrostatic pressure in the liquid film, the curvature of the contact line, and these inertial effects. These ones affect both the mechanical equilibrium of the rim surrounding the dry patch and the flow inside the rim. This model allows us to show that the dry patch shape remains extremely close to the viscous -Podgorski- prediction but with a rescaling of the apex curvature. It also allows us to get a better prediction of the apex curvature dependence upon flow rate and a prediction of the rewetting threshold above which dry patches are swept away by the film flow.

Numerical simulation of steady and unsteady viscous flow in turbomachinery using pressure based algorithm

NASA Astrophysics Data System (ADS)

Lakshminarayana, B.; Ho, Y.; Basson, A.

1993-07-01

The objective of this research is to simulate steady and unsteady viscous flows, including rotor/stator interaction and tip clearance effects in turbomachinery. The numerical formulation for steady flow developed here includes an efficient grid generation scheme, particularly suited to computational grids for the analysis of turbulent turbomachinery flows and tip clearance flows, and a semi-implicit, pressure-based computational fluid dynamics scheme that directly includes artificial dissipation, and is applicable to both viscous and inviscid flows. The values of these artificial dissipation is optimized to achieve accuracy and convergency in the solution. The numerical model is used to investigate the structure of tip clearance flows in a turbine nozzle. The structure of leakage flow is captured accurately, including blade-to-blade variation of all three velocity components, pitch and yaw angles, losses and blade static pressures in the tip clearance region. The simulation also includes evaluation of such quantities of leakage mass flow, vortex strength, losses, dominant leakage flow regions and the spanwise extent affected by the leakage flow. It is demonstrated, through optimization of grid size and artificial dissipation, that the tip clearance flow field can be captured accurately. The above numerical formulation was modified to incorporate time accurate solutions. An inner loop iteration scheme is used at each time step to account for the non-linear effects. The computation of unsteady flow through a flat plate cascade subjected to a transverse gust reveals that the choice of grid spacing and the amount of artificial dissipation is critical for accurate prediction of unsteady phenomena. The rotor-stator interaction problem is simulated by starting the computation upstream of the stator, and the upstream rotor wake is specified from the experimental data. The results show that the stator potential effects have appreciable influence on the upstream rotor wake

Computing nonhydrostatic shallow-water flow over steep terrain

USGS Publications Warehouse

Denlinger, R.P.; O'Connell, D. R. H.

2008-01-01

Flood and dambreak hazards are not limited to moderate terrain, yet most shallow-water models assume that flow occurs over gentle slopes. Shallow-water flow over rugged or steep terrain often generates significant nonhydrostatic pressures, violating the assumption of hydrostatic pressure made in most shallow-water codes. In this paper, we adapt a previously published nonhydrostatic granular flow model to simulate shallow-water flow, and we solve conservation equations using a finite volume approach and an Harten, Lax, Van Leer, and Einfeldt approximate Riemann solver that is modified for a sloping bed and transient wetting and drying conditions. To simulate bed friction, we use the law of the wall. We test the model by comparison with an analytical solution and with results of experiments in flumes that have steep (31??) or shallow (0.3??) slopes. The law of the wall provides an accurate prediction of the effect of bed roughness on mean flow velocity over two orders of magnitude of bed roughness. Our nonhydrostatic, law-of-the-wall flow simulation accurately reproduces flume measurements of front propagation speed, flow depth, and bed-shear stress for conditions of large bed roughness. ?? 2008 ASCE.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

PubMed Central

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K.; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G.; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H.

2017-01-01

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. PMID:27899623

Prediction of Flows about Forebodies at High-Angle-of-Attack Dynamic Conditions

NASA Technical Reports Server (NTRS)

Fremaux, C. M.; vanDam, C. P.; Saephan, S.; DalBello, T.

2003-01-01

A Reynolds-average Navier Stokes method developed for rotorcraft type of flow problems is applied for predicting the forces and moments of forebody models at high-angle-of-attack dynamic conditions and for providing insight into the flow characteristics at these conditions. Wind-tunnel results from rotary testing on generic forebody models conducted by NASA Langley and DERA are used for comparison. This paper focuses on the steady-state flow problem.

Accurate First-Principles Spectra Predictions for Planetological and Astrophysical Applications at Various T-Conditions

NASA Astrophysics Data System (ADS)

Rey, M.; Nikitin, A. V.; Tyuterev, V.

2014-06-01

Knowledge of near infrared intensities of rovibrational transitions of polyatomic molecules is essential for the modeling of various planetary atmospheres, brown dwarfs and for other astrophysical applications 1,2,3. For example, to analyze exoplanets, atmospheric models have been developed, thus making the need to provide accurate spectroscopic data. Consequently, the spectral characterization of such planetary objects relies on the necessity of having adequate and reliable molecular data in extreme conditions (temperature, optical path length, pressure). On the other hand, in the modeling of astrophysical opacities, millions of lines are generally involved and the line-by-line extraction is clearly not feasible in laboratory measurements. It is thus suggested that this large amount of data could be interpreted only by reliable theoretical predictions. There exists essentially two theoretical approaches for the computation and prediction of spectra. The first one is based on empirically-fitted effective spectroscopic models. Another way for computing energies, line positions and intensities is based on global variational calculations using ab initio surfaces. They do not yet reach the spectroscopic accuracy stricto sensu but implicitly account for all intramolecular interactions including resonance couplings in a wide spectral range. The final aim of this work is to provide reliable predictions which could be quantitatively accurate with respect to the precision of available observations and as complete as possible. All this thus requires extensive first-principles quantum mechanical calculations essentially based on three necessary ingredients which are (i) accurate intramolecular potential energy surface and dipole moment surface components well-defined in a large range of vibrational displacements and (ii) efficient computational methods combined with suitable choices of coordinates to account for molecular symmetry properties and to achieve a good numerical

Aerothermal and aeroelastic response prediction of aerospace structures in high-speed flows using direct numerical simulation

NASA Astrophysics Data System (ADS)

Ostoich, Christopher Mark

due to a dome-induced horseshoe vortex scouring the panel's surface. Comparisons with reduced-order models of heat transfer indicate that they perform with varying levels of accuracy around some portions of the geometry while completely failing to predict significant heat loads in re- gions where the dome-influenced flow impacts the ceramic panel. Cumulative effects of flow-thermal coupling at later simulation times on the reduction of panel drag and surface heat transfer are quantified. The second fluid-structure study investigates the interaction between a thin metallic panel and a Mach 2.25 turbulent boundary layer with an ini- tial momentum thickness Reynolds number of 1200. A transient, non-linear, large deformation, 3D finite element solver is developed to compute the dynamic response of the panel. The solver is coupled at the fluid-structure interface with the compressible Navier-Stokes solver, the latter of which is used for a direct numerical simulation of the turbulent boundary layer. In this approach, no simplifying assumptions regarding the structural solution or turbulence modeling are made in order to get detailed solution data. It is found that the thin panel state evolves into a flutter type response char- acterized by high-amplitude, high-frequency oscillations into the flow. The oscillating panel disturbs the supersonic flow by introducing compression waves, modifying the turbulence, and generating fluctuations in the power exiting the top of the flow domain. The work in this thesis serves as a step forward in structural response prediction in high-speed flows. The results demonstrate the ability of high- fidelity numerical approaches to serve as a guide for reduced-order model improvement and as well as provide accurate and detailed solution data in scenarios where experimental approaches are difficult or impossible.

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

Accurate prediction of vaccine stability under real storage conditions and during temperature excursions.

PubMed

Clénet, Didier

2018-04-01

Due to their thermosensitivity, most vaccines must be kept refrigerated from production to use. To successfully carry out global immunization programs, ensuring the stability of vaccines is crucial. In this context, two important issues are critical, namely: (i) predicting vaccine stability and (ii) preventing product damage due to excessive temperature excursions outside of the recommended storage conditions (cold chain break). We applied a combination of advanced kinetics and statistical analyses on vaccine forced degradation data to accurately describe the loss of antigenicity for a multivalent freeze-dried inactivated virus vaccine containing three variants. The screening of large amounts of kinetic models combined with a statistical model selection approach resulted in the identification of two-step kinetic models. Predictions based on kinetic analysis and experimental stability data were in agreement, with approximately five percentage points difference from real values for long-term stability storage conditions, after excursions of temperature and during experimental shipments of freeze-dried products. Results showed that modeling a few months of forced degradation can be used to predict various time and temperature profiles endured by vaccines, i.e. long-term stability, short time excursions outside the labeled storage conditions or shipments at ambient temperature, with high accuracy. Pharmaceutical applications of the presented kinetics-based approach are discussed. Copyright © 2018 The Author. Published by Elsevier B.V. All rights reserved.

Modeling and simulation of high-speed wake flows

NASA Astrophysics Data System (ADS)

Barnhardt, Michael Daniel

High-speed, unsteady flows represent a unique challenge in computational hypersonics research. They are found in nearly all applications of interest, including the wakes of reentry vehicles, RCS jet interactions, and scramjet combustors. In each of these examples, accurate modeling of the flow dynamics plays a critical role in design performance. Nevertheless, literature surveys reveal that very little modern research effort has been made toward understanding these problems. The objective of this work is to synthesize current computational methods for high-speed flows with ideas commonly used to model low-speed, turbulent flows in order to create a framework by which we may reliably predict unsteady, hypersonic flows. In particular, we wish to validate the new methodology for the case of a turbulent wake flow at reentry conditions. Currently, heat shield designs incur significant mass penalties due to the large margins applied to vehicle afterbodies in lieu of a thorough understanding of the wake aerothermodynamics. Comprehensive validation studies are required to accurately quantify these modeling uncertainties. To this end, we select three candidate experiments against which we evaluate the accuracy of our methodology. The first set of experiments concern the Mars Science Laboratory (MSL) parachute system and serve to demonstrate that our implementation produces results consistent with prior studies at supersonic conditions. Second, we use the Reentry-F flight test to expand the application envelope to realistic flight conditions. Finally, in the last set of experiments, we examine a spherical capsule wind tunnel configuration in order to perform a more detailed analysis of a realistic flight geometry. In each case, we find that current 1st order in time, 2nd order in space upwind numerical methods are sufficiently accurate to predict statistical measurements: mean, RMS, standard deviation, and so forth. Further potential gains in numerical accuracy are

Nonlinear Reynolds stress model for turbulent shear flows

NASA Technical Reports Server (NTRS)

Barton, J. Michael; Rubinstein, R.; Kirtley, K. R.

1991-01-01

A nonlinear algebraic Reynolds stress model, derived using the renormalization group, is applied to equilibrium homogeneous shear flow and fully developed flow in a square duct. The model, which is quadratically nonlinear in the velocity gradients, successfully captures the large-scale inhomogeneity and anisotropy of the flows studied. The ratios of normal stresses, as well as the actual magnitudes of the stresses are correctly predicted for equilibrium homogeneous shear flow. Reynolds normal stress anisotropy and attendant turbulence driven secondary flow are predicted for a square duct. Profiles of mean velocity and normal stresses are in good agreement with measurements. Very close to walls, agreement with measurements diminishes. The model has the benefit of containing no arbitrary constants; all values are determined directly from the theory. It seems that near wall behavior is influenced by more than the large scale anisotropy accommodated in the current model. More accurate near wall calculations may well require a model for anisotropic dissipation.

Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

DOE PAGES

Sanchez-Gonzalez, A.; Micaelli, P.; Olivier, C.; ...

2017-06-05

Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy,more » we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. Lastly, this opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers.« less

Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

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

Sanchez-Gonzalez, A.; Micaelli, P.; Olivier, C.

Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy,more » we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. Lastly, this opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers.« less

Predicting ecological flow regime at ungaged sites: A comparison of methods

USGS Publications Warehouse

Murphy, Jennifer C.; Knight, Rodney R.; Wolfe, William J.; Gain, W. Scott

2012-01-01

Nineteen ecologically relevant streamflow characteristics were estimated using published rainfall–runoff and regional regression models for six sites with observed daily streamflow records in Kentucky. The regional regression model produced median estimates closer to the observed median for all but two characteristics. The variability of predictions from both models was generally less than the observed variability. The variability of the predictions from the rainfall–runoff model was greater than that from the regional regression model for all but three characteristics. Eight characteristics predicted by the rainfall–runoff model display positive or negative bias across all six sites; biases are not as pronounced for the regional regression model. Results suggest that a rainfall–runoff model calibrated on a single characteristic is less likely to perform well as a predictor of a range of other characteristics (flow regime) when compared with a regional regression model calibrated individually on multiple characteristics used to represent the flow regime. Poor model performance may misrepresent hydrologic conditions, potentially distorting the perceived risk of ecological degradation. Without prior selection of streamflow characteristics, targeted calibration, and error quantification, the widespread application of general hydrologic models to ecological flow studies is problematic. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

Computational Challenges of Viscous Incompressible Flows

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, Cetin; Kim, Chang Sung

2004-01-01

Over the past thirty years, numerical methods and simulation tools for incompressible flows have been advanced as a subset of the computational fluid dynamics (CFD) discipline. Although incompressible flows are encountered in many areas of engineering, simulation of compressible flow has been the major driver for developing computational algorithms and tools. This is probably due to the rather stringent requirements for predicting aerodynamic performance characteristics of flight vehicles, while flow devices involving low-speed or incompressible flow could be reasonably well designed without resorting to accurate numerical simulations. As flow devices are required to be more sophisticated and highly efficient CFD took become increasingly important in fluid engineering for incompressible and low-speed flow. This paper reviews some of the successes made possible by advances in computational technologies during the same period, and discusses some of the current challenges faced in computing incompressible flows.

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.

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

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

Liu, J; Wu, Q.J.; Yin, F

2014-06-15

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into fivemore » groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH/NCI under

Accurate and dynamic predictive model for better prediction in medicine and healthcare.

PubMed

Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

2018-05-01

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

Simulator predicts transient flow for Malaysian subsea pipeline

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

Inayat-Hussain, A.A.; Ayob, M.S.; Zain, A.B.M.

1996-04-15

In a step towards acquiring in-house capability in multiphase flow technology, Petronas Research and Scientific Services Sdn. Bhd., Kuala Lumpur, has developed two-phase flow simulation software for analyzing slow gas-condensate transient flow. Unlike its general-purpose contemporaries -- TACITE, OLGA, Traflow (OGJ, Jan. 3, 1994, p. 42; OGJ, Jan. 10, 1994, p. 52), and PLAC (AEA Technology, U.K.) -- ABASs is a dedicated software for slow transient flows generated during pigging operations in the Duyong network, offshore Malaysia. This network links the Duyong and Bekok fields to the onshore gas terminal (OGT) on the east coast of peninsular Malaysia. It predictsmore » the steady-state pressure drop vs. flow rates, condensate volume in the network, pigging dynamics including volume of produced slug, and the condensate build-up following pigging. The predictions of ABASs have been verified against field data obtained from the Duyong network. Presented here is an overview of the development, verification, and application of the ABASs software. Field data are presented for verification of the software, and several operational scenarios are simulated using the software. The field data and simulation study documented here will provide software users and developers with a further set of results on which to benchmark their own software and two-phase pipeline operating guidelines.« less

Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation.

PubMed

Reagan, Andrew J; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M

2016-01-01

A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth's weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction.

Predicting Flow Reversals in a Computational Fluid Dynamics Simulated Thermosyphon Using Data Assimilation

PubMed Central

Reagan, Andrew J.; Dubief, Yves; Dodds, Peter Sheridan; Danforth, Christopher M.

2016-01-01

A thermal convection loop is a annular chamber filled with water, heated on the bottom half and cooled on the top half. With sufficiently large forcing of heat, the direction of fluid flow in the loop oscillates chaotically, dynamics analogous to the Earth’s weather. As is the case for state-of-the-art weather models, we only observe the statistics over a small region of state space, making prediction difficult. To overcome this challenge, data assimilation (DA) methods, and specifically ensemble methods, use the computational model itself to estimate the uncertainty of the model to optimally combine these observations into an initial condition for predicting the future state. Here, we build and verify four distinct DA methods, and then, we perform a twin model experiment with the computational fluid dynamics simulation of the loop using the Ensemble Transform Kalman Filter (ETKF) to assimilate observations and predict flow reversals. We show that using adaptively shaped localized covariance outperforms static localized covariance with the ETKF, and allows for the use of less observations in predicting flow reversals. We also show that a Dynamic Mode Decomposition (DMD) of the temperature and velocity fields recovers the low dimensional system underlying reversals, finding specific modes which together are predictive of reversal direction. PMID:26849061

Device for accurately measuring mass flow of gases

DOEpatents

Hylton, James O.; Remenyik, Carl J.

