Turbulence Models for Accurate Aerothermal Prediction in Hypersonic Flows
NASA Astrophysics Data System (ADS)
Zhang, Xiang-Hong; Wu, Yi-Zao; Wang, Jiang-Feng
Accurate description of the aerodynamic and aerothermal environment is crucial to the integrated design and optimization for high performance hypersonic vehicles. In the simulation of aerothermal environment, the effect of viscosity is crucial. The turbulence modeling remains a major source of uncertainty in the computational prediction of aerodynamic forces and heating. In this paper, three turbulent models were studied: the one-equation eddy viscosity transport model of Spalart-Allmaras, the Wilcox k-ω model and the Menter SST model. For the k-ω model and SST model, the compressibility correction, press dilatation and low Reynolds number correction were considered. The influence of these corrections for flow properties were discussed by comparing with the results without corrections. In this paper the emphasis is on the assessment and evaluation of the turbulence models in prediction of heat transfer as applied to a range of hypersonic flows with comparison to experimental data. This will enable establishing factor of safety for the design of thermal protection systems of hypersonic vehicle.
Accurately predicting copper interconnect topographies in foundry design for manufacturability flows
NASA Astrophysics Data System (ADS)
Lu, Daniel; Fan, Zhong; Tak, Ki Duk; Chang, Li-Fu; Zou, Elain; Jiang, Jenny; Yang, Josh; Zhuang, Linda; Chen, Kuang Han; Hurat, Philippe; Ding, Hua
2011-04-01
This paper presents a model-based Chemical Mechanical Polishing (CMP) Design for Manufacturability (DFM) () methodology that includes an accurate prediction of post-CMP copper interconnect topographies at the advanced process technology nodes. Using procedures of extensive model calibration and validation, the CMP process model accurately predicts post-CMP dimensions, such as erosion, dishing, and copper thickness with excellent correlation to silicon measurements. This methodology provides an efficient DFM flow to detect and fix physical manufacturing hotspots related to copper pooling and Depth of Focus (DOF) failures at both block- and full chip level designs. Moreover, the predicted thickness output is used in the CMP-aware RC extraction and Timing analysis flows for better understanding of performance yield and timing impact. In addition, the CMP model can be applied to the verification of model-based dummy fill flows.
A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows
NASA Astrophysics Data System (ADS)
Bijleveld, H. A.; Veldman, A. E. P.
2014-12-01
A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.
A high order accurate finite element algorithm for high Reynolds number flow prediction
NASA Technical Reports Server (NTRS)
Baker, A. J.
1978-01-01
A Galerkin-weighted residuals formulation is employed to establish an implicit finite element solution algorithm for generally nonlinear initial-boundary value problems. Solution accuracy, and convergence rate with discretization refinement, are quantized in several error norms, by a systematic study of numerical solutions to several nonlinear parabolic and a hyperbolic partial differential equation characteristic of the equations governing fluid flows. Solutions are generated using selective linear, quadratic and cubic basis functions. Richardson extrapolation is employed to generate a higher-order accurate solution to facilitate isolation of truncation error in all norms. Extension of the mathematical theory underlying accuracy and convergence concepts for linear elliptic equations is predicted for equations characteristic of laminar and turbulent fluid flows at nonmodest Reynolds number. The nondiagonal initial-value matrix structure introduced by the finite element theory is determined intrinsic to improved solution accuracy and convergence. A factored Jacobian iteration algorithm is derived and evaluated to yield a consequential reduction in both computer storage and execution CPU requirements while retaining solution accuracy.
Towards Accurate Prediction of Turbulent, Three-Dimensional, Recirculating Flows with the NCC
NASA Technical Reports Server (NTRS)
Iannetti, A.; Tacina, R.; Jeng, S.-M.; Cai, J.
2001-01-01
The National Combustion Code (NCC) was used to calculate the steady state, nonreacting flow field of a prototype Lean Direct Injection (LDI) swirler. This configuration used nine groups of eight holes drilled at a thirty-five degree angle to induce swirl. These nine groups created swirl in the same direction, or a corotating pattern. The static pressure drop across the holes was fixed at approximately four percent. Computations were performed on one quarter of the geometry, because the geometry is considered rotationally periodic every ninety degrees. The final computational grid used was approximately 2.26 million tetrahedral cells, and a cubic nonlinear k - epsilon model was used to model turbulence. The NCC results were then compared to time averaged Laser Doppler Velocimetry (LDV) data. The LDV measurements were performed on the full geometry, but four ninths of the geometry was measured. One-, two-, and three-dimensional representations of both flow fields are presented. The NCC computations compare both qualitatively and quantitatively well to the LDV data, but differences exist downstream. The comparison is encouraging, and shows that NCC can be used for future injector design studies. To improve the flow prediction accuracy of turbulent, three-dimensional, recirculating flow fields with the NCC, recommendations are given.
A time accurate prediction of the viscous flow in a turbine stage including a rotor in motion
NASA Astrophysics Data System (ADS)
Shavalikul, Akamol
accurate flow characteristics in the NGV domain and the rotor domain with less computational time and computer memory requirements. In contrast, the time accurate flow simulation can predict all unsteady flow characteristics occurring in the turbine stage, but with high computational resource requirements. (Abstract shortened by UMI.)
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.
New model accurately predicts reformate composition
Ancheyta-Juarez, J.; Aguilar-Rodriguez, E. )
1994-01-31
Although naphtha reforming is a well-known process, the evolution of catalyst formulation, as well as new trends in gasoline specifications, have led to rapid evolution of the process, including: reactor design, regeneration mode, and operating conditions. Mathematical modeling of the reforming process is an increasingly important tool. It is fundamental to the proper design of new reactors and revamp of existing ones. Modeling can be used to optimize operating conditions, analyze the effects of process variables, and enhance unit performance. Instituto Mexicano del Petroleo has developed a model of the catalytic reforming process that accurately predicts reformate composition at the higher-severity conditions at which new reformers are being designed. The new AA model is more accurate than previous proposals because it takes into account the effects of temperature and pressure on the rate constants of each chemical reaction.
Statistically accurate simulations for atmospheric flows
NASA Astrophysics Data System (ADS)
Dubinkina, S.
2009-04-01
A Hamiltonian particle-mesh method for quasi-geostrophic potential vorticity flow is proposed. The microscopic vorticity field at any time is an area- and energy-conserving rearrangement of the initial field. We construct a statistical mechanics theory to explain the long-time behavior of the numerical solution. The statistical theory correctly predicts the spatial distribution of particles as a function of their point vorticity. A nonlinear relation between the coarse grained mean stream function and mean vorticity fields is predicted, consistent with the preservation of higher moments of potential vorticity reported in [R. V. Abramov, A. J. Majda 2003, PNAS 100 3841--3846].
Selecting MODFLOW cell sizes for accurate flow fields.
Haitjema, H; Kelson, V; de Lange, W
2001-01-01
Contaminant transport models often use a velocity field derived from a MODFLOW flow field. Consequently, the accuracy of MODFLOW in representing a ground water flow field determines in part the accuracy of the transport predictions, particularly when advective transport is dominant. We compared MODFLOW ground water flow rates and MODPATH particle traces (advective transport) for a variety of conceptual models and different grid spacings to exact or approximate analytic solutions. All of our numerical experiments concerned flow in a single confined or semiconfined aquifer. While MODFLOW appeared robust in terms of both local and global water balance, we found that ground water flow rates, particle traces, and associated ground water travel times are accurate only when sufficiently small cells are used. For instance, a minimum of four or five cells are required to accurately model total ground water inflow in tributaries or other narrow surface water bodies that end inside the model domain. Also, about 50 cells are needed to represent zones of differing transmissivities or an incorrect flow field and (locally) inaccurate ground water travel times may result. Finally, to adequately represent leakage through aquitards or through the bottom of surface water bodies it was found that the maximum allowable cell dimensions should not exceed a characteristic leakage length lambda, which is defined as the square root of the aquifer transmissivity times the resistance of the aquitard or stream bottom. In some cases a cell size of one-tenth of lambda is necessary to obtain accurate results.
More-Accurate Model of Flows in Rocket Injectors
NASA Technical Reports Server (NTRS)
Hosangadi, Ashvin; Chenoweth, James; Brinckman, Kevin; Dash, Sanford
2011-01-01
An improved computational model for simulating flows in liquid-propellant injectors in rocket engines has been developed. Models like this one are needed for predicting fluxes of heat in, and performances of, the engines. An important part of predicting performance is predicting fluctuations of temperature, fluctuations of concentrations of chemical species, and effects of turbulence on diffusion of heat and chemical species. Customarily, diffusion effects are represented by parameters known in the art as the Prandtl and Schmidt numbers. Prior formulations include ad hoc assumptions of constant values of these parameters, but these assumptions and, hence, the formulations, are inaccurate for complex flows. In the improved model, these parameters are neither constant nor specified in advance: instead, they are variables obtained as part of the solution. Consequently, this model represents the effects of turbulence on diffusion of heat and chemical species more accurately than prior formulations do, and may enable more-accurate prediction of mixing and flows of heat in rocket-engine combustion chambers. The model has been implemented within CRUNCH CFD, a proprietary computational fluid dynamics (CFD) computer program, and has been tested within that program. The model could also be implemented within other CFD programs.
NASA Astrophysics Data System (ADS)
Heward, J.; Ohara, N.
2014-12-01
In many alpine regions, especially in the western United States, the snow pack is the cause of the peak discharge and most of the annual flow. A distributed snow melt model with a point-scale snow melt theory is used to estimate the timing and intensity of both snow accumulation and ablation. The type and distribution of vegetation across a watershed influences timing and intensity of snow melt processes. Efforts are being made to understand how a changing landscape will ultimately affect stream flow in a mountainous environment. This study includes an analysis of the effects of the recent bark beetle infestation, using leaf area index (LAI) data acquired from MODIS data sets. These changes were incorporated into the snow model to more accurately predict snow melt timing and intensity. It was observed through the primary model implementation that snowmelt was intensified by the LAI reduction. The radiation change and turbulent flux effects were separately quantified by the vegetation parameterization in the snow model. This distributed snow model will be used to more accurately predict stream flow in the Upper Little Laramie River, Wyoming watershed.
Time accurate simulations of compressible shear flows
NASA Technical Reports Server (NTRS)
Givi, Peyman; Steinberger, Craig J.; Vidoni, Thomas J.; Madnia, Cyrus K.
1993-01-01
The objectives of this research are to employ direct numerical simulation (DNS) to study the phenomenon of mixing (or lack thereof) in compressible free shear flows and to suggest new means of enhancing mixing in such flows. The shear flow configurations under investigation are those of parallel mixing layers and planar jets under both non-reacting and reacting nonpremixed conditions. During the three-years of this research program, several important issues regarding mixing and chemical reactions in compressible shear flows were investigated.
A gene expression biomarker accurately predicts estrogen ...
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
You Can Accurately Predict Land Acquisition Costs.
ERIC Educational Resources Information Center
Garrigan, Richard
1967-01-01
Land acquisition costs were tested for predictability based upon the 1962 assessed valuations of privately held land acquired for campus expansion by the University of Wisconsin from 1963-1965. By correlating the land acquisition costs of 108 properties acquired during the 3 year period with--(1) the assessed value of the land, (2) the assessed…
Towards more accurate vegetation mortality predictions
Sevanto, Sanna Annika; Xu, Chonggang
2016-09-26
Predicting the fate of vegetation under changing climate is one of the major challenges of the climate modeling community. Here, terrestrial vegetation dominates the carbon and water cycles over land areas, and dramatic changes in vegetation cover resulting from stressful environmental conditions such as drought feed directly back to local and regional climate, potentially leading to a vicious cycle where vegetation recovery after a disturbance is delayed or impossible.
A predictable and accurate technique with elastomeric impression materials.
Barghi, N; Ontiveros, J C
1999-08-01
A method for obtaining more predictable and accurate final impressions with polyvinylsiloxane impression materials in conjunction with stock trays is proposed and tested. Heavy impression material is used in advance for construction of a modified custom tray, while extra-light material is used for obtaining a more accurate final impression.
Accurate torque-speed performance prediction for brushless dc motors
NASA Astrophysics Data System (ADS)
Gipper, Patrick D.
Desirable characteristics of the brushless dc motor (BLDCM) have resulted in their application for electrohydrostatic (EH) and electromechanical (EM) actuation systems. But to effectively apply the BLDCM requires accurate prediction of performance. The minimum necessary performance characteristics are motor torque versus speed, peak and average supply current and efficiency. BLDCM nonlinear simulation software specifically adapted for torque-speed prediction is presented. The capability of the software to quickly and accurately predict performance has been verified on fractional to integral HP motor sizes, and is presented. Additionally, the capability of torque-speed prediction with commutation angle advance is demonstrated.
Device accurately measures and records low gas-flow rates
NASA Technical Reports Server (NTRS)
Branum, L. W.
1966-01-01
Free-floating piston in a vertical column accurately measures and records low gas-flow rates. The system may be calibrated, using an adjustable flow-rate gas supply, a low pressure gage, and a sequence recorder. From the calibration rates, a nomograph may be made for easy reduction. Temperature correction may be added for further accuracy.
Predicting Flows of Rarefied Gases
NASA Technical Reports Server (NTRS)
LeBeau, Gerald J.; Wilmoth, Richard G.
2005-01-01
DSMC Analysis Code (DAC) is a flexible, highly automated, easy-to-use computer program for predicting flows of rarefied gases -- especially flows of upper-atmospheric, propulsion, and vented gases impinging on spacecraft surfaces. DAC implements the direct simulation Monte Carlo (DSMC) method, which is widely recognized as standard for simulating flows at densities so low that the continuum-based equations of computational fluid dynamics are invalid. DAC enables users to model complex surface shapes and boundary conditions quickly and easily. The discretization of a flow field into computational grids is automated, thereby relieving the user of a traditionally time-consuming task while ensuring (1) appropriate refinement of grids throughout the computational domain, (2) determination of optimal settings for temporal discretization and other simulation parameters, and (3) satisfaction of the fundamental constraints of the method. In so doing, DAC ensures an accurate and efficient simulation. In addition, DAC can utilize parallel processing to reduce computation time. The domain decomposition needed for parallel processing is completely automated, and the software employs a dynamic load-balancing mechanism to ensure optimal parallel efficiency throughout the simulation.
On the Accurate Prediction of CME Arrival At the Earth
NASA Astrophysics Data System (ADS)
Zhang, Jie; Hess, Phillip
2016-07-01
We will discuss relevant issues regarding the accurate prediction of CME arrival at the Earth, from both observational and theoretical points of view. In particular, we clarify the importance of separating the study of CME ejecta from the ejecta-driven shock in interplanetary CMEs (ICMEs). For a number of CME-ICME events well observed by SOHO/LASCO, STEREO-A and STEREO-B, we carry out the 3-D measurements by superimposing geometries onto both the ejecta and sheath separately. These measurements are then used to constrain a Drag-Based Model, which is improved through a modification of including height dependence of the drag coefficient into the model. Combining all these factors allows us to create predictions for both fronts at 1 AU and compare with actual in-situ observations. We show an ability to predict the sheath arrival with an average error of under 4 hours, with an RMS error of about 1.5 hours. For the CME ejecta, the error is less than two hours with an RMS error within an hour. Through using the best observations of CMEs, we show the power of our method in accurately predicting CME arrival times. The limitation and implications of our accurate prediction method will be discussed.
Accurate modelling of unsteady flows in collapsible tubes.
Marchandise, Emilie; Flaud, Patrice
2010-01-01
The context of this paper is the development of a general and efficient numerical haemodynamic tool to help clinicians and researchers in understanding of physiological flow phenomena. We propose an accurate one-dimensional Runge-Kutta discontinuous Galerkin (RK-DG) method coupled with lumped parameter models for the boundary conditions. The suggested model has already been successfully applied to haemodynamics in arteries and is now extended for the flow in collapsible tubes such as veins. The main difference with cardiovascular simulations is that the flow may become supercritical and elastic jumps may appear with the numerical consequence that scheme may not remain monotone if no limiting procedure is introduced. We show that our second-order RK-DG method equipped with an approximate Roe's Riemann solver and a slope-limiting procedure allows us to capture elastic jumps accurately. Moreover, this paper demonstrates that the complex physics associated with such flows is more accurately modelled than with traditional methods such as finite difference methods or finite volumes. We present various benchmark problems that show the flexibility and applicability of the numerical method. Our solutions are compared with analytical solutions when they are available and with solutions obtained using other numerical methods. Finally, to illustrate the clinical interest, we study the emptying process in a calf vein squeezed by contracting skeletal muscle in a normal and pathological subject. We compare our results with experimental simulations and discuss the sensitivity to parameters of our model.
Passive samplers accurately predict PAH levels in resident crayfish.
Paulik, L Blair; Smith, Brian W; Bergmann, Alan J; Sower, Greg J; Forsberg, Norman D; Teeguarden, Justin G; Anderson, Kim A
2016-02-15
Contamination of resident aquatic organisms is a major concern for environmental risk assessors. However, collecting organisms to estimate risk is often prohibitively time and resource-intensive. Passive sampling accurately estimates resident organism contamination, and it saves time and resources. This study used low density polyethylene (LDPE) passive water samplers to predict polycyclic aromatic hydrocarbon (PAH) levels in signal crayfish, Pacifastacus leniusculus. Resident crayfish were collected at 5 sites within and outside of the Portland Harbor Superfund Megasite (PHSM) in the Willamette River in Portland, Oregon. LDPE deployment was spatially and temporally paired with crayfish collection. Crayfish visceral and tail tissue, as well as water-deployed LDPE, were extracted and analyzed for 62 PAHs using GC-MS/MS. Freely-dissolved concentrations (Cfree) of PAHs in water were calculated from concentrations in LDPE. Carcinogenic risks were estimated for all crayfish tissues, using benzo[a]pyrene equivalent concentrations (BaPeq). ∑PAH were 5-20 times higher in viscera than in tails, and ∑BaPeq were 6-70 times higher in viscera than in tails. Eating only tail tissue of crayfish would therefore significantly reduce carcinogenic risk compared to also eating viscera. Additionally, PAH levels in crayfish were compared to levels in crayfish collected 10 years earlier. PAH levels in crayfish were higher upriver of the PHSM and unchanged within the PHSM after the 10-year period. Finally, a linear regression model predicted levels of 34 PAHs in crayfish viscera with an associated R-squared value of 0.52 (and a correlation coefficient of 0.72), using only the Cfree PAHs in water. On average, the model predicted PAH concentrations in crayfish tissue within a factor of 2.4 ± 1.8 of measured concentrations. This affirms that passive water sampling accurately estimates PAH contamination in crayfish. Furthermore, the strong predictive ability of this simple model suggests
Inverter Modeling For Accurate Energy Predictions Of Tracking HCPV Installations
NASA Astrophysics Data System (ADS)
Bowman, J.; Jensen, S.; McDonald, Mark
2010-10-01
High efficiency high concentration photovoltaic (HCPV) solar plants of megawatt scale are now operational, and opportunities for expanded adoption are plentiful. However, effective bidding for sites requires reliable prediction of energy production. HCPV module nameplate power is rated for specific test conditions; however, instantaneous HCPV power varies due to site specific irradiance and operating temperature, and is degraded by soiling, protective stowing, shading, and electrical connectivity. These factors interact with the selection of equipment typically supplied by third parties, e.g., wire gauge and inverters. We describe a time sequence model accurately accounting for these effects that predicts annual energy production, with specific reference to the impact of the inverter on energy output and interactions between system-level design decisions and the inverter. We will also show two examples, based on an actual field design, of inverter efficiency calculations and the interaction between string arrangements and inverter selection.
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).
Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates
Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.
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 charged 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.
Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates
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
Basophile: Accurate Fragment Charge State Prediction Improves Peptide Identification Rates
Wang, Dong; Dasari, Surendra; Chambers, Matthew C.; Holman, Jerry D.; Chen, Kan; Liebler, Daniel C.; Orton, Daniel J.; Purvine, Samuel O.; Monroe, Matthew E.; Chung, Chang Y.; Rose, Kristie L.; Tabb, David L.
2013-01-01
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 charged 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. PMID:23499924
Accurate measurement of streamwise vortices in low speed aerodynamic flows
NASA Astrophysics Data System (ADS)
Waldman, Rye M.; Kudo, Jun; Breuer, Kenneth S.
2010-11-01
Low Reynolds number experiments with flapping animals (such as bats and small birds) are of current interest in understanding biological flight mechanics, and due to their application to Micro Air Vehicles (MAVs) which operate in a similar parameter space. Previous PIV wake measurements have described the structures left by bats and birds, and provided insight to the time history of their aerodynamic force generation; however, these studies have faced difficulty drawing quantitative conclusions due to significant experimental challenges associated with the highly three-dimensional and unsteady nature of the flows, and the low wake velocities associated with lifting bodies that only weigh a few grams. This requires the high-speed resolution of small flow features in a large field of view using limited laser energy and finite camera resolution. Cross-stream measurements are further complicated by the high out-of-plane flow which requires thick laser sheets and short interframe times. To quantify and address these challenges we present data from a model study on the wake behind a fixed wing at conditions comparable to those found in biological flight. We present a detailed analysis of the PIV wake measurements, discuss the criteria necessary for accurate measurements, and present a new dual-plane PIV configuration to resolve these issues.
Prediction of Geophysical Flow Mobility
NASA Astrophysics Data System (ADS)
Cagnoli, B.; Piersanti, A.
2014-12-01
The prediction of the mobility of geophysical flows to assess their hazards is one of the main research goals in the earth sciences. Our laboratory experiments and numerical simulations are carried out to understand the effects of grain size and flow volume on the mobility of the centre of mass of dry granular flows of angular rock fragments that have pyroclastic flows and rock avalanches as counterpart in nature. We focus on the centre of mass because it provides information about the intrinsic ability of a flow to dissipate more or less energy as a function of its own features. We show that the grain size and flow volume effects can be expressed by a linear relationship between scaling parameters where the finer the grain size or the smaller the flow volume, the more mobile the centre of mass of the granular flow. The grain size effect is the result of the decrease of particle agitation per unit of flow mass, and thus, the decrease of energy dissipation per unit of travel distance, as grain size decreases. In this sense, flows with different grain sizes are like cars with engines with different fuel efficiencies. The volume effect is the result of the fact that the deposit accretes backward during its formation on a slope change (either gradual or abrupt). We adopt for the numerical simulations a 3D discrete element modeling which confirms the grain size and flow volume effects shown by the laboratory experiments. This confirmation is obtained without prior fine tuning of the parameter values to get the desired output. The numerical simulations reveal also that the larger the initial compaction of the granular mass before release, the more mobile the flow. This behaviour must be taken into account to prevent misinterpretation of laboratory and field data. Discrete element modeling predicts the correct effects of grain size and flow volume because it takes into consideration particle interactions that are responsible for the energy dissipated by the flows.
Mouse models of human AML accurately predict chemotherapy response
Zuber, Johannes; Radtke, Ina; Pardee, Timothy S.; Zhao, Zhen; Rappaport, Amy R.; Luo, Weijun; McCurrach, Mila E.; Yang, Miao-Miao; Dolan, M. Eileen; Kogan, Scott C.; Downing, James R.; Lowe, Scott W.
2009-01-01
The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients. PMID:19339691
Mouse models of human AML accurately predict chemotherapy response.
Zuber, Johannes; Radtke, Ina; Pardee, Timothy S; Zhao, Zhen; Rappaport, Amy R; Luo, Weijun; McCurrach, Mila E; Yang, Miao-Miao; Dolan, M Eileen; Kogan, Scott C; Downing, James R; Lowe, Scott W
2009-04-01
The genetic heterogeneity of cancer influences the trajectory of tumor progression and may underlie clinical variation in therapy response. To model such heterogeneity, we produced genetically and pathologically accurate mouse models of common forms of human acute myeloid leukemia (AML) and developed methods to mimic standard induction chemotherapy and efficiently monitor therapy response. We see that murine AMLs harboring two common human AML genotypes show remarkably diverse responses to conventional therapy that mirror clinical experience. Specifically, murine leukemias expressing the AML1/ETO fusion oncoprotein, associated with a favorable prognosis in patients, show a dramatic response to induction chemotherapy owing to robust activation of the p53 tumor suppressor network. Conversely, murine leukemias expressing MLL fusion proteins, associated with a dismal prognosis in patients, are drug-resistant due to an attenuated p53 response. Our studies highlight the importance of genetic information in guiding the treatment of human AML, functionally establish the p53 network as a central determinant of chemotherapy response in AML, and demonstrate that genetically engineered mouse models of human cancer can accurately predict therapy response in patients.
Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics
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
Fast and accurate predictions of covalent bonds in chemical space
NASA Astrophysics Data System (ADS)
Chang, K. Y. Samuel; Fias, Stijn; Ramakrishnan, Raghunathan; von Lilienfeld, O. Anatole
2016-05-01
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 H 2+ . 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
Fast and accurate predictions of covalent bonds in chemical space.
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
IRIS: Towards an Accurate and Fast Stage Weight Prediction Method
NASA Astrophysics Data System (ADS)
Taponier, V.; Balu, A.
2002-01-01
The knowledge of the structural mass fraction (or the mass ratio) of a given stage, which affects the performance of a rocket, is essential for the analysis of new or upgraded launchers or stages, whose need is increased by the quick evolution of the space programs and by the necessity of their adaptation to the market needs. The availability of this highly scattered variable, ranging between 0.05 and 0.15, is of primary importance at the early steps of the preliminary design studies. At the start of the staging and performance studies, the lack of frozen weight data (to be obtained later on from propulsion, trajectory and sizing studies) leads to rely on rough estimates, generally derived from printed sources and adapted. When needed, a consolidation can be acquired trough a specific analysis activity involving several techniques and implying additional effort and time. The present empirical approach allows thus to get approximated values (i.e. not necessarily accurate or consistent), inducing some result inaccuracy as well as, consequently, difficulties of performance ranking for a multiple option analysis, and an increase of the processing duration. This forms a classical harsh fact of the preliminary design system studies, insufficiently discussed to date. It appears therefore highly desirable to have, for all the evaluation activities, a reliable, fast and easy-to-use weight or mass fraction prediction method. Additionally, the latter should allow for a pre selection of the alternative preliminary configurations, making possible a global system approach. For that purpose, an attempt at modeling has been undertaken, whose objective was the determination of a parametric formulation of the mass fraction, to be expressed from a limited number of parameters available at the early steps of the project. It is based on the innovative use of a statistical method applicable to a variable as a function of several independent parameters. A specific polynomial generator
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.
Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin
2015-01-01
Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale. PMID:26198229
Deng, Xin; Gumm, Jordan; Karki, Suman; Eickholt, Jesse; Cheng, Jianlin
2015-07-07
Protein disordered regions are segments of a protein chain that do not adopt a stable structure. Thus far, a variety of protein disorder prediction methods have been developed and have been widely used, not only in traditional bioinformatics domains, including protein structure prediction, protein structure determination and function annotation, but also in many other biomedical fields. The relationship between intrinsically-disordered proteins and some human diseases has played a significant role in disorder prediction in disease identification and epidemiological investigations. Disordered proteins can also serve as potential targets for drug discovery with an emphasis on the disordered-to-ordered transition in the disordered binding regions, and this has led to substantial research in drug discovery or design based on protein disordered region prediction. Furthermore, protein disorder prediction has also been applied to healthcare by predicting the disease risk of mutations in patients and studying the mechanistic basis of diseases. As the applications of disorder prediction increase, so too does the need to make quick and accurate predictions. To fill this need, we also present a new approach to predict protein residue disorder using wide sequence windows that is applicable on the genomic scale.
Prediction of Preoperative Anxiety in Children: Who is Most Accurate?
MacLaren, Jill E.; Thompson, Caitlin; Weinberg, Megan; Fortier, Michelle A.; Morrison, Debra E.; Perret, Danielle; Kain, Zeev N.
2009-01-01
Background In this investigation, we sought to assess the ability of pediatric attending anesthesiologists, resident anesthesiologists and mothers to predict anxiety during induction of anesthesia in 2 to 16-year-old children (n=125). Methods Anesthesiologists and mothers provided predictions using a visual analog scale and children's anxiety was assessed using a valid behavior observation tool the Modified Yale Preoperative Anxiety Scale (mYPAS). All mothers were present during anesthetic induction and no child received sedative premedication. Correlational analyses were conducted. Results A total of 125 children aged 2 to 16 years, their mothers, and their attending pediatric anesthesiologists and resident anesthesiologists were studied. Correlational analyses revealed significant associations between attending predictions and child anxiety at induction (rs= 0.38, p<0.001). Resident anesthesiologist and mother predictions were not significantly related to children's anxiety during induction (rs = 0.01 and 0.001, respectively). In terms of accuracy of prediction, 47.2% of predictions made by attending anesthesiologists were within one standard deviation of the observed anxiety exhibited by the child, and 70.4% of predictions were within 2 standard deviations. Conclusions We conclude that attending anesthesiologists who practice in pediatric settings are better than mothers in predicting the anxiety of children during induction of anesthesia. While this finding has significant clinical implications, it is unclear if it can be extended to attending anesthesiologists whose practice is not mostly pediatric anesthesia. PMID:19448201
Fast and accurate pressure-drop prediction in straightened atherosclerotic coronary arteries.
Schrauwen, Jelle T C; Koeze, Dion J; Wentzel, Jolanda J; van de Vosse, Frans N; van der Steen, Anton F W; Gijsen, Frank J H
2015-01-01
Atherosclerotic disease progression in coronary arteries is influenced by wall shear stress. To compute patient-specific wall shear stress, computational fluid dynamics (CFD) is required. In this study we propose a method for computing the pressure-drop in regions proximal and distal to a plaque, which can serve as a boundary condition in CFD. As a first step towards exploring the proposed method we investigated ten straightened coronary arteries. First, the flow fields were calculated with CFD and velocity profiles were fitted on the results. Second, the Navier-Stokes equation was simplified and solved with the found velocity profiles to obtain a pressure-drop estimate (Δp (1)). Next, Δp (1) was compared to the pressure-drop from CFD (Δp CFD) as a validation step. Finally, the velocity profiles, and thus the pressure-drop were predicted based on geometry and flow, resulting in Δp geom. We found that Δp (1) adequately estimated Δp CFD with velocity profiles that have one free parameter β. This β was successfully related to geometry and flow, resulting in an excellent agreement between Δp CFD and Δp geom: 3.9 ± 4.9% difference at Re = 150. We showed that this method can quickly and accurately predict pressure-drop on the basis of geometry and flow in straightened coronary arteries that are mildly diseased.
Accurate calculation and instability of supersonic wake flows
NASA Technical Reports Server (NTRS)
Papageorgiou, Demetrius T.
1990-01-01
This study is concerned with the computation and linear stability of a class of laminar compressible wake flows. The emphasis is on correct basic flow profiles that satisfy the steady equations of motion, and to this end the unperturbed state is obtained through numerical integration of the compressible boundary-layer equations. The linear stability of the flow is examined via the Rayleigh equation that describes evolution of inviscid disturbances. Analytical results are given for short- and long-wavelength disturbances and some numerical results of the general eigenvalue problem are also reported.
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.
Accurate, reliable control of process gases by mass flow controllers
Hardy, J.; McKnight, T.
1997-02-01
The thermal mass flow controller, or MFC, has become an instrument of choice for the monitoring and controlling of process gas flow throughout the materials processing industry. These MFCs are used on CVD processes, etching tools, and furnaces and, within the semiconductor industry, are used on 70% of the processing tools. Reliability and accuracy are major concerns for the users of the MFCs. Calibration and characterization technologies for the development and implementation of mass flow devices are described. A test facility is available to industry and universities to test and develop gas floe sensors and controllers and evaluate their performance related to environmental effects, reliability, reproducibility, and accuracy. Additional work has been conducted in the area of accuracy. A gravimetric calibrator was invented that allows flow sensors to be calibrated in corrosive, reactive gases to an accuracy of 0.3% of reading, at least an order of magnitude better than previously possible. Although MFCs are typically specified with accuracies of 1% of full scale, MFCs may often be implemented with unwarranted confidence due to the conventional use of surrogate gas factors. Surrogate gas factors are corrections applied to process flow indications when an MFC has been calibrated on a laboratory-safe surrogate gas, but is actually used on a toxic, or corrosive process gas. Previous studies have indicated that the use of these factors may cause process flow errors of typically 10%, but possibly as great as 40% of full scale. This paper will present possible sources of error in MFC process gas flow monitoring and control, and will present an overview of corrective measures which may be implemented with MFC use to significantly reduce these sources of error.
Is Three-Dimensional Soft Tissue Prediction by Software Accurate?
Nam, Ki-Uk; Hong, Jongrak
2015-11-01
The authors assessed whether virtual surgery, performed with a soft tissue prediction program, could correctly simulate the actual surgical outcome, focusing on soft tissue movement. Preoperative and postoperative computed tomography (CT) data for 29 patients, who had undergone orthognathic surgery, were obtained and analyzed using the Simplant Pro software. The program made a predicted soft tissue image (A) based on presurgical CT data. After the operation, we obtained actual postoperative CT data and an actual soft tissue image (B) was generated. Finally, the 2 images (A and B) were superimposed and analyzed differences between the A and B. Results were grouped in 2 classes: absolute values and vector values. In the absolute values, the left mouth corner was the most significant error point (2.36 mm). The right mouth corner (2.28 mm), labrale inferius (2.08 mm), and the pogonion (2.03 mm) also had significant errors. In vector values, prediction of the right-left side had a left-sided tendency, the superior-inferior had a superior tendency, and the anterior-posterior showed an anterior tendency. As a result, with this program, the position of points tended to be located more left, anterior, and superior than the "real" situation. There is a need to improve the prediction accuracy for soft tissue images. Such software is particularly valuable in predicting craniofacial soft tissues landmarks, such as the pronasale. With this software, landmark positions were most inaccurate in terms of anterior-posterior predictions.
Fast and accurate automatic structure prediction with HHpred.
Hildebrand, Andrea; Remmert, Michael; Biegert, Andreas; Söding, Johannes
2009-01-01
Automated protein structure prediction is becoming a mainstream tool for biological research. This has been fueled by steady improvements of publicly available automated servers over the last decade, in particular their ability to build good homology models for an increasing number of targets by reliably detecting and aligning more and more remotely homologous templates. Here, we describe the three fully automated versions of the HHpred server that participated in the community-wide blind protein structure prediction competition CASP8. What makes HHpred unique is the combination of usability, short response times (typically under 15 min) and a model accuracy that is competitive with those of the best servers in CASP8.
Accurate perception of negative emotions predicts functional capacity in schizophrenia.
Abram, Samantha V; Karpouzian, Tatiana M; Reilly, James L; Derntl, Birgit; Habel, Ute; Smith, Matthew J
2014-04-30
Several studies suggest facial affect perception (FAP) deficits in schizophrenia are linked to poorer social functioning. However, whether reduced functioning is associated with inaccurate perception of specific emotional valence or a global FAP impairment remains unclear. The present study examined whether impairment in the perception of specific emotional valences (positive, negative) and neutrality were uniquely associated with social functioning, using a multimodal social functioning battery. A sample of 59 individuals with schizophrenia and 41 controls completed a computerized FAP task, and measures of functional capacity, social competence, and social attainment. Participants also underwent neuropsychological testing and symptom assessment. Regression analyses revealed that only accurately perceiving negative emotions explained significant variance (7.9%) in functional capacity after accounting for neurocognitive function and symptoms. Partial correlations indicated that accurately perceiving anger, in particular, was positively correlated with functional capacity. FAP for positive, negative, or neutral emotions were not related to social competence or social attainment. Our findings were consistent with prior literature suggesting negative emotions are related to functional capacity in schizophrenia. Furthermore, the observed relationship between perceiving anger and performance of everyday living skills is novel and warrants further exploration.
Towards Accurate Ab Initio Predictions of the Spectrum of Methane
NASA Technical Reports Server (NTRS)
Schwenke, David W.; Kwak, Dochan (Technical Monitor)
2001-01-01
We have carried out extensive ab initio calculations of the electronic structure of methane, and these results are used to compute vibrational energy levels. We include basis set extrapolations, core-valence correlation, relativistic effects, and Born- Oppenheimer breakdown terms in our calculations. Our ab initio predictions of the lowest lying levels are superb.
Accurate Theoretical Prediction of the Properties of Energetic Materials
2007-11-02
calculations (e.g. Cheetah ). 8. Sensitivity. The structure prediction and lattice potential work will serve as a platform to examine impact/shock...nitromethane molecules. (In an extension of the present work, we will freeze the internal coordinates of the molecules and assess the extent to which the
Fluid flow in nanopores: Accurate boundary conditions for carbon nanotubes
NASA Astrophysics Data System (ADS)
Sokhan, Vladimir P.; Nicholson, David; Quirke, Nicholas
2002-11-01
Steady-state Poiseuille flow of a simple fluid in carbon nanopores under a gravitylike force is simulated using a realistic empirical many-body potential model for carbon. Building on our previous study of slit carbon nanopores we show that fluid flow in a nanotube is also characterized by a large slip length. By analyzing temporal profiles of the velocity components of particles colliding with the wall we obtain values of the Maxwell coefficient defining the fraction of molecules thermalized by the wall and, for the first time, propose slip boundary conditions for smooth continuum surfaces such that they are equivalent in adsorption, diffusion, and fluid flow properties to fully dynamic atomistic models.
Learning regulatory programs that accurately predict differential expression with MEDUSA.
Kundaje, Anshul; Lianoglou, Steve; Li, Xuejing; Quigley, David; Arias, Marta; Wiggins, Chris H; Zhang, Li; Leslie, Christina
2007-12-01
Inferring gene regulatory networks from high-throughput genomic data is one of the central problems in computational biology. In this paper, we describe a predictive modeling approach for studying regulatory networks, based on a machine learning algorithm called MEDUSA. MEDUSA integrates promoter sequence, mRNA expression, and transcription factor occupancy data to learn gene regulatory programs that predict the differential expression of target genes. Instead of using clustering or correlation of expression profiles to infer regulatory relationships, MEDUSA determines condition-specific regulators and discovers regulatory motifs that mediate the regulation of target genes. In this way, MEDUSA meaningfully models biological mechanisms of transcriptional regulation. MEDUSA solves the problem of predicting the differential (up/down) expression of target genes by using boosting, a technique from statistical learning, which helps to avoid overfitting as the algorithm searches through the high-dimensional space of potential regulators and sequence motifs. Experimental results demonstrate that MEDUSA achieves high prediction accuracy on held-out experiments (test data), that is, data not seen in training. We also present context-specific analysis of MEDUSA regulatory programs for DNA damage and hypoxia, demonstrating that MEDUSA identifies key regulators and motifs in these processes. A central challenge in the field is the difficulty of validating reverse-engineered networks in the absence of a gold standard. Our approach of learning regulatory programs provides at least a partial solution for the problem: MEDUSA's prediction accuracy on held-out data gives a concrete and statistically sound way to validate how well the algorithm performs. With MEDUSA, statistical validation becomes a prerequisite for hypothesis generation and network building rather than a secondary consideration.
Standardized EEG interpretation accurately predicts prognosis after cardiac arrest
Rossetti, Andrea O.; van Rootselaar, Anne-Fleur; Wesenberg Kjaer, Troels; Horn, Janneke; Ullén, Susann; Friberg, Hans; Nielsen, Niklas; Rosén, Ingmar; Åneman, Anders; Erlinge, David; Gasche, Yvan; Hassager, Christian; Hovdenes, Jan; Kjaergaard, Jesper; Kuiper, Michael; Pellis, Tommaso; Stammet, Pascal; Wanscher, Michael; Wetterslev, Jørn; Wise, Matt P.; Cronberg, Tobias
2016-01-01
Objective: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. Methods: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3–5 until 180 days. Results: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. Conclusions: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome. PMID:26865516
How Accurately Can We Predict Eclipses for Algol? (Poster abstract)
NASA Astrophysics Data System (ADS)
Turner, D.
2016-06-01
(Abstract only) beta Persei, or Algol, is a very well known eclipsing binary system consisting of a late B-type dwarf that is regularly eclipsed by a GK subgiant every 2.867 days. Eclipses, which last about 8 hours, are regular enough that predictions for times of minima are published in various places, Sky & Telescope magazine and The Observer's Handbook, for example. But eclipse minimum lasts for less than a half hour, whereas subtle mistakes in the current ephemeris for the star can result in predictions that are off by a few hours or more. The Algol system is fairly complex, with the Algol A and Algol B eclipsing system also orbited by Algol C with an orbital period of nearly 2 years. Added to that are complex long-term O-C variations with a periodicity of almost two centuries that, although suggested by Hoffmeister to be spurious, fit the type of light travel time variations expected for a fourth star also belonging to the system. The AB sub-system also undergoes mass transfer events that add complexities to its O-C behavior. Is it actually possible to predict precise times of eclipse minima for Algol months in advance given such complications, or is it better to encourage ongoing observations of the star so that O-C variations can be tracked in real time?
Predictive rendering for accurate material perception: modeling and rendering fabrics
NASA Astrophysics Data System (ADS)
Bala, Kavita
2012-03-01
In computer graphics, rendering algorithms are used to simulate the appearance of objects and materials in a wide range of applications. Designers and manufacturers rely entirely on these rendered images to previsualize scenes and products before manufacturing them. They need to differentiate between different types of fabrics, paint finishes, plastics, and metals, often with subtle differences, for example, between silk and nylon, formaica and wood. Thus, these applications need predictive algorithms that can produce high-fidelity images that enable such subtle material discrimination.
Device for accurately measuring mass flow of gases
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.
Device for accurately measuring mass flow of gases
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.
A time-accurate finite volume method valid at all flow velocities
NASA Astrophysics Data System (ADS)
Kim, S.-W.
1993-07-01
A finite volume method to solve the Navier-Stokes equations at all flow velocities (e.g., incompressible, subsonic, transonic, supersonic and hypersonic flows) is presented. The numerical method is based on a finite volume method that incorporates a pressure-staggered mesh and an incremental pressure equation for the conservation of mass. Comparison of three generally accepted time-advancing schemes, i.e., Simplified Marker-and-Cell (SMAC), Pressure-Implicit-Splitting of Operators (PISO), and Iterative-Time-Advancing (ITA) scheme, are made by solving a lid-driven polar cavity flow and self-sustained oscillatory flows over circular and square cylinders. Calculated results show that the ITA is the most stable numerically and yields the most accurate results. The SMAC is the most efficient computationally and is as stable as the ITA. It is shown that the PISO is the most weakly convergent and it exhibits an undesirable strong dependence on the time-step size. The degenerated numerical results obtained using the PISO are attributed to its second corrector step that cause the numerical results to deviate further from a divergence free velocity field. The accurate numerical results obtained using the ITA is attributed to its capability to resolve the nonlinearity of the Navier-Stokes equations. The present numerical method that incorporates the ITA is used to solve an unsteady transitional flow over an oscillating airfoil and a chemically reacting flow of hydrogen in a vitiated supersonic airstream. The turbulence fields in these flow cases are described using multiple-time-scale turbulence equations. For the unsteady transitional over an oscillating airfoil, the fluid flow is described using ensemble-averaged Navier-Stokes equations defined on the Lagrangian-Eulerian coordinates. It is shown that the numerical method successfully predicts the large dynamic stall vortex (DSV) and the trailing edge vortex (TEV) that are periodically generated by the oscillating airfoil
Objective criteria accurately predict amputation following lower extremity trauma.
Johansen, K; Daines, M; Howey, T; Helfet, D; Hansen, S T
1990-05-01
MESS (Mangled Extremity Severity Score) is a simple rating scale for lower extremity trauma, based on skeletal/soft-tissue damage, limb ischemia, shock, and age. Retrospective analysis of severe lower extremity injuries in 25 trauma victims demonstrated a significant difference between MESS values for 17 limbs ultimately salvaged (mean, 4.88 +/- 0.27) and nine requiring amputation (mean, 9.11 +/- 0.51) (p less than 0.01). A prospective trial of MESS in lower extremity injuries managed at two trauma centers again demonstrated a significant difference between MESS values of 14 salvaged (mean, 4.00 +/- 0.28) and 12 doomed (mean, 8.83 +/- 0.53) limbs (p less than 0.01). In both the retrospective survey and the prospective trial, a MESS value greater than or equal to 7 predicted amputation with 100% accuracy. MESS may be useful in selecting trauma victims whose irretrievably injured lower extremities warrant primary amputation.
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.
Improved Ecosystem Predictions of the California Current System via Accurate Light Calculations
2011-09-30
System via Accurate Light Calculations Curtis D. Mobley Sequoia Scientific, Inc. 2700 Richards Road, Suite 107 Bellevue, WA 98005 phone: 425...incorporate extremely fast but accurate light calculations into coupled physical-biological-optical ocean ecosystem models as used for operational three...dimensional ecosystem predictions. Improvements in light calculations lead to improvements in predictions of chlorophyll concentrations and other
Generating highly accurate prediction hypotheses through collaborative ensemble learning
Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco
2017-01-01
Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination. PMID:28304378
Accurate predictions for the production of vaporized water
Morin, E.; Montel, F.
1995-12-31
The production of water vaporized in the gas phase is controlled by the local conditions around the wellbore. The pressure gradient applied to the formation creates a sharp increase of the molar water content in the hydrocarbon phase approaching the well; this leads to a drop in the pore water saturation around the wellbore. The extent of the dehydrated zone which is formed is the key controlling the bottom-hole content of vaporized water. The maximum water content in the hydrocarbon phase at a given pressure, temperature and salinity is corrected by capillarity or adsorption phenomena depending on the actual water saturation. Describing the mass transfer of the water between the hydrocarbon phases and the aqueous phase into the tubing gives a clear idea of vaporization effects on the formation of scales. Field example are presented for gas fields with temperatures ranging between 140{degrees}C and 180{degrees}C, where water vaporization effects are significant. Conditions for salt plugging in the tubing are predicted.
Generating highly accurate prediction hypotheses through collaborative ensemble learning
NASA Astrophysics Data System (ADS)
Arsov, Nino; Pavlovski, Martin; Basnarkov, Lasko; Kocarev, Ljupco
2017-03-01
Ensemble generation is a natural and convenient way of achieving better generalization performance of learning algorithms by gathering their predictive capabilities. Here, we nurture the idea of ensemble-based learning by combining bagging and boosting for the purpose of binary classification. Since the former improves stability through variance reduction, while the latter ameliorates overfitting, the outcome of a multi-model that combines both strives toward a comprehensive net-balancing of the bias-variance trade-off. To further improve this, we alter the bagged-boosting scheme by introducing collaboration between the multi-model’s constituent learners at various levels. This novel stability-guided classification scheme is delivered in two flavours: during or after the boosting process. Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms to generalize is inspected by comparing them against Subbagging and Gentle Boost on various real-world datasets. In both cases, our models obtained a 40% generalization error decrease. But their true ability to capture details in data was revealed through their application for protein detection in texture analysis of gel electrophoresis images. They achieve improved performance of approximately 0.9773 AUROC when compared to the AUROC of 0.9574 obtained by an SVM based on recursive feature elimination.
