Science.gov

Sample records for flow prediction tools

  1. 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."

  2. Development of Next Generation Multiphase Pipe Flow Prediction Tools

    SciTech Connect

    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

  3. Development of Next Generation Multiphase Pipe Flow Prediction Tools

    SciTech Connect

    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

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

    NASA Astrophysics Data System (ADS)

    Kibler, K. M.; Alipour, M.

    2016-12-01

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

  5. Compressor map prediction tool

    NASA Astrophysics Data System (ADS)

    Ravi, Arjun; Sznajder, Lukasz; Bennett, Ian

    2015-08-01

    Shell Global Solutions uses an in-house developed system for remote condition monitoring of centrifugal compressors. It requires field process data collected during operation to calculate and assess the machine's performance. Performance is assessed by comparing live results of polytropic head and efficiency versus design compressor curves provided by the Manufacturer. Typically, these design curves are given for specific suction conditions. The further these conditions on site deviate from those prescribed at design, the less accurate the health assessment of the compressor becomes. To address this specified problem, a compressor map prediction tool is proposed. The original performance curves of polytropic head against volumetric flow for varying rotational speeds are used as an input to define a range of Mach numbers within which the non-dimensional invariant performance curve of head and volume flow coefficient is generated. The new performance curves of polytropic head vs. flow for desired set of inlet conditions are then back calculated using the invariant non-dimensional curve. Within the range of Mach numbers calculated from design data, the proposed methodology can predict polytropic head curves at a new set of inlet conditions within an estimated 3% accuracy. The presented methodology does not require knowledge of detailed impeller geometry such as throat areas, blade number, blade angles, thicknesses nor other aspects of the aerodynamic design - diffusion levels, flow angles, etc. The only required mechanical design feature is the first impeller tip diameter. Described method makes centrifugal compressor surveillance activities more accurate, enabling precise problem isolation affecting machine's performance.

  6. An efficient tool for modeling and predicting fluid flow in nanochannels.

    PubMed

    Ahadian, Samad; Mizuseki, Hiroshi; Kawazoe, Yoshiyuki

    2009-11-14

    Molecular dynamics simulations were performed to evaluate the penetration of two different fluids (i.e., a Lennard-Jones fluid and a polymer) through a designed nanochannel. For both fluids, the length of permeation as a function of time was recorded for various wall-fluid interactions. A novel methodology, namely, the artificial neural network (ANN) approach was then employed for modeling and prediction of the length of imbibition as a function of influencing parameters (i.e., time, the surface tension and the viscosity of fluids, and the wall-fluid interaction). It was demonstrated that the designed ANN is capable of modeling and predicting the length of penetration with superior accuracy. Moreover, the importance of variables in the designed ANN, i.e., time, the surface tension and the viscosity of fluids, and the wall-fluid interaction, was demonstrated with the aid of the so-called connection weight approach, by which all parameters are simultaneously considered. It was revealed that the wall-fluid interaction plays a significant role in such transport phenomena, namely, fluid flow in nanochannels.

  7. New Tool to Predict Glaucoma

    MedlinePlus

    ... News About Us Donate In This Section A New Tool to Predict Glaucoma email Send this article ... determine if a patient has glaucoma. Recently, a new tool has become available to eye care specialists ...

  8. The Implementation and Evaluation of the Patient Admission Prediction Tool: Assessing Its Impact on Decision-Making Strategies and Patient Flow Outcomes in 2 Australian Hospitals.

    PubMed

    Crilly, Julia L; Boyle, Justin; Jessup, Melanie; Wallis, Marianne; Lind, James; Green, David; FitzGerald, Gerry

    2015-01-01

    To evaluate the implementation of a Patient Admission Prediction Tool (PAPT) in terms of patient flow outcomes and decision-making strategies. The PAPT was implemented in 2 Australian public teaching hospitals during October-December 2010 (hospital A) and October-December 2011 (hospital B). A multisite prospective, comparative (before and after) design was used. Patient flow outcomes measured included access block and hospital occupancy. Daily and weekly data were collected from patient flow reports and routinely collected emergency department information by the site champion and researchers. Daily decision-making strategies ranged from business as usual to use of overcensus beds. Weekly strategies included advanced approval to use of overcensus beds and prebooking nursing staff. These strategies resulted in improved weekend discharges to manage incoming demand for the following week. Following the introduction of the PAPT and workflow guidelines, patient access and hospital occupancy levels could be maintained despite increases in patient presentations (hospital A). The use of a PAPT, embedded in patient flow management processes and championed by a manager, can benefit bed and staff management. Further research that incorporates wider evaluation of the use of the tool at other sites is warranted.

  9. Flow Analysis Tool White Paper

    NASA Technical Reports Server (NTRS)

    Boscia, Nichole K.

    2012-01-01

    Faster networks are continually being built to accommodate larger data transfers. While it is intuitive to think that implementing faster networks will result in higher throughput rates, this is often not the case. There are many elements involved in data transfer, many of which are beyond the scope of the network itself. Although networks may get bigger and support faster technologies, the presence of other legacy components, such as older application software or kernel parameters, can often cause bottlenecks. Engineers must be able to identify when data flows are reaching a bottleneck that is not imposed by the network and then troubleshoot it using the tools available to them. The current best practice is to collect as much information as possible on the network traffic flows so that analysis is quick and easy. Unfortunately, no single method of collecting this information can sufficiently capture the whole endto- end picture. This becomes even more of a hurdle when large, multi-user systems are involved. In order to capture all the necessary information, multiple data sources are required. This paper presents a method for developing a flow analysis tool to effectively collect network flow data from multiple sources and provide that information to engineers in a clear, concise way for analysis. The purpose of this method is to collect enough information to quickly (and automatically) identify poorly performing flows along with the cause of the problem. The method involves the development of a set of database tables that can be populated with flow data from multiple sources, along with an easyto- use, web-based front-end interface to help network engineers access, organize, analyze, and manage all the information.

  10. Control of Aerodynamic Flows. Delivery Order 0051: Transition Prediction Method Review Summary for the Rapid Assessment Tool for Transition Prediction (RATTraP)

    DTIC Science & Technology

    2005-06-15

    presented by Malik et al. (1994) who used a NPSE code to calculate the primary instability behavior of stationary disturbances of a swept Hiemenz flow. As...instabilities and to confirm previous experimental results. Hall, Malik, and Poll (1984) used nonparallel linear stability theory on a swept Hiemenz ...incompressible swept Hiemenz flow. J. Fluid Mech., 311:239-255. Lin, R.S., Malik, M.R. 1997. On the stability of attachment-line boundary layers. Part 2

  11. 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.

  12. 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.

  13. Critical review of prostate cancer predictive tools.

    PubMed

    Shariat, Shahrokh F; Kattan, Michael W; Vickers, Andrew J; Karakiewicz, Pierre I; Scardino, Peter T

    2009-12-01

    Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities and potential treatment-related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, look-up and propensity scoring tables, risk-class stratification prediction tools, classification and regression tree analysis, nomograms and artificial neural networks. Criteria to evaluate tools include discrimination, calibration, generalizability, level of complexity, decision analysis and ability to account for competing risks and conditional probabilities. The available predictive tools and their features, with a focus on nomograms, are described. While some tools are well-calibrated, few have been externally validated or directly compared with other tools. In addition, the clinical consequences of applying predictive tools need thorough assessment. Nevertheless, predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives. Additionally, accurate tools may improve clinical trial design.

  14. CRITICAL REVIEW OF PROSTATE CANCER PREDICTIVE TOOLS

    PubMed Central

    Shariat, Shahrokh F.; Kattan, Michael W.; Vickers, Andrew J.; Karakiewicz, Pierre I.; Scardino, Peter T.

    2010-01-01

    Summary Prostate cancer is a very complex disease, and the decision-making process requires the clinician to balance clinical benefits, life expectancy, comorbidities, and potential treatment related side effects. Accurate prediction of clinical outcomes may help in the difficult process of making decisions related to prostate cancer. In this review, we discuss attributes of predictive tools and systematically review those available for prostate cancer. Types of tools include probability formulas, look-up and propensity scoring tables, risk-class stratification prediction tools, classification and regression tree analysis, nomograms, and artificial neural networks. Criteria to evaluate tools include discrimination, calibration, generalizability, level of complexity, decision analysis, and ability to account for competing risks and conditional probabilities. We describe the available predictive tools and their features, focusing on nomograms. While some tools are well-calibrated, few have been externally validated or directly compared to other tools. In addition, the clinical consequences of applying predictive tools need thorough assessment. Nevertheless, predictive tools can facilitate medical decision-making by showing patients tailored predictions of their outcomes with various alternatives. Additionally, accurate tools may improve clinical trial design. PMID:20001796

  15. 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.

  16. Predictive Data Tools Find Uses in Schools

    ERIC Educational Resources Information Center

    Sparks, Sarah D.

    2011-01-01

    The use of analytic tools to predict student performance is exploding in higher education, and experts say the tools show even more promise for K-12 schools, in everything from teacher placement to dropout prevention. Use of such statistical techniques is hindered in precollegiate schools, however, by a lack of researchers trained to help…

  17. Predictive Data Tools Find Uses in Schools

    ERIC Educational Resources Information Center

    Sparks, Sarah D.

    2011-01-01

    The use of analytic tools to predict student performance is exploding in higher education, and experts say the tools show even more promise for K-12 schools, in everything from teacher placement to dropout prevention. Use of such statistical techniques is hindered in precollegiate schools, however, by a lack of researchers trained to help…

  18. Behavior Prediction Tools Strengthen Nanoelectronics

    NASA Technical Reports Server (NTRS)

    2013-01-01

    Several years ago, NASA started making plans to send robots to explore the deep, dark craters on the Moon. As part of these plans, NASA needed modeling tools to help engineer unique electronics to withstand extremely cold temperatures. According to Jonathan Pellish, a flight systems test engineer at Goddard Space Flight Center, "An instrument sitting in a shadowed crater on one of the Moon s poles would hover around 43 K", that is, 43 kelvin, equivalent to -382 F. Such frigid temperatures are one of the main factors that make the extreme space environments encountered on the Moon and elsewhere so extreme. Radiation is another main concern. "Radiation is always present in the space environment," says Pellish. "Small to moderate solar energetic particle events happen regularly and extreme events happen less than a handful of times throughout the 7 active years of the 11-year solar cycle." Radiation can corrupt data, propagate to other systems, require component power cycling, and cause a host of other harmful effects. In order to explore places like the Moon, Jupiter, Saturn, Venus, and Mars, NASA must use electronic communication devices like transmitters and receivers and data collection devices like infrared cameras that can resist the effects of extreme temperature and radiation; otherwise, the electronics would not be reliable for the duration of the mission.

  19. Orbiter Boundary Layer Transition Prediction Tool Enhancements

    NASA Technical Reports Server (NTRS)

    Berry, Scott A.; King, Rudolph A.; Kegerise, Michael A.; Wood, William A.; McGinley, Catherine B.; Berger, Karen T.; Anderson, Brian P.

    2010-01-01

    Updates to an analytic tool developed for Shuttle support to predict the onset of boundary layer transition resulting from thermal protection system damage or repair are presented. The boundary layer transition tool is part of a suite of tools that analyze the local aerothermodynamic environment to enable informed disposition of damage for making recommendations to fly as is or to repair. Using mission specific trajectory information and details of each d agmea site or repair, the expected time (and thus Mach number) of transition onset is predicted to help define proper environments for use in subsequent thermal and stress analysis of the thermal protection system and structure. The boundary layer transition criteria utilized within the tool were updated based on new local boundary layer properties obtained from high fidelity computational solutions. Also, new ground-based measurements were obtained to allow for a wider parametric variation with both protuberances and cavities and then the resulting correlations were calibrated against updated flight data. The end result is to provide correlations that allow increased confidence with the resulting transition predictions. Recently, a new approach was adopted to remove conservatism in terms of sustained turbulence along the wing leading edge. Finally, some of the newer flight data are also discussed in terms of how these results reflect back on the updated correlations.

  20. Web tools for predictive toxicology model building.

    PubMed

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  1. 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.

  2. 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)

  3. 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)

  4. Enhancing Technology-Mediated Communication: Tools, Analyses, and Predictive Models

    DTIC Science & Technology

    2007-09-01

    Enhancing Technology -Mediated Communication : Tools, Analyses, and Predictive Models patterns of sharing different types of context information with... Communication : Tools, Analyses, and Predictive Models application information regardless of the time interval they describe (e.g., group all Keyboard...University of Chicago Press Center for the Study of Language & Information . 186 Enhancing Technology -Mediated Communication : Tools, Analyses, and Predictive

  5. 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.

  6. DPIV prediction of flow induced platelet activation-comparison to numerical predictions.

    PubMed

    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.

  7. 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.

  8. 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.

  9. Palmistry: a tool for dental caries prediction!

    PubMed

    Madan, Nidhi; Rathnam, Arun; Bajaj, Neeti

    2011-01-01

    Dermatoglyphics can prove to be an extremely useful tool for preliminary investigations in conditions with a suspected genetic base. Since caries is a multifactorial disease with the influence of genetic pattern, early prediction for high-risk children can help in using effective and efficient caries preventive measures that are a part of the pedodontist arsenal. This study was done to determine the genetic aspect involved in the occurrence of dental caries through a cost-effective means, which can be used in field studies. 550 kindergarten school children in the age group 3-6 years were examined during a school examination camp. Of these, only 336 children were included in the study. They were divided into four groups as follows: caries-free males (df score=0), caries-free females, caries males (df score≥10), caries females. The handprints of each child were taken and the frequency of occurrence of type of dermatoglyphic pattern on fingertip of each digit was noted. Separate df scores were recorded. SPSS software and test of proportions were used for the analysis. Handprints of caries-free children, especially females, showed maximum ulnar loops. The caries group showed maximum occurrence of whorls (r=2:1), which were more prevalent in females on the left hand 3rd digit than in males where the whorls were found on the right hand 3 rd digit, and also low total ridge count, especially in males.

  10. Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

    NASA Technical Reports Server (NTRS)

    Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

    2000-01-01

    The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an

  11. Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

    NASA Technical Reports Server (NTRS)

    Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

    2000-01-01

    The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an

  12. A critical assessment of topologically associating domain prediction tools

    PubMed Central

    Dali, Rola

    2017-01-01

    Abstract Topologically associating domains (TADs) have been proposed to be the basic unit of chromosome folding and have been shown to play key roles in genome organization and gene regulation. Several different tools are available for TAD prediction, but their properties have never been thoroughly assessed. In this manuscript, we compare the output of seven different TAD prediction tools on two published Hi-C data sets. TAD predictions varied greatly between tools in number, size distribution and other biological properties. Assessed against a manual annotation of TADs, individual TAD boundary predictions were found to be quite reliable, but their assembly into complete TAD structures was much less so. In addition, many tools were sensitive to sequencing depth and resolution of the interaction frequency matrix. This manuscript provides users and designers of TAD prediction tools with information that will help guide the choice of tools and the interpretation of their predictions. PMID:28334773

  13. Slug flow: Occurrence, consequences, and prediction

    SciTech Connect

    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.

  14. A jet engine noise measurement and prediction tool.

    PubMed

    Frendi, Abdelkader; Dorland, Wade D; Maung, Thein; Nesman, Tom; Wang, Ten-See

    2002-11-01

    In this paper, the authors describe an innovative jet engine noise measurement and prediction tool. The tool measures sound-pressure levels and frequency spectra in the far field. In addition, the tool provides predicted results while the measurements are being made. The predictions are based on an existing computational fluid dynamics database coupled to an empirical acoustic radiation model based on the far-field approximation to the Lighthill acoustic analogy. Preliminary tests of this acoustic measurement and prediction tool produced very encouraging results.

  15. 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.

  16. Engineering Property Prediction Tools for Tailored Polymer Composite Structures

    SciTech Connect

    Nguyen, Ba Nghiep; Foss, Peter; Wyzgoski, Michael; Trantina, Gerry; Kunc, Vlastimil; Schutte, Carol; Smith, Mark T.

    2009-12-23

    This report summarizes our FY 2009 research activities for the project titled:"Engineering Property Prediction Tools for Tailored Polymer Composite Structures." These activities include (i) the completion of the development of a fiber length attrition model for injection-molded long-fiber thermoplastics (LFTs), (ii) development of the a fatigue damage model for LFTs and its implementation in ABAQUS, (iii) development of an impact damage model for LFTs and its implementation in ABAQUS, (iv) development of characterization methods for fatigue testing, (v) characterization of creep and fatigue responses of glass-fiber/polyamide (PA6,6) and glass-fiber/polypropylene (PP), (vi) characterization of fiber length distribution along the flow length of glass/PA6,6 and glass-fiber/PP, and (vii) characterization of impact responses of glass-fiber/PA6,6. The fiber length attrition model accurately captures the fiber length distribution along the flow length of the studied glass-fiber/PP material. The fatigue damage model is able to predict the S-N and stiffness reduction data which are valuable to the fatigue design of LFTs. The impact damage model correctly captures damage accumulation observed in experiments of glass-fiber/PA6,6 plaques.Further work includes validations of these models for representative LFT materials and a complex LFT part.

  17. 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.

  18. 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.

  19. 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.

  20. META-X Design Flow Tools

    DTIC Science & Technology

    2013-04-01

    Report for Congress. Tech. rep., Congressional Research Service, Jan. 7. 3. Hiltzik, M., 2011. “787 Dreamliner teaches Boeing costly lesson on...PDE pulse detonation engine PET Parametric Exploration Tool PID proportional-integral-derivative PTM phonetically tied mixture SUT System under Test WBS Work Breakdown Structure

  1. New imaging tools in cardiovascular medicine: computational fluid dynamics and 4D flow MRI.

    PubMed

    Itatani, Keiichi; Miyazaki, Shohei; Furusawa, Tokoki; Numata, Satoshi; Yamazaki, Sachiko; Morimoto, Kazuki; Makino, Rina; Morichi, Hiroko; Nishino, Teruyasu; Yaku, Hitoshi

    2017-09-19

    Blood flow imaging is a novel technology in cardiovascular medicine and surgery. Today, two types of blood flow imaging tools are available: measurement-based flow visualization including 4D flow MRI (or 3D cine phase-contrast magnetic resonance imaging), or echocardiography flow visualization software, and computer flow simulation modeling based on computational fluid dynamics (CFD). MRI and echocardiography flow visualization provide measured blood flow but have limitations in temporal and spatial resolution, whereas CFD flow calculates the flow according to assumptions instead of flow measurement, and it has sufficiently fine resolution up to the computer memory limit, and it enables even virtual surgery when combined with computer graphics. Blood flow imaging provides profound insight into the pathophysiology of cardiovascular diseases, because it quantifies and visualizes mechanical stress on the vessel walls or heart ventricle. Wall shear stress (WSS) is a stress on the endothelial wall caused by the near wall blood flow, and it is thought to be a predictor of atherosclerosis progression in coronary or aortic diseases. Flow energy loss (EL) is the loss of blood flow energy caused by viscous friction of turbulent diseased flow, and it is expected to be a predictor of ventricular workload on various heart diseases including heart valve disease, cardiomyopathy, and congenital heart diseases. Blood flow imaging can provide useful information for developing predictive medicine in cardiovascular diseases, and may lead to breakthroughs in cardiovascular surgery, especially in the decision-making process.

  2. CFD Validation Studies for Hypersonic Flow Prediction

    NASA Technical Reports Server (NTRS)

    Gnoffo, Peter A.

    2001-01-01

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

  3. A ground-water flow Mathematica tool package

    SciTech Connect

    Cheng, A.H.D.; Sidauruk, P.

    1996-01-01

    Mathematica, a symbolic computer mathematics program, is used to construct a tool package for ground-water flow and contaminant transport simulations. High level, mnemonic functions are designed that allow users to plot type curves, to animate ground-water flow fields, to perform parameter determination, and to visualize the movement of contaminant cloud.

  4. Towards a generalized energy prediction model for machine tools.

    PubMed

    Bhinge, Raunak; Park, Jinkyoo; Law, Kincho H; Dornfeld, David A; Helu, Moneer; Rachuri, Sudarsan

    2017-04-01

    Energy prediction of machine tools can deliver many advantages to a manufacturing enterprise, ranging from energy-efficient process planning to machine tool monitoring. Physics-based, energy prediction models have been proposed in the past to understand the energy usage pattern of a machine tool. However, uncertainties in both the machine and the operating environment make it difficult to predict the energy consumption of the target machine reliably. Taking advantage of the opportunity to collect extensive, contextual, energy-consumption data, we discuss a data-driven approach to develop an energy prediction model of a machine tool in this paper. First, we present a methodology that can efficiently and effectively collect and process data extracted from a machine tool and its sensors. We then present a data-driven model that can be used to predict the energy consumption of the machine tool for machining a generic part. Specifically, we use Gaussian Process (GP) Regression, a non-parametric machine-learning technique, to develop the prediction model. The energy prediction model is then generalized over multiple process parameters and operations. Finally, we apply this generalized model with a method to assess uncertainty intervals to predict the energy consumed to machine any part using a Mori Seiki NVD1500 machine tool. Furthermore, the same model can be used during process planning to optimize the energy-efficiency of a machining process.

  5. Numerical simulation and prediction of upwelling flow

    NASA Astrophysics Data System (ADS)

    Tadepalli, Srinivas

    The objectives of the present study are to better understand the instability mechanisms active in coastal upwelling, to assess the influence of coastal perturbations such as capes on the large scale structures and to devise efficient assimilation techniques for an improved flow forecast from limited observations. The structure of the frontal instabilities are revealed by employing large eddy simulation (Zang et al., 1995). The dominant instability is of mixed baroclinic-barotropic type and develops after the bottom fluid upwells. In the early stages, a weak Rayleigh-Taylor type instability modifies the surface front. Linear stability analysis applied to the modified surface front predicts a dominant wavelength that is consistent with the simulation results. The predicted large scale flow features agree well with the experiments of Narimousa and Maxworthy (1991, 1987). Later, nonlinear interactions moderate the growth of the large scales. Fish-hook structures are a by-product of the nonlinear interactions and originate from the modulation of the large scale structures. Large vertical front excursions cause mixed-layer deepening, observed in oceanic flows. We observe that density front excursions and mixing are enhanced by coastal perturbations due to strong vortex stretching. Continued vortex stretching, caused by the acceleration of the fluid around the cape results in vortex tearing. The large scales are modified and propagate; they are not phase-locked by the cape. We have devised an efficient hybrid assimilation technique which is applicable to a variety of geophysical flows. This scheme is based on the adjoint and nudging formulations and satisfies the conservation principles. It assimilates observations in both the linear and nonlinear regimes efficiently. Eigenfunctions of the linear stability problem give a better estimate of the forecast error. Existing error-driven assimilation methods do not identify the error in regions void of measurements. The adjoint

  6. Cluster Flow: A user-friendly bioinformatics workflow tool

    PubMed Central

    Ewels, Philip; Krueger, Felix; Käller, Max; Andrews, Simon

    2016-01-01

    Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

  7. Cluster Flow: A user-friendly bioinformatics workflow tool.

    PubMed

    Ewels, Philip; Krueger, Felix; Käller, Max; Andrews, Simon

    2016-01-01

    Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

  8. GAPIT: genome association and prediction integrated tool

    USDA-ARS?s Scientific Manuscript database

    Advances in high throughput sequencing have improved the detection of genes underlying important traits as well as the prediction accuracy of disease risk and breeding value of crop or livestock. Software programs developed to perform statistical genetic analysis that support these activities should...

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

    PubMed

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

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

  10. Assessment and prediction of debris-flow hazards

    USGS Publications Warehouse

    Wieczorek, Gerald F.; ,

    1993-01-01

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

  11. SUSY predictions and SUSY tools at the LHC

    NASA Astrophysics Data System (ADS)

    Allanach, B. C.

    2009-01-01

    We provide a bestiary of public codes and other algorithmic tools that can be used for analysing supersymmetric phenomenology. We also describe the organisation of the different tools and communication between them. Tools exist that calculate supersymmetric spectra and decay widths, simulate Monte Carlo events as well as those that make predictions of dark matter relic density or that predict precision electroweak or b-observables. Some global fitting tools for use in SUSY phenomenology are also presented. In each case, a description and a link to the relevant web-site is provided. It is hoped that this review could serve as an “entry-gate” and map for prospective users.

  12. Development of Doppler Global Velocimetry as a Flow Diagnostics Tool

    NASA Technical Reports Server (NTRS)

    Meyers, James F.

    1995-01-01

    The development of Doppler global velocimetry is described from its inception to its use as a flow diagnostics tool. Its evolution is traced from an elementary one-component laboratory prototype, to a full three-component configuration operating in a wind tunnel at focal distances exceeding 15 m. As part of the developmental process, several wind tunnel flow field investigations were conducted. These included supersonic flow measurements about an oblique shock, subsonic and supersonic measurements of the vortex flow above a delta wing, and three-component measurements of a high-speed jet.

  13. Updating Risk Prediction Tools: A Case Study in Prostate Cancer

    PubMed Central

    Ankerst, Donna P.; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J.; Feng, Ziding; Sanda, Martin G.; Partin, Alan W.; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M.

    2013-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [−2]proPSA measured on an external case control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. PMID:22095849

  14. 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.

  15. Predicting Operator Execution Times Using CogTool

    NASA Technical Reports Server (NTRS)

    Santiago-Espada, Yamira; Latorella, Kara A.

    2013-01-01

    Researchers and developers of NextGen systems can use predictive human performance modeling tools as an initial approach to obtain skilled user performance times analytically, before system testing with users. This paper describes the CogTool models for a two pilot crew executing two different types of a datalink clearance acceptance tasks, and on two different simulation platforms. The CogTool time estimates for accepting and executing Required Time of Arrival and Interval Management clearances were compared to empirical data observed in video tapes and registered in simulation files. Results indicate no statistically significant difference between empirical data and the CogTool predictions. A population comparison test found no significant differences between the CogTool estimates and the empirical execution times for any of the four test conditions. We discuss modeling caveats and considerations for applying CogTool to crew performance modeling in advanced cockpit environments.

  16. Common features of microRNA target prediction tools.

    PubMed

    Peterson, Sarah M; Thompson, Jeffrey A; Ufkin, Melanie L; Sathyanarayana, Pradeep; Liaw, Lucy; Congdon, Clare Bates

    2014-01-01

    The human genome encodes for over 1800 microRNAs (miRNAs), which are short non-coding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one miRNA to target multiple gene transcripts, miRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of miRNA targets is a critical initial step in identifying miRNA:mRNA target interactions for experimental validation. The available tools for miRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to miRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all miRNA target prediction tools, four main aspects of the miRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MiRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.

  17. Multiparametric Model for Penumbral Flow Prediction in Acute Stroke.

    PubMed

    Livne, Michelle; Kossen, Tabea; Madai, Vince I; Zaro-Weber, Olivier; Moeller-Hartmann, Walter; Mouridsen, Kim; Heiss, Wolf-Dieter; Sobesky, Jan

    2017-07-01

    Identification of salvageable penumbra tissue by dynamic susceptibility contrast magnetic resonance imaging is a valuable tool for acute stroke patient stratification for treatment. However, prior studies have not attempted to combine the different perfusion maps into a predictive model. In this study, we established a multiparametric perfusion imaging model and cross-validated it using positron emission tomography perfusion for detection of penumbral flow. In a retrospective analysis of 17 subacute stroke patients with consecutive magnetic resonance imaging and H2O15 positron emission tomography scans, perfusion maps of cerebral blood flow, cerebral blood volume, mean transit time, time-to-maximum, and time-to-peak were constructed and combined using a generalized linear model (GLM). Both the GLM maps and the single perfusion maps alone were cross-validated with positron emission tomography-cerebral blood flow scans to predict penumbral flow on a voxel-wise level. Performance was tested by receiver-operating characteristics curve analysis, that is, the area under the curve, and the models' fits were compared using the likelihood ratio test. The GLM demonstrated significantly improved model fit compared with each of the single perfusion maps (P<1×e-5) and demonstrated higher performance, with an area under the curve of 0.91. However, the absolute difference between the performance of GLM and the best-performing single perfusion parameter (time-to-maximum) was relatively low (area under the curve difference =0.04). Our results support a dynamic susceptibility contrast magnetic resonance imaging-based GLM as an improved model for penumbral flow prediction in stroke patients. With given perfusion maps, this model is a straightforward and observer-independent alternative for therapy stratification. © 2017 American Heart Association, Inc.

  18. 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.

  19. Virtual Beach: Decision Support Tools for Beach Pathogen Prediction

    EPA Science Inventory

    The Virtual Beach Managers Tool (VB) is decision-making software developed to help local beach managers make decisions as to when beaches should be closed due to predicted high levels of water borne pathogens. The tool is being developed under the umbrella of EPA's Advanced Monit...

  20. Virtual Beach: Decision Support Tools for Beach Pathogen Prediction

    EPA Science Inventory

    The Virtual Beach Managers Tool (VB) is decision-making software developed to help local beach managers make decisions as to when beaches should be closed due to predicted high levels of water borne pathogens. The tool is being developed under the umbrella of EPA's Advanced Monit...

  1. Water Impact Prediction Tool for Recoverable Rockets

    NASA Technical Reports Server (NTRS)

    Rooker, William; Glaese, John; Clayton, Joe

    2011-01-01

    Reusing components from a rocket launch can be cost saving. NASA's space shuttle system has reusable components that return to the Earth and impact the ocean. A primary example is the Space Shuttle Solid Rocket Booster (SRB) that descends on parachutes to the Earth after separation and impacts the ocean. Water impact generates significant structural loads that can damage the booster, so it is important to study this event in detail in the design of the recovery system. Some recent examples of damage due to water impact include the Ares I-X First Stage deformation as seen in Figure 1 and the loss of the SpaceX Falcon 9 First Stage.To ensure that a component can be recovered or that the design of the recovery system is adequate, an adequate set of structural loads is necessary for use in failure assessments. However, this task is difficult since there are many conditions that affect how a component impacts the water and the resulting structural loading that a component sees. These conditions include the angle of impact with respect to the water, the horizontal and vertical velocities, the rotation rate, the wave height and speed, and many others. There have been attempts to simulate water impact. One approach is to analyze water impact using explicit finite element techniques such as those employed by the LS-Dyna tool [1]. Though very detailed, this approach is time consuming and would not be suitable for running Monte Carlo or optimization analyses. The purpose of this paper is to describe a multi-body simulation tool that runs quickly and that captures the environments a component might see. The simulation incorporates the air and water interaction with the component, the component dynamics (i.e. modes and mode shapes), any applicable parachutes and lines, the interaction of winds and gusts, and the wave height and speed. It is capable of quickly conducting Monte Carlo studies to better capture the environments and genetic algorithm optimizations to reproduce a

  2. Predictive Technologies: Can Smart Tools Augment the Brain's Predictive Abilities?

    PubMed Central

    Pezzulo, Giovanni; D'Ausilio, Alessandro; Gaggioli, Andrea

    2016-01-01

    The ability of “looking into the future”—namely, the capacity of anticipating future states of the environment or of the body—represents a fundamental function of human (and animal) brains. A goalkeeper who tries to guess the ball's direction; a chess player who attempts to anticipate the opponent's next move; or a man-in-love who tries to calculate what are the chances of her saying yes—in all these cases, people are simulating possible future states of the world, in order to maximize the success of their decisions or actions. Research in neuroscience is showing that our ability to predict the behavior of physical or social phenomena is largely dependent on the brain's ability to integrate current and past information to generate (probabilistic) simulations of the future. But could predictive processing be augmented using advanced technologies? In this contribution, we discuss how computational technologies may be used to support, facilitate or enhance the prediction of future events, by considering exemplificative scenarios across different domains, from simpler sensorimotor decisions to more complex cognitive tasks. We also examine the key scientific and technical challenges that must be faced to turn this vision into reality. PMID:27199648

  3. RNA-SSPT: RNA Secondary Structure Prediction Tools

    PubMed Central

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

  4. RNA-SSPT: RNA Secondary Structure Prediction Tools.

    PubMed

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

  5. 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.