1994-01-01

A device for measuring mass flow of gases which utilizes a substantially buoyant pressure vessel suspended within a fluid/liquid in an enclosure. The pressure vessel is connected to a weighing device for continuously determining weight change of the vessel as a function of the amount of gas within the pressure vessel. In the preferred embodiment, this pressure vessel is formed from inner and outer right circular cylindrical hulls, with a volume between the hulls being vented to the atmosphere external the enclosure. The fluid/liquid, normally in the form of water typically with an added detergent, is contained within an enclosure with the fluid/liquid being at a level such that the pressure vessel is suspended beneath this level but above a bottom of the enclosure. The buoyant pressure vessel can be interconnected with selected valves to an auxiliary pressure vessel so that initial flow can be established to or from the auxiliary pressure vessel prior to flow to or from the buoyant pressure vessel.

Modeling flow and transport in fracture networks using graphs

NASA Astrophysics Data System (ADS)

Karra, S.; O'Malley, D.; Hyman, J. D.; Viswanathan, H. S.; Srinivasan, G.

2018-03-01

Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers. Although modeling flow and transport using the discrete fracture network (DFN) approach is known to be more accurate due to incorporation of the detailed fracture network structure over continuum-based methods, capturing the flow and transport in such a wide range of scales is still computationally intractable. Furthermore, if one has to quantify uncertainty, hundreds of realizations of these DFN models have to be run. To reduce the computational burden, we solve flow and transport on a graph representation of a DFN. We study the accuracy of the graph approach by comparing breakthrough times and tracer particle statistical data between the graph-based and the high-fidelity DFN approaches, for fracture networks with varying number of fractures and degree of heterogeneity. Due to our recent developments in capabilities to perform DFN high-fidelity simulations on fracture networks with large number of fractures, we are in a unique position to perform such a comparison. We show that the graph approach shows a consistent bias with up to an order of magnitude slower breakthrough when compared to the DFN approach. We show that this is due to graph algorithm's underprediction of the pressure gradients across intersections on a given fracture, leading to slower tracer particle speeds between intersections and longer travel times. We present a bias correction methodology to the graph algorithm that reduces the discrepancy between the DFN and graph predictions. We show that with this bias correction, the graph algorithm predictions significantly improve and the results are very accurate. The good accuracy and the low computational cost, with O (104) times lower times than

Modeling flow and transport in fracture networks using graphs.

PubMed

Karra, S; O'Malley, D; Hyman, J D; Viswanathan, H S; Srinivasan, G

2018-03-01

Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers. Although modeling flow and transport using the discrete fracture network (DFN) approach is known to be more accurate due to incorporation of the detailed fracture network structure over continuum-based methods, capturing the flow and transport in such a wide range of scales is still computationally intractable. Furthermore, if one has to quantify uncertainty, hundreds of realizations of these DFN models have to be run. To reduce the computational burden, we solve flow and transport on a graph representation of a DFN. We study the accuracy of the graph approach by comparing breakthrough times and tracer particle statistical data between the graph-based and the high-fidelity DFN approaches, for fracture networks with varying number of fractures and degree of heterogeneity. Due to our recent developments in capabilities to perform DFN high-fidelity simulations on fracture networks with large number of fractures, we are in a unique position to perform such a comparison. We show that the graph approach shows a consistent bias with up to an order of magnitude slower breakthrough when compared to the DFN approach. We show that this is due to graph algorithm's underprediction of the pressure gradients across intersections on a given fracture, leading to slower tracer particle speeds between intersections and longer travel times. We present a bias correction methodology to the graph algorithm that reduces the discrepancy between the DFN and graph predictions. We show that with this bias correction, the graph algorithm predictions significantly improve and the results are very accurate. The good accuracy and the low computational cost, with O(10^{4}) times lower times

Modeling flow and transport in fracture networks using graphs

DOE PAGES

Karra, S.; O'Malley, D.; Hyman, J. D.; ...

2018-03-09

Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers. Although modeling flow and transport using the discrete fracture network (DFN) approach is known to be more accurate due to incorporation of the detailed fracture network structure over continuum-based methods, capturing the flow and transport in such a wide range of scales is still computationally intractable. Furthermore, if one has to quantify uncertainty, hundreds of realizationsmore » of these DFN models have to be run. To reduce the computational burden, we solve flow and transport on a graph representation of a DFN. We study the accuracy of the graph approach by comparing breakthrough times and tracer particle statistical data between the graph-based and the high-fidelity DFN approaches, for fracture networks with varying number of fractures and degree of heterogeneity. Due to our recent developments in capabilities to perform DFN high-fidelity simulations on fracture networks with large number of fractures, we are in a unique position to perform such a comparison. We show that the graph approach shows a consistent bias with up to an order of magnitude slower breakthrough when compared to the DFN approach. We show that this is due to graph algorithm's underprediction of the pressure gradients across intersections on a given fracture, leading to slower tracer particle speeds between intersections and longer travel times. We present a bias correction methodology to the graph algorithm that reduces the discrepancy between the DFN and graph predictions. We show that with this bias correction, the graph algorithm predictions significantly improve and the results are very accurate. In conclusion, the good accuracy and the low computational cost, with O(10 4

Modeling flow and transport in fracture networks using graphs

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

Karra, S.; O'Malley, D.; Hyman, J. D.

Fractures form the main pathways for flow in the subsurface within low-permeability rock. For this reason, accurately predicting flow and transport in fractured systems is vital for improving the performance of subsurface applications. Fracture sizes in these systems can range from millimeters to kilometers. Although modeling flow and transport using the discrete fracture network (DFN) approach is known to be more accurate due to incorporation of the detailed fracture network structure over continuum-based methods, capturing the flow and transport in such a wide range of scales is still computationally intractable. Furthermore, if one has to quantify uncertainty, hundreds of realizationsmore » of these DFN models have to be run. To reduce the computational burden, we solve flow and transport on a graph representation of a DFN. We study the accuracy of the graph approach by comparing breakthrough times and tracer particle statistical data between the graph-based and the high-fidelity DFN approaches, for fracture networks with varying number of fractures and degree of heterogeneity. Due to our recent developments in capabilities to perform DFN high-fidelity simulations on fracture networks with large number of fractures, we are in a unique position to perform such a comparison. We show that the graph approach shows a consistent bias with up to an order of magnitude slower breakthrough when compared to the DFN approach. We show that this is due to graph algorithm's underprediction of the pressure gradients across intersections on a given fracture, leading to slower tracer particle speeds between intersections and longer travel times. We present a bias correction methodology to the graph algorithm that reduces the discrepancy between the DFN and graph predictions. We show that with this bias correction, the graph algorithm predictions significantly improve and the results are very accurate. In conclusion, the good accuracy and the low computational cost, with O(10 4

Accurate prediction of severe allergic reactions by a small set of environmental parameters (NDVI, temperature).

PubMed

Notas, George; Bariotakis, Michail; Kalogrias, Vaios; Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions.

Accurate Prediction of Severe Allergic Reactions by a Small Set of Environmental Parameters (NDVI, Temperature)

PubMed Central

Andrianaki, Maria; Azariadis, Kalliopi; Kampouri, Errika; Theodoropoulou, Katerina; Lavrentaki, Katerina; Kastrinakis, Stelios; Kampa, Marilena; Agouridakis, Panagiotis; Pirintsos, Stergios; Castanas, Elias

2015-01-01

Severe allergic reactions of unknown etiology,necessitating a hospital visit, have an important impact in the life of affected individuals and impose a major economic burden to societies. The prediction of clinically severe allergic reactions would be of great importance, but current attempts have been limited by the lack of a well-founded applicable methodology and the wide spatiotemporal distribution of allergic reactions. The valid prediction of severe allergies (and especially those needing hospital treatment) in a region, could alert health authorities and implicated individuals to take appropriate preemptive measures. In the present report we have collecterd visits for serious allergic reactions of unknown etiology from two major hospitals in the island of Crete, for two distinct time periods (validation and test sets). We have used the Normalized Difference Vegetation Index (NDVI), a satellite-based, freely available measurement, which is an indicator of live green vegetation at a given geographic area, and a set of meteorological data to develop a model capable of describing and predicting severe allergic reaction frequency. Our analysis has retained NDVI and temperature as accurate identifiers and predictors of increased hospital severe allergic reactions visits. Our approach may contribute towards the development of satellite-based modules, for the prediction of severe allergic reactions in specific, well-defined geographical areas. It could also probably be used for the prediction of other environment related diseases and conditions. PMID:25794106

A Machine Learned Classifier That Uses Gene Expression Data to Accurately Predict Estrogen Receptor Status

PubMed Central

Bastani, Meysam; Vos, Larissa; Asgarian, Nasimeh; Deschenes, Jean; Graham, Kathryn; Mackey, John; Greiner, Russell

2013-01-01

Background Selecting the appropriate treatment for breast cancer requires accurately determining the estrogen receptor (ER) status of the tumor. However, the standard for determining this status, immunohistochemical analysis of formalin-fixed paraffin embedded samples, suffers from numerous technical and reproducibility issues. Assessment of ER-status based on RNA expression can provide more objective, quantitative and reproducible test results. Methods To learn a parsimonious RNA-based classifier of hormone receptor status, we applied a machine learning tool to a training dataset of gene expression microarray data obtained from 176 frozen breast tumors, whose ER-status was determined by applying ASCO-CAP guidelines to standardized immunohistochemical testing of formalin fixed tumor. Results This produced a three-gene classifier that can predict the ER-status of a novel tumor, with a cross-validation accuracy of 93.17±2.44%. When applied to an independent validation set and to four other public databases, some on different platforms, this classifier obtained over 90% accuracy in each. In addition, we found that this prediction rule separated the patients' recurrence-free survival curves with a hazard ratio lower than the one based on the IHC analysis of ER-status. Conclusions Our efficient and parsimonious classifier lends itself to high throughput, highly accurate and low-cost RNA-based assessments of ER-status, suitable for routine high-throughput clinical use. This analytic method provides a proof-of-principle that may be applicable to developing effective RNA-based tests for other biomarkers and conditions. PMID:24312637

Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.

PubMed

Li, Fuyi; Li, Chen; Marquez-Lago, Tatiana T; Leier, André; Akutsu, Tatsuya; Purcell, Anthony W; Smith, A Ian; Lithgow, Trevor; Daly, Roger J; Song, Jiangning; Chou, Kuo-Chen

2018-06-27

Kinase-regulated phosphorylation is a ubiquitous type of post-translational modification (PTM) in both eukaryotic and prokaryotic cells. Phosphorylation plays fundamental roles in many signalling pathways and biological processes, such as protein degradation and protein-protein interactions. Experimental studies have revealed that signalling defects caused by aberrant phosphorylation are highly associated with a variety of human diseases, especially cancers. In light of this, a number of computational methods aiming to accurately predict protein kinase family-specific or kinase-specific phosphorylation sites have been established, thereby facilitating phosphoproteomic data analysis. In this work, we present Quokka, a novel bioinformatics tool that allows users to rapidly and accurately identify human kinase family-regulated phosphorylation sites. Quokka was developed by using a variety of sequence scoring functions combined with an optimized logistic regression algorithm. We evaluated Quokka based on well-prepared up-to-date benchmark and independent test datasets, curated from the Phospho.ELM and UniProt databases, respectively. The independent test demonstrates that Quokka improves the prediction performance compared with state-of-the-art computational tools for phosphorylation prediction. In summary, our tool provides users with high-quality predicted human phosphorylation sites for hypothesis generation and biological validation. The Quokka webserver and datasets are freely available at http://quokka.erc.monash.edu/. Supplementary data are available at Bioinformatics online.

Euler flow predictions for an oscillating cascade using a high resolution wave-split scheme

NASA Technical Reports Server (NTRS)

Huff, Dennis L.; Swafford, Timothy W.; Reddy, T. S. R.

1991-01-01

A compressible flow code that can predict the nonlinear unsteady aerodynamics associated with transonic flows over oscillating cascades is developed and validated. The code solves the two dimensional, unsteady Euler equations using a time-marching, flux-difference splitting scheme. The unsteady pressures and forces can be determined for arbitrary input motions, although only harmonic pitching and plunging motions are addressed. The code solves the flow equations on a H-grid which is allowed to deform with the airfoil motion. Predictions are presented for both flat plate cascades and loaded airfoil cascades. Results are compared to flat plate theory and experimental data. Predictions are also presented for several oscillating cascades with strong normal shocks where the pitching amplitudes, cascade geometry and interblade phase angles are varied to investigate nonlinear behavior.

Design optimization for accurate flow simulations in 3D printed vascular phantoms derived from computed tomography angiography

NASA Astrophysics Data System (ADS)

Sommer, Kelsey; Izzo, Rick L.; Shepard, Lauren; Podgorsak, Alexander R.; Rudin, Stephen; Siddiqui, Adnan H.; Wilson, Michael F.; Angel, Erin; Said, Zaid; Springer, Michael; Ionita, Ciprian N.

2017-03-01

3D printing has been used to create complex arterial phantoms to advance device testing and physiological condition evaluation. Stereolithographic (STL) files of patient-specific cardiovascular anatomy are acquired to build cardiac vasculature through advanced mesh-manipulation techniques. Management of distal branches in the arterial tree is important to make such phantoms practicable. We investigated methods to manage the distal arterial flow resistance and pressure thus creating physiologically and geometrically accurate phantoms that can be used for simulations of image-guided interventional procedures with new devices. Patient specific CT data were imported into a Vital Imaging workstation, segmented, and exported as STL files. Using a mesh-manipulation program (Meshmixer) we created flow models of the coronary tree. Distal arteries were connected to a compliance chamber. The phantom was then printed using a Stratasys Connex3 multimaterial printer: the vessel in TangoPlus and the fluid flow simulation chamber in Vero. The model was connected to a programmable pump and pressure sensors measured flow characteristics through the phantoms. Physiological flow simulations for patient-specific vasculature were done for six cardiac models (three different vasculatures comparing two new designs). For the coronary phantom we obtained physiologically relevant waves which oscillated between 80 and 120 mmHg and a flow rate of 125 ml/min, within the literature reported values. The pressure wave was similar with those acquired in human patients. Thus we demonstrated that 3D printed phantoms can be used not only to reproduce the correct patient anatomy for device testing in image-guided interventions, but also for physiological simulations. This has great potential to advance treatment assessment and diagnosis.

Flow resistance in open channels with fixed movable bed

USGS Publications Warehouse

Simoes, Francisco J.

2010-01-01

In spite of an increasingly large body of research by many investigators, accurate quantitative prediction of open channel flow resistance remains a challenge. In general, the relations between the elements influencing resistance (turbulence, boundary roughness, and channel shape features, such as discrete obstacles, bars, channel curvature, recirculation areas, secondary circulation, etc.) and mean flow variables are complex and poorly understood. This has resulted in numerous approaches to compute friction using many and diverse variables and equally diverse prescriptions for their use. In this paper, a new resistance law for surface (grain) resistance, the resistance due to the flow viscous effects on the channel boundary roughness elements, is presented for the cases of flow in the transition (5 < Re* <70) and fully rough (Re* ≥ 70) turbulent flow regimes, where Re* is the Reynolds number based on shear velocity and sediment particle mean diameter. It is shown that the new law is sensitive to bed movement without requiring previous knowledge of sediment transport conditions. Comparisons between computation and measurements, as well as comparisons with other well-known existing roughness predictors, are presented to demonstrate its accuracy and range of application. It is shown that the method accurately predicts total friction losses in channels and natural rivers with plane beds, regardless of sediment transport conditions. This work is useful to hydraulic engineers involved with the derivation of depth-discharge relations in open channel flow and with the estimation of sediment transport rates for the case of bedload transport.