Accurate solutions for transonic viscous flow over finite wings
NASA Technical Reports Server (NTRS)
Vatsa, V. N.
1986-01-01
An explicit multistage Runge-Kutta type time-stepping scheme is used for solving the three-dimensional, compressible, thin-layer Navier-Stokes equations. A finite-volume formulation is employed to facilitate treatment of complex grid topologies encountered in three-dimensional calculations. Convergence to steady state is expedited through usage of acceleration techniques. Further numerical efficiency is achieved through vectorization of the computer code. The accuracy of the overall scheme is evaluated by comparing the computed solutions with the experimental data for a finite wing under different test conditions in the transonic regime. A grid refinement study ir conducted to estimate the grid requirements for adequate resolution of salient features of such flows.
Change in BMI Accurately Predicted by Social Exposure to Acquaintances
Oloritun, Rahman O.; Ouarda, Taha B. M. J.; Moturu, Sai; Madan, Anmol; Pentland, Alex (Sandy); Khayal, Inas
2013-01-01
Research has mostly focused on obesity and not on processes of BMI change more generally, although these may be key factors that lead to obesity. Studies have suggested that obesity is affected by social ties. However these studies used survey based data collection techniques that may be biased toward select only close friends and relatives. In this study, mobile phone sensing techniques were used to routinely capture social interaction data in an undergraduate dorm. By automating the capture of social interaction data, the limitations of self-reported social exposure data are avoided. This study attempts to understand and develop a model that best describes the change in BMI using social interaction data. We evaluated a cohort of 42 college students in a co-located university dorm, automatically captured via mobile phones and survey based health-related information. We determined the most predictive variables for change in BMI using the least absolute shrinkage and selection operator (LASSO) method. The selected variables, with gender, healthy diet category, and ability to manage stress, were used to build multiple linear regression models that estimate the effect of exposure and individual factors on change in BMI. We identified the best model using Akaike Information Criterion (AIC) and R2. This study found a model that explains 68% (p<0.0001) of the variation in change in BMI. The model combined social interaction data, especially from acquaintances, and personal health-related information to explain change in BMI. This is the first study taking into account both interactions with different levels of social interaction and personal health-related information. Social interactions with acquaintances accounted for more than half the variation in change in BMI. This suggests the importance of not only individual health information but also the significance of social interactions with people we are exposed to, even people we may not consider as close friends. PMID
Boraldi, Federica; Bartolomeo, Angelica; De Biasi, Sara; Orlando, Stefania; Costa, Sonia; Cossarizza, Andrea; Quaglino, Daniela
2016-01-01
Introduction Although rare, circulating endothelial and progenitor cells could be considered as markers of endothelial damage and repair potential, possibly predicting the severity of cardiovascular manifestations. A number of studies highlighted the role of these cells in age-related diseases, including those characterized by ectopic calcification. Nevertheless, their use in clinical practice is still controversial, mainly due to difficulties in finding reproducible and accurate methods for their determination. Methods Circulating mature cells (CMC, CD45-, CD34+, CD133-) and circulating progenitor cells (CPC, CD45dim, CD34bright, CD133+) were investigated by polychromatic high-speed flow cytometry to detect the expression of endothelial (CD309+) or osteogenic (BAP+) differentiation markers in healthy subjects and in patients affected by peripheral vascular manifestations associated with ectopic calcification. Results This study shows that: 1) polychromatic flow cytometry represents a valuable tool to accurately identify rare cells; 2) the balance of CD309+ on CMC/CD309+ on CPC is altered in patients affected by peripheral vascular manifestations, suggesting the occurrence of vascular damage and low repair potential; 3) the increase of circulating cells exhibiting a shift towards an osteoblast-like phenotype (BAP+) is observed in the presence of ectopic calcification. Conclusion Differences between healthy subjects and patients with ectopic calcification indicate that this approach may be useful to better evaluate endothelial dysfunction in a clinical context. PMID:27560136
NASA Astrophysics Data System (ADS)
Jin, Xuhon; Huang, Fei; Hu, Pengju; Cheng, Xiaoli
2016-11-01
A fundamental prerequisite for satellites operating in a Low Earth Orbit (LEO) is the availability of fast and accurate prediction of non-gravitational aerodynamic forces, which is characterised by the free molecular flow regime. However, conventional computational methods like the analytical integral method and direct simulation Monte Carlo (DSMC) technique are found failing to deal with flow shadowing and multiple reflections or computationally expensive. This work develops a general computer program for the accurate calculation of aerodynamic forces in the free molecular flow regime using the test particle Monte Carlo (TPMC) method, and non-gravitational aerodynamic forces actiong on the Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellite is calculated for different freestream conditions and gas-surface interaction models by the computer program.
Accurate prediction of wall shear stress in a stented artery: newtonian versus non-newtonian models.
Mejia, Juan; Mongrain, Rosaire; Bertrand, Olivier F
2011-07-01
A significant amount of evidence linking wall shear stress to neointimal hyperplasia has been reported in the literature. As a result, numerical and experimental models have been created to study the influence of stent design on wall shear stress. Traditionally, blood has been assumed to behave as a Newtonian fluid, but recently that assumption has been challenged. The use of a linear model; however, can reduce computational cost, and allow the use of Newtonian fluids (e.g., glycerine and water) instead of a blood analog fluid in an experimental setup. Therefore, it is of interest whether a linear model can be used to accurately predict the wall shear stress caused by a non-Newtonian fluid such as blood within a stented arterial segment. The present work compares the resulting wall shear stress obtained using two linear and one nonlinear model under the same flow waveform. All numerical models are fully three-dimensional, transient, and incorporate a realistic stent geometry. It is shown that traditional linear models (based on blood's lowest viscosity limit, 3.5 Pa s) underestimate the wall shear stress within a stented arterial segment, which can lead to an overestimation of the risk of restenosis. The second linear model, which uses a characteristic viscosity (based on an average strain rate, 4.7 Pa s), results in higher wall shear stress levels, but which are still substantially below those of the nonlinear model. It is therefore shown that nonlinear models result in more accurate predictions of wall shear stress within a stented arterial segment.
Development of Next Generation Multiphase Pipe Flow Prediction Tools
Cem Sarica; Holden Zhang
2006-05-31
The developments of oil and gas fields in deep waters (5000 ft and more) will become more common in the future. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas, oil and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of hydrocarbon recovery from design to operation. Recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications, including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is crucial for any multiphase separation technique, either at topside, seabed or bottom-hole, to know inlet conditions such as flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. Therefore, the development of a new generation of multiphase flow predictive tools is needed. The overall objective of the proposed study is to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, fluid properties and flow rates). In the current multiphase modeling approach, flow pattern and flow behavior (pressure gradient and phase fractions) prediction modeling are separated. Thus, different models based on different physics are employed, causing inaccuracies and discontinuities. Moreover, oil and water are treated as a pseudo single phase, ignoring the distinct characteristics of both oil and water, and often resulting in inaccurate design that leads to operational problems. In this study, a new model is being developed through a theoretical and experimental study employing a revolutionary approach. The
Applications of URANS on predicting unsteady turbulent separated flows
NASA Astrophysics Data System (ADS)
Xu, Jinglei; Ma, Huiyang
2009-06-01
Accurate prediction of unsteady separated turbulent flows remains one of the toughest tasks and a practical challenge for turbulence modeling. In this paper, a 2D flow past a circular cylinder at Reynolds number 3,900 is numerically investigated by using the technique of unsteady RANS (URANS). Some typical linear and nonlinear eddy viscosity turbulence models (LEVM and NLEVM) and a quadratic explicit algebraic stress model (EASM) are evaluated. Numerical results have shown that a high-performance cubic NLEVM, such as CLS, are superior to the others in simulating turbulent separated flows with unsteady vortex shedding.
Development of Next Generation Multiphase Pipe Flow Prediction Tools
Tulsa Fluid Flow
2008-08-31
The developments of fields in deep waters (5000 ft and more) is a common occurrence. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas-oil-and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of the hydrocarbon recovery from design to operation. The recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is very crucial to any multiphase separation technique that is employed either at topside, seabed or bottom-hole to know inlet conditions such as the flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. The overall objective was to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict the flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, fluid properties and flow rates). The project was conducted in two periods. In Period 1 (four years), gas-oil-water flow in pipes were investigated to understand the fundamental physical mechanisms describing the interaction between the gas-oil-water phases under flowing conditions, and a unified model was developed utilizing a novel modeling approach. A gas-oil-water pipe flow database including field and laboratory data was formed in Period 2 (one year). The database was utilized in model performance demonstration. Period 1 primarily consisted of the development of a unified model and software to predict the gas-oil-water flow, and experimental studies of the gas-oil-water project, including flow behavior description and
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
NASA Technical Reports Server (NTRS)
Srokowski, A. J.
1978-01-01
The problem of obtaining accurate estimates of suction requirements on swept laminar flow control wings was discussed. A fast accurate computer code developed to predict suction requirements by integrating disturbance amplification rates was described. Assumptions and approximations used in the present computer code are examined in light of flow conditions on the swept wing which may limit their validity.
NASA Technical Reports Server (NTRS)
Constantinescu, G.S.; Lele, S. K.
2000-01-01
The motivation of this work is the ongoing effort at the Center for Turbulence Research (CTR) to use large eddy simulation (LES) techniques to calculate the noise radiated by jet engines. The focus on engine exhaust noise reduction is motivated by the fact that a significant reduction has been achieved over the last decade on the other main sources of acoustic emissions of jet engines, such as the fan and turbomachinery noise, which gives increased priority to jet noise. To be able to propose methods to reduce the jet noise based on results of numerical simulations, one first has to be able to accurately predict the spatio-temporal distribution of the noise sources in the jet. Though a great deal of understanding of the fundamental turbulence mechanisms in high-speed jets was obtained from direct numerical simulations (DNS) at low Reynolds numbers, LES seems to be the only realistic available tool to obtain the necessary near-field information that is required to estimate the acoustic radiation of the turbulent compressible engine exhaust jets. The quality of jet-noise predictions is determined by the accuracy of the numerical method that has to capture the wide range of pressure fluctuations associated with the turbulence in the jet and with the resulting radiated noise, and by the boundary condition treatment and the quality of the mesh. Higher Reynolds numbers and coarser grids put in turn a higher burden on the robustness and accuracy of the numerical method used in this kind of jet LES simulations. As these calculations are often done in cylindrical coordinates, one of the most important requirements for the numerical method is to provide a flow solution that is not contaminated by numerical artifacts. The coordinate singularity is known to be a source of such artifacts. In the present work we use 6th order Pade schemes in the non-periodic directions to discretize the full compressible flow equations. It turns out that the quality of jet-noise predictions
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)
Accurate Prediction of One-Dimensional Protein Structure Features Using SPINE-X.
Faraggi, Eshel; Kloczkowski, Andrzej
2017-01-01
Accurate prediction of protein secondary structure and other one-dimensional structure features is essential for accurate sequence alignment, three-dimensional structure modeling, and function prediction. SPINE-X is a software package to predict secondary structure as well as accessible surface area and dihedral angles ϕ and ψ. For secondary structure SPINE-X achieves an accuracy of between 81 and 84 % depending on the dataset and choice of tests. The Pearson correlation coefficient for accessible surface area prediction is 0.75 and the mean absolute error from the ϕ and ψ dihedral angles are 20(∘) and 33(∘), respectively. The source code and a Linux executables for SPINE-X are available from Research and Information Systems at http://mamiris.com .
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.
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.
Low thrust viscous nozzle flow fields prediction
NASA Technical Reports Server (NTRS)
Liaw, G. S.; Mo, J. D.
1991-01-01
A Navier-Stokes code was developed for low thrust viscous nozzle flow field prediction. An implicit finite volume in an arbitrary curvilinear coordinate system lower-upper (LU) scheme is used to solve the governing Navier-Stokes equations and species transportation equations. Sample calculations of carbon dioxide nozzle flow are presented to verify the validity and efficiency of this code. The computer results are in reasonable agreement with the experimental data.
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.
A flux monitoring method for easy and accurate flow rate measurement in pressure-driven flows.
Siria, Alessandro; Biance, Anne-Laure; Ybert, Christophe; Bocquet, Lydéric
2012-03-07
We propose a low-cost and versatile method to measure flow rate in microfluidic channels under pressure-driven flows, thereby providing a simple characterization of the hydrodynamic permeability of the system. The technique is inspired by the current monitoring method usually employed to characterize electro-osmotic flows, and makes use of the measurement of the time-dependent electric resistance inside the channel associated with a moving salt front. We have successfully tested the method in a micrometer-size channel, as well as in a complex microfluidic channel with a varying cross-section, demonstrating its ability in detecting internal shape variations.
Vincent, Mark A; Hillier, Ian H
2014-08-25
The accurate prediction of the adsorption energies of unsaturated molecules on graphene in the presence of water is essential for the design of molecules that can modify its properties and that can aid its processability. We here show that a semiempirical MO method corrected for dispersive interactions (PM6-DH2) can predict the adsorption energies of unsaturated hydrocarbons and the effect of substitution on these values to an accuracy comparable to DFT values and in good agreement with the experiment. The adsorption energies of TCNE, TCNQ, and a number of sulfonated pyrenes are also predicted, along with the effect of hydration using the COSMO model.
Cas9-chromatin binding information enables more accurate CRISPR off-target prediction
Singh, Ritambhara; Kuscu, Cem; Quinlan, Aaron; Qi, Yanjun; Adli, Mazhar
2015-01-01
The CRISPR system has become a powerful biological tool with a wide range of applications. However, improving targeting specificity and accurately predicting potential off-targets remains a significant goal. Here, we introduce a web-based CRISPR/Cas9 Off-target Prediction and Identification Tool (CROP-IT) that performs improved off-target binding and cleavage site predictions. Unlike existing prediction programs that solely use DNA sequence information; CROP-IT integrates whole genome level biological information from existing Cas9 binding and cleavage data sets. Utilizing whole-genome chromatin state information from 125 human cell types further enhances its computational prediction power. Comparative analyses on experimentally validated datasets show that CROP-IT outperforms existing computational algorithms in predicting both Cas9 binding as well as cleavage sites. With a user-friendly web-interface, CROP-IT outputs scored and ranked list of potential off-targets that enables improved guide RNA design and more accurate prediction of Cas9 binding or cleavage sites. PMID:26032770
A predictive, nonlocal rheology for granular flows
NASA Astrophysics Data System (ADS)
Kamrin, Ken; Henann, David
2013-11-01
We propose a continuum model for flowing granular matter and demonstrate that it quantitatively predicts flow and stress fields in many different geometries. The model is constructed in a step-by-step fashion. First we compose a relation based on existing granular rheological approaches (notably the ``inertial'' granular flow rheology) and point out where the resulting model succeeds and where it does not. The clearest missing ingredient is shown to be the lack of an intrinsic length-scale. To tie flow features more carefully to the characteristic grain size, we compose a nonlocal model that includes a new size-dependent term (with only one new material parameter). This new nonlocal model resolves some outstanding questions in the granular flow literature--of note, it is the first model to predict all features of flows in split-bottom cell geometries, a decade-long open question in the field. In total, we will show that this new model, using three material parameters, quantitatively matches the flow and stress data from over 160 experiments in several different geometries.
NASA Astrophysics Data System (ADS)
Bozinoski, Radoslav
Significant research has been performed over the last several years on understanding the unsteady aerodynamics of various fluid flows. Much of this work has focused on quantifying the unsteady, three-dimensional flow field effects which have proven vital to the accurate prediction of many fluid and aerodynamic problems. Up until recently, engineers have predominantly relied on steady-state simulations to analyze the inherently three-dimensional ow structures that are prevalent in many of today's "real-world" problems. Increases in computational capacity and the development of efficient numerical methods can change this and allow for the solution of the unsteady Reynolds-Averaged Navier-Stokes (RANS) equations for practical three-dimensional aerodynamic applications. An integral part of this capability has been the performance and accuracy of the turbulence models coupled with advanced parallel computing techniques. This report begins with a brief literature survey of the role fully three-dimensional, unsteady, Navier-Stokes solvers have on the current state of numerical analysis. Next, the process of creating a baseline three-dimensional Multi-Block FLOw procedure called MBFLO3 is presented. Solutions for an inviscid circular arc bump, laminar at plate, laminar cylinder, and turbulent at plate are then presented. Results show good agreement with available experimental, numerical, and theoretical data. Scalability data for the parallel version of MBFLO3 is presented and shows efficiencies of 90% and higher for processes of no less than 100,000 computational grid points. Next, the description and implementation techniques used for several turbulence models are presented. Following the successful implementation of the URANS and DES procedures, the validation data for separated, non-reattaching flows over a NACA 0012 airfoil, wall-mounted hump, and a wing-body junction geometry are presented. Results for the NACA 0012 showed significant improvement in flow predictions
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.
An effective method for accurate prediction of the first hyperpolarizability of alkalides.
Wang, Jia-Nan; Xu, Hong-Liang; Sun, Shi-Ling; Gao, Ting; Li, Hong-Zhi; Li, Hui; Su, Zhong-Min
2012-01-15
The proper theoretical calculation method for nonlinear optical (NLO) properties is a key factor to design the excellent NLO materials. Yet it is a difficult task to obatin the accurate NLO property of large scale molecule. In present work, an effective intelligent computing method, as called extreme learning machine-neural network (ELM-NN), is proposed to predict accurately the first hyperpolarizability (β(0)) of alkalides from low-accuracy first hyperpolarizability. Compared with neural network (NN) and genetic algorithm neural network (GANN), the root-mean-square deviations of the predicted values obtained by ELM-NN, GANN, and NN with their MP2 counterpart are 0.02, 0.08, and 0.17 a.u., respectively. It suggests that the predicted values obtained by ELM-NN are more accurate than those calculated by NN and GANN methods. Another excellent point of ELM-NN is the ability to obtain the high accuracy level calculated values with less computing cost. Experimental results show that the computing time of MP2 is 2.4-4 times of the computing time of ELM-NN. Thus, the proposed method is a potentially powerful tool in computational chemistry, and it may predict β(0) of the large scale molecules, which is difficult to obtain by high-accuracy theoretical method due to dramatic increasing computational cost.
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.
Hash: a Program to Accurately Predict Protein Hα Shifts from Neighboring Backbone Shifts3
Zeng, Jianyang; Zhou, Pei; Donald, Bruce Randall
2012-01-01
Chemical shifts provide not only peak identities for analyzing NMR data, but also an important source of conformational information for studying protein structures. Current structural studies requiring Hα chemical shifts suffer from the following limitations. (1) For large proteins, the Hα chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of Cα that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict Hα chemical shifts. Predicting accurate Hα chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict Hα chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate Hα chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins. PMID:23242797
Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
Samsudin, Firdaus; Parker, Joanne L.; Sansom, Mark S.P.; Newstead, Simon; Fowler, Philip W.
2016-01-01
Summary Membrane transporters are critical modulators of drug pharmacokinetics, efficacy, and safety. One example is the proton-dependent oligopeptide transporter PepT1, also known as SLC15A1, which is responsible for the uptake of the β-lactam antibiotics and various peptide-based prodrugs. In this study, we modeled the binding of various peptides to a bacterial homolog, PepTSt, and evaluated a range of computational methods for predicting the free energy of binding. Our results show that a hybrid approach (endpoint methods to classify peptides into good and poor binders and a theoretically exact method for refinement) is able to accurately predict affinities, which we validated using proteoliposome transport assays. Applying the method to a homology model of PepT1 suggests that the approach requires a high-quality structure to be accurate. Our study provides a blueprint for extending these computational methodologies to other pharmaceutically important transporter families. PMID:27028887
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.
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.
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.
2016-12-01
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.
Slug flow: Occurrence, consequences, and prediction
Hill, T.J.; Wood, D.G.
1994-12-31
BP Exploration currently has an interest in hundreds of kilometers of operating multiphase flowlines. Most of the company`s proposed field developments also involve multiphase flowlines. A large number of these do or will experience slug flow, either as the normal flow regime, or as a result of transient behavior. Data on flow regime and slug flow characteristics have been collected from many lines over the past 8 years. Information on slug characteristics from a number of different systems is presented in this paper, including velocity, length and holdup. Some unfavorable consequences of slug flow on both process performance and system integrity are highlighted, including plant shutdowns and mechanical damage. The need to be able to predict slug flow for the design of future systems, and to advise the operators of existing systems, remains a high priority for R and D activities, as ever longer and more complex multiphase systems are proposed. BP`s latest slug frequency method is described, followed by guidelines for pipework layout, and comments on current R and D on corrosion in multiphase flow.
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
Testani, Jeffrey M.; Hanberg, Jennifer S.; Cheng, Susan; Rao, Veena; Onyebeke, Chukwuma; Laur, Olga; Kula, Alexander; Chen, Michael; Wilson, F. Perry; Darlington, Andrew; Bellumkonda, Lavanya; Jacoby, Daniel; Tang, W. H. Wilson; Parikh, Chirag R.
2015-01-01
Background Removal of excess sodium and fluid is a primary therapeutic objective in acute decompensated heart failure (ADHF) and commonly monitored with fluid balance and weight loss. However, these parameters are frequently inaccurate or not collected and require a delay of several hours after diuretic administration before they are available. Accessible tools for rapid and accurate prediction of diuretic response are needed. Methods and Results Based on well-established renal physiologic principles an equation was derived to predict net sodium output using a spot urine sample obtained one or two hours following loop diuretic administration. This equation was then prospectively validated in 50 ADHF patients using meticulously obtained timed 6-hour urine collections to quantitate loop diuretic induced cumulative sodium output. Poor natriuretic response was defined as a cumulative sodium output of <50 mmol, a threshold that would result in a positive sodium balance with twice-daily diuretic dosing. Following a median dose of 3 mg (2–4 mg) of intravenous bumetanide, 40% of the population had a poor natriuretic response. The correlation between measured and predicted sodium output was excellent (r=0.91, p<0.0001). Poor natriuretic response could be accurately predicted with the sodium prediction equation (AUC=0.95, 95% CI 0.89–1.0, p<0.0001). Clinically recorded net fluid output had a weaker correlation (r=0.66, p<0.001) and lesser ability to predict poor natriuretic response (AUC=0.76, 95% CI 0.63–0.89, p=0.002). Conclusions In patients being treated for ADHF, poor natriuretic response can be predicted soon after diuretic administration with excellent accuracy using a spot urine sample. PMID:26721915
2015-01-01
Background Biclustering is a popular method for identifying under which experimental conditions biological signatures are co-expressed. However, the general biclustering problem is NP-hard, offering room to focus algorithms on specific biological tasks. We hypothesize that conditional co-regulation of genes is a key factor in determining cell phenotype and that accurately segregating conditions in biclusters will improve such predictions. Thus, we developed a bicluster sampled coherence metric (BSCM) for determining which conditions and signals should be included in a bicluster. Results Our BSCM calculates condition and cluster size specific p-values, and we incorporated these into the popular integrated biclustering algorithm cMonkey. We demonstrate that incorporation of our new algorithm significantly improves bicluster co-regulation scores (p-value = 0.009) and GO annotation scores (p-value = 0.004). Additionally, we used a bicluster based signal to predict whether a given experimental condition will result in yeast peroxisome induction. Using the new algorithm, the classifier accuracy improves from 41.9% to 76.1% correct. Conclusions We demonstrate that the proposed BSCM helps determine which signals ought to be co-clustered, resulting in more accurately assigned bicluster membership. Furthermore, we show that BSCM can be extended to more accurately detect under which experimental conditions the genes are co-clustered. Features derived from this more accurate analysis of conditional regulation results in a dramatic improvement in the ability to predict a cellular phenotype in yeast. The latest cMonkey is available for download at https://github.com/baliga-lab/cmonkey2. The experimental data and source code featured in this paper is available http://AitchisonLab.com/BSCM. BSCM has been incorporated in the official cMonkey release. PMID:25881257
Kieslich, Chris A; Tamamis, Phanourios; Guzman, Yannis A; Onel, Melis; Floudas, Christodoulos A
2016-01-01
HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/.
Accurate similarity index based on activity and connectivity of node for link prediction
NASA Astrophysics Data System (ADS)
Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun
2015-05-01
Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.
Numerical prediction of flow in slender vortices
NASA Technical Reports Server (NTRS)
Reyna, Luis G.; Menne, Stefan
1988-01-01
The slender vortex approximation was investigated using the Navier-Stokes equations written in cylindrical coordinates. It is shown that, for free vortices without external pressure gradient, the breakdown length is proportional to the Reynolds number. For free vortices with adverse pressure gradients, the breakdown length is inversely proportional to the value of its gradient. For low Reynolds numbers, the predictions of the simplified system agreed well with the ones obtained from solutions of the full Navier-Stokes equations, whereas for high Reynolds numbers, the flow became quite sensitive to pressure fluctuations; it was found that the failure of the slender vortex equations corresponded to the critical condition as identified by Benjamin (1962) for inviscid flows. The predictions obtained from the approximating system were compared with available experimental results. For low swirl, a good agreement was obtained; for high swirl, on the other hand, upstream effects on the pressure gradient produced by the breakdown bubble caused poor agreement.
Stephanou, Pavlos S; Mavrantzas, Vlasis G
2014-06-07
We present a hierarchical computational methodology which permits the accurate prediction of the linear viscoelastic properties of entangled polymer melts directly from the chemical structure, chemical composition, and molecular architecture of the constituent chains. The method entails three steps: execution of long molecular dynamics simulations with moderately entangled polymer melts, self-consistent mapping of the accumulated trajectories onto a tube model and parameterization or fine-tuning of the model on the basis of detailed simulation data, and use of the modified tube model to predict the linear viscoelastic properties of significantly higher molecular weight (MW) melts of the same polymer. Predictions are reported for the zero-shear-rate viscosity η0 and the spectra of storage G'(ω) and loss G″(ω) moduli for several mono and bidisperse cis- and trans-1,4 polybutadiene melts as well as for their MW dependence, and are found to be in remarkable agreement with experimentally measured rheological data.
Prediction of an axisymmetric combusting flow
NASA Technical Reports Server (NTRS)
Correa, S. M.
1983-01-01
A numerical model for turbulent, recirculating combusting flow is developed and applied to a research combustor. The model is based on the time-averaged Navier-Stokes equations with k-epsilon turbulence closure and the compositional fluctuations at each point are given probabilistically in terms of the mixture fraction. The probability density function is derived from transport equations for its first two moments along with an assumption regarding its shape. The resulting equations are solved using a standard line relaxation algorithm. It is found that the predictions of the model are in good agreement with data from an axisymmetric, bluff-body stabilized research combustor, while the major discrepancies are similar to those found in isothermal flow comparisons. The peculiar features of this flow which contribute to the errors are examined. The agreement between the theory and data deteriorates as the central jet velocity is increased which indicates an enhanced role for unsteady effects.
Assessment of a high-order accurate Discontinuous Galerkin method for turbomachinery flows
NASA Astrophysics Data System (ADS)
Bassi, F.; Botti, L.; Colombo, A.; Crivellini, A.; Franchina, N.; Ghidoni, A.
2016-04-01
In this work the capabilities of a high-order Discontinuous Galerkin (DG) method applied to the computation of turbomachinery flows are investigated. The Reynolds averaged Navier-Stokes equations coupled with the two equations k-ω turbulence model are solved to predict the flow features, either in a fixed or rotating reference frame, to simulate the fluid flow around bodies that operate under an imposed steady rotation. To ensure, by design, the positivity of all thermodynamic variables at a discrete level, a set of primitive variables based on pressure and temperature logarithms is used. The flow fields through the MTU T106A low-pressure turbine cascade and the NASA Rotor 37 axial compressor have been computed up to fourth-order of accuracy and compared to the experimental and numerical data available in the literature.
Sengupta, Arkajyoti; Raghavachari, Krishnan
2014-10-14
Accurate modeling of the chemical reactions in many diverse areas such as combustion, photochemistry, or atmospheric chemistry strongly depends on the availability of thermochemical information of the radicals involved. However, accurate thermochemical investigations of radical systems using state of the art composite methods have mostly been restricted to the study of hydrocarbon radicals of modest size. In an alternative approach, systematic error-canceling thermochemical hierarchy of reaction schemes can be applied to yield accurate results for such systems. In this work, we have extended our connectivity-based hierarchy (CBH) method to the investigation of radical systems. We have calibrated our method using a test set of 30 medium sized radicals to evaluate their heats of formation. The CBH-rad30 test set contains radicals containing diverse functional groups as well as cyclic systems. We demonstrate that the sophisticated error-canceling isoatomic scheme (CBH-2) with modest levels of theory is adequate to provide heats of formation accurate to ∼1.5 kcal/mol. Finally, we predict heats of formation of 19 other large and medium sized radicals for which the accuracy of available heats of formation are less well-known.
Planar Near-Field Phase Retrieval Using GPUs for Accurate THz Far-Field Prediction
NASA Astrophysics Data System (ADS)
Junkin, Gary
2013-04-01
With a view to using Phase Retrieval to accurately predict Terahertz antenna far-field from near-field intensity measurements, this paper reports on three fundamental advances that achieve very low algorithmic error penalties. The first is a new Gaussian beam analysis that provides accurate initial complex aperture estimates including defocus and astigmatic phase errors, based only on first and second moment calculations. The second is a powerful noise tolerant near-field Phase Retrieval algorithm that combines Anderson's Plane-to-Plane (PTP) with Fienup's Hybrid-Input-Output (HIO) and Successive Over-Relaxation (SOR) to achieve increased accuracy at reduced scan separations. The third advance employs teraflop Graphical Processing Units (GPUs) to achieve practically real time near-field phase retrieval and to obtain the optimum aperture constraint without any a priori information.
Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O Anatole; Müller, Klaus-Robert; Tkatchenko, Alexandre
2015-06-18
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.
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
Hansen, Katja; Biegler, Franziska; Ramakrishnan, Raghunathan; Pronobis, Wiktor; von Lilienfeld, O. Anatole; Müller, Klaus -Robert; Tkatchenko, Alexandre
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 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. The same representation allows us to predict accurate electronic properties of molecules, such as their polarizability and molecular frontier orbital energies.
A Novel Method for Accurate Operon Predictions in All SequencedProkaryotes
Price, Morgan N.; Huang, Katherine H.; Alm, Eric J.; Arkin, Adam P.
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, and 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.
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.
Ihm, Yungok; Cooper, Valentino R; Gallego, Nidia C; Contescu, Cristian I; Morris, James R
2014-01-01
We demonstrate a successful, efficient framework for predicting gas adsorption properties in real materials based on first-principles calculations, with a specific comparison of experiment and theory for methane adsorption in activated carbons. These carbon materials have different pore size distributions, leading to a variety of uptake characteristics. Utilizing these distributions, we accurately predict experimental uptakes and heats of adsorption without empirical potentials or lengthy simulations. We demonstrate that materials with smaller pores have higher heats of adsorption, leading to a higher gas density in these pores. This pore-size dependence must be accounted for, in order to predict and understand the adsorption behavior. The theoretical approach combines: (1) ab initio calculations with a van der Waals density functional to determine adsorbent-adsorbate interactions, and (2) a thermodynamic method that predicts equilibrium adsorption densities by directly incorporating the calculated potential energy surface in a slit pore model. The predicted uptake at P=20 bar and T=298 K is in excellent agreement for all five activated carbon materials used. This approach uses only the pore-size distribution as an input, with no fitting parameters or empirical adsorbent-adsorbate interactions, and thus can be easily applied to other adsorbent-adsorbate combinations.
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
NASA Astrophysics Data System (ADS)
Ben Ali, Jaouher; Chebel-Morello, Brigitte; Saidi, Lotfi; Malinowski, Simon; Fnaiech, Farhat
2015-05-01
Accurate remaining useful life (RUL) prediction of critical assets is an important challenge in condition based maintenance to improve reliability and decrease machine's breakdown and maintenance's cost. Bearing is one of the most important components in industries which need to be monitored and the user should predict its RUL. The challenge of this study is to propose an original feature able to evaluate the health state of bearings and to estimate their RUL by Prognostics and Health Management (PHM) techniques. In this paper, the proposed method is based on the data-driven prognostic approach. The combination of Simplified Fuzzy Adaptive Resonance Theory Map (SFAM) neural network and Weibull distribution (WD) is explored. WD is used just in the training phase to fit measurement and to avoid areas of fluctuation in the time domain. SFAM training process is based on fitted measurements at present and previous inspection time points as input. However, the SFAM testing process is based on real measurements at present and previous inspections. Thanks to the fuzzy learning process, SFAM has an important ability and a good performance to learn nonlinear time series. As output, seven classes are defined; healthy bearing and six states for bearing degradation. In order to find the optimal RUL prediction, a smoothing phase is proposed in this paper. Experimental results show that the proposed method can reliably predict the RUL of rolling element bearings (REBs) based on vibration signals. The proposed prediction approach can be applied to prognostic other various mechanical assets.
SIFTER search: a web server for accurate phylogeny-based protein function prediction
Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.
2015-01-01
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 to 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. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded. PMID:25979264
SIFTER search: a web server for accurate phylogeny-based protein function prediction
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 to 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.
SIFTER search: a web server for accurate phylogeny-based protein function prediction
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
Accurate verification of the conserved-vector-current and standard-model predictions
Sirlin, A.; Zucchini, R.
1986-10-20
An approximate analytic calculation of O(Z..cap alpha../sup 2/) corrections to Fermi decays is presented. When the analysis of Koslowsky et al. is modified to take into account the new results, it is found that each of the eight accurately studied scrFt values differs from the average by approx. <1sigma, thus significantly improving the comparison of experiments with conserved-vector-current predictions. The new scrFt values are lower than before, which also brings experiments into very good agreement with the three-generation standard model, at the level of its quantum corrections.
NASA Technical Reports Server (NTRS)
Tamma, Kumar K.; Railkar, Sudhir B.
1988-01-01
This paper represents an attempt to apply extensions of a hybrid transfinite element computational approach for accurately predicting thermoelastic stress waves. The applicability of the present formulations for capturing the thermal stress waves induced by boundary heating for the well known Danilovskaya problems is demonstrated. A unique feature of the proposed formulations for applicability to the Danilovskaya problem of thermal stress waves in elastic solids lies in the hybrid nature of the unified formulations and the development of special purpose transfinite elements in conjunction with the classical Galerkin techniques and transformation concepts. Numerical test cases validate the applicability and superior capability to capture the thermal stress waves induced due to boundary heating.
The MIDAS touch for Accurately Predicting the Stress-Strain Behavior of Tantalum
Jorgensen, S.
2016-03-02
Testing the behavior of metals in extreme environments is not always feasible, so material scientists use models to try and predict the behavior. To achieve accurate results it is necessary to use the appropriate model and material-specific parameters. This research evaluated the performance of six material models available in the MIDAS database [1] to determine at which temperatures and strain-rates they perform best, and to determine to which experimental data their parameters were optimized. Additionally, parameters were optimized for the Johnson-Cook model using experimental data from Lassila et al [2].
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.
A Weight-Averaged Interpolation Method for Coupling Time-Accurate Rarefied and Continuum Flows
NASA Astrophysics Data System (ADS)
Diaz, Steven William
A novel approach to coupling rarefied and continuum flow regimes as a single, hybrid model is introduced. The method borrows from techniques used in the simulation of spray flows to interpolate Lagrangian point-particles onto an Eulerian grid in a weight-averaged sense. A brief overview of traditional methods for modeling both rarefied and continuum domains is given, and a review of the literature regarding rarefied/continuum flow coupling is presented. Details of the theoretical development of the method of weighted interpolation are then described. The method evaluates macroscopic properties at the nodes of a CFD grid via the weighted interpolation of all simulated molecules in a set surrounding the node. The weight factor applied to each simulated molecule is the inverse of the linear distance between it and the given node. During development, the method was applied to several preliminary cases, including supersonic flow over an airfoil, subsonic flow over tandem airfoils, and supersonic flow over a backward facing step; all at low Knudsen numbers. The main thrust of the research centered on the time-accurate expansion of a rocket plume into a near-vacuum. The method proves flexible enough to be used with various flow solvers, demonstrated by the use of Fluent as the continuum solver for the preliminary cases and a NASA-developed Large Eddy Simulation research code, WRLES, for the full lunar model. The method is applicable to a wide range of Mach numbers and is completely grid independent, allowing the rarefied and continuum solvers to be optimized for their respective domains without consideration of the other. The work presented demonstrates the validity, and flexibility of the method of weighted interpolation as a novel concept in the field of hybrid flow coupling. The method marks a significant divergence from current practices in the coupling of rarefied and continuum flow domains and offers a kernel on which to base an ongoing field of research. It has the
Accurate prediction of human drug toxicity: a major challenge in drug development.
Li, Albert P
2004-11-01
Over the past decades, a number of drugs have been withdrawn or have required special labeling due to adverse effects observed post-marketing. Species differences in drug toxicity in preclinical safety tests and the lack of sensitive biomarkers and nonrepresentative patient population in clinical trials are probable reasons for the failures in predicting human drug toxicity. It is proposed that toxicology should evolve from an empirical practice to an investigative discipline. Accurate prediction of human drug toxicity requires resources and time to be spent in clearly defining key toxic pathways and corresponding risk factors, which hopefully, will be compensated by the benefits of a lower percentage of clinical failure due to toxicity and a decreased frequency of market withdrawal due to unacceptable adverse drug effects.
Prediction of inverted velocity profile for gas flow in nanochannel
NASA Astrophysics Data System (ADS)
Zhang, T. T.; Ren, Y. R.
2014-11-01
Velocity inversion is an interesting phenomenon of nanoscale which means that the velocity near the wall is greater than that of center. To solve this problem, fluid flow in nanochannel attracts more attention in recent years. The physical model of gas flow in two-dimensional nanochannel was established here. To describe the process with conventional control equations, Navier-Stokes equations combined with high-order accurate slip boundary conditions was used as mathematical model. With the introduction of new dimensionless variables, the problem was reduced to an ordinary differential equation. Then it was analytically solved and investigated using homotopy analysis method (HAM). The results were verified by comparing with other available experiment data. Result shows that the proposed method could predict velocity phenomenon.
Accurate prediction of the response of freshwater fish to a mixture of estrogenic chemicals.
Brian, Jayne V; Harris, Catherine A; Scholze, Martin; Backhaus, Thomas; Booy, Petra; Lamoree, Marja; Pojana, Giulio; Jonkers, Niels; Runnalls, Tamsin; Bonfà, Angela; Marcomini, Antonio; Sumpter, John P
2005-06-01
Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration-response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk.
Accurate Prediction of the Response of Freshwater Fish to a Mixture of Estrogenic Chemicals
Brian, Jayne V.; Harris, Catherine A.; Scholze, Martin; Backhaus, Thomas; Booy, Petra; Lamoree, Marja; Pojana, Giulio; Jonkers, Niels; Runnalls, Tamsin; Bonfà, Angela; Marcomini, Antonio; Sumpter, John P.
2005-01-01
Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration–response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk. PMID:15929895
IDSite: An accurate approach to predict P450-mediated drug metabolism
Li, Jianing; Schneebeli, Severin T.; Bylund, Joseph; Farid, Ramy; Friesner, Richard A.
2011-01-01
Accurate prediction of drug metabolism is crucial for drug design. Since a large majority of drugs metabolism involves P450 enzymes, we herein describe a computational approach, IDSite, to predict P450-mediated drug metabolism. To model induced-fit effects, IDSite samples the conformational space with flexible docking in Glide followed by two refinement stages using the Protein Local Optimization Program (PLOP). Sites of metabolism (SOMs) are predicted according to a physical-based score that evaluates the potential of atoms to react with the catalytic iron center. As a preliminary test, we present in this paper the prediction of hydroxylation and O-dealkylation sites mediated by CYP2D6 using two different models: a physical-based simulation model, and a modification of this model in which a small number of parameters are fit to a training set. Without fitting any parameters to experimental data, the Physical IDSite scoring recovers 83% of the experimental observations for 56 compounds with a very low false positive rate. With only 4 fitted parameters, the Fitted IDSite was trained with the subset of 36 compounds and successfully applied to the other 20 compounds, recovering 94% of the experimental observations with high sensitivity and specificity for both sets. PMID:22247702
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.
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
Assessment and prediction of debris-flow hazards
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.
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
Low thrust viscous nozzle flow fields prediction
NASA Technical Reports Server (NTRS)
Liaw, Goang-Shin
1987-01-01
An existing Navier-Stokes code (PARC2D) was used to compute the nozzle flow field. Grids were generated by the interactive grid generator codes TBGG and GENIE. All computations were made on the NASA/MSFC CRAY X-MP computer. Comparisons were made between the computations and MSFC in-house wall pressure measurements for CO2 flow through a conical nozzle having an area ratio of 40. Satisfactory agreements exist between the computations and measurements for different stagnation pressures of 29.4, 14.7, and 7.4 psia, at stagnation temperature of 1060 R. However, agreements did not match precisely near the nozzle exit. Several reasons for the lack of agreement are possible. The computational code assumes a constant gas gamma, whereas the gamma i.e. the specific heat ratio for CO2 varied from 1.22 in the plenum chamber to 1.38 at the nozzle exit. The computations also assumes adiabatic and no-slip walls. Both assumptions may not be correct. Finally, it is possible that condensation occurs during the nozzle expansion at the low stagnation pressure. The next phase of the work will incorporate variable gamma and slip wall boundary conditions in the computational code and develop a more accurate computer code.
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.
Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
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
NASA Astrophysics Data System (ADS)
Garrison, Stephen L.
2005-07-01
The combination of molecular simulations and potentials obtained from quantum chemistry is shown to be able to provide reasonably accurate thermodynamic property predictions. Gibbs ensemble Monte Carlo simulations are used to understand the effects of small perturbations to various regions of the model Lennard-Jones 12-6 potential. However, when the phase behavior and second virial coefficient are scaled by the critical properties calculated for each potential, the results obey a corresponding states relation suggesting a non-uniqueness problem for interaction potentials fit to experimental phase behavior. Several variations of a procedure collectively referred to as quantum mechanical Hybrid Methods for Interaction Energies (HM-IE) are developed and used to accurately estimate interaction energies from CCSD(T) calculations with a large basis set in a computationally efficient manner for the neon-neon, acetylene-acetylene, and nitrogen-benzene systems. Using these results and methods, an ab initio, pairwise-additive, site-site potential for acetylene is determined and then improved using results from molecular simulations using this initial potential. The initial simulation results also indicate that a limited range of energies important for accurate phase behavior predictions. Second virial coefficients calculated from the improved potential indicate that one set of experimental data in the literature is likely erroneous. This prescription is then applied to methanethiol. Difficulties in modeling the effects of the lone pair electrons suggest that charges on the lone pair sites negatively impact the ability of the intermolecular potential to describe certain orientations, but that the lone pair sites may be necessary to reasonably duplicate the interaction energies for several orientations. Two possible methods for incorporating the effects of three-body interactions into simulations within the pairwise-additivity formulation are also developed. A low density
Orbital Advection by Interpolation: A Fast and Accurate Numerical Scheme for Super-Fast MHD Flows
Johnson, B M; Guan, X; Gammie, F
2008-04-11
In numerical models of thin astrophysical disks that use an Eulerian scheme, gas orbits supersonically through a fixed grid. As a result the timestep is sharply limited by the Courant condition. Also, because the mean flow speed with respect to the grid varies with position, the truncation error varies systematically with position. For hydrodynamic (unmagnetized) disks an algorithm called FARGO has been developed that advects the gas along its mean orbit using a separate interpolation substep. This relaxes the constraint imposed by the Courant condition, which now depends only on the peculiar velocity of the gas, and results in a truncation error that is more nearly independent of position. This paper describes a FARGO-like algorithm suitable for evolving magnetized disks. Our method is second order accurate on a smooth flow and preserves {del} {center_dot} B = 0 to machine precision. The main restriction is that B must be discretized on a staggered mesh. We give a detailed description of an implementation of the code and demonstrate that it produces the expected results on linear and nonlinear problems. We also point out how the scheme might be generalized to make the integration of other supersonic/super-fast flows more efficient. Although our scheme reduces the variation of truncation error with position, it does not eliminate it. We show that the residual position dependence leads to characteristic radial variations in the density over long integrations.
Accurate optical flow field estimation using mechanical properties of soft tissues
NASA Astrophysics Data System (ADS)
Mehrabian, Hatef; Karimi, Hirad; Samani, Abbas
2009-02-01
A novel optical flow based technique is presented in this paper to measure the nodal displacements of soft tissue undergoing large deformations. In hyperelasticity imaging, soft tissues maybe compressed extensively [1] and the deformation may exceed the number of pixels ordinary optical flow approaches can detect. Furthermore in most biomedical applications there is a large amount of image information that represent the geometry of the tissue and the number of tissue types present in the organ of interest. Such information is often ignored in applications such as image registration. In this work we incorporate the information pertaining to soft tissue mechanical behavior (Neo-Hookean hyperelastic model is used here) in addition to the tissue geometry before compression into a hierarchical Horn-Schunck optical flow method to overcome this large deformation detection weakness. Applying the proposed method to a phantom using several compression levels proved that it yields reasonably accurate displacement fields. Estimated displacement results of this phantom study obtained for displacement fields of 85 pixels/frame and 127 pixels/frame are reported and discussed in this paper.
Intermolecular potentials and the accurate prediction of the thermodynamic properties of water
NASA Astrophysics Data System (ADS)
Shvab, I.; Sadus, Richard J.
2013-11-01
The ability of intermolecular potentials to correctly predict the thermodynamic properties of liquid water at a density of 0.998 g/cm3 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. 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.
Intermolecular potentials and the accurate prediction of the thermodynamic properties of water.
Shvab, I; Sadus, Richard J
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(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. 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.
Intermolecular potentials and the accurate prediction of the thermodynamic properties of water
Shvab, I.; Sadus, Richard J.
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. 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.
Using a highly accurate self-stop Cu-CMP model in the design flow
NASA Astrophysics Data System (ADS)
Izuha, Kyoko; Sakairi, Takashi; Shibuki, Shunichi; Bora, Monalisa; Hatem, Osama; Ghulghazaryan, Ruben; Strecker, Norbert; Wilson, Jeff; Takeshita, Noritsugu
2010-03-01
An accurate model for the self-stop copper chemical mechanical polishing (Cu-CMP) process has been developed using CMP modeling technology from Mentor Graphics. This technology was applied on data from Sony to create and optimize copper electroplating (ECD), Cu-CMP, and barrier metal polishing (BM-CMP) process models. These models take into account layout pattern dependency, long range diffusion and planarization effects, as well as microloading from local pattern density. The developed ECD model accurately predicted erosion and dishing over the entire range of width and space combinations present on the test chip. Then, the results of the ECD model were used as an initial structure to model the Cu-CMP step. Subsequently, the result of Cu-CMP was used for the BM-CMP model creation. The created model was successful in reproducing the measured data, including trends for a broad range of metal width and densities. Its robustness is demonstrated by the fact that it gives acceptable prediction of final copper thickness data although the calibration data included noise from line scan measurements. Accuracy of the Cu-CMP model has a great impact on the prediction results for BM-CMP. This is a critical feature for the modeling of high precision CMP such as self-stop Cu-CMP. Finally, the developed model could successfully extract planarity hotspots that helped identify potential problems in production chips before they were manufactured. The output thickness values of metal and dielectric can be used to drive layout enhancement tools and improve the accuracy of timing analysis.