  6. 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.

  7. OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems

    NASA Technical Reports Server (NTRS)

    Kao, David L.; Chan, William M.

    2012-01-01

    Structured grid solvers such as NASA's OVERFLOW compressible Navier-Stokes flow solver can generate large data files that contain convergence histories for flow equation residuals, turbulence model equation residuals, component forces and moments, and component relative motion dynamics variables. Most of today's large-scale problems can extend to hundreds of grids, and over 100 million grid points. However, due to the lack of efficient tools, only a small fraction of information contained in these files is analyzed. OVERSMART (OVERFLOW Solution Monitoring And Reporting Tool) provides a comprehensive report of solution convergence of flow computations over large, complex grid systems. It produces a one-page executive summary of the behavior of flow equation residuals, turbulence model equation residuals, and component forces and moments. Under the automatic option, a matrix of commonly viewed plots such as residual histograms, composite residuals, sub-iteration bar graphs, and component forces and moments is automatically generated. Specific plots required by the user can also be prescribed via a command file or a graphical user interface. Output is directed to the user s computer screen and/or to an html file for archival purposes. The current implementation has been targeted for the OVERFLOW flow solver, which is used to obtain a flow solution on structured overset grids. The OVERSMART framework allows easy extension to other flow solvers.

  8. Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays

    PubMed Central

    Hsieh, Helen V.; Dantzler, Jeffrey L.; Weigl, Bernhard H.

    2017-01-01

    Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor’s office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness. PMID:28555034

  9. Analytical Tools to Improve Optimization Procedures for Lateral Flow Assays.

    PubMed

    Hsieh, Helen V; Dantzler, Jeffrey L; Weigl, Bernhard H

    2017-05-28

    Immunochromatographic or lateral flow assays (LFAs) are inexpensive, easy to use, point-of-care medical diagnostic tests that are found in arenas ranging from a doctor's office in Manhattan to a rural medical clinic in low resource settings. The simplicity in the LFA itself belies the complex task of optimization required to make the test sensitive, rapid and easy to use. Currently, the manufacturers develop LFAs by empirical optimization of material components (e.g., analytical membranes, conjugate pads and sample pads), biological reagents (e.g., antibodies, blocking reagents and buffers) and the design of delivery geometry. In this paper, we will review conventional optimization and then focus on the latter and outline analytical tools, such as dynamic light scattering and optical biosensors, as well as methods, such as microfluidic flow design and mechanistic models. We are applying these tools to find non-obvious optima of lateral flow assays for improved sensitivity, specificity and manufacturing robustness.

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  11. Predictions of titanium alloy properties using thermodynamic modeling tools

    NASA Astrophysics Data System (ADS)

    Zhang, F.; Xie, F.-Y.; Chen, S.-L.; Chang, Y. A.; Furrer, D.; Venkatesh, V.

    2005-12-01

    Thermodynamic modeling tools have become essential in understanding the effect of alloy chemistry on the final microstructure of a material. Implementation of such tools to improve titanium processing via parameter optimization has resulted in significant cost savings through the elimination of shop/laboratory trials and tests. In this study, a thermodynamic modeling tool developed at CompuTherm, LLC, is being used to predict β transus, phase proportions, phase chemistries, partitioning coefficients, and phase boundaries of multicomponent titanium alloys. This modeling tool includes Pandat, software for multicomponent phase equilibrium calculations, and PanTitanium, a thermodynamic database for titanium alloys. Model predictions are compared with experimental results for one α-β alloy (Ti-64) and two near-β alloys (Ti-17 and Ti-10-2-3). The alloying elements, especially the interstitial elements O, N, H, and C, have been shown to have a significant effect on the β transus temperature, and are discussed in more detail herein.

  12. Flight Experiment Verification of Shuttle Boundary Layer Transition Prediction Tool

    NASA Technical Reports Server (NTRS)

    Berry, Scott A.; Berger, Karen T.; Horvath, Thomas J.; Wood, William A.

    2016-01-01

    Boundary layer transition at hypersonic conditions is critical to the design of future high-speed aircraft and spacecraft. Accurate methods to predict transition would directly impact the aerothermodynamic environments used to size a hypersonic vehicle's thermal protection system. A transition prediction tool, based on wind tunnel derived discrete roughness correlations, was developed and implemented for the Space Shuttle return-to-flight program. This tool was also used to design a boundary layer transition flight experiment in order to assess correlation uncertainties, particularly with regard to high Mach-number transition and tunnel-to-flight scaling. A review is provided of the results obtained from the flight experiment in order to evaluate the transition prediction tool implemented for the Shuttle program.

  13. The Motif Tool Assessment Platform (MTAP) for sequence-based transcription factor binding site prediction tools.

    PubMed

    Quest, Daniel; Ali, Hesham

    2010-01-01

    Predicting transcription factor binding sites (TFBS) from sequence is one of the most challenging problems in computational biology. The development of (semi-)automated computer-assisted prediction methods is needed to find TFBS over an entire genome, which is a first step in reconstructing mechanisms that control gene activity. Bioinformatics journals continue to publish diverse methods for predicting TFBS on a monthly basis. To help practitioners in deciding which method to use to predict for a particular TFBS, we provide a platform to assess the quality and applicability of the available methods. Assessment tools allow researchers to determine how methods can be expected to perform on specific organisms or on specific transcription factor families. This chapter introduces the TFBS detection problem and reviews current strategies for evaluating algorithm effectiveness. In this chapter, a novel and robust assessment tool, the Motif Tool Assessment Platform (MTAP), is introduced and discussed.

  14. Infrastructure Analysis Tools: A Focus on Cash Flow Analysis (Presentation)

    SciTech Connect

    Melaina, M.; Penev, M.

    2012-09-01

    NREL has developed and maintains a variety of infrastructure analysis models for the U.S. Department of Energy. Business case analysis has recently been added to this tool set. This presentation focuses on cash flow analysis. Cash flows depend upon infrastructure costs, optimized spatially and temporally, and assumptions about financing and revenue. NREL has incorporated detailed metrics on financing and incentives into the models. Next steps in modeling include continuing to collect feedback on regional/local infrastructure development activities and 'roadmap' dynamics, and incorporating consumer preference assumptions on infrastructure to provide direct feedback between vehicles and station rollout.

  15. Jet Measurements for Development of Jet Noise Prediction Tools

    NASA Technical Reports Server (NTRS)

    Bridges, James E.

    2006-01-01

    The primary focus of my presentation is the development of the jet noise prediction code JeNo with most examples coming from the experimental work that drove the theoretical development and validation. JeNo is a statistical jet noise prediction code, based upon the Lilley acoustic analogy. Our approach uses time-average 2-D or 3-D mean and turbulent statistics of the flow as input. The output is source distributions and spectral directivity.

  16. Tampa Bay Water Clarity Model (TBWCM): As a Predictive Tool

    EPA Science Inventory

    The Tampa Bay Water Clarity Model was developed as a predictive tool for estimating the impact of changing nutrient loads on water clarity as measured by secchi depth. The model combines a physical mixing model with an irradiance model and nutrient cycling model. A 10 segment bi...

  17. Tampa Bay Water Clarity Model (TBWCM): As a Predictive Tool

    EPA Science Inventory

    The Tampa Bay Water Clarity Model was developed as a predictive tool for estimating the impact of changing nutrient loads on water clarity as measured by secchi depth. The model combines a physical mixing model with an irradiance model and nutrient cycling model. A 10 segment bi...

  18. Predicting College Students' Acceptance of Podcasting as a Learning Tool

    ERIC Educational Resources Information Center

    Zacharis, Nick Z.

    2012-01-01

    Purpose: Podcasting is one of today's most prominent trends in media and computing, but until now, factors predicting its adoption in higher education settings remain largely unexplored. The purpose of this paper is to examine students' perceptions of enhanced podcasting as a review and exam preparatory tool, through the use of the Technology…

  19. Evolutionary theory as a tool for predicting extinction risk.

    PubMed

    Gallagher, Austin J; Hammerschlag, Neil; Cooke, Steven J; Costa, Daniel P; Irschick, Duncan J

    2015-02-01

    Timely and proactive wildlife conservation requires strategies for determining which species are most at the greatest threat of extinction. Here, we suggest that evolutionary theory, particularly the concept of specialization, can be a useful tool to inform such assessments and may greatly aid in our ability to predict the vulnerabilities of species to anthropogenic impacts. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. The Predictive Validity of the Early Warning System Tool

    ERIC Educational Resources Information Center

    Johnson, Evelyn; Semmelroth, Carrie

    2010-01-01

    The Early Warning System is a tool developed by the National High School Center to collect data on indicators including attendance, grade point average, course failures, and credits earned. These indicators have been found to be highly predictive of a student's likelihood of dropping out of high school in large, urban areas. The Early Warning…

  1. The Predictive Validity of the Early Warning System Tool

    ERIC Educational Resources Information Center

    Johnson, Evelyn; Semmelroth, Carrie

    2010-01-01

    The Early Warning System is a tool developed by the National High School Center to collect data on indicators including attendance, grade point average, course failures, and credits earned. These indicators have been found to be highly predictive of a student's likelihood of dropping out of high school in large, urban areas. The Early Warning…

  2. PLIO: a generic tool for real-time operational predictive optimal control of water networks.

    PubMed

    Cembrano, G; Quevedo, J; Puig, V; Pérez, R; Figueras, J; Verdejo, J M; Escaler, I; Ramón, G; Barnet, G; Rodríguez, P; Casas, M

    2011-01-01

    This paper presents a generic tool, named PLIO, that allows to implement the real-time operational control of water networks. Control strategies are generated using predictive optimal control techniques. This tool allows the flow management in a large water supply and distribution system including reservoirs, open-flow channels for water transport, water treatment plants, pressurized water pipe networks, tanks, flow/pressure control elements and a telemetry/telecontrol system. Predictive optimal control is used to generate flow control strategies from the sources to the consumer areas to meet future demands with appropriate pressure levels, optimizing operational goals such as network safety volumes and flow control stability. PLIO allows to build the network model graphically and then to automatically generate the model equations used by the predictive optimal controller. Additionally, PLIO can work off-line (in simulation) and on-line (in real-time mode). The case study of Santiago-Chile is presented to exemplify the control results obtained using PLIO off-line (in simulation).

  3. Water flow algorithm decision support tool for travelling salesman problem

    NASA Astrophysics Data System (ADS)

    Kamarudin, Anis Aklima; Othman, Zulaiha Ali; Sarim, Hafiz Mohd

    2016-08-01

    This paper discuss about the role of Decision Support Tool in Travelling Salesman Problem (TSP) for helping the researchers who doing research in same area will get the better result from the proposed algorithm. A study has been conducted and Rapid Application Development (RAD) model has been use as a methodology which includes requirement planning, user design, construction and cutover. Water Flow Algorithm (WFA) with initialization technique improvement is used as the proposed algorithm in this study for evaluating effectiveness against TSP cases. For DST evaluation will go through usability testing conducted on system use, quality of information, quality of interface and overall satisfaction. Evaluation is needed for determine whether this tool can assists user in making a decision to solve TSP problems with the proposed algorithm or not. Some statistical result shown the ability of this tool in term of helping researchers to conduct the experiments on the WFA with improvements TSP initialization.

  4. Empirical flow parameters : a tool for hydraulic model validity

    USGS Publications Warehouse

    Asquith, William H.; Burley, Thomas E.; Cleveland, Theodore G.

    2013-01-01

    The objectives of this project were (1) To determine and present from existing data in Texas, relations between observed stream flow, topographic slope, mean section velocity, and other hydraulic factors, to produce charts such as Figure 1 and to produce empirical distributions of the various flow parameters to provide a methodology to "check if model results are way off!"; (2) To produce a statistical regional tool to estimate mean velocity or other selected parameters for storm flows or other conditional discharges at ungauged locations (most bridge crossings) in Texas to provide a secondary way to compare such values to a conventional hydraulic modeling approach. (3.) To present ancillary values such as Froude number, stream power, Rosgen channel classification, sinuosity, and other selected characteristics (readily determinable from existing data) to provide additional information to engineers concerned with the hydraulic-soil-foundation component of transportation infrastructure.

  5. Two-phase flow regime map predictions under microgravity

    SciTech Connect

    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.

  6. PICADAR: a diagnostic predictive tool for primary ciliary dyskinesia

    PubMed Central

    Behan, Laura; Dimitrov, Borislav D.; Kuehni, Claudia E.; Hogg, Claire; Carroll, Mary; Evans, Hazel J.; Goutaki, Myrofora; Harris, Amanda; Packham, Samantha; Walker, Woolf T.

    2016-01-01

    Symptoms of primary ciliary dyskinesia (PCD) are nonspecific and guidance on whom to refer for testing is limited. Diagnostic tests for PCD are highly specialised, requiring expensive equipment and experienced PCD scientists. This study aims to develop a practical clinical diagnostic tool to identify patients requiring testing. Patients consecutively referred for testing were studied. Information readily obtained from patient history was correlated with diagnostic outcome. Using logistic regression, the predictive performance of the best model was tested by receiver operating characteristic curve analyses. The model was simplified into a practical tool (PICADAR) and externally validated in a second diagnostic centre. Of 641 referrals with a definitive diagnostic outcome, 75 (12%) were positive. PICADAR applies to patients with persistent wet cough and has seven predictive parameters: full-term gestation, neonatal chest symptoms, neonatal intensive care admittance, chronic rhinitis, ear symptoms, situs inversus and congenital cardiac defect. Sensitivity and specificity of the tool were 0.90 and 0.75 for a cut-off score of 5 points. Area under the curve for the internally and externally validated tool was 0.91 and 0.87, respectively. PICADAR represents a simple diagnostic clinical prediction rule with good accuracy and validity, ready for testing in respiratory centres referring to PCD centres. PMID:26917608

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

    NASA Technical Reports Server (NTRS)

    Cappelli, Daniele; Mansour, Nagi N.

    2012-01-01

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

  8. AnalyzeHOLE: An Integrated Wellbore Flow Analysis Tool

    SciTech Connect

    Keith J. Halford

    2009-10-01

    Conventional interpretation of flow logs assumes that hydraulic conductivity is directly proportional to flow change with depth. However, well construction can significantly alter the expected relation between changes in fluid velocity and hydraulic conductivity. Strong hydraulic conductivity contrasts between lithologic intervals can be masked in continuously screened wells. Alternating intervals of screen and blank casing also can greatly complicate the relation between flow and hydraulic properties. More permeable units are not necessarily associated with rapid fluid-velocity increases. Thin, highly permeable units can be misinterpreted as thick and less permeable intervals or not identified at all. These conditions compromise standard flow-log interpretation because vertical flow fields are induced near the wellbore. AnalyzeHOLE, an integrated wellbore analysis tool for simulating flow and transport in wells and aquifer systems, provides a better alternative for simulating and evaluating complex well-aquifer system interaction. A pumping well and adjacent aquifer system are simulated with an axisymmetric, radial geometry in a two-dimensional MODFLOW model. Hydraulic conductivities are distributed by depth and estimated with PEST by minimizing squared differences between simulated and measured flows and drawdowns. Hydraulic conductivity can vary within a lithology but variance is limited with regularization. Transmissivity of the simulated system also can be constrained to estimates from single-well, pumping tests. Water-quality changes in the pumping well are simulated with simple mixing models between zones of differing water quality. These zones are differentiated by backtracking thousands of particles from the well screens with MODPATH. An Excel spreadsheet is used to interface the various components of AnalyzeHOLE by (1) creating model input files, (2) executing MODFLOW, MODPATH, PEST, and supporting FORTRAN routines, and (3) importing and graphically

  9. AnalyzeHOLE - An Integrated Wellbore Flow Analysis Tool

    USGS Publications Warehouse

    Halford, Keith

    2009-01-01

    Conventional interpretation of flow logs assumes that hydraulic conductivity is directly proportional to flow change with depth. However, well construction can significantly alter the expected relation between changes in fluid velocity and hydraulic conductivity. Strong hydraulic conductivity contrasts between lithologic intervals can be masked in continuously screened wells. Alternating intervals of screen and blank casing also can greatly complicate the relation between flow and hydraulic properties. More permeable units are not necessarily associated with rapid fluid-velocity increases. Thin, highly permeable units can be misinterpreted as thick and less permeable intervals or not identified at all. These conditions compromise standard flow-log interpretation because vertical flow fields are induced near the wellbore. AnalyzeHOLE, an integrated wellbore analysis tool for simulating flow and transport in wells and aquifer systems, provides a better alternative for simulating and evaluating complex well-aquifer system interaction. A pumping well and adjacent aquifer system are simulated with an axisymmetric, radial geometry in a two-dimensional MODFLOW model. Hydraulic conductivities are distributed by depth and estimated with PEST by minimizing squared differences between simulated and measured flows and drawdowns. Hydraulic conductivity can vary within a lithology but variance is limited with regularization. Transmissivity of the simulated system also can be constrained to estimates from single-well, pumping tests. Water-quality changes in the pumping well are simulated with simple mixing models between zones of differing water quality. These zones are differentiated by backtracking thousands of particles from the well screens with MODPATH. An Excel spreadsheet is used to interface the various components of AnalyzeHOLE by (1) creating model input files, (2) executing MODFLOW, MODPATH, PEST, and supporting FORTRAN routines, and (3) importing and graphically

  10. Computational Prediction of Local Distorted Flow in Turbocharger

    NASA Astrophysics Data System (ADS)

    Yao, J.; Yao, Y. F.; Manson, P. J.; Zhang, T.; Heyes, F. J. G.; Roach, P. E.

    This paper presents numerical study by performing three-dimensional Navier-Stokes solution for mixture gas flow in a typical industrial turbocharger configuration. The primary focuses are the flow distortions and behaviours in the proximity of the nozzle vanes. Numerical predictions reveal local flow distortions, shown by a considerable total pressure drop of about 7.5%. The possible reason for this is probably due to the influence of the upstream guide vane wake flow. At both design and off-design conditions considered in this study, the flow near the nozzle vanes has noticeable inhomogeneous in the circumferential direction. However, both local flow distortions and inhomogeneous in annulus are gradually reduced and the flow recovers to near uniform at the nozzle exit plane. Thus the predicted flow distortions have negligible effects on downstream turbine blades.

  11. Falls risk prediction tools for hospital inpatients: do they work?

    PubMed

    Oliver, David; Healy, Frances

    A fall is the most reported safety incident in inpatients and occurs in all adult clinical areas. There is growing interest in prevention strategies and, as part of this, in risk assessment tools. These may be useful if the aim is to flag up common risk factors or causes of falls and prompt interventions that are actually delivered. Tools that claim to predict patients' risk of falling as 'high' or 'low' do not work well and may provide false reassurance that 'something is being done'. Falls prevention should focus on a wider range of actions at the level of patients and across organisations.

  12. A survey of aftbody flow prediction methods

    NASA Technical Reports Server (NTRS)

    Putnam, L. E.; Mace, J.

    1981-01-01

    A survey of computational methods used in the calculation of nozzle aftbody flows is presented. One class of methods reviewed are those which patch together solutions for the inviscid, boundary layer, and plume flow regions. The second class of methods reviewed are those which computationally solve the Navier Stokes equations over nozzle aftbodies with jet exhaust flow. Computed results from the methods are compared with experiment. Advantages and disadvantages of the various methods are discussed along with opportunities for further development of these methods.

  13. STRING 3: An Advanced Groundwater Flow Visualization Tool

    NASA Astrophysics Data System (ADS)

    Schröder, Simon; Michel, Isabel; Biedert, Tim; Gräfe, Marius; Seidel, Torsten; König, Christoph

    2016-04-01

    The visualization of 3D groundwater flow is a challenging task. Previous versions of our software STRING [1] solely focused on intuitive visualization of complex flow scenarios for non-professional audiences. STRING, developed by Fraunhofer ITWM (Kaiserslautern, Germany) and delta h Ingenieurgesellschaft mbH (Witten, Germany), provides the necessary means for visualization of both 2D and 3D data on planar and curved surfaces. In this contribution we discuss how to extend this approach to a full 3D tool and its challenges in continuation of Michel et al. [2]. This elevates STRING from a post-production to an exploration tool for experts. In STRING moving pathlets provide an intuition of velocity and direction of both steady-state and transient flows. The visualization concept is based on the Lagrangian view of the flow. To capture every detail of the flow an advanced method for intelligent, time-dependent seeding is used building on the Finite Pointset Method (FPM) developed by Fraunhofer ITWM. Lifting our visualization approach from 2D into 3D provides many new challenges. With the implementation of a seeding strategy for 3D one of the major problems has already been solved (see Schröder et al. [3]). As pathlets only provide an overview of the velocity field other means are required for the visualization of additional flow properties. We suggest the use of Direct Volume Rendering and isosurfaces for scalar features. In this regard we were able to develop an efficient approach for combining the rendering through raytracing of the volume and regular OpenGL geometries. This is achieved through the use of Depth Peeling or A-Buffers for the rendering of transparent geometries. Animation of pathlets requires a strict boundary of the simulation domain. Hence, STRING needs to extract the boundary, even from unstructured data, if it is not provided. In 3D we additionally need a good visualization of the boundary itself. For this the silhouette based on the angle of

  14. Predicting subjective perceptions of powered tool torque reactions.

    PubMed

    Lin, Jia-Hua; McGorry, Raymond W

    2009-01-01

    Powered hand tools have the potential to produce reaction forces that may be associated with upper extremity musculoskeletal disorders. In this study, subjective ratings of discomfort and acceptability of reaction forces were collected in an attempt to identify their associations with factors such as work location, and response covariates such as grip force and tool handle displacement. Three work configurations using pistol grip and right angle pneumatic nutrunners on horizontal and vertical surfaces were set up in the laboratory. Twenty healthy right-handed male participants operated four tools at nine locations and the corresponding subjective responses were collected. The results indicate that normalized grip force during the torque buildup period was a significant factor for both subjective ratings. For the unacceptable torque reactions across the three tool configurations, the ratio of hand moment impulse over tool torque impulse was significantly greater than for the acceptable reactions. For pistol grip tools used on the vertical surface, as the working height increased 30 cm, the odds of an unacceptable rating over an acceptable rating increased 1.6 times. Prediction models for subjective ratings of discomfort and acceptability provide insight regarding either workstation design or exposure control. These models can further be used to establish exposure limits based on handle displacement and grip force.

  15. 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.

  16. City traffic flow breakdown prediction based on fuzzy rough set

    NASA Astrophysics Data System (ADS)

    Yang, Xu; Da-wei, Hu; Bing, Su; Duo-jia, Zhang

    2017-05-01

    In city traffic management, traffic breakdown is a very important issue, which is defined as a speed drop of a certain amount within a dense traffic situation. In order to predict city traffic flow breakdown accurately, in this paper, we propose a novel city traffic flow breakdown prediction algorithm based on fuzzy rough set. Firstly, we illustrate the city traffic flow breakdown problem, in which three definitions are given, that is, 1) Pre-breakdown flow rate, 2) Rate, density, and speed of the traffic flow breakdown, and 3) Duration of the traffic flow breakdown. Moreover, we define a hazard function to represent the probability of the breakdown ending at a given time point. Secondly, as there are many redundant and irrelevant attributes in city flow breakdown prediction, we propose an attribute reduction algorithm using the fuzzy rough set. Thirdly, we discuss how to predict the city traffic flow breakdown based on attribute reduction and SVM classifier. Finally, experiments are conducted by collecting data from I-405 Freeway, which is located at Irvine, California. Experimental results demonstrate that the proposed algorithm is able to achieve lower average error rate of city traffic flow breakdown prediction.

  17. Development of Design Tools for Flow-Control Actuators

    NASA Technical Reports Server (NTRS)

    Mathew, Jose; Gallas, Quentin; Cattafesta, Louis N., III

    2003-01-01

    This report discusses the: 1. Development coupled electro/fluid/structural lumped-element model (LEM) of a prototypical flow-control actuator. 2. Validation the coupled electro/fluid/structural dynamics lumped-element models. 3. Development simple, yet effective, design tools for actuators. 4. Development structural dynamic models that accurately characterize the dynamic response of piezoelectric flap actuators using the Finite Element Method (FEW as well as analytical methods. 5. Perform a parametric study of a piezo-composite flap actuator. 6.Develop an optimization scheme for maximizing the actuator performance.

  18. GOPET: a tool for automated predictions of Gene Ontology terms.

    PubMed

    Vinayagam, Arunachalam; del Val, Coral; Schubert, Falk; Eils, Roland; Glatting, Karl-Heinz; Suhai, Sándor; König, Rainer

    2006-03-20

    Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO). Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool). It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

  19. 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.

  20. Predicting Flares and Solar Energetic Particle Events: The FORSPEF Tool

    NASA Astrophysics Data System (ADS)

    Anastasiadis, A.; Papaioannou, A.; Sandberg, I.; Georgoulis, M.; Tziotziou, K.; Kouloumvakos, A.; Jiggens, P.

    2017-09-01

    A novel integrated prediction system for solar flares (SFs) and solar energetic particle (SEP) events is presented here. The tool called forecasting solar particle events and flares (FORSPEF) provides forecasts of solar eruptive events, such as SFs with a projection to occurrence and velocity of coronal mass ejections (CMEs), and the likelihood of occurrence of an SEP event. In addition, the tool provides nowcasting of SEP events based on actual SF and CME near real-time data, as well as the SEP characteristics ( e.g. peak flux, fluence, rise time, and duration) per parent solar event. The prediction of SFs relies on the effective connected magnetic field strength (B_{eff}) metric, which is based on an assessment of potentially flaring active-region (AR) magnetic configurations, and it uses a sophisticated statistical analysis of a large number of AR magnetograms. For the prediction of SEP events, new statistical methods have been developed for the likelihood of the SEP occurrence and the expected SEP characteristics. The prediction window in the forecasting scheme is 24 hours with a refresh rate of 3 hours, while the respective prediction time for the nowcasting scheme depends on the availability of the near real-time data and ranges between 15 - 20 minutes for solar flares and 6 hours for CMEs. We present the modules of the FORSPEF system, their interconnection, and the operational setup. Finally, we demonstrate the validation of the modules of the FORSPEF tool using categorical scores constructed on archived data, and we also discuss independent case studies.

  1. Risk prediction tools for cancer in primary care

    PubMed Central

    Usher-Smith, Juliet; Emery, Jon; Hamilton, Willie; Griffin, Simon J; Walter, Fiona M

    2015-01-01

    Numerous risk tools are now available, which predict either current or future risk of a cancer diagnosis. In theory, these tools have the potential to improve patient outcomes through enhancing the consistency and quality of clinical decision-making, facilitating equitable and cost-effective distribution of finite resources such as screening tests or preventive interventions, and encouraging behaviour change. These potential uses have been recognised by the National Cancer Institute as an ‘area of extraordinary opportunity' and an increasing number of risk prediction models continue to be developed. The data on predictive utility (discrimination and calibration) of these models suggest that some have potential for clinical application; however, the focus on implementation and impact is much more recent and there remains considerable uncertainty about their clinical utility and how to implement them in order to maximise benefits and minimise harms such as over-medicalisation, anxiety and false reassurance. If the potential benefits of risk prediction models are to be realised in clinical practice, further validation of the underlying risk models and research to assess the acceptability, clinical impact and economic implications of incorporating them in practice are needed. PMID:26633558

  2. SitesIdentify: a protein functional site prediction tool

    PubMed Central

    2009-01-01

    Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify), based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/ PMID:19922660

  3. Popularity Prediction Tool for ATLAS Distributed Data Management

    NASA Astrophysics Data System (ADS)

    Beermann, T.; Maettig, P.; Stewart, G.; Lassnig, M.; Garonne, V.; Barisits, M.; Vigne, R.; Serfon, C.; Goossens, L.; Nairz, A.; Molfetas, A.; Atlas Collaboration

    2014-06-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  4. A biological tool to assess flow connectivity in reference temporary streams from the Mediterranean Basin.

    PubMed

    Cid, N; Verkaik, I; García-Roger, E M; Rieradevall, M; Bonada, N; Sánchez-Montoya, M M; Gómez, R; Suárez, M L; Vidal-Abarca, M R; Demartini, D; Buffagni, A; Erba, S; Karaouzas, I; Skoulikidis, N; Prat, N

    2016-01-01

    Many streams in the Mediterranean Basin have temporary flow regimes. While timing for seasonal drought is predictable, they undergo strong inter-annual variability in flow intensity. This high hydrological variability and associated ecological responses challenge the ecological status assessment of temporary streams, particularly when setting reference conditions. This study examined the effects of flow connectivity in aquatic macroinvertebrates from seven reference temporary streams across the Mediterranean Basin where hydrological variability and flow conditions are well studied. We tested for the effect of flow cessation on two streamflow indices and on community composition, and, by performing random forest and classification tree analyses we identified important biological predictors for classifying the aquatic state either as flowing or disconnected pools. Flow cessation was critical for one of the streamflow indices studied and for community composition. Macroinvertebrate families found to be important for classifying the aquatic state were Hydrophilidae, Simuliidae, Hydropsychidae, Planorbiidae, Heptageniidae and Gerridae. For biological traits, trait categories associated to feeding habits, food, locomotion and substrate relation were the most important and provided more accurate predictions compared to taxonomy. A combination of selected metrics and associated thresholds based on the most important biological predictors (i.e. Bio-AS Tool) were proposed in order to assess the aquatic state in reference temporary streams, especially in the absence of hydrological data. Although further development is needed, the tool can be of particular interest for monitoring, restoration, and conservation purposes, representing an important step towards an adequate management of temporary rivers not only in the Mediterranean Basin but also in other regions vulnerable to the effects of climate change. Copyright © 2015 Elsevier B.V. All rights reserved.

  5. Prediction of Hydrodynamics for Unidirectional Flow

    DTIC Science & Technology

    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

  6. Initial Integration of Noise Prediction Tools for Acoustic Scattering Effects

    NASA Technical Reports Server (NTRS)

    Nark, Douglas M.; Burley, Casey L.; Tinetti, Ana; Rawls, John W.

    2008-01-01

    This effort provides an initial glimpse at NASA capabilities available in predicting the scattering of fan noise from a non-conventional aircraft configuration. The Aircraft NOise Prediction Program, Fast Scattering Code, and the Rotorcraft Noise Model were coupled to provide increased fidelity models of scattering effects on engine fan noise sources. The integration of these codes led to the identification of several keys issues entailed in applying such multi-fidelity approaches. In particular, for prediction at noise certification points, the inclusion of distributed sources leads to complications with the source semi-sphere approach. Computational resource requirements limit the use of the higher fidelity scattering code to predict radiated sound pressure levels for full scale configurations at relevant frequencies. And, the ability to more accurately represent complex shielding surfaces in current lower fidelity models is necessary for general application to scattering predictions. This initial step in determining the potential benefits/costs of these new methods over the existing capabilities illustrates a number of the issues that must be addressed in the development of next generation aircraft system noise prediction tools.