Daily river flow prediction based on Two-Phase Constructive Fuzzy Systems Modeling: A case of hydrological - meteorological measurements asymmetry

NASA Astrophysics Data System (ADS)

Bou-Fakhreddine, Bassam; Mougharbel, Imad; Faye, Alain; Abou Chakra, Sara; Pollet, Yann

2018-03-01

Accurate daily river flow forecast is essential in many applications of water resources such as hydropower operation, agricultural planning and flood control. This paper presents a forecasting approach to deal with a newly addressed situation where hydrological data exist for a period longer than that of meteorological data (measurements asymmetry). In fact, one of the potential solutions to resolve measurements asymmetry issue is data re-sampling. It is a matter of either considering only the hydrological data or the balanced part of the hydro-meteorological data set during the forecasting process. However, the main disadvantage is that we may lose potentially relevant information from the left-out data. In this research, the key output is a Two-Phase Constructive Fuzzy inference hybrid model that is implemented over the non re-sampled data. The introduced modeling approach must be capable of exploiting the available data efficiently with higher prediction efficiency relative to Constructive Fuzzy model trained over re-sampled data set. The study was applied to Litani River in the Bekaa Valley - Lebanon by using 4 years of rainfall and 24 years of river flow daily measurements. A Constructive Fuzzy System Model (C-FSM) and a Two-Phase Constructive Fuzzy System Model (TPC-FSM) are trained. Upon validating, the second model has shown a primarily competitive performance and accuracy with the ability to preserve a higher day-to-day variability for 1, 3 and 6 days ahead. In fact, for the longest lead period, the C-FSM and TPC-FSM were able of explaining respectively 84.6% and 86.5% of the actual river flow variation. Overall, the results indicate that TPC-FSM model has provided a better tool to capture extreme flows in the process of streamflow prediction.

Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

NASA Technical Reports Server (NTRS)

McMillan, Michelle L.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James

2010-01-01

Fail-safe inlet flow control may enable high-speed cruise efficiency, low noise signature, and reduced fuel-burn goals for hybrid wing-body aircraft. The objectives of this program are to develop flow control and prediction methodologies for boundary-layer ingesting (BLI) inlets used in these aircraft. This report covers the second of a three year program. The approach integrates experiments and numerical simulations. Both passive and active flow-control devices were tested in a small-scale wind tunnel. Hybrid actuation approaches, combining a passive microvane and active synthetic jet, were tested in various geometric arrangements. Detailed flow measurements were taken to provide insight into the flow physics. Results of the numerical simulations were correlated against experimental data. The sensitivity of results to grid resolution and turbulence models was examined. Aerodynamic benefits from microvanes and microramps were assessed when installed in an offset BLI inlet. Benefits were quantified in terms of recovery and distortion changes. Microvanes were more effective than microramps at improving recovery and distortion.

Noise from Supersonic Coaxial Jets. Part 1; Mean Flow Predictions

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Morris, Philip J.

1997-01-01

Recent theories for supersonic jet noise have used an instability wave noise generation model to predict radiated noise. This model requires a known mean flow that has typically been described by simple analytic functions for single jet mean flows. The mean flow of supersonic coaxial jets is not described easily in terms of analytic functions. To provide these profiles at all axial locations, a numerical scheme is developed to calculate the mean flow properties of a coaxial jet. The Reynolds-averaged, compressible, parabolic boundary layer equations are solved using a mixing length turbulence model. Empirical correlations are developed to account for the effects of velocity and temperature ratios and Mach number on the shear layer spreading. Both normal velocity profile and inverted velocity profile coaxial jets are considered. The mixing length model is modified in each case to obtain reasonable results when the two stream jet merges into a single fully developed jet. The mean flow calculations show both good qualitative and quantitative agreement with measurements in single and coaxial jet flows.

Literature search of publications concerning the prediction of dynamic inlet flow distortion and related topics

NASA Technical Reports Server (NTRS)

Schweikhhard, W. G.; Chen, Y. S.

1983-01-01

Publications prior to March 1981 were surveyed to determine inlet flow dynamic distortion prediction methods and to catalog experimental and analytical information concerning inlet flow dynamic distortion prediction methods and to catalog experimental and analytical information concerning inlet flow dynamics at the engine-inlet interface of conventional aircraft (excluding V/STOL). The sixty-five publications found are briefly summarized and tabulated according to topic and are cross-referenced according to content and nature of the investigation (e.g., predictive, experimental, analytical and types of tests). Three appendices include lists of references, authors, organizations and agencies conducting the studies. Also, selected materials summaries, introductions and conclusions - from the reports are included. Few reports were found covering methods for predicting the probable maximum distortion. The three predictive methods found are those of Melick, Jacox and Motycka. The latter two require extensive high response pressure measurements at the compressor face, while the Melick Technique can function with as few as one or two measurements.

Prediction of Daily Flow Duration Curves and Streamflow for Ungauged Catchments Using Regional Flow Duration Curves

EPA Science Inventory

This study presents a method to predict flow duration curves (FDCs) and streamflow for ungauged catchments in the Mid-Atlantic Region, USA. We selected 29 catchments from the Appalachian Plateau, Ridge and Valley, and Piedmont physiographic provinces to develop and test the propo...

Validation of model predictions of pore-scale fluid distributions during two-phase flow

NASA Astrophysics Data System (ADS)

Bultreys, Tom; Lin, Qingyang; Gao, Ying; Raeini, Ali Q.; AlRatrout, Ahmed; Bijeljic, Branko; Blunt, Martin J.

2018-05-01

Pore-scale two-phase flow modeling is an important technology to study a rock's relative permeability behavior. To investigate if these models are predictive, the calculated pore-scale fluid distributions which determine the relative permeability need to be validated. In this work, we introduce a methodology to quantitatively compare models to experimental fluid distributions in flow experiments visualized with microcomputed tomography. First, we analyzed five repeated drainage-imbibition experiments on a single sample. In these experiments, the exact fluid distributions were not fully repeatable on a pore-by-pore basis, while the global properties of the fluid distribution were. Then two fractional flow experiments were used to validate a quasistatic pore network model. The model correctly predicted the fluid present in more than 75% of pores and throats in drainage and imbibition. To quantify what this means for the relevant global properties of the fluid distribution, we compare the main flow paths and the connectivity across the different pore sizes in the modeled and experimental fluid distributions. These essential topology characteristics matched well for drainage simulations, but not for imbibition. This suggests that the pore-filling rules in the network model we used need to be improved to make reliable predictions of imbibition. The presented analysis illustrates the potential of our methodology to systematically and robustly test two-phase flow models to aid in model development and calibration.

Topographic Controls on Landslide and Debris-Flow Mobility

NASA Astrophysics Data System (ADS)

McCoy, S. W.; Pettitt, S.

2014-12-01

Regardless of whether a granular flow initiates from failure and liquefaction of a shallow landslide or from overland flow that entrains sediment to form a debris flow, the resulting flow poses hazards to downslope communities. Understanding controls on granular-flow mobility is critical for accurate hazard prediction. The topographic form of granular-flow paths can vary significantly across different steeplands and is one of the few flow-path properties that can be readily altered by engineered control structures such as closed-type check dams. We use grain-scale numerical modeling (discrete element method simulations) of free-surface, gravity-driven granular flows to investigate how different topographic profiles with the same mean slope and total relief can produce notable differences in flow mobility due to strong nonlinearities inherent to granular-flow dynamics. We describe how varying the profile shape from planar, to convex up, to concave up, as well how varying the number, size, and location of check dams along a flow path, changes flow velocity, thickness, discharge, energy dissipation, impact force and runout distance. Our preliminary results highlight an important path dependence for this nonlinear system, show that caution should be used when predicting flow dynamics from path-averaged properties, and provide some mechanics-based guidance for engineering control structures.

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.

Capillary Flow in Containers of Polygonal Section: Theory and Experiment

NASA Technical Reports Server (NTRS)

Weislogel, Mark M.; Rame, Enrique (Technical Monitor)

2001-01-01

An improved understanding of the large-length-scale capillary flows arising in a low-gravity environment is critical to that engineering community concerned with the design and analysis of spacecraft fluids management systems. Because a significant portion of liquid behavior in spacecraft is capillary dominated it is natural to consider designs that best exploit the spontaneous character of such flows. In the present work, a recently verified asymptotic analysis is extended to approximate spontaneous capillary flows in a large class of cylindrical containers of irregular polygonal section experiencing a step reduction in gravitational acceleration. Drop tower tests are conducted using partially-filled irregular triangular containers for comparison with the theoretical predictions. The degree to which the experimental data agree with the theory is a testament to the robustness of the basic analytical assumption of predominantly parallel flow. As a result, the closed form analytical expressions presented serve as simple, accurate tools for predicting bulk flow characteristics essential to practical low-g system design and analysis. Equations for predicting corner wetting rates, total container flow rates, and transient surfaces shapes are provided that are relevant also to terrestrial applications such as capillary flow in porous media.

Modeling and measuring non-Newtonian shear flows of soft interfaces

NASA Astrophysics Data System (ADS)

Lopez, Juan; Raghunandan, Aditya; Underhill, Patrick; Hirsa, Amir

2017-11-01

Soft interfaces of polymers, particles, and proteins between fluid phases are ubiquitous in industrial and natural processes. The flow response of such systems to deformation is often not linear, as one would expect for Newtonian interfaces. The resistance to (pure shear) flow of interfaces is generally characterized by a single intrinsic material property, the surface shear viscosity. Predicted shear responses of Newtonian interfaces have achieved consensus across a wide range of flow conditions and measurement devices, when the nonlinear hydrodynamic coupling to the bulk phase is correctly accounted for. However, predicting the flows of sheared non-Newtonian interfaces remains a challenge. Here, we introduce a computational model that incorporates a non-Newtonian constitutive equation for the sheared interface and properly accounts for the coupled interfacial and bulk phase flows. We compare predictions to experiments performed with a model phospholipid system, DPPC - the main constituent of mammalian lung surfactant. Densely packed films of DPPC are directly sheared in a knife-edge surface viscometer. Yield-stress and shear thinning behaviors are shown to be accurately captured across hydrodynamic regimes straddling the Stokes flow limit to inertia dominated flows. Supported by NASA Grant NNX13AQ22G.

Critical heat flux in subcooled flow boiling

NASA Astrophysics Data System (ADS)

Hall, David Douglas

The critical heat flux (CHF) phenomenon was investigated for water flow in tubes with particular emphasis on the development of methods for predicting CHF in the subcooled flow boiling regime. The Purdue University Boiling and Two-Phase Flow Laboratory (PU-BTPFL) CHF database for water flow in a uniformly heated tube was compiled from the world literature dating back to 1949 and represents the largest CHF database ever assembled with 32,544 data points from over 100 sources. The superiority of this database was proven via a detailed examination of previous databases. The PU-BTPFL CHF database is an invaluable tool for the development of CHF correlations and mechanistic models that are superior to existing ones developed with smaller, less comprehensive CHF databases. In response to the many inaccurate and inordinately complex correlations, two nondimensional, subcooled CHF correlations were formulated, containing only five adjustable constants and whose unique functional forms were determined without using a statistical analysis but rather using the parametric trends observed in less than 10% of the subcooled CHF data. The correlation based on inlet conditions (diameter, heated length, mass velocity, pressure, inlet quality) was by far the most accurate of all known subcooled CHF correlations, having mean absolute and root-mean-square (RMS) errors of 10.3% and 14.3%, respectively. The outlet (local) conditions correlation was the most accurate correlation based on local CHF conditions (diameter, mass velocity, pressure, outlet quality) and may be used with a nonuniform axial heat flux. Both correlations proved more accurate than a recent CHF look-up table commonly employed in nuclear reactor thermal hydraulic computer codes. An interfacial lift-off, subcooled CHF model was developed from a consideration of the instability of the vapor-liquid interface and the fraction of heat required for liquid-vapor conversion as opposed to that for bulk liquid heating. Severe

A multiscale red blood cell model with accurate mechanics, rheology, and dynamics.

PubMed

Fedosov, Dmitry A; Caswell, Bruce; Karniadakis, George Em

2010-05-19

Red blood cells (RBCs) have highly deformable viscoelastic membranes exhibiting complex rheological response and rich hydrodynamic behavior governed by special elastic and bending properties and by the external/internal fluid and membrane viscosities. We present a multiscale RBC model that is able to predict RBC mechanics, rheology, and dynamics in agreement with experiments. Based on an analytic theory, the modeled membrane properties can be uniquely related to the experimentally established RBC macroscopic properties without any adjustment of parameters. The RBC linear and nonlinear elastic deformations match those obtained in optical-tweezers experiments. The rheological properties of the membrane are compared with those obtained in optical magnetic twisting cytometry, membrane thermal fluctuations, and creep followed by cell recovery. The dynamics of RBCs in shear and Poiseuille flows is tested against experiments and theoretical predictions, and the applicability of the latter is discussed. Our findings clearly indicate that a purely elastic model for the membrane cannot accurately represent the RBC's rheological properties and its dynamics, and therefore accurate modeling of a viscoelastic membrane is necessary. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Debris flow runup on vertical barriers and adverse slopes

USGS Publications Warehouse

Iverson, Richard M.; George, David L.; Logan, Matthew

2016-01-01

Runup of debris flows against obstacles in their paths is a complex process that involves profound flow deceleration and redirection. We investigate the dynamics and predictability of runup by comparing results from large-scale laboratory experiments, four simple analytical models, and a depth-integrated numerical model (D-Claw). The experiments and numerical simulations reveal the important influence of unsteady, multidimensional flow on runup, and the analytical models highlight key aspects of the underlying physics. Runup against a vertical barrier normal to the flow path is dominated by rapid development of a shock, or jump in flow height, associated with abrupt deceleration of the flow front. By contrast, runup on sloping obstacles is initially dominated by a smooth flux of mass and momentum from the flow body to the flow front, which precedes shock development and commonly increases the runup height. D-Claw simulations that account for the emergence of shocks show that predicted runup heights vary systematically with the adverse slope angle and also with the Froude number and degree of liquefaction (or effective basal friction) of incoming flows. They additionally clarify the strengths and limitations of simplified analytical models. Numerical simulations based on a priori knowledge of the evolving dynamics of incoming flows yield quite accurate runup predictions. Less predictive accuracy is attained in ab initio simulations that compute runup based solely on knowledge of static debris properties in a distant debris flow source area. Nevertheless, the paucity of inputs required in ab initio simulations enhances their prospective value in runup forecasting.

Error-growth dynamics and predictability of surface thermally induced atmospheric flow

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

Zeng, X.; Pielke, R.A.

1993-09-01

Using the CSU Regional Atmospheric Modeling System (RAMS) in its nonhydrostatic and compressible configuration, over 200 two-dimensional simulations with [Delta]x = 2 km and [Delta]x = 100 m are performed to study in detail the initial adjustment process and the error-growth dynamics of surface thermally induced circulation including the sensitivity to initial conditions, boundary conditions, and model parameters, and to study the predictability as a function of the size of surface heat patches under a calm mean wind. It is found that the error growth is not sensitive to the characterisitics of the initial perturbations. The numerical smoothing has amore » strong impact on the initial adjustment process and on the error-growth dynamics. The predictability and flow structures, it is found that the vertical velocity field is strongly affected by the mean wind, and the flow structures are quite sensitive to the initial soil water content. The transition from organized flow to the situation in which fluxes are dominated by noncoherent turbulent eddies under a calm mean wind is quantitatively evaluated and this transition is different for different variables. The relationship between the predictability of a realization and of an ensemble average is discussed. The predictability and the coherent circulations modulated by the surface inhomogeneities are also studied by computing the autocorrelations and the power spectra. The three-dimensional mesoscale and large-eddy simulations are performed to verify the above results. It is found that the two-dimensional mesoscale (or fine resolution) simulation yields very close or similar results regarding the predictability as those from the three-dimensional mesoscale (or large eddy) simulation. The horizontally averaged quantities based on two-dimensional fine-resolution simulations are insensitive to initial perturbations and agree with those based on three-dimensional large-eddy simulations. 87 refs., 25 figs.« less

A comparative study of computational solutions to flow over a backward-facing step

NASA Technical Reports Server (NTRS)

Mizukami, M.; Georgiadis, N. J.; Cannon, M. R.

1993-01-01

A comparative study was conducted for computational fluid dynamic solutions to flow over a backward-facing step. This flow is a benchmark problem, with a simple geometry, but involves complicated flow physics such as free shear layers, reattaching flow, recirculation, and high turbulence intensities. Three Reynolds-averaged Navier-Stokes flow solvers with k-epsilon turbulence models were used, each using a different solution algorithm: finite difference, finite element, and hybrid finite element - finite difference. Comparisons were made with existing experimental data. Results showed that velocity profiles and reattachment lengths were predicted reasonably well by all three methods, while the skin friction coefficients were more difficult to predict accurately. It was noted that, in general, selecting an appropriate solver for each problem to be considered is important.