NASA Astrophysics Data System (ADS)
Zacharias, Panagiotis P.; Chatzineofytou, Elpida G.; Spantideas, Sotirios T.; Capsalis, Christos N.
2016-07-01
In the present work, the determination of the magnetic behavior of localized magnetic sources from near-field measurements is examined. The distance power law of the magnetic field fall-off is used in various cases to accurately predict the magnetic signature of an equipment under test (EUT) consisting of multiple alternating current (AC) magnetic sources. Therefore, parameters concerning the location of the observation points (magnetometers) are studied towards this scope. The results clearly show that these parameters are independent of the EUT's size and layout. Additionally, the techniques developed in the present study enable the placing of the magnetometers close to the EUT, thus achieving high signal-to-noise ratio (SNR). Finally, the proposed method is verified by real measurements, using a mobile phone as an EUT.
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.
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.
Measuring solar reflectance Part I: Defining a metric that accurately predicts solar heat gain
Levinson, Ronnen; Akbari, Hashem; Berdahl, Paul
2010-05-14
Solar reflectance can vary with the spectral and angular distributions of incident sunlight, which in turn depend on surface orientation, solar position and atmospheric conditions. A widely used solar reflectance metric based on the ASTM Standard E891 beam-normal solar spectral irradiance underestimates the solar heat gain of a spectrally selective 'cool colored' surface because this irradiance contains a greater fraction of near-infrared light than typically found in ordinary (unconcentrated) global sunlight. At mainland U.S. latitudes, this metric RE891BN can underestimate the annual peak solar heat gain of a typical roof or pavement (slope {le} 5:12 [23{sup o}]) by as much as 89 W m{sup -2}, and underestimate its peak surface temperature by up to 5 K. Using R{sub E891BN} to characterize roofs in a building energy simulation can exaggerate the economic value N of annual cool-roof net energy savings by as much as 23%. We define clear-sky air mass one global horizontal ('AM1GH') solar reflectance R{sub g,0}, a simple and easily measured property that more accurately predicts solar heat gain. R{sub g,0} predicts the annual peak solar heat gain of a roof or pavement to within 2 W m{sup -2}, and overestimates N by no more than 3%. R{sub g,0} is well suited to rating the solar reflectances of roofs, pavements and walls. We show in Part II that R{sub g,0} can be easily and accurately measured with a pyranometer, a solar spectrophotometer or version 6 of the Solar Spectrum Reflectometer.
Point-of-care cardiac troponin test accurately predicts heat stroke severity in rats.
Audet, Gerald N; Quinn, Carrie M; Leon, Lisa R
2015-11-15
Heat stroke (HS) remains a significant public health concern. Despite the substantial threat posed by HS, there is still no field or clinical test of HS severity. We suggested previously that circulating cardiac troponin (cTnI) could serve as a robust biomarker of HS severity after heating. In the present study, we hypothesized that (cTnI) point-of-care test (ctPOC) could be used to predict severity and organ damage at the onset of HS. Conscious male Fischer 344 rats (n = 16) continuously monitored for heart rate (HR), blood pressure (BP), and core temperature (Tc) (radiotelemetry) were heated to maximum Tc (Tc,Max) of 41.9 ± 0.1°C and recovered undisturbed for 24 h at an ambient temperature of 20°C. Blood samples were taken at Tc,Max and 24 h after heat via submandibular bleed and analyzed on ctPOC test. POC cTnI band intensity was ranked using a simple four-point scale via two blinded observers and compared with cTnI levels measured by a clinical blood analyzer. Blood was also analyzed for biomarkers of systemic organ damage. HS severity, as previously defined using HR, BP, and recovery Tc profile during heat exposure, correlated strongly with cTnI (R(2) = 0.69) at Tc,Max. POC cTnI band intensity ranking accurately predicted cTnI levels (R(2) = 0.64) and HS severity (R(2) = 0.83). Five markers of systemic organ damage also correlated with ctPOC score (albumin, alanine aminotransferase, blood urea nitrogen, cholesterol, and total bilirubin; R(2) > 0.4). This suggests that cTnI POC tests can accurately determine HS severity and could serve as simple, portable, cost-effective HS field tests.
Li, Zheng-Wei; You, Zhu-Hong; Chen, Xing; Gui, Jie; Nie, Ru
2016-01-01
Protein-protein interactions (PPIs) occur at almost all levels of cell functions and play crucial roles in various cellular processes. Thus, identification of PPIs is critical for deciphering the molecular mechanisms and further providing insight into biological processes. Although a variety of high-throughput experimental techniques have been developed to identify PPIs, existing PPI pairs by experimental approaches only cover a small fraction of the whole PPI networks, and further, those approaches hold inherent disadvantages, such as being time-consuming, expensive, and having high false positive rate. Therefore, it is urgent and imperative to develop automatic in silico approaches to predict PPIs efficiently and accurately. In this article, we propose a novel mixture of physicochemical and evolutionary-based feature extraction method for predicting PPIs using our newly developed discriminative vector machine (DVM) classifier. The improvements of the proposed method mainly consist in introducing an effective feature extraction method that can capture discriminative features from the evolutionary-based information and physicochemical characteristics, and then a powerful and robust DVM classifier is employed. To the best of our knowledge, it is the first time that DVM model is applied to the field of bioinformatics. When applying the proposed method to the Yeast and Helicobacter pylori (H. pylori) datasets, we obtain excellent prediction accuracies of 94.35% and 90.61%, respectively. The computational results indicate that our method is effective and robust for predicting PPIs, and can be taken as a useful supplementary tool to the traditional experimental methods for future proteomics research. PMID:27571061
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.
Efficient computation of volume in flow predictions
NASA Technical Reports Server (NTRS)
Vinokur, M.; Kordulla, W.
1983-01-01
An efficient method for calculating cell volumes for time-dependent three-dimensional flow predictions by finite volume calculations is presented. Eight arbitrary corner points are considered and the shape face is divided into two planar triangles. The volume is then dependent on the orientation of the partitioning. In the case of a hexahedron, it is noted that any open surface with a boundary that is a closed curve possesses a surface vector independent of the surface shape. Expressions are defined for the surface vector, which is independent of the partitioning surface diagonal used to quantify the volume. Using a decomposition of the cell volume involving two corners, with each the vertex of three diagonals and six corners which are vertices of one diagonal, gives portions which are tetrahedra. The resultant mesh is can be used for time-dependent finite volume calculations one requires less computer time than previous methods.
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.
Fast and accurate numerical method for predicting gas chromatography retention time.
Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira
2015-08-07
Predictive modeling for gas chromatography compound retention depends on the retention factor (ki) and on the flow of the mobile phase. Thus, different approaches for determining an analyte ki in column chromatography have been developed. The main one is based on the thermodynamic properties of the component and on the characteristics of the stationary phase. These models can be used to estimate the parameters and to optimize the programming of temperatures, in gas chromatography, for the separation of compounds. Different authors have proposed the use of numerical methods for solving these models, but these methods demand greater computational time. Hence, a new method for solving the predictive modeling of analyte retention time is presented. This algorithm is an alternative to traditional methods because it transforms its attainments into root determination problems within defined intervals. The proposed approach allows for tr calculation, with accuracy determined by the user of the methods, and significant reductions in computational time; it can also be used to evaluate the performance of other prediction methods.
A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina.
Maturana, Matias I; Apollo, Nicholas V; Hadjinicolaou, Alex E; Garrett, David J; Cloherty, Shaun L; Kameneva, Tatiana; Grayden, David B; Ibbotson, Michael R; Meffin, Hamish
2016-04-01
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron's electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.
ChIP-seq Accurately Predicts Tissue-Specific Activity of Enhancers
Visel, Axel; Blow, Matthew J.; Li, Zirong; Zhang, Tao; Akiyama, Jennifer A.; Holt, Amy; Plajzer-Frick, Ingrid; Shoukry, Malak; Wright, Crystal; Chen, Feng; Afzal, Veena; Ren, Bing; Rubin, Edward M.; Pennacchio, Len A.
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. We 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.
A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina
Maturana, Matias I.; Apollo, Nicholas V.; Hadjinicolaou, Alex E.; Garrett, David J.; Cloherty, Shaun L.; Kameneva, Tatiana; Grayden, David B.; Ibbotson, Michael R.; Meffin, Hamish
2016-01-01
Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy. PMID:27035143
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.
Predictive models for moving contact line flows
NASA Technical Reports Server (NTRS)
Rame, Enrique; Garoff, Stephen
2003-01-01
Modeling flows with moving contact lines poses the formidable challenge that the usual assumptions of Newtonian fluid and no-slip condition give rise to a well-known singularity. This singularity prevents one from satisfying the contact angle condition to compute the shape of the fluid-fluid interface, a crucial calculation without which design parameters such as the pressure drop needed to move an immiscible 2-fluid system through a solid matrix cannot be evaluated. Some progress has been made for low Capillary number spreading flows. Combining experimental measurements of fluid-fluid interfaces very near the moving contact line with an analytical expression for the interface shape, we can determine a parameter that forms a boundary condition for the macroscopic interface shape when Ca much les than l. This parameter, which plays the role of an "apparent" or macroscopic dynamic contact angle, is shown by the theory to depend on the system geometry through the macroscopic length scale. This theoretically established dependence on geometry allows this parameter to be "transferable" from the geometry of the measurement to any other geometry involving the same material system. Unfortunately this prediction of the theory cannot be tested on Earth.
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
Accurate and Robust Genomic Prediction of Celiac Disease Using Statistical Learning
Abraham, Gad; Tye-Din, Jason A.; Bhalala, Oneil G.; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael
2014-01-01
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. PMID:24550740
Energy expenditure during level human walking: seeking a simple and accurate predictive solution.
Ludlow, Lindsay W; Weyand, Peter G
2016-03-01
Accurate prediction of the metabolic energy that walking requires can inform numerous health, bodily status, and fitness outcomes. We adopted a two-step approach to identifying a concise, generalized equation for predicting level human walking metabolism. Using literature-aggregated values we compared 1) the predictive accuracy of three literature equations: American College of Sports Medicine (ACSM), Pandolf et al., and Height-Weight-Speed (HWS); and 2) the goodness-of-fit possible from one- vs. two-component descriptions of walking metabolism. Literature metabolic rate values (n = 127; speed range = 0.4 to 1.9 m/s) were aggregated from 25 subject populations (n = 5-42) whose means spanned a 1.8-fold range of heights and a 4.2-fold range of weights. Population-specific resting metabolic rates (V̇o2 rest) were determined using standardized equations. Our first finding was that the ACSM and Pandolf et al. equations underpredicted nearly all 127 literature-aggregated values. Consequently, their standard errors of estimate (SEE) were nearly four times greater than those of the HWS equation (4.51 and 4.39 vs. 1.13 ml O2·kg(-1)·min(-1), respectively). For our second comparison, empirical best-fit relationships for walking metabolism were derived from the data set in one- and two-component forms for three V̇o2-speed model types: linear (∝V(1.0)), exponential (∝V(2.0)), and exponential/height (∝V(2.0)/Ht). We found that the proportion of variance (R(2)) accounted for, when averaged across the three model types, was substantially lower for one- vs. two-component versions (0.63 ± 0.1 vs. 0.90 ± 0.03) and the predictive errors were nearly twice as great (SEE = 2.22 vs. 1.21 ml O2·kg(-1)·min(-1)). Our final analysis identified the following concise, generalized equation for predicting level human walking metabolism: V̇o2 total = V̇o2 rest + 3.85 + 5.97·V(2)/Ht (where V is measured in m/s, Ht in meters, and V̇o2 in ml O2·kg(-1)·min(-1)).
Wong, Sharon; Back, Michael; Tan, Poh Wee; Lee, Khai Mun; Baggarley, Shaun; Lu, Jaide Jay
2012-07-01
Skin doses have been an important factor in the dose prescription for breast radiotherapy. Recent advances in radiotherapy treatment techniques, such as intensity-modulated radiation therapy (IMRT) and new treatment schemes such as hypofractionated breast therapy have made the precise determination of the surface dose necessary. Detailed information of the dose at various depths of the skin is also critical in designing new treatment strategies. The purpose of this work was to assess the accuracy of surface dose calculation by a clinically used treatment planning system and those measured by thermoluminescence dosimeters (TLDs) in a customized chest wall phantom. This study involved the construction of a chest wall phantom for skin dose assessment. Seven TLDs were distributed throughout each right chest wall phantom to give adequate representation of measured radiation doses. Point doses from the CMS Xio Registered-Sign treatment planning system (TPS) were calculated for each relevant TLD positions and results correlated. There were no significant difference between measured absorbed dose by TLD and calculated doses by the TPS (p > 0.05 (1-tailed). Dose accuracy of up to 2.21% was found. The deviations from the calculated absorbed doses were overall larger (3.4%) when wedges and bolus were used. 3D radiotherapy TPS is a useful and accurate tool to assess the accuracy of surface dose. Our studies have shown that radiation treatment accuracy expressed as a comparison between calculated doses (by TPS) and measured doses (by TLD dosimetry) can be accurately predicted for tangential treatment of the chest wall after mastectomy.
Polzer, S; Gasser, T C; Novak, K; Man, V; Tichy, M; Skacel, P; Bursa, J
2015-03-01
Structure-based constitutive models might help in exploring mechanisms by which arterial wall histology is linked to wall mechanics. This study aims to validate a recently proposed structure-based constitutive model. Specifically, the model's ability to predict mechanical biaxial response of porcine aortic tissue with predefined collagen structure was tested. Histological slices from porcine thoracic aorta wall (n=9) were automatically processed to quantify the collagen fiber organization, and mechanical testing identified the non-linear properties of the wall samples (n=18) over a wide range of biaxial stretches. Histological and mechanical experimental data were used to identify the model parameters of a recently proposed multi-scale constitutive description for arterial layers. The model predictive capability was tested with respect to interpolation and extrapolation. Collagen in the media was predominantly aligned in circumferential direction (planar von Mises distribution with concentration parameter bM=1.03 ± 0.23), and its coherence decreased gradually from the luminal to the abluminal tissue layers (inner media, b=1.54 ± 0.40; outer media, b=0.72 ± 0.20). In contrast, the collagen in the adventitia was aligned almost isotropically (bA=0.27 ± 0.11), and no features, such as families of coherent fibers, were identified. The applied constitutive model captured the aorta biaxial properties accurately (coefficient of determination R(2)=0.95 ± 0.03) over the entire range of biaxial deformations and with physically meaningful model parameters. Good predictive properties, well outside the parameter identification space, were observed (R(2)=0.92 ± 0.04). Multi-scale constitutive models equipped with realistic micro-histological data can predict macroscopic non-linear aorta wall properties. Collagen largely defines already low strain properties of media, which explains the origin of wall anisotropy seen at this strain level. The structure and mechanical
Prediction of Stream Flow in Ungauged Basins - a Comprehensive Framework
NASA Astrophysics Data System (ADS)
Ganti, R.; Agarwal, V.; Shetty, A.
2012-12-01
It is well established that critical information on stream-flow is essential in reducing uncertainties in planning and design of various water resource projects. Lack of data, at the desired spatial and temporal resolution, poses an enormous challenge in developing meaningful prediction models. Powerful techniques like Artificial Neural Network (ANN) modeling provide reasonably accurate prediction models, however development of such models require substantial amount of past data. Currently, empirical equations developed across the span of several hundred years are used on a regionalized basis. These equations are usually very simple, allowing for easy application, however not very accurate. This limited accuracy can be attributed to the use of noisy data and inclusion of only limited stream-flow variables. This study is an attempt to process noisy data and incorporate catchment variables to improve the accuracy of existing relationships whilst maintaining their simplicity. This study presents a comprehensive framework starting from data-processing to data-analysis that enables the development of regionalized empirical equations. A case-study has been presented for the sub-basins in "Dakshina Kannada" (Coastal Karnataka, India). Firstly, the data has first been processed to remove any outliers and estimate missing values, by replacing missing values with the average values of the neighboring entries for discrete data-sets or by using Least Square principles (LS) for continuously distributed date. Secondly, the existing models have been improved based on the processed dataset obtained through Exploratory Data Analysis (EDA). Further, utilizing Principal Component Analysis (PCA) other important parameters have been identified. All these parameters have then been included to arrive at an "improved regionalized relationship". Finally, the improved regionalized relationships have been evaluated for their performance based on the Correlation Coefficient and Standard Error
NASA Astrophysics Data System (ADS)
Powell, Jacob; Heider, Emily C.; Campiglia, Andres; Harper, James K.
2016-10-01
The ability of density functional theory (DFT) methods to predict accurate fluorescence spectra for polycyclic aromatic hydrocarbons (PAHs) is explored. Two methods, PBE0 and CAM-B3LYP, are evaluated both in the gas phase and in solution. Spectra for several of the most toxic PAHs are predicted and compared to experiment, including three isomers of C24H14 and a PAH containing heteroatoms. Unusually high-resolution experimental spectra are obtained for comparison by analyzing each PAH at 4.2 K in an n-alkane matrix. All theoretical spectra visually conform to the profiles of the experimental data but are systematically offset by a small amount. Specifically, when solvent is included the PBE0 functional overestimates peaks by 16.1 ± 6.6 nm while CAM-B3LYP underestimates the same transitions by 14.5 ± 7.6 nm. These calculated spectra can be empirically corrected to decrease the uncertainties to 6.5 ± 5.1 and 5.7 ± 5.1 nm for the PBE0 and CAM-B3LYP methods, respectively. A comparison of computed spectra in the gas phase indicates that the inclusion of n-octane shifts peaks by +11 nm on average and this change is roughly equivalent for PBE0 and CAM-B3LYP. An automated approach for comparing spectra is also described that minimizes residuals between a given theoretical spectrum and all available experimental spectra. This approach identifies the correct spectrum in all cases and excludes approximately 80% of the incorrect spectra, demonstrating that an automated search of theoretical libraries of spectra may eventually become feasible.
Wong, Florence; O’Leary, Jacqueline G; Reddy, K Rajender; Patton, Heather; Kamath, Patrick S; Fallon, Michael B; Garcia-Tsao, Guadalupe; Subramanian, Ram M.; Malik, Raza; Maliakkal, Benedict; Thacker, Leroy R; Bajaj, Jasmohan S
2015-01-01
Background & Aims A consensus conference proposed that cirrhosis-associated acute kidney injury (AKI) be defined as an increase in serum creatinine by >50% from the stable baseline value in <6 months or by ≥0.3mg/dL in <48 hrs. We prospectively evaluated the ability of these criteria to predict mortality within 30 days among hospitalized patients with cirrhosis and infection. Methods 337 patients with cirrhosis admitted with or developed an infection in hospital (56% men; 56±10 y old; model for end-stage liver disease score, 20±8) were followed. We compared data on 30-day mortality, hospital length-of-stay, and organ failure between patients with and without AKI. Results 166 (49%) developed AKI during hospitalization, based on the consensus criteria. Patients who developed AKI had higher admission Child-Pugh (11.0±2.1 vs 9.6±2.1; P<.0001), and MELD scores (23±8 vs17±7; P<.0001), and lower mean arterial pressure (81±16mmHg vs 85±15mmHg; P<.01) than those who did not. Also higher amongst patients with AKI were mortality in ≤30 days (34% vs 7%), intensive care unit transfer (46% vs 20%), ventilation requirement (27% vs 6%), and shock (31% vs 8%); AKI patients also had longer hospital stays (17.8±19.8 days vs 13.3±31.8 days) (all P<.001). 56% of AKI episodes were transient, 28% persistent, and 16% resulted in dialysis. Mortality was 80% among those without renal recovery, higher compared to partial (40%) or complete recovery (15%), or AKI-free patients (7%; P<.0001). Conclusions 30-day mortality is 10-fold higher among infected hospitalized cirrhotic patients with irreversible AKI than those without AKI. The consensus definition of AKI accurately predicts 30-day mortality, length of hospital stay, and organ failure. PMID:23999172
Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A
2015-09-18
Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).
Cluster abundance in chameleon f(R) gravity I: toward an accurate halo mass function prediction
NASA Astrophysics Data System (ADS)
Cataneo, Matteo; Rapetti, David; Lombriser, Lucas; Li, Baojiu
2016-12-01
We refine the mass and environment dependent spherical collapse model of chameleon f(R) gravity by calibrating a phenomenological correction inspired by the parameterized post-Friedmann framework against high-resolution N-body simulations. We employ our method to predict the corresponding modified halo mass function, and provide fitting formulas to calculate the enhancement of the f(R) halo abundance with respect to that of General Relativity (GR) within a precision of lesssim 5% from the results obtained in the simulations. Similar accuracy can be achieved for the full f(R) mass function on the condition that the modeling of the reference GR abundance of halos is accurate at the percent level. We use our fits to forecast constraints on the additional scalar degree of freedom of the theory, finding that upper bounds competitive with current Solar System tests are within reach of cluster number count analyses from ongoing and upcoming surveys at much larger scales. Importantly, the flexibility of our method allows also for this to be applied to other scalar-tensor theories characterized by a mass and environment dependent spherical collapse.
Accurate prediction of band gaps and optical properties of HfO2
NASA Astrophysics Data System (ADS)
Ondračka, Pavel; Holec, David; Nečas, David; Zajíčková, Lenka
2016-10-01
We report on optical properties of various polymorphs of hafnia predicted within the framework of density functional theory. The full potential linearised augmented plane wave method was employed together with the Tran-Blaha modified Becke-Johnson potential (TB-mBJ) for exchange and local density approximation for correlation. Unit cells of monoclinic, cubic and tetragonal crystalline, and a simulated annealing-based model of amorphous hafnia were fully relaxed with respect to internal positions and lattice parameters. Electronic structures and band gaps for monoclinic, cubic, tetragonal and amorphous hafnia were calculated using three different TB-mBJ parametrisations and the results were critically compared with the available experimental and theoretical reports. Conceptual differences between a straightforward comparison of experimental measurements to a calculated band gap on the one hand and to a whole electronic structure (density of electronic states) on the other hand, were pointed out, suggesting the latter should be used whenever possible. Finally, dielectric functions were calculated at two levels, using the random phase approximation without local field effects and with a more accurate Bethe-Salpether equation (BSE) to account for excitonic effects. We conclude that a satisfactory agreement with experimental data for HfO2 was obtained only in the latter case.
Accurate prediction of V1 location from cortical folds in a surface coordinate system
Hinds, Oliver P.; Rajendran, Niranjini; Polimeni, Jonathan R.; Augustinack, Jean C.; Wiggins, Graham; Wald, Lawrence L.; Rosas, H. Diana; Potthast, Andreas; Schwartz, Eric L.; Fischl, Bruce
2008-01-01
Previous studies demonstrated substantial variability of the location of primary visual cortex (V1) in stereotaxic coordinates when linear volume-based registration is used to match volumetric image intensities (Amunts et al., 2000). However, other qualitative reports of V1 location (Smith, 1904; Stensaas et al., 1974; Rademacher et al., 1993) suggested a consistent relationship between V1 and the surrounding cortical folds. Here, the relationship between folds and the location of V1 is quantified using surface-based analysis to generate a probabilistic atlas of human V1. High-resolution (about 200 μm) magnetic resonance imaging (MRI) at 7 T of ex vivo human cerebral hemispheres allowed identification of the full area via the stria of Gennari: a myeloarchitectonic feature specific to V1. Separate, whole-brain scans were acquired using MRI at 1.5 T to allow segmentation and mesh reconstruction of the cortical gray matter. For each individual, V1 was manually identified in the high-resolution volume and projected onto the cortical surface. Surface-based intersubject registration (Fischl et al., 1999b) was performed to align the primary cortical folds of individual hemispheres to those of a reference template representing the average folding pattern. An atlas of V1 location was constructed by computing the probability of V1 inclusion for each cortical location in the template space. This probabilistic atlas of V1 exhibits low prediction error compared to previous V1 probabilistic atlases built in volumetric coordinates. The increased predictability observed under surface-based registration suggests that the location of V1 is more accurately predicted by the cortical folds than by the shape of the brain embedded in the volume of the skull. In addition, the high quality of this atlas provides direct evidence that surface-based intersubject registration methods are superior to volume-based methods at superimposing functional areas of cortex, and therefore are better
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.
NASA Astrophysics Data System (ADS)
Ko, P.; Kurosawa, S.
2014-03-01
The understanding and accurate prediction of the flow behaviour related to cavitation and pressure fluctuation in a Kaplan turbine are important to the design work enhancing the turbine performance including the elongation of the operation life span and the improvement of turbine efficiency. In this paper, high accuracy turbine and cavitation performance prediction method based on entire flow passage for a Kaplan turbine is presented and evaluated. Two-phase flow field is predicted by solving Reynolds-Averaged Navier-Stokes equations expressed by volume of fluid method tracking the free surface and combined with Reynolds Stress model. The growth and collapse of cavitation bubbles are modelled by the modified Rayleigh-Plesset equation. The prediction accuracy is evaluated by comparing with the model test results of Ns 400 Kaplan model turbine. As a result that the experimentally measured data including turbine efficiency, cavitation performance, and pressure fluctuation are accurately predicted. Furthermore, the cavitation occurrence on the runner blade surface and the influence to the hydraulic loss of the flow passage are discussed. Evaluated prediction method for the turbine flow and performance is introduced to facilitate the future design and research works on Kaplan type turbine.
Bowler, Michael G.
2017-01-01
The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111–114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult’s law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult’s law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult’s law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample. PMID:28381983
Bowler, Michael G; Bowler, David R; Bowler, Matthew W
2017-04-01
The humidity surrounding a sample is an important variable in scientific experiments. Biological samples in particular require not just a humid atmosphere but often a relative humidity (RH) that is in equilibrium with a stabilizing solution required to maintain the sample in the same state during measurements. The controlled dehydration of macromolecular crystals can lead to significant increases in crystal order, leading to higher diffraction quality. Devices that can accurately control the humidity surrounding crystals while monitoring diffraction have led to this technique being increasingly adopted, as the experiments become easier and more reproducible. Matching the RH to the mother liquor is the first step in allowing the stable mounting of a crystal. In previous work [Wheeler, Russi, Bowler & Bowler (2012). Acta Cryst. F68, 111-114], the equilibrium RHs were measured for a range of concentrations of the most commonly used precipitants in macromolecular crystallography and it was shown how these related to Raoult's law for the equilibrium vapour pressure of water above a solution. However, a discrepancy between the measured values and those predicted by theory could not be explained. Here, a more precise humidity control device has been used to determine equilibrium RH points. The new results are in agreement with Raoult's law. A simple argument in statistical mechanics is also presented, demonstrating that the equilibrium vapour pressure of a solvent is proportional to its mole fraction in an ideal solution: Raoult's law. The same argument can be extended to the case where the solvent and solute molecules are of different sizes, as is the case with polymers. The results provide a framework for the correct maintenance of the RH surrounding a sample.
Solid rocket booster internal flow analysis by highly accurate adaptive computational methods
NASA Technical Reports Server (NTRS)
Huang, C. Y.; Tworzydlo, W.; Oden, J. T.; Bass, J. M.; Cullen, C.; Vadaketh, S.
1991-01-01
The primary objective of this project was to develop an adaptive finite element flow solver for simulating internal flows in the solid rocket booster. Described here is a unique flow simulator code for analyzing highly complex flow phenomena in the solid rocket booster. New methodologies and features incorporated into this analysis tool are described.
CFD and PTV steady flow investigation in an anatomically accurate abdominal aortic aneurysm.
Boutsianis, Evangelos; Guala, Michele; Olgac, Ufuk; Wildermuth, Simon; Hoyer, Klaus; Ventikos, Yiannis; Poulikakos, Dimos
2009-01-01
There is considerable interest in computational and experimental flow investigations within abdominal aortic aneurysms (AAAs). This task stipulates advanced grid generation techniques and cross-validation because of the anatomical complexity. The purpose of this study is to examine the feasibility of velocity measurements by particle tracking velocimetry (PTV) in realistic AAA models. Computed tomography and rapid prototyping were combined to digitize and construct a silicone replica of a patient-specific AAA. Three-dimensional velocity measurements were acquired using PTV under steady averaged resting boundary conditions. Computational fluid dynamics (CFD) simulations were subsequently carried out with identical boundary conditions. The computational grid was created by splitting the luminal volume into manifold and nonmanifold subsections. They were filled with tetrahedral and hexahedral elements, respectively. Grid independency was tested on three successively refined meshes. Velocity differences of about 1% in all three directions existed mainly within the AAA sack. Pressure revealed similar variations, with the sparser mesh predicting larger values. PTV velocity measurements were taken along the abdominal aorta and showed good agreement with the numerical data. The results within the aneurysm neck and sack showed average velocity variations of about 5% of the mean inlet velocity. The corresponding average differences increased for all velocity components downstream the iliac bifurcation to as much as 15%. The two domains differed slightly due to flow-induced forces acting on the silicone model. Velocity quantification through narrow branches was problematic due to decreased signal to noise ratio at the larger local velocities. Computational wall pressure and shear fields are also presented. The agreement between CFD simulations and the PTV experimental data was confirmed by three-dimensional velocity comparisons at several locations within the investigated AAA
Peak power prediction of a vanadium redox flow battery
NASA Astrophysics Data System (ADS)
Yu, V. K.; Chen, D.
2014-12-01
The vanadium redox flow battery (VRFB) is a promising grid-scale energy storage technology, but future widespread commercialization requires a considerable reduction in capital costs. Determining the appropriate battery size for the intended power range can help minimize the amount of materials needed, thereby reducing capital costs. A physics-based model is an essential tool for predicting the power range of large scale VRFB systems to aid in the design optimization process. This paper presents a modeling framework that accounts for the effects of flow rate on the pumping losses, local mass transfer rate, and nonuniform vanadium concentration in the cell. The resulting low-order model captures battery performance accurately even at high power densities and remains computationally practical for stack-level optimization and control purposes. We first use the model to devise an optimal control strategy that maximizes battery life during discharge. Assuming optimal control is implemented, we then determine the upper efficiency limits of a given VRFB system and compare the net power and associated overpotential and pumping losses at different operating points. We also investigate the effects of varying the electrode porosity, stack temperature, and total vanadium concentration on the peak power.
Two-phase flow regime map predictions under microgravity
Karri, S.B.R.; Mathur, V.K.
1988-01-01
In this paper, the widely used models of Taitel-Dukler and Weisman et al. are extrapolated to microgravity levels to compare predicted flow pattern boundaries for horizontal and vertical flows. Efforts have been made to analyze how the two-phase flow models available in the literature predict flow regime transitions in microgravity. The models of Taitel-Dukler and Weisman et al. have been found to be more suitable for extrapolation to a wide range of system parameters than the other two-phase flow regime maps available in the literature. The original criteria for all cases are used to predict the transition lines, except for the transition to dispersed flow regime in case of the Weisman model for horizontal flow. The constant 0.97 on the righthand side of this correlation should be two times that value, i.e., 1.94, in order to match this transition line in their original paper.
NASA Astrophysics Data System (ADS)
Stukel, Michael R.; Landry, Michael R.; Ohman, Mark D.; Goericke, Ralf; Samo, Ty; Benitez-Nelson, Claudia R.
2012-03-01
Despite the increasing use of linear inverse modeling techniques to elucidate fluxes in undersampled marine ecosystems, the accuracy with which they estimate food web flows has not been resolved. New Markov Chain Monte Carlo (MCMC) solution methods have also called into question the biases of the commonly used L2 minimum norm (L 2MN) solution technique. Here, we test the abilities of MCMC and L 2MN methods to recover field-measured ecosystem rates that are sequentially excluded from the model input. For data, we use experimental measurements from process cruises of the California Current Ecosystem (CCE-LTER) Program that include rate estimates of phytoplankton and bacterial production, micro- and mesozooplankton grazing, and carbon export from eight study sites varying from rich coastal upwelling to offshore oligotrophic conditions. Both the MCMC and L 2MN methods predicted well-constrained rates of protozoan and mesozooplankton grazing with reasonable accuracy, but the MCMC method overestimated primary production. The MCMC method more accurately predicted the poorly constrained rate of vertical carbon export than the L 2MN method, which consistently overestimated export. Results involving DOC and bacterial production were equivocal. Overall, when primary production is provided as model input, the MCMC method gives a robust depiction of ecosystem processes. Uncertainty in inverse ecosystem models is large and arises primarily from solution under-determinacy. We thus suggest that experimental programs focusing on food web fluxes expand the range of experimental measurements to include the nature and fate of detrital pools, which play large roles in the model.
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
NASA Technical Reports Server (NTRS)
Wilmoth, R. G.
1982-01-01
A viscous-inviscid interaction method to calculate the subsonic and transonic flow over nozzle afterbodies with supersonic jet exhausts was developed. The method iteratively combines a relaxation solution of the full potential equation for the inviscid external flow, a shock capturing-shock fitting inviscid jet solution, an integral boundary layer solution, a control volume method for treating separated flows, and an overlaid mixing layer solution. A computer program called RAXJET which incorporates the method, illustrates the predictive capabilities of the method by comparison with experimental data is described, a user's guide to the computer program is provided. The method accurately predicts afterbody pressures, drag, and flow field properties for attached and separated flows for which no shock induced separation occurs.
Margot Gerritsen
2008-10-31
Gas-injection processes are widely and increasingly used for enhanced oil recovery (EOR). In the United States, for example, EOR production by gas injection accounts for approximately 45% of total EOR production and has tripled since 1986. The understanding of the multiphase, multicomponent flow taking place in any displacement process is essential for successful design of gas-injection projects. Due to complex reservoir geometry, reservoir fluid properties and phase behavior, the design of accurate and efficient numerical simulations for the multiphase, multicomponent flow governing these processes is nontrivial. In this work, we developed, implemented and tested a streamline based solver for gas injection processes that is computationally very attractive: as compared to traditional Eulerian solvers in use by industry it computes solutions with a computational speed orders of magnitude higher and a comparable accuracy provided that cross-flow effects do not dominate. We contributed to the development of compositional streamline solvers in three significant ways: improvement of the overall framework allowing improved streamline coverage and partial streamline tracing, amongst others; parallelization of the streamline code, which significantly improves wall clock time; and development of new compositional solvers that can be implemented along streamlines as well as in existing Eulerian codes used by industry. We designed several novel ideas in the streamline framework. First, we developed an adaptive streamline coverage algorithm. Adding streamlines locally can reduce computational costs by concentrating computational efforts where needed, and reduce mapping errors. Adapting streamline coverage effectively controls mass balance errors that mostly result from the mapping from streamlines to pressure grid. We also introduced the concept of partial streamlines: streamlines that do not necessarily start and/or end at wells. This allows more efficient coverage and avoids
Prediction of unsteady loads on maneuvering delta wings using time-accurate Euler schemes
NASA Technical Reports Server (NTRS)
Kandil, Osama A.; Chuang, H. Andrew
1988-01-01
Three-dimensional steady and unsteady vortex-dominated flows around sharp-edged delta wings are considered in this paper. The problem is formulated by using the unsteady conservative Euler equations for the flow relative motion with respect to a moving frame of reference. An implicit approximately-factored finite volume scheme is used to solve the resulting equations on a three-dimensional computational grid which is generated by using a modified Joukowski transformation in cross-flow planes at the grid chord stations. The scheme is applied to a delta wing undergoing pitching oscillation around a large angle of attack. The initial conditions correspond to a steady flow around a delta wing of aspect ratio of one, freestream Mach number of 0.3 and mean angle of attack of 20.5. The steady flow results are compared with those of an explicit computational scheme and the experimental data, and they are in good agreement.
Towards more accurate wind and solar power prediction by improving NWP model physics
NASA Astrophysics Data System (ADS)
Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo
2014-05-01
The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during
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.
Cold flow properties of biodiesel: A guide to getting an accurate analysis
Technology Transfer Automated Retrieval System (TEKTRAN)
Biodiesel has several advantages compared to conventional diesel fuel (petrodiesel). Nevertheless, biodiesel has poor cold flow properties that may restrict its use in moderate climates. It is essential that the cold flow properties of biodiesel and its blends with petrodiesel be measured as accurat...
Prediction of Hydrodynamics for Unidirectional Flow
2009-01-01
representation of the flow field can be obtained. These methods have also recently been used to correct initial estimates of model parameters (e.g. Losa et...estimation for stochastic systems. Non-linear Processes in Geophysics, 10, 253. Losa , S., Kivman, G., Ryabchenko, V., 2001, Weak constraint parameter
A machine learning approach to the accurate prediction of multi-leaf collimator positional errors
NASA Astrophysics Data System (ADS)
Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon
2016-03-01
Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD = 1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be
Wang, Jia-Nan; Jin, Jun-Ling; Geng, Yun; Sun, Shi-Ling; Xu, Hong-Liang; Lu, Ying-Hua; Su, Zhong-Min
2013-03-15
Recently, the extreme learning machine neural network (ELMNN) as a valid computing method has been proposed to predict the nonlinear optical property successfully (Wang et al., J. Comput. Chem. 2012, 33, 231). In this work, first, we follow this line of work to predict the electronic excitation energies using the ELMNN method. Significantly, the root mean square deviation of the predicted electronic excitation energies of 90 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY) derivatives between the predicted and experimental values has been reduced to 0.13 eV. Second, four groups of molecule descriptors are considered when building the computing models. The results show that the quantum chemical descriptions have the closest intrinsic relation with the electronic excitation energy values. Finally, a user-friendly web server (EEEBPre: Prediction of electronic excitation energies for BODIPY dyes), which is freely accessible to public at the web site: http://202.198.129.218, has been built for prediction. This web server can return the predicted electronic excitation energy values of BODIPY dyes that are high consistent with the experimental values. We hope that this web server would be helpful to theoretical and experimental chemists in related research.
Sensor data fusion for accurate cloud presence prediction using Dempster-Shafer evidence theory.
Li, Jiaming; Luo, Suhuai; Jin, Jesse S
2010-01-01
Sensor data fusion technology can be used to best extract useful information from multiple sensor observations. It has been widely applied in various applications such as target tracking, surveillance, robot navigation, signal and image processing. This paper introduces a novel data fusion approach in a multiple radiation sensor environment using Dempster-Shafer evidence theory. The methodology is used to predict cloud presence based on the inputs of radiation sensors. Different radiation data have been used for the cloud prediction. The potential application areas of the algorithm include renewable power for virtual power station where the prediction of cloud presence is the most challenging issue for its photovoltaic output. The algorithm is validated by comparing the predicted cloud presence with the corresponding sunshine occurrence data that were recorded as the benchmark. Our experiments have indicated that comparing to the approaches using individual sensors, the proposed data fusion approach can increase correct rate of cloud prediction by ten percent, and decrease unknown rate of cloud prediction by twenty three percent.
Accurate and robust methods for variable density incompressible flows with discontinuities
Rider, W.J.; Kothe, D.B.; Puckett, E.G.
1996-09-01
We are interested in the solution of incompressible flows which are characterized by large density variations, interfacial physics, arbitrary material topologies and strong vortical content. The issues present in constant density incompressible flow are exacerbated by the presence of density discontinuities. A much greater premium requirement is placed the positivity of computed quantities The mechanism of baroclinc vorticity generation exists ({gradient}p x {gradient}p) to further complicate the physics.
Tuning-free controller to accurately regulate flow rates in a microfluidic network
Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun
2016-01-01
We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework. PMID:26987587
Tuning-free controller to accurately regulate flow rates in a microfluidic network
NASA Astrophysics Data System (ADS)
Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun
2016-03-01
We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework.
Tuning-free controller to accurately regulate flow rates in a microfluidic network.
Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun
2016-03-18
We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework.
Predictions of bubbly flows in vertical pipes using two-fluid models in CFDS-FLOW3D code
Banas, A.O.; Carver, M.B.; Unrau, D.
1995-09-01
This paper reports the results of a preliminary study exploring the performance of two sets of two-fluid closure relationships applied to the simulation of turbulent air-water bubbly upflows through vertical pipes. Predictions obtained with the default CFDS-FLOW3D model for dispersed flows were compared with the predictions of a new model (based on the work of Lee), and with the experimental data of Liu. The new model, implemented in the CFDS-FLOW3D code, included additional source terms in the {open_quotes}standard{close_quotes} {kappa}-{epsilon} transport equations for the liquid phase, as well as modified model coefficients and wall functions. All simulations were carried out in a 2-D axisymmetric format, collapsing the general multifluid framework of CFDS-FLOW3D to the two-fluid (air-water) case. The newly implemented model consistently improved predictions of radial-velocity profiles of both phases, but failed to accurately reproduce the experimental phase-distribution data. This shortcoming was traced to the neglect of anisotropic effects in the modelling of liquid-phase turbulence. In this sense, the present investigation should be considered as the first step toward the ultimate goal of developing a theoretically sound and universal CFD-type two-fluid model for bubbly flows in channels.
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.
NASA Astrophysics Data System (ADS)
Brunker, J.; Beard, P.
2014-03-01
An assessment has been made of various experimental factors affecting the accuracy of flow velocities measured using a pulsed time correlation photoacoustic Doppler technique. In this method, Doppler time shifts are quantified via crosscorrelation of pairs of photoacoustic waveforms generated in moving absorbers using pairs of laser light pulses, and the photoacoustic waves are detected using an ultrasound transducer. The acoustic resolution mode is employed by using the transducer focal width, rather than the large illuminated volume, to define the lateral spatial resolution. This enables penetration depths of several millimetres or centimetres, unlike methods using the optical resolution mode, which limits the maximum penetration depth to approximately 1 mm. In the acoustic resolution mode, it is difficult to detect time shifts in highly concentrated suspensions of flowing absorbers, such as red blood cell suspensions and whole blood, and this challenge supposedly arises because of the lack of spatial heterogeneity. However, by assessing the effect of different absorption coefficients and tube diameters, we offer an alternative explanation relating to light attenuation and parabolic flow. We also demonstrate a new signal processing method that surmounts the previous problem of measurement under-reading. This method is a form of signal range gating and enables mapping of the flow velocity profile across the tube as well as measurement of the average flow velocity. We show that, using our signal processing scheme, it is possible to measure the flow of whole blood using a relatively low frequency detector. This important finding paves the way for application of the technique to measurements of blood flow several centimetres deep in living tissue.
NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.
Kosugi, Shunichi; Yanagawa, Hiroshi; Terauchi, Ryohei; Tabata, Satoshi
2014-09-01
The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs) in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS). Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.
Kim, Minseung; Rai, Navneet; Zorraquino, Violeta; Tagkopoulos, Ilias
2016-01-01
A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a consistent, quality-controlled multi-omics compendium for Escherichia coli with cohesive meta-data information. We then use this resource to train a multi-scale model that integrates four omics layers to predict genome-wide concentrations and growth dynamics. The genetic and environmental ontology reconstructed from the omics data is substantially different and complementary to the genetic and chemical ontologies. The integration of different layers confers an incremental increase in the prediction performance, as does the information about the known gene regulatory and protein-protein interactions. The predictive performance of the model ranges from 0.54 to 0.87 for the various omics layers, which far exceeds various baselines. This work provides an integrative framework of omics-driven predictive modelling that is broadly applicable to guide biological discovery. PMID:27713404
Modeling Tools Predict Flow in Fluid Dynamics
NASA Technical Reports Server (NTRS)
2010-01-01
"Because rocket engines operate under extreme temperature and pressure, they present a unique challenge to designers who must test and simulate the technology. To this end, CRAFT Tech Inc., of Pipersville, Pennsylvania, won Small Business Innovation Research (SBIR) contracts from Marshall Space Flight Center to develop software to simulate cryogenic fluid flows and related phenomena. CRAFT Tech enhanced its CRUNCH CFD (computational fluid dynamics) software to simulate phenomena in various liquid propulsion components and systems. Today, both government and industry clients in the aerospace, utilities, and petrochemical industries use the software for analyzing existing systems as well as designing new ones."
NASA Astrophysics Data System (ADS)
Dale, Andy; Stolpovsky, Konstantin; Wallmann, Klaus
2016-04-01
The recycling and burial of biogenic material in the sea floor plays a key role in the regulation of ocean chemistry. Proper consideration of these processes in ocean biogeochemical models is becoming increasingly recognized as an important step in model validation and prediction. However, the rate of organic matter remineralization in sediments and the benthic flux of redox-sensitive elements are difficult to predict a priori. In this communication, examples of empirical benthic flux models that can be coupled to earth system models to predict sediment-water exchange in the open ocean are presented. Large uncertainties hindering further progress in this field include knowledge of the reactivity of organic carbon reaching the sediment, the importance of episodic variability in bottom water chemistry and particle rain rates (for both the deep-sea and margins) and the role of benthic fauna. How do we meet the challenge?
Koot, Yvonne E. M.; van Hooff, Sander R.; Boomsma, Carolien M.; van Leenen, Dik; Groot Koerkamp, Marian J. A.; Goddijn, Mariëtte; Eijkemans, Marinus J. C.; Fauser, Bart C. J. M.; Holstege, Frank C. P.; Macklon, Nick S.
2016-01-01
The primary limiting factor for effective IVF treatment is successful embryo implantation. Recurrent implantation failure (RIF) is a condition whereby couples fail to achieve pregnancy despite consecutive embryo transfers. Here we describe the collection of gene expression profiles from mid-luteal phase endometrial biopsies (n = 115) from women experiencing RIF and healthy controls. Using a signature discovery set (n = 81) we identify a signature containing 303 genes predictive of RIF. Independent validation in 34 samples shows that the gene signature predicts RIF with 100% positive predictive value (PPV). The strength of the RIF associated expression signature also stratifies RIF patients into distinct groups with different subsequent implantation success rates. Exploration of the expression changes suggests that RIF is primarily associated with reduced cellular proliferation. The gene signature will be of value in counselling and guiding further treatment of women who fail to conceive upon IVF and suggests new avenues for developing intervention. PMID:26797113
Use of flow cytometry for rapid and accurate enumeration of live pathogenic Leptospira strains.