  7. Software Tool Integrating Data Flow Diagrams and Petri Nets

    NASA Technical Reports Server (NTRS)

    Thronesbery, Carroll; Tavana, Madjid

    2010-01-01

    Data Flow Diagram - Petri Net (DFPN) is a software tool for analyzing other software to be developed. The full name of this program reflects its design, which combines the benefit of data-flow diagrams (which are typically favored by software analysts) with the power and precision of Petri-net models, without requiring specialized Petri-net training. (A Petri net is a particular type of directed graph, a description of which would exceed the scope of this article.) DFPN assists a software analyst in drawing and specifying a data-flow diagram, then translates the diagram into a Petri net, then enables graphical tracing of execution paths through the Petri net for verification, by the end user, of the properties of the software to be developed. In comparison with prior means of verifying the properties of software to be developed, DFPN makes verification by the end user more nearly certain, thereby making it easier to identify and correct misconceptions earlier in the development process, when correction is less expensive. After the verification by the end user, DFPN generates a printable system specification in the form of descriptions of processes and data.

  8. Color visualization for fluid flow prediction

    NASA Technical Reports Server (NTRS)

    Smith, R. E.; Speray, D. E.

    1982-01-01

    High-resolution raster scan color graphics allow variables to be presented as a continuum, in a color-coded picture that is referenced to a geometry such as a flow field grid or a boundary surface. Software is used to map a scalar variable such as pressure or temperature, defined on a two-dimensional slice of a flow field. The geometric shape is preserved in the resulting picture, and the relative magnitude of the variable is color-coded onto the geometric shape. The primary numerical process for color coding is an efficient search along a raster scan line to locate the quadrilteral block in the grid that bounds each pixel on the line. Tension spline interpolation is performed relative to the grid for specific values of the scalar variable, which is then color coded. When all pixels for the field of view are color-defined, a picture is played back from a memory device onto a television screen.

  9. Discovering new in silico tools for antimicrobial peptide prediction.

    PubMed

    Torrent, Marc; Nogués, M Victòria; Boix, Ester

    2012-08-01

    Antimicrobial peptides (AMPs) are important effectors of the innate immune system and play a vital role in the prevention of infections. Due to the increased emergence of new antibiotic-resistant bacteria, new drugs are constantly under investigation. AMPs in particular are recognized as promising candidates because of their modularity and wide antimicrobial spectrum. However, the mechanisms of action of AMPs, as well as their structure-activity relationships, are not completely understood. AMPs display no conserved three-dimensional structure and poor sequence conservation, which hinders rational design. Several bioinformatics tools have been developed to generate new templates with appealing antimicrobial properties with the aim of finding highly active peptide compounds with low cytotoxicity. The current tools reviewed here allow for the prediction and design of new active peptides with reasonable accuracy. However, a reliable method to assess the antimicrobial activity of AMPs has not yet been developed. The standardization of procedures to experimentally evaluate the antimicrobial activity of AMPs, together with the constant growth of current well-established databases, may allow for the future development of new bioinformatics tools to accurately predict antimicrobial activity.

  10. IPMP 2013--a comprehensive data analysis tool for predictive microbiology.

    PubMed

    Huang, Lihan

    2014-02-03

    Predictive microbiology is an area of applied research in food science that uses mathematical models to predict the changes in the population of pathogenic or spoilage microorganisms in foods exposed to complex environmental changes during processing, transportation, distribution, and storage. It finds applications in shelf-life prediction and risk assessments of foods. The objective of this research was to describe the performance of a new user-friendly comprehensive data analysis tool, the Integrated Pathogen Modeling Model (IPMP 2013), recently developed by the USDA Agricultural Research Service. This tool allows users, without detailed programming knowledge, to analyze experimental kinetic data and fit the data to known mathematical models commonly used in predictive microbiology. Data curves previously published in literature were used to test the models in IPMP 2013. The accuracies of the data analysis and models derived from IPMP 2013 were compared in parallel to commercial or open-source statistical packages, such as SAS® or R. Several models were analyzed and compared, including a three-parameter logistic model for growth curves without lag phases, reduced Huang and Baranyi models for growth curves without stationary phases, growth models for complete growth curves (Huang, Baranyi, and re-parameterized Gompertz models), survival models (linear, re-parameterized Gompertz, and Weibull models), and secondary models (Ratkowsky square-root, Huang square-root, Cardinal, and Arrhenius-type models). The comparative analysis suggests that the results from IPMP 2013 were equivalent to those obtained from SAS® or R. This work suggested that the IPMP 2013 could be used as a free alternative to SAS®, R, or other more sophisticated statistical packages for model development in predictive microbiology.

  11. PRmePRed: A protein arginine methylation prediction tool

    PubMed Central

    Kumar, Pawan; Joy, Joseph; Pandey, Ashutosh

    2017-01-01

    Protein methylation is an important Post-Translational Modification (PTMs) of proteins. Arginine methylation carries out and regulates several important biological functions, including gene regulation and signal transduction. Experimental identification of arginine methylation site is a daunting task as it is costly as well as time and labour intensive. Hence reliable prediction tools play an important task in rapid screening and identification of possible methylation sites in proteomes. Our preliminary assessment using the available prediction methods on collected data yielded unimpressive results. This motivated us to perform a comprehensive data analysis and appraisal of features relevant in the context of biological significance, that led to the development of a prediction tool PRmePRed with better performance. The PRmePRed perform reasonably well with an accuracy of 84.10%, 82.38% sensitivity, 83.77% specificity, and Matthew’s correlation coefficient of 66.20% in 10-fold cross-validation. PRmePRed is freely available at http://bioinfo.icgeb.res.in/PRmePRed/ PMID:28813517

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

    USGS Publications Warehouse

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

    2007-01-01

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

  13. Pulmonary outcome prediction (POP) tools for cystic fibrosis patients.

    PubMed

    VanDevanter, Donald R; Wagener, Jeffrey S; Pasta, David J; Elkin, Eric; Jacobs, Joan R; Morgan, Wayne J; Konstan, Michael W

    2010-12-01

    Loss of lung function in patients with cystic fibrosis (CF) is associated with increased mortality and varies between individuals and over time. Predicting this decline could improve patient management. To develop simple pulmonary outcome prediction (POP) tools to estimate lung function at age 6 in patients aged 2-5 years (POP(2-5)) and lung function change over a 4-year period in patients aged 6-17 years (POP(6-17)). Analyses were conducted using patients from the Epidemiologic Study of CF (ESCF). To be included in any analysis, patients had to have 1 year of clinical history recorded in ESCF prior to a clinically stable routine Index Clinic Visit (ICV). In addition to this criterion, for the POP(2-5) tool patients had to be between 2 and 5 years old at ICV and have a second clinically stable visit with spirometric measures at age 6. For the POP(6-17) tool, patients had to be between the ages of 6 and 17 years old at an ICV that included spirometric measures and had to have a second clinically stable visit with spirometric measures from 3 to 5 years after ICV. All patients enrolled in ESCF who met these inclusion criteria were studied. POP(2-5) and POP(6-17) populations were further divided into development groups (with ICV before January 1, 1998) and validation groups (with ICV after that date). Development groups were used to model forced expiratory volume in 1 sec (FEV(1)) percent predicted at age 6 years (for POP(2-5)) and annualized FEV(1) % predicted change from ICV to the second visit (for POP(6-17)) by multivariable linear regression using age, sex, weight-for-age percentile, cough, sputum production, clubbing, crackles, wheeze, sinusitis, number of exacerbations requiring intravenous antibiotics in the past year, elevated liver enzymes, pancreatic enzyme use, and respiratory tract culture status, plus height-for-age percentile (POP(2-5)) and index FEV(1) (POP(6-17)). Integer-based POP(2-5) and POP(6-17) tools created from selected variables were

  14. The development of a tool to predict team performance.

    PubMed

    Sinclair, M A; Siemieniuch, C E; Haslam, R A; Henshaw, M J D C; Evans, L

    2012-01-01

    The paper describes the development of a tool to predict quantitatively the success of a team when executing a process. The tool was developed for the UK defence industry, though it may be useful in other domains. It is expected to be used by systems engineers in initial stages of systems design, when concepts are still fluid, including the structure of the team(s) which are expected to be operators within the system. It enables answers to be calculated for questions such as "What happens if I reduce team size?" and "Can I reduce the qualifications necessary to execute this process and still achieve the required level of success?". The tool has undergone verification and validation; it predicts fairly well and shows promise. An unexpected finding is that the tool creates a good a priori argument for significant attention to Human Factors Integration in systems projects. The simulations show that if a systems project takes full account of human factors integration (selection, training, process design, interaction design, culture, etc.) then the likelihood of team success will be in excess of 0.95. As the project derogates from this state, the likelihood of team success will drop as low as 0.05. If the team has good internal communications and good individuals in key roles, the likelihood of success rises towards 0.25. Even with a team comprising the best individuals, p(success) will not be greater than 0.35. It is hoped that these results will be useful for human factors professionals involved in systems design.

  15. Flow Control Analysis on the Hump Model with RANS Tools

    NASA Technical Reports Server (NTRS)

    Viken, Sally A.; Vatsa, Veer N.; Rumsey, Christopher L.; Carpenter, Mark H.

    2003-01-01

    A concerted effort is underway at NASA Langley Research Center to create a benchmark for Computational Fluid Dynamic (CFD) codes. both unstructured and structured, against a data set for the hump model with actuation. The hump model was tested in the NASA Langley 0.3-m Transonic Cryogenic Tunnel. The CFD codes used for the analyses are the FUN2D (Full Unstructured Navier-Stokes 2-Dimensional) code, the structured TLNS3D (Thin-Layer Navier-Stokes 3-Dimensional) code, and the structured CFL3D code, all developed at NASA Langley. The current investigation uses the time-accurate Reynolds-Averaged Navier-Stokes (RANS) approach to predict aerodynamic performance of the active flow control experimental database for the hump model. Two-dimensional computational results verified that steady blowing and suction and oscillatory suction/blowing can be used to significantly reduce the separated flow region on the model. Discrepancies do exist between the CFD results and experimental data in the region downstream of the slot with the largest differences in the oscillatory cases. Overall, the structured CFD codes exhibited similar behavior with each other for a wide range of control conditions, with the unstructured FUN2D code showing moderately different results in the separated flow region for the suction and oscillatory cases.

  16. 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.

  17. 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.

  18. Low thrust viscous nozzle flow fields prediction

    NASA Astrophysics Data System (ADS)

    Liaw, Goang-Shin

    1987-12-01

    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.

  19. Potential predictability of a Colombian river flow

    NASA Astrophysics Data System (ADS)

    Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

    2017-04-01

    In this study the predictability of an important Colombian river (Cauca) has been analysed based on the use of climatic variables as potential predictors. Cauca River is considered one of the most important rivers of Colombia because its basin supports important productive activities related with the agriculture, such as the production of coffee or sugar. Potential relationships between the Cauca River seasonal streamflow anomalies and different climatic variables such as sea surface temperature (SST), precipitation (Pt), temperature over land (Tm) and soil water (Sw) have been analysed for the period 1949-2009. For this end, moving correlation analysis of 30 years have been carried out for lags from one to four seasons for the global SST, and from one to two seasons for South America Pt, Tm and Sw. Also, the stability of the significant correlations have been also studied, identifying the regions used as potential predictors of streamflow. Finally, in order to establish a prediction scheme based on the previous stable correlations, a Principal Component Analysis (PCA) applied on the potential predictor regions has been carried out in order to obtain a representative time series for each predictor field. Significant and stable correlations between the seasonal streamflow and the tropical Pacific SST (El Niño region) are found for lags from one to four (one-year) season. Additionally, some regions in the Indian and Atlantic Oceans also show significant and stable correlations at different lags, highlighting the importance that exerts the Atlantic SST on the hydrology of Colombia. Also significant and stable correlations are found with the Pt, Tm and Sw for some regions over South America, at lags of one and two seasons. The prediction of Cauca seasonal streamflow based on this scheme shows an acceptable skill and represents a relative improvement compared with the predictability obtained using the teleconnection indices associated with El Niño. Keywords

  20. 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

  1. Mass Transport through Nanostructured Membranes: Towards a Predictive Tool

    PubMed Central

    Darvishmanesh, Siavash; Van der Bruggen, Bart

    2016-01-01

    This study proposes a new mechanism to understand the transport of solvents through nanostructured membranes from a fundamental point of view. The findings are used to develop readily applicable mathematical models to predict solvent fluxes and solute rejections through solvent resistant membranes used for nanofiltration. The new model was developed based on a pore-flow type of transport. New parameters found to be of fundamental importance were introduced to the equation, i.e., the affinity of the solute and the solvent for the membrane expressed as the hydrogen-bonding contribution of the solubility parameter for the solute, solvent and membrane. A graphical map was constructed to predict the solute rejection based on the hydrogen-bonding contribution of the solubility parameter. The model was evaluated with performance data from the literature. Both the solvent flux and the solute rejection calculated with the new approach were similar to values reported in the literature. PMID:27918434

  2. Plasticity Tool for Predicting Shear Nonlinearity of Unidirectional Laminates Under Multiaxial Loading

    NASA Technical Reports Server (NTRS)

    Wang, John T.; Bomarito, Geoffrey F.

    2016-01-01

    This study implements a plasticity tool to predict the nonlinear shear behavior of unidirectional composite laminates under multiaxial loadings, with an intent to further develop the tool for use in composite progressive damage analysis. The steps for developing the plasticity tool include establishing a general quadratic yield function, deriving the incremental elasto-plastic stress-strain relations using the yield function with associated flow rule, and integrating the elasto-plastic stress-strain relations with a modified Euler method and a substepping scheme. Micromechanics analyses are performed to obtain normal and shear stress-strain curves that are used in determining the plasticity parameters of the yield function. By analyzing a micromechanics model, a virtual testing approach is used to replace costly experimental tests for obtaining stress-strain responses of composites under various loadings. The predicted elastic moduli and Poisson's ratios are in good agreement with experimental data. The substepping scheme for integrating the elasto-plastic stress-strain relations is suitable for working with displacement-based finite element codes. An illustration problem is solved to show that the plasticity tool can predict the nonlinear shear behavior for a unidirectional laminate subjected to multiaxial loadings.

  3. Predicting Rediated Noise With Power Flow Finite Element Analysis

    DTIC Science & Technology

    2007-02-01

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

  4. Prediction tool for thrombi associated with peripherally inserted central catheters.

    PubMed

    Seeley, Maria A; Santiago, Mary; Shott, Susan

    2007-01-01

    The upper extremity deep vein thrombosis rate is increasing at the same time that the rate for insertions of peripherally inserted central catheters is on the rise. There is little information on whether the established risk factors for lower extremity deep vein thromboses are effective to predict the occurrence of upper extremity deep vein thrombosis. The purpose of this study was to identify patients at highest risk for upper extremity deep vein thrombosis in order to initiate effective prophylaxis. A retrospective review was undertaken of medical records of all patients with peripherally inserted central catheters inserted in a 6-month period at a Midwestern US hospital. Of the 233 charts reviewed, 17 (7.3%) recorded an upper extremity deep vein thrombosis during the patient's hospital stay. Of the multiple factors identified with deep vein thrombosis in the literature, a weighted risk factor measure, the upper extremity deep vein thrombosis prediction tool, was developed. Sensitivity of the instrument for upper extremity deep vein thrombosis is high (88%), as are its specificity (82%) and negative predictive value (99%), whereas the positive predictive value is low (28%). The total percentage of cases correctly classified is 82%. Further testing is indicated on a larger sample to extend the validity of this instrument.

  5. Three computational tools for predicting bacterial essential genes.

    PubMed

    Guo, Feng-Biao; Ye, Yuan-Nong; Ning, Lu-Wen; Wei, Wen

    2015-01-01

    Essential genes are those genes indispensable for the survival of any living cell. Bacterial essential genes constitute the cornerstones of synthetic biology and are often attractive targets in the development of antibiotics and vaccines. Because identification of essential genes with wet-lab ways often means expensive economic costs and tremendous labor, scientists changed to seek for alternative way of computational prediction. Aiming to help to solve this issue, our research group (CEFG: group of Computational, Comparative, Evolutionary and Functional Genomics, http://cefg.uestc.edu.cn) has constructed three online services to predict essential genes in bacterial genomes. These freely available tools are applicable for single gene sequences without annotated functions, single genes with definite names, and complete genomes of bacterial strains. To ensure reliable predictions, the investigated species should belong to the same family (for EGP) or phylum (for CEG_Match and Geptop) with one of the reference species, respectively. As the pilot software for the issue, predicting accuracies of them have been assessed and compared with existing algorithms, and note that all of other published algorithms have not any formed online services. We hope these services at CEFG will help scientists and researchers in the field of essential genes.

  6. Modified Breastfeeding Attrition Prediction Tool: Prenatal and Postpartum Tests

    PubMed Central

    Evans, Marilyn L.; Dick, Margaret J.; Lewallen, Lynne P.; Jeffrey, Cynthia

    2004-01-01

    In earlier studies, the Breastfeeding Attrition Prediction Tool (BAPT) demonstrated predictive validity in the postpartum period. The purpose of this study was to compare the effectiveness of a modified version of the BAPT when given in the last trimester (BAPT1) and following delivery (BAPT2) in predicting breastfeeding attrition among 117 women who planned to breastfeed for at least 8 weeks. Subjects completed the BAPT during a prenatal breastfeeding class and again at delivery, and they received a phone call at 8 weeks to determine breastfeeding status. In this study, neither of the two administrations of the BAPT was predictive of breastfeeding status at 8 weeks. Findings here may differ because subjects in the current study were all committed enough to attend breastfeeding class and, thus, varied less on commitment than women in earlier studies. Significant associations were found with level of education and having a close relative who breastfed. To assist the perinatal educator in identifying women most at risk for early cessation of breastfeeding, the use of three questions regarding level of education, family support, and breastfeeding preparation is suggested. PMID:17273370

  7. Modified breastfeeding attrition prediction tool: prenatal and postpartum tests.

    PubMed

    Evans, Marilyn L; Dick, Margaret J; Lewallen, Lynne P; Jeffrey, Cynthia

    2004-01-01

    In earlier studies, the Breastfeeding Attrition Prediction Tool (BAPT) demonstrated predictive validity in the postpartum period. The purpose of this study was to compare the effectiveness of a modified version of the BAPT when given in the last trimester (BAPT1) and following delivery (BAPT2) in predicting breastfeeding attrition among 117 women who planned to breastfeed for at least 8 weeks. Subjects completed the BAPT during a prenatal breastfeeding class and again at delivery, and they received a phone call at 8 weeks to determine breastfeeding status. In this study, neither of the two administrations of the BAPT was predictive of breastfeeding status at 8 weeks. Findings here may differ because subjects in the current study were all committed enough to attend breastfeeding class and, thus, varied less on commitment than women in earlier studies. Significant associations were found with level of education and having a close relative who breastfed. To assist the perinatal educator in identifying women most at risk for early cessation of breastfeeding, the use of three questions regarding level of education, family support, and breastfeeding preparation is suggested.

  8. Fetal Right Ventricular Prominence: Associated Postnatal Abnormalities and Coarctation Clinical Prediction Tool.

    PubMed

    Power, Alyssa; Nettel-Aguirre, Alberto; Fruitman, Deborah

    2017-07-24

    Fetal right ventricular (RV) prominence is a known indicator of possible left-sided structural heart disease with a low positive predictive value for aortic coarctation. There is a paucity of data on identifying which fetuses with RV prominence will have postnatal arch obstruction. Our study objectives were to create a clinical prediction tool for coarctation and to describe the diagnostic outcomes of our cohort with fetal RV prominence. We performed a retrospective review of patients referred with fetal RV prominence from January 2009 to October 2015. Recorded fetal echocardiographic variables included gestational age, semilunar and atrioventricular valve dimensions, left and right ventricular mid-cavitary dimensions, foramen ovale and aortic arch flow direction, and isthmal diameter. Postnatal cardiac and non-cardiac diagnoses were documented. We performed descriptive analysis for postnatal outcomes and classification tree analysis to create a clinical prediction tool. Eighty-eight patients were reviewed; 58 (66%) had abnormal postnatal echocardiograms, 45 (51%) had left-sided lesions, including 26 (30%) with coarctation, and 6 (7%) had pulmonary hypertension. Our clinical prediction tool employs gestational age, RV mid-cavitary dimension z-score, and isthmal diameter z-score to predict coarctation with 85% accuracy, 95% confidence interval [75.3, 92.4%]. Our model correctly classified 45/54 non-coarctation and 19/21 coarctation cases, with 90% sensitivity and 83% specificity. Developing an accurate prediction tool for coarctation in cases of fetal RV prominence is an important first step in improving our management of these challenging cases.

  9. 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.

  10. Two dimensional Coupled Eulerian Lagrangian (CEL) model for banded structure prediction in friction stir welding with trigonal tool

    NASA Astrophysics Data System (ADS)

    Tongne, A.; Robe, H.; Desrayaud, C.; Jahazi, M.; Feulvarch, E.

    2016-10-01

    A finite element model has been developed by means of a coupled Eulerian-Lagrangian approach. The banded structure which is related to the periodical material deposition is predicted in two dimensions as the experimental investigation shows that, during FSW with trigonal tool, the material flow operates mainly in the welded plates plan.

  11. Modeling and Prediction of Hot Deformation Flow Curves

    NASA Astrophysics Data System (ADS)

    Mirzadeh, Hamed; Cabrera, Jose Maria; Najafizadeh, Abbas

    2012-01-01

    The modeling of hot flow stress and prediction of flow curves for unseen deformation conditions are important in metal-forming processes because any feasible mathematical simulation needs accurate flow description. In the current work, in an attempt to summarize, generalize, and introduce efficient methods, the dynamic recrystallization (DRX) flow curves of a 17-4 PH martensitic precipitation hardening stainless steel, a medium carbon microalloyed steel, and a 304 H austenitic stainless steel were modeled and predicted using (1) a hyperbolic sine equation with strain dependent constants, (2) a developed constitutive equation in a simple normalized stress-normalized strain form and its modified version, and (3) a feed-forward artificial neural network (ANN). These methods were critically discussed, and the ANN technique was found to be the best for the modeling available flow curves; however, the developed constitutive equation showed slightly better performance than that of ANN and significantly better predicted values than those of the hyperbolic sine equation in prediction of flow curves for unseen deformation conditions.

  12. Numerical prediction of impact force in cavitating flows

    NASA Astrophysics Data System (ADS)

    Zhu, B.; Wang, H.

    2010-08-01

    An analytical method including a macroscopic cavitation model based on the homogeneous flow theory and a microscopic cavitation model based on the bubble dynamic was proposed for the prediction of the impact force caused by cavitation bubbles collapse in cavitating flows. A Large Eddy Simulation (LES) solver incorporated the macroscopic cavitation model was applied to simulate the unsteady cavitating flows. Based on the simulated flow field, the evolution of the cavitation bubbles was determined by a microscopic cavitation model from the resolution of a Rayleigh-Plesset equation including of the effects of the surface tension, the viscosity and compressibility of fluid, thermal conduction and radiation, the phase transition of water vapor at interface and chemical reactions. The cavitation flow around a hydrofoil was simulated to validate the macroscopic cavitation model. A good quantitative agreement was obtained between the prediction and the experiment. The proposed analytical method was applied to predict the impact force at cavitation bubbles collapse on a KT section in cavitating flows. It was found that the shock pressure caused by cavitation bubble collapse is very high. The impact force was predicted accurately comparing with the experimental data.

  13. Cardiovascular risk prediction tools for populations in Asia

    PubMed Central

    Collaboration, Asia Pacific Cohort Studies

    2007-01-01

    Background Cardiovascular risk equations are traditionally derived from the Framingham Study. The accuracy of this approach in Asian populations, where resources for risk factor measurement may be limited, is unclear. Objective To compare “low‐information” equations (derived using only age, systolic blood pressure, total cholesterol and smoking status) derived from the Framingham Study with those derived from the Asian cohorts, on the accuracy of cardiovascular risk prediction. Design Separate equations to predict the 8‐year risk of a cardiovascular event were derived from Asian and Framingham cohorts. The performance of these equations, and a subsequently “recalibrated” Framingham equation, were evaluated among participants from independent Chinese cohorts. Setting Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US. Participants 172 077 participants from the Asian cohorts; 25 682 participants from Chinese cohorts and 6053 participants from the Framingham Study. Main results In the Chinese cohorts, 542 cardiovascular events occurred during 8 years of follow‐up. Both the Asian cohorts and the Framingham equations discriminated cardiovascular risk well in the Chinese cohorts; the area under the receiver–operator characteristic curve was at least 0.75 for men and women. However, the Framingham risk equation systematically overestimated risk in the Chinese cohorts by an average of 276% among men and 102% among women. The corresponding average overestimation using the Asian cohorts equation was 11% and 10%, respectively. Recalibrating the Framingham risk equation using cardiovascular disease incidence from the non‐Chinese Asian cohorts led to an overestimation of risk by an average of 4% in women and underestimation of risk by an average of 2% in men. Interpretation A low‐information Framingham cardiovascular risk prediction tool, which, when recalibrated with

  14. Predictions of Bedforms in Steady, Tidal and Oscillatory Flows

    NASA Astrophysics Data System (ADS)

    Gallagher, E. L.

    2016-02-01

    Bedforms are ubiquitous in unconsolidated sediments. They range in size from small orbital ripples (l 5-50 cm) to megaripples (l 1-5 m) to large dunes (l 10-100 m). Bedforms are important because they affect sediment transport, flow energy dissipation, and larger-scale hydro- and morpho-dynamics. Bedforms in different environments (eg, deserts, rivers and oceans) are thought to be dynamically similar, therefore modeling approaches from one environment can be used to predicted features in another (Gallagher 2011). Here, a self-organization model is used to simulate the formation and development of bedforms in the combined flows of the surf zone, tidal inlets and river mouths. Sediment flux is determined from combined wave and current flows using different formulations, but, interestingly, the transport formulation has little effect on model results. Random bed irregularities, either imposed or resulting from small variations in the flow representing turbulence, are seeds for bedform development. Feedback between the bed and the flow in the form of a shadow zone downstream of a bedform and increasing flow velocity with elevation over bedform crests alter the transport such that organized bedforms emerge. The model has been used to predict surf zone megaripples and bedforms in tidal inlets and river mouths. Many bedform models (e.g., Hulscher et al. 1996, Nielsen 1981, Clifton 1976, Wiberg and Harris 1994), predict specific bedform characteristics for a given flow condition. However, many observations report multiple scales existing simultaneously. A recent study by Lefevbre et al (2013) found that the boundary layer thickness and resulting bedform-induced roughness was different for single and multiple bedform fields. The present model predicts multiple bedform scales. In this study, predictions of different time and length scales of bedform evolution and roughness, as a function of flow magnitude, direction and variability are being examined.

  15. 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.

  16. 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.

  17. Micropollutants in urban watersheds : substance flow analysis as management tool

    NASA Astrophysics Data System (ADS)

    Rossi, L.; Copin, P. J.; Barry, A. D.; Bader, H.-P.; Scheidegger, R.; Chèvre, N.

    2009-04-01

    Micropollutants released by cities into water are of increasing concern as they are suspected of inducing long-term effects on both aquatic organisms and humans (eg., hormonally active substances). Substances found in the urban water cycle have different sources in the urban area and different fates in this cycle. For example, the pollutants emitted from traffic, like copper or PAHs get to surface water during rain events often without any treatment. Pharmaceuticals resulting from human medical treatments get to surface water mainly through wastewater treatment plants, where they are only partly treated and eliminated. One other source of contamination in urban areas for these compounds are combined sewer overflows (CSOs). Once in the receiving waters (lakes, rivers, groundwater), these substances may re-enter the cycle through drinking water. It is therefore crucial to study the behaviour of micropollutants in the urban water cycle and to get flexible tools for urban water management. Substance flow analysis (SFA) has recently been proposed as instrument for water pollution management in urban water systems. This kind of analysis is an extension of material flow analysis (MFA) originally developed in the economic sector and later adapted to regional investigations. In this study, we propose to test the application of SFA for a large number of classes of micropollutants to evaluate its use for urban water management. We chose the city of Lausanne as case study since the receiving water of this city (Lake Geneva) is an important source of drinking water for the surrounding population. Moreover a profound system-knowledge and many data were available, both on the sewer system and the water quality. We focus our study on one heavy metal (copper) and four pharmaceuticals (diclofenac, ibuprofen, carbamazepine and naproxen). Results conducted on copper reveals that around 1500 kg of copper enter the aquatic compartment yearly. This amount contributes to sediment

  18. Microparticle tracking velocimetry as a tool for microfluidic flow measurements

    NASA Astrophysics Data System (ADS)

    Salipante, Paul; Hudson, Steven D.; Schmidt, James W.; Wright, John D.

    2017-07-01

    The accurate measurement of flows in microfluidic channels is important for commercial and research applications. We compare the accuracy of flow measurement techniques over a wide range flows. Flow measurements made using holographic microparticle tracking velocimetry (µPTV) and a gravimetric flow standard over the range of 0.5-100 nL/s agree within 0.25%, well within the uncertainty of the two flow systems. Two commercial thermal flow sensors were used as the intermediaries (transfer standards) between the two flow measurement systems. The gravimetric flow standard was used to calibrate the thermal flow sensors by measuring the rate of change of the mass of liquid in a beaker on a micro-balance as it fills. The holographic µPTV flow measurements were made in a rectangular channel and the flow was seeded with 1 µm diameter polystyrene spheres. The volumetric flow was calculated using the Hagen-Pouiseille solution for a rectangular channel. The uncertainty of both flow measurement systems is given. For the gravimetric standard, relative uncertainty increased for decreasing flows due to surface tension forces between the pipette carrying the flow and the free surface of the liquid in the beaker. The uncertainty of the holographic µPTV measurements did not vary significantly over the measured flow range, and thus comparatively are especially useful at low flow velocities.

  19. Predicted impact and evaluation of North Carolina's phosphorus indexing tool.

    PubMed

    Johnson, Amy M; Osmond, Deanna L; Hodges, Steven C

    2005-01-01

    Increased concern about potential losses of phosphorus (P) from agricultural fields receiving animal waste has resulted in the implementation of new state and federal regulations related to nutrient management. In response to strengthened nutrient management standards that require consideration of P, North Carolina has developed a site-specific P indexing system called the Phosphorus Loss Assessment Tool (PLAT) to predict relative amounts of potential P loss from agricultural fields. The purpose of this study was to apply the PLAT index on farms throughout North Carolina in an attempt to predict the percentage and types of farms that will be forced to change management practices due to implementation of new regulations. Sites from all 100 counties were sampled, with the number of samples taken from each county depending on the proportion of the state's agricultural land that occurs in that county. Results showed that approximately 8% of producers in the state will be required to apply animal waste or inorganic fertilizer on a P rather than nitrogen basis, with the percentage increasing for farmers who apply animal waste (approximately 27%). The PLAT index predicted the greatest amounts of P loss from sites in the Coastal Plain region of North Carolina and from sites receiving poultry waste. Loss of dissolved P through surface runoff tended to be greater than other loss pathways and presents an area of concern as no best management practices (BMPs) currently exist for the reduction of in-field dissolved P. The PLAT index predicted the areas in the state that are known to be disproportionately vulnerable to P loss due to histories of high P applications, high densities of animal units, or soil type and landscapes that are most susceptible to P loss.

  20. 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.

  1. Ontology-based tools to expedite predictive model construction.

    PubMed

    Haug, Peter; Holmen, John; Wu, Xinzi; Mynam, Kumar; Ebert, Matthew; Ferraro, Jeffrey

    2014-01-01

    Large amounts of medical data are collected electronically during the course of caring for patients using modern medical information systems. This data presents an opportunity to develop clinically useful tools through data mining and observational research studies. However, the work necessary to make sense of this data and to integrate it into a research initiative can require substantial effort from medical experts as well as from experts in medical terminology, data extraction, and data analysis. This slows the process of medical research. To reduce the effort required for the construction of computable, diagnostic predictive models, we have developed a system that hybridizes a medical ontology with a large clinical data warehouse. Here we describe components of this system designed to automate the development of preliminary diagnostic models and to provide visual clues that can assist the researcher in planning for further analysis of the data behind these models.