Predicting the magnetospheric plasma of weather

NASA Technical Reports Server (NTRS)

Dawson, John M.

1986-01-01

The prediction of the plasma environment in time, the plasma weather, is discussed. It is important to be able to predict when large magnetic storms will produce auroras, which will affect the space station operating in low orbit, and what precautions to take both for personnel and sensitive control (computer) equipment onboard. It is also important to start to establish a set of plasma weather records and a record of the ability to predict this weather. A successful forecasting system requires a set of satellite weather stations to provide data from which predictions can be made and a set of plasma weather codes capable of accurately forecasting the status of the Earth's magnetosphere. A numerical magnetohydrodynamic fluid model which is used to model the flow in the magnetosphere, the currents flowing into and out of the auroral regions, the magnetopause, the bow shock location and the magnetotail of the Earth is discussed.

Device for accurately measuring mass flow of gases

DOEpatents

Hylton, J.O.; Remenyik, C.J.

1994-08-09

A device for measuring mass flow of gases which utilizes a substantially buoyant pressure vessel suspended within a fluid/liquid in an enclosure is disclosed. The pressure vessel is connected to a weighing device for continuously determining weight change of the vessel as a function of the amount of gas within the pressure vessel. In the preferred embodiment, this pressure vessel is formed from inner and outer right circular cylindrical hulls, with a volume between the hulls being vented to the atmosphere external the enclosure. The fluid/liquid, normally in the form of water typically with an added detergent, is contained within an enclosure with the fluid/liquid being at a level such that the pressure vessel is suspended beneath this level but above a bottom of the enclosure. The buoyant pressure vessel can be interconnected with selected valves to an auxiliary pressure vessel so that initial flow can be established to or from the auxiliary pressure vessel prior to flow to or from the buoyant pressure vessel. 5 figs.

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.

PubMed

Schmidt, Florian; Gasparoni, Nina; Gasparoni, Gilles; Gianmoena, Kathrin; Cadenas, Cristina; Polansky, Julia K; Ebert, Peter; Nordström, Karl; Barann, Matthias; Sinha, Anupam; Fröhler, Sebastian; Xiong, Jieyi; Dehghani Amirabad, Azim; Behjati Ardakani, Fatemeh; Hutter, Barbara; Zipprich, Gideon; Felder, Bärbel; Eils, Jürgen; Brors, Benedikt; Chen, Wei; Hengstler, Jan G; Hamann, Alf; Lengauer, Thomas; Rosenstiel, Philip; Walter, Jörn; Schulz, Marcel H

2017-01-09

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Progress and challenges in the development of physically-based numerical models for prediction of flow and contaminant dispersion in the urban environment

NASA Astrophysics Data System (ADS)

Lien, F. S.; Yee, E.; Ji, H.; Keats, A.; Hsieh, K. J.

2006-06-01

The release of chemical, biological, radiological, or nuclear (CBRN) agents by terrorists or rogue states in a North American city (densely populated urban centre) and the subsequent exposure, deposition and contamination are emerging threats in an uncertain world. The modeling of the transport, dispersion, deposition and fate of a CBRN agent released in an urban environment is an extremely complex problem that encompasses potentially multiple space and time scales. The availability of high-fidelity, time-dependent models for the prediction of a CBRN agent's movement and fate in a complex urban environment can provide the strongest technical and scientific foundation for support of Canada's more broadly based effort at advancing counter-terrorism planning and operational capabilities.The objective of this paper is to report the progress of developing and validating an integrated, state-of-the-art, high-fidelity multi-scale, multi-physics modeling system for the accurate and efficient prediction of urban flow and dispersion of CBRN (and other toxic) materials discharged into these flows. Development of this proposed multi-scale modeling system will provide the real-time modeling and simulation tool required to predict injuries, casualties and contamination and to make relevant decisions (based on the strongest technical and scientific foundations) in order to minimize the consequences of a CBRN incident in a populated centre.

Assessment of Various Flow Solvers Used to Predict the Thermal Environment inside Space Shuttle Solid Rocket Motor Joints

NASA Technical Reports Server (NTRS)

Wang, Qun-Zhen; Cash, Steve (Technical Monitor)

2002-01-01

It is very important to accurately predict the gas pressure, gas and solid temperature, as well as the amount of O-ring erosion inside the space shuttle Reusable Solid Rocket Motor (RSRM) joints in the event of a leak path. The scenarios considered are typically hot combustion gas rapid pressurization events of small volumes through narrow and restricted flow paths. The ideal method for this prediction is a transient three-dimensional computational fluid dynamics (CFD) simulation with a computational domain including both combustion gas and surrounding solid regions. However, this has not yet been demonstrated to be economical for this application due to the enormous amount of CPU time and memory resulting from the relatively long fill time as well as the large pressure and temperature rising rate. Consequently, all CFD applications in RSRM joints so far are steady-state simulations with solid regions being excluded from the computational domain by assuming either a constant wall temperature or no heat transfer between the hot combustion gas and cool solid walls.

A Structured-Grid Quality Measure for Simulated Hypersonic Flows

NASA Technical Reports Server (NTRS)

Alter, Stephen J.

2004-01-01

A structured-grid quality measure is proposed, combining three traditional measurements: intersection angles, stretching, and curvature. Quality assesses whether the grid generated provides the best possible tradeoffs in grid stretching and skewness that enable accurate flow predictions, whereas the grid density is assumed to be a constraint imposed by the available computational resources and the desired resolution of the flow field. The usefulness of this quality measure is assessed by comparing heat transfer predictions from grid convergence studies for grids of varying quality in the range of [0.6-0.8] on an 8'half-angle sphere-cone, at laminar, perfect gas, Mach 10 wind tunnel conditions.

Exchange-Hole Dipole Dispersion Model for Accurate Energy Ranking in Molecular Crystal Structure Prediction.

PubMed

Whittleton, Sarah R; Otero-de-la-Roza, A; Johnson, Erin R

2017-02-14

Accurate energy ranking is a key facet to the problem of first-principles crystal-structure prediction (CSP) of molecular crystals. This work presents a systematic assessment of B86bPBE-XDM, a semilocal density functional combined with the exchange-hole dipole moment (XDM) dispersion model, for energy ranking using 14 compounds from the first five CSP blind tests. Specifically, the set of crystals studied comprises 11 rigid, planar compounds and 3 co-crystals. The experimental structure was correctly identified as the lowest in lattice energy for 12 of the 14 total crystals. One of the exceptions is 4-hydroxythiophene-2-carbonitrile, for which the experimental structure was correctly identified once a quasi-harmonic estimate of the vibrational free-energy contribution was included, evidencing the occasional importance of thermal corrections for accurate energy ranking. The other exception is an organic salt, where charge-transfer error (also called delocalization error) is expected to cause the base density functional to be unreliable. Provided the choice of base density functional is appropriate and an estimate of temperature effects is used, XDM-corrected density-functional theory is highly reliable for the energetic ranking of competing crystal structures.

Successes and Challenges of Incompressible Flow Simulation

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, Cetin

2003-01-01

During the past thirty years, numerical methods and simulation tools for incompressible flows have been advanced as a subset of CFD discipline. Even though incompressible flows are encountered in many areas of engineering, simulation of compressible flow has been the major driver for developing computational algorithms and tools. This is probably due to rather stringent requirements for predicting aerodynamic performance characteristics of flight vehicles, while flow devices involving low speed or incompressible flow could be reasonably well designed without resorting to accurate numerical simulations. As flow devices are required to be more sophisticated and highly efficient, CFD tools become indispensable in fluid engineering for incompressible and low speed flow. This paper is intended to review some of the successes made possible by advances in computational technologies during the same period, and discuss some of the current challenges.

Prediction of recirculation zones in isothermal coaxial jet flows relevant to combustors

NASA Technical Reports Server (NTRS)

Nallasamy, M.

1987-01-01

The characteristics of the recirculation zones in confined coaxial turbulent jets are investigated numerically employing the kappa - epsilon turbulence model. The geometrical arrangement corresponds to the experimental study of Owen (AIAA J. 1976) and the investigation is undertaken to provide information for isothermal flow relevant to combustor flows. For the first time, the shape, size, and location of the recirculation zones for the above experimental configuration are correctly predicted. The processes leading to the observed results are explained. Detailed comparisons of the prediction with measurements are made. It is shown that the recirculation zones are very sensitive to the central jet exit configuration and the velocity ratio of the jets.

An Extrapolation of a Radical Equation More Accurately Predicts Shelf Life of Frozen Biological Matrices.

PubMed

De Vore, Karl W; Fatahi, Nadia M; Sass, John E

2016-08-01

Arrhenius modeling of analyte recovery at increased temperatures to predict long-term colder storage stability of biological raw materials, reagents, calibrators, and controls is standard practice in the diagnostics industry. Predicting subzero temperature stability using the same practice is frequently criticized but nevertheless heavily relied upon. We compared the ability to predict analyte recovery during frozen storage using 3 separate strategies: traditional accelerated studies with Arrhenius modeling, and extrapolation of recovery at 20% of shelf life using either ordinary least squares or a radical equation y = B1x(0.5) + B0. Computer simulations were performed to establish equivalence of statistical power to discern the expected changes during frozen storage or accelerated stress. This was followed by actual predictive and follow-up confirmatory testing of 12 chemistry and immunoassay analytes. Linear extrapolations tended to be the most conservative in the predicted percent recovery, reducing customer and patient risk. However, the majority of analytes followed a rate of change that slowed over time, which was fit best to a radical equation of the form y = B1x(0.5) + B0. Other evidence strongly suggested that the slowing of the rate was not due to higher-order kinetics, but to changes in the matrix during storage. Predicting shelf life of frozen products through extrapolation of early initial real-time storage analyte recovery should be considered the most accurate method. Although in this study the time required for a prediction was longer than a typical accelerated testing protocol, there are less potential sources of error, reduced costs, and a lower expenditure of resources. © 2016 American Association for Clinical Chemistry.

A comparison between Bayes discriminant analysis and logistic regression for prediction of debris flow in southwest Sichuan, China

NASA Astrophysics Data System (ADS)

Xu, Wenbo; Jing, Shaocai; Yu, Wenjuan; Wang, Zhaoxian; Zhang, Guoping; Huang, Jianxi

2013-11-01

In this study, the high risk areas of Sichuan Province with debris flow, Panzhihua and Liangshan Yi Autonomous Prefecture, were taken as the studied areas. By using rainfall and environmental factors as the predictors and based on the different prior probability combinations of debris flows, the prediction of debris flows was compared in the areas with statistical methods: logistic regression (LR) and Bayes discriminant analysis (BDA). The results through the comprehensive analysis show that (a) with the mid-range scale prior probability, the overall predicting accuracy of BDA is higher than those of LR; (b) with equal and extreme prior probabilities, the overall predicting accuracy of LR is higher than those of BDA; (c) the regional predicting models of debris flows with rainfall factors only have worse performance than those introduced environmental factors, and the predicting accuracies of occurrence and nonoccurrence of debris flows have been changed in the opposite direction as the supplemented information.

SnowyOwl: accurate prediction of fungal genes by using RNA-Seq and homology information to select among ab initio models

PubMed Central

2014-01-01

Background Locating the protein-coding genes in novel genomes is essential to understanding and exploiting the genomic information but it is still difficult to accurately predict all the genes. The recent availability of detailed information about transcript structure from high-throughput sequencing of messenger RNA (RNA-Seq) delineates many expressed genes and promises increased accuracy in gene prediction. Computational gene predictors have been intensively developed for and tested in well-studied animal genomes. Hundreds of fungal genomes are now or will soon be sequenced. The differences of fungal genomes from animal genomes and the phylogenetic sparsity of well-studied fungi call for gene-prediction tools tailored to them. Results SnowyOwl is a new gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions and to evaluate the resulting models. The pipeline has been developed and streamlined by comparing its predictions to manually curated gene models in three fungal genomes and validated against the high-quality gene annotation of Neurospora crassa; SnowyOwl predicted N. crassa genes with 83% sensitivity and 65% specificity. SnowyOwl gains sensitivity by repeatedly running the HMM gene predictor Augustus with varied input parameters and selectivity by choosing the models with best homology to known proteins and best agreement with the RNA-Seq data. Conclusions SnowyOwl efficiently uses RNA-Seq data to produce accurate gene models in both well-studied and novel fungal genomes. The source code for the SnowyOwl pipeline (in Python) and a web interface (in PHP) is freely available from http://sourceforge.net/projects/snowyowl/. PMID:24980894

A Statistical Weather-Driven Streamflow Model: Enabling future flow predictions in data-scarce headwater streams

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.

2014-12-01

Predicting streamflow in headwaters and over a broad spatial scale pose unique challenges due to limited data availability. Flow observation gages for headwaters streams are less common than for larger rivers, and gages with records lengths of ten year or more are even more scarce. Thus, there is a great need for estimating streamflows in ungaged or sparsely-gaged headwaters. Further, there is often insufficient basin information to develop rainfall-runoff models that could be used to predict future flows under various climate scenarios. Headwaters in the northeastern U.S. are of particular concern to aquatic biologists, as these stream serve as essential habitat for native coldwater fish. In order to understand fish response to past or future environmental drivers, estimates of seasonal streamflow are needed. While there is limited flow data, there is a wealth of data for historic weather conditions. Observed data has been modeled to interpolate a spatially continuous historic weather dataset. (Mauer et al 2002). We present a statistical model developed by pairing streamflow observations with precipitation and temperature information for the same and preceding time-steps. We demonstrate this model's use to predict flow metrics at the seasonal time-step. While not a physical model, this statistical model represents the weather drivers. Since this model can predict flows not directly tied to reference gages, we can generate flow estimates for historic as well as potential future conditions.

Development of a One-Equation Eddy Viscosity Turbulence Model for Application to Complex Turbulent Flows

NASA Astrophysics Data System (ADS)

Wray, Timothy J.

Computational fluid dynamics (CFD) is routinely used in performance prediction and design of aircraft, turbomachinery, automobiles, and in many other industrial applications. Despite its wide range of use, deficiencies in its prediction accuracy still exist. One critical weakness is the accurate simulation of complex turbulent flows using the Reynolds-Averaged Navier-Stokes equations in conjunction with a turbulence model. The goal of this research has been to develop an eddy viscosity type turbulence model to increase the accuracy of flow simulations for mildly separated flows, flows with rotation and curvature effects, and flows with surface roughness. It is accomplished by developing a new zonal one-equation turbulence model which relies heavily on the flow physics; it is now known in the literature as the Wray-Agarwal one-equation turbulence model. The effectiveness of the new model is demonstrated by comparing its results with those obtained by the industry standard one-equation Spalart-Allmaras model and two-equation Shear-Stress-Transport k - o model and experimental data. Results for subsonic, transonic, and supersonic flows in and about complex geometries are presented. It is demonstrated that the Wray-Agarwal model can provide the industry and CFD researchers an accurate, efficient, and reliable turbulence model for the computation of a large class of complex turbulent flows.

Does the emergency surgery score accurately predict outcomes in emergent laparotomies?

PubMed

Peponis, Thomas; Bohnen, Jordan D; Sangji, Naveen F; Nandan, Anirudh R; Han, Kelsey; Lee, Jarone; Yeh, D Dante; de Moya, Marc A; Velmahos, George C; Chang, David C; Kaafarani, Haytham M A

2017-08-01

The emergency surgery score is a mortality-risk calculator for emergency general operation patients. We sought to examine whether the emergency surgery score predicts 30-day morbidity and mortality in a high-risk group of patients undergoing emergent laparotomy. Using the 2011-2012 American College of Surgeons National Surgical Quality Improvement Program database, we identified all patients who underwent emergent laparotomy using (1) the American College of Surgeons National Surgical Quality Improvement Program definition of "emergent," and (2) all Current Procedural Terminology codes denoting a laparotomy, excluding aortic aneurysm rupture. Multivariable logistic regression analyses were performed to measure the correlation (c-statistic) between the emergency surgery score and (1) 30-day mortality, and (2) 30-day morbidity after emergent laparotomy. As sensitivity analyses, the correlation between the emergency surgery score and 30-day mortality was also evaluated in prespecified subgroups based on Current Procedural Terminology codes. A total of 26,410 emergent laparotomy patients were included. Thirty-day mortality and morbidity were 10.2% and 43.8%, respectively. The emergency surgery score correlated well with mortality (c-statistic = 0.84); scores of 1, 11, and 22 correlated with mortalities of 0.4%, 39%, and 100%, respectively. Similarly, the emergency surgery score correlated well with morbidity (c-statistic = 0.74); scores of 0, 7, and 11 correlated with complication rates of 13%, 58%, and 79%, respectively. The morbidity rates plateaued for scores higher than 11. Sensitivity analyses demonstrated that the emergency surgery score effectively predicts mortality in patients undergoing emergent (1) splenic, (2) gastroduodenal, (3) intestinal, (4) hepatobiliary, or (5) incarcerated ventral hernia operation. The emergency surgery score accurately predicts outcomes in all types of emergent laparotomy patients and may prove valuable as a bedside decision

Quantification of electrical field-induced flow reversal in a microchannel.