Fontana, Célia; Crussard, Steve; Simon-Dufay, Nathalie; Pialot, Daniel; Bomchil, Natalia; Reyes, Jean
2017-01-01
Enumeration of Leptospira, the causative agent of leptospirosis, is arduous mainly because of its slow growth rate. Rapid and reliable tools for numbering leptospires are still lacking. The current standard for Leptospira cultures is the count on Petroff-Hausser chamber under dark-field microscopy, but this method remains time-consuming, requires well-trained operators and lacks reproducibility. Here we present the development of a flow-cytometry technique for counting leptospires. We showed that upon addition of fluorescent dyes, necessary to discriminate the bacterial population from debris, several live Leptospira strains could be enumerated at different physiologic states. Flow cytometry titers were highly correlated to counts with Petroff-Hausser chambers (R(2)>0.99). Advantages of flow cytometry lie in its rapidity, its reproducibility significantly higher than Petroff-Hausser method and its wide linearity range, from 10(4) to 10(8)leptospires/ml. Therefore, flow cytometry is a fast, reproducible and sensitive tool representing a promising technology to replace current enumeration techniques of Leptospira in culture. We were also able to enumerate Leptospira in artificially infected urine and blood with a sensitivity limit of 10(5)leptospires/ml and 10(6)leptospires/ml, respectively, demonstrating the feasibility to use flow cytometry as first-line tool for diagnosis or bacterial dissemination studies.
Time-Accurate Computation of Viscous Flow Around Deforming Bodies Using Overset Grids
Fast, P; Henshaw, W D
2001-04-02
Dynamically evolving boundaries and deforming bodies interacting with a flow are commonly encountered in fluid dynamics. However, the numerical simulation of flows with dynamic boundaries is difficult with current methods. We propose a new method for studying such problems. The key idea is to use the overset grid method with a thin, body-fitted grid near the deforming boundary, while using fixed Cartesian grids to cover most of the computational domain. Our approach combines the strengths of earlier moving overset grid methods for rigid body motion, and unstructured grid methods for Aow-structure interactions. Large scale deformation of the flow boundaries can be handled without a global regridding, and in a computationally efficient way. In terms of computational cost, even a full overset grid regridding is significantly cheaper than a full regridding of an unstructured grid for the same domain, especially in three dimensions. Numerical studies are used to verify accuracy and convergence of our flow solver. As a computational example, we consider two-dimensional incompressible flow past a flexible filament with prescribed dynamics.
Victora, Andrea; Möller, Heiko M.; Exner, Thomas E.
2014-01-01
NMR chemical shift predictions based on empirical methods are nowadays indispensable tools during resonance assignment and 3D structure calculation of proteins. However, owing to the very limited statistical data basis, such methods are still in their infancy in the field of nucleic acids, especially when non-canonical structures and nucleic acid complexes are considered. Here, we present an ab initio approach for predicting proton chemical shifts of arbitrary nucleic acid structures based on state-of-the-art fragment-based quantum chemical calculations. We tested our prediction method on a diverse set of nucleic acid structures including double-stranded DNA, hairpins, DNA/protein complexes and chemically-modified DNA. Overall, our quantum chemical calculations yield highly/very accurate predictions with mean absolute deviations of 0.3–0.6 ppm and correlation coefficients (r2) usually above 0.9. This will allow for identifying misassignments and validating 3D structures. Furthermore, our calculations reveal that chemical shifts of protons involved in hydrogen bonding are predicted significantly less accurately. This is in part caused by insufficient inclusion of solvation effects. However, it also points toward shortcomings of current force fields used for structure determination of nucleic acids. Our quantum chemical calculations could therefore provide input for force field optimization. PMID:25404135
Predicting the temporal variation of flow contributing areas using SWAT
NASA Astrophysics Data System (ADS)
Golmohammadi, Golmar; Rudra, Ramesh; Dickinson, Trevor; Goel, Pradeep; Veliz, Mari
2017-04-01
This study assessed the capability of soil and water assessment tool (SWAT) to identify areas contributing to flow in the Gully Creek Watershed in Ontario. The SWAT model predicted the streamflow at the outlet of the watershed, with monthly and daily Nash-Sutcliffe efficiencies of 0.75 and 0.60 during the validation period. In addition to the daily streamflow data, the flow was also observed at 16 monitoring stations during 6 different events. The validated model was then used to simulate flow at the monitoring stations. The effect of watershed delineation on streamflow and events at 16 monitoring station were then examined by SWAT. The delineation of 99 subbasins, with highest efficiency was selected for the purpose of predicting the potential flow contributing areas with the model. Overall, the flow events were overestimated by SWAT. Temporal variations in the potential flow contributing areas during each event were then analyzed. Flow contributing areas during each event was predicted by the model first and the results showed a good agreement with available information. A current precipitation index was used to simulate the continuous change of soil water content during each rainstorm, and the modeling results of the individual events were used to explore the capability of the model to predict the temporal variation of flow contributing areas during each event. The results revealed that the SWAT model over-predicted the areas contributing flow for events with lower rainfall; while for the events with higher rainfall amount the model closely simulated the time-varying contributing area. The results of this study provide some insight into the possible capability of SWAT model to predict the temporal variations in potential contributing area, and therefore provide an important contribution to the modeling of runoff generation in watersheds, a vital aspect in the evaluation and planning of best management practices.
Debris flow hazards mitigation--Mechanics, prediction, and assessment
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.
Dynamics of Flexible MLI-type Debris for Accurate Orbit Prediction
2014-09-01
SUBJECT TERMS EOARD, orbital debris , HAMR objects, multi-layered insulation, orbital dynamics, orbit predictions, orbital propagation 16. SECURITY...illustration are orbital debris [Souce: NASA...piece of space junk (a paint fleck) during the STS-7 mission (Photo: NASA Orbital Debris Program Office
Stempler, Shiri; Waldman, Yedael Y; Wolf, Lior; Ruppin, Eytan
2012-09-01
Numerous metabolic alterations are associated with the impairment of brain cells in Alzheimer's disease (AD). Here we use gene expression microarrays of both whole hippocampus tissue and hippocampal neurons of AD patients to investigate the ability of metabolic gene expression to predict AD progression and its cognitive decline. We find that the prediction accuracy of different AD stages is markedly higher when using neuronal expression data (0.9) than when using whole tissue expression (0.76). Furthermore, the metabolic genes' expression is shown to be as effective in predicting AD severity as the entire gene list. Remarkably, a regression model from hippocampal metabolic gene expression leads to a marked correlation of 0.57 with the Mini-Mental State Examination cognitive score. Notably, the expression of top predictive neuronal genes in AD is significantly higher than that of other metabolic genes in the brains of healthy subjects. All together, the analyses point to a subset of metabolic genes that is strongly associated with normal brain functioning and whose disruption plays a major role in AD.
Predicting repeat self-harm in children--how accurate can we expect to be?
Chitsabesan, Prathiba; Harrington, Richard; Harrington, Valerie; Tomenson, Barbara
2003-01-01
The main objective of the study was to find which variables predict repetition of deliberate self-harm in children. The study is based on a group of children who took part in a randomized control trial investigating the effects of a home-based family intervention for children who had deliberately poisoned themselves. These children had a range of baseline and outcome measures collected on two occasions (two and six months follow-up). Outcome data were collected from 149 (92 %) of the initial 162 children over the six months. Twenty-three children made a further deliberate self-harm attempt within the follow-up period. A number of variables at baseline were found to be significantly associated with repeat self-harm. Parental mental health and a history of previous attempts were the strongest predictors. A model of prediction of further deliberate self-harm combining these significant individual variables produced a high positive predictive value (86 %) but had low sensitivity (28 %). Predicting repeat self-harm in children is difficult, even with a comprehensive series of assessments over multiple time points, and we need to adapt services with this in mind. We propose a model of service provision which takes these findings into account.
Predicting Rediated Noise With Power Flow Finite Element Analysis
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
An innovative algorithm to accurately solve the Euler equations for rotary wing flow
NASA Astrophysics Data System (ADS)
Wagner, S.; Kraemer, E.
Due to the ability of Euler methods to treat rotational, nonisentropic flows and also to correctly transport on the rotation embedded in the flow field it is possible to correctly represent the inflow conditions on the blade in the stationary hovering flight of a helicopter, which are significantly influenced by the tip vortices (blade-vortex interaction) of all blades. It is shown that also the very complex starting procedure of a helicopter rotor can be very well described by a simple Euler method that is to say without a wake model. The algorithm based on the procedure is part of category upwind schemes, in which the difference formation orientates to the actual, local flow state that is to say to the typical distrubance expansion direction. Hence, the artificial dissipation required for the numerical stability is included in a natural way adapted to the real flow state over the break-up error of the difference equation and has not to be included from outside. This makes the procedure robust. An implicit solution algorithm is used, where the invertation of the coefficient matrix is carried out by means of a Point-Gauss-Seidel relaxation.
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
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.
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.
Hashmi, Muhammad Ali; Andreassend, Sarah K; Keyzers, Robert A; Lein, Matthias
2016-09-21
Despite advances in electronic structure theory the theoretical prediction of spectroscopic properties remains a computational challenge. This is especially true for natural products that exhibit very large conformational freedom and hence need to be sampled over many different accessible conformations. We report a strategy, which is able to predict NMR chemical shifts and more elusive properties like the optical rotation with great precision, through step-wise incremental increases of the conformational degrees of freedom. The application of this method is demonstrated for 3-epi-xestoaminol C, a chiral natural compound with a long, linear alkyl chain of 14 carbon atoms. Experimental NMR and [α]D values are reported to validate the results of the density functional theory calculations.
FastRNABindR: Fast and Accurate Prediction of Protein-RNA Interface Residues.
El-Manzalawy, Yasser; Abbas, Mostafa; Malluhi, Qutaibah; Honavar, Vasant
2016-01-01
A wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses are mediated by RNA-protein interactions. However, experimental determination of the structures of protein-RNA complexes is expensive and technically challenging. Hence, a number of computational tools have been developed for predicting protein-RNA interfaces. Some of the state-of-the-art protein-RNA interface predictors rely on position-specific scoring matrix (PSSM)-based encoding of the protein sequences. The computational efforts needed for generating PSSMs severely limits the practical utility of protein-RNA interface prediction servers. In this work, we experiment with two approaches, random sampling and sequence similarity reduction, for extracting a representative reference database of protein sequences from more than 50 million protein sequences in UniRef100. Our results suggest that random sampled databases produce better PSSM profiles (in terms of the number of hits used to generate the profile and the distance of the generated profile to the corresponding profile generated using the entire UniRef100 data as well as the accuracy of the machine learning classifier trained using these profiles). Based on our results, we developed FastRNABindR, an improved version of RNABindR for predicting protein-RNA interface residues using PSSM profiles generated using 1% of the UniRef100 sequences sampled uniformly at random. To the best of our knowledge, FastRNABindR is the only protein-RNA interface residue prediction online server that requires generation of PSSM profiles for query sequences and accepts hundreds of protein sequences per submission. Our approach for determining the optimal BLAST database for a protein-RNA interface residue classification task has the potential of substantially speeding up, and hence increasing the practical utility of, other amino acid sequence based predictors of protein-protein and protein
Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data.
Pagán, Josué; De Orbe, M Irene; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L; Mora, J Vivancos; Moya, José M; Ayala, José L
2015-06-30
Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives.
Accurate structure prediction of peptide–MHC complexes for identifying highly immunogenic antigens
Park, Min-Sun; Park, Sung Yong; Miller, Keith R.; Collins, Edward J.; Lee, Ha Youn
2013-11-01
Designing an optimal HIV-1 vaccine faces the challenge of identifying antigens that induce a broad immune capacity. One factor to control the breadth of T cell responses is the surface morphology of a peptide–MHC complex. Here, we present an in silico protocol for predicting peptide–MHC structure. A robust signature of a conformational transition was identified during all-atom molecular dynamics, which results in a model with high accuracy. A large test set was used in constructing our protocol and we went another step further using a blind test with a wild-type peptide and two highly immunogenic mutants, which predicted substantial conformational changes in both mutants. The center residues at position five of the analogs were configured to be accessible to solvent, forming a prominent surface, while the residue of the wild-type peptide was to point laterally toward the side of the binding cleft. We then experimentally determined the structures of the blind test set, using high resolution of X-ray crystallography, which verified predicted conformational changes. Our observation strongly supports a positive association of the surface morphology of a peptide–MHC complex to its immunogenicity. Our study offers the prospect of enhancing immunogenicity of vaccines by identifying MHC binding immunogens.
Asmadi, Aldi; Neumann, Marcus A; Kendrick, John; Girard, Pascale; Perrin, Marc-Antoine; Leusen, Frank J J
2009-12-24
In the 2007 blind test of crystal structure prediction hosted by the Cambridge Crystallographic Data Centre (CCDC), a hybrid DFT/MM method correctly ranked each of the four experimental structures as having the lowest lattice energy of all the crystal structures predicted for each molecule. The work presented here further validates this hybrid method by optimizing the crystal structures (experimental and submitted) of the first three CCDC blind tests held in 1999, 2001, and 2004. Except for the crystal structures of compound IX, all structures were reminimized and ranked according to their lattice energies. The hybrid method computes the lattice energy of a crystal structure as the sum of the DFT total energy and a van der Waals (dispersion) energy correction. Considering all four blind tests, the crystal structure with the lowest lattice energy corresponds to the experimentally observed structure for 12 out of 14 molecules. Moreover, good geometrical agreement is observed between the structures determined by the hybrid method and those measured experimentally. In comparison with the correct submissions made by the blind test participants, all hybrid optimized crystal structures (apart from compound II) have the smallest calculated root mean squared deviations from the experimentally observed structures. It is predicted that a new polymorph of compound V exists under pressure.
Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data
Pagán, Josué; Irene De Orbe, M.; Gago, Ana; Sobrado, Mónica; Risco-Martín, José L.; Vivancos Mora, J.; Moya, José M.; Ayala, José L.
2015-01-01
Migraine is one of the most wide-spread neurological disorders, and its medical treatment represents a high percentage of the costs of health systems. In some patients, characteristic symptoms that precede the headache appear. However, they are nonspecific, and their prediction horizon is unknown and pretty variable; hence, these symptoms are almost useless for prediction, and they are not useful to advance the intake of drugs to be effective and neutralize the pain. To solve this problem, this paper sets up a realistic monitoring scenario where hemodynamic variables from real patients are monitored in ambulatory conditions with a wireless body sensor network (WBSN). The acquired data are used to evaluate the predictive capabilities and robustness against noise and failures in sensors of several modeling approaches. The obtained results encourage the development of per-patient models based on state-space models (N4SID) that are capable of providing average forecast windows of 47 min and a low rate of false positives. PMID:26134103
Accurate prediction of drug-induced liver injury using stem cell-derived populations.
Szkolnicka, Dagmara; Farnworth, Sarah L; Lucendo-Villarin, Baltasar; Storck, Christopher; Zhou, Wenli; Iredale, John P; Flint, Oliver; Hay, David C
2014-02-01
Despite major progress in the knowledge and management of human liver injury, there are millions of people suffering from chronic liver disease. Currently, the only cure for end-stage liver disease is orthotopic liver transplantation; however, this approach is severely limited by organ donation. Alternative approaches to restoring liver function have therefore been pursued, including the use of somatic and stem cell populations. Although such approaches are essential in developing scalable treatments, there is also an imperative to develop predictive human systems that more effectively study and/or prevent the onset of liver disease and decompensated organ function. We used a renewable human stem cell resource, from defined genetic backgrounds, and drove them through developmental intermediates to yield highly active, drug-inducible, and predictive human hepatocyte populations. Most importantly, stem cell-derived hepatocytes displayed equivalence to primary adult hepatocytes, following incubation with known hepatotoxins. In summary, we have developed a serum-free, scalable, and shippable cell-based model that faithfully predicts the potential for human liver injury. Such a resource has direct application in human modeling and, in the future, could play an important role in developing renewable cell-based therapies.
A second-order accurate immersed boundary-lattice Boltzmann method for particle-laden flows
NASA Astrophysics Data System (ADS)
Zhou, Qiang; Fan, Liang-Shih
2014-07-01
A new immersed boundary-lattice Boltzmann method (IB-LBM) is presented for fully resolved simulations of incompressible viscous flows laden with rigid particles. The immersed boundary method (IBM) recently developed by Breugem (2012) [19] is adopted in the present method, development including the retraction technique, the multi-direct forcing method and the direct account of the inertia of the fluid contained within the particles. The present IB-LBM is, however, formulated with further improvement with the implementation of the high-order Runge-Kutta schemes in the coupled fluid-particle interaction. The major challenge to implement high-order Runge-Kutta schemes in the LBM is that the flow information such as density and velocity cannot be directly obtained at a fractional time step from the LBM since the LBM only provides the flow information at an integer time step. This challenge can be, however, overcome as given in the present IB-LBM by extrapolating the flow field around particles from the known flow field at the previous integer time step. The newly calculated fluid-particle interactions from the previous fractional time steps of the current integer time step are also accounted for in the extrapolation. The IB-LBM with high-order Runge-Kutta schemes developed in this study is validated by several benchmark applications. It is demonstrated, for the first time, that the IB-LBM has the capacity to resolve the translational and rotational motion of particles with the second-order accuracy. The optimal retraction distances for spheres and tubes that help the method achieve the second-order accuracy are found to be around 0.30 and -0.47 times of the lattice spacing, respectively. Simulations of the Stokes flow through a simple cubic lattice of rotational spheres indicate that the lift force produced by the Magnus effect can be very significant in view of the magnitude of the drag force when the practical rotating speed of the spheres is encountered. This finding
NASA Astrophysics Data System (ADS)
Zhang, Xiang; Vu-Quoc, Loc
2007-07-01
We present in this paper the displacement-driven version of a tangential force-displacement (TFD) model that accounts for both elastic and plastic deformations together with interfacial friction occurring in collisions of spherical particles. This elasto-plastic frictional TFD model, with its force-driven version presented in [L. Vu-Quoc, L. Lesburg, X. Zhang. An accurate tangential force-displacement model for granular-flow simulations: contacting spheres with plastic deformation, force-driven formulation, Journal of Computational Physics 196(1) (2004) 298-326], is consistent with the elasto-plastic frictional normal force-displacement (NFD) model presented in [L. Vu-Quoc, X. Zhang. An elasto-plastic contact force-displacement model in the normal direction: displacement-driven version, Proceedings of the Royal Society of London, Series A 455 (1991) 4013-4044]. Both the NFD model and the present TFD model are based on the concept of additive decomposition of the radius of contact area into an elastic part and a plastic part. The effect of permanent indentation after impact is represented by a correction to the radius of curvature. The effect of material softening due to plastic flow is represented by a correction to the elastic moduli. The proposed TFD model is accurate, and is validated against nonlinear finite element analyses involving plastic flows in both the loading and unloading conditions. The proposed consistent displacement-driven, elasto-plastic NFD and TFD models are designed for implementation in computer codes using the discrete-element method (DEM) for granular-flow simulations. The model is shown to be accurate and is validated against nonlinear elasto-plastic finite-element analysis.
Multigrid Acceleration of Time-Accurate DNS of Compressible Turbulent Flow
NASA Technical Reports Server (NTRS)
Broeze, Jan; Geurts, Bernard; Kuerten, Hans; Streng, Martin
1996-01-01
An efficient scheme for the direct numerical simulation of 3D transitional and developed turbulent flow is presented. Explicit and implicit time integration schemes for the compressible Navier-Stokes equations are compared. The nonlinear system resulting from the implicit time discretization is solved with an iterative method and accelerated by the application of a multigrid technique. Since we use central spatial discretizations and no artificial dissipation is added to the equations, the smoothing method is less effective than in the more traditional use of multigrid in steady-state calculations. Therefore, a special prolongation method is needed in order to obtain an effective multigrid method. This simulation scheme was studied in detail for compressible flow over a flat plate. In the laminar regime and in the first stages of turbulent flow the implicit method provides a speed-up of a factor 2 relative to the explicit method on a relatively coarse grid. At increased resolution this speed-up is enhanced correspondingly.
An affordable and accurate conductivity probe for density measurements in stratified flows
NASA Astrophysics Data System (ADS)
Carminati, Marco; Luzzatto-Fegiz, Paolo
2015-11-01
In stratified flow experiments, conductivity (combined with temperature) is often used to measure density. The probes typically used can provide very fine spatial scales, but can be fragile, expensive to replace, and sensitive to environmental noise. A complementary instrument, comprising a low-cost conductivity probe, would prove valuable in a wide range of applications where resolving extremely small spatial scales is not needed. We propose using micro-USB cables as the actual conductivity sensors. By removing the metallic shield from a micro-B connector, 5 gold-plated microelectrodes are exposed and available for 4-wire measurements. These have a cell constant ~550m-1, an intrinsic thermal noise of at most 30pA/Hz1/2, as well as sub-millisecond time response, making them highly suitable for many stratified flow measurements. In addition, we present the design of a custom electronic board (Arduino-based and Matlab-controlled) for simultaneous acquisition from 4 sensors, with resolution (in conductivity, and resulting density) exceeding the performance of typical existing probes. We illustrate the use of our conductivity-measuring system through stratified flow experiments, and describe plans to release simple instructions to construct our complete system for around 200.
NASA Astrophysics Data System (ADS)
Nissley, Daniel A.; Sharma, Ajeet K.; Ahmed, Nabeel; Friedrich, Ulrike A.; Kramer, Günter; Bukau, Bernd; O'Brien, Edward P.
2016-02-01
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.
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.
Predicting Transition from Laminar to Turbulent Flow over a Surface
NASA Technical Reports Server (NTRS)
Rajnarayan, Dev (Inventor); Sturdza, Peter (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.
Can tritiated water-dilution space accurately predict total body water in chukar partridges
Crum, B.G.; Williams, J.B.; Nagy, K.A.
1985-11-01
Total body water (TBW) volumes determined from the dilution space of injected tritiated water have consistently overestimated actual water volumes (determined by desiccation to constant mass) in reptiles and mammals, but results for birds are controversial. We investigated potential errors in both the dilution method and the desiccation method in an attempt to resolve this controversy. Tritiated water dilution yielded an accurate measurement of water mass in vitro. However, in vivo, this method yielded a 4.6% overestimate of the amount of water (3.1% of live body mass) in chukar partridges, apparently largely because of loss of tritium from body water to sites of dissociable hydrogens on body solids. An additional source of overestimation (approximately 2% of body mass) was loss of tritium to the solids in blood samples during distillation of blood to obtain pure water for tritium analysis. Measuring tritium activity in plasma samples avoided this problem but required measurement of, and correction for, the dry matter content in plasma. Desiccation to constant mass by lyophilization or oven-drying also overestimated the amount of water actually in the bodies of chukar partridges by 1.4% of body mass, because these values included water adsorbed onto the outside of feathers. When desiccating defeathered carcasses, oven-drying at 70 degrees C yielded TBW values identical to those obtained from lyophilization, but TBW was overestimated (0.5% of body mass) by drying at 100 degrees C due to loss of organic substances as well as water.
Barron, M R; Roch, A M; Waters, J A; Parikh, J A; DeWitt, J M; Al-Haddad, M A; Ceppa, E P; House, M G; Zyromski, N J; Nakeeb, A; Pitt, H A; Schmidt, C Max
2014-03-01
Main pancreatic duct (MPD) involvement is a well-demonstrated risk factor for malignancy in intraductal papillary mucinous neoplasm (IPMN). Preoperative radiographic determination of IPMN type is heavily relied upon in oncologic risk stratification. We hypothesized that radiographic assessment of MPD involvement in IPMN is an accurate predictor of pathological MPD involvement. Data regarding all patients undergoing resection for IPMN at a single academic institution between 1992 and 2012 were gathered prospectively. Retrospective analysis of imaging and pathologic data was undertaken. Preoperative classification of IPMN type was based on cross-sectional imaging (MRI/magnetic resonance cholangiopancreatography (MRCP) and/or CT). Three hundred sixty-two patients underwent resection for IPMN. Of these, 334 had complete data for analysis. Of 164 suspected branch duct (BD) IPMN, 34 (20.7%) demonstrated MPD involvement on final pathology. Of 170 patients with suspicion of MPD involvement, 50 (29.4%) demonstrated no MPD involvement. Of 34 patients with suspected BD-IPMN who were found to have MPD involvement on pathology, 10 (29.4%) had invasive carcinoma. Alternatively, 2/50 (4%) of the patients with suspected MPD involvement who ultimately had isolated BD-IPMN demonstrated invasive carcinoma. Preoperative radiographic IPMN type did not correlate with final pathology in 25% of the patients. In addition, risk of invasive carcinoma correlates with pathologic presence of MPD involvement.
Wang, Zhiheng; Yang, Qianqian; Li, Tonghua; Cong, Peisheng
2015-01-01
The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS) obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database. Availability The DisoMCS is available at http://cal.tongji.edu.cn/disorder/. PMID:26090958
Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.
2014-01-28
Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.
NASA Astrophysics Data System (ADS)
Oyeyemi, Victor B.; Krisiloff, David B.; Keith, John A.; Libisch, Florian; Pavone, Michele; Carter, Emily A.
2014-01-01
Oxygenated hydrocarbons play important roles in combustion science as renewable fuels and additives, but many details about their combustion chemistry remain poorly understood. Although many methods exist for computing accurate electronic energies of molecules at equilibrium geometries, a consistent description of entire combustion reaction potential energy surfaces (PESs) requires multireference correlated wavefunction theories. Here we use bond dissociation energies (BDEs) as a foundational metric to benchmark methods based on multireference configuration interaction (MRCI) for several classes of oxygenated compounds (alcohols, aldehydes, carboxylic acids, and methyl esters). We compare results from multireference singles and doubles configuration interaction to those utilizing a posteriori and a priori size-extensivity corrections, benchmarked against experiment and coupled cluster theory. We demonstrate that size-extensivity corrections are necessary for chemically accurate BDE predictions even in relatively small molecules and furnish examples of unphysical BDE predictions resulting from using too-small orbital active spaces. We also outline the specific challenges in using MRCI methods for carbonyl-containing compounds. The resulting complete basis set extrapolated, size-extensivity-corrected MRCI scheme produces BDEs generally accurate to within 1 kcal/mol, laying the foundation for this scheme's use on larger molecules and for more complex regions of combustion PESs.
Krokhotin, Andrey; Dokholyan, Nikolay V
2015-01-01
Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.
Bakhtiarizadeh, Mohammad Reza; Moradi-Shahrbabak, Mohammad; Ebrahimi, Mansour; Ebrahimie, Esmaeil
2014-09-07
Due to the central roles of lipid binding proteins (LBPs) in many biological processes, sequence based identification of LBPs is of great interest. The major challenge is that LBPs are diverse in sequence, structure, and function which results in low accuracy of sequence homology based methods. Therefore, there is a need for developing alternative functional prediction methods irrespective of sequence similarity. To identify LBPs from non-LBPs, the performances of support vector machine (SVM) and neural network were compared in this study. Comprehensive protein features and various techniques were employed to create datasets. Five-fold cross-validation (CV) and independent evaluation (IE) tests were used to assess the validity of the two methods. The results indicated that SVM outperforms neural network. SVM achieved 89.28% (CV) and 89.55% (IE) overall accuracy in identification of LBPs from non-LBPs and 92.06% (CV) and 92.90% (IE) (in average) for classification of different LBPs classes. Increasing the number and the range of extracted protein features as well as optimization of the SVM parameters significantly increased the efficiency of LBPs class prediction in comparison to the only previous report in this field. Altogether, the results showed that the SVM algorithm can be run on broad, computationally calculated protein features and offers a promising tool in detection of LBPs classes. The proposed approach has the potential to integrate and improve the common sequence alignment based methods.
Accurate Prediction of the Dynamical Changes within the Second PDZ Domain of PTP1e
Cilia, Elisa; Vuister, Geerten W.; Lenaerts, Tom
2012-01-01
Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods. PMID:23209399
Dynamic model for horizontal two-phase flow predicting low head flooding
Saarinen, M. . Nuclear Engineering Lab.)
1994-10-01
The countercurrent flow of gas and water in a short horizontal pipe is studied numerically with a two-phase flow model. It is observed that the onset of flooding cannot be predicted at low liquid flow rates using conventional one-dimensional equations. The conventional equations yield the same underestimated results as the Taitel-Dukler criterion. Utilizing physical reasoning, improved equations have been derived. The basic idea is that the distribution of the phase velocities should not be treated as uniform in the cross-sectional area occupied by phases but transverse dependencies for the velocities should be allowed. By comparing measurement data and calculated results, it is shown that flooding transition can be predicted accurately with these equations.
A second-order accurate immersed boundary-lattice Boltzmann method for particle-laden flows
Zhou, Qiang; Fan, Liang-Shih
2014-07-01
A new immersed boundary-lattice Boltzmann method (IB-LBM) is presented for fully resolved simulations of incompressible viscous flows laden with rigid particles. The immersed boundary method (IBM) recently developed by Breugem (2012) [19] is adopted in the present method, development including the retraction technique, the multi-direct forcing method and the direct account of the inertia of the fluid contained within the particles. The present IB-LBM is, however, formulated with further improvement with the implementation of the high-order Runge–Kutta schemes in the coupled fluid–particle interaction. The major challenge to implement high-order Runge–Kutta schemes in the LBM is that the flow information such as density and velocity cannot be directly obtained at a fractional time step from the LBM since the LBM only provides the flow information at an integer time step. This challenge can be, however, overcome as given in the present IB-LBM by extrapolating the flow field around particles from the known flow field at the previous integer time step. The newly calculated fluid–particle interactions from the previous fractional time steps of the current integer time step are also accounted for in the extrapolation. The IB-LBM with high-order Runge–Kutta schemes developed in this study is validated by several benchmark applications. It is demonstrated, for the first time, that the IB-LBM has the capacity to resolve the translational and rotational motion of particles with the second-order accuracy. The optimal retraction distances for spheres and tubes that help the method achieve the second-order accuracy are found to be around 0.30 and −0.47 times of the lattice spacing, respectively. Simulations of the Stokes flow through a simple cubic lattice of rotational spheres indicate that the lift force produced by the Magnus effect can be very significant in view of the magnitude of the drag force when the practical rotating speed of the spheres is encountered
NASA Astrophysics Data System (ADS)
Samuel, Henri
2010-05-01
Advection is one of the major processes that commonly acts on various scales in nature (core formation, mantle convective stirring, multi-phase flows in magma chambers, salt diapirism ...). While this process can be modeled numerically by solving conservation equations, various geodynamic scenarios involve advection of quantities with sharp discontinuities. Unfortunately, in these cases modeling numerically pure advection becomes very challenging, in particular because sharp discontinuities lead to numerical instabilities, which prevent the local use of high order numerical schemes. Several approaches have been used in computational geodynamics in order to overcome this difficulty, with variable amounts of success. Despite the use of correcting filters or non-oscillatory, shock-preserving schemes, Eulerian (fixed grid) techniques generally suffer from artificial numerical diffusion. Lagrangian approaches (dynamic grids or particles) tend to be more popular in computational geodynamics because they are not prone to excessive numerical diffusion. However, these approaches are generally computationally expensive, especially in 3D, and can suffer from spurious statistical noise. As an alternative to these aforementioned approaches, I have applied a relatively recent Particle Level set method [Enright et al., 2002] for modeling advection of quantities with the presence of sharp discontinuities. I have adapted this improved method, which combines the best of Eulerian and Lagrangian approaches, and I have tested it against well known benchmarks and classical Geodynamic flows. In each case the Particle Level Set method accuracy equals or is better than other Eulerian and Lagrangian methods, and leads to significantly smaller computational cost, in particular in three-dimensional flows, where the reduction of computational time for modeling advection processes is most needed.
Martin, Katherine J.; Patrick, Denis R.; Bissell, Mina J.; Fournier, Marcia V.
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 datasets 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 prognostic
NASA Astrophysics Data System (ADS)
Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.
2013-06-01
This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.
How Accurate Is the Prediction of Maximal Oxygen Uptake with Treadmill Testing?
Wicks, John R.; Oldridge, Neil B.
2016-01-01
Background Cardiorespiratory fitness measured by treadmill testing has prognostic significance in determining mortality with cardiovascular and other chronic disease states. The accuracy of a recently developed method for estimating maximal oxygen uptake (VO2peak), the heart rate index (HRI), is dependent only on heart rate (HR) and was tested against oxygen uptake (VO2), either measured or predicted from conventional treadmill parameters (speed, incline, protocol time). Methods The HRI equation, METs = 6 x HRI– 5, where HRI = maximal HR/resting HR, provides a surrogate measure of VO2peak. Forty large scale treadmill studies were identified through a systematic search using MEDLINE, Google Scholar and Web of Science in which VO2peak was either measured (TM-VO2meas; n = 20) or predicted (TM-VO2pred; n = 20) based on treadmill parameters. All studies were required to have reported group mean data of both resting and maximal HRs for determination of HR index-derived oxygen uptake (HRI-VO2). Results The 20 studies with measured VO2 (TM-VO2meas), involved 11,477 participants (median 337) with a total of 105,044 participants (median 3,736) in the 20 studies with predicted VO2 (TM-VO2pred). A difference of only 0.4% was seen between mean (±SD) VO2peak for TM- VO2meas and HRI-VO2 (6.51±2.25 METs and 6.54±2.28, respectively; p = 0.84). In contrast, there was a highly significant 21.1% difference between mean (±SD) TM-VO2pred and HRI-VO2 (8.12±1.85 METs and 6.71±1.92, respectively; p<0.001). Conclusion Although mean TM-VO2meas and HRI-VO2 were almost identical, mean TM-VO2pred was more than 20% greater than mean HRI-VO2. PMID:27875547
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.
A Foundation for the Accurate Prediction of the Soft Error Vulnerability of Scientific Applications
Bronevetsky, G; de Supinski, B; Schulz, M
2009-02-13
Understanding the soft error vulnerability of supercomputer applications is critical as these systems are using ever larger numbers of devices that have decreasing feature sizes and, thus, increasing frequency of soft errors. As many large scale parallel scientific applications use BLAS and LAPACK linear algebra routines, the soft error vulnerability of these methods constitutes a large fraction of the applications overall vulnerability. This paper analyzes the vulnerability of these routines to soft errors by characterizing how their outputs are affected by injected errors and by evaluating several techniques for predicting how errors propagate from the input to the output of each routine. The resulting error profiles can be used to understand the fault vulnerability of full applications that use these routines.
Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile.
Faraggi, Eshel; Kouza, Maksim; Zhou, Yaoqi; Kloczkowski, Andrzej
2017-01-01
A fast accessible surface area (ASA) predictor is presented. In this new approach no residue mutation profiles generated by multiple sequence alignments are used as inputs. Instead, we use only single sequence information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for ASAquick are available from Research and Information Systems at http://mamiris.com and from the Battelle Center for Mathematical Medicine at http://mathmed.org .
Sequence features accurately predict genome-wide MeCP2 binding in vivo
Rube, H. Tomas; Lee, Wooje; Hejna, Miroslav; Chen, Huaiyang; Yasui, Dag H.; Hess, John F.; LaSalle, Janine M.; Song, Jun S.; Gong, Qizhi
2016-01-01
Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2's affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons. PMID:27008915
Telfer, Scott; Erdemir, Ahmet; Woodburn, James; Cavanagh, Peter R
2016-01-25
Integration of patient-specific biomechanical measurements into the design of therapeutic footwear has been shown to improve clinical outcomes in patients with diabetic foot disease. The addition of numerical simulations intended to optimise intervention design may help to build on these advances, however at present the time and labour required to generate and run personalised models of foot anatomy restrict their routine clinical utility. In this study we developed second-generation personalised simple finite element (FE) models of the forefoot with varying geometric fidelities. Plantar pressure predictions from barefoot, shod, and shod with insole simulations using simplified models were compared to those obtained from CT-based FE models incorporating more detailed representations of bone and tissue geometry. A simplified model including representations of metatarsals based on simple geometric shapes, embedded within a contoured soft tissue block with outer geometry acquired from a 3D surface scan was found to provide pressure predictions closest to the more complex model, with mean differences of 13.3kPa (SD 13.4), 12.52kPa (SD 11.9) and 9.6kPa (SD 9.3) for barefoot, shod, and insole conditions respectively. The simplified model design could be produced in <1h compared to >3h in the case of the more detailed model, and solved on average 24% faster. FE models of the forefoot based on simplified geometric representations of the metatarsal bones and soft tissue surface geometry from 3D surface scans may potentially provide a simulation approach with improved clinical utility, however further validity testing around a range of therapeutic footwear types is required.
NASA Astrophysics Data System (ADS)
Du, Xia; Zhao, Dong-Xia; Yang, Zhong-Zhi
2013-02-01
A new approach to characterize and measure bond strength has been developed. First, we propose a method to accurately calculate the potential acting on an electron in a molecule (PAEM) at the saddle point along a chemical bond in situ, denoted by Dpb. Then, a direct method to quickly evaluate bond strength is established. We choose some familiar molecules as models for benchmarking this method. As a practical application, the Dpb of base pairs in DNA along C-H and N-H bonds are obtained for the first time. All results show that C7-H of A-T and C8-H of G-C are the relatively weak bonds that are the injured positions in DNA damage. The significance of this work is twofold: (i) A method is developed to calculate Dpb of various sizable molecules in situ quickly and accurately; (ii) This work demonstrates the feasibility to quickly predict the bond strength in macromolecules.
Ghost particle velocimetry: accurate 3D flow visualization using standard lab equipment.
Buzzaccaro, Stefano; Secchi, Eleonora; Piazza, Roberto
2013-07-26
We describe and test a new approach to particle velocimetry, based on imaging and cross correlating the scattering speckle pattern generated on a near-field plane by flowing tracers with a size far below the diffraction limit, which allows reconstructing the velocity pattern in microfluidic channels without perturbing the flow. As a matter of fact, adding tracers is not even strictly required, provided that the sample displays sufficiently refractive-index fluctuations. For instance, phase separation in liquid mixtures in the presence of shear is suitable to be directly investigated by this "ghost particle velocimetry" technique, which just requires a microscope with standard lamp illumination equipped with a low-cost digital camera. As a further bonus, the peculiar spatial coherence properties of the illuminating source, which displays a finite longitudinal coherence length, allows for a 3D reconstruction of the profile with a resolution of few tenths of microns and makes the technique suitable to investigate turbid samples with negligible multiple scattering effects.
Resnic, F S; Ohno-Machado, L; Selwyn, A; Simon, D I; Popma, J J
2001-07-01
The objectives of this analysis were to develop and validate simplified risk score models for predicting the risk of major in-hospital complications after percutaneous coronary intervention (PCI) in the era of widespread stenting and use of glycoprotein IIb/IIIa antagonists. We then sought to compare the performance of these simplified models with those of full logistic regression and neural network models. From January 1, 1997 to December 31, 1999, data were collected on 4,264 consecutive interventional procedures at a single center. Risk score models were derived from multiple logistic regression models using the first 2,804 cases and then validated on the final 1,460 cases. The area under the receiver operating characteristic (ROC) curve for the risk score model that predicted death was 0.86 compared with 0.85 for the multiple logistic model and 0.83 for the neural network model (validation set). For the combined end points of death, myocardial infarction, or bypass surgery, the corresponding areas under the ROC curves were 0.74, 0.78, and 0.81, respectively. Previously identified risk factors were confirmed in this analysis. The use of stents was associated with a decreased risk of in-hospital complications. Thus, risk score models can accurately predict the risk of major in-hospital complications after PCI. Their discriminatory power is comparable to those of logistic models and neural network models. Accurate bedside risk stratification may be achieved with these simple models.
NASA Astrophysics Data System (ADS)
Sakai, Yasumasa; Taki, Hirofumi; Kanai, Hiroshi
2016-07-01
In our previous study, the viscoelasticity of the radial artery wall was estimated to diagnose endothelial dysfunction using a high-frequency (22 MHz) ultrasound device. In the present study, we employed a commercial ultrasound device (7.5 MHz) and estimated the viscoelasticity using arterial pressure and diameter, both of which were measured at the same position. In a phantom experiment, the proposed method successfully estimated the elasticity and viscosity of the phantom with errors of 1.8 and 30.3%, respectively. In an in vivo measurement, the transient change in the viscoelasticity was measured for three healthy subjects during flow-mediated dilation (FMD). The proposed method revealed the softening of the arterial wall originating from the FMD reaction within 100 s after avascularization. These results indicate the high performance of the proposed method in evaluating vascular endothelial function just after avascularization, where the function is difficult to be estimated by a conventional FMD measurement.
Prediction of pressure fluctuations in turbulent flows using the immersed boundary method
NASA Astrophysics Data System (ADS)
Kang, Seongwon; Iaccarino, Gianluca; Ham, Frank; Moin, Parviz
2009-11-01
The immersed boundary (IB) method has been widely used to model flow problems in complex geometries. We investigate the capability of the IB method to predict wall pressure fluctuations in turbulent flows. We introduce a new numerical treatment of the cells crossed by the IB that ensures mass consrvation and provides accurate evaluation of the wall pressure. The present approach has been successfully validated through computations of the space-time correlations of the wall-pressure fluctuations. Compared to the original IB method (Fadlun et al., 2000), the present approach shows better agreement with the standard DNS results. When applied to turbulent flow around an airfoil, the computed flow statistics - the mean/RMS and power spectra of the wall pressure - are in good agreement with the LES performed on body- fitted mesh and experiment (Roger and Moreau, 2004).
Integrative subcellular proteomic analysis allows accurate prediction of human disease-causing genes
Zhao, Li; Chen, Yiyun; Bajaj, Amol Onkar; Eblimit, Aiden; Xu, Mingchu; Soens, Zachry T.; Wang, Feng; Ge, Zhongqi; Jung, Sung Yun; He, Feng; Li, Yumei; Wensel, Theodore G.; Qin, Jun; Chen, Rui
2016-01-01
Proteomic profiling on subcellular fractions provides invaluable information regarding both protein abundance and subcellular localization. When integrated with other data sets, it can greatly enhance our ability to predict gene function genome-wide. In this study, we performed a comprehensive proteomic analysis on the light-sensing compartment of photoreceptors called the outer segment (OS). By comparing with the protein profile obtained from the retina tissue depleted of OS, an enrichment score for each protein is calculated to quantify protein subcellular localization, and 84% accuracy is achieved compared with experimental data. By integrating the protein OS enrichment score, the protein abundance, and the retina transcriptome, the probability of a gene playing an essential function in photoreceptor cells is derived with high specificity and sensitivity. As a result, a list of genes that will likely result in human retinal disease when mutated was identified and validated by previous literature and/or animal model studies. Therefore, this new methodology demonstrates the synergy of combining subcellular fractionation proteomics with other omics data sets and is generally applicable to other tissues and diseases. PMID:26912414
Accurate prediction of the refractive index of polymers using first principles and data modeling
NASA Astrophysics Data System (ADS)
Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes
Organic polymers with a high refractive index (RI) have recently attracted considerable interest due to their potential application in optical and optoelectronic devices. The ability to tailor the molecular structure of polymers is the key to increasing the accessible RI values. Our work concerns the creation of predictive in silico models for the optical properties of organic polymers, the screening of large-scale candidate libraries, and the mining of the resulting data to extract the underlying design principles that govern their performance. This work was set up to guide our experimentalist partners and allow them to target the most promising candidates. Our model is based on the Lorentz-Lorenz equation and thus includes the polarizability and number density values for each candidate. For the former, we performed a detailed benchmark study of different density functionals, basis sets, and the extrapolation scheme towards the polymer limit. For the number density we devised an exceedingly efficient machine learning approach to correlate the polymer structure and the packing fraction in the bulk material. We validated the proposed RI model against the experimentally known RI values of 112 polymers. We could show that the proposed combination of physical and data modeling is both successful and highly economical to characterize a wide range of organic polymers, which is a prerequisite for virtual high-throughput screening.
Slodownik, Dan; Grinberg, Igor; Spira, Ram M; Skornik, Yehuda; Goldstein, Ronald S
2009-04-01
The current standard method for predicting contact allergenicity is the murine local lymph node assay (LLNA). Public objection to the use of animals in testing of cosmetics makes the development of a system that does not use sentient animals highly desirable. The chorioallantoic membrane (CAM) of the chick egg has been extensively used for the growth of normal and transformed mammalian tissues. The CAM is not innervated, and embryos are sacrificed before the development of pain perception. The aim of this study was to determine whether the sensitization phase of contact dermatitis to known cosmetic allergens can be quantified using CAM-engrafted human skin and how these results compare with published EC3 data obtained with the LLNA. We studied six common molecules used in allergen testing and quantified migration of epidermal Langerhans cells (LC) as a measure of their allergic potency. All agents with known allergic potential induced statistically significant migration of LC. The data obtained correlated well with published data for these allergens generated using the LLNA test. The human-skin CAM model therefore has great potential as an inexpensive, non-radioactive, in vivo alternative to the LLNA, which does not require the use of sentient animals. In addition, this system has the advantage of testing the allergic response of human, rather than animal skin.
Searching for Computational Strategies to Accurately Predict pKas of Large Phenolic Derivatives.
Rebollar-Zepeda, Aida Mariana; Campos-Hernández, Tania; Ramírez-Silva, María Teresa; Rojas-Hernández, Alberto; Galano, Annia
2011-08-09
Twenty-two reaction schemes have been tested, within the cluster-continuum model including up to seven explicit water molecules. They have been used in conjunction with nine different methods, within the density functional theory and with second-order Møller-Plesset. The quality of the pKa predictions was found to be strongly dependent on the chosen scheme, while only moderately influenced by the method of calculation. We recommend the E1 reaction scheme [HA + OH(-) (3H2O) ↔ A(-) (H2O) + 3H2O], since it yields mean unsigned errors (MUE) lower than 1 unit of pKa for most of the tested functionals. The best pKa values obtained from this reaction scheme are those involving calculations with PBE0 (MUE = 0.77), TPSS (MUE = 0.82), BHandHLYP (MUE = 0.82), and B3LYP (MUE = 0.86) functionals. This scheme has the additional advantage, compared to the proton exchange method, which also gives very small values of MUE, of being experiment independent. It should be kept in mind, however, that these recommendations are valid within the cluster-continuum model, using the polarizable continuum model in conjunction with the united atom Hartree-Fock cavity and the strategy based on thermodynamic cycles. Changes in any of these aspects of the used methodology may lead to different outcomes.
Towards Relaxing the Spherical Solar Radiation Pressure Model for Accurate Orbit Predictions
NASA Astrophysics Data System (ADS)
Lachut, M.; Bennett, J.
2016-09-01
The well-known cannonball model has been used ubiquitously to capture the effects of atmospheric drag and solar radiation pressure on satellites and/or space debris for decades. While it lends itself naturally to spherical objects, its validity in the case of non-spherical objects has been debated heavily for years throughout the space situational awareness community. One of the leading motivations to improve orbit predictions by relaxing the spherical assumption, is the ongoing demand for more robust and reliable conjunction assessments. In this study, we explore the orbit propagation of a flat plate in a near-GEO orbit under the influence of solar radiation pressure, using a Lambertian BRDF model. Consequently, this approach will account for the spin rate and orientation of the object, which is typically determined in practice using a light curve analysis. Here, simulations will be performed which systematically reduces the spin rate to demonstrate the point at which the spherical model no longer describes the orbital elements of the spinning plate. Further understanding of this threshold would provide insight into when a higher fidelity model should be used, thus resulting in improved orbit propagations. Therefore, the work presented here is of particular interest to organizations and researchers that maintain their own catalog, and/or perform conjunction analyses.