  2. A numerical hemodynamic tool for predictive vascular surgery.

    PubMed

    Marchandise, Emilie; Willemet, Marie; Lacroix, Valérie

    2009-01-01

    We suggest a new approach to peripheral vascular bypass surgery planning based on solving the one-dimensional (1D) governing equations of blood flow in patient-specific models. The aim of the present paper is twofold. First, we present the coupled 1D-0D model based on a discontinuous Galerkin method in a comprehensive manner, such as it becomes accessible to a wider community than the one of mathematicians and engineers. Then we show how this model can be applied to predict hemodynamic parameters and help therefore clinicians to choose for the best surgical option bettering the hemodynamics of a bypass. After presenting some benchmark problems, we apply our model to a real-life clinical application, i.e. a femoro-popliteal bypass surgery. Our model shows good agreement with preoperative and intraoperative measurements of velocity and pressure and post-surgical reports.

  3. A pollutant removal prediction tool for stormwater derived diffuse pollution.

    PubMed

    Revitt, D Michael; Scholes, Lian; Ellis, J Bryan

    2008-01-01

    This report describes the development of a methodology to theoretically assess the effectiveness of structural BMPs with regard to their treatment of selected stormwater pollutants (metals, polyaromatic hydrocarbons and herbicides). The result is a prioritisation, in terms of pollutant removal efficiency, of 15 different BMPs which can inform stormwater managers and other stakeholders of the best available options for the treatment of urban runoff pollutants of particular environmental concern. Regardless of the selected pollutant, infiltration basins and sub-surface flow constructed wetlands are predicted to perform most efficiently with lagoons, porous asphalt and sedimentation tanks being the least effective systems for the removal of pollutants. The limitations of the approach in terms of the variabilities in BMP designs and applications are considered. (c) IWA Publishing 2008.

  4. Orbit Prediction Tool for Different Classes of Space Debris Orbits

    NASA Astrophysics Data System (ADS)

    Wnuk, Edwin; Wytrzyszczak, Iwona; Golembiewska, Justyna; Klinkrad, Heiner

    There are two aspects of the orbital evolution of space debris: the long-term evolution and the short-term prediction of individual object orbits. In the case of the long-term evolution (years or tens of years time span) general characteristics (e.g. total number of objects, spa-tial distribution and density) of a future space environment are predicted with the use of a relatively simple theory of motion for statistical analysis of future orbits of a large number of objects -a cloud of particles". In the short-term orbital evolution of space debris objects, as considered in this paper, future positions and velocities of individual objects are calculated for a few days or a few weeks time span. A much more sophisticated theory of satellite motion is applied in this case. The paper presents the orbital prediction tool that uses an analytical and semi-analytical theories of satellite motion. The force model includes all important perturbing factors: geopotential effects with arbitrary degree and order spherical harmonic coefficients taken into account, luni-solar attractions, solar radiation pressure and atmospheric drag. The analytical theory of motion is of the second order and is not sensitive to singularities for small eccentricities and small inclinations. A new algorithm for the transformation between mean and osculating elements for the second order theory is applied. Predicted positions of a satel-lite on a given level of accuracy are calculated only with the use of terms that essentially influence on predicted satellite orbit, all other terms are omitted. The number of terms in for-mulas for perturbations, and thus complexity of the theory, depends on the defined level of accuracy and the type of orbit. In practice, we create a dynamical model for a given class of satellite orbit. Geopotential and luni-solar perturbations are calculated in the two following steps. In the first step, values of secular terms and all amplitudes of periodic terms are calculated

  5. 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.

  6. MODFLOW 2. 0: A program for predicting moderator flow patterns

    SciTech Connect

    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.

  7. Prediction of leakage flow in a shrouded centrifugal blood pump.

    PubMed

    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.

  8. [Implementation of a clinical prediction tool in renal transplant recipients].

    PubMed

    Martínez-Mier, Gustavo; Ávila-Pardo, Sandro Fabricio; Méndez-López, Marco Tulio; Budar-Fernández, Luis Filadelfo; Soto-Miranda, Ernesto; Romero-de Lara, Paloma Itzel; González-Velázquez, Felipe; Lajud-Barquín, Francisco Antonio; Zilli-Hernández, Stefan

    2017-01-01

    Kasiske developed a tool for predicting the risk of 5-year graft loss. We analyzed our results using this model. 109 deceased donor kidney transplants were included. 5-year probability of graft survival was calculated during transplantation, seven days after transplantation and 1-year after transplantation. Z-test and ROC curves were used for proportion differences and discrimination ability. Mean age of donor and recipient was 33.7 and 33.9 years, respectively. 59.6% died due to trauma. Mean of years on dialysis was 3.7. 22.9% of patients had delayed graft function (DGF). Calculated 5-year probability of graft survival during transplantation time was 74.1%; 7 days after transplantation, 74.9%; and one year after transplantation, 76.4%. 5-year death censored graft survival was 64.9%. There were no differences between death-censored graft survival and calculated probabilities (Z-test), with a C-statistic value of 0.54 ± 0.6 (95%CI 0.42-0.65, p = 0.5) and 0.51 ± 0.6 (0.39-0.63, 95% CI, p = 0. 7) for transplant time and seven days after. C-statistic value 1-year after transplantation was 0.68 ± 0.8 (95%CI 0.52-0.84, p = 0.02). Only calculated 5-year graft survival one year after transplantation had modest prediction ability.

  9. 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

  10. Does the Risk Assessment and Prediction Tool predict discharge disposition after joint replacement?

    PubMed

    Hansen, Viktor J; Gromov, Kirill; Lebrun, Lauren M; Rubash, Harry E; Malchau, Henrik; Freiberg, Andrew A

    2015-02-01

    Payers of health services and policymakers place a major focus on cost containment in health care. Studies have shown that early planning of discharge is essential in reducing length of stay and achieving financial benefit; tools that can help predict discharge disposition would therefore be of use. The Risk Assessment and Prediction Tool (RAPT) is a preoperative survey constructed to predict discharge disposition after total joint arthroplasty (TJA). The RAPT was developed and tested on a population of Australian patients undergoing joint replacement, but its validity in other populations is unknown. A low RAPT score is reported to indicate a high risk of needing any form of inpatient rehabilitation after TJA, including short-term nursing facilities. This study attempts (1) to assess predictive accuracy of the RAPT on US patients undergoing total hip and knee arthroplasty (THA/TKA); and (2) to determine predictive accuracy of each individual score (1-12). Between June 2006 and December 2011, RAPT scores of 3213 patients (1449 THAs; 1764 TKAs) were prospectively captured during the preoperative clinical visit. Scores were stored along with other clinical data, including discharge disposition, in a dedicated database on a secure server. The database was queried by the nursing case manager to retrieve the RAPT scores of all patients captured during this time period. Binary logistic regression was used to analyze the scores and determine predictive accuracy. Overall predictive accuracy was 78%. RAPT scores<6 and >10 (of 12) predicted with >90% accuracy discharge to inpatient rehabilitation and home, respectively. Predictive accuracy was lowest for scores between 7 and 10 at 65.2% and almost 50% of patients received scores in this range. Based on our findings, the risk categories in our populations should be high risk<7, intermediate risk 7 to 10, and low risk>10. The RAPT accurately predicted discharge disposition for high- and low-risk patients in our cohort. Based

  11. Larvicidal activity prediction against Aedes aegypti mosquito using computational tools.

    PubMed

    Cañizares-Carmenate, Yudith; Hernandez-Morfa, Mirelys; Torrens, Francisco; Castellano, Gloria; Castillo-Garit, Juan A

    2017-01-01

    Aedes aegypti is an important vector for transmission of dengue, yellow fever, chikun- gunya, arthritis, and Zika fever. According to the World Health Organization, it is estimated that Ae. aegypti causes 50 million infections and 25,000 deaths per year. Use of larvicidal agents is one of the recommendations of health organizations to control mosquito populations and limit their distribution. The aim of present study was to deduce a mathematical model to predict the larvicidal action of chemical compounds, based on their structure. A series of different compounds with experimental evidence of larvicidal activity were selected to develop a predictive model, using multiple linear regression and a genetic algorithm for the selection of variables, implemented in the QSARINS software. The model was assessed and validated using the OECDs principles. The best model showed good value for the determination coefficient (R2 = 0.752), and others parameters were appropriate for fitting (s = 0.278 and RMSEtr = 0.261). The validation results confirmed that the model hasgood robustness (Q2LOO = 0.682) and stability (R2-Q2LOO = 0.070) with low correlation between the descriptors (KXX = 0.241), an excellent predictive power (R2 ext = 0.834) and was product of a non-random correlation R2 Y-scr = 0.100). The present model shows better parameters than the models reported earlier in the literature, using the same dataset, indicating that the proposed computational tools are more efficient in identifying novel larvicidal compounds against Ae. aegypti.

  12. A discrete event simulation tool to support and predict hospital and clinic staffing.

    PubMed

    DeRienzo, Christopher M; Shaw, Ryan J; Meanor, Phillip; Lada, Emily; Ferranti, Jeffrey; Tanaka, David

    2017-06-01

    We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit's staffing, referral patterns, or patient mix would affect a unit in a future state.

  13. Doppler flowmetry as a tool of predictive, preventive and personalised dentistry

    PubMed Central

    2013-01-01

    Periodontal lesions are considered a major problem in the global burden of oral diseases due to their high frequency and negative impact on quality of life. Periodontal inflammation is accomplished by a breakdown of microcirculatory function. Early detection of gingival microvessel dysfunction helps diagnose and prevent the progression of initial periodontal pathology. Doppler flowmetry is a useful tool in the diagnosis, monitoring, prognosis and management of periodontal patients which allows access not only of gingival blood flow but also of pulpal microcirculation. Doppler flowmeters might help to realise the ultimate target of predictive, preventive and personalised periodontology tailored with respect to the particular patient. This article highlights the main working principles of laser Doppler flowmeters and the ultrasonic Doppler flowmeters. The advances in blood flow measurement by ultrasonic flowmetry are discussed. PMID:23981527

  14. Thermal Protection System Evaluation Using Arc-jet Flows: Flight Simulation or Research Tool?

    NASA Technical Reports Server (NTRS)

    Stewart, David A.; Venkatapathy, Ethiras (Technical Monitor)

    2002-01-01

    The arc-jet has been used to evaluate thermal protection systems (TPS) and materials for the past forty years. Systems that have been studied in this environmerd include ablators, active, and passive TPS concepts designed for vehicles entering planetary and Earth atmospheres. The question of whether arc-jet flow can simulate a flight environment or is it a research tool that provides an aero-thermodynamic heating environment to obtain critical material properties will be addressed. Stagnation point tests in arc-jets are commonly used to obtain material properties such as mass loss rates, thermal chemical stability data, optical properties, and surface catalytic efficiency. These properties are required in computational fluid dynamic codes to accurately predict the performance of a TPS during flight. Special facilities have been developed at NASA Ames Research Center to approximate the flow environment over the mid-fuselage and body flap regions of proposed space-planes type vehicles. This paper compares flow environments generated in flight over a vehicle with those created over an arc-jet test articles in terms of scale, chemistry, and fluid dynamic properties. Flight experiments are essential in order to validate the material properties obtained from arc-jet tests and used to predict flight performance of any TPS being considered for use on a vehicle entering the Earth atmosphere at hypersonic speed.

  15. TCAF model in XSPEC : An efficient tool to understand accretion flow dynamics around black holes

    NASA Astrophysics Data System (ADS)

    Debnath, Dipak; Sarathi Pal, Partha; Chakrabarti, Sandip Kumar; Mondal, Santanu; Jana, Arghajit; Chatterjee, Debjit; Molla, Aslam Ali

    2016-07-01

    It has been more than two decades of the classic work by Chakrabarti and his collaborators on the two component advective flow (TCAF) model. Recently we successfully been able to include it in HEASARC's spectral analysis software package XSPEC as an additive local model to fit energy spectra from black hole candidates (BHCs) and obtain physical accretion flow parameters, such as, two component (Keplerian disk and sub-Keplerian halo) accretion rates, shock (location, i.e., the size of the Compton cloud, and the compression ratio) parameters. Evolutions of spectral and timing properties are transparent from the TCAF model fitted/derived physical parameters. Reason of different spectral states and their transitions during an outburst of a transient BHC are also clear. One can also predict frequency of the dominating quasi-periodic oscillation (QPO) from TCAF model fitted shock parameters and even predict most preferable mass range of an unknown BHC from TCAF fits. To our knowledge this gives us the most physical tool to investigate the accretion flow dynamics around black hole candidates.

  16. Thermal Protection System Evaluation Using Arc-jet Flows: Flight Simulation or Research Tool?

    NASA Technical Reports Server (NTRS)

    Stewart, David A.; Venkatapathy, Ethiras (Technical Monitor)

    2002-01-01

    The arc-jet has been used to evaluate thermal protection systems (TPS) and materials for the past forty years. Systems that have been studied in this environmerd include ablators, active, and passive TPS concepts designed for vehicles entering planetary and Earth atmospheres. The question of whether arc-jet flow can simulate a flight environment or is it a research tool that provides an aero-thermodynamic heating environment to obtain critical material properties will be addressed. Stagnation point tests in arc-jets are commonly used to obtain material properties such as mass loss rates, thermal chemical stability data, optical properties, and surface catalytic efficiency. These properties are required in computational fluid dynamic codes to accurately predict the performance of a TPS during flight. Special facilities have been developed at NASA Ames Research Center to approximate the flow environment over the mid-fuselage and body flap regions of proposed space-planes type vehicles. This paper compares flow environments generated in flight over a vehicle with those created over an arc-jet test articles in terms of scale, chemistry, and fluid dynamic properties. Flight experiments are essential in order to validate the material properties obtained from arc-jet tests and used to predict flight performance of any TPS being considered for use on a vehicle entering the Earth atmosphere at hypersonic speed.

  17. Predicting the Performance of an Axial-Flow Compressor

    NASA Technical Reports Server (NTRS)

    Steinke, R. J.

    1986-01-01

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

  18. Comparison of Performance Predictions for New Low-Thrust Trajectory Tools

    NASA Technical Reports Server (NTRS)

    Polsgrove, Tara; Kos, Larry; Hopkins, Randall; Crane, Tracie

    2006-01-01

    Several low thrust trajectory optimization tools have been developed over the last 3% years by the Low Thrust Trajectory Tools development team. This toolset includes both low-medium fidelity and high fidelity tools which allow the analyst to quickly research a wide mission trade space and perform advanced mission design. These tools were tested using a set of reference trajectories that exercised each tool s unique capabilities. This paper compares the performance predictions of the various tools against several of the reference trajectories. The intent is to verify agreement between the high fidelity tools and to quantify the performance prediction differences between tools of different fidelity levels.

  19. 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.

  20. 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

  1. Predictive modeling of particle-laden turbulent flows. Final report

    SciTech Connect

    Shaffer, F.; Bolio, E.J.; Hrenya, C.M.

    1993-12-31

    Earlier work of Sinclair and Jackson which treats the laminar flow of gas-solid suspensions is extended to model dilute turbulent flow. The random particle motion, often exceeding the turbulent fluctuations in the gas, is obtained using a model based on kinetic theory of granular materials. A two-equation low Reynolds number turbulence model is, modified to account for the presence of the dilute particle phase. Comparisons of the model predictions with available experimental data for the mean and fluctuating velocity profiles for both phases indicate that the resulting theory captures many of the flow features observed in the pneumatic transport of large particles. The model predictions did not manifest an extreme sensitivity to the degree of inelasticity in the particle-particle collisions for the range of solid loading ratios investigated.

  2. 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.

  3. 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.

  4. 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.

  5. 3PE: A Tool for Estimating Groundwater Flow Vectors

    EPA Science Inventory

    Evaluation of hydraulic gradients and the associated groundwater flow rates and directions is a fundamental aspect of hydrogeologic characterization. Many methods, ranging in complexity from simple three-point solution techniques to complex numerical models of groundwater flow, ...

  6. 3PE: A Tool for Estimating Groundwater Flow Vectors

    EPA Science Inventory

    Evaluation of hydraulic gradients and the associated groundwater flow rates and directions is a fundamental aspect of hydrogeologic characterization. Many methods, ranging in complexity from simple three-point solution techniques to complex numerical models of groundwater flow, ...

  7. Gas-liquid annular flow under microgravity conditions: Linear stability as a tool for flow regime identification

    SciTech Connect

    Best, F.R.; Carron, I.

    1994-12-31

    A single parameter has been developed that predicts the highly nonlinear state of a microgravity flow with a confidence of up to 95% in differentiating slug flow from other regimes for different fluids of radically different properties such as air/water and Freon-11, -12, and -114. The authors have also shown that by taking the best data available based on current knowledge, it was possible to predict the flow regime in experiments with an accuracy of at least 85%, whether the flow was slug or bubbly, slug/annular and annular flow.

  8. Practical Predictability of Flows with Many Scales of Motion

    NASA Astrophysics Data System (ADS)

    Snyder, C.

    2016-12-01

    With advances in both observational and computational capabilities, data assimilation and prediction that treat a range of spatial or temporal scales simultaneously are increasingly feasible. This raises the question of predictability in practice, for a given observing network, across that range of scales. Basic insights follow from generalizing Lorenz's (1969) model for the intrinsic predictability of isotropic, homogeneous turbulence to include data assimilation. When the exponent of the flow's kinetic-energy power law is -3 (the situation that characterizes atmospheric motions for scales larger than roughly 400 km), even scales smaller than the resolution of the observational network can be analyzed and predicted skillfully. For an exponent of -5/3 (the situation that characterizes atmospheric scales below roughly 400 km), recovery of unobserved scales by the assimilation scheme is much more limited and skillful prediction is possible only for observed scales.

  9. Transient Heat and Material Flow Modeling of Friction Stir Processing of Magnesium Alloy using Threaded Tool

    SciTech Connect

    Yu, Zhenzhen; Zhang, Wei; Choo, Hahn; Feng, Zhili

    2012-01-01

    A three-dimensional transient computational fluid dynamics (CFD) model was developed to investigate the material flow and heat transfer during friction stir processing (FSP) in an AZ31B magnesium alloy. The material was assumed to be a non-Newtonian viscoplastic fluid, and the Zener-Hollomon parameter was used to describe the dependence of material viscosity on temperature and strain rate. The material constants used in the constitutive equation were determined experimentally from compression tests of the AZ31B Mg alloy under a wide range of strain rates and temperatures. A dynamic mesh method, combining both Lagrangian and Eulerian formulations, was used to capture the material flow induced by the movement of the threaded tool pin. Massless inert particles were embedded in the simulation domain to track the detailed history of material flow. The actual FSP was also carried out on a wrought Mg plate where temperature profiles were recorded by embedding thermocouples. The predicted transient temperature history was found to be consistent with that measured during FSP. Finally, the influence of the thread on the simulated results of thermal history and material flow was studied by comparing two models: one with threaded pin and the other with smooth pin surface.

  10. Temperature as a predictive tool for plantar triaxial loading.

    PubMed

    Yavuz, Metin; Brem, Ryan W; Davis, Brian L; Patel, Jalpa; Osbourne, Abe; Matassini, Megan R; Wood, David A; Nwokolo, Irene O

    2014-11-28

    Diabetic foot ulcers are caused by moderate repetitive plantar stresses in the presence of peripheral neuropathy. In severe cases, the development of these foot ulcers can lead to lower extremity amputations. Plantar pressure measurements have been considered a capable predictor of ulceration sites in the past, but some investigations have pointed out inconsistencies when solely relying on this method. The other component of ground reaction forces/stresses, shear, has been understudied due to a lack of adequate equipment. Recent articles reported the potential clinical significance of shear in diabetic ulcer etiology. With the lack of adequate tools, plantar temperature has been used as an alternative method for determining plantar triaxial loading and/or shear. However, this method has not been previously validated. The purpose of this study was to analyze the potential association between exercise-induced plantar temperature increase and plantar stresses. Thirteen healthy individuals walked on a treadmill for 10 minutes at 3.2km/h. Pre and post-exercise temperature profiles were obtained with a thermal camera. Plantar triaxial stresses were quantified with a custom-built stress plate. A statistically significant correlation was observed between peak shear stress (PSS) and temperature increase (r=0.78), but not between peak resultant stress (PRS) and temperature increase (r=0.46). Plantar temperature increase could predict the location of PSS and PRS in 23% and 39% of the subjects, respectively. Only a moderate linear relationship was established between triaxial plantar stresses and walking-induced temperature increase. Future research will investigate the value of nonlinear models in predicting plantar loading through foot temperature.

  11. Bathyphotometer bioluminescence potential measurements: A framework for characterizing flow agitators and predicting flow-stimulated bioluminescence intensity

    NASA Astrophysics Data System (ADS)

    Latz, Michael I.; Rohr, Jim

    2013-07-01

    BBP. This correlation, when further scaled by pipe diameter, effectively predicted bioluminescence intensity in fully developed turbulent flow in a 0.83-cm i.d. pipe. Determining similar correlations between other bathyphotometer flow agitators and flow fields will allow bioluminescence potential measurements to become a more powerful tool for the oceanographic community.

  12. Multiscale prediction of patient-specific platelet function under flow.

    PubMed

    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.

  13. Artificial neural networks as tool for atmospheric modeling and prediction

    NASA Astrophysics Data System (ADS)

    Scharringhausen, Marco

    Applications of the theory of neural networks to the modeling of the middle and upper atmo-sphere are presented. Artificial neural networks are a tool to mimic biological behavior and exploit capabilities in terms of learning and pattern recognition. Neural networks belong to the class of "first-principles" models. That is, the interaction between individual neuron cells is modeled. The basic tuning parameter in such networks is the set of weights describing the interconnections between individual neuron cells. by adjustment of the weight vector, the network can be trained to reproduce a certain amount of data. The MSIS-2000 model is utilized to train an artificial neural network. Certain atmospheric state parameters such as temperature, ion density are included in the analysis. It is shown that after a training phase covering the years 1970 -1995 the neural network reproduces the model calculations of 1996 -2005 to a good extend. The deviations are quantified. It is concluded that after a training phase the neural network can be utilized to predict the atmospheric state beyond the actual time phase covered by the empirical model. This method is suggested to be utilized for different kinds of empirical models, e.g. models of solar variability.

  14. Spatial statistics for predicting flow through a rock fracture

    SciTech Connect

    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.

  15. 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.

  16. 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

  17. 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

  18. Prediction of strongly-heated internal gas flows

    SciTech Connect

    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.

  19. Risk assessment tools used to predict outcomes of total hip and total knee arthroplasty.

    PubMed

    Konopka, Joseph F; Hansen, Viktor J; Rubash, Harry E; Freiberg, Andrew A

    2015-07-01

    This article reviews recently proposed clinical tools for predicting risks and outcomes in total hip arthroplasty and total knee arthroplasty patients. Additionally, we share the Massachusetts General Hospital experience with using the Risk Assessment and Prediction Tool to predict the need for an extended care facility after total joint arthroplasty.

  20. FASB 95--a tool for identifying cash flow problems.

    PubMed

    Edwards, D E; Hauser, R C

    1989-06-01

    Increasing expenditures and longer collection periods for receivables are symptoms of the cash flow problem that many not-for-profit healthcare organizations face. The FASB 95 provisions for a cash flow statement could help many of these organizations deal with their cash flow crises. The statement allows managers to evaluate their institution's financial performance, providing timely information that may make the difference in the struggle to maintain an adequate cash position.

  1. Clusters as a diagnostics tool for gas flows

    NASA Astrophysics Data System (ADS)

    Ganeva, M.; Kashtanov, P. V.; Kosarim, A. V.; Smirnov, B. M.; Hippler, R.

    2015-06-01

    The example of a gas flowing through an orifice into the surrounding rarefied space is used to demonstrate the possibility of using clusters for diagnosing gas flows. For the conditions studied (it takes a cluster velocity about the same time to relax to the gas velocity as it does to reach the orifice), information on the flow parameters inside the chamber is obtained from the measurement of the cluster drift velocity after the passage through an orifice for various gas consumptions. Other possible uses of clusters in gas flow diagnostics are discussed as well.

  2. 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.

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

    NASA Technical Reports Server (NTRS)

    Abid, R.; Speziale, C. G.

    1992-01-01

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

  4. Flow Control Predictions using URANS Modeling: A Parametric Study

    NASA Technical Reports Server (NTRS)

    Rumsey, Christopher L.; Greenblatt, David

    2007-01-01

    A computational study was performed for steady and oscillatory flow control over a hump model with flow separation to assess how well the steady and unsteady Reynolds-averaged Navier-Stokes equations predict trends due to Reynolds number, control magnitude, and control frequency. As demonstrated previously, the hump model case is useful because it clearly demonstrates a failing in all known turbulence models: they under-predict the turbulent shear stress in the separated region and consequently reattachment occurs too far downstream. In spite of this known failing, three different turbulence models were employed to determine if trends can be captured even though absolute levels are not. The three turbulence models behaved similarly. Overall they showed very similar trends as experiment for steady suction, but only agreed qualitatively with some of the trends for oscillatory control.

  5. 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.

  6. Turbulent flow field predictions in sharply curved turn around ducts

    NASA Technical Reports Server (NTRS)

    Santi, L. M.

    1986-01-01

    In this investigation, two-dimensional turbulent flow of incompressible Newtonian fluids in sharply curved 180 deg turn around ducts is studied. Results of an approximate numerical flow field analysis utilizing an orthogonal, body-fitted, curvilinear coordinate system are compared to results based on a traditional cylindrical reference frame. Qualitative indication of general streamfield characteristics as well as quantitative benchmarks for the planning of future experimentation are provided. In addition, preliminary results of an augmented kappa-epsilon turbulence model analysis, which explicitly accounts for the effects of streamline curvature and pressure strain in internal turbulent flows, are presented. Specific model difficulties are discussed and comparisons with standard kappa-esilon model predictions are included.

  7. Special session: computational predictability of natural convection flows in enclosures

    SciTech Connect

    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.

  8. Early Antenatal Prediction of Gestational Diabetes in Obese Women: Development of Prediction Tools for Targeted Intervention

    PubMed Central

    White, Sara L.; Lawlor, Debbie A.; Briley, Annette L.; Nelson, Scott M.; Oteng-Ntim, Eugene; Sattar, Naveed; Seed, Paul T.; Welsh, Paul; Whitworth, Melissa; Poston, Lucilla; Pasupathy, Dharmintra

    2016-01-01

    All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0–18+6 weeks’ gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68–0.74). This increased to 0.77 (95%CI 0.73–0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74–0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described

  9. Early Antenatal Prediction of Gestational Diabetes in Obese Women: Development of Prediction Tools for Targeted Intervention.

    PubMed

    White, Sara L; Lawlor, Debbie A; Briley, Annette L; Godfrey, Keith M; Nelson, Scott M; Oteng-Ntim, Eugene; Robson, Stephen C; Sattar, Naveed; Seed, Paul T; Vieira, Matias C; Welsh, Paul; Whitworth, Melissa; Poston, Lucilla; Pasupathy, Dharmintra

    2016-01-01

    All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0-18+6 weeks' gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68-0.74). This increased to 0.77 (95%CI 0.73-0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74-0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  12. Production flow analysis: a tool for designing a lean hospital.

    PubMed

    Karvonen, Sauli; Korvenranta, Heikki; Paatela, Mikael; Seppälä, Timo

    2007-01-01

    Production flow analysis (PFA) was used in the planning process for a new acute care hospital. The PFA demonstrated that functional organisation--for example, with centralised medical imaging-- generates a lot of back and forth patient transfers between functional units. This to-and-fro patient flow increases lead times of care processes and also exposes the patients to unnecessary complications. PFA produced an ideal patient flow model and layout model for the acute care hospital. Thus, PFA revealed information for use in proximity ranking of different units of the hospital; the planning team then decided which units should be placed next to each other. Medical imaging should be essentially ubiquitous, to achieve simple, high-velocity patient flow. Thus, a modern decentralized layout model for medical imaging was planned. Furthermore, PFA enables optimizing transfer routes for patients and also, e.g., lift capacity in the hospital.

  13. 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.

  14. Predicting the evolution of fast chemical reactions in chaotic flows.

    PubMed

    Tsang, Yue-Kin

    2009-08-01

    We study the fast irreversible bimolecular reaction in a two-dimensional chaotic flow. The reactants are initially segregated and together fill the whole domain. Simulations show that the reactant concentration decays exponentially with rate lambda and then crosses over to the algebraic law of chemical kinetics in the final stage of the reaction. We estimate the crossover time from the reaction rate constant and the flow parameters. The exponential decay phase of the reaction can be described in terms of an equivalent passive scalar problem, allowing us to predict lambda using the theory of passive scalar advection. Depending on the relative length scale between the velocity and the concentration fields, lambda is either related to the distribution of the finite-time Lyapunov exponent of the flow or given in terms of an effective diffusivity which is independent of the small-scale stretching properties of the flow. For the former case, we suggest an optimal choice of flow parameters at which lambda is maximum.

  15. Assessment of RANS to predict flows with large streamline curvature

    NASA Astrophysics Data System (ADS)

    Yin, J. L.; Wang, D. Z.; Cheng, H.; Gu, W. G.

    2013-12-01

    In order to provide a guideline for choosing turbulence models in computation of complex flows with large streamline curvature, this paper presents a comprehensive comparison investigation of different RANS models widely used in engineering to check each model's sensibility on the streamline curvature. First, different models including standard k-ε, Realizable k-ε, Renormalization-group (RNG) k-ε model, Shear-stress transport k-ω model and non-linear eddy-viscosity model v2-f model are tested to simulated the flow in a 2D U-bend which has the standard bench mark available. The comparisons in terms of non-dimensional velocity and turbulent kinetic energy show that large differences exist among the results calculated by various models. To further validate the capability to predict flows with secondary flows, the involved models are tested in a 3D 90° bend flow. Also, the velocities are compared. As a summary, the advantages and disadvantages of each model are analysed and guidelines for choice of turbulence model are presented.

  16. 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.

  17. Predictive onboard flow control in packet switching satellites

    NASA Technical Reports Server (NTRS)

    Bobinsky, E. 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.

  18. Prognostic and Prediction Tools in Bladder Cancer: A Comprehensive Review of the Literature.

    PubMed

    Kluth, Luis A; Black, Peter C; Bochner, Bernard H; Catto, James; Lerner, Seth P; Stenzl, Arnulf; Sylvester, Richard; Vickers, Andrew J; Xylinas, Evanguelos; Shariat, Shahrokh F

    2015-08-01

    This review focuses on risk assessment and prediction tools for bladder cancer (BCa). To review the current knowledge on risk assessment and prediction tools to enhance clinical decision making and counseling of patients with BCa. A literature search in English was performed using PubMed in July 2013. Relevant risk assessment and prediction tools for BCa were selected. More than 1600 publications were retrieved. Special attention was given to studies that investigated the clinical benefit of a prediction tool. Most prediction tools for BCa focus on the prediction of disease recurrence and progression in non-muscle-invasive bladder cancer or disease recurrence and survival after radical cystectomy. Although these tools are helpful, recent prediction tools aim to address a specific clinical problem, such as the prediction of organ-confined disease and lymph node metastasis to help identify patients who might benefit from neoadjuvant chemotherapy. Although a large number of prediction tools have been reported in recent years, many of them lack external validation. Few studies have investigated the clinical utility of any given model as measured by its ability to improve clinical decision making. There is a need for novel biomarkers to improve the accuracy and utility of prediction tools for BCa. Decision tools hold the promise of facilitating the shared decision process, potentially improving clinical outcomes for BCa patients. Prediction models need external validation and assessment of clinical utility before they can be incorporated into routine clinical care. We looked at models that aim to predict outcomes for patients with bladder cancer (BCa). We found a large number of prediction models that hold the promise of facilitating treatment decisions for patients with BCa. However, many models are missing confirmation in a different patient cohort, and only a few studies have tested the clinical utility of any given model as measured by its ability to improve

  19. Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

    NASA Technical Reports Server (NTRS)

    Morey, Susan; Prevot, Thomas; Mercer, Joey; Martin, Lynne; Bienert, Nancy; Cabrall, Christopher; Hunt, Sarah; Homola, Jeffrey; Kraut, Joshua

    2013-01-01

    A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

  20. From Gaged to Ungaged- Predicting Long-term Environmental Flows, and Ecosystems Responses.

    NASA Astrophysics Data System (ADS)

    Sengupta, A.; Adams, S. K.; Stein, E. D.; Mazor, R.; Bledsoe, B. P.