PubMed

Pirat, C; Naso, A; van der Wouden, E J; Gardeniers, J G E; Lohse, D; van den Berg, A

2008-06-01

We characterize the electroosmotic flow in a microchannel with field effect flow control. High resolution measurements of the flow velocity, performed by micro particle image velocimetry, evidence the flow reversal induced by a local modification of the surface charge due to the presence of the gate. The shape of the microchannel cross-section is accurately extracted from these measurements. Experimental velocity profiles show a quantitative agreement with numerical results accounting for this exact shape. Analytical predictions assuming a rectangular cross-section are found to give a reasonable estimate of the velocity far enough from the walls.

Output-Adaptive Tetrahedral Cut-Cell Validation for Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Darmofal, David L.

2008-01-01

A cut-cell approach to Computational Fluid Dynamics (CFD) that utilizes the median dual of a tetrahedral background grid is described. The discrete adjoint is also calculated, which permits adaptation based on improving the calculation of a specified output (off-body pressure signature) in supersonic inviscid flow. These predicted signatures are compared to wind tunnel measurements on and off the configuration centerline 10 body lengths below the model to validate the method for sonic boom prediction. Accurate mid-field sonic boom pressure signatures are calculated with the Euler equations without the use of hybrid grid or signature propagation methods. Highly-refined, shock-aligned anisotropic grids were produced by this method from coarse isotropic grids created without prior knowledge of shock locations. A heuristic reconstruction limiter provided stable flow and adjoint solution schemes while producing similar signatures to Barth-Jespersen and Venkatakrishnan limiters. The use of cut-cells with an output-based adaptive scheme completely automated this accurate prediction capability after a triangular mesh is generated for the cut surface. This automation drastically reduces the manual intervention required by existing methods.

Predicting boundary shear stress and sediment transport over bed forms

USGS Publications Warehouse

McLean, S.R.; Wolfe, S.R.; Nelson, J.M.

1999-01-01

To estimate bed-load sediment transport rates in flows over bed forms such as ripples and dunes, spatially averaged velocity profiles are frequently used to predict mean boundary shear stress. However, such averaging obscures the complex, nonlinear interaction of wake decay, boundary-layer development, and topographically induced acceleration downstream of flow separation and often leads to inaccurate estimates of boundary stress, particularly skin friction, which is critically important in predicting bed-load transport rates. This paper presents an alternative methodology for predicting skin friction over 2D bed forms. The approach is based on combining the equations describing the mechanics of the internal boundary layer with semiempirical structure functions to predict the velocity at the crest of a bedform, where the flow is most similar to a uniform boundary layer. Significantly, the methodology is directed toward making specific predictions only at the bed-form crest, and as a result it avoids the difficulty and questionable validity of spatial averaging. The model provides an accurate estimate of the skin friction at the crest where transport rates are highest. Simple geometric constraints can be used to derive the mean transport rates as long as bed load is dominant.To estimate bed-load sediment transport rates in flows over bed forms such as ripples and dunes, spatially averaged velocity profiles are frequently used to predict mean boundary shear stress. However, such averaging obscures the complex, nonlinear interaction of wake decay, boundary-layer development, and topographically induced acceleration downstream of flow separation and often leads to inaccurate estimates of boundary stress, particularly skin friction, which is critically important in predicting bed-load transport rates. This paper presents an alternative methodology for predicting skin friction over 2D bed forms. The approach is based on combining the equations describing the mechanics of

Pelton turbine Needle erosion prediction based on 3D three- phase flow simulation

NASA Astrophysics Data System (ADS)

Chongji, Z.; Yexiang, X.; Wei, Z.; Yangyang, Y.; Lei, C.; Zhengwei, W.

2014-03-01

Pelton turbine, which applied to the high water head and small flow rate, is widely used in the mountainous area. During the operation period the sediment contained in the water does not only induce the abrasion of the buckets, but also leads to the erosion at the nozzle which may damage the needle structure. The nozzle and needle structure are mainly used to form high quality cylindrical jet and increase the efficiency of energy exchange in the runner to the most. Thus the needle erosion will lead to the deformation of jet, and then may cause the efficiency loss and cavitation. The favourable prediction of abrasion characteristic of needle can effectively guide the optimization design and maintenance of needle structure. This paper simulated the unsteady three-dimensional multi-phase flow in the nozzle and injected jet flow. As the jet containing water and sediment is injected into the free atmosphere air with high velocity, the VOF model was adopted to predict the water and air flow. The sediment is simplified into round solid particle and the discrete particle model (DPM) was employed to predict the needle abrasion characteristic. The sand particle tracks were analyzed to interpret the mechanism of sand erosion on the needle surface. And the numerical result of needle abrasion was obtained and compared with the abrasion field observation. The similarity of abrasion pattern between the numerical results and field observation illustrated the validity of the 3D multi-phase flow simulation method.

A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

PubMed

Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

2015-09-01

Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The computational modeling of supercritical carbon dioxide flow in solid wood material

NASA Astrophysics Data System (ADS)

Gething, Brad Allen

The use of supercritical carbon dioxide (SC CO2) as a solvent to deliver chemicals to porous media has shown promise in various industries. Recently, efforts by the wood treating industry have been made to use SC CO 2 as a replacement to more traditional methods of chemical preservative delivery. Previous studies have shown that the SC CO2 pressure treatment process is capable of impregnating solid wood materials with chemical preservatives, but concentration gradients of preservative often develop during treatment. Widespread application of the treatment process is unlikely unless the treatment inconsistencies can be improved for greater overall treating homogeneity. The development of a computational flow model to accurately predict the internal pressure of CO2 during treatment is integral to a more consistent treatment process. While similar models that attempt to describe the flow process have been proposed by Ward (1989) and Sahle-Demessie (1994), neither have been evaluated for accuracy. The present study was an evaluation of those models. More specifically, the present study evaluated the performance of a computational flow model, which was based on the viscous flow of compressible CO2 as a single phase through a porous medium at the macroscopic scale. Flow model performance was evaluated through comparisons between predicted pressures that corresponded to internal pressure development measured with inserted sensor probes during treatment of specimens. Pressure measurements were applied through a technique developed by Schneider (2000), which utilizes epoxy-sealed stainless steel tubes that are inserted into the wood as pressure probes. Two different wood species were investigated as treating specimens, Douglas-fir and shortleaf pine. Evaluations of the computational flow model revealed that it is sensitive to input parameters that relate to both processing conditions and material properties, particularly treating temperature and wood permeability

Computational and Experimental Flow Field Analyses of Separate Flow Chevron Nozzles and Pylon Interaction

NASA Technical Reports Server (NTRS)

Massey, Steven J.; Thomas, Russell H.; AbdolHamid, Khaled S.; Elmiligui, Alaa A.

2003-01-01

A computational and experimental flow field analyses of separate flow chevron nozzles is presented. The goal of this study is to identify important flow physics and modeling issues required to provide highly accurate flow field data which will later serve as input to the Jet3D acoustic prediction code. Four configurations are considered: a baseline round nozzle with and without a pylon, and a chevron core nozzle with and without a pylon. The flow is simulated by solving the asymptotically steady, compressible, Reynolds-averaged Navier-Stokes equations using an implicit, up-wind, flux-difference splitting finite volume scheme and standard two-equation kappa-epsilon turbulence model with a linear stress representation and the addition of a eddy viscosity dependence on total temperature gradient normalized by local turbulence length scale. The current CFD results are seen to be in excellent agreement with Jet Noise Lab data and show great improvement over previous computations which did not compensate for enhanced mixing due to high temperature gradients.

Predicting Turbulent Convective Heat Transfer in Three-Dimensional Duct Flows

NASA Technical Reports Server (NTRS)

Rokni, M.; Gatski, T. B.

1999-01-01

The performance of an explicit algebraic stress model is assessed in predicting the turbulent flow and forced heat transfer in straight ducts, with square, rectangular, trapezoidal and triangular cross-sections, under fully developed conditions over a range of Reynolds numbers. Iso-thermal conditions are imposed on the duct walls and the turbulent heat fluxes are modeled by gradient-diffusion type models. At high Reynolds numbers (>/= 10(exp 5)), wall functions are used for the velocity and temperature fields; while at low Reynolds numbers damping functions are introduced into the models. Hydraulic parameters such as friction factor and Nusselt number are well predicted even when damping functions are used, and the present formulation imposes minimal demand on the number of grid points without any convergence or stability problems. Comparison between the models is presented in terms of the hydraulic parameters, friction factor and Nusselt number, as well as in terms of the secondary flow patterns occurring within the ducts.

Monthly to seasonal low flow prediction: statistical versus dynamical models

NASA Astrophysics Data System (ADS)

Ionita-Scholz, Monica; Klein, Bastian; Meissner, Dennis; Rademacher, Silke

2016-04-01

While the societal and economical impacts of floods are well documented and assessable, the impacts of lows flows are less studied and sometimes overlooked. For example, over the western part of Europe, due to intense inland waterway transportation, the economical loses due to low flows are often similar compared to the ones due to floods. In general, the low flow aspect has the tendency to be underestimated by the scientific community. One of the best examples in this respect is the facts that at European level most of the countries have an (early) flood alert system, but in many cases no real information regarding the development, evolution and impacts of droughts. Low flows, occurring during dry periods, may result in several types of problems to society and economy: e.g. lack of water for drinking, irrigation, industrial use and power production, deterioration of water quality, inland waterway transport, agriculture, tourism, issuing and renewing waste disposal permits, and for assessing the impact of prolonged drought on aquatic ecosystems. As such, the ever-increasing demand on water resources calls for better a management, understanding and prediction of the water deficit situation and for more reliable and extended studies regarding the evolution of the low flow situations. In order to find an optimized monthly to seasonal forecast procedure for the German waterways, the Federal Institute of Hydrology (BfG) is exploring multiple approaches at the moment. On the one hand, based on the operational short- to medium-range forecasting chain, existing hydrological models are forced with two different hydro-meteorological inputs: (i) resampled historical meteorology generated by the Ensemble Streamflow Prediction approach and (ii) ensemble (re-) forecasts of ECMWF's global coupled ocean-atmosphere general circulation model, which have to be downscaled and bias corrected before feeding the hydrological models. As a second approach BfG evaluates in cooperation with

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

PubMed

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Numerical algorithm comparison for the accurate and efficient computation of high-incidence vortical flow

NASA Technical Reports Server (NTRS)

Chaderjian, Neal M.

1991-01-01

Computations from two Navier-Stokes codes, NSS and F3D, are presented for a tangent-ogive-cylinder body at high angle of attack. Features of this steady flow include a pair of primary vortices on the leeward side of the body as well as secondary vortices. The topological and physical plausibility of this vortical structure is discussed. The accuracy of these codes are assessed by comparison of the numerical solutions with experimental data. The effects of turbulence model, numerical dissipation, and grid refinement are presented. The overall efficiency of these codes are also assessed by examining their convergence rates, computational time per time step, and maximum allowable time step for time-accurate computations. Overall, the numerical results from both codes compared equally well with experimental data, however, the NSS code was found to be significantly more efficient than the F3D code.

NMRDSP: an accurate prediction of protein shape strings from NMR chemical shifts and sequence data.

PubMed

Mao, Wusong; Cong, Peisheng; Wang, Zhiheng; Lu, Longjian; Zhu, Zhongliang; Li, Tonghua

2013-01-01

Shape string is structural sequence and is an extremely important structure representation of protein backbone conformations. Nuclear magnetic resonance chemical shifts give a strong correlation with the local protein structure, and are exploited to predict protein structures in conjunction with computational approaches. Here we demonstrate a novel approach, NMRDSP, which can accurately predict the protein shape string based on nuclear magnetic resonance chemical shifts and structural profiles obtained from sequence data. The NMRDSP uses six chemical shifts (HA, H, N, CA, CB and C) and eight elements of structure profiles as features, a non-redundant set (1,003 entries) as the training set, and a conditional random field as a classification algorithm. For an independent testing set (203 entries), we achieved an accuracy of 75.8% for S8 (the eight states accuracy) and 87.8% for S3 (the three states accuracy). This is higher than only using chemical shifts or sequence data, and confirms that the chemical shift and the structure profile are significant features for shape string prediction and their combination prominently improves the accuracy of the predictor. We have constructed the NMRDSP web server and believe it could be employed to provide a solid platform to predict other protein structures and functions. The NMRDSP web server is freely available at http://cal.tongji.edu.cn/NMRDSP/index.jsp.

Effect of Spatio-Temporal Variability of Rainfall on Stream flow Prediction of Birr Watershed

NASA Astrophysics Data System (ADS)

Demisse, N. S.; Bitew, M. M.; Gebremichael, M.

2012-12-01

The effect of rainfall variability on our ability to forecast flooding events was poorly studied in complex terrain region of Ethiopia. In order to establish relation between rainfall variability and stream flow, we deployed 24 rain gauges across Birr watershed. Birr watershed is a medium size mountainous watershed with an area of 3000 km2 and elevation ranging between 1435 m.a.s.l and 3400 m.a.s.l in the central Ethiopia highlands. One summer monsoon rainfall of 2012 recorded at high temporal scale of 15 minutes interval and stream flow recorded at an hourly interval in three sub-watershed locations representing different scales were used in this study. Based on the data obtained from the rain gauges and stream flow observations, we quantify extent of temporal and spatial variability of rainfall across the watershed using standard statistical measures including mean, standard deviation and coefficient of variation. We also establish rainfall-runoff modeling system using a physically distributed hydrological model: the Soil and Water Assessment Tool (SWAT) and examine the effect of rainfall variability on stream flow prediction. The accuracy of predicted stream flow is measured through direct comparison with observed flooding events. The results demonstrate the significance of relation between stream flow prediction and rainfall variability in the understanding of runoff generation mechanisms at watershed scale, determination of dominant water balance components, and effect of variability on accuracy of flood forecasting activities.

Fast and accurate predictions of covalent bonds in chemical space.