Prediction of flow duration curves for ungauged basins
NASA Astrophysics Data System (ADS)
Atieh, Maya; Taylor, Graham; Sattar, Ahmed M. A.; 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.
Ni, Chuen-Fa; Yeh, Tian-Chyi Jim; Chent, Jui-Sheng
2009-05-15
This study shows how a cost-effective hydraulic tomography survey (HTS) and the associated data estimator can be used to characterize flow and transport in heterogeneous aquifers. The HTS is an improved field hydraulic test that accounts for responses of hydraulic stresses caused by pumping or injection events at different locations of an aquifer. A sequential data assimilation method based on a cokriging algorithm is then used to map the aquifer hydraulic conductivity (K). This study uses a synthetic two-dimensional aquifer to assess the accuracy of predicted concentration breakthrough curves (BTCs) on the basis of the Kfields estimated by geometric mean, kriging, and HTS. Such Kfields represent different degrees of flow resolutions as compared with the synthetically generated one. Without intensive experimentsto calibrate accurate dispersivities at sites, the flow field based on the HTS Kfield can yield accurate predictions of BTC peaks and phases. On the basis of calculating mean absolute and square errors for estimated K fields, numerical assessments on the HTS operation strategy show that more pumping events will generally lead to more accurate estimations of Kfields, and the pump locations need to be installed in high Kzones to maximize the delivery of head information from pumps to measurement points. Additionally, the appropriate distances of installed wells are suggested to be less than one-third of the ln(K) correlation length in x direction.
Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke
2015-11-15
attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries.
Yu, Victoria Y.; Tran, Angelia; Nguyen, Dan; Cao, Minsong; Ruan, Dan; Low, Daniel A.; Sheng, Ke
2015-01-01
attributed to phantom setup errors due to the slightly deformable and flexible phantom extremities. The estimated site-specific safety buffer distance with 0.001% probability of collision for (gantry-to-couch, gantry-to-phantom) was (1.23 cm, 3.35 cm), (1.01 cm, 3.99 cm), and (2.19 cm, 5.73 cm) for treatment to the head, lung, and prostate, respectively. Automated delivery to all three treatment sites was completed in 15 min and collision free using a digital Linac. Conclusions: An individualized collision prediction model for the purpose of noncoplanar beam delivery was developed and verified. With the model, the study has demonstrated the feasibility of predicting deliverable beams for an individual patient and then guiding fully automated noncoplanar treatment delivery. This work motivates development of clinical workflows and quality assurance procedures to allow more extensive use and automation of noncoplanar beam geometries. PMID:26520735
Shakibaee, Abolfazl; Faghihzadeh, Soghrat; Alishiri, Gholam Hossein; Ebrahimpour, Zeynab; Faradjzadeh, Shahram; Sobhani, Vahid; Asgari, Alireza
2015-01-01
Background: The body composition varies according to different life styles (i.e. intake calories and caloric expenditure). Therefore, it is wise to record military personnel’s body composition periodically and encourage those who abide to the regulations. Different methods have been introduced for body composition assessment: invasive and non-invasive. Amongst them, the Jackson and Pollock equation is most popular. Objectives: The recommended anthropometric prediction equations for assessing men’s body composition were compared with dual-energy X-ray absorptiometry (DEXA) gold standard to develop a modified equation to assess body composition and obesity quantitatively among Iranian military men. Patients and Methods: A total of 101 military men aged 23 - 52 years old with a mean age of 35.5 years were recruited and evaluated in the present study (average height, 173.9 cm and weight, 81.5 kg). The body-fat percentages of subjects were assessed both with anthropometric assessment and DEXA scan. The data obtained from these two methods were then compared using multiple regression analysis. Results: The mean and standard deviation of body fat percentage of the DEXA assessment was 21.2 ± 4.3 and body fat percentage obtained from three Jackson and Pollock 3-, 4- and 7-site equations were 21.1 ± 5.8, 22.2 ± 6.0 and 20.9 ± 5.7, respectively. There was a strong correlation between these three equations and DEXA (R² = 0.98). Conclusions: The mean percentage of body fat obtained from the three equations of Jackson and Pollock was very close to that of body fat obtained from DEXA; however, we suggest using a modified Jackson-Pollock 3-site equation for volunteer military men because the 3-site equation analysis method is simpler and faster than other methods. PMID:26715964
Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Arnold, Steven M.
2002-01-01
NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.
Blasco, Antonio Javier; Crevillén, Agustín González; de la Fuente, Pedro; González, María Cristina; Escarpa, Alberto
2007-04-01
A novel strategy integrating methodological calibration and analysis on board on a planar first-generation microfluidics system for the determination of total isoflavones in soy samples is proposed. The analytical strategy is conceptually proposed and successfully demonstrated on the basis of (i) the microchip design (with the possibility to use both reservoirs), (ii) the analytical characteristics of the developed method (statically zero intercept and excellent robustness between calibration slopes, RSDs < 5%), (iii) the irreversible electrochemical behaviour of isoflavone oxidation (no significant electrode fouling effect was observed between calibration and analysis runs) and (iv) the inherent versatility of the electrochemical end-channel configurations (possibility of use different pumping and detection media). Repeatability obtained in both standard (calibration) and real soy samples (analysis) with values of RSD less than 1% for the migration times indicated the stability of electroosmotic flow (EOF) during both integrated operations. The accuracy (an error of less than 6%) is demonstrated for the first time in these microsystems using a documented secondary standard from the Drug Master File (SW/1211/03) as reference material. Ultra fast calibration and analysis of total isoflavones in soy samples was integrated successfully employing 60 s each; enhancing notably the analytical performance of these microdevices with an important decrease in overall analysis times (less than 120 s) and with an increase in accuracy by a factor of 3.
Prediction of leakage flow in a shrouded centrifugal blood pump.
Teo, Ji-Bin; Chan, Weng-Kong; Wong, Yew-Wah
2010-09-01
This article proposes a phenomenological model to predict the leakage flow in the clearance gap of shrouded centrifugal blood pumps. A good washout in the gap clearance between the rotating impeller surfaces and volute casing is essential to avoid thrombosis. However, excessive leakage flow will result in higher fluid shear stress that may lead to hemolysis. Computational fluid dynamics (CFD) analysis was performed to investigate the leakage flow in a miniaturized shrouded centrifugal blood pump operating at a speed of 2000 rpm. Based on an analytical model derived earlier, a phenomenological model is proposed to predict the leakage flow. The leakage flow rate is found to be proportional to h(α) , where h is the gap size and the exponent α ranges from 2.955 to 3.15 for corresponding gap sizes of 0.2-0.5 mm. In addition, it is observed that α is a linear function of the gap size h. The exponent α compensates for the variation of pressure difference along the circumferential direction as well as inertia effects that are dominant for larger gap clearances. The proposed model displays good agreement with computational results. The CFD analysis also showed that for larger gap sizes, the total leakage flow rate is of the same order of magnitude as the operating flow rate, thus suggesting low volumetric efficiency.
Ballester, Pedro J; Schreyer, Adrian; Blundell, Tom L
2014-03-24
Predicting the binding affinities of large sets of diverse molecules against a range of macromolecular targets is an extremely challenging task. The scoring functions that attempt such computational prediction are essential for exploiting and analyzing the outputs of docking, which is in turn an important tool in problems such as structure-based drug design. Classical scoring functions assume a predetermined theory-inspired functional form for the relationship between the variables that describe an experimentally determined or modeled structure of a protein-ligand complex and its binding affinity. The inherent problem of this approach is in the difficulty of explicitly modeling the various contributions of intermolecular interactions to binding affinity. New scoring functions based on machine-learning regression models, which are able to exploit effectively much larger amounts of experimental data and circumvent the need for a predetermined functional form, have already been shown to outperform a broad range of state-of-the-art scoring functions in a widely used benchmark. Here, we investigate the impact of the chemical description of the complex on the predictive power of the resulting scoring function using a systematic battery of numerical experiments. The latter resulted in the most accurate scoring function to date on the benchmark. Strikingly, we also found that a more precise chemical description of the protein-ligand complex does not generally lead to a more accurate prediction of binding affinity. We discuss four factors that may contribute to this result: modeling assumptions, codependence of representation and regression, data restricted to the bound state, and conformational heterogeneity in data.
Flood and Debris Flow Hazard Predictions in Steep, Burned Landscapes
NASA Astrophysics Data System (ADS)
Rengers, Francis; McGuire, Luke; Kean, Jason; Staley, Dennis
2016-04-01
Post-wildfire natural hazards such as flooding and debris flows threaten infrastructure and can even lead to loss of life. The risk from these natural hazards could be reduced if floods and debris flows could be predicted from modeling. Our ability to test predictive models is primarily constrained by a lack of observational data that can be used for comparison with model predictions. Following the 2009 Station Fire in the San Gabriel Mountains, CA, USA, we conducted a study with high-resolution topography and hydrologic measurements to test the effectiveness of two different hydrologic routing models to predict flood and debris flow timing. Our research focuses on comparing the performance of two hydrologic models with differing levels of complexity and efficiency using high-resolution, lidar-derived digital elevation models. The simpler model uses the kinematic wave approximation to route flows, while the more complex model uses the full shallow water equations. In both models precipitation is spatially uniform and infiltration is simulated using the Green-Ampt infiltration equation. Input data for the numerical models was constrained by time series data of soil moisture, and rainfall collected at field sites as well as high-resolution lidar-derived digital elevation models. We ran the numerical models and varied parameter values for the roughness coefficient and hydraulic conductivity. These parameter values were calibrated by minimizing the difference between the simulated and observed flow timing. Moreover, the two parameters were calibrated in two different watersheds, spanning two orders of magnitude in drainage area. The calibrated parameters were subsequently used to model a third watershed, and the results show a good match with observed timing of flow peaks for both models. Calibrated roughness coefficients are generally higher when using the kinematic wave approximation relative to the full shallow water equations, and decrease with increasing spatial
Staranowicz, Aaron N; Ray, Christopher; Mariottini, Gian-Luca
2015-01-01
Falls are the most-common causes of unintentional injury and death in older adults. Many clinics, hospitals, and health-care providers are urgently seeking accurate, low-cost, and easy-to-use technology to predict falls before they happen, e.g., by monitoring the human walking pattern (or "gait"). Despite the wide popularity of Microsoft's Kinect and the plethora of solutions for gait monitoring, no strategy has been proposed to date to allow non-expert users to calibrate the cameras, which is essential to accurately fuse the body motion observed by each camera in a single frame of reference. In this paper, we present a novel multi-Kinect calibration algorithm that has advanced features when compared to existing methods: 1) is easy to use, 2) it can be used in any generic Kinect arrangement, and 3) it provides accurate calibration. Extensive real-world experiments have been conducted to validate our algorithm and to compare its performance against other multi-Kinect calibration approaches, especially to show the improved estimate of gait parameters. Finally, a MATLAB Toolbox has been made publicly available for the entire research community.
NASA Astrophysics Data System (ADS)
Dougherty, N. S.; Burnette, D. W.; Holt, J. B.; Matienzo, Jose
1993-07-01
Time-accurate unsteady flow simulations are being performed supporting the SRM T+68sec pressure 'spike' anomaly investigation. The anomaly occurred in the RH SRM during the STS-54 flight (STS-54B) but not in the LH SRM (STS-54A) causing a momentary thrust mismatch approaching the allowable limit at that time into the flight. Full-motor internal flow simulations using the USA-2D axisymmetric code are in progress for the nominal propellant burn-back geometry and flow conditions at T+68-sec--Pc = 630 psi, gamma = 1.1381, T(sub c) = 6200 R, perfect gas without aluminum particulate. In a cooperative effort with other investigation team members, CFD-derived pressure loading on the NBR and castable inhibitors was used iteratively to obtain nominal deformed geometry of each inhibitor, and the deformed (bent back) inhibitor geometry was entered into this model. Deformed geometry was computed using structural finite-element models. A solution for the unsteady flow has been obtained for the nominal flow conditions (existing prior to the occurrence of the anomaly) showing sustained standing pressure oscillations at nominally 14.5 Hz in the motor IL acoustic mode that flight and static test data confirm to be normally present at this time. Average mass flow discharged from the nozzle was confirmed to be the nominal expected (9550 lbm/sec). The local inlet boundary condition is being perturbed at the location of the presumed reconstructed anomaly as identified by interior ballistics performance specialist team members. A time variation in local mass flow is used to simulate sudden increase in burning area due to localized propellant grain cracks. The solution will proceed to develop a pressure rise (proportional to total mass flow rate change squared). The volume-filling time constant (equivalent to 0.5 Hz) comes into play in shaping the rise rate of the developing pressure 'spike' as it propagates at the speed of sound in both directions to the motor head end and nozzle. The
Hourihan, Kathleen L.; Benjamin, Aaron S.; Liu, Xiping
2012-01-01
The Cross-Race Effect (CRE) in face recognition is the well-replicated finding that people are better at recognizing faces from their own race, relative to other races. The CRE reveals systematic limitations on eyewitness identification accuracy and suggests that some caution is warranted in evaluating cross-race identification. The CRE is a problem because jurors value eyewitness identification highly in verdict decisions. In the present paper, we explore how accurate people are in predicting their ability to recognize own-race and other-race faces. Caucasian and Asian participants viewed photographs of Caucasian and Asian faces, and made immediate judgments of learning during study. An old/new recognition test replicated the CRE: both groups displayed superior discriminability of own-race faces, relative to other-race faces. Importantly, relative metamnemonic accuracy was also greater for own-race faces, indicating that the accuracy of predictions about face recognition is influenced by race. This result indicates another source of concern when eliciting or evaluating eyewitness identification: people are less accurate in judging whether they will or will not recognize a face when that face is of a different race than they are. This new result suggests that a witness’s claim of being likely to recognize a suspect from a lineup should be interpreted with caution when the suspect is of a different race than the witness. PMID:23162788
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.
Correa da Rosa, Joel; Kim, Jaehwan; Tian, Suyan; Tomalin, Lewis E; Krueger, James G; Suárez-Fariñas, Mayte
2017-02-01
There is an "assessment gap" between the moment a patient's response to treatment is biologically determined and when a response can actually be determined clinically. Patients' biochemical profiles are a major determinant of clinical outcome for a given treatment. It is therefore feasible that molecular-level patient information could be used to decrease the assessment gap. Thanks to clinically accessible biopsy samples, high-quality molecular data for psoriasis patients are widely available. Psoriasis is therefore an excellent disease for testing the prospect of predicting treatment outcome from molecular data. Our study shows that gene-expression profiles of psoriasis skin lesions, taken in the first 4 weeks of treatment, can be used to accurately predict (>80% area under the receiver operating characteristic curve) the clinical endpoint at 12 weeks. This could decrease the psoriasis assessment gap by 2 months. We present two distinct prediction modes: a universal predictor, aimed at forecasting the efficacy of untested drugs, and specific predictors aimed at forecasting clinical response to treatment with four specific drugs: etanercept, ustekinumab, adalimumab, and methotrexate. We also develop two forms of prediction: one from detailed, platform-specific data and one from platform-independent, pathway-based data. We show that key biomarkers are associated with responses to drugs and doses and thus provide insight into the biology of pathogenesis reversion.
Prediction of fluid forces acting on a hand model in unsteady flow conditions.
Kudo, Shigetada; Yanai, Toshimasa; Wilson, Barry; Takagi, Hideki; Vennell, Ross
2008-01-01
The aim of this study was to develop a method to predict fluid forces acting on the human hand in unsteady flow swimming conditions. A mechanical system consisting of a pulley and chain mechanism and load cell was constructed to rotate a hand model in fluid flows. To measure the angular displacement of the hand model a potentiometer was attached to the axis of the rotation. The hand model was then fixed at various angles about the longitudinal axis of the hand model and rotated at different flow velocities in a swimming flume for 258 different trials to approximate a swimmer's stroke in unsteady flow conditions. Pressures were taken from 12 transducers embedded in the hand model at a sampling frequency of 200Hz. The resultant fluid force acting on the hand model was then determined on the basis of the kinetic and kinematic data taken from the mechanical system at the frequency of 200Hz. A stepwise regression analysis was applied to acquire higher order polynomial equations that predict the fluid force acting on the accelerating hand model from the 12 pressure values. The root mean square (RMS) difference between the resultant fluid force measured and that predicted from the single best-fit polynomial equation across all trials was 5N. The method developed in the present study accurately predicted the fluid forces acting on the hand model.
DPIV prediction of flow induced platelet activation-comparison to numerical predictions.
Raz, Sagi; Einav, Shmuel; Alemu, Yared; Bluestein, Danny
2007-04-01
Flow induced platelet activation (PA) can lead to platelet aggregation, deposition onto the blood vessel wall, and thrombus formation. PA was thoroughly studied under unidirectional flow conditions. However, in regions of complex flow, where the platelet is exposed to varying levels of shear stress for varying durations, the relationship between flow and PA is not well understood. Numerical models were developed for studying flow induced PA resulting from stress histories along Lagrangian trajectories in the flow field. However, experimental validation techniques such as Digital Particle Image Velocimetry (DPIV) were not extended to include such models. In this study, a general experimental tool for PA analysis by means of continuous DPIV was utilized and compared to numerical simulation in a model of coronary stenosis. A scaled up (5:1) 84% eccentric and axisymetric coronary stenosis model was used for analysis of shear stress and exposure time along particle trajectories. Flow induced PA was measured using the PA State (PAS) assay. An algorithm for computing the PA level in pertinent trajectories was developed as a tool for extracting information from DPIV measurements for predicting the flow induced thrombogenic potential. CFD, DPIV and PAS assay results agreed well in predicting the level of PA. In addition, the same trend predicted by the DPIV was measured in vitro using the Platelet Activity State (PAS) assay, namely, that the symmetric stenosis activated the platelets more as compared to the eccentric stenosis.
Ensemble stream flow predictions using the ECMWF forecasts
NASA Astrophysics Data System (ADS)
Kiczko, Adam; Romanowicz, Renata; Osuch, Marzena; Pappenberger, Florian; Karamuz, Emilia
2015-04-01
Floods and low flows in rivers are seasonal phenomena that can cause several problems to society. To anticipate high and low flow events, flow forecasts are crucial. They are of particular importance in mountainous catchments, where the lead time of forecasts is usually short. In order to prolong the forecast lead-time, numerical weather predictions (NWPs) are used as a hydrological model driving force. The forecasted flow is commonly given as one value, even though it is uncertain. There is an increasing interest in accounting for the uncertainty in flood early warning and decision support systems. When NWP are given in the form of ensembles, such as the ECMWF forecasts, the uncertainty of these forecasts can be accounted for. Apart from the forecast uncertainty the uncertainty related to the hydrological model used also plays an important role in the uncertainty of the final flow prediction. The aim of this study is the development of a stream flow prediction system for the Biała Tarnowska, a mountainous catchment in the south of Poland. We apply two different hydrological models. One is a conceptual HBV model for rainfall-flow predictions, applied within a Generalised Likelihood Uncertainty Estimation (GLUE) framework, the second is a data-based DBM model, adjusted for Polish conditions by adding the Soil Moisture Accounting (SMA) and snow-melt modules. Both models provide the uncertainty of the predictions, but the DBM approach is much more numerically efficient, therefore more suitable for the real-time forecasting.. The ECMWF forecasts require bias reduction in order to correspond to observations. Therefore we applied Quantile Mapping with and without seasonal adjustment for bias correction. Up to seven-days ahead forecast skills are compared using the Relative Operation Characteristic (ROC) graphs, for the flood warning and flood alarm flow value thresholds. The ECMWF forecasts are obtained from the project TIGGE (http
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.
Prediction of cavitating flow noise by direct numerical simulation
NASA Astrophysics Data System (ADS)
Seo, Jung H.; Moon, Young J.; Shin, Byeong Rog
2008-06-01
In this study, a direct numerical simulation procedure for the cavitating flow noise is presented. The compressible Navier-Stokes equations are written for the two-phase fluid, employing a density-based homogeneous equilibrium model with a linearly-combined equation of state. To resolve the linear and non-linear waves in the cavitating flow, a sixth-order compact central scheme is utilized with the selective spatial filtering technique. The present cavitation model and numerical methods are validated for two benchmark problems: linear wave convection and acoustic saturation in a bubbly flow. The cavitating flow noise is then computed for a 2D circular cylinder flow at Reynolds number based on a cylinder diameter, 200 and cavitation numbers, σ=0.7-2. It is observed that, at cavitation numbers σ=1 and 0.7, the cavitating flow and noise characteristics are significantly changed by the shock waves due to the coherent collapse of the cloud cavitation in the wake. To verify the present direct simulation and further analyze the sources of cavitation noise, an acoustic analogy based on a classical theory of Fitzpatrik and Strasberg is derived. The far-field noise predicted by direct simulation is well compared with that of acoustic analogy, and it also confirms the f-2 decaying rate in the spectrum, as predicted by the model of Fitzpatrik and Strasberg with the Rayleigh-Plesset equation.
Potential flow predictions for a flapping flat plate wing
NASA Astrophysics Data System (ADS)
Krishna, Swathi; Mulleners, Karen; Green, Melissa
2016-11-01
It is well established that the leading edge vortex is one of the major contributors to the generation of lift on a flapping insect wing. However, the contributions of the trailing edge vortices and the shear layer to unsteady force production mechanisms needs more investigation. The individual contribution of different flow structures is especially important if reliable theoretical predictions of lift and drag are to be made, that eventually assist in the design of micro air vehicles. The current work aims to distinguish different flow features of an unsteady flow field generated by a flapping wing in hover and to quantify the role played by them in the generation of aerodynamic forces. This is achieved by employing a semi-empirical potential flow model that allows for the calculation of lift by theoretically recreating the potential flow field based on the vortex strengths and locations obtained from phase-averaged particle image velocimetry (PIV) data. Individual flow structures are detected in the PIV data based on the vorticity contours. The theoretically predicted lift is compared with direct force measurements to demonstrate the utility and limitations of the model.
NASA Technical Reports Server (NTRS)
Hendricks, W. L.
1974-01-01
The slip conditions for a multicomponent mixture with diffusion, wall-catalyzed atom recombination and thermal radiation are derived, and simplified expressions for engineering applications are presented. The gas mixture may be in chemical nonequilibrium with finite-rate catalytic recombination occurring on the wall. These boundary conditions, which are used for rarefied flow regime flow field calculations, are shown to be necessary for accurate predictions of skin friction and heat transfer coefficients in the rarefied portion of the space shuttle trajectory.
Model-Based Predictive Control of Turbulent Channel Flow
NASA Astrophysics Data System (ADS)
Kellogg, Steven M.; Collis, S. Scott
1999-11-01
In recent simulations of optimal turbulence control, the time horizon over which the control is determined matches the time horizon over which the flow is advanced. A popular workhorse of the controls community, Model-Based Predictive Control (MBPC), suggests using longer predictive horizons than advancement windows. Including additional time information in the optimization may generate improved controls. When the advancement horizon is smaller than the predictive horizon, part of the optimization and resulting control are discarded. Although this inherent inefficiency may be justified by improved control predictions, it has hampered prior investigations of MBPC for turbulent flow due to the expense associated with optimal control based on Direct Numerical Simulation. The current approach overcomes this by using our optimal control formulation based on Large Eddy Simulation. This presentation summarizes the results of optimal control simulations for turbulent channel flow using various ratios of advancement and predictive horizons. These results provide clues as to the roles of foresight, control history, cost functional, and turbulence structures for optimal control of wall-bounded turbulence.
Predictions of Phase Distribution in Liquid-Liquid Two-Component Flow
NASA Astrophysics Data System (ADS)
Wang, Xia; Sun, Xiaodong; Duval, Walter M.
2011-06-01
Ground-based liquid-liquid two-component flow can be used to study reduced-gravity gas-liquid two-phase flows provided that the two liquids are immiscible with similar densities. In this paper, we present a numerical study of phase distribution in liquid-liquid two-component flows using the Eulerian two-fluid model in FLUENT, together with a one-group interfacial area transport equation (IATE) that takes into account fluid particle interactions, such as coalescence and disintegration. This modeling approach is expected to dynamically capture changes in the interfacial structure. We apply the FLUENT-IATE model to a water-Therminol 59® two-component vertical flow in a 25-mm inner diameter pipe, where the two liquids are immiscible with similar densities (3% difference at 20°C). This study covers bubbly (drop) flow and bubbly-to-slug flow transition regimes with area-averaged void (drop) fractions from 3 to 30%. Comparisons of the numerical results with the experimental data indicate that for bubbly flows, the predictions of the lateral phase distributions using the FLUENT-IATE model are generally more accurate than those using the model without the IATE. In addition, we demonstrate that the coalescence of fluid particles is dominated by wake entrainment and enhanced by increasing either the continuous or dispersed phase velocity. However, the predictions show disagreement with experimental data in some flow conditions for larger void fraction conditions, which fall into the bubbly-to-slug flow transition regime. We conjecture that additional fluid particle interaction mechanisms due to the change of flow regimes are possibly involved.
A disaggregation theory for predicting concentration gradient distributions in heterogeneous flows
NASA Astrophysics Data System (ADS)
Le Borgne, Tanguy; Huck, Peter; Dentz, Marco; Villermaux, Emmanuel
2016-04-01
Many transport processes occurring in fluid flows depend on concentration gradients, including a wide range of chemical reactions, such as mixing-driven precipitation, and biological processes, such as chemotaxis. A general framework for predicting the distribution of concentration gradients in heterogeneous flow fields is proposed based on a disaggregation theory. The evolution of concentration fields under the combined action of heterogeneous advection and diffusion is quantified from the analysis of the development and aggregation of elementary lamellar structures, which naturally form under the stretching action of flow fields. Therefore spatial correlations in concentrations can be estimated based on the understanding of the lamellae aggregation process that determine the concentration levels at neighboring spatial locations. Using this principle we quantify the temporal evolution of the concentration gradient Probability Density Functions in heterogeneous Darcy fields for arbitrary Peclet numbers. This approach is shown to provide accurate predictions of concentration gradient distributions for a range of flow systems, including turbulent flows and low Reynolds number porous media flows, for confined and dispersing mixtures.
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.
NASA Astrophysics Data System (ADS)
Hughes, Timothy J.; Kandathil, Shaun M.; Popelier, Paul L. A.
2015-02-01
As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G**, B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol-1, decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol-1.
Hughes, Timothy J; Kandathil, Shaun M; Popelier, Paul L A
2015-02-05
As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31G(**), B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1).
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
Multiscale prediction of patient-specific platelet function under flow.
Flamm, Matthew H; Colace, Thomas V; Chatterjee, Manash S; Jing, Huiyan; Zhou, Songtao; Jaeger, Daniel; Brass, Lawrence F; Sinno, Talid; Diamond, Scott L
2012-07-05
During thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A(2), recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient's platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye-loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y(1)/P2Y(12), TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donor's pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y(1) inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subject's platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.
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.
Spatial statistics for predicting flow through a rock fracture
Coakley, K.J.
1989-03-01
Fluid flow through a single rock fracture depends on the shape of the space between the upper and lower pieces of rock which define the fracture. In this thesis, the normalized flow through a fracture, i.e. the equivalent permeability of a fracture, is predicted in terms of spatial statistics computed from the arrangement of voids, i.e. open spaces, and contact areas within the fracture. Patterns of voids and contact areas, with complexity typical of experimental data, are simulated by clipping a correlated Gaussian process defined on a N by N pixel square region. The voids have constant aperture; the distance between the upper and lower surfaces which define the fracture is either zero or a constant. Local flow is assumed to be proportional to local aperture cubed times local pressure gradient. The flow through a pattern of voids and contact areas is solved using a finite-difference method. After solving for the flow through simulated 10 by 10 by 30 pixel patterns of voids and contact areas, a model to predict equivalent permeability is developed. The first model is for patterns with 80% voids where all voids have the same aperture. The equivalent permeability of a pattern is predicted in terms of spatial statistics computed from the arrangement of voids and contact areas within the pattern. Four spatial statistics are examined. The change point statistic measures how often adjacent pixel alternate from void to contact area (or vice versa ) in the rows of the patterns which are parallel to the overall flow direction. 37 refs., 66 figs., 41 tabs.
Prediction of strongly-heated internal gas flows
McEligot, D.M. ||; Shehata, A.M.; Kunugi, Tomoaki |
1997-12-31
The purposes of the present article are to remind practitioners why the usual textbook approaches may not be appropriate for treating gas flows heated from the surface with large heat fluxes and to review the successes of some recent applications of turbulence models to this case. Simulations from various turbulence models have been assessed by comparison to the measurements of internal mean velocity and temperature distributions by Shehata for turbulent, laminarizing and intermediate flows with significant gas property variation. Of about fifteen models considered, five were judged to provide adequate predictions.
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
On predicting debris flows in arid mountain belts
NASA Astrophysics Data System (ADS)
Stolle, Amelie; Langer, Maria; Blöthe, Jan Henrik; Korup, Oliver
2015-03-01
The use of topographic metrics for estimating the susceptibility to, and reconstructing the characteristics of, debris flows has a long research tradition, although largely devoted to humid mountainous terrain. The exceptional 2010 monsoonal rainstorms in the high-altitude mountain desert of Ladakh and Zanskar, NW India, were a painful reminder of how susceptible arid regions are to rainfall-triggered flash floods, landslides, and debris flows. The rainstorms of August 4-6 triggered numerous debris flows, killing 182 people, devastating 607 houses, and more than 10 bridges around Ladakh's capital of Leh. The lessons from this disaster motivated us to revisit methods of predicting (a) flow parameters such as peak discharge and maximum velocity from field and remote sensing data, and (b) the susceptibility to debris flows from catchment morphometry. We focus on quantifying uncertainties tied to these approaches. Comparison of high-resolution satellite images pre- and post-dating the 2010 rainstorm reveals the extent of damage and catastrophic channel widening. Computations based on these geomorphic markers indicate maximum flow velocities of 1.6-6.7 m s- 1 with runout of up to ~ 10 km on several alluvial fans that sustain most of the region's settlements. We estimate median peak discharges of 310-610 m3 s- 1, which are largely consistent with previous estimates. Monte Carlo-based error propagation for a single given flow-reconstruction method returns a variance in discharge similar to one derived from juxtaposing several different flow reconstruction methods. We further compare discriminant analysis, classification tree modelling, and Bayesian logistic regression to predict debris-flow susceptibility from morphometric variables of 171 catchments in the Ladakh Range. These methods distinguish between fluvial and debris flow-prone catchments at similar success rates, but Bayesian logistic regression allows quantifying uncertainties and relationships between potential
TIMP2•IGFBP7 biomarker panel accurately predicts acute kidney injury in high-risk surgical patients
Gunnerson, Kyle J.; Shaw, Andrew D.; Chawla, Lakhmir S.; Bihorac, Azra; Al-Khafaji, Ali; Kashani, Kianoush; Lissauer, Matthew; Shi, Jing; Walker, Michael G.; Kellum, John A.
2016-01-01
BACKGROUND Acute kidney injury (AKI) is an important complication in surgical patients. Existing biomarkers and clinical prediction models underestimate the risk for developing AKI. We recently reported data from two trials of 728 and 408 critically ill adult patients in whom urinary TIMP2•IGFBP7 (NephroCheck, Astute Medical) was used to identify patients at risk of developing AKI. Here we report a preplanned analysis of surgical patients from both trials to assess whether urinary tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor–binding protein 7 (IGFBP7) accurately identify surgical patients at risk of developing AKI. STUDY DESIGN We enrolled adult surgical patients at risk for AKI who were admitted to one of 39 intensive care units across Europe and North America. The primary end point was moderate-severe AKI (equivalent to KDIGO [Kidney Disease Improving Global Outcomes] stages 2–3) within 12 hours of enrollment. Biomarker performance was assessed using the area under the receiver operating characteristic curve, integrated discrimination improvement, and category-free net reclassification improvement. RESULTS A total of 375 patients were included in the final analysis of whom 35 (9%) developed moderate-severe AKI within 12 hours. The area under the receiver operating characteristic curve for [TIMP-2]•[IGFBP7] alone was 0.84 (95% confidence interval, 0.76–0.90; p < 0.0001). Biomarker performance was robust in sensitivity analysis across predefined subgroups (urgency and type of surgery). CONCLUSION For postoperative surgical intensive care unit patients, a single urinary TIMP2•IGFBP7 test accurately identified patients at risk for developing AKI within the ensuing 12 hours and its inclusion in clinical risk prediction models significantly enhances their performance. LEVEL OF EVIDENCE Prognostic study, level I. PMID:26816218
Prediction of the Hot Flow Stress Behavior of AA6063 Including Mg2Si Dissolution
NASA Astrophysics Data System (ADS)
Odoh, Daniel; Mahmoodkhani, Yahya; Whitney, Mark; Wells, Mary
2017-02-01
A constitutive model that includes the effect of Mg2Si dissolution during pre-deformation heating and holding has been developed for the prediction of the hot flow stress behavior of AA6063 aluminum alloy. The deformation behavior of homogenized AA6063 aluminum alloy was studied by performing compression tests on a Gleeble 3500 thermomechanical simulator at temperatures ranging from 400 to 550 °C and strain rates from 0.01 to 10 s-1. A one-dimensional model of particle dissolution in spherical coordinate system was developed to determine the Mg-Si solute content during pre-deformation heating and holding. Using the Mg solute content determined from the particle dissolution model, the flow stress during the deformation of AA6063 aluminum alloy at specific temperatures and strain rates was predicted using a modified hyperbolic sine equation. The constitutive model developed was found to be in good agreement with experimental measurements in this study as well as other experimental and model results published in the literature. A 14% increase in flow stress of the alloy was observed for an increase in hold time from 60 to 1500 s at 450 °C. This is due to increased deformation resistance of the alloy as the Mg-Si solute content increases. The modified hyperbolic sine equation developed in this study clearly shows that accounting for Mg-Si solute content improves the ability to accurately predict the flow stress behavior of AA6063 aluminum alloy.
Prediction of the Hot Flow Stress Behavior of AA6063 Including Mg2Si Dissolution
NASA Astrophysics Data System (ADS)
Odoh, Daniel; Mahmoodkhani, Yahya; Whitney, Mark; Wells, Mary
2017-03-01
A constitutive model that includes the effect of Mg2Si dissolution during pre-deformation heating and holding has been developed for the prediction of the hot flow stress behavior of AA6063 aluminum alloy. The deformation behavior of homogenized AA6063 aluminum alloy was studied by performing compression tests on a Gleeble 3500 thermomechanical simulator at temperatures ranging from 400 to 550 °C and strain rates from 0.01 to 10 s-1. A one-dimensional model of particle dissolution in spherical coordinate system was developed to determine the Mg-Si solute content during pre-deformation heating and holding. Using the Mg solute content determined from the particle dissolution model, the flow stress during the deformation of AA6063 aluminum alloy at specific temperatures and strain rates was predicted using a modified hyperbolic sine equation. The constitutive model developed was found to be in good agreement with experimental measurements in this study as well as other experimental and model results published in the literature. A 14% increase in flow stress of the alloy was observed for an increase in hold time from 60 to 1500 s at 450 °C. This is due to increased deformation resistance of the alloy as the Mg-Si solute content increases. The modified hyperbolic sine equation developed in this study clearly shows that accounting for Mg-Si solute content improves the ability to accurately predict the flow stress behavior of AA6063 aluminum alloy.
Ydreborg, Magdalena; Lisovskaja, Vera; Lagging, Martin; Brehm Christensen, Peer; Langeland, Nina; Buhl, Mads Rauning; Pedersen, Court; Mørch, Kristine; Wejstål, Rune; Norkrans, Gunnar; Lindh, Magnus; Färkkilä, Martti; Westin, Johan
2014-01-01
Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV) infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI) in the paper, was based on the model: Log-odds (predicting cirrhosis) = -12.17+ (age × 0.11) + (BMI (kg/m(2)) × 0.23) + (D7-lathosterol (μg/100 mg cholesterol)×(-0.013)) + (Platelet count (x10(9)/L) × (-0.018)) + (Prothrombin-INR × 3.69). The area under the ROC curve (AUROC) for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96). The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98). In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Nikolopoulos, Efthymios I.; Borga, Marco; Destro, Elisa; Marchi, Lorenzo
2015-04-01
Most of the work so far on the prediction of debris flow occurrence is focused on the identification of critical rainfall conditions. However, findings in the literature have shown that critical rainfall thresholds cannot always accurately identify debris flow occurrence, leading to false detections (positive or negative). One of the main reasons for this limitation is attributed to the fact that critical rainfall thresholds do not account for the characteristics of underlying land surface (e.g. geomorphology, moisture conditions, sediment availability, etc), which are strongly related to debris flow triggering. In addition, in areas where debris flows occur predominantly as a result of channel bed failure (as in many Alpine basins), the triggering factor is runoff, which suggests that identification of critical runoff conditions for debris flow prediction is more pertinent than critical rainfall. The primary objective of this study is to investigate the potential of a triggering index (TI), which combines variables related to runoff generation and channel morphology, for predicting debris flows occurrence. TI is based on a threshold criterion developed on past works (Tognacca et al., 2000; Berti and Simoni, 2005; Gregoretti and Dalla Fontana, 2008) and combines information on unit width peak flow, local channel slope and mean grain size. Estimation of peak discharge is based on the application of a distributed hydrologic model, while local channel slope is derived from a high-resolution (5m) DEM. Scaling functions of peak flows and channel width with drainage area are adopted since it is not possible to measure channel width or simulate peak flow at all channel nodes. TI values are mapped over the channel network thus allowing spatially distributed prediction but instead of identifying debris flow occurrence on single points, we identify their occurrence with reference to the tributary catchment involved. Evaluation of TI is carried out for five different basins
Block, Stephan; Fast, Björn Johansson; Lundgren, Anders; Zhdanov, Vladimir P.; Höök, Fredrik
2016-01-01
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. PMID:27658367
Cheng, Song; Chen, Ming-Hui; Zhang, Gang-Gang; Yu, Zhi-Biao; Liu, Dao-Feng; Xiong, Yong-Hua; Wei, Hua; Lai, Wei-Hua
2017-04-02
Escherichia coli O157:H7 is known to cause serious diseases including hemorrhagic colitis and hemolytic uremic syndrome. A gold nanoparticle lateral flow immunoassay (Au-LFIA) was used to detect Escherichia coli O157:H7 in ground pork samples. False-positive results were detected using Au-LFIA; a Citrobacterfreundii strain was isolated from the ground pork samples and identified by using CHROmagar(TM) plates, API 20E, and 16S RNA sequencing. Since C.freundii showed cross-reactivity with E. coli O157:H7 when Au-LFIA test strips were used, a novel method combining modified enrichment with a lateral flow immunoassay for accurate and convenient detection of E. coli O157:H7 in ground pork was developed in this study to minimize these false positives. MacConkey broth was optimized for E. coli O157:H7 enrichment and C.freundii inhibition by the addition of 5 mg/L potassium tellurite and 0.10 mg/L cefixime. Using the proposed modified enrichment procedure, the false-positive rate of ground pork samples spiked with 100 CFU/g C.freundii decreased to 5%.
Kawai, Soshi; Terashima, Hiroshi; Negishi, Hideyo
2015-11-01
This paper addresses issues in high-fidelity numerical simulations of transcritical turbulent flows at supercritical pressure. The proposed strategy builds on a tabulated look-up table method based on REFPROP database for an accurate estimation of non-linear behaviors of thermodynamic and fluid transport properties at the transcritical conditions. Based on the look-up table method we propose a numerical method that satisfies high-order spatial accuracy, spurious-oscillation-free property, and capability of capturing the abrupt variation in thermodynamic properties across the transcritical contact surface. The method introduces artificial mass diffusivity to the continuity and momentum equations in a physically-consistent manner in order to capture the steep transcritical thermodynamic variations robustly while maintaining spurious-oscillation-free property in the velocity field. The pressure evolution equation is derived from the full compressible Navier–Stokes equations and solved instead of solving the total energy equation to achieve the spurious pressure oscillation free property with an arbitrary equation of state including the present look-up table method. Flow problems with and without physical diffusion are employed for the numerical tests to validate the robustness, accuracy, and consistency of the proposed approach.
NASA Astrophysics Data System (ADS)
An, Zhe; Rey, Daniel; Ye, Jingxin; Abarbanel, Henry D. I.
2017-01-01
The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of the full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. We show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.
NASA Astrophysics Data System (ADS)
Liang, Yufeng; Vinson, John; Pemmaraju, Sri; Drisdell, Walter S.; Shirley, Eric L.; Prendergast, David
2017-03-01
Constrained-occupancy delta-self-consistent-field (Δ SCF ) methods and many-body perturbation theories (MBPT) are two strategies for obtaining electronic excitations from first principles. Using the two distinct approaches, we study the O 1 s core excitations that have become increasingly important for characterizing transition-metal oxides and understanding strong electronic correlation. The Δ SCF approach, in its current single-particle form, systematically underestimates the pre-edge intensity for chosen oxides, despite its success in weakly correlated systems. By contrast, the Bethe-Salpeter equation within MBPT predicts much better line shapes. This motivates one to reexamine the many-electron dynamics of x-ray excitations. We find that the single-particle Δ SCF approach can be rectified by explicitly calculating many-electron transition amplitudes, producing x-ray spectra in excellent agreement with experiments. This study paves the way to accurately predict x-ray near-edge spectral fingerprints for physics and materials science beyond the Bethe-Salpether equation.
NASA Astrophysics Data System (ADS)
Lemoine, X.; Sriram, S.; Kergen, R.
2011-05-01
ArcelorMittal continuously develops new steel grades (AHSS) with high performance for the automotive industry to improve the weight reduction and the passive safety. The wide market introduction of AHSS raises a new challenge for manufacturers in terms of material models in the prediction of forming—especially formability and springback. The relatively low uniform elongation, the high UTS and the low forming limit curve of these AHSS may cause difficulties in forming simulations. One of these difficulties is the consequence of the relatively low uniform elongation on the parameters identification of isotropic hardening model. Different experimental tests allow to reach large plastic strain levels (hydraulic bulge test, stack compression test, shear test…). After a description on how to determine the flow curve in these experimental tests, a comparison of the different flow curves is made for different steel grades. The ArcelorMittal identification protocol for hardening models is only based on stress-strain curves determined in uniaxial tension. Experimental tests where large plastic strain levels are reached are used to validate our identification protocol and to recommend some hardening models. Finally, the influence of isotropic hardening models and yield loci in forming prediction for AHSS steels will be presented.
Special session: computational predictability of natural convection flows in enclosures
Christon, M A; Gresho, P M; Sutton, S B
2000-08-14
Modern thermal design practices often rely on a ''predictive'' simulation capability--although predictability is rarely quantified and often difficult to confidently achieve in practice. The computational predictability of natural convection in enclosures is a significant issue for many industrial thermal design problems. One example of this is the design for mitigation of optical distortion due to buoyancy-driven flow in large-scale laser systems. In many instances the sensitivity of buoyancy-driven enclosure flows can be linked to the presence of multiple bifurcation points that yield laminar thermal convective processes that transition from steady to various modes of unsteady flow. This behavior is brought to light by a problem as ''simple'' as a differentially-heated tall rectangular cavity (8:1 height/width aspect ratio) filled with a Boussinesq fluid with Pr = 0.71--which defines, at least partially, the focus of this special session. For our purposes, the differentially-heated cavity provides a virtual fluid dynamics laboratory.
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.
NASA Astrophysics Data System (ADS)
Bonilla, Jose; Kalwa, Fritz; Händel, Falk; Binder, Martin; Stefan, Catalin
2016-04-01
The Dupuit-Thiem equation is normally used to assess flow towards a pumping well in unconfined aquifers under steady-state conditions. For the formulation of the equation it is assumed that flow is laminar, radial and horizontal towards the well. It is well known that these assumptions are not met in the vicinity of the well; some authors restrict the application of the equation only to a radius larger than 1.5-fold the aquifer thickness. In this study, the equation accuracy to predict the pressure head is evaluated as a simple and quick analytical method to describe the flow pattern for different injection rates in the LSAW. A laboratory scale aquifer-well system (LSAW) was implemented to study the aquifer recharge through wells. The LSAW consists of a 1.0 m-diameter tank with a height of 1.1 meters, filled with sand and a screened well in the center with a diameter of 0.025 m. A regulated outflow system establishes a controlled water level at the tank wall to simulate various aquifer thicknesses. The pressure head at the bottom of the tank along one axis can be measured to assess the flow profile every 0.1 m between the well and the tank wall. In order to evaluate the accuracy of the Dupuit-Thiem equation, a combination of different injection rates and aquifer thicknesses were simulated in the LSAW. Contrary to what was expected (significant differences between the measured and calculated pressure heads in the well), the absolute difference between the calculated and measured pressure head is less than 10%. Beside this, the highest differences are not observed in the well itself, but in the near proximity of it, at a radius of 0.1 m. The results further show that the difference between the calculated and measured pressure heads tends to decrease with higher flow rates. Despite its limitations (assumption of laminar and horizontal flow throughout the whole aquifer), the Dupuit-Thiem equation is considered to accurately represent the flow system in the LSAW.
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.
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.
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.
NASA Astrophysics Data System (ADS)
Margelowsky, G.; Foster, D.; Traykovski, P.; Felzenberg, J. A.
2010-12-01
The dynamics of wave-current and tidal flow bottom boundary layers are evaluated with a quasi-three-dimensional non-hydrostatic phase-resolving wave-current bottom boundary layer model, Dune. In each case, the model is evaluated with field observations of velocity profiles and seabed geometry. For wave-current boundary layers, the observations were obtained over a 26-day period in 13 m of water at the Martha’s Vineyard Coastal Observatory (MVCO, Edgartown, MA) in 2002 - 2003. Bedforms were orbital-scale ripples with wavelengths of 50-125 cm and heights of 5-20 cm with peak root-mean-square orbital velocities and mean flows typically ranging from 50-70 cm/s and 10-20 cm/s, respectively. The observations for tidal flows were obtained over a 3-day period in 13-16 m of water in Portsmouth Harbor (Portsmouth, NH) in 2008. Bedforms were dunes with wavelengths on the order of 1 m and heights on the order of 10 cm with typical peak tidal currents of approximately 1 m/s. The flow field is simulated with a finite volume approach to solve the Reynolds-Averaged Navier-Stokes equations with a k-ω 2nd order turbulence closure scheme. The model simulations are performed for a range of theoretical and observed bedforms to examine the boundary layer sensitivity to the resolution of the bottom roughness. The observed and predicted vertical velocity profiles are evaluated with correlations and Briar’s Skill scores over the range of data sets.
Christensen, S.; Cooley, R.L.