    2015-12-01

    Modern management needs, such as water supply, quality, and ecosystem protection place numerous demands on instream flows. Many regions are interested in developing numeric flow criteria as a way of ensuring maintenance of flow patterns that protect biological resources while meeting other demands. Developing flow criteria requires the capacity to generate reliable time series of the daily flow at any stream reach of interest and to relate flow patterns to biological indicators of stream health. Most stream reaches are not gaged, and it is impractical to develop detailed models for all reaches where flow alteration needs to be evaluated. We present a novel mechanistic approach to efficiently predict flows and flow alteration at all ungaged stream locations within a region of interest. We used an "ensemble approach" whereby a series of regionally representative models were developed and calibrated. New sites of interest are assigned to one of the ensemble models based on similarity of catchment properties. For southern California, we selected 43 gaged sites representing the range of geomorphology, and watershed characteristics of streams in the region. For each gaged site, we developed a hydrologic model (HEC-HMS) to predict daily flows for a period representing dry, wet and normal precipitation. The final goal is to relate flow alterations to ecological responses, the models were calibrated to three separate performance metrics that reflect conditions important for instream biological communities- proportion of low flow days, flashiness and Nash Sutcliffe efficiency for overall model performance. We cross-validated the models using a "jack-knife" approach. Models were assigned to novel 840 bioassessment sites based on the results of a Random Forest model that identified catchment properties that most affected the runoff patterns. Daily flow data for existing and "reference conditions" was simulated for a 23-year period for current and reference (undeveloped

  1. 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.

  2. Predicting Great Lakes fish yields: tools and constraints

    USGS Publications Warehouse

    Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

    1987-01-01

    Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

  3. Predicting tool operator capacity to react against torque within acceptable handle deflection limits in automotive assembly.

    PubMed

    Radwin, Robert G; Chourasia, Amrish; Fronczak, Frank J; Subedi, Yashpal; Howery, Robert; Yen, Thomas Y; Sesto, Mary E; Irwin, Curtis B

    2016-05-01

    The proportion of tool operators capable of maintaining published psychophysically derived threaded fastener tool handle deflection limits were predicted using a biodynamic tool operator model, interacting with the tool, task and workstation. Tool parameters, including geometry, speed and torque were obtained from the specifications for 35 tools used in an auto assembly plant. Tool mass moments of inertia were measured for these tools using a novel device that engages the tool in a rotating system of known inertia. Task parameters, including fastener target torque and joint properties (soft, medium or hard), were ascertained from the vehicle design specifications. Workstation parameters, including vertical and horizontal distances from the operator were measured using a laser rangefinder for 69 tool installations in the plant. These parameters were entered into the model and tool handle deflection was predicted for each job. While handle deflection for most jobs did not exceed the capacity of 75% females and 99% males, six jobs exceeded the deflection criterion. Those tool installations were examined and modifications in tool speed and operator position improved those jobs within the deflection limits, as predicted by the model. We conclude that biodynamic tool operator models may be useful for identifying stressful tool installations and interventions that bring them within the capacity of most operators.

  4. Prediction and archival tools for asteroid radar observations

    NASA Astrophysics Data System (ADS)

    Margot, J.

    2014-07-01

    The Earth-based radar facilities at Arecibo and Goldstone have provided very powerful tools for characterizing the trajectories and physical properties of asteroids. This is especially important for near-Earth asteroids (NEAs) which are key in the contexts of hazard mitigation, spacecraft exploration, and resource utilization. Over 10,000 NEAs have been identified and over 430 have been detected with radar (http://radarastronomy.org). Both of these numbers are growing rapidly, necessitating efficient tools for data archival and observation planning. The asteroid radar database hosted at radarastronomy.org keeps track of all radar detections, documents NEA physical properties, and provides NEA observability conditions. With the help of UCLA students, we are integrating a number of tools with the database to facilitate recordkeeping and observation planning. For instance, a geometry-finder tool allows us to identify the optimal times to observe specific NEAs and to compute rise-transit-set windows. Signal-to-noise (SNR) tools allow us to compute SNR values for both Arecibo and Goldstone observations. Python-based graphical tools help visualize the history of asteroid detections and plan future observations. A collaborative research environment (wiki) facilitates interactions among radar observers. These tools and others in preparation enable a more coordinated and efficient process for asteroid radar observations.

  5. A probabilistic prediction network for hydrological drought identification and environmental flow assessment

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyong; Törnros, Tobias; Menzel, Lucas

    2016-08-01

    A general probabilistic prediction network is proposed for hydrological drought examination and environmental flow assessment. This network consists of three major components. First, we present the joint streamflow drought indicator (JSDI) to describe the hydrological dryness/wetness conditions. The JSDI is established based on a high-dimensional multivariate probabilistic model. In the second part, a drought-based environmental flow assessment method is introduced, which provides dynamic risk-based information about how much flow (the environmental flow target) is required for drought recovery and its likelihood under different hydrological drought initial situations. The final part involves estimating the conditional probability of achieving the required environmental flow under different precipitation scenarios according to the joint dependence structure between streamflow and precipitation. Three watersheds from different countries (Germany, China, and the United States) with varying sizes from small to large were used to examine the usefulness of this network. The results show that the JSDI can provide an assessment of overall hydrological dryness/wetness conditions and performs well in identifying both drought onset and persistence. This network also allows quantitative prediction of targeted environmental flow required for hydrological drought recovery and estimation of the corresponding likelihood. Moreover, the results confirm that the general network can estimate the conditional probability associated with the required flow under different precipitation scenarios. The presented methodology offers a promising tool for water supply planning and management and for drought-based environmental flow assessment. The network has no restrictions that would prevent it from being applied to other basins worldwide.

  6. TAS: A Transonic Aircraft/Store flow field prediction code

    NASA Technical Reports Server (NTRS)

    Thompson, D. S.

    1983-01-01

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

  7. Predicting Extubation Outcome by Cough Peak Flow Measured Using a Built-in Ventilator Flow Meter.

    PubMed

    Gobert, Florent; Yonis, Hodane; Tapponnier, Romain; Fernandez, Raul; Labaune, Marie-Aude; Burle, Jean-François; Barbier, Jack; Vincent, Bernard; Cleyet, Maria; Richard, Jean-Christophe; Guérin, Claude

    2017-09-12

    Successful weaning from mechanical ventilation depends on the patient's ability to cough efficiently. Cough peak flow (CPF) could predict extubation success using a dedicated flow meter but required patient disconnection. We aimed to predict extubation outcome using an overall model, including cough performance assessed by a ventilator flow meter. This was a prospective observational study conducted from November 2014 to October 2015. Before and after a spontaneous breathing trial, subjects were encouraged to cough as strongly as possible before freezing the ventilator screen to assess CPF and tidal volume (VT) in the preceding inspiration. Early extubation success rate was defined as the proportion of subjects not re-intubated 48h after extubation. Diagnostic performance of CPF and VT was assessed by using the area under the curve of the receiver operating characteristic curve. Cut-off values for CPF and VT were defined according to median values and used to describe the performance of a predictive test combining them with risk factors of early extubation failure. Among 673 subjects admitted, 92 had a cough assessment before extubation. For the 81 subjects with early extubation success, the median CPF was -67.7L/min, and median VT was 0.646L. For the 11 subjects with early extubation failure, the median CPF was -57.3L/min, and median VT was 0.448L. Area under the curve was 0.61 (95% CI 0.37-0.83) for CPF and 0.64 (95% CI 0.42-0.84) for CPF/VT combined. After dichotomization (CPF < -60L/min or VT> 0.55L), there was a synergistic effect to predict early extubation success (P < .001). The predictive value of success reached 94.2% for CPF/VT combined. The overall model including pH before extubation < 7.45 reached a 66.7% predictive value of failure. CPF measured using the flow meter of an ICU ventilator was able to predict extubation success and to build a composite score to predict extubation failure. The results were close to that found in previous studies that

  8. The efficacy of violence prediction: a meta-analytic comparison of nine risk assessment tools.

    PubMed

    Yang, Min; Wong, Stephen C P; Coid, Jeremy

    2010-09-01

    Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their predictive efficacies for violence. The effect sizes were extracted from 28 original reports published between 1999 and 2008, which assessed the predictive accuracy of more than one tool. We used a within-subject design to improve statistical power and multilevel regression models to disentangle random effects of variation between studies and tools and to adjust for study features. All 9 tools and their subscales predicted violence at about the same moderate level of predictive efficacy with the exception of Psychopathy Checklist--Revised (PCL-R) Factor 1, which predicted violence only at chance level among men. Approximately 25% of the total variance was due to differences between tools, whereas approximately 85% of heterogeneity between studies was explained by methodological features (age, length of follow-up, different types of violent outcome, sex, and sex-related interactions). Sex-differentiated efficacy was found for a small number of the tools. If the intention is only to predict future violence, then the 9 tools are essentially interchangeable; the selection of which tool to use in practice should depend on what other functions the tool can perform rather than on its efficacy in predicting violence. The moderate level of predictive accuracy of these tools suggests that they should not be used solely for some criminal justice decision making that requires a very high level of accuracy such as preventive detention.

  9. Error estimation for CFD aeroheating prediction under rarefied flow condition

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  10. 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.

  11. 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.

  12. The Efficacy of Violence Prediction: A Meta-Analytic Comparison of Nine Risk Assessment Tools

    ERIC Educational Resources Information Center

    Yang, Min; Wong, Stephen C. P.; Coid, Jeremy

    2010-01-01

    Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their…

  13. The Efficacy of Violence Prediction: A Meta-Analytic Comparison of Nine Risk Assessment Tools

    ERIC Educational Resources Information Center

    Yang, Min; Wong, Stephen C. P.; Coid, Jeremy

    2010-01-01

    Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their…

  14. IHT: Tools for Computing Insolation Absorption by Particle Laden Flows

    SciTech Connect

    Grout, Ray

    2013-09-17

    INT is a toolkit for computing radiative heat exchange between particles. The algorithm is based on the the 'Photon Monte Carlo" approach described by Wang and Modest and implemented as a library that can be interfaced with a variety of CFD codes to analyze radiative heat transfer in particle laden flows.

  15. Debris flow early warning systems in Norway: organization and tools

    NASA Astrophysics Data System (ADS)

    Kleivane, I.; Colleuille, H.; Haugen, L. E.; Alve Glad, P.; Devoli, G.

    2012-04-01

    In Norway, shallow slides and debris flows occur as a combination of high-intensity precipitation, snowmelt, high groundwater level and saturated soil. Many events have occurred in the last decades and are often associated with (or related to) floods events, especially in the Southern of Norway, causing significant damages to roads, railway lines, buildings, and other infrastructures (i.e November 2000; August 2003; September 2005; November 2005; Mai 2008; June and Desember 2011). Since 1989 the Norwegian Water Resources and Energy Directorate (NVE) has had an operational 24 hour flood forecasting system for the entire country. From 2009 NVE is also responsible to assist regions and municipalities in the prevention of disasters posed by landslides and snow avalanches. Besides assisting the municipalities through implementation of digital landslides inventories, susceptibility and hazard mapping, areal planning, preparation of guidelines, realization of mitigation measures and helping during emergencies, NVE is developing a regional scale debris flow warning system that use hydrological models that are already available in the flood warning systems. It is well known that the application of rainfall thresholds is not sufficient to evaluate the hazard for debris flows and shallow slides, and soil moisture conditions play a crucial role in the triggering conditions. The information on simulated soil and groundwater conditions and water supply (rain and snowmelt) based on weather forecast, have proved to be useful variables that indicate the potential occurrence of debris flows and shallow slides. Forecasts of runoff and freezing-thawing are also valuable information. The early warning system is using real-time measurements (Discharge; Groundwater level; Soil water content and soil temperature; Snow water equivalent; Meteorological data) and model simulations (a spatially distributed version of the HBV-model and an adapted version of 1-D soil water and energy balance

  16. A New Imaging Tool for Realtime Measurement of Flow Velocity in Intracranial Aneurysms.

    PubMed

    Petridis, Athanasios K; Kaschner, Marius; Cornelius, Jan F; Kamp, Marcel A; Tortora, Angelo; Steiger, Hans-Jakob; Turowski, Bernd

    2017-06-07

    With modern imaging modalities of the brain a significant number of unruptured aneurysms are detected. However, not every aneurysm is prone to rupture. Because treatment morbidity is about 10% it is crucial to identify unstable aneurysms for which treatment should be discussed. Recently, new imaging tools allow analysis of flow dynamics and wall stability have become available. It seems that they might provide additional data for better risk profiling. In this study we present a new imaging tool for analysis of flow dynamics, which calculates fluid velocity in an aneurysm (Phillips Electronics, N.V.). It may identify regions with high flow and calculate flow reduction after stenting of aneurysms. Contrast is injected with a stable injection speed of 2 mL/sec for 3 sec. Two clinical cases are illustrated. Velocity in aneurysms and areas of instability can be identified and calculated during angiography in real-time. After stenting and flow diverter deployment flow reduction in the internal carotid aneurysm was reduced by 60% and there was a reduction of about 65% in the posterior cerebral artery in the second case we are reporting. The dynamic flow software calculates the flow profile in the aneurysm immediately after contrast injection. It is a real-time, patient specific tool taking into account systole, diastole and flexibility of the vasculature. These factors are an improvement as compared to current models of computational flow dynamics. We think it is a highly efficient, user friendly tool. Further clinical studies are on their way.

  17. A New Imaging Tool for Realtime Measurement of Flow Velocity in Intracranial Aneurysms

    PubMed Central

    Petridis, Athanasios K.; Kaschner, Marius; Cornelius, Jan F.; Kamp, Marcel A.; Tortora, Angelo; Steiger, Hans-Jakob; Turowski, Bernd

    2017-01-01

    With modern imaging modalities of the brain a significant number of unruptured aneurysms are detected. However, not every aneurysm is prone to rupture. Because treatment morbidity is about 10% it is crucial to identify unstable aneurysms for which treatment should be discussed. Recently, new imaging tools allow analysis of flow dynamics and wall stability have become available. It seems that they might provide additional data for better risk profiling. In this study we present a new imaging tool for analysis of flow dynamics, which calculates fluid velocity in an aneurysm (Phillips Electronics, N.V.). It may identify regions with high flow and calculate flow reduction after stenting of aneurysms. Contrast is injected with a stable injection speed of 2 mL/sec for 3 sec. Two clinical cases are illustrated. Velocity in aneurysms and areas of instability can be identified and calculated during angiography in real-time. After stenting and flow diverter deployment flow reduction in the internal carotid aneurysm was reduced by 60% and there was a reduction of about 65% in the posterior cerebral artery in the second case we are reporting. The dynamic flow software calculates the flow profile in the aneurysm immediately after contrast injection. It is a real-time, patient specific tool taking into account systole, diastole and flexibility of the vasculature. These factors are an improvement as compared to current models of computational flow dynamics. We think it is a highly efficient, user friendly tool. Further clinical studies are on their way. PMID:28839527

  18. 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.

  19. Predicting breast-feeding attrition: adapting the breast-feeding attrition prediction tool.

    PubMed

    Gill, Sara L; Reifsnider, Elizabeth; Lucke, Joseph F; Mann, Angela R

    2007-01-01

    Current breast-feeding rates fall short of the recommendations set forth in Health People 2010. The Breast-feeding Attrition Prediction Tool (BAPT), administered in the postpartum period, has been useful in predicting breast-feeding attrition. However, assessing a woman's intention to breast-feed prior to birth would identify women at risk for breast-feeding attrition. The purpose of this study was to describe a revised BAPT, administered antepartally that measures intention to breast-feed. The BAPT, comprising 94 items on a 6-point Likert-type scale, was translated into Spanish and back-translated for accuracy. The BAPT was then revised by reducing the number of items to 35 (32 were used for analysis) and contracting the 6-point scale to 3 categories. A Bayesian item response model provided the psychometric properties of the revised BAPT. The revised BAPT was completed by 143 Mexican American pregnant women. Items, some reverse scored, were recoded as "agree" versus "disagree." Item analyses indicated a wide range of item discriminabilities, with most items being useful measures of intention to breast-feed. Person analyses provided scores for intention to breast-feed. A simpler scoring system was devised for applications. The revised BAPT shows promise as a measure of intention to breast-feed. The scoring system also indicates which women may need additional interventions to promote breast-feeding.

  20. 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

  1. 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.

  2. Velocity prediction errors related to flow model calibration uncertainty

    SciTech Connect

    Stephenson, D.E. ); Duffield, G.M.; Buss, D.R. )

    1990-01-01

    At the Savannah River Site (SRS), a United States Department of Energy facility in South Carolina, a three-dimensional, steady-state numerical model has been developed for a four aquifer, three aquitard groundwater flow system. This model has been used for numerous predictive simulation applications at SRS, and since the initial calibration, the model has been refined several times. Originally, calibration of the model was accomplished using a nonlinear least-squares inverse technique for a set of 50 water-level calibration targets non-uniformly distributed in the four aquifers. The estimated hydraulic properties from this calibration generally showed reasonable agreement with values estimated from field tests. Subsequent model refinements and application of this model to field problems have shown that uncertainties in the model parameterization become much more apparent in the prediction of the velocity field than in the simulation of the distribution of hydraulic heads. The combined use of three types of information (hydraulic head distributions, geologic framework models, and velocity field monitoring) provide valuable calibration data for flow modeling investigations; however, calibration of a flow model typically relies upon measured water levels. For a given set of water-level calibration targets, the uncertainties associated with imperfect knowledge of physical system parameters or groundwater velocities may not be discernable in the calibrated hydraulic head distribution. In this paper, modeling results from studies at SRS illustrate examples of model inadequacy resulting from calibrating only on observed water levels, and the effects of these inadequacies on velocity field prediction are discussed. 14 refs., 6 figs.

  3. IPMP 2013 - A comprehensive data analysis tool for predictive microbiology

    USDA-ARS?s Scientific Manuscript database

    Predictive microbiology is an area of applied research in food science that uses mathematical models to predict the changes in the population of pathogenic or spoilage microorganisms in foods undergoing complex environmental changes during processing, transportation, distribution, and storage. It f...

  4. Tool Life Prediction for Ceramic Tools in Intermittent Turning of Hardened Steel Based on Damage Evolution Model

    NASA Astrophysics Data System (ADS)

    Cui, Xiaobin; Zhao, Jun; Zhou, Yonghui; Zheng, Guangming

    2011-07-01

    Al2O3-based ceramic is one of the most widely used materials for tools employed in hardened steel turning applications due to its high hardness, wear resistance, heat resistance and chemical stability. The objective of this work is to predict the lives of Al2O3-(W, Ti)C ceramic tools in intermittent turning of hardened AISI 1045 steel by means of damage evolution model taking into account the mechanical loading and thermal effect in the cutting process. A damage evolution model analyzing the RVE with uniformly distributed interacting cracks is constructed based on micromechanics. The calculated results of the proposed damage evolution model are compared with the lives of two kinds of Al2O3-(W, Ti)C ceramic tools obtained through experiments. It is found that the proposed model can be used to predict the lives of the ceramic cutting tools in intermittent turning operation.

  5. 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.

  6. Prediction and Archival Tools for Asteroid Radar Observations

    NASA Astrophysics Data System (ADS)

    Miles, Brittany; Margot, J.

    2014-01-01

    The Earth-based radar facilities at Arecibo and Goldstone have provided very powerful tools for characterizing the trajectories and physical properties of asteroids. This is especially important for near-Earth asteroids (NEAs) (perihelion distance < 1.3 AU) which are important in the context of hazard mitigation and resource utilization. Over 10,000 NEAs have been identified (https://www.iau.org/public/themes/neo/nea/) and over 400 have been detected with radar (http://radarastronomy.org). Both of these numbers are growing rapidly, necessitating efficient tools for data archival and observation planning. The asteroid radar database hosted at radarastronomy.org keeps track of all radar detections, documents NEA physical properties, and provides NEA observability conditions. We have integrated a number of tools with the database to facilitate recordkeeping and observation planning. First, a geometry finder program allows us to identify the optimal times to observe specific NEAs and to compute rise-transit-set windows. Second, a python-based signal-to-noise (SNR) tool allows us to compute SNR values for both Arecibo and Goldstone observations. SNR is dependent on asteroid properties (size, spin, reflectivity), geocentric distance, and telescope parameters. Finally, python-based graphical tools help visualize the history of asteroid detections.

  7. Flow cytometry as a tool to quantify oyster defence mechanisms.

    PubMed

    Goedken, Michael; De Guise, Sylvain

    2004-04-01

    The fast growing oyster aquaculture industry is greatly hindered by Perkinsus marinus and Haplosporidium nelsoni which can kill up to 80% of the production. The relationship between parasites and oyster defence mechanisms is unclear. Two defence mechanisms of the Eastern Oyster (Crassostrea virginica) were quantified at the single cell level utilising flow cytometry. Phagocytosis was measured using fluorescent beads. Respiratory burst activity was quantified as the H2O2-specific increase in dichlorofluorescein-associated fluorescence upon stimulation. These two assays distinguished three populations of haemocytes (granulocytes, hyalinocytes and intermediate cells) with unique functional characteristics. Granulocytes were most active at phagocytosis and H2O2 production while hyalinocytes were relatively inactive. The intermediate cells had moderate phagocytic and respiratory burst activity. Flow cytometry can rapidly, accurately and directly quantify the morphology and function of a large number of individual cells, and will lead to a better understanding of the bivalve immune system.

  8. Lung cancer risk prediction: a tool for early detection.

    PubMed

    Cassidy, Adrian; Duffy, Stephen W; Myles, Jonathan P; Liloglou, Triantafillos; Field, John K

    2007-01-01

    Although 45% of men and 39% of women will be diagnosed with cancer in their lifetime, it is difficult to predict which individuals will be affected. For some cancers, substantial progress in individual risk estimation has already been made. However, relatively few models have been developed to predict lung cancer risk beyond effects of age and smoking. This paper reviews published models for lung cancer risk prediction, discusses their potential contribution to clinical and research settings and suggests improvements to the risk modeling strategy for lung cancer. The sensitivity and specificity of existing cancer risk models is less than optimal. Improvement in individual risk prediction is important for selection of individuals for prevention or early detection interventions. In addition to smoking, factors related to occupational exposure, personal medical history and family history of cancer can add to the predictive power. A good risk prediction model is one that can identify a small fraction of the population in which a large proportion of the disease cases will occur. In the future, genetic and other biological markers are likely to be useful, although they will require rigorous evaluation. Validation is essential to establish the predictive effect and for ongoing monitoring of the model's continued relevance.

  9. Advances and computational tools towards predictable design in biological engineering.

    PubMed

    Pasotti, Lorenzo; Zucca, Susanna

    2014-01-01

    The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

  10. Advances and Computational Tools towards Predictable Design in Biological Engineering

    PubMed Central

    2014-01-01

    The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated. PMID:25161694

  11. 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

  12. Are transit times key process-based tools for regional classification and prediction in ungauged basins?

    NASA Astrophysics Data System (ADS)

    Tetzlaff, D.; Soulsby, C.; Hrachowitz, M.; Speed, M.

    2009-04-01

    In recent years, transit times (TTs) have been increasingly explored as a process-based tools for conceptualising hydrological processes in an integrated manner at a range of scales. Traditionally the identification of the appropriate transit time distribution (TTD) for a hydrological system (e.g. hillslope or catchment), and the derivation of metrics such as the mean transit time (MTT) have required quantitative assessment of input-output relationships for conservative tracers using lumped parameter models. Such work has allowed the main landscape controls on TTs to be identified and facilitated the prediction of MTT in ungauged basins in particular geomorphic provinces. This has shown TT to be a useful diagnostic index of similarity that can be valuable in process-based catchment classification. In this contribution, we used well-constrained MTT estimates (with uncertainty) from 32 experimental catchments (1 to 250km2 in area) with contrasting geologic, topographic, pedologic and climatic characteristics in Scotland. The MTT was highly variable ranging from 30 days to ca. 1200 days for individual catchments. Moreover, MTT was also found to be closely correlated with key hydrometric design statistics such as the Q95, Q5, Mean Annual Flood (MAF) and the slope of the hydrograph recession curve. Analysis of the TT estimates, in conjunction with GIS-based quantitative assessment of key landscape controls, showed that MTT could be predicted to within 25% for ungauged basins from catchment soil cover, drainage density and topographic wetness index. For ungauged basins it was found that the hydrometric design statistics (Q95, Q5, MAF and the recession slope) could be more simply and accurately forecasted from MTT predictions than a single set of catchment characteristics. We demonstrate that TTs - predicted from mapped landscape characteristics - are useful integrating diagnostic metrics for regional classification, prediction and process assessment in ungauged montane

  13. 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.

  14. SSFinder: high throughput CRISPR-Cas target sites prediction tool.

    PubMed

    Upadhyay, Santosh Kumar; Sharma, Shailesh

    2014-01-01

    Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) system facilitates targeted genome editing in organisms. Despite high demand of this system, finding a reliable tool for the determination of specific target sites in large genomic data remained challenging. Here, we report SSFinder, a python script to perform high throughput detection of specific target sites in large nucleotide datasets. The SSFinder is a user-friendly tool, compatible with Windows, Mac OS, and Linux operating systems, and freely available online.

  15. Influence of FSW pin tool geometry on plastic flow of AA7075 T651

    NASA Astrophysics Data System (ADS)

    Lertora, Enrico; Mandolfino, Chiara; Gambaro, Carla

    2016-10-01

    In this paper the behaviour of the plastic flow during Friction Stir Welding of AA7075 T651 plates, realized with different shaped tools, has been investigated. In particular, the influence of the shape of three tools was studied using copper strips placed along the welds. After welding, radiography and metallurgical analysis were used in order to investigate the marker movement and its fragmentation.

  16. Current tools for prediction of arteriovenous fistula outcomes

    PubMed Central

    McGrogan, Damian G.; Maxwell, Alexander P.; Khawaja, Aurang Z.; Inston, Nicholas G.

    2015-01-01

    It remains challenging to accurately predict whether an individual arteriovenous fistula (AVF) will mature and be useable for haemodialysis vascular access. Current best practice involves the use of routine clinical assessment and ultrasonography complemented by selective venography and magnetic resonance imaging. The purpose of this literature review is to describe current practices in relation to pre-operative assessment prior to AVF formation and highlight potential areas for future research to improve the clinical prediction of AVF outcomes. PMID:26034589

  17. Hansen solubility parameter as a tool to predict cocrystal formation.

    PubMed

    Mohammad, Mohammad Amin; Alhalaweh, Amjad; Velaga, Sitaram P

    2011-04-04

    The objective of this study was to investigate whether the miscibility of a drug and coformer, as predicted by Hansen solubility parameters (HSPs), can indicate cocrystal formation and guide cocrystal screening. It was also our aim to evaluate various HSPs-based approaches in miscibility prediction. HSPs for indomethacin (the model drug) and over thirty coformers were calculated according to the group contribution method. Differences in the HSPs between indomethacin and each coformer were then calculated using three established approaches, and the miscibility was predicted. Subsequently, differential scanning calorimetry was used to investigate the experimental miscibility and cocrystal formation. The formation of cocrystals was also verified using liquid-assisted grinding. All except one of the drug-coformers that were predicted to be miscible were confirmed experimentally as miscible. All tested theoretical approaches were in agreement in predicting miscibility. All systems that formed cocrystals were miscible. Remarkably, two new cocrystals of indomethacin were discovered in this study. Though it may be necessary to test this approach in a wide range of different coformer and drug compound types for accurate generalizations, the trends with tested systems were clear and suggest that the drug and coformer should be miscible for cocrystal formation. Thus, predicting the miscibility of cocrystal components using solubility parameters can guide the selection of potential coformers prior to exhaustive cocrystal screening work.

  18. Engineering Property Prediction Tools for Tailored Polymer Composite Structures (49465)

    SciTech Connect

    Nguyen, Ba Nghiep; Kunc, Vlastimil

    2009-12-29

    Process and constitutive models as well as characterization tools and testing methods were developed to determine stress-strain responses, damage development, strengths and creep of long-fiber thermoplastics (LFTs). The developed models were implemented in Moldflow and ABAQUS and have been validated against LFT data obtained experimentally.

  19. 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.

  20. Continuous flow chemistry: a discovery tool for new chemical reactivity patterns.

    PubMed

    Hartwig, Jan; Metternich, Jan B; Nikbin, Nikzad; Kirschning, Andreas; Ley, Steven V

    2014-06-14

    Continuous flow chemistry as a process intensification tool is well known. However, its ability to enable chemists to perform reactions which are not possible in batch is less well studied or understood. Here we present an example, where a new reactivity pattern and extended reaction scope has been achieved by transferring a reaction from batch mode to flow. This new reactivity can be explained by suppressing back mixing and precise control of temperature in a flow reactor set up.

  1. IHT: Tools for Computing Insolation Absorption by Particle Laden Flows

    SciTech Connect

    Grout, R. W.

    2013-10-01

    This report describes IHT, a toolkit for computing radiative heat exchange between particles. Well suited for insolation absorption computations, it is also has potential applications in combustion (sooting flames), biomass gasification processes and similar processes. The algorithm is based on the 'Photon Monte Carlo' approach and implemented in a library that can be interfaced with a variety of computational fluid dynamics codes to analyze radiative heat transfer in particle-laden flows. The emphasis in this report is on the data structures and organization of IHT for developers seeking to use the IHT toolkit to add Photon Monte Carlo capabilities to their own codes.

  2. Visualization tools for vorticity transport analysis in incompressible flow.

    PubMed

    Sadlo, Filip; Peikert, Ronald; Sick, Mirjam

    2006-01-01

    Vortices are undesirable in many applications while indispensable in others. It is therefore of common interest to understand their mechanisms of creation. This paper aims at analyzing the transport of vorticity inside incompressible flow. The analysis is based on the vorticity equation and is performed along pathlines which are typically started in upstream direction from vortex regions. Different methods for the quantitative and explorative analysis of vorticity transport are presented and applied to CFD simulations of water turbines. Simulation quality is accounted for by including the errors of meshing and convergence into analysis and visualization. The obtained results are discussed and interpretations with respect to engineering questions are given.

  3. 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.

  4. 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.

  5. Tool wear predictive model based on least squares support vector machines

    NASA Astrophysics Data System (ADS)

    Shi, Dongfeng; Gindy, Nabil N.

    2007-05-01

    The development of tool wear monitoring system for machining processes has been well recognised in industry due to the ever-increased demand for product quality and productivity improvement. This paper presents a new tool wear predictive model by combination of least squares support vector machines (LS-SVM) and principal component analysis (PCA) technique. The corresponding tool wear monitoring system is developed based on the platform of PXI and LabVIEW. PCA is firstly proposed to extract features from multiple sensory signals acquired from machining processes. Then, LS-SVM-based tool wear prediction model is constructed by learning correlation between extracted features and actual tool wear. The effectiveness of proposed predictive model and corresponding tool wear monitoring system is demonstrated by experimental results from broaching trials.