PubMed

Chang, K Y Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O Anatole

2016-05-07

We assess the predictive accuracy of perturbation theory based estimates of changes in covalent bonding due to linear alchemical interpolations among molecules. We have investigated σ bonding to hydrogen, as well as σ and π bonding between main-group elements, occurring in small sets of iso-valence-electronic molecules with elements drawn from second to fourth rows in the p-block of the periodic table. Numerical evidence suggests that first order Taylor expansions of covalent bonding potentials can achieve high accuracy if (i) the alchemical interpolation is vertical (fixed geometry), (ii) it involves elements from the third and fourth rows of the periodic table, and (iii) an optimal reference geometry is used. This leads to near linear changes in the bonding potential, resulting in analytical predictions with chemical accuracy (∼1 kcal/mol). Second order estimates deteriorate the prediction. If initial and final molecules differ not only in composition but also in geometry, all estimates become substantially worse, with second order being slightly more accurate than first order. The independent particle approximation based second order perturbation theory performs poorly when compared to the coupled perturbed or finite difference approach. Taylor series expansions up to fourth order of the potential energy curve of highly symmetric systems indicate a finite radius of convergence, as illustrated for the alchemical stretching of H2 (+). Results are presented for (i) covalent bonds to hydrogen in 12 molecules with 8 valence electrons (CH4, NH3, H2O, HF, SiH4, PH3, H2S, HCl, GeH4, AsH3, H2Se, HBr); (ii) main-group single bonds in 9 molecules with 14 valence electrons (CH3F, CH3Cl, CH3Br, SiH3F, SiH3Cl, SiH3Br, GeH3F, GeH3Cl, GeH3Br); (iii) main-group double bonds in 9 molecules with 12 valence electrons (CH2O, CH2S, CH2Se, SiH2O, SiH2S, SiH2Se, GeH2O, GeH2S, GeH2Se); (iv) main-group triple bonds in 9 molecules with 10 valence electrons (HCN, HCP, HCAs, HSiN, HSi

An accurate method for measuring triploidy of larval fish spawns

USGS Publications Warehouse

Jenkins, Jill A.; Draugelis-Dale, Rassa O.; Glennon, Robert; Kelly, Anita; Brown, Bonnie L.; Morrison, John

2017-01-01

A standard flow cytometric protocol was developed for estimating triploid induction in batches of larval fish. Polyploid induction treatments are not guaranteed to be 100% efficient, thus the ability to quantify the proportion of triploid larvae generated by a particular treatment helps managers to stock high-percentage spawns and researchers to select treatments for efficient triploid induction. At 3 d posthatch, individual Grass Carp Ctenopharyngodon idella were mechanically dissociated into single-cell suspensions; nuclear DNA was stained with propidium iodide then analyzed by flow cytometry. Following ploidy identification of individuals, aliquots of diploid and triploid cell suspensions were mixed to generate 15 levels (0–100%) of known triploidy (n = 10). Using either 20 or 50 larvae per level, the observed triploid percentages were lower than the known, actual values. Using nonlinear regression analyses, quadratic equations solved for triploid proportions in mixed samples and corresponding estimation reference plots allowed for predicting triploidy. Thus, an accurate prediction of the proportion of triploids in a spawn can be made by following a standard larval processing and analysis protocol with either 20 or 50 larvae from a single spawn, coupled with applying the quadratic equations or reference plots to observed flow cytometry results. Due to the universality of triploid DNA content being 1.5 times the diploid level and because triploid fish consist of fewer cells than diploids, this method should be applicable to other produced triploid fish species, and it may be adapted for use with bivalves or other species where batch analysis is appropriate.

Improved prediction of disturbed flow via hemodynamically-inspired geometric variables.

PubMed

Bijari, Payam B; Antiga, Luca; Gallo, Diego; Wasserman, Bruce A; Steinman, David A

2012-06-01

Arterial geometry has long been considered as a pragmatic alternative for inferring arterial flow disturbances, and their impact on the natural history and treatment of vascular diseases. Traditionally, definition of geometric variables is based on convenient shape descriptors, with only superficial consideration of their influence on flow and wall shear stress patterns. In the present study we demonstrate that a more studied consideration of the actual (cf. nominal) local hemodynamics can lead to substantial improvements in the prediction of disturbed flow by geometry. Starting from a well-characterized computational fluid dynamics (CFD) dataset of 50 normal carotid bifurcations, we observed that disturbed flow tended to be confined proximal to the flow divider, whereas geometric variables previously shown to be significant predictors of disturbed flow included features distal to the flow divider in their definitions. Flaring of the bifurcation leading to flow separation was redefined as the maximum relative expansion of the common carotid artery (CCA), proximal to the flow divider. The beneficial effect of primary curvature on flow inertia, via suppression of flow separation, was characterized by the in-plane tortuosity of CCA as it enters the flare region. Multiple linear regressions of these redefined geometric variables against various metrics of disturbed flow revealed R(2) values approaching 0.6, better than the roughly 0.3 achieved using the conventional shape-based variables, while maintaining their demonstrated real-world reproducibility. Such a hemodynamically-inspired approach to the definition of geometric variables may reap benefits for other applications where geometry is used as a surrogate marker of local hemodynamics. Copyright © 2012 Elsevier Ltd. All rights reserved.

Error estimation for CFD aeroheating prediction under rarefied flow condition

NASA Astrophysics Data System (ADS)

Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian

2014-12-01

Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.

Investigation on the heat transfer characteristics during flow boiling of liquefied natural gas in a vertical micro-fin tube

NASA Astrophysics Data System (ADS)

Xu, Bin; Shi, Yumei; Chen, Dongsheng

2014-03-01

This paper presents an experimental investigation on the heat transfer characteristics of liquefied natural gas flow boiling in a vertical micro-fin tube. The effect of heat flux, mass flux and inlet pressure on the flow boiling heat transfer coefficients was analyzed. The Kim, Koyama, and two kinds of Wellsandt correlations with different Ftp coefficients were used to predict the flow boiling heat transfer coefficients. The predicted results showed that the Koyama correlation was the most accurate over the range of experimental conditions.

Does mesenteric venous imaging assessment accurately predict pathologic invasion in localized pancreatic ductal adenocarcinoma?

PubMed

Clanton, Jesse; Oh, Stephen; Kaplan, Stephen J; Johnson, Emily; Ross, Andrew; Kozarek, Richard; Alseidi, Adnan; Biehl, Thomas; Picozzi, Vincent J; Helton, William S; Coy, David; Dorer, Russell; Rocha, Flavio G

2018-05-09

Accurate prediction of mesenteric venous involvement in pancreatic ductal adenocarcinoma (PDAC) is necessary for adequate staging and treatment. A retrospective cohort study was conducted in PDAC patients at a single institution. All patients with resected PDAC and staging CT and EUS between 2003 and 2014 were included and sub-divided into "upfront resected" and "neoadjuvant chemotherapy (NAC)" groups. Independent imaging re-review was correlated to venous resection and venous invasion. Sensitivity, specificity, positive and negative predictive values were then calculated. A total of 109 patients underwent analysis, 60 received upfront resection, and 49 NAC. Venous resection (30%) and vein invasion (13%) was less common in patients resected upfront than those who received NAC (53% and 16%, respectively). Both CT and EUS had poor sensitivity (14-44%) but high specificity (75-95%) for detecting venous resection and vein invasion in patients resected upfront, whereas sensitivity was high (84-100%) and specificity was low (27-44%) after NAC. Preoperative CT and EUS in PDAC have similar efficacy but different predictive capacity in assessing mesenteric venous involvement depending on whether patients are resected upfront or received NAC. Both modalities appear to significantly overestimate true vascular involvement and should be interpreted in the appropriate clinical context. Copyright © 2018 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

Improved numerical methods for turbulent viscous flows aerothermal modeling program, phase 2

NASA Technical Reports Server (NTRS)

Karki, K. C.; Patankar, S. V.; Runchal, A. K.; Mongia, H. C.

1988-01-01

The details of a study to develop accurate and efficient numerical schemes to predict complex flows are described. In this program, several discretization schemes were evaluated using simple test cases. This assessment led to the selection of three schemes for an in-depth evaluation based on two-dimensional flows. The scheme with the superior overall performance was incorporated in a computer program for three-dimensional flows. To improve the computational efficiency, the selected discretization scheme was combined with a direct solution approach in which the fluid flow equations are solved simultaneously rather than sequentially.

Accurate load prediction by BEM with airfoil data from 3D RANS simulations

NASA Astrophysics Data System (ADS)

Schneider, Marc S.; Nitzsche, Jens; Hennings, Holger

2016-09-01

In this paper, two methods for the extraction of airfoil coefficients from 3D CFD simulations of a wind turbine rotor are investigated, and these coefficients are used to improve the load prediction of a BEM code. The coefficients are extracted from a number of steady RANS simulations, using either averaging of velocities in annular sections, or an inverse BEM approach for determination of the induction factors in the rotor plane. It is shown that these 3D rotor polars are able to capture the rotational augmentation at the inner part of the blade as well as the load reduction by 3D effects close to the blade tip. They are used as input to a simple BEM code and the results of this BEM with 3D rotor polars are compared to the predictions of BEM with 2D airfoil coefficients plus common empirical corrections for stall delay and tip loss. While BEM with 2D airfoil coefficients produces a very different radial distribution of loads than the RANS simulation, the BEM with 3D rotor polars manages to reproduce the loads from RANS very accurately for a variety of load cases, as long as the blade pitch angle is not too different from the cases from which the polars were extracted.

Accurate secondary structure prediction and fold recognition for circular dichroism spectroscopy

PubMed Central

Micsonai, András; Wien, Frank; Kernya, Linda; Lee, Young-Ho; Goto, Yuji; Réfrégiers, Matthieu; Kardos, József

2015-01-01

Circular dichroism (CD) spectroscopy is a widely used technique for the study of protein structure. Numerous algorithms have been developed for the estimation of the secondary structure composition from the CD spectra. These methods often fail to provide acceptable results on α/β-mixed or β-structure–rich proteins. The problem arises from the spectral diversity of β-structures, which has hitherto been considered as an intrinsic limitation of the technique. The predictions are less reliable for proteins of unusual β-structures such as membrane proteins, protein aggregates, and amyloid fibrils. Here, we show that the parallel/antiparallel orientation and the twisting of the β-sheets account for the observed spectral diversity. We have developed a method called β-structure selection (BeStSel) for the secondary structure estimation that takes into account the twist of β-structures. This method can reliably distinguish parallel and antiparallel β-sheets and accurately estimates the secondary structure for a broad range of proteins. Moreover, the secondary structure components applied by the method are characteristic to the protein fold, and thus the fold can be predicted to the level of topology in the CATH classification from a single CD spectrum. By constructing a web server, we offer a general tool for a quick and reliable structure analysis using conventional CD or synchrotron radiation CD (SRCD) spectroscopy for the protein science research community. The method is especially useful when X-ray or NMR techniques fail. Using BeStSel on data collected by SRCD spectroscopy, we investigated the structure of amyloid fibrils of various disease-related proteins and peptides. PMID:26038575

Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles.

PubMed

Zou, Lingyun; Nan, Chonghan; Hu, Fuquan

2013-12-15

Various human pathogens secret effector proteins into hosts cells via the type IV secretion system (T4SS). These proteins play important roles in the interaction between bacteria and hosts. Computational methods for T4SS effector prediction have been developed for screening experimental targets in several isolated bacterial species; however, widely applicable prediction approaches are still unavailable In this work, four types of distinctive features, namely, amino acid composition, dipeptide composition, .position-specific scoring matrix composition and auto covariance transformation of position-specific scoring matrix, were calculated from primary sequences. A classifier, T4EffPred, was developed using the support vector machine with these features and their different combinations for effector prediction. Various theoretical tests were performed in a newly established dataset, and the results were measured with four indexes. We demonstrated that T4EffPred can discriminate IVA and IVB effectors in benchmark datasets with positive rates of 76.7% and 89.7%, respectively. The overall accuracy of 95.9% shows that the present method is accurate for distinguishing the T4SS effector in unidentified sequences. A classifier ensemble was designed to synthesize all single classifiers. Notable performance improvement was observed using this ensemble system in benchmark tests. To demonstrate the model's application, a genome-scale prediction of effectors was performed in Bartonella henselae, an important zoonotic pathogen. A number of putative candidates were distinguished. A web server implementing the prediction method and the source code are both available at http://bioinfo.tmmu.edu.cn/T4EffPred.

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

Towards accurate cosmological predictions for rapidly oscillating scalar fields as dark matter

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

Ureña-López, L. Arturo; Gonzalez-Morales, Alma X., E-mail: lurena@ugto.mx, E-mail: alma.gonzalez@fisica.ugto.mx

2016-07-01

As we are entering the era of precision cosmology, it is necessary to count on accurate cosmological predictions from any proposed model of dark matter. In this paper we present a novel approach to the cosmological evolution of scalar fields that eases their analytic and numerical analysis at the background and at the linear order of perturbations. The new method makes use of appropriate angular variables that simplify the writing of the equations of motion, and which also show that the usual field variables play a secondary role in the cosmological dynamics. We apply the method to a scalar fieldmore » endowed with a quadratic potential and revisit its properties as dark matter. Some of the results known in the literature are recovered, and a better understanding of the physical properties of the model is provided. It is confirmed that there exists a Jeans wavenumber k {sub J} , directly related to the suppression of linear perturbations at wavenumbers k > k {sub J} , and which is verified to be k {sub J} = a √ mH . We also discuss some semi-analytical results that are well satisfied by the full numerical solutions obtained from an amended version of the CMB code CLASS. Finally we draw some of the implications that this new treatment of the equations of motion may have in the prediction of cosmological observables from scalar field dark matter models.« less

Accurate prediction of cellular co-translational folding indicates proteins can switch from post- to co-translational folding

PubMed Central

Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.

2016-01-01

The rates at which domains fold and codons are translated are important factors in determining whether a nascent protein will co-translationally fold and function or misfold and malfunction. Here we develop a chemical kinetic model that calculates a protein domain's co-translational folding curve during synthesis using only the domain's bulk folding and unfolding rates and codon translation rates. We show that this model accurately predicts the course of co-translational folding measured in vivo for four different protein molecules. We then make predictions for a number of different proteins in yeast and find that synonymous codon substitutions, which change translation-elongation rates, can switch some protein domains from folding post-translationally to folding co-translationally—a result consistent with previous experimental studies. Our approach explains essential features of co-translational folding curves and predicts how varying the translation rate at different codon positions along a transcript's coding sequence affects this self-assembly process. PMID:26887592

A multi-objective framework to predict flows of ungauged rivers within regions of sparse hydrometeorologic observation

NASA Astrophysics Data System (ADS)

Alipour, M.; Kibler, K. M.

2017-12-01

Despite advances in flow prediction, managers of ungauged rivers located within broad regions of sparse hydrometeorologic observation still lack prescriptive methods robust to the data challenges of such regions. We propose a multi-objective streamflow prediction framework for regions of minimum observation to select models that balance runoff efficiency with choice of accurate parameter values. We supplement sparse observed data with uncertain or low-resolution information incorporated as `soft' a priori parameter estimates. The performance of the proposed framework is tested against traditional single-objective and constrained single-objective calibrations in two catchments in a remote area of southwestern China. We find that the multi-objective approach performs well with respect to runoff efficiency in both catchments (NSE = 0.74 and 0.72), within the range of efficiencies returned by other models (NSE = 0.67 - 0.78). However, soil moisture capacity estimated by the multi-objective model resonates with a priori estimates (parameter residuals of 61 cm versus 289 and 518 cm for maximum soil moisture capacity in one catchment, and 20 cm versus 246 and 475 cm in the other; parameter residuals of 0.48 versus 0.65 and 0.7 for soil moisture distribution shape factor in one catchment, and 0.91 versus 0.79 and 1.24 in the other). Thus, optimization to a multi-criteria objective function led to very different representations of soil moisture capacity as compared to models selected by single-objective calibration, without compromising runoff efficiency. These different soil moisture representations may translate into considerably different hydrological behaviors. The proposed approach thus offers a preliminary step towards greater process understanding in regions of severe data limitations. For instance, the multi-objective framework may be an adept tool to discern between models of similar efficiency to select models that provide the "right answers for the right reasons

Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

NASA Technical Reports Server (NTRS)

McMillan, Michelle L.; Mackie, Scott A.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James L.

2011-01-01

Fail-safe, hybrid, flow control (HFC) is a promising technology for meeting high-speed cruise efficiency, low-noise signature, and reduced fuel-burn goals for future, Hybrid-Wing-Body (HWB) aircraft with embedded engines. This report details the development of HFC technology that enables improved inlet performance in HWB vehicles with highly integrated inlets and embedded engines without adversely affecting vehicle performance. In addition, new test techniques for evaluating Boundary-Layer-Ingesting (BLI)-inlet flow-control technologies developed and demonstrated through this program are documented, including the ability to generate a BLI-like inlet-entrance flow in a direct-connect, wind-tunnel facility, as well as, the use of D-optimal, statistically designed experiments to optimize test efficiency and enable interpretation of results. Validated improvements in numerical analysis tools and methods accomplished through this program are also documented, including Reynolds-Averaged Navier-Stokes CFD simulations of steady-state flow physics for baseline, BLI-inlet diffuser flow, as well as, that created by flow-control devices. Finally, numerical methods were employed in a ground-breaking attempt to directly simulate dynamic distortion. The advances in inlet technologies and prediction tools will help to meet and exceed "N+2" project goals for future HWB aircraft.

Landscape genetics as a tool for conservation planning: predicting the effects of landscape change on gene flow.