1999-01-01
We tested the accuracy of 95% individual prediction intervals for hydraulic heads, streamflow gains, and effective transmissivities computed by groundwater models of two Danish aquifers. To compute the intervals, we assumed that each predicted value can be written as the sum of a computed dependent variable and a random error. Testing was accomplished by using a cross-validation method and by using new field measurements of hydraulic heads and transmissivities that were not used to develop or calibrate the models. The tested null hypotheses are that the coverage probability of the prediction intervals is not significantly smaller than the assumed probability (95%) and that each tail probability is not significantly different from the assumed probability (2.5%). In all cases tested, these hypotheses were accepted at the 5% level of significance. We therefore conclude that for the groundwater models of two real aquifers the individual prediction intervals appear to be accurate.We tested the accuracy of 95% individual prediction intervals for hydraulic heads, streamflow gains, and effective transmissivities computed by groundwater models of two Danish aquifers. To compute the intervals, we assumed that each predicted value can be written as the sum of a computed dependent variable and a random error. Testing was accomplished by using a cross-validation method and by using new field measurements of hydraulic heads and transmissivities that were not used to develop or calibrate the models. The tested null hypotheses are that the coverage probability of the prediction intervals is not significantly smaller than the assumed probability (95%) and that each tail probability is not significantly different from the assumed probability (2.5%). In all cases tested, these hypotheses were accepted at the 5% level of significance. We therefore conclude that for the groundwater models of two real aquifers the individual prediction intervals appear to be accurate.
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.
OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers
NASA Astrophysics Data System (ADS)
Žliobaitė, Indrė; Bakker, Jorn; Pechenizkiy, Mykola
Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) boilers. If control systems fail to compensate the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. Accurate estimates of fuel consumption among other factors are needed for control systems operation. In this paper we address a problem of online mass flow prediction. Particularly, we consider the problems of (1) constructing the ground truth, (2) handling noise and abrupt concept drift, and (3) learning an accurate predictor. Last but not least we emphasize the importance of having the domain knowledge concerning the considered case. We demonstrate the performance of OMPF using real data sets collected from the experimental CFB boiler.
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...
Improving a prediction system for oil spills in the Yellow Sea: effect of tides on subtidal flow.
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.
Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.
2015-01-01
database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887
Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J
2015-09-30
database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior.
Parameter-free prediction of DNA dynamics in planar extensional flow of semidilute solutions
NASA Astrophysics Data System (ADS)
Sasmal, Chandi; Hsiao, Kai-Wen; Schroeder, Charles M.; Ravi Prakash, J.
2017-01-01
The dynamics of individual DNA molecules in semidilute solutions undergoing planar extensional flow is simulated using a multi-particle Brownian dynamics algorithm, which incorporates hydrodynamic and excluded volume interactions in the context of a coarse-grained bead-spring chain model for DNA. The successive fine-graining protocol [1, 2], in which simulation data acquired for bead-spring chains with increasing values of the number of beads $N_b$, is extrapolated to the number of Kuhn steps $N_\\text{K}$ in DNA (while keeping key physical parameters invariant), is used to obtain parameter-free predictions for a range of Weissenberg numbers and Hencky strain units. A systematic comparison of simulation predictions is carried out with the experimental observations of [3], who have recently used single molecule techniques to investigate the dynamics of dilute and semidilute solutions of $\\lambda$-phage DNA in planar extensional flow. In particular, they examine the response of individual chains to step-strain deformation followed by cessation of flow, thereby capturing both chain stretch and relaxation in a single experiment. The successive fine-graining technique is shown to lead to quantitatively accurate predictions of the experimental observations in the stretching and relaxation phases. Additionally, the transient chain stretch following a step strain deformation is shown to be much smaller in semidilute solutions than in dilute solutions, in agreement with experimental observations.
On the inconsistencies related to prediction of flow into an enclosing hood obstructed by a worker.
Karaismail, Ertan; Celik, Ismail
2010-06-01
The recirculating flow structures formed in the wake of a worker standing in front of an enclosing fume hood were numerically investigated. Two- and three-dimensional, unsteady, laminar/turbulent computations were performed for a Reynolds number (Re) range of 1.0 x 10(3)-1.0 x 10(5). The standard k-epsilon, Renormalization group (RNG) k-epsilon, and Shear Stress Transport (SST) k-omega models were used in Unsteady Reynolds Averaged Navier-Stokes (URANS) computations, and the results were compared with each other and also with the previous predictions reported in the literature. Numerical issues regarding the grid convergence and the inadequacies of turbulence models that may come into play at low Reynolds numbers were addressed. On the whole, SST k-omega model was found to be promising for qualitatively accurate prediction of both steady and unsteady recirculatory flow patterns in the wake of the worker. On the other hand, the standard and RNG k-epsilon models failed in prediction of anticipated unsteadiness at low Reynolds numbers. In a more realistic three-dimensional simulation with SST k-omega model, the anticipated unsteady and recirculating flow field in the wake of the worker was captured. Present results seem to qualitatively agree with the deductions made from experimental analyses in the literature while conflicting with some aspects of the previously reported numerical results. The apparent inconsistencies observed between the current results and those published in the literature were elucidated.
Predictions of Flow Duration Curve Shifts Due to Anthropogenic and Climatic Changes
NASA Astrophysics Data System (ADS)
Henry, N. F.; Kroll, C. N.; Endreny, T. A.
2014-12-01
Methods are needed to understand and predict streamflows in systems undergoing anthropogenic and climatic alteration. This study is motivated by a need to develop methods to accurately estimate historical and future flow regimes of the Delaware River to inform management decisions for the endangered dwarf wedgemussel (Alasmidonta heterodon). Many streamflow regimes in this system have undergone substantial alteration within the past 100 years. Here, flow duration curves (FDCs), a common hydrologic tool used to assess flow regimes, are created and examined at 145 Delaware River Basin catchments. These catchments have experienced various hydrologic alterations, including land use changes, water withdrawals, and river regulation due to dams and reservoirs. Linear regression models are developed for various percentile flows across a FDC. These models use watershed characteristics that describe observed flow regimes in altered as well as unaltered systems. The characteristics that have the most significant influence on the shape of the FDCs are then identified and isolated as descriptors of the alteration. Once these models are developed to include these key variables, given a specific alteration (e.g. fresh water withdrawals, change in annual precipitation, etc.), a new flow regime can be estimated. Preliminary results indicate that certain watershed characteristics related to alteration (e.g. magnitude of land fragmentation, water withdrawals, hydrologic disturbance index) are significant in our models and influence FDC patterns. The results of this study may prove to have broader applications in regards to water resources management as the methods developed here may serve as a predictive tool as human interference and climatic changes continue to alter flow regimes.
NASA Astrophysics Data System (ADS)
Lau, K.-C.; Ng, C. Y.
2006-01-01
The ionization energies (IEs) for the 2-propyl (2-C3H7), phenyl (C6H5), and benzyl (C6H5CH2) radicals have been calculated by the wave-function-based ab initio CCSD(T)/CBS approach, which involves the approximation to the complete basis set (CBS) limit at the coupled cluster level with single and double excitations plus quasiperturbative triple excitation [CCSD(T)]. The zero-point vibrational energy correction, the core-valence electronic correction, and the scalar relativistic effect correction have been also made in these calculations. Although a precise IE value for the 2-C3H7 radical has not been directly determined before due to the poor Franck-Condon factor for the photoionization transition at the ionization threshold, the experimental value deduced indirectly using other known energetic data is found to be in good accord with the present CCSD(T)/CBS prediction. The comparison between the predicted value through the focal-point analysis and the highly precise experimental value for the IE(C6H5CH2) determined in the previous pulsed field ionization photoelectron (PFI-PE) study shows that the CCSD(T)/CBS method is capable of providing an accurate IE prediction for C6H5CH2, achieving an error limit of 35 meV. The benchmarking of the CCSD(T)/CBS IE(C6H5CH2) prediction suggests that the CCSD(T)/CBS IE(C6H5) prediction obtained here has a similar accuracy of 35 meV. Taking into account this error limit for the CCSD(T)/CBS prediction and the experimental uncertainty, the CCSD(T)/CBS IE(C6H5) value is also consistent with the IE(C6H5) reported in the previous HeI photoelectron measurement. Furthermore, the present study provides support for the conclusion that the CCSD(T)/CBS approach with high-level energy corrections can be used to provide reliable IE predictions for C3-C7 hydrocarbon radicals with an uncertainty of +/-35 meV. Employing the atomization scheme, we have also computed the 0 K (298 K) heats of formation in kJ/mol at the CCSD(T)/CBS level for 2-C3H7
Predicting the natural flow regime: Models for assessing hydrological alteration in streams
Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.
2010-01-01
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
Geostatistical prediction of flow-duration curves in an index-flow framework
NASA Astrophysics Data System (ADS)
Pugliese, A.; Castellarin, A.; Brath, A.
2014-09-01
An empirical period-of-record flow-duration curve (FDC) describes the percentage of time (duration) in which a given streamflow was equaled or exceeded over an historical period of time. In many practical applications one has to construct FDCs in basins that are ungauged or where very few observations are available. We present an application strategy of top-kriging, which makes the geostatistical procedure capable of predicting FDCs in ungauged catchments. Previous applications of top-kriging mainly focused on the prediction of point streamflow indices (e.g. flood quantiles, low-flow indices, etc.); here the procedure is used to predict the entire curve in ungauged sites as a weighted average of standardised empirical FDCs through the traditional linear-weighting scheme of kriging methods. In particular, we propose to standardise empirical FDCs by a reference index-flow value (i.e. mean annual flow, or mean annual precipitation × the drainage area) and to compute the overall negative deviation of the curves from this reference value. We then propose to use these values, which we term total negative deviation (TND), for expressing the hydrological similarity between catchments and for deriving the geostatistical weights. We focus on the prediction of FDCs for 18 unregulated catchments located in central Italy, and we quantify the accuracy of the proposed technique under various operational conditions through an extensive cross-validation and sensitivity analysis. The cross-validation points out that top-kriging is a reliable approach for predicting FDCs with Nash-Sutcliffe efficiency measures ranging from 0.85 to 0.96 (depending on the model settings) very low biases over the entire duration range, and an enhanced representation of the low-flow regime relative to other regionalisation models that were recently developed for the same study region.
Arcon, Juan Pablo; Defelipe, Lucas A; Modenutti, Carlos P; López, Elias D; Alvarez-Garcia, Daniel; Barril, Xavier; Turjanski, Adrián G; Martí, Marcelo A
2017-03-31
One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.
Integrated uncertainty assessment of flow predictions in a Swiss catchment
NASA Astrophysics Data System (ADS)
Honti, M.; Stamm, C.; Reichert, P.
2012-04-01
, in an aggregated sense the model performed satisfactorily with about 10% discharge error along the flow duration curve. Although the uncertainty of future inputs was even bigger, the model results suggest that on the system level the magnitude of expected changes exceed the present uncertainty. Despite the varying predictions on the seasonal distribution and amount of precipitation between the model chains, there was a consensus that extreme events (floods and low flow periods) are likely to get more severe. The results suggest that by defining the predicted set of indicators we implicitly influence whether the predicted changes will be statistically different from the present or will be dissolved in the existing uncertainty.
Fast reconstruction and prediction of frozen flow turbulence based on structured Kalman filtering.
Fraanje, Rufus; Rice, Justin; Verhaegen, Michel; Doelman, Niek
2010-11-01
Efficient and optimal prediction of frozen flow turbulence using the complete observation history of the wavefront sensor is an important issue in adaptive optics for large ground-based telescopes. At least for the sake of error budgeting and algorithm performance, the evaluation of an accurate estimate of the optimal performance of a particular adaptive optics configuration is important. However, due to the large number of grid points, high sampling rates, and the non-rationality of the turbulence power spectral density, the computational complexity of the optimal predictor is huge. This paper shows how a structure in the frozen flow propagation can be exploited to obtain a state-space innovation model with a particular sparsity structure. This sparsity structure enables one to efficiently compute a structured Kalman filter. By simulation it is shown that the performance can be improved and the computational complexity can be reduced in comparison with auto-regressive predictors of low order.
Webb-Robertson, Bobbie-Jo M.; Cannon, William R.; Oehmen, Christopher S.; Shah, Anuj R.; Gurumoorthi, Vidhya; Lipton, Mary S.; Waters, Katrina M.
2008-07-01
Motivation: The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares these profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic). Results: We present a Support Vector Machine (SVM) model that uses a simple descriptor space based on 35 properties of amino acid content, charge, hydrophilicity, and polarity for the quantitative prediction of proteotypic peptides. Using three independently derived AMT databases (Shewanella oneidensis, Salmonella typhimurium, Yersinia pestis) for training and validation within and across species, the SVM resulted in an average accuracy measure of ~0.8 with a standard deviation of less than 0.025. Furthermore, we demonstrate that these results are achievable with a small set of 12 variables and can achieve high proteome coverage. Availability: http://omics.pnl.gov/software/STEPP.php
Predicting Turbulent Convective Heat Transfer in Fully Developed Duct Flows
NASA Technical Reports Server (NTRS)
Rokni, Masoud; Gatski, Thomas B.
2001-01-01
The performance of an explicit algebraic stress model (EASM) is assessed in predicting the turbulent flow and forced heat transfer in both straight and wavy ducts, with rectangular, trapezoidal and triangular cross-sections, under fully developed conditions. A comparison of secondary flow patterns. including velocity vectors and velocity and temperature contours, are shown in order to study the effect of waviness on flow dynamics, and comparisons between the hydraulic parameters. Fanning friction factor and Nusselt number, are also presented. In all cases. isothermal conditions are imposed on the duct walls, and the turbulent heat fluxes are modeled using gradient-diffusion type models. The formulation is valid for Reynolds numbers up to 10(exp 5) and this minimizes the need for wall functions that have been used with mixed success in previous studies of complex duct flows. In addition, the present formulation imposes minimal demand on the number of grid points without any convergence or stability problems. Criteria in terms of heat transfer and friction factor needed to choose the optimal wavy duct cross-section for industrial applications among the ones considered are discussed.
Flow and noise predictions for the tandem cylinder aeroacoustic benchmarka)
NASA Astrophysics Data System (ADS)
Brès, Guillaume A.; Freed, David; Wessels, Michael; Noelting, Swen; Pérot, Franck
2012-03-01
Flow and noise predictions for the tandem cylinder benchmark are performed using lattice Boltzmann and Ffowcs Williams-Hawkings methods. The numerical results are compared to experimental measurements from the Basic Aerodynamic Research Tunnel and Quiet Flow Facility (QFF) at NASA Langley Research Center. The present study focuses on two configurations: the first configuration corresponds to the typical setup with uniform inflow and spanwise periodic boundary condition. To investigate installation effects, the second configuration matches the QFF setup and geometry, including the rectangular open jet nozzle, and the two vertical side plates mounted in the span to support the test models. For both simulations, the full span of 16 cylinder diameters is simulated, matching the experimental dimensions. Overall, good agreement is obtained with the experimental surface data, flow field, and radiated noise measurements. In particular, the presence of the side plates significantly reduces the excessive spanwise coherence observed with periodic boundary conditions and improves the predictions of the tonal peak amplitude in the far-field noise spectra. Inclusion of the contributions from the side plates in the calculation of the radiated noise shows an overall increase in the predicted spectra and directivity, leading to a better match with the experimental measurements. The measured increase is about 1 to 2 dB at the main shedding frequency and harmonics, and is likely caused by reflections on the spanwise side plates. The broadband levels are also slightly higher by about 2 to 3 dB, likely due to the shear layers from the nozzle exit impacting the side plates.
Zhang, Jin-Feng; Chen, Yao; Lin, Guo-Shi; Zhang, Jian-Dong; Tang, Wen-Long; Huang, Jian-Huang; Chen, Jin-Shou; Wang, Xing-Fu; Lin, Zhi-Xiong
2016-06-01
Interferon-induced protein with tetratricopeptide repeat 1 (IFIT1) plays a key role in growth suppression and apoptosis promotion in cancer cells. Interferon was reported to induce the expression of IFIT1 and inhibit the expression of O-6-methylguanine-DNA methyltransferase (MGMT).This study aimed to investigate the expression of IFIT1, the correlation between IFIT1 and MGMT, and their impact on the clinical outcome in newly diagnosed glioblastoma. The expression of IFIT1 and MGMT and their correlation were investigated in the tumor tissues from 70 patients with newly diagnosed glioblastoma. The effects on progression-free survival and overall survival were evaluated. Of 70 cases, 57 (81.4%) tissue samples showed high expression of IFIT1 by immunostaining. The χ(2) test indicated that the expression of IFIT1 and MGMT was negatively correlated (r = -0.288, P = .016). Univariate and multivariate analyses confirmed high IFIT1 expression as a favorable prognostic indicator for progression-free survival (P = .005 and .017) and overall survival (P = .001 and .001), respectively. Patients with 2 favorable factors (high IFIT1 and low MGMT) had an improved prognosis as compared with others. The results demonstrated significantly increased expression of IFIT1 in newly diagnosed glioblastoma tissue. The negative correlation between IFIT1 and MGMT expression may be triggered by interferon. High IFIT1 can be a predictive biomarker of favorable clinical outcome, and IFIT1 along with MGMT more accurately predicts prognosis in newly diagnosed glioblastoma.
USM3D Predictions of Supersonic Nozzle Flow
NASA Technical Reports Server (NTRS)
Carter, Melissa B.; Elmiligui, Alaa A.; Campbell, Richard L.; Nayani, Sudheer N.
2014-01-01
This study focused on the NASA Tetrahedral Unstructured Software System CFD code (USM3D) capability to predict supersonic plume flow. Previous studies, published in 2004 and 2009, investigated USM3D's results versus historical experimental data. This current study continued that comparison however focusing on the use of the volume souring to capture the shear layers and internal shock structure of the plume. This study was conducted using two benchmark axisymmetric supersonic jet experimental data sets. The study showed that with the use of volume sourcing, USM3D was able to capture and model a jet plume's shear layer and internal shock structure.
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.
Geostatistical prediction of flow-duration curves in an index-flow framework
NASA Astrophysics Data System (ADS)
Pugliese, Alessio; Castellarin, Attilio; Brath, Armando
2014-05-01
An empirical period-of-record Flow-Duration Curve (FDC) describes the percentage of time (duration) in which a given streamflow was equaled or exceeded over an historical period of time. FDCs have always attracted a great deal of interest in engineering applications because of their ability to provide a simple yet comprehensive graphical view of the overall historical variability of streamflows in a river basin, from floods to low-flows. Nevertheless, in many practical applications one has to construct FDC in basins that are ungauged or where very few observations are available. We present in this study an application strategy of Topological kriging (or Top-kriging), which makes the geostatistical procedure capable of predicting flow-duration curves (FDCs) in ungauged catchments. Previous applications of Top-kriging mainly focused on the prediction of point streamflow indices (e.g. flood quantiles, low-flow indices, etc.). In this study Top-kriging is used to predict FDCs in ungauged sites as a weighted average of standardised empirical FDCs through the traditional linear-weighting scheme of kriging methods. Our study focuses on the prediction of FDCs for 18 unregulated catchments located in Central Italy, for which daily streamflow series with length from 5 to 40 years are available, together with information on climate referring to the same time-span of each daily streamflow sequence. Empirical FDCs are standardised by a reference index-flow value (i.e. mean annual flow, or mean annual precipitation times the catchment drainage area) and the overall deviation of the curves from this reference value is then used for expressing the hydrological similarity between catchments and for deriving the geostatistical weights. We performed an extensive leave-one-out cross-validation to quantify the accuracy of the proposed technique, and to compare it to traditional regionalisation models that were recently developed for the same study region. The cross-validation points
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
Evaluating the use of high-resolution numerical weather forecast for debris flow prediction.
NASA Astrophysics Data System (ADS)
Nikolopoulos, Efthymios I.; Bartsotas, Nikolaos S.; Borga, Marco; Kallos, George
2015-04-01
The sudden occurrence combined with the high destructive power of debris flows pose a significant threat to human life and infrastructures. Therefore, developing early warning procedures for the mitigation of debris flows risk is of great economical and societal importance. Given that rainfall is the predominant factor controlling debris flow triggering, it is indisputable that development of effective debris flows warning procedures requires accurate knowledge of the properties (e.g. duration, intensity) of the triggering rainfall. Moreover, efficient and timely response of emergency operations depends highly on the lead-time provided by the warning systems. Currently, the majority of early warning systems for debris flows are based on nowcasting procedures. While the latter may be successful in predicting the hazard, they provide warnings with a relatively short lead-time (~6h). Increasing the lead-time is necessary in order to improve the pre-incident operations and communication of the emergency, thus coupling warning systems with weather forecasting is essential for advancing early warning procedures. In this work we evaluate the potential of using high-resolution (1km) rainfall fields forecasted with a state-of-the-art numerical weather prediction model (RAMS/ICLAMS), in order to predict the occurrence of debris flows. Analysis is focused over the Upper Adige region, Northeast Italy, an area where debris flows are frequent. Seven storm events that generated a large number (>80) of debris flows during the period 2007-2012 are analyzed. Radar-based rainfall estimates, available from the operational C-band radar located at Mt Macaion, are used as the reference to evaluate the forecasted rainfall fields. Evaluation is mainly focused on assessing the error in forecasted rainfall properties (magnitude, duration) and the correlation in space and time with the reference field. Results show that the forecasted rainfall fields captured very well the magnitude and
NASA Astrophysics Data System (ADS)
Magnoli, M. V.
2016-11-01
An accurate prediction of pressure fluctuations in Francis turbines has become more and more important over the last years, due to the continuously increasing requirements of wide operating range capability. Depending on the machine operator, Francis turbines are operated at full load, part load, deep part load and speed-no-load. Each of these operating conditions is associated with different flow phenomena and pressure fluctuation levels. The better understanding of the pressure fluctuation phenomena and the more accurate prediction of their amplitude along the hydraulic surfaces can significantly contribute to improve the hydraulic and mechanical design of Francis turbines, their hydraulic stability and their reliability. With the objective to acquire a deeper knowledge about the pressure fluctuation characteristics in Francis turbines and to improve the accuracy of numerical simulation methods used for the prediction of the dynamic fluid flow through the turbine, pressure fluctuations were experimentally measured in a mid specific speed model machine. The turbine runner of a model machine with specific speed around nq,opt = 60 min-1, was instrumented with dynamic pressure transducers at the runner blades. The model machine shaft was equipped with a telemetry system able to transmit the measured pressure values to the data acquisition system. The transient pressure signal was measured at multiple locations on the blade and at several operating conditions. The stored time signal was also evaluated in terms of characteristic amplitude and dominating frequency. The dynamic fluid flow through the hydraulic turbine was numerically simulated with computational fluid dynamics (CFD) for selected operating points. Among others, operating points at full load, part load and deep part load were calculated. For the fluid flow numerical simulations more advanced turbulence models were used, such as the detached eddy simulation (DES) and scale adaptive simulation (SAS). At the
Introduction: Prediction of F-16XL Flight Flow Physics
NASA Technical Reports Server (NTRS)
Lamar, John E.
2009-01-01
This special section is the result of fruitful endeavors by an international group of researchers in industry, government laboratories and university-led efforts to improve the technology readiness level of their CFD solvers through comparisons with flight data collected on the F-16XL-1 aircraft at a variety of test conditions. These 1996 flight data were documented and detailed the flight-flow physics of this aircraft through surface tufts and pressures, boundary-layer rakes and skin-friction measurements. The flight project was called the Cranked Wing Aerodynamics Project (CAWAP), due to its leading-edge sweep crank (70 degrees inboard, 50 degrees outboard), and served as a basis for the International comparisons to be made, called CAWAPI. This highly focused effort was one of two vortical flow studies facilitated by the NATO Research and Technology Organization through its Applied Vehicle Panel with a title of Understanding and Modeling Vortical Flows to Improve the Technology Readiness Level for Military Aircraft. It was given a task group number of AVT-113 and had an official start date of Spring 2003. The companion part of this task group dealt with fundamentals of vortical flow from both an experimental and numerical perspective on an analytically describable 65 degree delta-wing model for which much surface pressure data had already been measured at NASA Langley Research Center at a variety of Mach and Reynolds numbers and is called the Vortex Flow Experiment - 2 (VFE-2). These two parts or facets helped one another in understanding the predictions and data that had been or were being collected.
Pressure drop and thrust predictions for transonic micronozzle flows
NASA Astrophysics Data System (ADS)
Gomez, J.; Groll, R.
2016-02-01
In this paper, the expansion of xenon, argon, krypton, and neon gases through a Laval nozzle is studied experimentally and numerically. The pressurized gases are accelerated through the nozzle into a vacuum chamber in an attempt to simulate the operating conditions of a cold-gas thruster for attitude control of a micro-satellite. The gases are evaluated at several mass flow rates ranging between 0.178 mg/s and 3.568 mg/s. The Re numbers are low (8-256) and the estimated values of Kn number lie between 0.33 and 0.02 (transition and slip-flow regime). Direct Simulation Monte Carlo (DSMC) and continuum-based simulations with a no-slip boundary condition are performed. The DSMC and the experimental results show good agreement in the range Kn > 0.1, while the Navier-Stokes results describe the experimental data more accurately for Kn < 0.05. Comparison between the experimental and Navier-Stokes results shows high deviations at the lower mass flow rates and higher Kn numbers. A relation describing the deviation of the pressure drop through the nozzle as a function of Kn is obtained. For gases with small collision cross sections, the experimental pressure results deviate more strongly from the no-slip assumption. From the analysis of the developed function, it is possible to correct the pressure results for the studied gases, both in the slip-flow and transition regimes, with four gas-independent accommodation coefficients. The thrust delivered by the cold-gas thruster and the specific impulse is determined based on the numerical results. Furthermore, an increase of the thickness of the viscous boundary layer through the diffuser of the micronozzle is observed. This results in a shock-less decrease of the Mach number and the flow velocity, which penalizes thrust efficiency. The negative effect of the viscous boundary layer on thrust efficiency can be lowered through higher values of Re and a reduction of the diffuser length.
Flow field predictions for a slab delta wing at incidence
NASA Technical Reports Server (NTRS)
Conti, R. J.; Thomas, P. D.; Chou, Y. S.
1972-01-01
Theoretical results are presented for the structure of the hypersonic flow field of a blunt slab delta wing at moderately high angle of attack. Special attention is devoted to the interaction between the boundary layer and the inviscid entropy layer. The results are compared with experimental data. The three-dimensional inviscid flow is computed numerically by a marching finite difference method. Attention is concentrated on the windward side of the delta wing, where detailed comparisons are made with the data for shock shape and surface pressure distributions. Surface streamlines are generated, and used in the boundary layer analysis. The three-dimensional laminar boundary layer is computed numerically using a specially-developed technique based on small cross-flow in streamline coordinates. In the rear sections of the wing the boundary layer decreases drastically in the spanwise direction, so that it is still submerged in the entropy layer at the centerline, but surpasses it near the leading edge. Predicted heat transfer distributions are compared with experimental data.
Power flow prediction in vibrating systems via model reduction
NASA Astrophysics Data System (ADS)
Li, Xianhui
This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.
ERIC Educational Resources Information Center
Salley, Charles D.
Accurate enrollment forecasts are a prerequisite for reliable budget projections. This is because tuition payments make up a significant portion of a university's revenue, and anticipated revenue is the immediate constraint on current operating expenditures. Accurate forecasts are even more critical to revenue projections when a university's…
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.
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.
Engineering approach to the prediction of shock patterns in bounded high-speed flows
NASA Technical Reports Server (NTRS)
Azevedo, D. J.; Liu, Ching Shi
1993-01-01
A two-dimensional symmetric wedge configuration representative of a single high-speed intake in steady flow was investigated. The analysis presented here is intended as an engineering approach for estimating certain features of the internal shock system. The primary interest here is the prediction of the size and location of the almost-normal shock wave that develops when the leading-edge shocks intersect at angles above a certain critical value that is less than the wedge detachment angle. The almost-normal shock wave is frequently referred to as the 'Mach stem', Parametric studies enabled the sensitivity of the Mach stem height to various flowfield parameters to be examined, thus indicating how accurately these parameters must be measured in a given experiment. Results of these predictions were compared with those of a steady-flow experiment performed at nominal freestream Mach numbers from 2.8 to 5. The predicted stem heights were consistently lower than the mean experimental values, attributable both to experimental uncertainties and to certain simplifying assumptions used in the analysis. Modification of these assumptions to better represent the test environment improved the analytical results.
A validated predictive model of coronary fractional flow reserve
Huo, Yunlong; Svendsen, Mark; Choy, Jenny Susana; Zhang, Z.-D.; Kassab, Ghassan S.
2012-01-01
Myocardial fractional flow reserve (FFR), an important index of coronary stenosis, is measured by a pressure sensor guidewire. The determination of FFR, only based on the dimensions (lumen diameters and length) of stenosis and hyperaemic coronary flow with no other ad hoc parameters, is currently not possible. We propose an analytical model derived from conservation of energy, which considers various energy losses along the length of a stenosis, i.e. convective and diffusive energy losses as well as energy loss due to sudden constriction and expansion in lumen area. In vitro (constrictions were created in isolated arteries using symmetric and asymmetric tubes as well as an inflatable occluder cuff) and in vivo (constrictions were induced in coronary arteries of eight swine by an occluder cuff) experiments were used to validate the proposed analytical model. The proposed model agreed well with the experimental measurements. A least-squares fit showed a linear relation as (Δp or FFR)experiment = a(Δp or FFR)theory + b, where a and b were 1.08 and −1.15 mmHg (r2 = 0.99) for in vitro Δp, 0.96 and 1.79 mmHg (r2 = 0.75) for in vivo Δp, and 0.85 and 0.1 (r2 = 0.7) for FFR. Flow pulsatility and stenosis shape (e.g. eccentricity, exit angle divergence, etc.) had a negligible effect on myocardial FFR, while the entrance effect in a coronary stenosis was found to contribute significantly to the pressure drop. We present a physics-based experimentally validated analytical model of coronary stenosis, which allows prediction of FFR based on stenosis dimensions and hyperaemic coronary flow with no empirical parameters. PMID:22112650
Prediction of surface flow hydrology and sediment retention upslope of a vetiver buffer strip
NASA Astrophysics Data System (ADS)
Hussein, Janet; Yu, Bofu; Ghadiri, Hossein; Rose, Calvin
2007-05-01
SummaryVegetated buffer strips are widely used to reduce fluxes of eroding soil and associated chemicals, from hillslopes into waterways. Sediment retention by buffers is time-dependent, with its effectiveness changing with the deposition process. Our research focuses on settling of sediment upslope of stiff grass buffers at three slopes, under subcritical flow conditions. A new model is developed which couples the hydraulics, sediment deposition and subsequent adjustment to topography in order to predict water and sediment profiles upslope of a buffer with time. Experiments to test the model were carried out in the Griffith University Tilting-Flume Simulated Rainfall facility using subcritical flows at 1%, 3% and 5% slopes. Water and sediment profiles were measured at different times as Vertisol sediment was introduced upslope of a vetiver grass strip. A region of increased flow depth (backwater) was produced upslope of the strip which increased in depth and decreased in length with increasing slope. Backwater height could be predicted from flow rates and thus could be used as an input for the model in the absence of experimental data. As slope increased, sediment was deposited closer to the grass strip, moving into the grass strip itself at 5% slope. The grass strip was less effective in reducing sediment in the outflow as slope increased and differences between slopes were significant. Model prediction of water and sediment profiles compared reasonably well with measured data, giving low root mean square errors and high coefficients of model efficiency. Masses of deposited sediment were generally simulated within 20% of measured values. However, simulated particle size distributions of deposited sediment were less accurate.
On kinematics and flow velocity prediction in step-pool channels
NASA Astrophysics Data System (ADS)
D'Agostino, V.; Michelini, T.
2015-06-01
This paper verifies methods for the prediction of mean flow velocity at the reach scale in mountain streams, investigating the kinematics of a series of two small-scale artificial step-pool sequences and a transitional reach between plane-bed and step-pool under well-controlled hydraulic conditions, and improving the estimation of the energy expenditure between the step crest and the downstream pool. Experimental data were collected using three fish ladder reaches with slopes between 2.6 and 10%. Four types of field measurements were conducted: topographical surveys to extract the thalweg profiles and cross-sectional geometry of reference cross sections; grain size analyses of the bed surface; steady state runs with a given flow rate (0.005-0.234 m3/s), and surveying of the water profile in the most significant cross sections. The following main conclusions were reached: (i) the dominance of spill resistance at the lowest discharge (pool water depth-step height ratios of 0.4) causes primary dimensionless head losses of up to 80%, and these losses progressively decrease to approximately 40% when the water discharge and related pool water depth submerge the upstream step height. A specific predictive equation for the head loss was calibrated and then verified via data from the Rio Cordon. (ii) The verification of literature-sourced equations to predict the reach-averaged flow velocity provided suitable results for several of these equations indicating that the use of a specific step-pool equation does not appear to be crucial to achieving accurate predictions.
NASA Astrophysics Data System (ADS)
Iden, Sascha; Reineke, Daniela; Koonce, Jeremy; Berli, Markus; Durner, Wolfgang
2015-04-01
A reliable quantification of the soil water balance in semi-arid regions requires an accurate determination of bare soil evaporation. Modeling of soil water movement in relatively dry soils and the quantitative prediction of evaporation rates and groundwater recharge pose considerable challenges in these regions. Actual evaporation from dry soil cannot be predicted without detailed knowledge of the complex interplay between liquid, vapor and heat flow and soil hydraulic properties exert a strong influence on evaporation rates during stage-two evaporation. We have analyzed data from the SEPHAS lysimeter facility in Boulder City (NV) which was installed to investigate the near-surface processes of water and energy exchange in desert environments. The scientific instrumentation consists of 152 sensors per Lysimeter which measured soil temperature, soil water content, and soil water potential. Data from three weighing lysimeters (3 m long, surface area 4 m2) were used to identifiy effective soil hydraulic properties of the disturbed soil monoliths by inverse modeling with the Richards equation assuming isothermal flow conditions. Results indicate that the observed soil water content in 8 different soil depths can be well matched for all three lysimeters and that the effective soil hydraulic properties of the three lysimeters agree well. These results could only be obtained with a flexible model of the soil hydraulic properties which guaranteed physical plausibility of water retention towards complete dryness and accounted for capillary, film and isothermal vapor flow. Conversely, flow models using traditional parameterizations of the soil hydraulic properties were not able to match the observed evaporation fluxes and water contents. After identifying the system properties by inverse modeling, we checked the possibility to forecast evaporation rates by running a fully coupled water, heat and vapor flow model which solved the energy balance of the soil surface. In these
Flow and transport simulation models for prediction of chlorine contact tank flow-through curves.
Wang, Hong; Shao, Xuejun; Falconer, Roger A
2003-01-01
Turbulent flow, solute transport, and chemical and biological decay are some of the basic processes encountered in water treatment plants. This paper presents recent developments in the numerical simulation of turbulent flow and disinfection processes in disinfection contact tanks. Simulation runs have been conducted for various tank design alternatives and in different grid resolutions. The accuracy of simulated contact tank flow and the disinfection process depends largely on calculations of the hydrodynamic and solute transport characteristics in the tanks. A key factor of this is the accuracy of advection and shear stress term computations, which can be affected by the use of different hydrodynamic submodels and numerical schemes. The performance of a simulation model relies to a great extent on the right combination of such submodels and numerical schemes. In this study, a number of simulation models were tested against realistic tank configurations and measurements to evaluate the various combinations of turbulence models and difference schemes by analyzing predicted flow and solute transport patterns, as well as the corresponding flow-through curves. Models for disinfection tank simulations are recommended based on comparisons of simulation results with measurements. These models may also be applied to other water treatment processes such as wastewater treatment.
NASA Astrophysics Data System (ADS)
Bhushan, R.; Ng, T. L.
2014-12-01
Accurate stream flow forecasts are critical for reservoir operations for water supply planning. As the world urban population increases, the demand for water in cities is also increasing, making accurate forecasts even more important. However, accurate forecasting of stream flows is difficult owing to short- and long-term weather variations. We propose to reduce this need for accurate stream flow forecasts by augmenting reservoir operations with seawater desalination and wastewater recycling. We develop a robust operating policy for the joint operation of the three sources. With the joint model, we tap into the unlimited reserve of seawater through desalination, and make use of local supplies of wastewater through recycling. However, both seawater desalination and recycling are energy intensive and relatively expensive. Reservoir water on the other hand, is generally cheaper but is limited and variable in its availability, increasing the risk of water shortage during extreme climate events. We operate the joint system by optimizing it using a genetic algorithm to maximize water supply reliability and resilience while minimizing vulnerability subject to a budget constraint and for a given stream flow forecast. To compute the total cost of the system, we take into account the pumping cost of transporting reservoir water to its final destination, and the capital and operating costs of desalinating seawater and recycling wastewater. We produce results for different hydro climatic regions based on artificial stream flows we generate using a simple hydrological model and an autoregressive time series model. The artificial flows are generated from precipitation and temperature data from the Canadian Regional Climate model for present and future scenarios. We observe that the joint operation is able to effectively minimize the negative effects of stream flow forecast uncertainty on system performance at an overall cost that is not significantly greater than the cost of a
Flow resistance and its prediction methods in compound channels
NASA Astrophysics Data System (ADS)
Yang, Kejun; Cao, Shuyou; Liu, Xingnian
2007-02-01
A series of experiments was carried out in a large symmetric compound channel composed of a rough main channel and rough floodplains to investigate the resistance characteristics of inbank and overbank flows. The effective Manning, Darcy-Weisbach, Chezy coefficients and the relative Nikuradse roughness height were analyzed. Many different representative methods for predicting the composite roughness were systematically summarized. Besides the measured data, a vast number of laboratory data and field data for compound channels were collected and used to check the validity of these methods for different subsection divisions including the vertical, horizontal, diagonal and bisectional divisions. The computation showed that these methods resulted in big errors in assessing the composite roughness in compound channels, and the reasons were analyzed in detail. The error magnitude is related to the subsection divisions.
Prediction of jet flows from the axisymmetric supersonic nozzle
NASA Astrophysics Data System (ADS)
Liu, Y.; Kendall, M. A. F.; Costigan, G.; Bellhouse, B. J.
This study is motivated by the authors' interest in developing a needle-free powdered vaccine delivery device, the Epidermal Powdered Injection system(EPI). The behaviour of a supersonic jet, which accelerates powdered vaccines in micro-form to a sufficient momentum to penetrate the outer layer of human skin or mucosal tissue, is therefore of great importance. In this paper, a well established Modified Implicit Flux Vector Splitting (MIFVS) solver for the Navier-Stokes equations is extended to numerically study the transient supersonic jet flows of interest. A low Reynolds number k-ɛ turbulence model, with the compressibility effect considered, is integrated into MIFVS solver to the prediction of the turbulent structures and interactions with inherent shock systems. The results for the NASA validation case NPARC, Contoured Shock Tube and Venturi of EPI system are discussed.
NASA Astrophysics Data System (ADS)
Schiavon, Ricardo P.
2007-07-01
We present a new set of model predictions for 16 Lick absorption line indices from Hδ through Fe5335 and UBV colors for single stellar populations with ages ranging between 1 and 15 Gyr, [Fe/H] ranging from -1.3 to +0.3, and variable abundance ratios. The models are based on accurate stellar parameters for the Jones library stars and a new set of fitting functions describing the behavior of line indices as a function of effective temperature, surface gravity, and iron abundance. The abundances of several key elements in the library stars have been obtained from the literature in order to characterize the abundance pattern of the stellar library, thus allowing us to produce model predictions for any set of abundance ratios desired. We develop a method to estimate mean ages and abundances of iron, carbon, nitrogen, magnesium, and calcium that explores the sensitivity of the various indices modeled to those parameters. The models are compared to high-S/N data for Galactic clusters spanning the range of ages, metallicities, and abundance patterns of interest. Essentially all line indices are matched when the known cluster parameters are adopted as input. Comparing the models to high-quality data for galaxies in the nearby universe, we reproduce previous results regarding the enhancement of light elements and the spread in the mean luminosity-weighted ages of early-type galaxies. When the results from the analysis of blue and red indices are contrasted, we find good consistency in the [Fe/H] that is inferred from different Fe indices. Applying our method to estimate mean ages and abundances from stacked SDSS spectra of early-type galaxies brighter than L*, we find mean luminosity-weighed ages of the order of ~8 Gyr and iron abundances slightly below solar. Abundance ratios, [X/Fe], tend to be higher than solar and are positively correlated with galaxy luminosity. Of all elements, nitrogen is the more strongly correlated with galaxy luminosity, which seems to indicate
Predicting the stability of a compressible periodic parallel jet flow
NASA Technical Reports Server (NTRS)
Miles, Jeffrey H.
1996-01-01
It is known that mixing enhancement in compressible free shear layer flows with high convective Mach numbers is difficult. One design strategy to get around this is to use multiple nozzles. Extrapolating this design concept in a one dimensional manner, one arrives at an array of parallel rectangular nozzles where the smaller dimension is omega and the longer dimension, b, is taken to be infinite. In this paper, the feasibility of predicting the stability of this type of compressible periodic parallel jet flow is discussed. The problem is treated using Floquet-Bloch theory. Numerical solutions to this eigenvalue problem are presented. For the case presented, the interjet spacing, s, was selected so that s/omega =2.23. Typical plots of the eigenvalue and stability curves are presented. Results obtained for a range of convective Mach numbers from 3 to 5 show growth rates omega(sub i)=kc(sub i)/2 range from 0.25 to 0.29. These results indicate that coherent two-dimensional structures can occur without difficulty in multiple parallel periodic jet nozzles and that shear layer mixing should occur with this type of nozzle design.
ERIC Educational Resources Information Center
Lin, Jing-Wen
2016-01-01
Holding scientific conceptions and having the ability to accurately predict students' preconceptions are a prerequisite for science teachers to design appropriate constructivist-oriented learning experiences. This study explored the types and sources of students' preconceptions of electric circuits. First, 438 grade 3 (9 years old) students were…
A fully unsteady prescribed wake model for HAWT performance prediction in yawed flow
Coton, F.N.; Tongguang, Wang; Galbraith, R.A.M.; Lee, D.
1997-12-31
This paper describes the development of a fast, accurate, aerodynamic prediction scheme for yawed flow on horizontal axis wind turbines (HAWTs). The method is a fully unsteady three-dimensional model which has been developed over several years and is still being enhanced in a number of key areas. The paper illustrates the current ability of the method by comparison with field data from the NREL combined experiment and also describes the developmental work in progress. In particular, an experimental test programme designed to yield quantitative wake convection information is summarised together with modifications to the numerical model which are necessary for meaningful comparison with the experiments. Finally, current and future work on aspects such as tower-shadow and improved unsteady aerodynamic modelling are discussed.
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
Tariq, Umar; Hsiao, Albert; Alley, Marcus; Zhang, Tao; Lustig, Michael; Vasanawala, Shreyas S.
2012-01-01
Purpose To evaluate precision and accuracy of parallel-imaging compressed-sensing 4D phase contrast (PICS-4DPC) MRI venous flow quantification in children with patients referred for cardiac MRI at our children’s hospital. Materials and Methods With IRB approval and HIPAA compliance, 22 consecutive patients without shunts underwent 4DPC as part of clinical cardiac MRI examinations. Flow measurements were obtained in the superior and inferior vena cava, ascending and descending aorta and the pulmonary trunk. Conservation of flow to the upper, lower and whole body was used as an internal physiologic control. The arterial and venous flow rates at each location were compared with paired t-tests and F-tests to assess relative accuracy and precision. RESULTS Arterial and venous flow measurements were strongly correlated for the upper (ρ=0.89), lower (ρ=0.96) and whole body (ρ=0.97); net aortic and pulmonary trunk flow rates were also tightly correlated (ρ=0.97). There was no significant difference in the value or precision of arterial and venous flow measurements in upper, lower or whole body, though there was a trend toward improved precision with lower velocity-encoding settings. Conclusion With PICS-4DPC MRI, the accuracy and precision of venous flow quantification are comparable to that of arterial flow quantification at velocity-encodings appropriate for arterial vessels. PMID:23172846
Flow noise predictions of a submerged cylinder under turbulent boundary layer excitations
NASA Astrophysics Data System (ADS)
Wu, Kuangcheng; Vlahopoulos, Nickolas
2002-05-01
The unsteady fluctuated pressure underneath turbulent boundary layers (TBL) is one of major noise sources in moving vehicles. Recently, discretized TBL forcing functions have been applied to planar structures in air [Y. F. Hwang and S. A. Hambric, Noise-Con, 2000; M. Allen and N. Vlahopoulos, Computers and Structures, 2000; M. Allen and N. Vlahopoulos, Finite Elements in Analysis and Design, 2001; M. Allen, R. Sbragio, and N. Vlahopoulos, AIAA J. 2001]. This paper discusses prediction of the flow-induced radiated noise and surface responses of a submerged hemisphere-capped cylindrical shell (L/D=11). The FEM/IFEM (infinite finite element method) approach is used to calculate structural acoustic transfer functions and to accurately account for the fluid loading effects. The effect on TBL due to the curvature of a cylinder is captured by utilizing the potential flow-boundary layer theory to determine key boundary layer parameters. Predictions of the surface intensity and far field responses are developed through stochastic analysis due to the natural of the TBL excitations. A MATLAB script is generated to determine the power spectral density of the responses. [Work supported by ONR Code 334.
NASA Astrophysics Data System (ADS)
Slottke, D.; Ketcham, R. A.; Sharp, J. M.
2008-05-01
Fractures dominate fluid flow and transport of solutes when they are open and connected. The prediction of flow through fractured media has implications for development of water resources, petroleum reservoir exploitation, contamination and remediation assessment, and site evaluation for waste repositories. Assessing the impact of surface roughness on fluid flow and solute transport through fractured media from samples on the order of 100 cm2 assumes the existence of a relationship between fracture morphology and discharge that is scale invariant or at least smoothly transformable. Although some studies assume that the length scale at which surface roughness significantly contributes to the discharge through a fracture falls within the size of a typical hand sample, there is a dearth of empirical data supporting an extension of the relationships found at small scales to larger samples. Furthermore, an appropriate metric to describe a fracture volume accurately must be chosen. We compile data from physical flow tests and numerical modeling of two discrete natural fractures of different scales in rhyolitc tuff. The University of Texas HRXCT facility provided computed tomography representations of the fractures that allow analysis of surface roughness and aperture statistics at 0.25mm grid resolution, which form the basis for transmissivity field inputs to numerical models. We show that although a small (10cm2) representative surface can describe roughness, aperture fields are not so well behaved. We compare physical flow test results, modeled flow, and analytical solutions of the cubic law using various methods of assigning a meaningful aperture to illustrate the challenges of accurate modeling of fracture flow without a priori flow information. While a geometric mean aperture of the entire aperture field closely approximates the hydraulic aperture, an arbitrary profile mean aperture has little utility for predictive purposes.