  6. A systematic review of screening tools for predicting the development of dementia.

    PubMed

    Lischka, Andrea R; Mendelsohn, Marissa; Overend, Tom; Forbes, Dorothy

    2012-09-01

    Early detection of dementia is essential to guide front-line health care practitioners in further clinical evaluations and treatments. There is a paucity of literature assessing the effectiveness of screening tools to predict the development of dementia, thus we conducted a systematic review to fill this gap. The purpose of the systematic review was to make recommendations to health care practitioners on which screening tool best predicts the development of dementia and is most feasible in the primary care setting. Ten databases were searched for relevant articles, yielding 751 papers. Of these, 12 met relevance criteria for inclusion. Screening tools were assessed for test accuracy, cognitive domain coverage, predictive ability, and feasibility. Four screening tools were recommended. Addenbrooke's Cognitive Examination (ACE) was considered to be the ideal tool. A revised version of this tool is now used in clinical practice but the psychometric properties of the ACE-R remain to be established.

  7. The Plastic Flow Field in the Vicinity of the Pin-Tool During Friction Stir Welding

    NASA Technical Reports Server (NTRS)

    Bernstein, E. L.; Nunes, A. C., Jr.

    2000-01-01

    The plastic flow field in the vicinity of the pin-tool during Friction Stir Welding (FSW) needs to be understood if a theoretical understanding of the process is to be attained. The structure of welds does not exhibit the flow field itself, but consists in a residue of displacements left by the plastic flow field. The residue requires analysis to extract from it the instantaneous flow field around the pin-tool. A simplified merry-go-round model makes sense of some tracer experiments reported in the literature. A quantitative comparison is made of the displacements of copper wire markers with displacements computed from a hypothetical plastic flow field. The hypothetical plastic flow field consists in a circular rotation field about a translating pin tool with angular velocity varying with radius from the pin centerline. A sharply localized rotational field comprising slip on a surface around the tool agreed better with observations than a distributed slip field occupying a substantial volume around the tool. Both the tracer and the wire displacements support the "rotating plug" model, originally invoked or thermal reasons, of the FSW process.

  8. A validated predictive model of coronary fractional flow reserve

    PubMed Central

    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

  9. Flow and transport simulation models for prediction of chlorine contact tank flow-through curves.

    PubMed

    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.

  10. Emerging Tools to Estimate and to Predict Exposures to ...

    EPA Pesticide Factsheets

    The timely assessment of the human and ecological risk posed by thousands of existing and emerging commercial chemicals is a critical challenge facing EPA in its mission to protect public health and the environment The US EPA has been conducting research to enhance methods used to estimate and forecast exposures for tens of thousands of chemicals. This research is aimed at both assessing risks and supporting life cycle analysis, by developing new models and tools for high throughput exposure screening and prioritization, as well as databases that support these and other tools, especially regarding consumer products. The models and data address usage, and take advantage of quantitative structural activity relationships (QSARs) for both inherent chemical properties and function (why the chemical is a product ingredient). To make them more useful and widely available, the new tools, data and models are designed to be: • Flexible • Intraoperative • Modular (useful to more than one, stand-alone application) • Open (publicly available software) Presented at the Society for Risk Analysis Forum: Risk Governance for Key Enabling Technologies, Venice, Italy, March 1-3, 2017

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

    NASA Technical Reports Server (NTRS)

    Clark, William S.; Hall, Kenneth C.

    1994-01-01

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

  12. Comparison Between Predicted and Experimentally Measured Flow Fields at the Exit of the SSME HPFTP Impeller

    NASA Technical Reports Server (NTRS)

    Bache, George

    1993-01-01

    Validation of CFD codes is a critical first step in the process of developing CFD design capability. The MSFC Pump Technology Team has recognized the importance of validation and has thus funded several experimental programs designed to obtain CFD quality validation data. The first data set to become available is for the SSME High Pressure Fuel Turbopump Impeller. LDV Data was taken at the impeller inlet (to obtain a reliable inlet boundary condition) and three radial positions at the impeller discharge. Our CFD code, TASCflow, is used within the Propulsion and Commercial Pump industry as a tool for pump design. The objective of this work, therefore, is to further validate TASCflow for application in pump design. TASCflow was used to predict flow at the impeller discharge for flowrates of 80, 100 and 115 percent of design flow. Comparison to data has been made with encouraging results.

  13. A new tool for predicting drought: An application over India

    PubMed Central

    Kulkarni, M. N.

    2015-01-01

    This is the first attempt of application of atmospheric electricity for rainfall prediction. The atmospheric electrical columnar resistance based on the model calculations involving satellite data has been proposed as a new predictor. It is physically sound, simple to calculate and not probabilistic like the standardized precipitation index. After applying this new predictor over India, it has been found that the data solely over the Bay of Bengal (BB) are sufficient to predict a drought over the country as a whole. Finally, two independent new methods to predict drought conditions and a preliminary forecast of the same for India for year 2014 have been given. Unlike the existing drought prediction techniques, the identification of drought conditions in a pre-drought year during 1981–1990 and 2001–2013 over India has been achieved 100% successfully using the suggested new methods. The association between rainfall and this new predictor has also been found on the sub-regional scale. So, the present predictor is expected to get global application and application in climate models. From the analysis, generally, a long period rising trend in aerosol concentration over the BB causes weak monsoon over India but that for a short time i.e. in pre-monsoon period strengthens it. PMID:25567244

  14. A comparative study of S/MAR prediction tools

    PubMed Central

    Evans, Kenneth; Ott, Sascha; Hansen, Annika; Koentges, Georgy; Wernisch, Lorenz

    2007-01-01

    Background S/MARs are regions of the DNA that are attached to the nuclear matrix. These regions are known to affect substantially the expression of genes. The computer prediction of S/MARs is a highly significant task which could contribute to our understanding of chromatin organisation in eukaryotic cells, the number and distribution of boundary elements, and the understanding of gene regulation in eukaryotic cells. However, while a number of S/MAR predictors have been proposed, their accuracy has so far not come under scrutiny. Results We have selected S/MARs with sufficient experimental evidence and used these to evaluate existing methods of S/MAR prediction. Our main results are: 1.) all existing methods have little predictive power, 2.) a simple rule based on AT-percentage is generally competitive with other methods, 3.) in practice, the different methods will usually identify different sub-sequences as S/MARs, 4.) more research on the H-Rule would be valuable. Conclusion A new insight is needed to design a method which will predict S/MARs well. Our data, including the control data, has been deposited as additional material and this may help later researchers test new predictors. PMID:17335576

  15. A new tool for predicting drought: an application over India.

    PubMed

    Kulkarni, M N

    2015-01-08

    This is the first attempt of application of atmospheric electricity for rainfall prediction. The atmospheric electrical columnar resistance based on the model calculations involving satellite data has been proposed as a new predictor. It is physically sound, simple to calculate and not probabilistic like the standardized precipitation index. After applying this new predictor over India, it has been found that the data solely over the Bay of Bengal (BB) are sufficient to predict a drought over the country as a whole. Finally, two independent new methods to predict drought conditions and a preliminary forecast of the same for India for year 2014 have been given. Unlike the existing drought prediction techniques, the identification of drought conditions in a pre-drought year during 1981-1990 and 2001-2013 over India has been achieved 100% successfully using the suggested new methods. The association between rainfall and this new predictor has also been found on the sub-regional scale. So, the present predictor is expected to get global application and application in climate models. From the analysis, generally, a long period rising trend in aerosol concentration over the BB causes weak monsoon over India but that for a short time i.e. in pre-monsoon period strengthens it.

  16. Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

    PubMed

    El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

    2015-04-01

    This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

  17. Risk tools for the prediction of violence: 'VRAG, HCR-20, PCL-R'.

    PubMed

    Jaber, F S; Mahmoud, K F

    2015-03-01

    Many instruments have been introduced as measures of violence risk prediction. Studies on risk assessment displayed two major approaches - clinical risk evaluation and actuarial measures - and three tools were mostly used: (1) Violence Risk Appraisal Guide, (2) Historical-Clinical-Risk-20 item scale and (3) Psychopathy Checklist-Revised. Although these tools are commonly used in clinical practice, they differ in their uses, benefits and limitations, and their ability to predict future violence. Subsequently, this paper aim to provide the readers an in-depth description that specifies these aspects, as well as a comparison of these tools in order to help readers decide which tool to use.

  18. Development of Antimicrobial Peptide Prediction Tool for Aquaculture Industries.

    PubMed

    Gautam, Aditi; Sharma, Asuda; Jaiswal, Sarika; Fatma, Samar; Arora, Vasu; Iquebal, M A; Nandi, S; Sundaray, J K; Jayasankar, P; Rai, Anil; Kumar, Dinesh

    2016-09-01

    Microbial diseases in fish, plant, animal and human are rising constantly; thus, discovery of their antidote is imperative. The use of antibiotic in aquaculture further compounds the problem by development of resistance and consequent consumer health risk by bio-magnification. Antimicrobial peptides (AMPs) have been highly promising as natural alternative to chemical antibiotics. Though AMPs are molecules of innate immune defense of all advance eukaryotic organisms, fish being heavily dependent on their innate immune defense has been a good source of AMPs with much wider applicability. Machine learning-based prediction method using wet laboratory-validated fish AMP can accelerate the AMP discovery using available fish genomic and proteomic data. Earlier AMP prediction servers are based on multi-phyla/species data, and we report here the world's first AMP prediction server in fishes. It is freely accessible at http://webapp.cabgrid.res.in/fishamp/ . A total of 151 AMPs related to fish collected from various databases and published literature were taken for this study. For model development and prediction, N-terminus residues, C-terminus residues and full sequences were considered. Best models were with kernels polynomial-2, linear and radial basis function with accuracy of 97, 99 and 97 %, respectively. We found that performance of support vector machine-based models is superior to artificial neural network. This in silico approach can drastically reduce the time and cost of AMP discovery. This accelerated discovery of lead AMP molecules having potential wider applications in diverse area like fish and human health as substitute of antibiotics, immunomodulator, antitumor, vaccine adjuvant and inactivator, and also for packaged food can be of much importance for industries.

  19. A tool for the prediction of structures of complex sugars.

    PubMed

    Xia, Junchao; Margulis, Claudio

    2008-12-01

    In two recent back to back articles(Xia et al., J Chem Theory Comput 3:1620-1628 and 1629-1643, 2007a, b) we have started to address the problem of complex oligosaccharide conformation and folding. The scheme previously presented was based on exhaustive searches in configuration space in conjunction with Nuclear Overhauser Effect (NOE) calculations and the use of a complex rotameric library that takes branching into account. NOEs are extremely useful for structural determination but only provide information about short range interactions and ordering. Instead, the measurement of residual dipolar couplings (RDC), yields information about molecular ordering or folding that is long range in nature. In this article we show the results obtained by incorporation RDC calculations into our prediction scheme. Using this new approach we are able to accurately predict the structure of six human milk sugars: LNF-1, LND-1, LNF-2, LNF-3, LNnT and LNT. Our exhaustive search in dihedral configuration space combined with RDC and NOE calculations allows for highly accurate structural predictions that, because of the non-ergodic nature of these molecules on a time scale compatible with molecular dynamics simulations, are extremely hard to obtain otherwise (Almond et al., Biochemistry 43:5853-5863, 2004). Molecular dynamics simulations in explicit solvent using as initial configurations the structures predicted by our algorithm show that the histo-blood group epitopes in these sugars are relatively rigid and that the whole family of oligosaccharides derives its conformational variability almost exclusively from their common linkage (beta-D: -GlcNAc-(1-->3)-beta-D: -Gal) which can exist in two distinct conformational states. A population analysis based on the conformational variability of this flexible glycosidic link indicates that the relative population of the two distinct states varies for different human milk oligosaccharides.

  20. Neural networks as tools for predicting materials properties

    SciTech Connect

    Sumpter, B.G.; Noid, D.W.

    1995-12-31

    Materials science is of fundamental significance to science and technology because our industrial base and society depend upon our ability to develop advanced materials. Materials and materials processing cuts across almost every sector of industry. The key in all of these areas is the ability to rapidly screen possible designs which will have significant impact. However up to now materials design and processing have been to a large extent empirical sciences. In addition we are still unable to design new alloys and polymers to meet application specific requirements. Being able to do so quickly and at minimum cost would provide an incredible advantage. Obviously, the ability to predict physical, chemical, or mechanical properties of compounds prior to their synthesis is of great technological value in optimizing their design, processing, or recycling. In addition, in order to realize the ultimate goal of materials by computational design, the reverse problem, prediction of chemical structure based on desired properties, has to be resolved. Research at ORNL has lead to the development of a novel computational paradigm (coupling computational neural networks with graph theory, genetic algorithms, wavelet theory, fuzzy logic, molecular dynamics, and quantum chemistry) capable of performing accurate computational synthesis (both predictions of properties or the design of compounds that have specified performance criteria). The computational paradigm represents a hybrid of a number of emerging technologies and has proven to work very well for test compounds ranging from small organic molecules to polymeric materials. Fundamental to the method is the neural network-based formulation of the correlations between structure and properties. The advantages of this method is in its ease of use, speed, accuracy, and that it can be used to predict both properties from structure, and also structure from properties.

  1. Concepts and tools for predictive modeling of microbial dynamics.

    PubMed

    Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

    2004-09-01

    Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

  2. Prediction of boiling points of organic compounds by QSPR tools.

    PubMed

    Dai, Yi-min; Zhu, Zhi-ping; Cao, Zhong; Zhang, Yue-fei; Zeng, Ju-lan; Li, Xun

    2013-07-01

    The novel electro-negativity topological descriptors of YC, WC were derived from molecular structure by equilibrium electro-negativity of atom and relative bond length of molecule. The quantitative structure-property relationships (QSPR) between descriptors of YC, WC as well as path number parameter P3 and the normal boiling points of 80 alkanes, 65 unsaturated hydrocarbons and 70 alcohols were obtained separately. The high-quality prediction models were evidenced by coefficient of determination (R(2)), the standard error (S), average absolute errors (AAE) and predictive parameters (Qext(2),RCV(2),Rm(2)). According to the regression equations, the influences of the length of carbon backbone, the size, the degree of branching of a molecule and the role of functional groups on the normal boiling point were analyzed. Comparison results with reference models demonstrated that novel topological descriptors based on the equilibrium electro-negativity of atom and the relative bond length were useful molecular descriptors for predicting the normal boiling points of organic compounds.

  3. Can Nutritional Assessment Tools Predict Response to Nutritional Therapy?

    PubMed

    Patel, Chirag; Omer, Endashaw; Diamond, Sarah J; McClave, Stephen A

    2016-04-01

    Traditional tools and scoring systems for nutritional assessment have focused solely on parameters of poor nutritional status in the past, in an effort to define the elusive concept of malnutrition. Such tools fail to account for the contribution of disease severity to overall nutritional risk. High nutritional risk, caused by either deterioration of nutritional status or greater disease severity (or a combination of both factors), puts the patient in a metabolic stress state characterized by adverse outcome and increased complications. Newer scoring systems for determining nutritional risk, such as the Nutric Score and the Nutritional Risk Score-2002 have created a paradigm shift connecting assessment and treatment with quality outcome measures of success. Clinicians now have the opportunity to identify high risk patients through their initial assessment, provide adequate or sufficient nutrition therapy, and expect improved patient outcomes as a result. These concepts are supported by observational and prospective interventional trials. Greater clinical experience and refinement in these scoring systems are needed in the future to optimize patient response to nutrition therapy.

  4. Theory, methods and tools for determining environmental flows for riparian vegetation: Riparian vegetation-flow response guilds

    USGS Publications Warehouse

    Merritt, D.M.; Scott, M.L.; Leroy, Poff N.; Auble, G.T.; Lytle, D.A.

    2010-01-01

    Riparian vegetation composition, structure and abundance are governed to a large degree by river flow regime and flow-mediated fluvial processes. Streamflow regime exerts selective pressures on riparian vegetation, resulting in adaptations (trait syndromes) to specific flow attributes. Widespread modification of flow regimes by humans has resulted in extensive alteration of riparian vegetation communities. Some of the negative effects of altered flow regimes on vegetation may be reversed by restoring components of the natural flow regime. 2. Models have been developed that quantitatively relate components of the flow regime to attributes of riparian vegetation at the individual, population and community levels. Predictive models range from simple statistical relationships, to more complex stochastic matrix population models and dynamic simulation models. Of the dozens of predictive models reviewed here, most treat one or a few species, have many simplifying assumptions such as stable channel form, and do not specify the time-scale of response. In many cases, these models are very effective in developing alternative streamflow management plans for specific river reaches or segments but are not directly transferable to other rivers or other regions. 3. A primary goal in riparian ecology is to develop general frameworks for prediction of vegetation response to changing environmental conditions. The development of riparian vegetation-flow response guilds offers a framework for transferring information from rivers where flow standards have been developed to maintain desirable vegetation attributes, to rivers with little or no existing information. 4. We propose to organise riparian plants into non-phylogenetic groupings of species with shared traits that are related to components of hydrologic regime: life history, reproductive strategy, morphology, adaptations to fluvial disturbance and adaptations to water availability. Plants from any river or region may be grouped

  5. Advanced Flow Control as a Management Tool in the National Airspace System

    NASA Technical Reports Server (NTRS)

    Wugalter, S.

    1974-01-01

    Advanced Flow Control is closely related to Air Traffic Control. Air Traffic Control is the business of the Federal Aviation Administration. To formulate an understanding of advanced flow control and its use as a management tool in the National Airspace System, it becomes necessary to speak somewhat of air traffic control, the role of FAA, and their relationship to advanced flow control. Also, this should dispell forever, any notion that advanced flow control is the inspirational master valve scheme to be used on the Alaskan Oil Pipeline.

  6. 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.

  7. 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.

  8. PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models.

    PubMed

    Ford, Matthew D; Nikolov, Hristo N; Milner, Jaques S; Lownie, Stephen P; Demont, Edwin M; Kalata, Wojciech; Loth, Francis; Holdsworth, David W; Steinman, David A

    2008-04-01

    Computational fluid dynamics (CFD) modeling of nominally patient-specific cerebral aneurysms is increasingly being used as a research tool to further understand the development, prognosis, and treatment of brain aneurysms. We have previously developed virtual angiography to indirectly validate CFD-predicted gross flow dynamics against the routinely acquired digital subtraction angiograms. Toward a more direct validation, here we compare detailed, CFD-predicted velocity fields against those measured using particle imaging velocimetry (PIV). Two anatomically realistic flow-through phantoms, one a giant internal carotid artery (ICA) aneurysm and the other a basilar artery (BA) tip aneurysm, were constructed of a clear silicone elastomer. The phantoms were placed within a computer-controlled flow loop, programed with representative flow rate waveforms. PIV images were collected on several anterior-posterior (AP) and lateral (LAT) planes. CFD simulations were then carried out using a well-validated, in-house solver, based on micro-CT reconstructions of the geometries of the flow-through phantoms and inlet/outlet boundary conditions derived from flow rates measured during the PIV experiments. PIV and CFD results from the central AP plane of the ICA aneurysm showed a large stable vortex throughout the cardiac cycle. Complex vortex dynamics, captured by PIV and CFD, persisted throughout the cardiac cycle on the central LAT plane. Velocity vector fields showed good overall agreement. For the BA, aneurysm agreement was more compelling, with both PIV and CFD similarly resolving the dynamics of counter-rotating vortices on both AP and LAT planes. Despite the imposition of periodic flow boundary conditions for the CFD simulations, cycle-to-cycle fluctuations were evident in the BA aneurysm simulations, which agreed well, in terms of both amplitudes and spatial distributions, with cycle-to-cycle fluctuations measured by PIV in the same geometry. The overall good agreement

  9. Aeration efficiency over stepped cascades: better predictions from flow regimes.

    PubMed

    Khdhiri, Hatem; Potier, Olivier; Leclerc, Jean-Pierre

    2014-05-15

    Stepped cascades are recognized as high potential air-water gas exchangers. In natural rivers, these structures enhance oxygen transfer to water by creating turbulence at interface with increasing air entrainment in water and air-water surface exchange. Stepped cascades could be really useful to improve the natural self-purification process by providing oxygen to aerobic micro-organisms. The aeration performance of these structures depends on several operating and geometrical parameters. In the literature, several empirical correlations for aeration efficiency prediction on stepped cascades exist. Most of these correlations are only applicable for operating and geometrical parameters in the range of which they have been developed. In this paper, 398 experimental sets of data (from our experiments and collected from literature) were used to develop a correlation for aeration prediction over stepped cascades derived from dimensional analysis and parameterized for each individual flow regime in order to consider change in flow regime effect on oxygen transfer. This new correlation allowed calculating the whole set of data obtained for cascades with steps heights between 0.05 m and 0.254 m, cascade total height between 0.25 m and 2.5 m, for discharges per unit of width ranging from 0.28 10(-3) m(2)/s to 600 10(-3) m(2)/s and for cascade steps number between 3 and 25. In these ranges of parameters, standard deviation for aeration efficiency estimation was found to be less than 17%. Finally, advices were proposed to help and improve the structure design in order to improve aeration. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    USGS Publications Warehouse

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

    2001-01-01

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

  11. Predictive Value of Retrobulbar Blood Flow Velocities in Glaucoma Suspects

    PubMed Central

    Calvo, Pilar; Ferreras, Antonio; Polo, Vicente; Güerri, Noemi; Seral, Pilar; Fuertes-Lazaro, Isabel; Pablo, Luis E.

    2012-01-01

    Purpose. To determine whether retrobulbar blood flow (RBF) velocities are predictive of conversion to glaucoma. Methods. A total of 262 glaucoma suspects were prospectively selected. Participants had normal visual field, increased intraocular pressure, and glaucomatous optic disc appearance at baseline. Topographic analysis of the optic nerve head was performed using a confocal laser scanning ophthalmoscope and the blood flow velocity of retrobulbar vessels was measured by color Doppler imaging. Conversion to glaucoma was assessed according to the changes in the color-coded Moorfields Regression Analysis (MRA) classification of the confocal laser scanning system during a 48-month follow-up period. Survival curves and hazard ratios (HRs) for the association between RBF parameters and conversion to glaucoma were calculated. Results. End-diastolic velocity and mean velocity in the ophthalmic artery were reduced in subjects that converted to glaucoma based on MRA (36 individuals, 13.7%), while resistivity (RI) and pulsatility indices were increased in the same vessel. Patients with RI values lower than 0.75 in the ophthalmic artery had a survival rate (MRA-converters versus nonconverters) of 93.9%, whereas individuals with RI values greater than 0.75 had a survival rate of 81.7% (HR = 3.306; P = 0.002). Conclusions. Abnormal RBF velocities measured by color Doppler ultrasound may be a risk factor for conversion to glaucoma. An RI value higher than 0.75 in the ophthalmic artery was associated with the development of glaucoma. PMID:22589447

  12. 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.

  13. Predicting cancer prognosis using interactive online tools: A systematic review and implications for cancer care providers

    PubMed Central

    Rabin, Borsika A.; Gaglio, Bridget; Sanders, Tristan; Nekhlyudov, Larissa; Dearing, James W.; Bull, Sheana; Glasgow, Russell E.; Marcus, Alfred

    2013-01-01

    Cancer prognosis is of keen interest for cancer patients, their caregivers and providers. Prognostic tools have been developed to guide patient-physician communication and decision-making. Given the proliferation of prognostic tools, it is timely to review existing online cancer prognostic tools and discuss implications for their use in clinical settings. Using a systematic approach, we searched the Internet, Medline, and consulted with experts to identify existing online prognostic tools. Each was reviewed for content and format. Twenty-two prognostic tools addressing 89 different cancers were identified. Tools primarily focused on prostate (n=11), colorectal (n=10), breast (n=8), and melanoma (n=6), though at least one tool was identified for most malignancies. The input variables for the tools included cancer characteristics (n=22), patient characteristics (n=18), and comorbidities (n=9). Effect of therapy on prognosis was included in 15 tools. The most common predicted outcome was cancer specific survival/mortality (n=17). Only a few tools (n=4) suggested patients as potential target users. A comprehensive repository of online prognostic tools was created to understand the state-of-the-art in prognostic tool availability and characteristics. Use of these tools may support communication and understanding about cancer prognosis. Dissemination, testing, refinement of existing, and development of new tools under different conditions are needed. PMID:23956026

  14. Predicting cancer prognosis using interactive online tools: a systematic review and implications for cancer care providers.

    PubMed

    Rabin, Borsika A; Gaglio, Bridget; Sanders, Tristan; Nekhlyudov, Larissa; Dearing, James W; Bull, Sheana; Glasgow, Russell E; Marcus, Alfred

    2013-10-01

    Cancer prognosis is of keen interest for patients with cancer, their caregivers, and providers. Prognostic tools have been developed to guide patient-physician communication and decision-making. Given the proliferation of prognostic tools, it is timely to review existing online cancer prognostic tools and discuss implications for their use in clinical settings. Using a systematic approach, we searched the Internet, Medline, and consulted with experts to identify existing online prognostic tools. Each was reviewed for content and format. Twenty-two prognostic tools addressing 89 different cancers were identified. Tools primarily focused on prostate (n = 11), colorectal (n = 10), breast (n = 8), and melanoma (n = 6), although at least one tool was identified for most malignancies. The input variables for the tools included cancer characteristics (n = 22), patient characteristics (n = 18), and comorbidities (n = 9). Effect of therapy on prognosis was included in 15 tools. The most common predicted outcome was cancer-specific survival/mortality (n = 17). Only a few tools (n = 4) suggested patients as potential target users. A comprehensive repository of online prognostic tools was created to understand the state-of-the-art in prognostic tool availability and characteristics. Use of these tools may support communication and understanding about cancer prognosis. Dissemination, testing, refinement of existing, and development of new tools under different conditions are needed.

  15. Reactive metabolites in early drug development: predictive in vitro tools.

    PubMed

    Pelkonen, Olavi; Pasanen, Markku; Tolonen, Ari; Koskinen, Mikko; Hakkola, Jukka; Abass, Khaled; Laine, Jaana; Hakkinen, Merja; Juvonen, Risto; Auriola, Seppo; Storvik, Markus; Huuskonen, Pasi; Rousu, Timo; Rahikkala, Maiju

    2015-01-01

    Drug metabolism can result in the formation of highly reactive metabolites that are known to play a role in toxicity resulting in a significant proportion of attrition during drug development and clinical use. Thus, the earlier such reactivity was detected, the better. This review summarizes our multi-year project, together with pertinent literature, to examine a battery of in vitro tests capable of detecting the formation of reactive metabolites. Principal prerequisites for such tests were delineated: chemicals known/not known to cause tissue injury and produce reactive metabolites, activation system (mainly human-derived), small- and large-molecular targets (small-molecular trappers, peptides, proteins), analytical techniques (mass spectrometry), and cellular toxicity biomarkers. The current status of in vitro tools to detect reactive intermediates is the following: 1. Small-molecular trapping agents such glutathione or cyanide detect the production of reactive species with high sensitivity by proper MS technique. However, it seems that also putative "negatives" give rise to corresponding adducts. 2. Results from peptide and dG (DNA targeting) trapper studies are generally in line with those of small-molecular trappers, although also important differences exist. These two trapping platforms do not overlap. 3. It is anticipated that the in vitro adduct studies could be fully interpreted only in conjunction with toxicity biomarker (such as the Nrf2 pathway) information from whole cells or tissues. However, while there are tools to characterize the chemical liability and there are correlation between individual/integrated endpoints and toxicity, there are still severe gaps in understanding the mechanisms behind the link between reactive metabolites and adverse effects.

  16. About Using Predictive Models and Tools To Assess Chemicals under TSCA

    EPA Pesticide Factsheets

    As part of EPA's effort to promote chemical safety, OPPT provides public access to predictive models and tools which can help inform the public on the hazards and risks of substances and improve chemical management decisions.

  17. Predictive Maintenance--An Effective Money Saving Tool Being Applied in Industry Today.

    ERIC Educational Resources Information Center

    Smyth, Tom

    2000-01-01

    Looks at preventive/predictive maintenance as it is used in industry. Discusses core preventive maintenance tools that must be understood to prepare students. Includes a list of websites related to the topic. (JOW)

  18. Predictive Maintenance--An Effective Money Saving Tool Being Applied in Industry Today.

    ERIC Educational Resources Information Center

    Smyth, Tom

    2000-01-01

    Looks at preventive/predictive maintenance as it is used in industry. Discusses core preventive maintenance tools that must be understood to prepare students. Includes a list of websites related to the topic. (JOW)

  19. Effect of Pin Tool Shape on Metal Flow During Friction Stir Welding

    NASA Technical Reports Server (NTRS)

    McClure, J. C.; Coronado, E.; Aloor, S.; Nowak, B.; Murr, L. M.; Nunes, Arthur C., Jr.; Munafo, Paul M. (Technical Monitor)

    2002-01-01

    It has been shown that metal moves behind the rotating Friction Stir Pin Tool in two separate currents or streams. One current, mostly on the advancing side, enters a zone of material that rotates with the pin tool for one or more revolutions and eventually is abandoned behind the pin tool in crescent-shaped pieces. The other current, largely on the retreating side of the pin tool is moved by a wiping process to the back of the pin tool and fills in between the pieces of the rotational zone that have been shed by the rotational zone. This process was studied by using a faying surface copper trace to clarify the metal flow. Welds were made with pin tools having various thread pitches. Decreasing the thread pitch causes the large scale top-to-bottorn flow to break up into multiple vortices along the pin and an unthreaded pin tool provides insufficient vertical motion for there to be a stable rotational zone and flow of material via the rotational zone is not possible leading to porosity on the advancing side of the weld.

  20. A clinical tool for predicting survival in ALS

    PubMed Central

    Knibb, Jonathan A; Keren, Noa; Kulka, Anna; Leigh, P Nigel; Martin, Sarah; Shaw, Christopher E; Tsuda, Miho; Al-Chalabi, Ammar

    2016-01-01

    Background Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. Methods 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Findings Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. Interpretation A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors. PMID:27378085

  1. Cluster analysis as a prediction tool for pregnancy outcomes.

    PubMed

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  2. JV TASK - PREDICTIVE COAL QUALITY EFFECTS SCREENING TOOL (PCQUEST)

    SciTech Connect

    Jason D. Laumb; Joshua J. Stanislowski

    2006-08-01

    PCQUEST, a package of eight predictive indices, was developed with U.S. Department of Energy (DOE) support by the Energy and Environmental Research Center to predict fireside performance in coal-fired utility boilers more reliably than traditional indices. Since the development of PCQUEST, the need has arisen for additional fuel types into the program database. PCQUEST was developed using combustion inorganic transformation theory from previous projects and from empirical data derived from laboratory experiments and coal boiler field observations. The goal of this joint venture project between commercial industry clients and DOE is to further enhance PCQUEST and improve its utility for a variety of new fuels and systems. Specific objectives include initiating joint venture projects with utilities, boiler vendors, and coal companies that involve real-world situations and needs in order to strategically improve algorithms and input-output functions of PCQUEST, as well as to provide technology transfer to the industrial sector. The main body of this report provides a short summary of the projects that were closed from February 1999 through June 2006. All of the reports sent to the commercial clients can be found in the appendix.