PubMed

van Strien, Maarten J; Keller, Daniela; Holderegger, Rolf; Ghazoul, Jaboury; Kienast, Felix; Bolliger, Janine

2014-03-01

For conservation managers, it is important to know whether landscape changes lead to increasing or decreasing gene flow. Although the discipline of landscape genetics assesses the influence of landscape elements on gene flow, no studies have yet used landscape-genetic models to predict gene flow resulting from landscape change. A species that has already been severely affected by landscape change is the large marsh grasshopper (Stethophyma grossum), which inhabits moist areas in fragmented agricultural landscapes in Switzerland. From transects drawn between all population pairs within maximum dispersal distance (< 3 km), we calculated several measures of landscape composition as well as some measures of habitat configuration. Additionally, a complete sampling of all populations in our study area allowed incorporating measures of population topology. These measures together with the landscape metrics formed the predictor variables in linear models with gene flow as response variable (F(ST) and mean pairwise assignment probability). With a modified leave-one-out cross-validation approach, we selected the model with the highest predictive accuracy. With this model, we predicted gene flow under several landscape-change scenarios, which simulated construction, rezoning or restoration projects, and the establishment of a new population. For some landscape-change scenarios, significant increase or decrease in gene flow was predicted, while for others little change was forecast. Furthermore, we found that the measures of population topology strongly increase model fit in landscape genetic analysis. This study demonstrates the use of predictive landscape-genetic models in conservation and landscape planning.

Methodology Development of a Gas-Liquid Dynamic Flow Regime Transition Model

NASA Astrophysics Data System (ADS)

Doup, Benjamin Casey

Current reactor safety analysis codes, such as RELAP5, TRACE, and CATHARE, use flow regime maps or flow regime transition criteria that were developed for static fully-developed two-phase flows to choose interfacial transfer models that are necessary to solve the two-fluid model. The flow regime is therefore difficult to identify near the flow regime transitions, in developing two-phase flows, and in transient two-phase flows. Interfacial area transport equations were developed to more accurately predict the dynamic nature of two-phase flows. However, other model coefficients are still flow regime dependent. Therefore, an accurate prediction of the flow regime is still important. In the current work, the methodology for the development of a dynamic flow regime transition model that uses the void fraction and interfacial area concentration obtained by solving three-field the two-fluid model and two-group interfacial area transport equation is investigated. To develop this model, detailed local experimental data are obtained, the two-group interfacial area transport equations are revised, and a dynamic flow regime transition model is evaluated using a computational fluid dynamics model. Local experimental data is acquired for 63 different flow conditions in bubbly, cap-bubbly, slug, and churn-turbulent flow regimes. The measured parameters are the group-1 and group-2 bubble number frequency, void fraction, interfacial area concentration, and interfacial bubble velocities. The measurements are benchmarked by comparing the prediction of the superficial gas velocities, determined using the local measurements with those determined from volumetric flow rate measurements and the agreement is generally within +/-20%. The repeatability four-sensor probe construction process is within +/-10%. The repeatability of the measurement process is within +/-7%. The symmetry of the test section is examined and the average agreement is within +/-5.3% at z/D = 10 and +/-3.4% at z/D = 32

A gene expression biomarker accurately predicts estrogen ...

EPA Pesticide Factsheets

The EPA’s vision for the Endocrine Disruptor Screening Program (EDSP) in the 21st Century (EDSP21) includes utilization of high-throughput screening (HTS) assays coupled with computational modeling to prioritize chemicals with the goal of eventually replacing current Tier 1 screening tests. The ToxCast program currently includes 18 HTS in vitro assays that evaluate the ability of chemicals to modulate estrogen receptor α (ERα), an important endocrine target. We propose microarray-based gene expression profiling as a complementary approach to predict ERα modulation and have developed computational methods to identify ERα modulators in an existing database of whole-genome microarray data. The ERα biomarker consisted of 46 ERα-regulated genes with consistent expression patterns across 7 known ER agonists and 3 known ER antagonists. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression data sets from experiments in MCF-7 cells. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% or 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) OECD ER reference chemicals including “very weak” agonists and replicated predictions based on 18 in vitro ER-associated HTS assays. For 114 chemicals present in both the HTS data and the MCF-7 c

Comparison of simplified models in the prediction of two phase flow in pipelines

NASA Astrophysics Data System (ADS)

Jerez-Carrizales, M.; Jaramillo, J. E.; Fuentes, D.

2014-06-01

Prediction of two phase flow in pipelines is a common task in engineering. It is a complex phenomenon and many models have been developed to find an approximate solution to the problem. Some old models, such as the Hagedorn & Brown (HB) model, have been highlighted by many authors to give very good performance. Furthermore, many modifications have been applied to this method to improve its predictions. In this work two simplified models which are based on empiricism (HB and Mukherjee and Brill, MB) are considered. One mechanistic model which is based on the physics of the phenomenon (AN) and it still needs some correlations called closure relations is also used. Moreover, a drift flux model defined in steady state that is flow pattern dependent (HK model) is implemented. The implementation of these methods was tested using published data in the scientific literature for vertical upward flows. Furthermore, a comparison of the predictive performance of the four models is done against a well from Campo Escuela Colorado. Difference among four models is smaller than difference with experimental data from the well in Campo Escuela Colorado.

A numerical study of granular dam-break flow

NASA Astrophysics Data System (ADS)

Pophet, N.; Rébillout, L.; Ozeren, Y.; Altinakar, M.

2017-12-01

Accurate prediction of granular flow behavior is essential to optimize mitigation measures for hazardous natural granular flows such as landslides, debris flows and tailings-dam break flows. So far, most successful models for these types of flows focus on either pure granular flows or flows of saturated grain-fluid mixtures by employing a constant friction model or more complex rheological models. These saturated models often produce non-physical result when they are applied to simulate flows of partially saturated mixtures. Therefore, more advanced models are needed. A numerical model was developed for granular flow employing a constant friction and μ(I) rheology (Jop et al., J. Fluid Mech. 2005) coupled with a groundwater flow model for seepage flow. The granular flow is simulated by solving a mixture model using Finite Volume Method (FVM). The Volume-of-Fluid (VOF) technique is used to capture the free surface motion. The constant friction and μ(I) rheological models are incorporated in the mixture model. The seepage flow is modeled by solving Richards equation. A framework is developed to couple these two solvers in OpenFOAM. The model was validated and tested by reproducing laboratory experiments of partially and fully channelized dam-break flows of dry and initially saturated granular material. To obtain appropriate parameters for rheological models, a series of simulations with different sets of rheological parameters is performed. The simulation results obtained from constant friction and μ(I) rheological models are compared with laboratory experiments for granular free surface interface, front position and velocity field during the flows. The numerical predictions indicate that the proposed model is promising in predicting dynamics of the flow and deposition process. The proposed model may provide more reliable insight than the previous assumed saturated mixture model, when saturated and partially saturated portions of granular mixture co-exist.

Highly accurate apparatus for electrochemical characterization of the felt electrodes used in redox flow batteries

NASA Astrophysics Data System (ADS)

Park, Jong Ho; Park, Jung Jin; Park, O. Ok; Jin, Chang-Soo; Yang, Jung Hoon

2016-04-01

Because of the rise in renewable energy use, the redox flow battery (RFB) has attracted extensive attention as an energy storage system. Thus, many studies have focused on improving the performance of the felt electrodes used in RFBs. However, existing analysis cells are unsuitable for characterizing felt electrodes because of their complex 3-dimensional structure. Analysis is also greatly affected by the measurement conditions, viz. compression ratio, contact area, and contact strength between the felt and current collector. To address the growing need for practical analytical apparatus, we report a new analysis cell for accurate electrochemical characterization of felt electrodes under various conditions, and compare it with previous ones. In this cell, the measurement conditions can be exhaustively controlled with a compression supporter. The cell showed excellent reproducibility in cyclic voltammetry analysis and the results agreed well with actual RFB charge-discharge performance.

A Hybrid Windkessel Model of Blood Flow in Arterial Tree Using Velocity Profile Method

NASA Astrophysics Data System (ADS)

Aboelkassem, Yasser; Virag, Zdravko

2016-11-01

For the study of pulsatile blood flow in the arterial system, we derived a coupled Windkessel-Womersley mathematical model. Initially, a 6-elements Windkessel model is proposed to describe the hemodynamics transport in terms of constant resistance, inductance and capacitance. This model can be seen as a two compartment model, in which the compartments are connected by a rigid pipe, modeled by one inductor and resistor. The first viscoelastic compartment models proximal part of the aorta, the second elastic compartment represents the rest of the arterial tree and aorta can be seen as the connection pipe. Although the proposed 6-elements lumped model was able to accurately reconstruct the aortic pressure, it can't be used to predict the axial velocity distribution in the aorta and the wall shear stress and consequently, proper time varying pressure drop. We then modified this lumped model by replacing the connection pipe circuit elements with a vessel having a radius R and a length L. The pulsatile flow motions in the vessel are resolved instantaneously along with the Windkessel like model enable not only accurate prediction of the aortic pressure but also wall shear stress and frictional pressure drop. The proposed hybrid model has been validated using several in-vivo aortic pressure and flow rate data acquired from different species such as, humans, dogs and pigs. The method accurately predicts the time variation of wall shear stress and frictional pressure drop. Institute for Computational Medicine, Dept. Biomedical Engineering.

Bathyphotometer bioluminescence potential measurements: A framework for characterizing flow agitators and predicting flow-stimulated bioluminescence intensity

NASA Astrophysics Data System (ADS)

Latz, Michael I.; Rohr, Jim

2013-07-01

BBP. This correlation, when further scaled by pipe diameter, effectively predicted bioluminescence intensity in fully developed turbulent flow in a 0.83-cm i.d. pipe. Determining similar correlations between other bathyphotometer flow agitators and flow fields will allow bioluminescence potential measurements to become a more powerful tool for the oceanographic community.

Studies on Normal and Microgravity Annular Two Phase Flows

NASA Technical Reports Server (NTRS)

Balakotaiah, V.; Jayawardena, S. S.; Nguyen, L. T.

1999-01-01

Two-phase gas-liquid flows occur in a wide variety of situations. In addition to normal gravity applications, such flows may occur in space operations such as active thermal control systems, power cycles, and storage and transfer of cryogenic fluids. Various flow patterns exhibiting characteristic spatial and temporal distribution of the two phases are observed in two-phase flows. The magnitude and orientation of gravity with respect to the flow has a strong impact on the flow patterns observed and on their boundaries. The identification of the flow pattern of a flow is somewhat subjective. The same two-phase flow (especially near a flow pattern transition boundary) may be categorized differently by different researchers. Two-phase flow patterns are somewhat simplified in microgravity, where only three flow patterns (bubble, slug and annular) have been observed. Annular flow is obtained for a wide range of gas and liquid flow rates, and it is expected to occur in many situations under microgravity conditions. Slug flow needs to be avoided, because vibrations caused by slugs result in unwanted accelerations. Therefore, it is important to be able to accurately predict the flow pattern which exists under given operating conditions. It is known that the wavy liquid film in annular flow has a profound influence on the transfer of momentum and heat between the phases. Thus, an understanding of the characteristics of the wavy film is essential for developing accurate correlations. In this work, we review our recent results on flow pattern transitions and wavy films in microgravity.

PredSTP: a highly accurate SVM based model to predict sequential cystine stabilized peptides.

PubMed

Islam, S M Ashiqul; Sajed, Tanvir; Kearney, Christopher Michel; Baker, Erich J

2015-07-05

Numerous organisms have evolved a wide range of toxic peptides for self-defense and predation. Their effective interstitial and macro-environmental use requires energetic and structural stability. One successful group of these peptides includes a tri-disulfide domain arrangement that offers toxicity and high stability. Sequential tri-disulfide connectivity variants create highly compact disulfide folds capable of withstanding a variety of environmental stresses. Their combination of toxicity and stability make these peptides remarkably valuable for their potential as bio-insecticides, antimicrobial peptides and peptide drug candidates. However, the wide sequence variation, sources and modalities of group members impose serious limitations on our ability to rapidly identify potential members. As a result, there is a need for automated high-throughput member classification approaches that leverage their demonstrated tertiary and functional homology. We developed an SVM-based model to predict sequential tri-disulfide peptide (STP) toxins from peptide sequences. One optimized model, called PredSTP, predicted STPs from training set with sensitivity, specificity, precision, accuracy and a Matthews correlation coefficient of 94.86%, 94.11%, 84.31%, 94.30% and 0.86, respectively, using 200 fold cross validation. The same model outperforms existing prediction approaches in three independent out of sample testsets derived from PDB. PredSTP can accurately identify a wide range of cystine stabilized peptide toxins directly from sequences in a species-agnostic fashion. The ability to rapidly filter sequences for potential bioactive peptides can greatly compress the time between peptide identification and testing structural and functional properties for possible antimicrobial and insecticidal candidates. A web interface is freely available to predict STP toxins from http://crick.ecs.baylor.edu/.

Predicting Low Flow Conditions from Climatic Indices - Indicator-Based Modeling for Climate Change Impact Assessment

NASA Astrophysics Data System (ADS)

Fangmann, Anne; Haberlandt, Uwe

2014-05-01

In the face of climate change, the assessment of future hydrological regimes has become indispensable in the field of water resources management. Investigation of potential change is vital for proper planning, especially with regard to hydrological extremes. Commonly, projection of future streamflow is done applying process-based hydrological models, using climate model data as input, whose complex model structures generally require excessive amounts of time and effort for set-up and computation. This study aims at identifying practical alternatives to the employment of sophisticated models by considering simpler, yet sufficiently accurate methods for modeling rainfall-runoff relations with regard to hydrological extremes. The focus is thereby put on the prediction of low flow periods, which are, in contrast to flood events, characterized by extended durations and spatial dimensions. The models to be established in this study base on indicators, which characterize both meteorological and hydrological conditions within dry periods. This approach makes direct use of the coupling between atmospheric driving forces and streamflow response with the underlying presumption that low-precipitation and high-evaporation periods result in diminished flow, implying that relationships exist between the properties of both meteorological and hydrological events (duration, volume, severity etc.). Eventually, optimal combinations of meteorological indicators are sought that are suitable to predict various low flow characteristics with satisfactory accuracy. Two approaches for model specification are tested: a) multiple linear regression, and b) Fuzzy logic. The data used for this study are daily time series of mean discharge obtained from 294 gauges with variable record length situated in the federal state of Lower Saxony, Germany, as well as interpolated climate variables available for a period from 1951 to 2011. After extraction of a variety of indicators from the available

Flow Test to Predict Early Hypotony and Hypertensive Phase After Ahmed Glaucoma Valve (AGV) Surgical Implantation.

PubMed

Cheng, Jason; Beltran-Agullo, Laura; Buys, Yvonne M; Moss, Edward B; Gonzalez, Johanna; Trope, Graham E

2016-06-01

To assess the validity of a preimplantation flow test to predict early hypotony [intraocular pressure (IOP)≤5 mm Hg on 2 consecutive visits and hypertensive phase (HP) (IOP>21 mm Hg) after Ahmed Glaucoma Valve (AGV) implantation. Prospective interventional study on patients receiving an AGV. A preimplantation flow test using a gravity-driven reservoir and an open manometer was performed on all AGVs. Opening pressure (OP) and closing pressure (CP) were defined as the pressure at which fluid was seen to flow or stop flowing through the AGV, respectively. OP and CP were measured twice per AGV. Patients were followed for 12 weeks. In total, 20 eyes from 19 patients were enrolled. At 12 weeks the mean IOP decreased from 29.2±9.1 to 16.8±5.2 mm Hg (P<0.01). The mean AGV OP was 17.5±5.4 mm Hg and the mean CP was 6.7±2.3 mm Hg. Early (within 2 wk postoperative) HP occurred in 37% and hypotony in 16% of cases. An 18 mm Hg cutoff for the OP gave a sensitivity of 0.71, specificity of 0.83, positive predictive value of 0.71, and negative predictive value of 0.83 for predicting an early HP. A 7 mm Hg cutoff for the CP yielded a sensitivity of 1.0, specificity of 0.38, positive predictive value of 0.23, and negative predictive value of 1.0 for predicting hypotony. Preoperative OP and CP may predict early hypotony or HP and may be used as a guide as to which AGV valves to discard before implantation surgery.