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.
Roberts, Stephen J; Cain, Russell; Dawkins, Marian Stamp
2012-12-07
Currently, assessment of broiler (meat) chicken welfare relies largely on labour-intensive or post-mortem measures of welfare. We here describe a method for continuously and robustly monitoring the welfare of living birds while husbandry changes are still possible. We detail the application of Bayesian modelling to motion data derived from the output of cameras placed in commercial broiler houses. We show that the forecasts produced by the model can be used to accurately assess certain key aspects of the future health and welfare of a flock. The difference between healthy flocks and less-healthy ones becomes predictable days or even weeks before clinical symptoms become apparent. Hockburn (damaged leg skin, usually only seen in birds of two weeks or older) can be well predicted in flocks of only 1-2 days of age, using this approach. Our model combines optical flow descriptors of bird motion with robust multivariate forecasting and provides a sparse, efficient model with sparsity-inducing priors to achieve maximum predictive power with the minimum number of key variables.
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.
Flow Field and Acoustic Predictions for Three-Stream Jets
NASA Technical Reports Server (NTRS)
Simmons, Shaun Patrick; Henderson, Brenda S.; Khavaran, Abbas
2014-01-01
Computational fluid dynamics was used to analyze a three-stream nozzle parametric design space. The study varied bypass-to-core area ratio, tertiary-to-core area ratio and jet operating conditions. The flowfield solutions from the Reynolds-Averaged Navier-Stokes (RANS) code Overflow 2.2e were used to pre-screen experimental models for a future test in the Aero-Acoustic Propulsion Laboratory (AAPL) at the NASA Glenn Research Center (GRC). Flowfield solutions were considered in conjunction with the jet-noise-prediction code JeNo to screen the design concepts. A two-stream versus three-stream computation based on equal mass flow rates showed a reduction in peak turbulent kinetic energy (TKE) for the three-stream jet relative to that for the two-stream jet which resulted in reduced acoustic emission. Additional three-stream solutions were analyzed for salient flowfield features expected to impact farfield noise. As tertiary power settings were increased there was a corresponding near nozzle increase in shear rate that resulted in an increase in high frequency noise and a reduction in peak TKE. As tertiary-to-core area ratio was increased the tertiary potential core elongated and the peak TKE was reduced. The most noticeable change occurred as secondary-to-core area ratio was increased thickening the secondary potential core, elongating the primary potential core and reducing peak TKE. As forward flight Mach number was increased the jet plume region decreased and reduced peak TKE.
Prediction of frequencies in thermosolutal convection from mean flows
NASA Astrophysics Data System (ADS)
Turton, Sam E.; Tuckerman, Laurette S.; Barkley, Dwight
2015-04-01
Motivated by studies of the cylinder wake, in which the vortex-shedding frequency can be obtained from the mean flow, we study thermosolutal convection driven by opposing thermal and solutal gradients. In the archetypal two-dimensional geometry with horizontally periodic and vertical no-slip boundary conditions, branches of traveling waves and standing waves are created simultaneously by a Hopf bifurcation. Consistent with similar analyses performed on the cylinder wake, we find that the traveling waves of thermosolutal convection have the RZIF property, meaning that linearization about the mean fields of the traveling waves yields an eigenvalue whose real part is almost zero and whose imaginary part corresponds very closely to the nonlinear frequency. In marked contrast, linearization about the mean field of the standing waves yields neither zero growth nor the nonlinear frequency. It is shown that this difference can be attributed to the fact that the temporal power spectrum for the traveling waves is peaked, while that of the standing waves is broad. We give a general demonstration that the frequency of any quasimonochromatic oscillation can be predicted from its temporal mean.
Sengupta, Arkajyoti; Ramabhadran, Raghunath O; Raghavachari, Krishnan
2014-08-14
In this study we have used the connectivity-based hierarchy (CBH) method to derive accurate heats of formation of a range of biomolecules, 18 amino acids and 10 barbituric acid/uracil derivatives. The hierarchy is based on the connectivity of the different atoms in a large molecule. It results in error-cancellation reaction schemes that are automated, general, and can be readily used for a broad range of organic molecules and biomolecules. Herein, we first locate stable conformational and tautomeric forms of these biomolecules using an accurate level of theory (viz. CCSD(T)/6-311++G(3df,2p)). Subsequently, the heats of formation of the amino acids are evaluated using the CBH-1 and CBH-2 schemes and routinely employed density functionals or wave function-based methods. The calculated heats of formation obtained herein using modest levels of theory and are in very good agreement with those obtained using more expensive W1-F12 and W2-F12 methods on amino acids and G3 results on barbituric acid derivatives. Overall, the present study (a) highlights the small effect of including multiple conformers in determining the heats of formation of biomolecules and (b) in concurrence with previous CBH studies, proves that use of the more effective error-cancelling isoatomic scheme (CBH-2) results in more accurate heats of formation with modestly sized basis sets along with common density functionals or wave function-based methods.
NASA Astrophysics Data System (ADS)
Ryu, Jaiyoung; Hu, Xiao; Shadden, Shawn C.
2014-11-01
The cerebral circulation is unique in its ability to maintain blood flow to the brain under widely varying physiologic conditions. Incorporating this autoregulatory response is critical to cerebral blood flow modeling, as well as investigations into pathological conditions. We discuss a one-dimensional nonlinear model of blood flow in the cerebral arteries that includes coupling of autoregulatory lumped parameter networks. The model is tested to reproduce a common clinical test to assess autoregulatory function - the carotid artery compression test. The change in the flow velocity at the middle cerebral artery (MCA) during carotid compression and release demonstrated strong agreement with published measurements. The model is then used to investigate vasospasm of the MCA, a common clinical concern following subarachnoid hemorrhage. Vasospasm was modeled by prescribing vessel area reduction in the middle portion of the MCA. Our model showed similar increases in velocity for moderate vasospasms, however, for serious vasospasm (~ 90% area reduction), the blood flow velocity demonstrated decrease due to blood flow rerouting. This demonstrates a potentially important phenomenon, which otherwise would lead to false-negative decisions on clinical vasospasm if not properly anticipated.
2005-06-01
AFRL-VA-WP-TR-2005-3060 AIR VEHICLES TECHNOLOGY INTEGRATION PROGRAM (AVTIP) Delivery Order 0020 : Prediction Of... Technology Integration Program (AVTIP) 5b. GRANT NUMBER Delivery Order 0020 : Prediction Of Manufacturing Tolerances For Laminar Flow 5c. PROGRAM
NASA Astrophysics Data System (ADS)
Naveed, Muhammad; Moldrup, Per; Schaap, Marcel G.; Tuller, Markus; Kulkarni, Ramaprasad; Vogel, Hans-Jörg; Wollesen de Jonge, Lis
2016-10-01
conductivity, air permeability, and gas diffusivity performed reasonably well when parameterized with novel, X-ray CT-derived parameters such as effective percolating macroporosity for biopore-dominated flow and total macroporosity for matrix-dominated flow. The obtained results further indicate that it is crucially important to discern between matrix-dominated and biopore-dominated flow for accurate prediction of macropore flow from X-ray CT-derived macropore network characteristics.
KIVA-hpFE. Predictive turbulent reactive and multiphase flow in engines - An Overview
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. 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.
Development of Computational Aeroacoustics Code for Jet Noise and Flow Prediction
NASA Technical Reports Server (NTRS)
Keith, Theo G., Jr.; Hixon, Duane R.
2002-01-01
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
NASA Astrophysics Data System (ADS)
Baldner, Charles; Bogart, Richard S.
2016-05-01
The use of helioseismology to study the properties of the Sun has yielded very high precision measurements of solar flows throughout much of the interior. It has been apparent for many years, however, that the accuracy of many of these measurements is suspect due to significant systematic effects in helioseismic techniques. The most well-known effect in flow measurements is sometimes referred to as the `center-to-limb' effect, in which flow measurements depend strongly on the distance of the measurement from the center of the observed solar disk. Attempts have already been made to explain the origin of this error (e.g. Balder & Schou 2012) and to correct it (e.g. Zhao et al. 2011). Significant work remains, however.In this work, we report on continued efforts to precisely characterize the effect of position on the observed disk on flow measurements in the HMI ring diagram pipeline, and from other HMI data. Our efforts are focused on 1) quantifying the non-radial systematic effect in flow measurements; 2) understanding the effect of the underlying model used in the mode parameter estimations; and 3) characterizing the difference between helioseismic measurements made with different observed quantities.
Mayes, Janice M; Mouraviev, Vladimir; Sun, Leon; Tsivian, Matvey; Madden, John F; Polascik, Thomas J
2011-01-01
We evaluate the reliability of routine sextant prostate biopsy to detect unilateral lesions. A total of 365 men with complete records including all clinical and pathologic variables who underwent a preoperative sextant biopsy and subsequent radical prostatectomy (RP) for clinically localized prostate cancer at our medical center between January 1996 and December 2006 were identified. When the sextant biopsy detects unilateral disease, according to RP results, the NPV is high (91%) with a low false negative rate (9%). However, the sextant biopsy has a PPV of 28% with a high false positive rate (72%). Therefore, a routine sextant prostate biopsy cannot provide reliable, accurate information about the unilaterality of tumor lesion(s).
Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve
2015-01-01
For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease. PMID:25938675
Luo, Wei; Nguyen, Thin; Nichols, Melanie; Tran, Truyen; Rana, Santu; Gupta, Sunil; Phung, Dinh; Venkatesh, Svetha; Allender, Steve
2015-01-01
For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.
A Maximal Graded Exercise Test to Accurately Predict VO2max in 18-65-Year-Old Adults
ERIC Educational Resources Information Center
George, James D.; Bradshaw, Danielle I.; Hyde, Annette; Vehrs, Pat R.; Hager, Ronald L.; Yanowitz, Frank G.
2007-01-01
The purpose of this study was to develop an age-generalized regression model to predict maximal oxygen uptake (VO sub 2 max) based on a maximal treadmill graded exercise test (GXT; George, 1996). Participants (N = 100), ages 18-65 years, reached a maximal level of exertion (mean plus or minus standard deviation [SD]; maximal heart rate [HR sub…
Karwath, Andreas; Clare, Amanda; Dehaspe, Luc
2000-01-01
The analysis of genomics data needs to become as automated as its generation. Here we present a novel data-mining approach to predicting protein functional class from sequence. This method is based on a combination of inductive logic programming clustering and rule learning. We demonstrate the effectiveness of this approach on the M. tuberculosis and E. coli genomes, and identify biologically interpretable rules which predict protein functional class from information only available from the sequence. These rules predict 65% of the ORFs with no assigned function in M. tuberculosis and 24% of those in E. coli, with an estimated accuracy of 60–80% (depending on the level of functional assignment). The rules are founded on a combination of detection of remote homology, convergent evolution and horizontal gene transfer. We identify rules that predict protein functional class even in the absence of detectable sequence or structural homology. These rules give insight into the evolutionary history of M. tuberculosis and E. coli. PMID:11119305
Danner, Holger; Desurmont, Gaylord A; Cristescu, Simona M; van Dam, Nicole M
2017-01-30
Herbivore-induced plant volatiles (HIPVs) serve as specific cues to higher trophic levels. Novel, exotic herbivores entering native foodwebs may disrupt the infochemical network as a result of changes in HIPV profiles. Here, we analysed HIPV blends of native Brassica rapa plants infested with one of 10 herbivore species with different coexistence histories, diet breadths and feeding modes. Partial least squares (PLS) models were fitted to assess whether HIPV blends emitted by Dutch B. rapa differ between native and exotic herbivores, between specialists and generalists, and between piercing-sucking and chewing herbivores. These models were used to predict the status of two additional herbivores. We found that HIPV blends predicted the evolutionary history, diet breadth and feeding mode of the herbivore with an accuracy of 80% or higher. Based on the HIPVs, the PLS models reliably predicted that Trichoplusia ni and Spodoptera exigua are perceived as exotic, leaf-chewing generalists by Dutch B. rapa plants. These results indicate that there are consistent and predictable differences in HIPV blends depending on global herbivore characteristics, including coexistence history. Consequently, native organisms may be able to rapidly adapt to potentially disruptive effects of exotic herbivores on the infochemical network.
Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano
2014-01-01
Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030
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
NASA Technical Reports Server (NTRS)
Gloss, B. B.; Johnson, F. T.
1976-01-01
The Boeing Commercial Airplane Company developed an inviscid three-dimensional lifting surface method that shows promise in being able to accurately predict loads, subsonic and supersonic, on wings with leading-edge separation and reattachment.
NASA Technical Reports Server (NTRS)
Desmarais, R. N.
1982-01-01
The method is capable of generating approximations of arbitrary accuracy. It is based on approximating the algebraic part of the nonelementary integrals in the kernel by exponential functions and then integrating termwise. The exponent spacing in the approximation is a geometric sequence. The coefficients and exponent multiplier of the exponential approximation are computed by least squares so the method is completely automated. Exponential approximates generated in this manner are two orders of magnitude more accurate than the exponential approximation that is currently most often used for this purpose. The method can be used to generate approximations to attain any desired trade-off between accuracy and computing cost.
NASA Astrophysics Data System (ADS)
Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning
2016-02-01
The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.
Grassi, Lorenzo; Väänänen, Sami P; Ristinmaa, Matti; Jurvelin, Jukka S; Isaksson, Hanna
2016-03-21
Subject-specific finite element models have been proposed as a tool to improve fracture risk assessment in individuals. A thorough laboratory validation against experimental data is required before introducing such models in clinical practice. Results from digital image correlation can provide full-field strain distribution over the specimen surface during in vitro test, instead of at a few pre-defined locations as with strain gauges. The aim of this study was to validate finite element models of human femora against experimental data from three cadaver femora, both in terms of femoral strength and of the full-field strain distribution collected with digital image correlation. The results showed a high accuracy between predicted and measured principal strains (R(2)=0.93, RMSE=10%, 1600 validated data points per specimen). Femoral strength was predicted using a rate dependent material model with specific strain limit values for yield and failure. This provided an accurate prediction (<2% error) for two out of three specimens. In the third specimen, an accidental change in the boundary conditions occurred during the experiment, which compromised the femoral strength validation. The achieved strain accuracy was comparable to that obtained in state-of-the-art studies which validated their prediction accuracy against 10-16 strain gauge measurements. Fracture force was accurately predicted, with the predicted failure location being very close to the experimental fracture rim. Despite the low sample size and the single loading condition tested, the present combined numerical-experimental method showed that finite element models can predict femoral strength by providing a thorough description of the local bone mechanical response.
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
NASA Technical Reports Server (NTRS)
Simonich, J. C.; Caplin, B.
1989-01-01
A users manual for a computer program for predicting atmospheric turbulence and mean flow and turbulence contraction as part of a noise prediction scheme for nonisotropic turbulence ingestion noise in helicopters is described. Included are descriptions of the various program modules and subroutines, their function, programming structure, and the required input and output variables. This routine is incorporated as one module of NASA's ROTONET helicopter noise prediction program.
Barone, Veronica; Hod, Oded; Peralta, Juan E; Scuseria, Gustavo E
2011-04-19
Over the last several years, low-dimensional graphene derivatives, such as carbon nanotubes and graphene nanoribbons, have played a central role in the pursuit of a plausible carbon-based nanotechnology. Their electronic properties can be either metallic or semiconducting depending purely on morphology, but predicting their electronic behavior has proven challenging. The combination of experimental efforts with modeling of these nanometer-scale structures has been instrumental in gaining insight into their physical and chemical properties and the processes involved at these scales. Particularly, approximations based on density functional theory have emerged as a successful computational tool for predicting the electronic structure of these materials. In this Account, we review our efforts in modeling graphitic nanostructures from first principles with hybrid density functionals, namely the Heyd-Scuseria-Ernzerhof (HSE) screened exchange hybrid and the hybrid meta-generalized functional of Tao, Perdew, Staroverov, and Scuseria (TPSSh). These functionals provide a powerful tool for quantitatively studying structure-property relations and the effects of external perturbations such as chemical substitutions, electric and magnetic fields, and mechanical deformations on the electronic and magnetic properties of these low-dimensional carbon materials. We show how HSE and TPSSh successfully predict the electronic properties of these materials, providing a good description of their band structure and density of states, their work function, and their magnetic ordering in the cases in which magnetism arises. Moreover, these approximations are capable of successfully predicting optical transitions (first and higher order) in both metallic and semiconducting single-walled carbon nanotubes of various chiralities and diameters with impressive accuracy. This versatility includes the correct prediction of the trigonal warping splitting in metallic nanotubes. The results predicted
Predicting multidimensional annular flows with a locally based two-fluid model
Antal, S.P. Edwards, D.P.; Strayer, T.D.
1998-06-01
Annular flows are a well utilized flow regime in many industrial applications, such as, heat exchangers, chemical reactors and industrial process equipment. These flows are characterized by a droplet laden vapor core with a thin, wavy liquid film wetting the walls. The prediction of annular flows has been largely confined to one-dimensional modeling which typically correlates the film thickness, droplet loading, and phase velocities by considering the average flow conditions and global mass and momentum balances to infer the flow topology. In this paper, a methodology to predict annular flows using a locally based two-fluid model of multiphase flow is presented. The purpose of this paper is to demonstrate a modeling approach for annular flows using a multifield, multidimensional two-fluid model and discuss the need for further work in this area.
Kinetic Methods for Predicting Flow Physics of Small Thruster Expansions
2011-01-24
approach for simulation of rarefied gas flows by modeling the motion of fictitious particles. The correct usage of the DSMC method requires time and...simulated and measured condensation onset occur in the flow at ethanol gas pressures and temperatures above the saturation pressure, as expected...Current Status and Prospects of the DSMCModeling of Near-Continuum Flows of Non-reacting and Reacting Gases,” Proceedings of the Rarefied Gas Dynamics
2013-08-01
24 Figure 20. ABQ experiment showing five volunteers located 1.0 m from source in upper-left panel wearing...study (Royster et al.,1996) in which users self-fit hearing protectors (ANSI S12.6- 2008 method B: user fit) with no experimenter instruction gives an...values provided by the experimenters and simulator fits for the intact and modified muffs. Figure 22 (upper panel) shows the simulator prediction
NASA Astrophysics Data System (ADS)
Cleves, Ann E.; Jain, Ajay N.
2015-06-01
Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.
Cleves, Ann E; Jain, Ajay N
2015-06-01
Prediction of the bound configuration of small-molecule ligands that differ substantially from the cognate ligand of a protein co-crystal structure is much more challenging than re-docking the cognate ligand. Success rates for cross-docking in the range of 20-30 % are common. We present an approach that uses structural information known prior to a particular cutoff-date to make predictions on ligands whose bounds structures were determined later. The knowledge-guided docking protocol was tested on a set of ten protein targets using a total of 949 ligands. The benchmark data set, called PINC ("PINC Is Not Cognate"), is publicly available. Protein pocket similarity was used to choose representative structures for ensemble-docking. The docking protocol made use of known ligand poses prior to the cutoff-date, both to help guide the configurational search and to adjust the rank of predicted poses. Overall, the top-scoring pose family was correct over 60 % of the time, with the top-two pose families approaching a 75 % success rate. Correct poses among all those predicted were identified nearly 90 % of the time. The largest improvements came from the use of molecular similarity to improve ligand pose rankings and the strategy for identifying representative protein structures. With the exception of a single outlier target, the knowledge-guided docking protocol produced results matching the quality of cognate-ligand re-docking, but it did so on a very challenging temporally-segregated cross-docking benchmark.
Li, Haibo; Ding, Jie; Wen, Ping; Zhang, Qin; Xiang, Jingjing; Li, Qiong; Xuan, Liming; Kong, Lingyin; Mao, Yan; Zhu, Yijun; Shen, Jingjing; Liang, Bo; Li, Hong
2016-01-01
Massively parallel sequencing (MPS) combined with bioinformatic analysis has been widely applied to detect fetal chromosomal aneuploidies such as trisomy 21, 18, 13 and sex chromosome aneuploidies (SCAs) by sequencing cell-free fetal DNA (cffDNA) from maternal plasma, so-called non-invasive prenatal testing (NIPT). However, many technical challenges, such as dependency on correct fetal sex prediction, large variations of chromosome Y measurement and high sensitivity to random reads mapping, may result in higher false negative rate (FNR) and false positive rate (FPR) in fetal sex prediction as well as in SCAs detection. Here, we developed an optimized method to improve the accuracy of the current method by filtering out randomly mapped reads in six specific regions of the Y chromosome. The method reduces the FNR and FPR of fetal sex prediction from nearly 1% to 0.01% and 0.06%, respectively and works robustly under conditions of low fetal DNA concentration (1%) in testing and simulation of 92 samples. The optimized method was further confirmed by large scale testing (1590 samples), suggesting that it is reliable and robust enough for clinical testing. PMID:27441628
Baldassi, Carlo; Zamparo, Marco; Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea
2014-01-01
In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code.
Li, Xiaowei; Liu, Taigang; Tao, Peiying; Wang, Chunhua; Chen, Lanming
2015-12-01
Structural class characterizes the overall folding type of a protein or its domain. Many methods have been proposed to improve the prediction accuracy of protein structural class in recent years, but it is still a challenge for the low-similarity sequences. In this study, we introduce a feature extraction technique based on auto cross covariance (ACC) transformation of position-specific score matrix (PSSM) to represent a protein sequence. Then support vector machine-recursive feature elimination (SVM-RFE) is adopted to select top K features according to their importance and these features are input to a support vector machine (SVM) to conduct the prediction. Performance evaluation of the proposed method is performed using the jackknife test on three low-similarity datasets, i.e., D640, 1189 and 25PDB. By means of this method, the overall accuracies of 97.2%, 96.2%, and 93.3% are achieved on these three datasets, which are higher than those of most existing methods. This suggests that the proposed method could serve as a very cost-effective tool for predicting protein structural class especially for low-similarity datasets.
Eguchi, K; Hoshide, S; Shimada, K; Kario, K
2014-12-01
We tested the hypothesis that multiple clinic blood pressure (BP) readings over an extended baseline period would be as predictive as ambulatory BP (ABP) for cardiovascular disease (CVD). Clinic and ABP monitoring were performed in 457 hypertensive patients at baseline. Clinic BP was measured monthly and the means of the first 3, 5 and 10 clinic BP readings were taken as the multiple clinic BP readings. The subjects were followed up, and stroke, HARD CVD, and ALL CVD events were determined as outcomes. In multivariate Cox regression analyses, ambulatory systolic BP (SBP) best predicted three outcomes independently of baseline and multiple clinic SBP readings. The mean of 10 clinic SBP readings predicted stroke (hazards ratio (HR)=1.39, 95% confidence interval (CI)=1.02-1.90, P=0.04) and ALL CVD (HR=1.41, 95% CI=1.13-1.74, P=0.002) independently of baseline clinic SBP. Clinic SBPs by three and five readings were not associated with any CVD events, except that clinic SBP by three readings was associated with ALL CVD (P=0.015). Besides ABP values, the mean of the first 10 clinic SBP values was a significant predictor of stroke and ALL CVD events. It is important to take more than several clinic BP readings early after the baseline period for the risk stratification of future CVD events.
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.
Pearce, K L; Ferguson, M; Gardner, G; Smith, N; Greef, J; Pethick, D W
2009-01-01
Fifty merino wethers (liveweight range from 44 to 81kg, average of 58.6kg) were lot fed for 42d and scanned through a dual X-ray absorptiometry (DXA) as both a live animal and whole carcass (carcass weight range from 15 to 32kg, average of 22.9kg) producing measures of total tissue, lean, fat and bone content. The carcasses were subsequently boned out into saleable cuts and the weights and yield of boned out muscle, fat and bone recorded. The relationship between chemical lean (protein+water) was highly correlated with DXA carcass lean (r(2)=0.90, RSD=0.674kg) and moderately with DXA live lean (r(2)=0.72, RSD=1.05kg). The relationship between the chemical fat was moderately correlated with DXA carcass fat (r(2)=0.86, RSD=0.42kg) and DXA live fat (r(2)=0.70, RSD=0.71kg). DXA carcass and live animal bone was not well correlated with chemical ash (both r(2)=0.38, RSD=0.3). DXA carcass lean was moderately well predicted from DXA live lean with the inclusion of bodyweight in the regression (r(2)=0.82, RSD=0.87kg). DXA carcass fat was well predicted from DXA live fat (r(2)=0.86, RSD=0.54kg). DXA carcass lean and DXA carcass fat with the inclusion of carcass weight in the regression significantly predicted boned out muscle (r(2)=0.97, RSD=0.32kg) and fat weight, respectively (r(2)=0.92, RSD=0.34kg). The use of DXA live lean and DXA live fat with the inclusion of bodyweight to predict boned out muscle (r(2)=0.83, RSD=0.75kg) and fat (r(2)=0.86, RSD=0.46kg) weight, respectively, was moderate. The use of DXA carcass and live lean and fat to predict boned out muscle and fat yield was not correlated as weight. The future for the DXA will exist in the determination of body composition in live animals and carcasses in research experiments but there is potential for the DXA to be used as an online carcass grading system.
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.
Zhi-Gang Feng
2012-05-31
The simulation of particulate flows for industrial applications often requires the use of two-fluid models, where the solid particles are considered as a separate continuous phase. One of the underlining uncertainties in the use of the two-fluid models in multiphase computations comes from the boundary condition of the solid phase. Typically, the gas or liquid fluid boundary condition at a solid wall is the so called no-slip condition, which has been widely accepted to be valid for single-phase fluid dynamics provided that the Knudsen number is low. However, the boundary condition for the solid phase is not well understood. The no-slip condition at a solid boundary is not a valid assumption for the solid phase. Instead, several researchers advocate a slip condition as a more appropriate boundary condition. However, the question on the selection of an exact slip length or a slip velocity coefficient is still unanswered. Experimental or numerical simulation data are needed in order to determinate the slip boundary condition that is applicable to a two-fluid model. The goal of this project is to improve the performance and accuracy of the boundary conditions used in two-fluid models such as the MFIX code, which is frequently used in multiphase flow simulations. The specific objectives of the project are to use first principles embedded in a validated Direct Numerical Simulation particulate flow numerical program, which uses the Immersed Boundary method (DNS-IB) and the Direct Forcing scheme in order to establish, modify and validate needed energy and momentum boundary conditions for the MFIX code. To achieve these objectives, we have developed a highly efficient DNS code and conducted numerical simulations to investigate the particle-wall and particle-particle interactions in particulate flows. Most of our research findings have been reported in major conferences and archived journals, which are listed in Section 7 of this report. In this report, we will present a
DeMuth, S.F.; Watson, J.S.
1985-01-01
A model of compressible flow through an orifice, in the region of transition from free molecular to isentropic expansion flow, has been developed and tested for accuracy. The transitional or slip regime is defined as the conditions where molecular interactions are too many for free molecular flow modeling, yet not great enough for isentropic expansion flow modeling. Due to a lack of literature establishing a well-accepted model for predicting transitional flow, it was felt such work would be beneficial. The model is nonlinear and cannot be satisfactorily linearized for a linear regression analysis. Consequently, a computer routine was developed which minimized the sum of the squares of the residual flow for the nonlinear model. The results indicate an average accuracy within 15% of the measured flow throughout the range of test conditions. Furthermore, the results of the regression analysis indicate that the transitional regime lies between Knudsen numbers of approximately 2 and 45. 4 refs., 3 figs., 1 tab.
MODFLOW 2. 0: A program for predicting moderator flow patterns
Peterson, P.F. . Dept. of Nuclear Engineering); Paik, I.K. )
1991-07-01
Sudden changes in the temperature of flowing liquids can result in transient buoyancy forces which strongly impact the flow hydrodynamics via flow stratification. These effects have been studied for the case of potential flow of stratified liquids to line sinks, but not for moderator flow in SRS reactors. Standard codes, such as TRAC and COMMIX, do not have the capability to capture the stratification effect, due to strong numerical diffusion which smears away the hot/cold fluid interface. A related problem with standard codes is the inability to track plumes injected into the liquid flow, again due to numerical diffusion. The combined effects of buoyant stratification and plume dispersion have been identified as being important in operation the Supplementary Safety System which injects neutron-poison ink into SRS reactors to provide safe shutdown in the event of safety rod failure. The MODFLOW code discussed here provides transient moderator flow pattern information with stratification effects, and tracks the location of ink plumes in the reactor. The code, written in Fortran, is compiled for Macintosh II computers, and includes subroutines for interactive control and graphical output. Removing the graphics capabilities, the code can also be compiled on other computers. With graphics, in addition to the capability to perform safety related computations, MODFLOW also provides an easy tool for becoming familiar with flow distributions in SRS reactors.
Yuan, Xuye; Chen, Jiajia; Lin, Yuxin; Li, Yin; Xu, Lihua; Chen, Luonan; Hua, Haiying; Shen, Bairong
2017-01-01
Leukemia is a leading cause of cancer deaths in the developed countries. Great efforts have been undertaken in search of diagnostic biomarkers of leukemia. However, leukemia is highly complex and heterogeneous, involving interaction among multiple molecular components. Individual molecules are not necessarily sensitive diagnostic indicators. Network biomarkers are considered to outperform individual molecules in disease characterization. We applied an integrative approach that identifies active network modules as putative biomarkers for leukemia diagnosis. We first reconstructed the leukemia-specific PPI network using protein-protein interactions from the Protein Interaction Network Analysis (PINA) and protein annotations from GeneGo. The network was further integrated with gene expression profiles to identify active modules with leukemia relevance. Finally, the candidate network-based biomarker was evaluated for the diagnosing performance. A network of 97 genes and 400 interactions was identified for accurate diagnosis of leukemia. Functional enrichment analysis revealed that the network biomarkers were enriched in pathways in cancer. The network biomarkers could discriminate leukemia samples from the normal controls more effectively than the known biomarkers. The network biomarkers provide a useful tool to diagnose leukemia and also aids in further understanding the molecular basis of leukemia. PMID:28243332
Flow ensemble prediction for flash flood warnings at ungauged basins
NASA Astrophysics Data System (ADS)
Demargne, Julie; Javelle, Pierre; Organde, Didier; Caseri, Angelica; Ramos, Maria-Helena; de Saint Aubin, Céline; Jurdy, Nicolas
2015-04-01
Flash floods, which are typically triggered by severe rainfall events, are difficult to monitor and predict at the spatial and temporal scales of interest due to large meteorological and hydrologic uncertainties. In particular, uncertainties in quantitative precipitation forecasts (QPF) and quantitative precipitation estimates (QPE) need to be taken into account to provide skillful flash flood warnings with increased warning lead time. In France, the AIGA discharge-threshold flood warning system is currently being enhanced to ingest high-resolution ensemble QPFs from convection-permitting numerical weather prediction (NWP) models, as well as probabilistic QPEs, to improve flash flood warnings for small-to-medium (from 10 to 1000 km²) ungauged basins. The current deterministic AIGA system is operational in the South of France since 2005. It ingests the operational radar-gauge QPE grids from Météo-France to run a simplified hourly distributed hydrologic model at a 1-km² resolution every 15 minutes (Javelle et al. 2014). This produces real-time peak discharge estimates along the river network, which are subsequently compared to regionalized flood frequency estimates of given return periods. Warnings are then provided to the French national hydro-meteorological and flood forecasting centre (SCHAPI) and regional flood forecasting offices, based on the estimated severity of ongoing events. The calibration and regionalization of the hydrologic model has been recently enhanced to implement an operational flash flood warning system for the entire French territory. To quantify the QPF uncertainty, the COSMO-DE-EPS rainfall ensembles from the Deutscher Wetterdienst (20 members at a 2.8-km resolution for a lead time of 21 hours), which are available on the North-eastern part of France, were ingested in the hydrologic model of the AIGA system. Streamflow ensembles were produced and probabilistic flash flood warnings were derived for the Meuse and Moselle river basins and
Walsh, Susan; Liu, Fan; Ballantyne, Kaye N; van Oven, Mannis; Lao, Oscar; Kayser, Manfred
2011-06-01
A new era of 'DNA intelligence' is arriving in forensic biology, due to the impending ability to predict externally visible characteristics (EVCs) from biological material such as those found at crime scenes. EVC prediction from forensic samples, or from body parts, is expected to help concentrate police investigations towards finding unknown individuals, at times when conventional DNA profiling fails to provide informative leads. Here we present a robust and sensitive tool, termed IrisPlex, for the accurate prediction of blue and brown eye colour from DNA in future forensic applications. We used the six currently most eye colour-informative single nucleotide polymorphisms (SNPs) that previously revealed prevalence-adjusted prediction accuracies of over 90% for blue and brown eye colour in 6168 Dutch Europeans. The single multiplex assay, based on SNaPshot chemistry and capillary electrophoresis, both widely used in forensic laboratories, displays high levels of genotyping sensitivity with complete profiles generated from as little as 31pg of DNA, approximately six human diploid cell equivalents. We also present a prediction model to correctly classify an individual's eye colour, via probability estimation solely based on DNA data, and illustrate the accuracy of the developed prediction test on 40 individuals from various geographic origins. Moreover, we obtained insights into the worldwide allele distribution of these six SNPs using the HGDP-CEPH samples of 51 populations. Eye colour prediction analyses from HGDP-CEPH samples provide evidence that the test and model presented here perform reliably without prior ancestry information, although future worldwide genotype and phenotype data shall confirm this notion. As our IrisPlex eye colour prediction test is capable of immediate implementation in forensic casework, it represents one of the first steps forward in the creation of a fully individualised EVC prediction system for future use in forensic DNA intelligence.
McCoy, Rajiv C.; Garud, Nandita R.; Kelley, Joanna L.; Boggs, Carol L.; Petrov, Dmitri A.
2015-01-01
The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here we present and evaluate a method of SNP discovery using RNA-sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has since experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA-sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all-in-one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other non-model systems. PMID:24237665
NASA Astrophysics Data System (ADS)
Russo, A.; Zuccarello, B.
2007-07-01
The paper presents a theoretical-numerical hybrid method for determining the stresses distribution in composite laminates containing a circular hole and subjected to uniaxial tensile loading. The method is based upon an appropriate corrective function allowing a simple and rapid evaluation of stress distributions in a generic plate of finite width with a hole based on the theoretical stresses distribution in an infinite plate with the same hole geometry and material. In order to verify the accuracy of the method proposed, various numerical and experimental tests have been performed by considering different laminate lay-ups; in particular, the experimental results have shown that a combined use of the method proposed and the well-know point-stress criterion leads to reliable strength predictions for GFRP or CFRP laminates with a circular hole.
Samudrala, Ram; Heffron, Fred; McDermott, Jason E.
2009-04-24
The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates, effector proteins, are not. We have used a machine learning approach to identify new secreted effectors. The method integrates evolutionary measures, such as the pattern of homologs in a range of other organisms, and sequence-based features, such as G+C content, amino acid composition and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from Salmonella typhimurium and validated on a corresponding set of effectors from Pseudomonas syringae, after eliminating effectors with detectable sequence similarity. The method was able to identify all of the known effectors in P. syringae with a specificity of 84% and sensitivity of 82%. The reciprocal validation, training on P. syringae and validating on S. typhimurium, gave similar results with a specificity of 86% when the sensitivity level was 87%. These results show that type III effectors in disparate organisms share common features. We found that maximal performance is attained by including an N-terminal sequence of only 30 residues, which agrees with previous studies indicating that this region contains the secretion signal. We then used the method to define the most important residues in this putative secretion signal. Finally, we present novel predictions of secreted effectors in S. typhimurium, some of which have been experimentally validated, and apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis. This approach is a novel and effective way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal.
Deleebeeck, Nele M E; De Laender, Frederik; Chepurnov, Victor A; Vyverman, Wim; Janssen, Colin R; De Schamphelaere, Karel A C
2009-04-01
The major research questions addressed in this study were (i) whether green microalgae living in soft water (operationally defined water hardness<10mg CaCO(3)/L) are intrinsically more sensitive to Ni than green microalgae living in hard water (operationally defined water hardness >25mg CaCO(3)/L), and (ii) whether a single bioavailability model can be used to predict the effect of water hardness on the toxicity of Ni to green microalgae in both soft and hard water. Algal growth inhibition tests were conducted with clones of 10 different species collected in soft and hard water lakes in Sweden. Soft water algae were tested in a 'soft' and a 'moderately hard' test medium (nominal water hardness=6.25 and 16.3mg CaCO(3)/L, respectively), whereas hard water algae were tested in a 'moderately hard' and a 'hard' test medium (nominal water hardness=16.3 and 43.4 mg CaCO(3)/L, respectively). The results from the growth inhibition tests in the 'moderately hard' test medium revealed no significant sensitivity differences between the soft and the hard water algae used in this study. Increasing water hardness significantly reduced Ni toxicity to both soft and hard water algae. Because it has previously been demonstrated that Ca does not significantly protect the unicellular green alga Pseudokirchneriella subcapitata against Ni toxicity, it was assumed that the protective effect of water hardness can be ascribed to Mg alone. The logK(MgBL) (=5.5) was calculated to be identical for the soft and the hard water algae used in this study. A single bioavailability model can therefore be used to predict Ni toxicity to green microalgae in soft and hard surface waters as a function of water hardness.
Prediction of Anomalous Blood Viscosity in Confined Shear Flow
NASA Astrophysics Data System (ADS)
Thiébaud, Marine; Shen, Zaiyi; Harting, Jens; Misbah, Chaouqi
2014-06-01
Red blood cells play a major role in body metabolism by supplying oxygen from the microvasculature to different organs and tissues. Understanding blood flow properties in microcirculation is an essential step towards elucidating fundamental and practical issues. Numerical simulations of a blood model under a confined linear shear flow reveal that confinement markedly modifies the properties of blood flow. A nontrivial spatiotemporal organization of blood elements is shown to trigger hitherto unrevealed flow properties regarding the viscosity η, namely ample oscillations of its normalized value [η]=(η-η0)/(η0ϕ) as a function of hematocrit ϕ (η0=solvent viscosity). A scaling law for the viscosity as a function of hematocrit and confinement is proposed. This finding can contribute to the conception of new strategies to efficiently detect blood disorders, via in vitro diagnosis based on confined blood rheology. It also constitutes a contribution for a fundamental understanding of rheology of confined complex fluids.
Prediction of flow profiles in arteries from local measurements.
NASA Technical Reports Server (NTRS)
Ling, S. C.; Atabek, H. B.
1971-01-01
This paper develops an approximate numerical method for calculating flow profiles in arteries. The theory takes into account the nonlinear terms of the Navier-Stokes equations as well as the large deformations of the arterial wall. The method, assuming axially symmetric flow, determines velocity distribution and wall shear at a given location from the locally measured values of the pressure, pressure gradient, and pressure-radius relation. The computed results agree well with the corresponding experimental data.
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.
NASA Astrophysics Data System (ADS)
Tan, Samuel; Barrera Acevedo, Santiago; Izgorodina, Ekaterina I.
2017-02-01
The accurate calculation of intermolecular interactions is important to our understanding of properties in large molecular systems. The high computational cost of the current "gold standard" method, coupled cluster with singles and doubles and perturbative triples (CCSD(T), limits its application to small- to medium-sized systems. Second-order Møller-Plesset perturbation (MP2) theory is a cheaper alternative for larger systems, although at the expense of its decreased accuracy, especially when treating van der Waals complexes. In this study, a new modification of the spin-component scaled MP2 method was proposed for a wide range of intermolecular complexes including two well-known datasets, S22 and S66, and a large dataset of ionic liquids consisting of 174 single ion pairs, IL174. It was found that the spin ratio, ɛΔ s=E/INT O SEIN T S S , calculated as the ratio of the opposite-spin component to the same-spin component of the interaction correlation energy fell in the range of 0.1 and 1.6, in contrast to the range of 3-4 usually observed for the ratio of absolute correlation energy, ɛs=E/OSES S , in individual molecules. Scaled coefficients were found to become negative when the spin ratio fell in close proximity to 1.0, and therefore, the studied intermolecular complexes were divided into two groups: (1) complexes with ɛΔ s< 1 and (2) complexes with ɛΔ s≥ 1 . A separate set of coefficients was obtained for both groups. Exclusion of counterpoise correction during scaling was found to produce superior results due to decreased error. Among a series of Dunning's basis sets, cc-pVTZ and cc-pVQZ were found to be the best performing ones, with a mean absolute error of 1.4 kJ mol-1 and maximum errors below 6.2 kJ mol-1. The new modification, spin-ratio scaled second-order Møller-Plesset perturbation, treats both dispersion-driven and hydrogen-bonded complexes equally well, thus validating its robustness with respect to the interaction type ranging from ionic
Advances in the analysis and prediction of turbulent viscoelastic flows
NASA Astrophysics Data System (ADS)
Gatski, T. B.; Thais, L.; Mompean, G.
2014-08-01
It has been well-known for over six decades that the addition of minute amounts of long polymer chains to organic solvents, or water, can lead to significant turbulent drag reduction. This discovery has had many practical applications such as in pipeline fluid transport, oil well operations, vehicle design and submersible vehicle projectiles, and more recently arteriosclerosis treatment. However, it has only been the last twenty-five years that the full utilization of direct numerical simulation of such turbulent viscoelastic flows has been achieved. The unique characteristics of viscoelastic fluid flow are dictated by the nonlinear differential relationship between the flow strain rate field and the extra-stress induced by the additive polymer. A primary motivation for the analysis of these turbulent fluid flows is the understanding of the effect on the dynamic transfer of energy in the turbulent flow due to the presence of the extra-stress field induced by the presence of the viscoelastic polymer chain. Such analyses now utilize direct numerical simulation data of fully developed channel flow for the FENE-P (Finite Extendable Nonlinear Elastic - Peterlin) fluid model. Such multi-scale dynamics suggests an analysis of the transfer of energy between the various component motions that include the turbulent kinetic energy, and the mean polymeric and elastic potential energies. It is shown that the primary effect of the interaction between the turbulent and polymeric fields is to transfer energy from the turbulence to the polymer.
Transient flow thrust prediction for an ejector propulsion concept
NASA Technical Reports Server (NTRS)
Drummond, Colin K.
1989-01-01
A method for predicting transient thrust augmenting ejector characteristics is introduced. The analysis blends classic self-similar turbulent jet descriptions with a mixing region control volume analysis to predict transient effects in a new way. Details of the theoretical foundation, the solution algorithm, and sample calculations are given.
NASA Technical Reports Server (NTRS)
Voorhies, Coerte V.; Conrad, Joy
1996-01-01
The geomagnetic spatial power spectrum R(sub n)(r) is the mean square magnetic induction represented by degree n spherical harmonic coefficients of the internal scalar potential averaged over the geocentric sphere of radius r. McLeod's Rule for the magnetic field generated by Earth's core geodynamo says that the expected core surface power spectrum (R(sub nc)(c)) is inversely proportional to (2n + 1) for 1 less than n less than or equal to N(sub E). McLeod's Rule is verified by locating Earth's core with main field models of Magsat data; the estimated core radius of 3485 kn is close to the seismologic value for c of 3480 km. McLeod's Rule and similar forms are then calibrated with the model values of R(sub n) for 3 less than or = n less than or = 12. Extrapolation to the degree 1 dipole predicts the expectation value of Earth's dipole moment to be about 5.89 x 10(exp 22) Am(exp 2)rms (74.5% of the 1980 value) and the expected geomagnetic intensity to be about 35.6 (mu)T rms at Earth's surface. Archeo- and paleomagnetic field intensity data show these and related predictions to be reasonably accurate. The probability distribution chi(exp 2) with 2n+1 degrees of freedom is assigned to (2n + 1)R(sub nc)/(R(sub nc). Extending this to the dipole implies that an exceptionally weak absolute dipole moment (less than or = 20% of the 1980 value) will exist during 2.5% of geologic time. The mean duration for such major geomagnetic dipole power excursions, one quarter of which feature durable axial dipole reversal, is estimated from the modern dipole power time-scale and the statistical model of excursions. The resulting mean excursion duration of 2767 years forces us to predict an average of 9.04 excursions per million years, 2.26 axial dipole reversals per million years, and a mean reversal duration of 5533 years. Paleomagnetic data show these predictions to be quite accurate. McLeod's Rule led to accurate predictions of Earth's core radius, mean paleomagnetic field
Magozzi, Sarah; Calosi, Piero
2015-01-01
Predicting species vulnerability to global warming requires a comprehensive, mechanistic understanding of sublethal and lethal thermal tolerances. To date, however, most studies investigating species physiological responses to increasing temperature have focused on the underlying physiological traits of either acute or chronic tolerance in isolation. Here we propose an integrative, synthetic approach including the investigation of multiple physiological traits (metabolic performance and thermal tolerance), and their plasticity, to provide more accurate and balanced predictions on species and assemblage vulnerability to both acute and chronic effects of global warming. We applied this approach to more accurately elucidate relative species vulnerability to warming within an assemblage of six caridean prawns occurring in the same geographic, hence macroclimatic, region, but living in different thermal habitats. Prawns were exposed to four incubation temperatures (10, 15, 20 and 25 °C) for 7 days, their metabolic rates and upper thermal limits were measured, and plasticity was calculated according to the concept of Reaction Norms, as well as Q10 for metabolism. Compared to species occupying narrower/more stable thermal niches, species inhabiting broader/more variable thermal environments (including the invasive Palaemon macrodactylus) are likely to be less vulnerable to extreme acute thermal events as a result of their higher upper thermal limits. Nevertheless, they may be at greater risk from chronic exposure to warming due to the greater metabolic costs they incur. Indeed, a trade-off between acute and chronic tolerance was apparent in the assemblage investigated. However, the invasive species P. macrodactylus represents an exception to this pattern, showing elevated thermal limits and plasticity of these limits, as well as a high metabolic control. In general, integrating multiple proxies for species physiological acute and chronic responses to increasing
ERIC Educational Resources Information Center
Powell, Erica Dion
2013-01-01
This study presents a survey developed to measure the skills of entering college freshmen in the areas of responsibility, motivation, study habits, literacy, and stress management, and explores the predictive power of this survey as a measure of academic performance during the first semester of college. The survey was completed by 334 incoming…
Vlaming, M L H; van Duijn, E; Dillingh, M R; Brands, R; Windhorst, A D; Hendrikse, N H; Bosgra, S; Burggraaf, J; de Koning, M C; Fidder, A; Mocking, J A J; Sandman, H; de Ligt, R A F; Fabriek, B O; Pasman, W J; Seinen, W; Alves, T; Carrondo, M; Peixoto, C; Peeters, P A M; Vaes, W H J
2015-08-01
Preclinical development of new biological entities (NBEs), such as human protein therapeutics, requires considerable expenditure of time and costs. Poor prediction of pharmacokinetics in humans further reduces net efficiency. In this study, we show for the first time that pharmacokinetic data of NBEs in humans can be successfully obtained early in the drug development process by the use of microdosing in a small group of healthy subjects combined with ultrasensitive accelerator mass spectrometry (AMS). After only minimal preclinical testing, we performed a first-in-human phase 0/phase 1 trial with a human recombinant therapeutic protein (RESCuing Alkaline Phosphatase, human recombinant placental alkaline phosphatase [hRESCAP]) to assess its safety and kinetics. Pharmacokinetic analysis showed dose linearity from microdose (53 μg) [(14) C]-hRESCAP to therapeutic doses (up to 5.3 mg) of the protein in healthy volunteers. This study demonstrates the value of a microdosing approach in a very small cohort for accelerating the clinical development of NBEs.