  3. JV Task 5 - Predictive Coal Quality Effects Screening Tool (PCQUEST)

    SciTech Connect

    Jason Laumb; Joshua Stanislowski

    2007-07-01

    PCQUEST, a package of eight predictive indices, was developed with U.S. Department of Energy (DOE) support by the Energy & Environmental Research Center to predict fireside performance in coal-fired utility boilers more reliably than traditional indices. Since the development of PCQUEST, the need has arisen for additional improvement, validation, and enhancement of the model, as well as to incorporate additional fuel types into the program database. PCQUEST was developed using combustion inorganic transformation theory from previous projects and from empirical data derived from laboratory experiments and coal boiler field observations. The goal of this joint venture project between commercial industry clients and DOE is to further enhance PCQUEST and improve its utility for a variety of new fuels and systems. Specific objectives include initiating joint venture projects with utilities, boiler vendors, and coal companies that involve real-world situations and needs in order to strategically improve algorithms and input-output functions of PCQUEST, as well as to provide technology transfer to the industrial sector. The main body of this report provides a short summary of the projects that were closed from February 1999 through July 2007. All of the reports sent to the commercial clients can be found in the appendix.

  4. Evaluation of predictive tools for cell culture clarification performance.

    PubMed

    Senczuk, Anna; Petty, Krista; Thomas, Anne; McNerney, Thomas; Moscariello, John; Yigzaw, Yinges

    2016-03-01

    Recent advances in the productivity of industrial mammalian cell culture processes have resulted in part in increased cell density. This increase and the associated increase in cellular debris are known to challenge harvest operations, however this understanding is limited and largely qualitative. Part of the issue arises from the heterogeneous size and composition of cellular debris, which makes harvest feed stream extremely difficult to characterize. Improved characterization methods would facilitate the development of clarification approaches that are consistent and scalable. This work describes how both particle size and cholesterol analysis can be used to characterize the feed stream. Particle size analysis by focused beam reflectance and dynamic light scattering are shown to be predictive of centrate filterability under certain harvest conditions. Because of the particle size range limitations of each detector, their applicability is limited to a particular stage or method of clarification. The measurement of cholesterol present in the cell culture supernatant or centrate was successfully used in providing relative amount of lysed cellular debris and enabled us to predict clarification performance of acid precipitated harvest regardless of particle size distribution profile. © 2015 Wiley Periodicals, Inc.

  5. HVPG signature: A prognostic and predictive tool in hepatocellular carcinoma

    PubMed Central

    Xiang, Yi; Chen, Jinjun; Zhao, Jianbo; Li, Jing; Qi, Fu-Zhen; Xu, Yong

    2016-01-01

    Hepatic venous pressure gradient (HVPG) measurement provides independent prognostic value in patients with cirrhosis, and the prognostic and predictive role of HVPG in hepatocellular carcinoma (HCC) also has been explored. The management of HCC is limited to the European Association for the Study of the Liver (EASL) and American Association for the Study of Liver Diseases (AASLD) guidelines that consider that HVPG≥10 mmHg to be a contraindication for hepatic resection (HR), otherwise other treatment modalities are recommended. Current studies show that a raised HVPG diagnosed directly or indirectly leads to a negative prognosis of patients with HCC and cirrhosis, but HVPG greater than 10 mmHg should not be regarded as an absolute contraindication for HR. Selecting direct or surrogate measurement of HVPG is still under debate. Only several studies reported the impact of HVPG in negative prognosis of HCC patients after liver transplantation (LT) and the value of HVPG in the prediction of HCC development, which need to be further validated. PMID:27566593

  6. Flow Cytometry, a Versatile Tool for Diagnosis and Monitoring of Primary Immunodeficiencies

    PubMed Central

    Aubert, Geraldine

    2016-01-01

    Genetic defects of the immune system are referred to as primary immunodeficiencies (PIDs). These immunodeficiencies are clinically and immunologically heterogeneous and, therefore, pose a challenge not only for the clinician but also for the diagnostic immunologist. There are several methodological tools available for evaluation and monitoring of patients with PIDs, and of these tools, flow cytometry has gained prominence, both for phenotyping and functional assays. Flow cytometry allows real-time analysis of cellular composition, cell signaling, and other relevant immunological pathways, providing an accessible tool for rapid diagnostic and prognostic assessment. This minireview provides an overview of the use of flow cytometry in disease-specific diagnosis of PIDs, in addition to other broader applications, which include immune phenotyping and cellular functional measurements. PMID:26912782

  7. STGSTK- PREDICTING MULTISTAGE AXIAL-FLOW COMPRESSOR PERFORMANCE BY A MEANLINE STAGE-STACKING METHOD

    NASA Technical Reports Server (NTRS)

    Steinke, R. J.

    1994-01-01

    The STGSTK computer program was developed for predicting the off-design performance of multistage axial-flow compressors. The axial-flow compressor is widely used in aircraft engines. In addition to its inherent advantage of high mass flow per frontal area, it can exhibit very good aerodynamic performance. However, good aerodynamic performance over an acceptable range of operating conditions is not easily attained. STGSTK provides an analytical tool for the development of new compressor designs. The simplicity of a one-dimensional compressible flow model enables the stage-stacking method used in STGSTK to have excellent convergence properties and short computer run times. Also, the simplicity of the model makes STGSTK a manageable code that eases the incorporation, or modification, of empirical correlations directly linked to test data. Thus, the user can adapt the code to meet varying design needs. STGSTK uses a meanline stage-stacking method to predict off-design performance. Stage and cumulative compressor performance is calculated from representative meanline velocity diagrams located at rotor inlet and outlet meanline radii. STGSTK includes options for the following: 1) non-dimensional stage characteristics may be input directly or calculated from stage design performance input, 2) stage characteristics may be modified for off-design speed and blade reset, and 3) rotor design deviation angle may be modified for off-design flow, speed, and blade setting angle. Many of the code's options use correlations that are normally obtained from experimental data. The STGSTK user may modify these correlations as needed. This program is written in FORTRAN IV for batch execution and has been implemented on an IBM 370 series computer with a central memory requirement of approximately 85K of 8 bit bytes. STGSTK was developed in 1982.

  8. How Well Do Selection Tools Predict Performance Later in a Medical Programme?

    ERIC Educational Resources Information Center

    Shulruf, Boaz; Poole, Phillippa; Wang, Grace Ying; Rudland, Joy; Wilkinson, Tim

    2012-01-01

    The choice of tools with which to select medical students is complex and controversial. This study aimed to identify the extent to which scores on each of three admission tools (Admission GPA, UMAT and structured interview) predicted the outcomes of the first major clinical year (Y4) of a 6 year medical programme. Data from three student cohorts…

  9. Predictive validity of adult risk assessment tools with juveniles who offended sexually.

    PubMed

    Ralston, Christopher A; Epperson, Douglas L

    2013-09-01

    An often-held assumption in the area of sexual recidivism risk assessment is that different tools should be used for adults and juveniles. This assumption is driven either by the observation that adolescents tend to be in a constant state of flux in the areas of development, education, and social structure or by the fact that the judicial system recognizes that juveniles and adults are different. Though the assumption is plausible, it is largely untested. The present study addressed this issue by scoring 2 adult sexual offender risk assessment tools, the Minnesota Sex Offender Screening Tool-Revised and the Static-99, on an exhaustive sample (N = 636) of juveniles who had sexually offended (JSOs) in Utah. For comparison, 2 tools designed for JSOs were also scored: the Juvenile-Sex Offender Assessment Protocol-II and the Juvenile Risk Assessment Scale. Recidivism data were collected for 2 time periods: before age 18 (sexual, violent, any recidivism) and from age 18 to the year 2004 (sexual). The adult actuarial risk assessment tools predicted all types of juvenile recidivism significantly and at approximately the same level of accuracy as juvenile-specific tools. However, the accuracy of longer term predictions of adult sexual recidivism across all 4 tools was substantially lower than the accuracy achieved in predicting juvenile sexual recidivism, with 2 of the tools producing nonsignificant results, documenting the greater difficulty in making longer term predictions on the basis of adolescent behavior.

  10. Prediction of feather damage in laying hens using optical flows and Markov models.

    PubMed

    Lee, Hyoung-joo; Roberts, Stephen J; Drake, Kelly A; Dawkins, Marian Stamp

    2011-04-06

    Feather pecking in laying hens is a major welfare and production problem for commercial egg producers, resulting in mortality, loss of production as well as welfare issues for the damaged birds. Damaging outbreaks of feather pecking are currently impossible to control, despite a number of proposed interventions. However, the ability to predict feather damage in advance would be a valuable research tool for identifying which management or environmental factors could be the most effective interventions at different ages. This paper proposes a framework for forecasting the damage caused by injurious pecking based on automated image processing and statistical analysis. By frame-by-frame analysis of video recordings of laying hen flocks, optical flow measures are calculated as indicators of the movement of the birds. From the optical flow datasets, measures of disturbance are extracted using hidden Markov models. Based on these disturbance measures and age-related variables, the levels of feather damage in flocks in future weeks is predicted. Applying the proposed method to real-world datasets, it is shown that the disturbance measures offer improved predictive values for feather damage thus enabling an identification of flocks with probable prevalence of damage and injury later in lay.

  11. An Assessment of Open Rotor Noise Prediction Tools

    NASA Technical Reports Server (NTRS)

    Envia, Ed

    2012-01-01

    Assess the current capability for predicting the aerodynamic and acoustic performance of open rotors. The testbed is a GE blade set called F31/A31 for which significant amount of aerodynamic and acoustic data was acquired in model scale tests. F31/A31 is a vintage 1990s design with a 12-bladed front rotor and a 10-bladed aft rotor. This blade set was tested in both low-speed regime (representative of approach and takeoff conditions) and high-speed regime (representative of climb and cruise conditions). Uninstalled as well as installed configurations were tested. The focus of this interim presentation is on a subset of the low-speed tests for which the tip speed was varied, but the blade setting angles and tunnel Mach number were held fixed.

  12. Monitoring Subsurface Fluid Flow Using Perfluorocarbon Tracers: Another Tool Potentially Available for Subsurface Fluid Flow Assessments

    EPA Pesticide Factsheets

    Perfluorocarbon Tracers (PFTs) Complement stable Isotopes and Geochemistry for Verifying, Assessing or Modeling Fluid Flow. Geochemistry, Isotopes and PFT’s complement Geophysics to monitor and verify plume movement, leakage to shallow aquifers or surface

  13. Biomimetic Dissolution: A Tool to Predict Amorphous Solid Dispersion Performance.

    PubMed

    Puppolo, Michael M; Hughey, Justin R; Dillon, Traciann; Storey, David; Jansen-Varnum, Susan

    2017-05-30

    The presented study describes the development of a membrane permeation non-sink dissolution method that can provide analysis of complete drug speciation and emulate the in vivo performance of poorly water-soluble Biopharmaceutical Classification System class II compounds. The designed membrane permeation methodology permits evaluation of free/dissolved/unbound drug from amorphous solid dispersion formulations with the use of a two-cell apparatus, biorelevant dissolution media, and a biomimetic polymer membrane. It offers insight into oral drug dissolution, permeation, and absorption. Amorphous solid dispersions of felodipine were prepared by hot melt extrusion and spray drying techniques and evaluated for in vitro performance. Prior to ranking performance of extruded and spray-dried felodipine solid dispersions, optimization of the dissolution methodology was performed for parameters such as agitation rate, membrane type, and membrane pore size. The particle size and zeta potential were analyzed during dissolution experiments to understand drug/polymer speciation and supersaturation sustainment of felodipine solid dispersions. Bland-Altman analysis was performed to measure the agreement or equivalence between dissolution profiles acquired using polymer membranes and porcine intestines and to establish the biomimetic nature of the treated polymer membranes. The utility of the membrane permeation dissolution methodology is seen during the evaluation of felodipine solid dispersions produced by spray drying and hot melt extrusion. The membrane permeation dissolution methodology can suggest formulation performance and be employed as a screening tool for selection of candidates to move forward to pharmacokinetic studies. Furthermore, the presented model is a cost-effective technique.

  14. Prediction of liver cirrhosis, using diagnostic imaging tools

    PubMed Central

    Yeom, Suk Keu; Lee, Chang Hee; Cha, Sang Hoon; Park, Cheol Min

    2015-01-01

    Early diagnosis of liver cirrhosis is important. Ultrasound-guided liver biopsy is the gold standard for diagnosis of liver cirrhosis. However, its invasiveness and sampling bias limit the applicability of the method. Basic imaging for the diagnosis of liver cirrhosis has developed over the last few decades, enabling early detection of morphological changes of the liver by ultrasonography (US), computed tomography, and magnetic resonance imaging (MRI). They are also accurate diagnostic methods for advanced liver cirrhosis, for which early diagnosis is difficult. There are a number of ways to compensate for this difficulty, including texture analysis to more closely identify the homogeneity of hepatic parenchyma, elastography to measure the stiffness and elasticity of the liver, and perfusion studies to determine the blood flow volume, transit time, and velocity. Amongst these methods, elastography using US and MRI was found to be slightly easier, faster, and able to provide an accurate diagnosis. Early diagnosis of liver cirrhosis using MRI or US elastography is therefore a realistic alternative, but further research is still needed. PMID:26301049

  15. Model-based calculating tool for pollen-mediated gene flow frequencies in plants.

    PubMed

    Lei, Wang; Bao-Rong, Lu

    2016-12-30

    The potential social-economic and environmental impacts caused by transgene flow from genetically engineered (GE) crops have stimulated worldwide biosafety concerns. To determine transgene flow frequencies resulted from pollination is the first critical step for assessing such impacts, in addition to the determination of transgene expression and fitness in crop-wild hybrid descendants. Two methods are commonly used to estimate pollen-mediated gene flow (PMGF) frequencies: field experimenting and mathematical modeling. Field experiments can provide relatively accurate results but are time/resource consuming. Modeling offers an effective complement for PMGF experimental assessment. However, many published models describe PMGF by mathematical equations and are practically not easy to use. To increase the application of PMGF modeling for the estimation of transgene flow, we established a tool to calculate PMGF frequencies based on a quasi-mechanistic PMGF model for wind-pollination species. This tool includes a calculating program displayed by an easy-operating interface. PMGF frequencies of different plant species can be quickly calculated under different environmental conditions by including a number of biological and wind speed parameters that can be measured in the fields/laboratories or obtained from published data. The tool is freely available in the public domain (http://ecology.fudan.edu.cn/userfiles/cn/files/Tool_Manual.zip). Case studies including rice, wheat, and maize demonstrated similar results between the calculated frequencies based on this tool and those from published PMGF data. This PMGF calculating tool will provide useful information for assessing and monitoring social-economic and environmental impacts caused by transgene flow from GE crops. This tool can also be applied to determine the isolation distances between GE and non-GE crops in a coexistence agro-ecosystem, and to ensure the purity of certified seeds by setting proper isolation distances

  16. Influence of the Tool Shoulder Contact Conditions on the Material Flow During Friction Stir Welding

    NASA Astrophysics Data System (ADS)

    Doude, Haley R.; Schneider, Judy A.; Nunes, Arthur C.

    2014-09-01

    Friction stir welding (FSWing) is a solid-state joining process of special interest in joining alloys that are traditionally difficult to fusion weld. In order to optimize the process, various numeric modeling approaches have been pursued. Of importance to furthering modeling efforts is a better understanding of the contact conditions between the workpiece and the weld tool. Both theoretical and experimental studies indicate the contact conditions between the workpiece and weld tool are unknown, possibly varying during the FSW process. To provide insight into the contact conditions, this study characterizes the material flow in the FSW nugget by embedding a lead (Pb) wire that melted at the FSWing temperature of aluminum alloy 2195. The Pb trace provided evidence of changes in material flow characteristics which were attributed to changes in the contact conditions between the weld tool and workpiece, as driven by temperature, as the tool travels the length of a weld seam.

  17. 'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools

    PubMed Central

    Shen, Yao Qing; Burger, Gertraud

    2007-01-01

    Background Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes. Results In order to develop a method for enhanced prediction of subcellular localization, we integrated the outputs of available localization prediction tools by several strategies, and tested the performance of each strategy with known mitochondrial proteins. The accuracy obtained (up to 92%) surpasses by far the individual tools. The method of integration proved crucial to the performance. For the prediction of mitochondrion-located proteins, integration via a two-layer decision tree clearly outperforms simpler methods, as it allows emphasis of biologically relevant features such as the mitochondrial targeting peptide and transmembrane domains. Conclusion We developed an approach that enhances the prediction accuracy of mitochondrial proteins by uniting the strength of specialized tools. The combination of machine-learning based integration with biological expert knowledge leads to improved performance. This approach also alleviates the conundrum of how to choose between conflicting predictions. Our approach is easy to implement, and applicable to predicting subcellular locations other than mitochondria, as well as other biological features. For a trial of our approach, we provide a webservice for mitochondrial protein

  18. Hemodynamic flow modeling through an abdominal aorta aneurysm using data mining tools.

    PubMed

    Filipovic, Nenad; Ivanovic, Milos; Krstajic, Damjan; Kojic, Milos

    2011-03-01

    Geometrical changes of blood vessels, called aneurysm, occur often in humans with possible catastrophic outcome. Then, the blood flow is enormously affected, as well as the blood hemodynamic interaction forces acting on the arterial wall. These forces are the cause of the wall rupture. A mechanical quantity characteristic for the blood-wall interaction is the wall shear stress, which also has direct physiological effects on the endothelial cell behavior. Therefore, it is very important to have an insight into the blood flow and shear stress distribution when an aneurysm is developed in order to help correlating the mechanical conditions with the pathogenesis of pathological changes on the blood vessels. This insight can further help in improving the prevention of cardiovascular diseases evolution. Computational fluid dynamics (CFD) has been used in general as a tool to generate results for the mechanical conditions within blood vessels with and without aneurysms. However, aneurysms are very patient specific and reliable results from CFD analyses can be obtained by a cumbersome and time-consuming process of the computational model generation followed by huge computations. In order to make the CFD analyses efficient and suitable for future everyday clinical practice, we have here employed data mining (DM) techniques. The focus was to combine the CFD and DM methods for the estimation of the wall shear stresses in an abdominal aorta aneurysm (AAA) underprescribed geometrical changes. Additionally, computing on the grid infrastructure was performed to improve efficiency, since thousands of CFD runs were needed for creating machine learning data. We used several DM techniques and found that our DM models provide good prediction of the shear stress at the AAA in comparison with full CFD model results on real patient data.

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

    NASA Technical Reports Server (NTRS)

    Owen, Albert K.

    1992-01-01

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

  20. Genomics: Tool to predict and prevent male infertility.

    PubMed

    Halder, Ashutosh; Kumar, Prashant; Jain, Manish; Kalsi, Amanpreet Kaur

    2017-06-01

    A large number of human diseases arise as a result of genetic abnormalities. With the advent of improved molecular biology techniques, the genetic etiology of male infertility is increasing. The common genetic factors responsible for male infertility are chromosomal abnormalities, Yq microdeletion and cystic fibrosis. These are responsible for approximately 30 percent cases of male infertility. About 40 percent cases of male infertility are categorized as idiopathic. These cases may be associated with genetic and genomic abnormalities. During last few years more and more genes are implicated in male infertility leading to decline in prevalence of idiopathic etiology. In this review we will summarize up to date published works on genetic etiologies of male infertility including our own works. We also briefly describe reproductive technologies used to overcome male infertility, dangers of transmitting genetic disorders to offspring and ways to prevent transmission of genetic disorders during assisted reproduction. At the end we will provide our points on how genomic information can be utilized for prediction and prevention of male infertility in coming years.

  1. The Monte Carlo technique as a tool to predict LOAEL.

    PubMed

    Veselinović, Jovana B; Veselinović, Aleksandar M; Toropova, Alla P; Toropov, Andrey A

    2016-06-30

    Quantitative structure - activity relationships (QSARs) for the Lowest Observed Adverse Effect Level (LOAEL) for a large set of organic compounds (n = 341) are suggested. The molecular structures of these compounds are represented by Simplified Molecular Input-Line Entry Systems (SMILES). A criteria for the estimation quality of split into the "visible" training set (used for developing a model) and "invisible" external validation set is suggested. The correlation between the above criterion and the predictive potential of developed QSAR model (root-mean-square error for "invisible" validation set) has been detected. One-variable models are built up for several different splits into the "visible" training set and "invisible" validation set. The statistical quality of these models is quite good. Mechanistic interpretation and the domain of applicability for these models are defined according to probabilistic point of view. The methodology for defining applicability domain in QSAR modeling with SMILES notation based optimal descriptors is presented. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  2. Prediction of Severe Accident Counter Current Natural Circulation Flows in the Hot Leg of a Pressurized Water Reactor

    SciTech Connect

    Boyd, Christopher F.

    2006-07-01

    During certain phases of a severe accident in a pressurized water reactor (PWR), the core becomes uncovered and steam carries heat to the steam generators through natural circulation. For PWR's with U-tube steam generators and loop seals filled with water, a counter current flow pattern is established in the hot leg. This flow pattern has been experimentally observed and has been predicted using computational fluid dynamics (CFD). Predictions of severe accident behavior are routinely carried out using severe accident system analysis codes such as SCDAP/RELAP5 or MELCOR. These codes, however, were not developed for predicting the three-dimensional natural circulation flow patterns during this phase of a severe accident. CFD, along with a set of experiments at 1/7. scale, have been historically used to establish the flow rates and mixing for the system analysis tools. One important aspect of these predictions is the counter current flow rate in the nearly 30 inch diameter hot leg between the reactor vessel and steam generator. This flow rate is strongly related to the amount of energy that can be transported away from the reactor core. This energy transfer plays a significant role in the prediction of core failures as well as potential failures in other reactor coolant system piping. CFD is used to determine the counter current flow rate during a severe accident. Specific sensitivities are completed for parameters such as surge line flow rates, hydrogen content, as well as vessel and steam generator temperatures. The predictions are carried out for the reactor vessel upper plenum, hot leg, a portion of the surge line, and a steam generator blocked off at the outlet plenum. All predictions utilize the FLUENT V6 CFD code. The volumetric flow in the hot leg is assumed to be proportional to the square root of the product of normalized density difference, gravity, and hydraulic diameter to the 5. power. CFD is used to determine the proportionality constant in the range

  3. CNT Based Artificial Hair Sensors for Predictable Boundary Layer Air Flow Sensing (Postscript)

    DTIC Science & Technology

    2016-11-07

    ABSTRACT (Maximum 200 words) While numerous flow sensor architectures mimic the natural cilia of crickets, locusts, bats, and fish, the prediction...magnitude variability in both sensitivity and CNT compressive modulus. 15. SUBJECT TERMS flow sensor architectures ; hair sensor; piezoresistive...Boundary Layer Air Flow Sensing Keith A. Slinker,* Corey Kondash, Benjamin T. Dickinson, and Jeffery W. Baur While numerous flow sensor architectures

  4. Material Flow Tracking for Various Tool Geometries During the Friction Stir Spot Welding Process

    NASA Astrophysics Data System (ADS)

    Lin, Yuan-Ching; Liu, Ju-Jen; Chen, Jiun-Nan

    2013-12-01

    This study applied powder-tracing techniques to mount Cu and W powders on A6061-T6 aluminum sheets to investigate the material flow mechanism of friction stir spot welding (FSSW) using various geometric tools. The experimental results showed that the geometry of the tools plays a crucial role and determines the entrances of material flow during FSSW. It was believed that instantaneous voids were filled up with material flow in all directions for triangular pins, and the voids were located at the pin bottom for cylindrical pins. In accordance with the plastic rule of material flow, the pressure gradient is the necessary condition to cause material flow during FSSW; therefore, the transient constraint space (TCS) is required to generate pressure in this space. Enlargement of the TCS accompanies the evolution of the stir zone (SZ). A generated void causes a steep pressure gradient, which is regarded as the entrance of material flow. A tool with screw threads causes downward driving force, which determines the intermixing behavior between the upper and lower sheets, and also affects the size of the SZs.

  5. Comparison of three different tools for prediction of seminal vesicle invasion at radical prostatectomy.

    PubMed

    Lughezzani, Giovanni; Zorn, Kevin C; Budäus, Lars; Sun, Maxine; Lee, David I; Shalhav, Arieh L; Zagaya, Gregory P; Shikanov, Sergey A; Gofrit, Ofer N; Thong, Alan E; Albala, David M; Sun, Leon; Cronin, Angel; Vickers, Andrew J; Karakiewicz, Pierre I

    2012-10-01

    Statistical prediction tools are increasingly common, but there is considerable disagreement about how they should be evaluated. Three tools--Partin tables, the European Society for Urological Oncology (ESUO) criteria, and the Gallina nomogram--have been proposed for the prediction of seminal vesicle invasion (SVI) in patients with clinically localized prostate cancer who are candidates for a radical prostatectomy. Using different statistical methods, we aimed to determine which of these tools should be used to predict SVI. The independent validation cohort consisted of 2584 patients treated surgically for clinically localized prostate cancer at four North American tertiary care centers between 2002 and 2007. Robot-assisted laparoscopic radical prostatectomy. Primary outcome was the presence of SVI. Traditional (area under the receiver operating characteristic [ROC] curve, calibration plots, the Brier score, sensitivity and specificity, positive and negative predictive value) and novel (decision curve analysis and predictiveness curves) statistical methods quantified the predictive abilities of the three models. Traditional statistical methods (ie, ROC plots and Brier scores) could not clearly determine which one of the three SVI prediction tools should be preferred. For example, ROC plots and Brier scores seemed biased against the binary decision tool (ESUO criteria) and gave discordant results for the continuous predictions of the Partin tables and the Gallina nomogram. The results of the calibration plots were discordant with those of the ROC plots. Conversely, the decision curve indicated that the Partin tables represent the best strategy for stratifying the risk of SVI, resulting in the highest net benefit within the whole range of threshold probabilities. When predicting SVI, surgeons should prefer the Partin tables over the ESUO criteria and the Gallina nomogram because this tool provided the highest net benefit. In contrast to traditional statistical

  6. TepiTool: A Pipeline for Computational Prediction of T Cell Epitope Candidates.

    PubMed

    Paul, Sinu; Sidney, John; Sette, Alessandro; Peters, Bjoern

    2016-08-01

    Computational prediction of T cell epitope candidates is currently being used in several applications including vaccine discovery studies, development of diagnostics, and removal of unwanted immune responses against protein therapeutics. There have been continuous improvements in the performance of MHC binding prediction tools, but their general adoption by immunologists has been slow due to the lack of user-friendly interfaces and guidelines. Current tools only provide minimal advice on what alleles to include, what lengths to consider, how to deal with homologous peptides, and what cutoffs should be considered relevant. This protocol provides step-by-step instructions with necessary recommendations for prediction of the best T cell epitope candidates with the newly developed online tool called TepiTool. TepiTool, which is part of the Immune Epitope Database (IEDB), provides some of the top MHC binding prediction algorithms for number of species including humans, chimpanzees, bovines, gorillas, macaques, mice, and pigs. The TepiTool is freely accessible at http://tools.iedb.org/tepitool/. © 2016 by John Wiley & Sons, Inc.

  7. A clinical tool to predict failed response to therapy in children with severe pneumonia.

    PubMed

    Mamtani, Manju; Patel, Archana; Hibberd, Patricia L; Tuan, Tran Anh; Jeena, Prakash; Chisaka, Noel; Hassan, Mumtaz; Radovan, Irene Maulen; Thea, Donald M; Qazi, Shamim; Kulkarni, Hemant

    2009-04-01

    Severe pneumonia in children under 5 years of age continues to be an important clinical entity with treatment failure rates as high as 20%. Where severe pneumonias are common, predictive tools for treatment failure like chest radiography and pulse oximetry are not available or affordable. Thus, there is a need for development of simple, accurate and inexpensive clinical tools for prediction of treatment failure. Using clinical, chest radiographic and pulse oximetry data from 1702 children recruited in the Amoxicillin Penicillin Pneumonia International Study (APPIS) trial we developed and validated a simple clinical tool. For development, a randomly derived development sample (n = 889) was used. The tool which was based on the results of multivariate logistic regression models was validated on a separate sample of 813 children. The derived clinical tool in its final form contained three clinical predictors: age of child, excess age-specific respiratory rate at baseline and at 24 hr of hospitalization. This tool had a 70% and 66% predictive accuracy in the development and validation samples, respectively. The tool is presented as an easy-to-use nomogram. It is possible to predict the likelihood of treatment failure in children with severe pneumonia based on clinical features that are simple and inexpensive to measure.

  8. Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

    NASA Astrophysics Data System (ADS)

    Starn, J. J.; Belitz, K.

    2014-12-01

    National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions

  9. Materials Flows Through Industry Tool to Track Supply Chain Energy Demand

    SciTech Connect

    Carpenter, Alberta; Mann, Margaret; Gelman, Rachel; Lewis, John; Benson, David; Cresko, Joe; Ma, Seungwook

    2014-10-01

    In evaluating next-generation materials and processes, the supply chain can have a large impact on the life cycle energy impacts. The Materials Flow through Industry (MFI) tool was developed for the Department of Energy's Advanced Manufacturing Office to be able to evaluate the energy impacts of the U.S. supply chain. The tool allows users to perform process comparisons, material substitutions, and grid modifications, and to see the effects of implementing sector efficiency potentials (Masanet, et al. 2009). This paper reviews the methodology of the tool and provides results around specific scenarios.

  10. How well do selection tools predict performance later in a medical programme?

    PubMed

    Shulruf, Boaz; Poole, Phillippa; Wang, Grace Ying; Rudland, Joy; Wilkinson, Tim

    2012-12-01

    The choice of tools with which to select medical students is complex and controversial. This study aimed to identify the extent to which scores on each of three admission tools (Admission GPA, UMAT and structured interview) predicted the outcomes of the first major clinical year (Y4) of a 6 year medical programme. Data from three student cohorts (n = 324) were analysed using regression analyses. The Admission GPA was the best predictor of academic achievement in years 2 and 3 with regression coefficients (B) of 1.31 and 0.9 respectively (each P < 0.001). Furthermore, Admission GPA predicted whether or not a student was likely to earn 'Distinction' rather than 'Pass' in year 4. In comparison, UMAT and interview showed low predictive ability for any outcomes. Interview scores correlated negatively with those on the other tools. None of the tools predicted failure to complete year 4 on time, but only 3% of students fell into this category. Prior academic achievement remains the best measure of subsequent student achievement within a medical programme. Interview scores have little predictive value. Future directions include longer term studies of what UMAT predicts, and of novel ways to combine selection tools to achieve the optimum student cohort.

  11. sedFlow - a tool for simulating fractional bedload transport and longitudinal profile evolution in mountain streams

    NASA Astrophysics Data System (ADS)

    Heimann, F. U. M.; Rickenmann, D.; Turowski, J. M.; Kirchner, J. W.

    2015-01-01

    Especially in mountainous environments, the prediction of sediment dynamics is important for managing natural hazards, assessing in-stream habitats and understanding geomorphic evolution. We present the new modelling tool {sedFlow} for simulating fractional bedload transport dynamics in mountain streams. sedFlow is a one-dimensional model that aims to realistically reproduce the total transport volumes and overall morphodynamic changes resulting from sediment transport events such as major floods. The model is intended for temporal scales from the individual event (several hours to few days) up to longer-term evolution of stream channels (several years). The envisaged spatial scale covers complete catchments at a spatial discretisation of several tens of metres to a few hundreds of metres. sedFlow can deal with the effects of streambeds that slope uphill in a downstream direction and uses recently proposed and tested approaches for quantifying macro-roughness effects in steep channels. sedFlow offers different options for bedload transport equations, flow-resistance relationships and other elements which can be selected to fit the current application in a particular catchment. Local grain-size distributions are dynamically adjusted according to the transport dynamics of each grain-size fraction. sedFlow features fast calculations and straightforward pre- and postprocessing of simulation data. The high simulation speed allows for simulations of several years, which can be used, e.g., to assess the long-term impact of river engineering works or climate change effects. In combination with the straightforward pre- and postprocessing, the fast calculations facilitate efficient workflows for the simulation of individual flood events, because the modeller gets the immediate results as direct feedback to the selected parameter inputs. The model is provided together with its complete source code free of charge under the terms of the GNU General Public License (GPL) (www.wsl.ch/sedFlow

  12. Non Invasive Assessment of Tissue Oxygenation and Blood Flow as a Tool for Staging Diabetes

    NASA Astrophysics Data System (ADS)

    Sujatha, N.; Anand, B. S. Suresh; Jayanthy, A. K.; Murthy, V. B. Narayana; Sheshadri; Poddar, Richa

    2011-10-01

    Diffuse reflectance spectroscopy and laser speckle imaging have been identified as an effective tool in characterizing/assessing tissue oxygenation and blood flow in real time tissues. In this paper we are exploring the possibility of finding out blood flow/oxygenation at different areas of feet of subjects with different levels of diabetes. Tissue blood flow is determined by assessing the contrast variations in the laser speckle image of the foot and tissue oxygenation is assessed by diffuse reflectance spectroscopy. A combination of both techniques offers an effective and purely non invasive mode of examination in the staging of Diabetes.