Getting into the musical zone: trait emotional intelligence and amount of practice predict flow in pianists

PubMed Central

Marin, Manuela M.; Bhattacharya, Joydeep

2013-01-01

Being “in flow” or “in the zone” is defined as an extremely focused state of consciousness which occurs during intense engagement in an activity. In general, flow has been linked to peak performances (high achievement) and feelings of intense pleasure and happiness. However, empirical research on flow in music performance is scarce, although it may offer novel insights into the question of why musicians engage in musical activities for extensive periods of time. Here, we focused on individual differences in a group of 76 piano performance students and assessed their flow experience in piano performance as well as their trait emotional intelligence. Multiple regression analysis revealed that flow was predicted by the amount of daily practice and trait emotional intelligence. Other background variables (gender, age, duration of piano training and age of first piano training) were not predictive. To predict high achievement in piano performance (i.e., winning a prize in a piano competition), a seven-predictor logistic regression model was fitted to the data, and we found that the odds of winning a prize in a piano competition were predicted by the amount of daily practice and the age at which piano training began. Interestingly, a positive relationship between flow and high achievement was not supported. Further, we explored the role of musical emotions and musical styles in the induction of flow by a self-developed questionnaire. Results suggest that besides individual differences among pianists, specific structural and compositional features of musical pieces and related emotional expressions may facilitate flow experiences. Altogether, these findings highlight the role of emotion in the experience of flow during music performance and call for further experiments addressing emotion in relation to the performer and the music alike. PMID:24319434

Project for Solar-Terrestrial Environment Prediction (PSTEP): Towards Predicting Next Solar Cycle

NASA Astrophysics Data System (ADS)

Imada, S.; Iijima, H.; Hotta, H.; Shiota, D.; Kanou, O.; Fujiyama, M.; Kusano, K.

2016-10-01

It is believed that the longer-term variations of the solar activity can affect the Earth's climate. Therefore, predicting the next solar cycle is crucial for the forecast of the "solar-terrestrial environment". To build prediction schemes for the activity level of the next solar cycle is a key for the long-term space weather study. Although three-years prediction can be almost achieved, the prediction of next solar cycle is very limited, so far. We are developing a five-years prediction scheme by combining the Surface Flux Transport (SFT) model and the most accurate measurements of solar magnetic fields as a part of the PSTEP (Project for Solar-Terrestrial Environment Prediction),. We estimate the meridional flow, differential rotation, and turbulent diffusivity from recent modern observations (Hinode and Solar Dynamics Observatory). These parameters are used in the SFT models to predict the polar magnetic fields strength at the solar minimum. In this presentation, we will explain the outline of our strategy to predict the next solar cycle. We also report the present status and the future perspective of our project.

PSSP-RFE: accurate prediction of protein structural class by recursive feature extraction from PSI-BLAST profile, physical-chemical property and functional annotations.

PubMed

Li, Liqi; Cui, Xiang; Yu, Sanjiu; Zhang, Yuan; Luo, Zhong; Yang, Hua; Zhou, Yue; Zheng, Xiaoqi

2014-01-01

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies of protein structural class prediction are sufficiently high for high similarity datasets, but still far from being satisfactory for low similarity datasets, i.e., below 40% in pairwise sequence similarity. Therefore, we present a novel method for accurate and reliable protein structural class prediction for both high and low similarity datasets. This method is based on Support Vector Machine (SVM) in conjunction with integrated features from position-specific score matrix (PSSM), PROFEAT and Gene Ontology (GO). A feature selection approach, SVM-RFE, is also used to rank the integrated feature vectors through recursively removing the feature with the lowest ranking score. The definitive top features selected by SVM-RFE are input into the SVM engines to predict the structural class of a query protein. To validate our method, jackknife tests were applied to seven widely used benchmark datasets, reaching overall accuracies between 84.61% and 99.79%, which are significantly higher than those achieved by state-of-the-art tools. These results suggest that our method could serve as an accurate and cost-effective alternative to existing methods in protein structural classification, especially for low similarity datasets.

Non-Darcian flow of shear-thinning fluids through packed beads: Experiments and predictions using Forchheimer's law and Ergun's equation

NASA Astrophysics Data System (ADS)

Rodríguez de Castro, Antonio; Radilla, Giovanni

2017-02-01

The flow of shear-thinning fluids through unconsolidated porous media is present in a number of important industrial applications such as soil depollution, Enhanced Oil Recovery or filtration of polymeric liquids. Therefore, predicting the pressure drop-flow rate relationship in model porous media has been the scope of major research efforts during the last decades. Although the flow of Newtonian fluids through packs of spherical particles is well understood in most cases, much less is known regarding the flow of shear-thinning fluids as high molecular weight polymer aqueous solutions. In particular, the experimental data for the non-Darcian flow of shear-thinning fluids are scarce and so are the current approaches for their prediction. Given the relevance of non-Darcian shear-thinning flow, the scope of this work is to perform an experimental study to systematically evaluate the effects of fluid shear rheology on the flow rate-pressure drop relationships for the non-Darcian flow through different packs of glass spheres. To do so, xanthan gum aqueous solutions with different polymer concentrations are injected through four packs of glass spheres with uniform size under Darcian and inertial flow regimes. A total of 1560 experimental data are then compared with predictions coming from different methods based on the extension of widely used Ergun's equation and Forchheimer's law to the case of shear thinning fluids, determining the accuracy of these predictions. The use of a proper definition for Reynolds number and a realistic model to represent the rheology of the injected fluids results in the porous media are shown to be key aspects to successfully predict pressure drop-flow rate relationships for the inertial shear-thinning flow in packed beads.

Turbulent flow in a 180 deg bend: Modeling and computations

NASA Technical Reports Server (NTRS)

Kaul, Upender K.

1989-01-01

A low Reynolds number k-epsilon turbulence model was presented which yields accurate predictions of the kinetic energy near the wall. The model is validated with the experimental channel flow data of Kreplin and Eckelmann. The predictions are also compared with earlier results from direct simulation of turbulent channel flow. The model is especially useful for internal flows where the inflow boundary condition of epsilon is not easily prescribed. The model partly derives from some observations based on earlier direct simulation results of near-wall turbulence. The low Reynolds number turbulence model together with an existing curvature correction appropriate to spinning cylinder flows was used to simulate the flow in a U-bend with the same radius of curvature as the Space Shuttle Main Engine (SSME) Turn-Around Duct (TAD). The present computations indicate a space varying curvature correction parameter as opposed to a constant parameter as used in the spinning cylinder flows. Comparison with limited available experimental data is made. The comparison is favorable, but detailed experimental data is needed to further improve the curvature model.

Numerical prediction of flow induced fibers orientation in injection molded polymer composites

NASA Astrophysics Data System (ADS)

Oumer, A. N.; Hamidi, N. M.; Mat Sahat, I.

2015-12-01

Since the filling stage of injection molding process has important effect on the determination of the orientation state of the fibers, accurate analysis of the flow field for the mold filling stage becomes a necessity. The aim of the paper is to characterize the flow induced orientation state of short fibers in injection molding cavities. A dog-bone shaped model is considered for the simulation and experiment. The numerical model for determination of the fibers orientation during mold-filling stage of injection molding process was solved using Computational Fluid Dynamics (CFD) software called MoldFlow. Both the simulation and experimental results showed that two different regions (or three layers of orientation structures) across the thickness of the specimen could be found: a shell region which is near to the mold cavity wall, and a core region at the middle of the cross section. The simulation results support the experimental observations that for thin plates the probability of fiber alignment to the flow direction near the mold cavity walls is high but low at the core region. It is apparent that the results of this study could assist in decisions regarding short fiber reinforced polymer composites.

Aeroacoustic prediction of turbulent free shear flows

NASA Astrophysics Data System (ADS)

Bodony, Daniel Joseph

2005-12-01

For many people living in the immediate vicinity of an active airport the noise of jet aircraft flying overhead can be a nuisance, if not worse. Airports, which are held accountable for the noise they produce, and upcoming international noise limits are pressuring the major airframe and jet engine manufacturers to bring quieter aircraft into service. However, component designers need a predictive tool that can estimate the sound generated by a new configuration. Current noise prediction techniques are almost entirely based on previously collected experimental data and are applicable only to evolutionary, not revolutionary, changes in the basic design. Physical models of final candidate designs must still be built and tested before a single design is selected. By focusing on the noise produced in the jet engine exhaust at take-off conditions, the prediction of sound generated by turbulent flows is addressed. The technique of large-eddy simulation is used to calculate directly the radiated sound produced by jets at different operating conditions. Predicted noise spectra agree with measurements for frequencies up to, and slightly beyond, the peak frequency. Higher frequencies are missed, however, due to the limited resolution of the simulations. Two methods of estimating the 'missing' noise are discussed. In the first a subgrid scale noise model, analogous to a subgrid scale closure model, is proposed. In the second method the governing equations are expressed in a wavelet basis from which simplified time-dependent equations for the subgrid scale fluctuations can be derived. These equations are inexpensively integrated to yield estimates of the subgrid scale fluctuations with proper space-time dynamics.

PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models.

PubMed

Ford, Matthew D; Nikolov, Hristo N; Milner, Jaques S; Lownie, Stephen P; Demont, Edwin M; Kalata, Wojciech; Loth, Francis; Holdsworth, David W; Steinman, David A

2008-04-01

Computational fluid dynamics (CFD) modeling of nominally patient-specific cerebral aneurysms is increasingly being used as a research tool to further understand the development, prognosis, and treatment of brain aneurysms. We have previously developed virtual angiography to indirectly validate CFD-predicted gross flow dynamics against the routinely acquired digital subtraction angiograms. Toward a more direct validation, here we compare detailed, CFD-predicted velocity fields against those measured using particle imaging velocimetry (PIV). Two anatomically realistic flow-through phantoms, one a giant internal carotid artery (ICA) aneurysm and the other a basilar artery (BA) tip aneurysm, were constructed of a clear silicone elastomer. The phantoms were placed within a computer-controlled flow loop, programed with representative flow rate waveforms. PIV images were collected on several anterior-posterior (AP) and lateral (LAT) planes. CFD simulations were then carried out using a well-validated, in-house solver, based on micro-CT reconstructions of the geometries of the flow-through phantoms and inlet/outlet boundary conditions derived from flow rates measured during the PIV experiments. PIV and CFD results from the central AP plane of the ICA aneurysm showed a large stable vortex throughout the cardiac cycle. Complex vortex dynamics, captured by PIV and CFD, persisted throughout the cardiac cycle on the central LAT plane. Velocity vector fields showed good overall agreement. For the BA, aneurysm agreement was more compelling, with both PIV and CFD similarly resolving the dynamics of counter-rotating vortices on both AP and LAT planes. Despite the imposition of periodic flow boundary conditions for the CFD simulations, cycle-to-cycle fluctuations were evident in the BA aneurysm simulations, which agreed well, in terms of both amplitudes and spatial distributions, with cycle-to-cycle fluctuations measured by PIV in the same geometry. The overall good agreement

A study of pressure-based methodology for resonant flows in non-linear combustion instabilities

NASA Technical Reports Server (NTRS)

Yang, H. Q.; Pindera, M. Z.; Przekwas, A. J.; Tucker, K.

1992-01-01

This paper presents a systematic assessment of a large variety of spatial and temporal differencing schemes on nonstaggered grids by the pressure-based methods for the problems of fast transient flows. The observation from the present study is that for steady state flow problems, pressure-based methods can be very competitive with the density-based methods. For transient flow problems, pressure-based methods utilizing the same differencing scheme are less accurate, even though the wave speeds are correctly predicted.

Prediction of retention times in comprehensive two-dimensional gas chromatography using thermodynamic models.

PubMed

McGinitie, Teague M; Harynuk, James J

2012-09-14

A method was developed to accurately predict both the primary and secondary retention times for a series of alkanes, ketones and alcohols in a flow-modulated GC×GC system. This was accomplished through the use of a three-parameter thermodynamic model where ΔH, ΔS, and ΔC(p) for an analyte's interaction with the stationary phases in both dimensions are known. Coupling this thermodynamic model with a time summation calculation it was possible to accurately predict both (1)t(r) and (2)t(r) for all analytes. The model was able to predict retention times regardless of the temperature ramp used, with an average error of only 0.64% for (1)t(r) and an average error of only 2.22% for (2)t(r). The model shows promise for the accurate prediction of retention times in GC×GC for a wide range of compounds and is able to utilize data collected from 1D experiments. Copyright © 2012 Elsevier B.V. All rights reserved.

The Predictability of Extratropical Transition and of its Impact on the Downstream Flow

DTIC Science & Technology

2008-03-28

is predicted to reach a continent as an extratropical storm . Arguably the larger impact on predictability, however, occurs due to the above mentioned...Office of Naval Research Project The Predictability of Extratropical Transition and of its Impact on the Downstream Flow Award Number: N00014-06-1...12 0 76128 Karlsruhe 0 March 28, 2008 1 * 4 -d 60-( CONTENTS 3 Contents 1 Objectives 5 2 Scientific Importance 6 3 Extratropical Transition in

Viscous/potential flow about multi-element two-dimensional and infinite-span swept wings: Theory and experiment

NASA Technical Reports Server (NTRS)

Olson, L. E.; Dvorak, F. A.

1975-01-01

The viscous subsonic flow past two-dimensional and infinite-span swept multi-component airfoils is studied theoretically and experimentally. The computerized analysis is based on iteratively coupled boundary layer and potential flow analysis. The method, which is restricted to flows with only slight separation, gives surface pressure distribution, chordwise and spanwise boundary layer characteristics, lift, drag, and pitching moment for airfoil configurations with up to four elements. Merging confluent boundary layers are treated. Theoretical predictions are compared with an exact theoretical potential flow solution and with experimental measures made in the Ames 40- by 80-Foot Wind Tunnel for both two-dimensional and infinite-span swept wing configurations. Section lift characteristics are accurately predicted for zero and moderate sweep angles where flow separation effects are negligible.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Magnetohydrodynamic pressure drop and flow balancing of liquid metal flow in a prototypic fusion blanket manifold

NASA Astrophysics Data System (ADS)

Rhodes, Tyler J.; Smolentsev, Sergey; Abdou, Mohamed

2018-05-01

Understanding magnetohydrodynamic (MHD) phenomena associated with the flow of electrically conducting fluids in complex geometry ducts subject to a strong magnetic field is required to effectively design liquid metal (LM) blankets for fusion reactors. Particularly, accurately predicting the 3D MHD pressure drop and flow distribution is important. To investigate these topics, we simulate a LM MHD flow through an electrically non-conducting prototypic manifold for a wide range of flow and geometry parameters using a 3D MHD solver, HyPerComp incompressible MHD solver for arbitrary geometry. The reference manifold geometry consists of a rectangular feeding duct which suddenly expands such that the duct thickness in the magnetic field direction abruptly increases by a factor rexp. Downstream of the sudden expansion, the LM is distributed into several parallel channels. As a first step in qualifying the flow, a magnitude of the curl of the induced Lorentz force was used to distinguish between inviscid, irrotational core flows and boundary and internal shear layers where inertia and/or viscous forces are important. Scaling laws have been obtained which characterize the 3D MHD pressure drop and flow balancing as a function of the flow parameters and the manifold geometry. Associated Hartmann and Reynolds numbers in the computations were ˜103 and ˜101-103, respectively, while rexp was varied from 4 to 12. An accurate model for the pressure drop was developed for the first time for inertial-electromagnetic and viscous-electromagnetic regimes based on 96 computed cases. Analysis shows that flow balance can be improved by lengthening the distance between the manifold inlet and the entrances of the parallel channels by utilizing the effect of flow transitioning to a quasi-two-dimensional state in the expansion region of the manifold.

Numerical simulation of flow in a high head Francis turbine with prediction of efficiency, rotor stator interaction and vortex structures in the draft tube

NASA Astrophysics Data System (ADS)

Jošt, D.; Škerlavaj, A.; Morgut, M.; Mežnar, P.; Nobile, E.

2015-01-01

The paper presents numerical simulations of flow in a model of a high head Francis turbine and comparison of results to the measurements. Numerical simulations were done by two CFD (Computational Fluid Dynamics) codes, Ansys CFX and OpenFOAM. Steady-state simulations were performed by k-epsilon and SST model, while for transient simulations the SAS SST ZLES model was used. With proper grid refinement in distributor and runner and with taking into account losses in labyrinth seals very accurate prediction of torque on the shaft, head and efficiency was obtained. Calculated axial and circumferential velocity components on two planes in the draft tube matched well with experimental results.

Predictable turn-around time for post tape-out flow