Kato, Keiichi; Ueno, Satoshi; Yabuuchi, Akiko; Uchiyama, Kazuo; Okuno, Takashi; Kobayashi, Tamotsu; Segawa, Tomoya; Teramoto, Shokichi
2014-10-01
The aim of this study was to establish a simple, objective blastocyst grading system using women's age and embryo developmental speed to predict clinical pregnancy after single vitrified-warmed blastocyst transfer. A 6-year retrospective cohort study was conducted in a private infertility centre. A total of 7341 single vitrified-armed blastocyst transfer cycles were included, divided into those carried out between 2006 and 2011 (6046 cycles) and 2012 (1295 cycles). Clinical pregnancy rate, ongoing pregnancy rate and delivery rates were stratified by women's age (<35, 35-37, 38-39, 40-41, 42-45 years) and time to blastocyst expansion (<120, 120-129, 130-139, 140-149, >149 h) as embryo developmental speed. In all the age groups, clinical pregnancy rate, ongoing pregnancy rate and delivery rates decreased as the embryo developmental speed decreased (P < 0.0001). A simple five-grade score based on women's age and embryo developmental speed was determined by actual clinical pregnancy rates observed in the 2006-2011 cohort. Subsequently, the novel grading score was validated in the 2012 cohort (1295 cycles), finding an excellent association. In conclusion, we established a novel blastocyst grading system using women's age and embryo developmental speed as objective parameters.
Essaghir, Ahmed; Toffalini, Federica; Knoops, Laurent; Kallin, Anders; van Helden, Jacques; Demoulin, Jean-Baptiste
2010-01-01
Deciphering transcription factor networks from microarray data remains difficult. This study presents a simple method to infer the regulation of transcription factors from microarray data based on well-characterized target genes. We generated a catalog containing transcription factors associated with 2720 target genes and 6401 experimentally validated regulations. When it was available, a distinction between transcriptional activation and inhibition was included for each regulation. Next, we built a tool (www.tfacts.org) that compares submitted gene lists with target genes in the catalog to detect regulated transcription factors. TFactS was validated with published lists of regulated genes in various models and compared to tools based on in silico promoter analysis. We next analyzed the NCI60 cancer microarray data set and showed the regulation of SOX10, MITF and JUN in melanomas. We then performed microarray experiments comparing gene expression response of human fibroblasts stimulated by different growth factors. TFactS predicted the specific activation of Signal transducer and activator of transcription factors by PDGF-BB, which was confirmed experimentally. Our results show that the expression levels of transcription factor target genes constitute a robust signature for transcription factor regulation, and can be efficiently used for microarray data mining. PMID:20215436
González, Lorenzo; Thorne, Leigh; Jeffrey, Martin; Martin, Stuart; Spiropoulos, John; Beck, Katy E; Lockey, Richard W; Vickery, Christopher M; Holder, Thomas; Terry, Linda
2012-11-01
It is widely accepted that abnormal forms of the prion protein (PrP) are the best surrogate marker for the infectious agent of prion diseases and, in practice, the detection of such disease-associated (PrP(d)) and/or protease-resistant (PrP(res)) forms of PrP is the cornerstone of diagnosis and surveillance of the transmissible spongiform encephalopathies (TSEs). Nevertheless, some studies question the consistent association between infectivity and abnormal PrP detection. To address this discrepancy, 11 brain samples of sheep affected with natural scrapie or experimental bovine spongiform encephalopathy were selected on the basis of the magnitude and predominant types of PrP(d) accumulation, as shown by immunohistochemical (IHC) examination; contra-lateral hemi-brain samples were inoculated at three different dilutions into transgenic mice overexpressing ovine PrP and were also subjected to quantitative analysis by three biochemical tests (BCTs). Six samples gave 'low' infectious titres (10⁶·⁵ to 10⁶·⁷ LD₅₀ g⁻¹) and five gave 'high titres' (10⁸·¹ to ≥ 10⁸·⁷ LD₅₀ g⁻¹) and, with the exception of the Western blot analysis, those two groups tended to correspond with samples with lower PrP(d)/PrP(res) results by IHC/BCTs. However, no statistical association could be confirmed due to high individual sample variability. It is concluded that although detection of abnormal forms of PrP by laboratory methods remains useful to confirm TSE infection, infectivity titres cannot be predicted from quantitative test results, at least for the TSE sources and host PRNP genotypes used in this study. Furthermore, the near inverse correlation between infectious titres and Western blot results (high protease pre-treatment) argues for a dissociation between infectivity and PrP(res).
Raymond, Yves; Champagne, Claude P
2015-04-01
The goals of this study were to evaluate the precision and accuracy of flow cytometry (FC) methodologies in the evaluation of populations of probiotic bacteria (Lactobacillus rhamnosus R0011) in two commercial dried forms, and ascertain the challenges in enumerating them in a chocolate matrix. FC analyses of total (FC(T)) and viable (FC(V)) counts in liquid or dried cultures were almost two times more precise (reproducible) than traditional direct microscopic counts (DCM) or colony forming units (CFU). With FC, it was possible to ascertain low levels of dead cells (FC(D)) in fresh cultures, which is not possible with traditional CFU and DMC methodologies. There was no interference of chocolate solids on FC counts of probiotics when inoculation was above 10(7) bacteria per g. Addition of probiotics in chocolate at 40 °C resulted in a 37% loss in viable cells. Blending of the probiotic powder into chocolate was not uniform which raised a concern that the precision of viable counts could suffer. FCT data can serve to identify the correct inoculation level of a sample, and viable counts (FCV or CFU) can subsequently be better interpreted.
NASA Astrophysics Data System (ADS)
Kommajosyula, Ravikishore; Mazzocco, Thomas; Ambrosini, Walter; Baglietto, Emilio
2016-11-01
Accurate prediction of Bubble Departure and Lift-off Diameters is key for development of closures in two-phase Eulerian CFD simulation of Flow Boiling, owing to its sensitivity in the Heat Flux partitioning approach. Several models ranging from simple correlations to solving complex force balance models have been proposed in literature; however, they rely on data-fitting for specific databases, and have shown to be inapplicable for general flow applications. The aim of this study is to extend the approach by proposing a more consistent and general formulation that accounts for relevant forces acting on the Bubble at the point of Departure and Lift-off. Among the key features of the model, the Bubble Inclination angle is treated as an unknown to be inferred along with the Departure Diameter, and the relative velocity of the bubble sliding on the surface, is modeled to determine the Lift-off Diameter. A novel expression is developed for the bubble growth force in terms of flow quantities, based on extensive data analysis. The model has been validated using 6 different experimental databases with varying flow conditions and 3 fluids. Results show high accuracy of predictions over a broad range, outperforming existing models both in terms of accuracy and generality. CASL - The Consortium for Advanced Simulation of LWRs.
Geng, Jiun-Hung; Tu, Hung-Pin; Shih, Paul Ming-Chen; Shen, Jung-Tsung; Jang, Mei-Yu; Wu, Wen-Jen; Li, Ching-Chia; Chou, Yii-Her; Juan, Yung-Shun
2015-01-01
Urolithiasis is a common disease of the urinary system. Extracorporeal shockwave lithotripsy (SWL) has become one of the standard treatments for renal and ureteral stones; however, the success rates range widely and failure of stone disintegration may cause additional outlay, alternative procedures, and even complications. We used the data available from noncontrast abdominal computed tomography (NCCT) to evaluate the impact of stone parameters and abdominal fat distribution on calculus-free rates following SWL. We retrospectively reviewed 328 patients who had urinary stones and had undergone SWL from August 2012 to August 2013. All of them received pre-SWL NCCT; 1 month after SWL, radiography was arranged to evaluate the condition of the fragments. These patients were classified into stone-free group and residual stone group. Unenhanced computed tomography variables, including stone attenuation, abdominal fat area, and skin-to-stone distance (SSD) were analyzed. In all, 197 (60%) were classified as stone-free and 132 (40%) as having residual stone. The mean ages were 49.35 ± 13.22 years and 55.32 ± 13.52 years, respectively. On univariate analysis, age, stone size, stone surface area, stone attenuation, SSD, total fat area (TFA), abdominal circumference, serum creatinine, and the severity of hydronephrosis revealed statistical significance between these two groups. From multivariate logistic regression analysis, the independent parameters impacting SWL outcomes were stone size, stone attenuation, TFA, and serum creatinine. [Adjusted odds ratios and (95% confidence intervals): 9.49 (3.72-24.20), 2.25 (1.22-4.14), 2.20 (1.10-4.40), and 2.89 (1.35-6.21) respectively, all p < 0.05]. In the present study, stone size, stone attenuation, TFA and serum creatinine were four independent predictors for stone-free rates after SWL. These findings suggest that pretreatment NCCT may predict the outcomes after SWL. Consequently, we can use these predictors for selecting
NASA Astrophysics Data System (ADS)
Ercolani, Giulia; Castelli, Fabio
2016-04-01
Data assimilation (DA) has the potential of improving hydrologic forecasts. However, many issues arise in case it is employed for spatially distributed hydrologic models that describes processes in various compartments: large dimensionality of the inverse problem, layers governed by different equations, non-linear and discontinuous model structure, complex topology of domains such as surface drainage and river network.On the other hand, integrated models offer the possibility of improving prediction of specific states by exploiting observations of quantities belonging to other compartments. In terms of forecasting river discharges, and hence for their enhancement, soil moisture is a key variable, since it determines the partitioning of rainfall into infiltration and surface runoff. However, soil moisture measurements are affected by issues that could prevent a successful DA and an actual improvement of discharge predictions.In-situ measurements suffer a dramatic spatial scarcity, while observations from satellite are barely accurate and provide spatial information only at a very coarse scale (around 40 km).Hydrologic models that explicitly represent land surface processes of coupled water and energy balance provide a valid alternative to direct DA of soil moisture.They gives the possibility of inferring soil moisture states through DA of remotely sensed Land Surface Temperature (LST), whose measurements are more accurate and with a higher spatial resolution in respect to those of soil moisture. In this work we present the assimilation of LST data in a hydrologic model (Mobidic) that is part of the operational forecasting chain for the Arno river, central Italy, with the aim of improving flood predictions. Mobidic is a raster based, continuous in time and distributed in space hydrologic model, with coupled mass and energy balance at the surface and coupled groundwater and surface hydrology. The variational approach is adopted for DA, since it requires less
Transonic Turbulent Flow Predictions With Two-Equation Turbulence Models
NASA Technical Reports Server (NTRS)
Liou, William W.; Shih, Tsan-Hsing
1996-01-01
Solutions of the Favre-averaged Navier-Stokes equations for two well-documented transonic turbulent flows are compared in detail with existing experimental data. While the boundary layer in the first case remains attached, a region of extensive flow separation has been observed in the second case. Two recently developed k-epsilon, two-equation, eddy-viscosity models are used to model the turbulence field. These models satisfy the realizability constraints of the Reynolds stresses. Comparisons with the measurements are made for the wall pressure distribution, the mean streamwise velocity profiles, and turbulent quantities. Reasonably good agreement is obtained with the experimental data.
Predicted Variations in Flow Patterns in a Horizontal CVD Reactor
NASA Technical Reports Server (NTRS)
Kuczmarski, Maria A.
1999-01-01
Expressions in terms of common reactor operating parameters were derived for the ratio of the Grashof number to the Reynolds number, Gr/Re, the ratio of the Grashof to the square of 2 the Reynolds number, Gr/Re(exp 2), and the Rayleigh number, Ra. Values for these numbers were computed for an example horizontal CVD reactor and compared to numerical simulations to gauge their effectiveness as predictors of the presence or absence of transverse and longitudinal rolls in the reactor. Comparisons were made for both argon and hydrogen carrier gases over the pressure range 2- 101 kPa. Reasonable agreement was achieved in most cases when using Gr/Re to predict the presence of transverse rolls and Ra to predict the presence of longitudinal rolls. The ratio Gr/Re(exp 2) did not yield useful predictions regarding the presence of transverse rolls. This comparison showed that the ratio of the Grashof number to the Reynolds number, as well as the Rayleigh number, can be used to predict the presence or absence of transverse and longitudinal rolls in a horizontal CVD reactor for a given set of reactor conditions. These predictions are approximate, and care must be exercised when making predictions near transition regions.
Axial flow fan broad-band noise and prediction
NASA Astrophysics Data System (ADS)
Carolus, Thomas; Schneider, Marc; Reese, Hauke
2007-02-01
Two prediction methods for broad-band noise of low-pressure axial fans are investigated. Emphasis is put on the interaction noise due to ingested turbulence. The numerical large eddy simulation (LES) is applied to predict the unsteady blade forces due to grid generated highly turbulent inflow; the blade forces are then fed into an analytical two-dimensional acoustic ducted source model. A simple semi-empirical noise prediction model (SEM) is utilized for indicative comparison. Finally, to obtain a database for detailed verification, the turbulence statistics for a variety of different inflow configurations are determined experimentally using hot wire anemometry and a correlation analysis. In the limits of the necessary assumptions the SEM predicts the noise spectra and the overall sound power surprisingly well without any further tuning of parameters; the influence of the fan operating point and the nature of the inflow is obtained. Naturally, the predicted spectra appear unrealistically "smooth", since the empirical input data are averaged and modeled in the frequency domain. By way of contrast the LES yields the fluctuating forces on the blades in the time domain. Details of the source characteristics and their origin are obtained rather clearly. The predicted effects of the ingested turbulence on the fluctuating blade forces and the fan noise compare favorably with experiments. However, the choice of the numerical grid size determines the maximal resolvable frequency and the computational cost. As contrasted with the SEM, the cost for the LES-based method are immense.
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.
Wang, Shiyao; Deng, Zhidong; Yin, Gang
2016-02-24
A high-performance differential global positioning system (GPS) receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.
Wang, Shiyao; Deng, Zhidong; Yin, Gang
2016-01-01
A high-performance differential global positioning system (GPS) receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108
Martin, Eric; Mukherjee, Prasenjit; Sullivan, David; Jansen, Johanna
2011-08-22
Profile-QSAR is a novel 2D predictive model building method for kinases. This "meta-QSAR" method models the activity of each compound against a new kinase target as a linear combination of its predicted activities against a large panel of 92 previously studied kinases comprised from 115 assays. Profile-QSAR starts with a sparse incomplete kinase by compound (KxC) activity matrix, used to generate Bayesian QSAR models for the 92 "basis-set" kinases. These Bayesian QSARs generate a complete "synthetic" KxC activity matrix of predictions. These synthetic activities are used as "chemical descriptors" to train partial-least squares (PLS) models, from modest amounts of medium-throughput screening data, for predicting activity against new kinases. The Profile-QSAR predictions for the 92 kinases (115 assays) gave a median external R²(ext) = 0.59 on 25% held-out test sets. The method has proven accurate enough to predict pairwise kinase selectivities with a median correlation of R²(ext) = 0.61 for 958 kinase pairs with at least 600 common compounds. It has been further expanded by adding a "C(k)XC" cellular activity matrix to the KxC matrix to predict cellular activity for 42 kinase driven cellular assays with median R²(ext) = 0.58 for 24 target modulation assays and R²(ext) = 0.41 for 18 cell proliferation assays. The 2D Profile-QSAR, along with the 3D Surrogate AutoShim, are the foundations of an internally developed iterative medium-throughput screening (IMTS) methodology for virtual screening (VS) of compound archives as an alternative to experimental high-throughput screening (HTS). The method has been applied to 20 actual prospective kinase projects. Biological results have so far been obtained in eight of them. Q² values ranged from 0.3 to 0.7. Hit-rates at 10 uM for experimentally tested compounds varied from 25% to 80%, except in K5, which was a special case aimed specifically at finding "type II" binders, where none of the compounds were predicted to be
Oyedepo, Gbenga A; Wilson, Angela K
2010-08-26
The correlation consistent Composite Approach, ccCA [ Deyonker , N. J. ; Cundari , T. R. ; Wilson , A. K. J. Chem. Phys. 2006 , 124 , 114104 ] has been demonstrated to predict accurate thermochemical properties of chemical species that can be described by a single configurational reference state, and at reduced computational cost, as compared with ab initio methods such as CCSD(T) used in combination with large basis sets. We have developed three variants of a multireference equivalent of this successful theoretical model. The method, called the multireference correlation consistent composite approach (MR-ccCA), is designed to predict the thermochemical properties of reactive intermediates, excited state species, and transition states to within chemical accuracy (e.g., 1 kcal/mol for enthalpies of formation) of reliable experimental values. In this study, we have demonstrated the utility of MR-ccCA: (1) in the determination of the adiabatic singlet-triplet energy separations and enthalpies of formation for the ground states for a set of diradicals and unsaturated compounds, and (2) in the prediction of energetic barriers to internal rotation, in ethylene and its heavier congener, disilene. Additionally, we have utilized MR-ccCA to predict the enthalpies of formation of the low-lying excited states of all the species considered. MR-ccCA is shown to give quantitative results without reliance upon empirically derived parameters, making it suitable for application to study novel chemical systems with significant nondynamical correlation effects.
Reichen, J; Widmer, T; Cotting, J
1991-09-01
We retrospectively analyzed the predictive accuracy of serial determinations of galactose elimination capacity in 61 patients with primary biliary cirrhosis. Death was predicted from the time that the regression line describing the decline in galactose elimination capacity vs. time intersected a value of 4 mg.min-1.kg-1. Thirty-one patients exhibited decreasing galactose elimination capacity; in 11 patients it remained stable and in 19 patients only one value was available. Among those patients with decreasing galactose elimination capacity, 10 died and three underwent liver transplantation; prediction of death was accurate to 7 +/- 19 mo. This criterion incorrectly predicted death in two patients with portal-vein thrombosis; otherwise, it did better than or as well as the Mayo clinic score. The latter was also tested on our patients and was found to adequately describe risk in yet another independent population of patients with primary biliary cirrhosis. Cox regression analysis selected only bilirubin and galactose elimination capacity, however, as independent predictors of death. We submit that serial determination of galactose elimination capacity in patients with primary biliary cirrhosis may be a useful adjunct to optimize the timing of liver transplantation and to evaluate new pharmacological treatment modalities of this disease.
NASA Astrophysics Data System (ADS)
Rocha, Joana
2016-07-01
A precise definition of the turbulent boundary layer excitation is required to accurately predict the sound radiation and surface vibration levels, produced by an aircraft panel excited turbulent flow during flight. Hence, any existing inaccuracy on turbulent boundary layer excitation models leads to an inaccurate prediction of the panel response. A number of empirical models have been developed over the years to provide the turbulent boundary layer wall pressure spectral density. However, different empirical models provide dissimilar predictions for the wall pressure spectral density. The objective of the present study is to investigate and quantify the impact of the chosen empirical model on the predicted radiated sound power, and on the predicted panel surface acceleration levels. This study provides a novel approach and a detailed analysis on the use of different turbulent boundary layer wall pressure empirical models, and impact on mathematical predictions. Closed-form mathematical relationships are developed, and recommendations are provided for the level of deviation and uncertainty associated to different models, in relation to a baseline model, both for panel surface acceleration and radiated sound power.
Measurement and infrared image prediction of a heated exhaust flow
NASA Astrophysics Data System (ADS)
Nelson, Edward L.; Mahan, J. Robert; Turk, Jeffrey A.; Birckelbaw, Larry D.; Wardwell, Douglas A.; Hange, Craig E.
1994-06-01
The focus of the current research is to numerically predict an infrared image of a jet engine exhaust plume, given field variables such as temperature, pressure, and exhaust plume constituents as a function of spatial position within the plume, and to compare this predicted image directly with measured data. This work is motivated by the need to validate CFD codes through infrared imaging. The technique of reducing the 3D field-variable domain to a 2D infrared image invokes the use of an inverse Monte-Carlo ray trace algorithm and an infrared band model for exhaust gases. This paper describes an experiment in which the above- mentioned field variables were carefully measured. Data from this experiment in the form of velocity plots are shown. The inverse Monte-Carlo ray trace technique is described. Finally, an experimentally obtained infrared image is directly compared to an infrared image predicted from the measured field variables.
Prediction and Control of Vortex Dominated and Vortex-wake Flows
NASA Technical Reports Server (NTRS)
Kandil, Osama
1996-01-01
This report describes the activities and accomplishments under this research grant, including a list of publications and dissertations, produced in the field of prediction and control of vortex dominated and vortex wake flows.
Use of finite volume radiation for predicting the Knudsen minimum in 2D channel flow
Malhotra, Chetan P.; Mahajan, Roop L.
2014-12-09
In an earlier paper we employed an analogy between surface-to-surface radiation and free-molecular flow to model Knudsen flow through tubes and onto planes. In the current paper we extend the analogy between thermal radiation and molecular flow to model the flow of a gas in a 2D channel across all regimes of rarefaction. To accomplish this, we break down the problem of gaseous flow into three sub-problems (self-diffusion, mass-motion and generation of pressure gradient) and use the finite volume method for modeling radiation through participating media to model the transport in each sub-problem as a radiation problem. We first model molecular self-diffusion in the stationary gas by modeling the transport of the molecular number density through the gas starting from the analytical asymptote for free-molecular flow to the kinetic theory limit of gaseous self-diffusion. We then model the transport of momentum through the gas at unit pressure gradient to predict Poiseuille flow and slip flow in the 2D gas. Lastly, we predict the generation of pressure gradient within the gas due to molecular collisions by modeling the transport of the forces generated due to collisions per unit volume of gas. We then proceed to combine the three radiation problems to predict flow of the gas over the entire Knudsen number regime from free-molecular to transition to continuum flow and successfully capture the Knudsen minimum at Kn ∼ 1.
NASA Astrophysics Data System (ADS)
Tetrault, Philippe-Andre
2000-10-01
In transonic flow, the aerodynamic interference that occurs on a strut-braced wing airplane, pylons, and other applications is significant. The purpose of this work is to provide relationships to estimate the interference drag of wing-strut, wing-pylon, and wing-body arrangements. Those equations are obtained by fitting a curve to the results obtained from numerous Computational Fluid Dynamics (CFD) calculations using state-of-the-art codes that employ the Spalart-Allmaras turbulence model. In order to estimate the effect of the strut thickness, the Reynolds number of the flow, and the angle made by the strut with an adjacent surface, inviscid and viscous calculations are performed on a symmetrical strut at an angle between parallel walls. The computations are conducted at a Mach number of 0.85 and Reynolds numbers of 5.3 and 10.6 million based on the strut chord. The interference drag is calculated as the drag increment of the arrangement compared to an equivalent two-dimensional strut of the same cross-section. The results show a rapid increase of the interference drag as the angle of the strut deviates from a position perpendicular to the wall. Separation regions appear for low intersection angles, but the viscosity generally provides a positive effect in alleviating the strength of the shock near the junction and thus the drag penalty. When the thickness-to-chord ratio of the strut is reduced, the flowfield is disturbed only locally at the intersection of the strut with the wall. This study provides an equation to estimate the interference drag of simple intersections in transonic flow. In the course of performing the calculations associated with this work, an unstructured flow solver was utilized. Accurate drag prediction requires a very fine grid and this leads to problems associated with the grid generator. Several challenges facing the unstructured grid methodology are discussed: slivers, grid refinement near the leading edge and at the trailing edge, grid
Turbulence Modeling for Thrust Reverser Flow Field Prediction Methods
1992-12-01
Barata 28 of a normal impinging jet at H/D = 5 and Vj/V_. = 30 indicate that the shear stress in the vortex is roughly an order of magnitude less than...Speed Afterbody Flows," 1. Propulsion and Power, Vol. 7, No. 4, 1991, pp. 607-616 28. Barata , J. M. M., Durao, D. F. G., and Heitor, M. V., "Turbulent
Fluid Flow Prediction with Development System Interwell Connectivity Influence
NASA Astrophysics Data System (ADS)
Bolshakov, M.; Deeva, T.; Pustovskikh, A.
2016-03-01
In this paper interwell connectivity has been studied. First of all, literature review of existing methods was made which is divided into three groups: Statistically-Based Methods, Material (fluid) Propagation-Based Methods and Potential (pressure) Change Propagation-Based Method. The disadvantages of the first and second groups are as follows: methods do not involve fluid flow through porous media, ignore any changes of well conditions (BHP, skin factor, etc.). The last group considers changes of well conditions and fluid flow through porous media. In this work Capacitance method (CM) has been chosen for research. This method is based on material balance and uses weight coefficients lambdas to assess well influence. In the next step synthetic model was created for examining CM. This model consists of an injection well and a production well. CM gave good results, it means that flow rates which were calculated by analytical method (CM) show matching with flow rate in model. Further new synthetic model was created which includes six production and one injection wells. This model represents seven-spot pattern. To obtain lambdas weight coefficients, the delta function was entered using by minimization algorithm. Also synthetic model which has three injectors and thirteen producer wells was created. This model simulates seven-spot pattern production system. Finally Capacitance method (CM) has been adjusted on real data of oil Field Ω. In this case CM does not give enough satisfying results in terms of field data liquid rate. In conclusion, recommendations to simplify CM calculations were given. Field Ω is assumed to have one injection and one production wells. In this case, satisfying results for production rates and cumulative production were obtained.
Heat Transfer Prediction of Film Cooling in Supersonic Flow
NASA Astrophysics Data System (ADS)
Luchi, Riccardo; Salvadori, Simone; Martelli, Francesco
2008-09-01
Considering the modern high pressure stages of gas turbines, the flow over the suction side of the blades can be affected by the presence of shock impingement and boundary layer separation. Furthermore, it should be pointed out that the combustor exit temperature reaches values which are close to the allowable material limit. Then, a cooling system based on the film cooling approach should be designed to prevent failure. The interaction between the ejected coolant and the shock impingement must be studied to achieve a higher efficiency of the cooling system. The proposed approach is based on the numerical evaluation of a film cooled test section experimentally studied at the University of Karlsruhe. The testing rig consists in a converging-diverging nozzle that accelerates the flow up to sonic conditions while an oblique shock is generated at the nozzle exit section. Three cases have been studied, changing the cooling holes position with respect to the shock impingement over the cooled surface. The obtained results are presented and compared with the experimental data. The used solver is the in-house CFD 3D code HybFlow, developed at the University of Florence. This study has been carried out in the frame of the EU funded TATEF2 project.
Using Prediction Markets to Track Information Flows: Evidence from Google
NASA Astrophysics Data System (ADS)
Cowgill, Bo; Wolfers, Justin; Zitzewitz, Eric
Since 2005, Google has conducted the largest corporate experiment with prediction markets we are aware of. In this paper, we illustrate how markets can be used to study how an organization processes information. We show that market participants are not typical of Google’s workforce, and that market participation and success is skewed towards Google’s engineering and quantitatively oriented employees.
NASA Technical Reports Server (NTRS)
Simonich, J. C.
1989-01-01
Prediction of helicopter main rotor noise due to ingestion of atmospheric turbulence was analyzed. The analysis combines several different models that describe the fluid mechanics of the turbulence and the ingestion process. Two models, atmospheric turbulence, and mean flow and turbulence contraction were covered. The third model, covered in a separate report, describes the rotor acoustic mode. The method incorporates the atmospheric turbulence model and a rapid distortion turbulence contraction description to determine the statistics of the anisotropic turbulence at the rotor plane. The analytical basis for a module was provided which was incorporated in NASA's ROTONET helicopter noise prediction program. The mean flow and turbulence statistics associated with the atmospheric boundary layer were modeled including effects of atmospheric stability length, wind speed, and altitude. The turbulence distortion process is modeled as a deformation of vortex filaments (which represent the turbulence field) by a mean flow field due to the rotor inflow.
Three dimensional numerical prediction of two phase flow in industrial CFB boiler
Balzer, G.; Simonin, O.
1997-12-31
Gas-solid two phase flows are encountered in number of industrial applications such as pneumatic transport, catalytic cracking, coal combustors. The paper aims at presenting the numerical model of gas-solid flows which have been developed for several years at the Laboratoire National d`Hydraulique of Electricite de France and its application to the prediction of an industrial CFB Boiler.
Simple numerical method for predicting steady compressible flows
NASA Technical Reports Server (NTRS)
Von Lavante, E.; Melson, N. Duane
1987-01-01
The present numerical method for the solution of the isenthalpic form of the governing equations for compressible viscous and inviscid flows has its basis in the concept of flux vector splitting in its implicit form, and has been tested in the cases of several difficult viscous and inviscid configurations. An acceleration of time-marching to steady state is accomplished by implementing a multigrid procedure which effectively increases the convergence rate. The steady state results obtained are largely of good quality, and required only short computational times.
Transonic vortical flow predicted with a structured miltiblock Euler solver
NASA Astrophysics Data System (ADS)
Santillan, S.; Selmin, V.
A methodology for solving the Euler equations in geometrically complex domains has been developed at Alenia (DVD). The general features of the Alenia multiblock system, which provides a grid generation and Euler solution capability for complex configuration, are discussed. A systematic multiblock grid generator has been used to make the grids. Numerical results compared with available experimental data in transonic vortical flow around delta wing, wing-body and wing-body-canard configurations with sharp leading edge are presented and explained in a physical context.
Simple numerical method for predicting steady compressible flows
NASA Technical Reports Server (NTRS)
Vonlavante, Ernst; Nelson, N. Duane
1986-01-01
A numerical method for solving the isenthalpic form of the governing equations for compressible viscous and inviscid flows was developed. The method was based on the concept of flux vector splitting in its implicit form. The method was tested on several demanding inviscid and viscous configurations. Two different forms of the implicit operator were investigated. The time marching to steady state was accelerated by the implementation of the multigrid procedure. Its various forms very effectively increased the rate of convergence of the present scheme. High quality steady state results were obtained in most of the test cases; these required only short computational times due to the relative efficiency of the basic method.
2016-01-01
Drug discovery programs frequently target members of the human kinome and try to identify small molecule protein kinase inhibitors, primarily for cancer treatment, additional indications being increasingly investigated. One of the challenges is controlling the inhibitors degree of selectivity, assessed by in vitro profiling against panels of protein kinases. We manually extracted, compiled, and standardized such profiles published in the literature: we collected 356 908 data points corresponding to 482 protein kinases, 2106 inhibitors, and 661 patents. We then analyzed this data set in terms of kinome coverage, results reproducibility, popularity, and degree of selectivity of both kinases and inhibitors. We used the data set to create robust proteochemometric models capable of predicting kinase activity (the ligand–target space was modeled with an externally validated RMSE of 0.41 ± 0.02 log units and R02 0.74 ± 0.03), in order to account for missing or unreliable measurements. The influence on the prediction quality of parameters such as number of measurements, Murcko scaffold frequency or inhibitor type was assessed. Interpretation of the models enabled to highlight inhibitors and kinases properties correlated with higher affinities, and an analysis in the context of kinases crystal structures was performed. Overall, the models quality allows the accurate prediction of kinase-inhibitor activities and their structural interpretation, thus paving the way for the rational design of compounds with a targeted selectivity profile. PMID:27482722
Adde, Lars; Helbostad, Jorunn; Jensenius, Alexander R; Langaas, Mette; Støen, Ragnhild
2013-08-01
This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies.
Unsteady-flow-field predictions for oscillating cascades
NASA Technical Reports Server (NTRS)
Huff, Dennis L.
1991-01-01
The unsteady flow field around an oscillating cascade of flat plates with zero stagger was studied by using a time marching Euler code. This case had an exact solution based on linear theory and served as a model problem for studying pressure wave propagation in the numerical solution. The importance of using proper unsteady boundary conditions, grid resolution, and time step size was shown for a moderate reduced frequency. Results show that an approximate nonreflecting boundary condition based on linear theory does a good job of minimizing reflections from the inflow and outflow boundaries and allows the placement of the boundaries to be closer to the airfoils than when reflective boundaries are used. Stretching the boundary to dampen the unsteady waves is another way to minimize reflections. Grid clustering near the plates captures the unsteady flow field better than when uniform grids are used as long as the 'Courant Friedrichs Levy' (CFL) number is less than 1 for a sufficient portion of the grid. Finally, a solution based on an optimization of grid, CFL number, and boundary conditions shows good agreement with linear theory.
Applications Determine the Best Model to Predict Flow Duration Curves in Ungauged Basins
NASA Astrophysics Data System (ADS)
Muller, M. F.; Thompson, S. E.
2014-12-01
Flow duration curves (FDCs) are an important tool for watershed management and their prediction in ungauged catchments is a challenging problem. Selecting the most appropriate model for prediction the FDC is itself a challenge that determines how theoretical improvements in prediction are transferred into engineering practice. Available performance metrics (e.g., Nash Sutcliffe Coefficient, error on flow moments) typically consider the aggregated ability of the model to predict all streamflow quantiles. These metrics may be inappropriate for model selection in practice because watershed management decisions are typically driven by a limited number of streamflow quantiles that may be poorly represented by an aggregate performance metric. As an illustrative case study, the performance of three distinct FDC prediction approaches -- graphical, statistical and process-based -- are compared for ungauged streams in Nepal. The practical application of these predictions is to inform the design of run-of-river hydropower plants. The process-based approach provides the best prediction of the observed flow distribution and results in significantly higher Nash coefficients. However, the graphical approach provides the best prediction of the flow quantiles that are most relevant for hydropower design and reduces the design error caused by streamflow estimation. To assist in an application driven model selection process, we propose a novel model selection framework.
NASA Technical Reports Server (NTRS)
Chang, Chau-Lyan; Venkatachari, Balaji Shankar; Cheng, Gary
2013-01-01
With the wide availability of affordable multiple-core parallel supercomputers, next generation numerical simulations of flow physics are being focused on unsteady computations for problems involving multiple time scales and multiple physics. These simulations require higher solution accuracy than most algorithms and computational fluid dynamics codes currently available. This paper focuses on the developmental effort for high-fidelity multi-dimensional, unstructured-mesh flow solvers using the space-time conservation element, solution element (CESE) framework. Two approaches have been investigated in this research in order to provide high-accuracy, cross-cutting numerical simulations for a variety of flow regimes: 1) time-accurate local time stepping and 2) highorder CESE method. The first approach utilizes consistent numerical formulations in the space-time flux integration to preserve temporal conservation across the cells with different marching time steps. Such approach relieves the stringent time step constraint associated with the smallest time step in the computational domain while preserving temporal accuracy for all the cells. For flows involving multiple scales, both numerical accuracy and efficiency can be significantly enhanced. The second approach extends the current CESE solver to higher-order accuracy. Unlike other existing explicit high-order methods for unstructured meshes, the CESE framework maintains a CFL condition of one for arbitrarily high-order formulations while retaining the same compact stencil as its second-order counterpart. For large-scale unsteady computations, this feature substantially enhances numerical efficiency. Numerical formulations and validations using benchmark problems are discussed in this paper along with realistic examples.
Assessment of a 3-D boundary layer code to predict heat transfer and flow losses in a turbine
NASA Technical Reports Server (NTRS)
Vatsa, V. N.
1983-01-01
The prediction of the complete flow field in a turbine passage is an extremely difficult task due to the complex three dimensional pattern which contains separation and attachment lines, a saddle point and horseshoe vortex. Whereas, in principle such a problem can be solved using full Navier-Stokes equations, in reality methods based on a Navier-Stokes solution procedure encounter difficulty in accurately predicting surface quantities (e.g., heat transfer) due to grid limitations imposed by the speed and size of the existing computers. On the other hand the overall problem is strongly three dimensional and too complex to be analyzed by the current design methods based on inviscid and/or viscous strip theories. Thus there is a strong need for enhancing the current prediction techniques through inclusion of 3-D viscous effects. A potentially simple and cost effective way to achieve this is to use a prediction method based on three dimensional boundary layer (3-DBL) theory. The major objective of this program is to assess the applicability of such a 3-DBL approach for the prediction of heat loads, boundary layer growth, pressure losses and streamline skewing in critical areas of a turbine passage. A brief discussion of the physical problem addressed here along with the overall approach is presented.
NASA Astrophysics Data System (ADS)
Hrubý, Jan
2012-04-01
Mathematical modeling of the non-equilibrium condensing transonic steam flow in the complex 3D geometry of a steam turbine is a demanding problem both concerning the physical concepts and the required computational power. Available accurate formulations of steam properties IAPWS-95 and IAPWS-IF97 require much computation time. For this reason, the modelers often accept the unrealistic ideal-gas behavior. Here we present a computation scheme based on a piecewise, thermodynamically consistent representation of the IAPWS-95 formulation. Density and internal energy are chosen as independent variables to avoid variable transformations and iterations. On the contrary to the previous Tabular Taylor Series Expansion Method, the pressure and temperature are continuous functions of the independent variables, which is a desirable property for the solution of the differential equations of the mass, energy, and momentum conservation for both phases.
Residual bias in a multiphase flow model calibration and prediction
Poeter, E.P.; Johnson, R.H.
2002-01-01
When calibrated models produce biased residuals, we assume it is due to an inaccurate conceptual model and revise the model, choosing the most representative model as the one with the best-fit and least biased residuals. However, if the calibration data are biased, we may fail to identify an acceptable model or choose an incorrect model. Conceptual model revision could not eliminate biased residuals during inversion of simulated DNAPL migration under controlled conditions at the Borden Site near Ontario Canada. This paper delineates hypotheses for the source of bias, and explains the evolution of the calibration and resulting model predictions.
Chao, Chien-Chung; Zhangm, Zhiwen; Weissenberger, Giulia; Chen, Hua-Wei; Ching, Wei-Mei
2017-03-01
Scrub typhus (ST) is an infection caused by Orientia tsutsugamushi. Historically, ST was ranked as the second most important arthropod-borne medical problem only behind malaria during World War II and the Vietnam War. The disease occurs mainly in Southeast Asia and has been shown to emerge and reemerge in new areas, implying the increased risk for U.S. military and civilian personnel deployed to these regions. ST can effectively be treated by doxycycline provided the diagnosis is made early, before the development of severe complications. Scrub Typhus Detect is a lateral flow rapid test based on a mixture of recombinant 56-kDa antigens with broad reactivity. The performance of this prototype product was evaluated against indirect immunofluorescence assay, the serological gold standard. Using 249 prospectively collected samples from Thailand, the sensitivity and specificity for IgM was found to be 100% and 92%, respectively, suggesting a high potential of this product for clinical use. This product will provide a user friendly, rapid, and accurate diagnosis of ST for clinicians to provide timely and accurate treatments of deployed personnel.
NASA Technical Reports Server (NTRS)
Constantinescu, George S.; Lele, S. K.
2001-01-01
Numerical methods for solving the flow equations in cylindrical or spherical coordinates should be able to capture the behavior of the exact solution near the regions where the particular form of the governing equations is singular. In this work we focus on the treatment of these numerical singularities for finite-differences methods by reinterpreting the regularity conditions developed in the context of pseudo-spectral methods. A generally applicable numerical method for treating the singularities present at the polar axis, when nonaxisymmetric flows are solved in cylindrical, coordinates using highly accurate finite differences schemes (e.g., Pade schemes) on non-staggered grids, is presented. Governing equations for the flow at the polar axis are derived using series expansions near r=0. The only information needed to calculate the coefficients in these equations are the values of the flow variables and their radial derivatives at the previous iteration (or time) level. These derivatives, which are multi-valued at the polar axis, are calculated without dropping the accuracy of the numerical method using a mapping of the flow domain from (0,R)*(0,2pi) to (-R,R)*(0,pi), where R is the radius of the computational domain. This allows the radial derivatives to be evaluated using high-order differencing schemes (e.g., compact schemes) at points located on the polar axis. The proposed technique is illustrated by results from simulations of laminar-forced jets and turbulent compressible jets using large eddy simulation (LES) methods. In term of the general robustness of the numerical method and smoothness of the solution close to the polar axis, the present results compare very favorably to similar calculations in which the equations are solved in Cartesian coordinates at the polar axis, or in which the singularity is removed by employing a staggered mesh in the radial direction without a mesh point at r=0, following the method proposed recently by Mohseni and Colonius
Measurement and multidimensional prediction of flow in a axisymmetric port/valve assembly
Gosman, A.D.; Ahmed, A.M.Y.
1987-01-01
The results are reported of a combined experimental and computational study of steady flow through an axisymmetric valve/port assembly, the main objective of which was to assess the accuracy of the multidimensional model predictions of this flow. Measurements of the discharge coefficient, mean velocity and the turbulent Reynolds stress fields were obtained by hot-wire anemometry at various valve lifts. These were supplemented by flow visualisation studies. Predictions were made using a finite-volume method employing a body-fitted computational mesh and the k-epsilon turbulence model. Good agreement was found at low lifts, but at higher values this deteriorated due to the inability of the turbulence model to provoke the flow separations which occurred in the experiments. The conclusion is that for both idealised and practical ports multidimensional predictions will be of limited accuracy until better turbulence models become available.
Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft
NASA Technical Reports Server (NTRS)
Birckelbaw, Lourdes G.
1992-01-01
A ski jump model was developed to predict ski jump takeoff performance for a short takeoff and vertical landing (STOVL) aircraft. The objective was to verify the model with results from a piloted simulation of a mixed flow, remote lift STOVL aircraft. The prediction model is discussed. The predicted results are compared with the piloted simulation results. The ski jump model can be utilized for basic research of other thrust vectoring STOVL aircraft performing a ski jump takeoff.
NASA Astrophysics Data System (ADS)
Silva, Goncalo; Talon, Laurent; Ginzburg, Irina
2017-04-01
is thoroughly evaluated in three benchmark tests, which are run throughout three distinctive permeability regimes. The first configuration is a horizontal porous channel, studied with a symbolic approach, where we construct the exact solutions of FEM and BF/IBF with different boundary schemes. The second problem refers to an inclined porous channel flow, which brings in as new challenge the formation of spurious boundary layers in LBM; that is, numerical artefacts that arise due to a deficient accommodation of the bulk solution by the low-accurate boundary scheme. The third problem considers a porous flow past a periodic square array of solid cylinders, which intensifies the previous two tests with the simulation of a more complex flow pattern. The ensemble of numerical tests provides guidelines on the effect of grid resolution and the TRT free collision parameter over the accuracy and the quality of the velocity field, spanning from Stokes to Darcy permeability regimes. It is shown that, with the use of the high-order accurate boundary schemes, the simple, uniform-mesh-based TRT-LBM formulation can even surpass the accuracy of FEM employing hardworking body-fitted meshes.
Howdeshell, Kembra L.; Rider, Cynthia V.; Wilson, Vickie S.; Furr, Johnathan R.; Lambright, Christy R.; Gray, L. Earl
2015-01-01
Challenges in cumulative risk assessment of anti-androgenic phthalate mixtures include a lack of data on all the individual phthalates and difficulty determining the biological relevance of reduction in fetal testosterone (T) on postnatal development. The objectives of the current study were 2-fold: (1) to test whether a mixture model of dose addition based on the fetal T production data of individual phthalates would predict the effects of a 5 phthalate mixture on androgen-sensitive postnatal male reproductive tract development, and (2) to determine the biological relevance of the reductions in fetal T to induce abnormal postnatal reproductive tract development using data from the mixture study. We administered a dose range of the mixture (60, 40, 20, 10, and 5% of the top dose used in the previous fetal T production study consisting of 300 mg/kg per chemical of benzyl butyl (BBP), di(n)butyl (DBP), diethyl hexyl phthalate (DEHP), di-isobutyl phthalate (DiBP), and 100 mg dipentyl (DPP) phthalate/kg; the individual phthalates were present in equipotent doses based on their ability to reduce fetal T production) via gavage to Sprague Dawley rat dams on GD8-postnatal day 3. We compared observed mixture responses to predictions of dose addition based on the previously published potencies of the individual phthalates to reduce fetal T production relative to a reference chemical and published postnatal data for the reference chemical (called DAref). In addition, we predicted DA (called DAall) and response addition (RA) based on logistic regression analysis of all 5 individual phthalates when complete data were available. DA ref and DA all accurately predicted the observed mixture effect for 11 of 14 endpoints. Furthermore, reproductive tract malformations were seen in 17–100% of F1 males when fetal T production was reduced by about 25–72%, respectively. PMID:26350170
Ferrari, Clarissa; Uher, Rudolf; Bocchio-Chiavetto, Luisella; Riva, Marco Andrea; Pariante, Carmine M.
2016-01-01
Background: Increased levels of inflammation have been associated with a poorer response to antidepressants in several clinical samples, but these findings have had been limited by low reproducibility of biomarker assays across laboratories, difficulty in predicting response probability on an individual basis, and unclear molecular mechanisms. Methods: Here we measured absolute mRNA values (a reliable quantitation of number of molecules) of Macrophage Migration Inhibitory Factor and interleukin-1β in a previously published sample from a randomized controlled trial comparing escitalopram vs nortriptyline (GENDEP) as well as in an independent, naturalistic replication sample. We then used linear discriminant analysis to calculate mRNA values cutoffs that best discriminated between responders and nonresponders after 12 weeks of antidepressants. As Macrophage Migration Inhibitory Factor and interleukin-1β might be involved in different pathways, we constructed a protein-protein interaction network by the Search Tool for the Retrieval of Interacting Genes/Proteins. Results: We identified cutoff values for the absolute mRNA measures that accurately predicted response probability on an individual basis, with positive predictive values and specificity for nonresponders of 100% in both samples (negative predictive value=82% to 85%, sensitivity=52% to 61%). Using network analysis, we identified different clusters of targets for these 2 cytokines, with Macrophage Migration Inhibitory Factor interacting predominantly with pathways involved in neurogenesis, neuroplasticity, and cell proliferation, and interleukin-1β interacting predominantly with pathways involved in the inflammasome complex, oxidative stress, and neurodegeneration. Conclusion: We believe that these data provide a clinically suitable approach to the personalization of antidepressant therapy: patients who have absolute mRNA values above the suggested cutoffs could be directed toward earlier access to more
Impact of meteorological predictions on real-time spring flow forecasting
NASA Astrophysics Data System (ADS)
Coulibaly, Paulin
2003-12-01
Meteorological predictions, such as precipitation and temperature, are commonly used to improve real-time hydrologic forecasting, despite their inherent uncertainty and their absence in the model calibration stage. In this study, we quantify the effect of meteorological prediction errors on the accuracy of daily spring reservoir inflow forecasts using weather predictions in both the model calibration and testing phases. Different modelling experiments are compared using an operational conceptual model and nonlinear empirical models to assess the effects of using daily numerical weather predictions as opposed to the use of historical observations. It is found that, even with large prediction errors, meteorological forecasts can provide significant improvement of spring flow forecast for up to 7 days lead time, particularly for low