  13. Major histocompatibility complex linked databases and prediction tools for designing vaccines.

    PubMed

    Singh, Satarudra Prakash; Mishra, Bhartendu Nath

    2016-03-01

    Presently, the major histocompatibility complex (MHC) is receiving considerable interest owing to its remarkable role in antigen presentation and vaccine design. The specific databases and prediction approaches related to MHC sequences, structures and binding/nonbinding peptides have been aggressively developed in the past two decades with their own benchmarks and standards. Before using these databases and prediction tools, it is important to analyze why and how the tools are constructed along with their strengths and limitations. The current review presents insights into web-based immunological bioinformatics resources that include searchable databases of MHC sequences, epitopes and prediction tools that are linked to MHC based vaccine design, including population coverage analysis. In T cell epitope forecasts, MHC class I binding predictions are very accurate for most of the identified MHC alleles. However, these predictions could be further improved by integrating proteasome cleavage (in conjugation with transporter associated with antigen processing (TAP) binding) prediction, as well as T cell receptor binding prediction. On the other hand, MHC class II restricted epitope predictions display relatively low accuracy compared to MHC class I. To date, pan-specific tools have been developed, which not only deliver significantly improved predictions in terms of accuracy, but also in terms of the coverage of MHC alleles and supertypes. In addition, structural modeling and simulation systems for peptide-MHC complexes enable the molecular-level investigation of immune processes. Finally, epitope prediction tools, and their assessments and guidelines, have been presented to immunologist for the design of novel vaccine and diagnostics. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

  14. Experimental results and wear predictions of petal tools that freely rotate.

    PubMed

    Cordero-Dávila, Alberto; Cabrera-Peláez, Víctor; Cuautle-Cortés, Jorge; González-García, Jorge; Robledo-Sánchez, Carlos; Bautista-Elivar, Nazario

    2005-03-10

    It is difficult to calculate the wear produced by free-pinned tools because their angular movement is not entirely predictable. We analyze the wear produced with free-pinned ring tools, using both simulations and experiments. We conclude that the wear of an incomplete ring is directly proportional to the ring's angular size, independently of the mean radius of the ring. We present an algorithm for calculation of the wear produced by free-pinned petal tools, as they can be considered a linear combination of incomplete free-pinned ring tools. Finally, we apply this result to the enhancement of a defective flat surface and to making a concave spheric surface.

  15. Predicting the impact of water demand and river flow regulation over riparian vegetation through mathematical modeling

    NASA Astrophysics Data System (ADS)

    Garcia-Arias, A.; Pons, C.; Frances, F.

    2013-12-01

    The vegetation of the riversides is a main part of the complex riparian ecosystems and has an important role maintaining the fluvial ecosystems. Biotic and abiotic interactions between the river and the riverbank are essential for the subsistence and the development of both ecosystems. In semi-arid Mediterranean areas, the riparian vegetation growth and distribution is especially controlled by the water accessibility, determining the limit between the lush riparian bands and the sparse upland. Human intervention can alter the river hydrology determining the riparian vegetation wellbeing and its distribution and, in consequence, affecting both riparian and fluvial ecosystems. Predictive models are necessary decision support tools for adequate river management and restoration initiatives. In this context, the RibAV model is useful to predict the impact of water demand and river flow regulation on the riparian vegetation. RibAV is able to reproduce the vegetation performance on the riverside allowing the scenarios analysis in terms of vegetation distribution and wellbeing. In this research several flow regulation and water demand scenarios are proposed and the impacts over three plant functional types (PFTs) are analyzed. The PFTs group the herbaceous riparian plants, the woody riparian plants and the terrestrial vegetation. The study site is the Terde reach at the Mijares River, a 539m length reach located in a semi-arid Mediterranean area in Spain. The scenarios represent river flow alterations required to attend different human demands. These demands encompass different seasonality, magnitude and location. The seasonality is represented as hydroelectric (constant all over the year), urban (increased during the summer period) and agricultural demands (monthly seasonality). The magnitude is varied considering the 20%, the 40% and the 80% of the mean daily flow. Two locations are considered, upstream or downstream the study site. To attend the demands located

  16. Laser flow cytometry as a tool for the advancement of clinical medicine.

    PubMed

    Aebisher, David; Bartusik, Dorota; Tabarkiewicz, Jacek

    2017-01-01

    Flow cytometry is a classic laser technology. With the discovery of the cytometer, flow cytometry has become a primary tool in biodiagnostic research. This review focuses on current applications of flow cytometry to the diagnosis of disease and treatment monitoring at the single-cell level. A description of the principles of flow cytometry and a brief overview of the major applications are presented. Our criteria for selecting research papers for this review are those that show advances in biomedicine and pharmacotherapy achieved by using non-invasive flow cytometry. New concepts for diagnosis and classification based on quantitative measurements of cellular parameters and the expression of specific differentiation antigens on the surface of cells will be discussed herein. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  17. Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool.

    PubMed

    Saffian, Shamin M; Duffull, Stephen B; Roberts, Rebecca L; Tait, Robert C; Black, Leanne; Lund, Kirstin A; Thomson, Alison H; Wright, Daniel F B

    2016-12-01

    A previously established Bayesian dosing tool for warfarin was found to produce biased maintenance dose predictions. In this study, we aimed (1) to determine whether the biased warfarin dose predictions previously observed could be replicated in a new cohort of patients from 2 different clinical settings, (2) to explore the influence of CYP2C9 and VKORC1 genotype on predictive performance of the Bayesian dosing tool, and (3) to determine whether the previous population used to develop the kinetic-pharmacodynamic model underpinning the Bayesian dosing tool was sufficiently different from the test (posterior) population to account for the biased dose predictions. The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values. The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations. Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.

  18. 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.

  19. 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.

  20. Improving Joint Expeditionary Medical Planning Tools Based on a Patient Flow Approach

    DTIC Science & Technology

    2012-01-01

    considers neither the significant daily variability observed in histori - 1 A patient condition code is a standardized coding scheme that contains a...Medical Planning Tools Based on a Patient Flow Approach wounds become infected, including with tetanus .9 The high incidence of infected wounds may...2004) Hurricane Katrina (2005) Kashmir earthquake (2005) Fracture Puncture Strain/sprain Laceration Tetanus vaccination Distribution (%) 70

  1. The Fast-Flow Discharge Reactor as an Undergraduate Instructional Tool.

    ERIC Educational Resources Information Center

    Provencher, G. M.

    1981-01-01

    A fast-flow discharge reactor has been used in an analytical chemistry demonstration of gas phase titration, in inorganic preparative chemistry, and in physical chemistry as a "practice" vacuum line, kinetic reactor, and spectroscopic source as well as an undergraduate research tool. (SK)

  2. The Fast-Flow Discharge Reactor as an Undergraduate Instructional Tool.

    ERIC Educational Resources Information Center

    Provencher, G. M.

    1981-01-01

    A fast-flow discharge reactor has been used in an analytical chemistry demonstration of gas phase titration, in inorganic preparative chemistry, and in physical chemistry as a "practice" vacuum line, kinetic reactor, and spectroscopic source as well as an undergraduate research tool. (SK)

  3. A critical evaluation of a three-dimensional Navier-Stokes method as a tool to calculate transonic flows inside a low-aspect-ratio compressor

    NASA Technical Reports Server (NTRS)

    Hah, Chunill; Puterbaugh, Steven L.

    1992-01-01

    A numerical study to evaluate a three-dimensional Navier-Stokes method as a tool to predict the detailed flow field inside a low-aspect-ratio compressor at various operating conditions was conducted. The details of the flow structure inside a low aspect ratio compressor (three-dimensional shock structure, shock-boundary layer interaction, and tip leakage vortex) and the overall aerodynamic performance at design and off-design conditions are numerically analyzed and the results are compared with the available experimental data. The flow field inside a state-of-the-art transonic compressor is used for the purpose of the evaluation.

  4. Introduction: Assessment of aerothermodynamic flight prediction tools through ground and flight experimentation

    NASA Astrophysics Data System (ADS)

    Schmisseur, John D.; Erbland, Peter

    2012-01-01

    This article provides an introduction and overview to the efforts of NATO Research and Technology Organization Task Group AVT-136, Assessment of Aerothermodynamic Flight Prediction Tools through Ground and Flight Experimentation. During the period of 2006-2010, AVT-136 coordinated international contributions to assess the state-of-the-art and research challenges for the prediction of critical aerothermodynamic flight phenomena based on the extrapolation of ground test and numerical simulation. To achieve this goal, efforts were organized around six scientific topic areas: (1) Noses and leading edges, (2) Shock Interactions and Control Surfaces, (3) Shock Layers and Radiation, (4) Boundary Layer Transition, (5) Gas-Surface Interactions, and (6) Base and Afterbody Flows. A key component of the AVT-136 strategy was comparison of state-of-the-art numerical simulations with data to be acquired from planned flight research programs. Although it was recognized from the onset of AVT-136 activities that reliance on flight research data yet to be collected posed a significant risk, the group concluded the substantial benefit to be derived from comparison of computational simulations with flight data warranted pursuit of such a program of work. Unfortunately, program delays and failures in the flight programs contributing to the AVT-136 effort prevented timely access to flight research data. Despite this setback, most of the scientific topic areas developed by the Task Group made significant progress in the assessment of current capabilities. Additionally, the activities of AVT-136 generated substantial interest within the international scientific research community and the work of the Task Group was prominently featured in a total of six invited sessions in European and American technical conferences. In addition to this overview, reviews of the state-of-the-art and research challenges identified by the six research thrusts of AVT-136 are also included in this special

  5. A Bayesian Hierarchical Modeling Approach to Predicting Flow in Ungauged Basins

    NASA Astrophysics Data System (ADS)

    Gronewold, A.; Alameddine, I.; Anderson, R. M.

    2009-12-01

    Recent innovative approaches to identifying and applying regression-based relationships between land use patterns (such as increasing impervious surface area and decreasing vegetative cover) and rainfall-runoff model parameters represent novel and promising improvements to predicting flow from ungauged basins. In particular, these approaches allow for predicting flows under uncertain and potentially variable future conditions due to rapid land cover changes, variable climate conditions, and other factors. Despite the broad range of literature on estimating rainfall-runoff model parameters, however, the absence of a robust set of modeling tools for identifying and quantifying uncertainties in (and correlation between) rainfall-runoff model parameters represents a significant gap in current hydrological modeling research. Here, we build upon a series of recent publications promoting novel Bayesian and probabilistic modeling strategies for quantifying rainfall-runoff model parameter estimation uncertainty. Our approach applies alternative measures of rainfall-runoff model parameter joint likelihood (including Nash-Sutcliffe efficiency, among others) to simulate samples from the joint parameter posterior probability density function. We then use these correlated samples as response variables in a Bayesian hierarchical model with land use coverage data as predictor variables in order to develop a robust land use-based tool for forecasting flow in ungauged basins while accounting for, and explicitly acknowledging, parameter estimation uncertainty. We apply this modeling strategy to low-relief coastal watersheds of Eastern North Carolina, an area representative of coastal resource waters throughout the world because of its sensitive embayments and because of the abundant (but currently threatened) natural resources it hosts. Consequently, this area is the subject of several ongoing studies and large-scale planning initiatives, including those conducted through the United

  6. GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes.

    PubMed

    Li, Aiguo; Bozdag, Serdar; Kotliarov, Yuri; Fine, Howard A

    2010-07-15

    Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine. We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework. GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision-making. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.

  7. Progress in the development and integration of fluid flow control tools in paper microfluidics.

    PubMed

    Fu, Elain; Downs, Corey

    2017-02-14

    Paper microfluidics is a rapidly growing subfield of microfluidics in which paper-like porous materials are used to create analytical devices. There is a need for higher performance field-use tests for many application domains including human disease diagnosis, environmental monitoring, and veterinary medicine. A key factor in creating high performance paper-based devices is the ability to manipulate fluid flow within the devices. This critical review is focused on the progress that has been made in (i) the development of fluid flow control tools and (ii) the integration of those tools into paper microfluidic devices. Further, we strive to be comprehensive in our presentation and provide historical context through discussion and performance comparisons, when possible, of both relevant earlier work and recent work. Finally, we discuss the major areas of focus for fluid flow methods development to advance the potential of paper microfluidics for high-performance field applications.

  8. Automatic generation of bioinformatics tools for predicting protein–ligand binding sites

    PubMed Central

    Banno, Masaki; Ueki, Kokoro; Saad, Gul; Shimizu, Kentaro

    2016-01-01

    Motivation: Predictive tools that model protein–ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein–ligand binding predictive tools would be useful. Results: We developed a system for automatically generating protein–ligand binding predictions. Implementation of this system in a pipeline of Semantic Web technique-based web tools will allow users to specify a ligand and receive the tool within 0.5–1 day. We demonstrated high prediction accuracy for three machine learning algorithms and eight ligands. Availability and implementation: The source code and web application are freely available for download at http://utprot.net. They are implemented in Python and supported on Linux. Contact: shimizu@bi.a.u-tokyo.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26545824

  9. Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.

    PubMed

    Komiyama, Yusuke; Banno, Masaki; Ueki, Kokoro; Saad, Gul; Shimizu, Kentaro

    2016-03-15

    Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful. We developed a system for automatically generating protein-ligand binding predictions. Implementation of this system in a pipeline of Semantic Web technique-based web tools will allow users to specify a ligand and receive the tool within 0.5-1 day. We demonstrated high prediction accuracy for three machine learning algorithms and eight ligands. The source code and web application are freely available for download at http://utprot.net They are implemented in Python and supported on Linux. shimizu@bi.a.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  10. Predicting Right Ventricular Failure in the Modern, Continuous Flow Left Ventricular Assist Device Era

    PubMed Central

    Atluri, Pavan; Goldstone, Andrew B.; Fairman, Alex S.; MacArthur, John W.; Shudo, Yasuhiro; Cohen, Jeffrey E.; Acker, Alexandra L.; Hiesinger, William; Howard, Jessica L.; Acker, Michael A.; Woo, Y. Joseph

    2014-01-01

    Background In the era of destination continuous flow left ventricular assist devices (LVAD), the decision of whether a patient will tolerate isolated LVAD support or will need biventricular support (BIVAD) can be challenging. Incorrect decision making with delayed right ventricular (RV) assist device implantation results in increased morbidity and mortality. Continuous flow LVADs have been shown to decrease pulmonary hyper-tension and improve RV function. We undertook this study to determine predictors in the continuous flow LVAD era that identify patients who are candidates for isolated LVAD therapy as opposed to biventricular support. Methods We reviewed demographic, hemodynamic, laboratory, and echocardiographic variables for 218 patients who underwent VAD implant from 2003 through 2011 (LVAD = 167, BIVAD = 51), during the era of continuous flow LVADs. Results Fifty preoperative risk factors were compared between patients who were successfully managed with an LVAD and those who required a BIVAD. Seventeen variables demonstrated statistical significance by univariate analysis. Multivariable logistic regression analysis identified central venous pressure >15 mmHg (OR 2.0, “C”), severe RV dysfunction (OR 3.7, “R”), preoperative intubation (OR 4.3, “I”), severe tricuspid regurgitation (OR 4.1, “T”), heart rate >100 (OR 2.0, Tachycardia - “T”) -CRITT as the major criteria predictive of the need for biventricular support. Utilizing these data, a highly sensitive and easy to use risk score for determining RV failure was generated that outperformed other established risk stratification tools. Conclusions We present a preoperative risk calculator to determine suitability of a patient for isolated LVAD support in the current continuous flow ventricular assist device era. PMID:23791165

  11. Multicentre validation of different predictive tools of non-sentinel lymph node involvement in breast cancer.

    PubMed

    Cserni, G; Boross, G; Maráz, R; Leidenius, M H K; Meretoja, T J; Heikkila, P S; Regitnig, P; Luschin-Ebengreuth, G; Zgajnar, J; Perhavec, A; Gazic, B; Lázár, G; Takács, T; Vörös, A; Audisio, R A

    2012-06-01

    Sentinel lymph node (SN) biopsy offers the possibility of selective axillary treatment for breast cancer patients, but there are only limited means for the selective treatment of SN-positive patients. Eight predictive models assessing the risk of non-SN involvement in patients with SN metastasis were tested in a multi-institutional setting. Data of 200 consecutive patients with metastatic SNs and axillary lymph node dissection from each of the 5 participating centres were entered into the selected non-SN metastasis predictive tools. There were significant differences between centres in the distribution of most parameters used in the predictive models, including tumour size, type, grade, oestrogen receptor positivity, rate of lymphovascular invasion, proportion of micrometastatic cases and the presence of extracapsular extension of SN metastasis. There were also significant differences in the proportion of cases classified as having low risk of non-SN metastasis. Despite these differences, there were practically no such differences in the sensitivities, specificities and false reassurance rates of the predictive tools. Each predictive tool used in clinical practice for patient and physician decision on further axillary treatment of SN-positive patients may require individual institutional validation; such validation may reveal different predictive tools to be the best in different institutions.

  12. Nutrition Screening Tools and the Prediction of Clinical Outcomes among Chinese Hospitalized Gastrointestinal Disease Patients

    PubMed Central

    Wang, Fang; Chen, Wei; Bruening, Kay Stearns; Raj, Sudha

    2016-01-01

    Nutrition risk Screening 2002 (NRS-2002) and Subjective Global Assessment (SGA) are widely used screening tools but have not been compared in a Chinese population. We conducted secondary data analysis of a cross-sectional study which included 332 hospitalized gastrointestinal disease patients, collected by the Gastrointestinal department of Peking Union Medical College Hospital (PUMCH) in 2008. Results of NRS-2002 and SGA screening tools, complications, length of stay (LOS), cost, and death were measured. The agreement between the tools was assessed via Kappa (κ) statistics. The performance of NRS-2002 and SGA in predicting LOS and cost was assessed via linear regression. The complications and death prediction of tools was assessed using receiver operating characteristic (ROC) curves. NRS-2002 and SGA identified nutrition risk at 59.0% and 45.2% respectively. Moderate agreement (κ >0.50) between the two tools was found among all age groups except individuals aged ≤ 20, which only slight agreement was found (κ = 0.087). NRS-2002 (R square 0.130) and SGA (R square 0.140) did not perform differently in LOS prediction. The cost prediction of NRS-2002 (R square 0.198) and SGA (R square 0.190) were not significantly different. There was no difference between NRS-2002 (infectious complications: area under ROC (AUROC) = 0.615, death: AUROC = 0.810) and SGA (infectious complications: AUROC = 0.600, death: AUROC = 0.846) in predicting infectious complication and death, but NRS-2002 (0.738) seemed to perform better than SGA (0.552) in predicting non-infectious complications. The risk of malnutrition among patients was high. NRS-2002 and SGA have similar capacity to predict LOS, cost, infectious complications and death, but NRS-2002 performed better in predicting non-infectious complications. PMID:27490480

  13. Towards early software reliability prediction for computer forensic tools (case study).

    PubMed

    Abu Talib, Manar

    2016-01-01

    Versatility, flexibility and robustness are essential requirements for software forensic tools. Researchers and practitioners need to put more effort into assessing this type of tool. A Markov model is a robust means for analyzing and anticipating the functioning of an advanced component based system. It is used, for instance, to analyze the reliability of the state machines of real time reactive systems. This research extends the architecture-based software reliability prediction model for computer forensic tools, which is based on Markov chains and COSMIC-FFP. Basically, every part of the computer forensic tool is linked to a discrete time Markov chain. If this can be done, then a probabilistic analysis by Markov chains can be performed to analyze the reliability of the components and of the whole tool. The purposes of the proposed reliability assessment method are to evaluate the tool's reliability in the early phases of its development, to improve the reliability assessment process for large computer forensic tools over time, and to compare alternative tool designs. The reliability analysis can assist designers in choosing the most reliable topology for the components, which can maximize the reliability of the tool and meet the expected reliability level specified by the end-user. The approach of assessing component-based tool reliability in the COSMIC-FFP context is illustrated with the Forensic Toolkit Imager case study.

  14. Multiphase flow modeling: A tool to aid in scale up of processes

    NASA Astrophysics Data System (ADS)

    Nandakumar, Krishnaswamy

    2010-10-01

    Multiphase flows are ubiquitous in chemical processing industries. Traditional approach has been to ignore fluid dynamical effects by invoking simplifying assumptions of homogeneity, but pay the price during scale-up of processes. The question that I address is ``Can Multiphase flow modeling come to our rescue in minimizing the need for pilot scale experiments?'' On the fundamental side, we have developed algorithms for direct numerical simulation of multiphase flows. For dispersed rigid particles as in suspension flows, sedimentation etc, we couple the Navier-Stokes equations with the rigid body dynamics in a rigorous fashion to track the particle motion in a fluid. For deformable bubbles/droplets dispersed in another fluid, we also track their motion in an Eulerian grid. The two classes of algorithms show great promise in attempting direct simulation of multiphase flows, from which we can extract statistically meaningful average behavior of suspensions or bubbly flows. On the other hand, there is an immediate need to study flow of complex fluids of industrial importance. Such cases include polymer blending processes, erosion in pipelines and process vessels and mass transfer in packed beds. In such studies we use volume averaged equations as the basis of flow models coupled with experimental validation of such predictions in an effort to develop scale invariant closure models that are needed as part of the volume averaged flow models.

  15. Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid

    SciTech Connect

    Etingov, Pavel; Makarov, PNNL Yuri; Subbarao, PNNL Kris; PNNL,

    2014-03-03

    RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.

  16. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    NASA Astrophysics Data System (ADS)

    Miles, M.; Karki, U.; Hovanski, Y.

    2014-10-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11-14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge® software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within 4%, and the position of the joint interface to within 10%, of the experimental results.

  17. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    SciTech Connect

    Miles, Michael; Karki, U.; Hovanski, Yuri

    2014-10-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11–14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge* software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within percent, and the position of the joint interface to within 10 percent, of the experimental results.

  18. Musite, a Tool for Global Prediction of General and Kinase-specific Phosphorylation Sites*

    PubMed Central

    Gao, Jianjiong; Thelen, Jay J.; Dunker, A. Keith; Xu, Dong

    2010-01-01

    Reversible protein phosphorylation is one of the most pervasive post-translational modifications, regulating diverse cellular processes in various organisms. High throughput experimental studies using mass spectrometry have identified many phosphorylation sites, primarily from eukaryotes. However, the vast majority of phosphorylation sites remain undiscovered, even in well studied systems. Because mass spectrometry-based experimental approaches for identifying phosphorylation events are costly, time-consuming, and biased toward abundant proteins and proteotypic peptides, in silico prediction of phosphorylation sites is potentially a useful alternative strategy for whole proteome annotation. Because of various limitations, current phosphorylation site prediction tools were not well designed for comprehensive assessment of proteomes. Here, we present a novel software tool, Musite, specifically designed for large scale predictions of both general and kinase-specific phosphorylation sites. We collected phosphoproteomics data in multiple organisms from several reliable sources and used them to train prediction models by a comprehensive machine-learning approach that integrates local sequence similarities to known phosphorylation sites, protein disorder scores, and amino acid frequencies. Application of Musite on several proteomes yielded tens of thousands of phosphorylation site predictions at a high stringency level. Cross-validation tests show that Musite achieves some improvement over existing tools in predicting general phosphorylation sites, and it is at least comparable with those for predicting kinase-specific phosphorylation sites. In Musite V1.0, we have trained general prediction models for six organisms and kinase-specific prediction models for 13 kinases or kinase families. Although the current pretrained models were not correlated with any particular cellular conditions, Musite provides a unique functionality for training customized prediction models

  19. Cerebral aneurysm treatment using flow-diverting stents: in-vivo visualization of flow alterations by parametric colour coding to predict aneurysmal occlusion: preliminary results.

    PubMed

    Gölitz, Philipp; Struffert, Tobias; Rösch, Julie; Ganslandt, Oliver; Knossalla, Frauke; Doerfler, Arnd

    2015-02-01

    After deployment of flow-diverting stents (FDS), complete aneurysm occlusion is not predictable. This study investigated whether parametric colour coding (PCC) could allow in vivo visualization of flow alterations induced by FDS and identify favourable or adverse flow modulations. Thirty-six patients treated by FDS were analyzed. Preinterventional and postinterventional DSA-series were postprocessed by PCC and time-density curves (TDCs) were calculated. The parameters aneurysmal inflow, outflow, and relative time-to-peak (rTTP) were calculated. Preinterventional and postinterventional values were compared and related to occlusion rate. Postinterventional inflow showed a mean reduction of 37%, outflow of 51%, and rTTP a prolongation of 82%. Saccular aneurysm occlusion occurred if a reduction of at least 15% was achieved for inflow and 35% for outflow (sensitivity: 89%, specificity: 82%). Unchanged outflow and a slightly prolonged rTTP were associated with growth in one fusiform aneurysm. PCC allows visualization of flow alterations after FDS treatment, illustrating "flow diverting effects" by the TDC shape and indicating mainly aneurysmal outflow and lesser inflow changes. Quantifiable parameters (inflow, outflow, rTTP) can be obtained, thresholds for predicting aneurysm occlusion determined, and adverse flow modulations assumed. As a rapid intraprocedural tool, PCC might support the decision to implant more than one FDS. • After deployment of a flow-diverting stent, complete aneurysm occlusion is unpredictable. • Parametric colour coding offers new options for visualizing in vivo flow alterations non-invasively. • Quantifiable parameters, i.e., aneurysmal inflow/outflow can be obtained allowing prognostic stratification. • Rapid, intraprocedural application allows treatment monitoring, potentially contributing to patient safety.

  20. Predicting multidimensional annular flows with a locally based two-fluid model

    SciTech Connect

    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.

  1. Star-Shaped Fluid Flow Tool for Use in Making Differential Measurements

    NASA Technical Reports Server (NTRS)

    England, John Dwight (Inventor); Kelley, Anthony R. (Inventor); Cronise, Raymond J. (Inventor)

    2014-01-01

    A fluid flow tool's plate-like structure has a ring portion defining a flow hole, a support portion extending radially away from the ring portion and adapted to be coupled to conduit wall, and extensions extending radially away from the ring portion such that a periphery of the plate-like structure is defined by the extensions and trough regions between adjacent extensions. One or more ports formed in the ring portion are in fluid communication with the flow hole. A first manifold in the plate-like structure is in fluid communication with each port communicating with the flow hole. One or more ports are formed in the periphery of the plate-like structure. A second manifold in the plate-like structure is in fluid communication with each port formed in the periphery. The first and second manifolds extend through the plate-like structure to terminate and be accessible at the conduit wall.

  2. Ultrasound: An Unexplored Tool for Blood Flow Visualization and Hemodynamic Measurements

    NASA Astrophysics Data System (ADS)

    Shung, K. Kirk; Paeng, Dong-Guk

    2003-05-01

    Ultrasonic scattering by blood has been studied both theoretically and experimentally for a better characterization of the performance of ultrasonic devices. In the course of these investigations it became clear that ultrasonic scattering from blood is critically related to the hematological and hemodynamic properties of blood, including hematocrit, plasma protein concentration, flow rate, and flow cycle duration, to name a few parameters. An unexpected conclusion from this work is that ultrasound appears to be a totally unexplored and ignored tool for blood flow visualization and hemodynamic measurements. Two unique hemodynamic phenomena have been observed: the black hole, a low echogenic zone in the center stream of a blood vessel, and the collapsing ring, an hyperechogenic ring converging from the vessel periphery toward the center, and eventually collapsing during pulsatile flow. They seemed to be resulted from the spatial and temporal variations of the shear rate and acceleration in the vessel.

  3. Epitope prediction based on random peptide library screening: benchmark dataset and prediction tools evaluation.

    PubMed

    Sun, Pingping; Chen, Wenhan; Huang, Yanxin; Wang, Hongyan; Ma, Zhiqiang; Lv, Yinghua

    2011-06-16

    Epitope prediction based on random peptide library screening has become a focus as a promising method in immunoinformatics research. Some novel software and web-based servers have been proposed in recent years and have succeeded in given test cases. However, since the number of available mimotopes with the relevant structure of template-target complex is limited, a systematic evaluation of these methods is still absent. In this study, a new benchmark dataset was defined. Using this benchmark dataset and a representative dataset, five examples of the most popular epitope prediction software products which are based on random peptide library screening have been evaluated. Using the benchmark dataset, in no method did performance exceed a 0.42 precision and 0.37 sensitivity, and the MCC scores suggest that the epitope prediction results of these software programs are greater than random prediction about 0.09-0.13; while using the representative dataset, most of the values of these performance measures are slightly improved, but the overall performance is still not satisfactory. Many test cases in the benchmark dataset cannot be applied to these pieces of software due to software limitations. Moreover chances are that these software products are overfitted to the small dataset and will fail in other cases. Therefore finding the correlation between mimotopes and genuine epitope residues is still far from resolved and much larger dataset for mimotope-based epitope prediction is desirable.

  4. A computational model based on fibrin accumulation for the prediction of stasis thrombosis following flow-diverting treatment in cerebral aneurysms.

    PubMed

    Ou, Chubin; Huang, Wei; Yuen, Matthew Ming-Fai

    2017-01-01

    Flow diverters, the specially designed low porosity stents, have been used to redirect blood flow from entering aneurysm, which induces flow stasis in aneurysm and promote thrombosis for repairing aneurysm. However, it is not clear how thrombus develops following flow-diversion treatment. Our objective was to develop a computation model for the prediction of stasis-induced thrombosis following flow-diversion treatment in cerebral aneurysms. We proposed a hypothesis to initiate coagulation following flow-diversion treatment. An experimental model was used by ligating rat's right common carotid artery (RCCA) to create flow-stasis environment. Thrombus formed in RCCA as a result of flow stasis. The fibrin distributions in different sections along the axial length of RCCA were measured. The fibrin distribution predicted by our computational model displayed a trend of increase from the proximal neck to the distal tip, consistent with the experimental results on rats. The model was applied on a saccular aneurysm treated with flow diverter to investigate thrombus development following flow diversion. Thrombus was predicted to form inside the sac, and the aneurysm was occluded with only a small remnant neck remained. Our model can serve as a tool to evaluate flow-diversion treatment outcome and optimize the design of flow diverters.

  5. Prediction of flow rates through an orifice at pressures corresponding to the transition between molecular and isentropic flow

    SciTech Connect

    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.

  6. Software tools for simultaneous data visualization and T cell epitopes and disorder prediction in proteins.

    PubMed

    Jandrlić, Davorka R; Lazić, Goran M; Mitić, Nenad S; Pavlović, Mirjana D

    2016-04-01

    We have developed EpDis and MassPred, extendable open source software tools that support bioinformatic research and enable parallel use of different methods for the prediction of T cell epitopes, disorder and disordered binding regions and hydropathy calculation. These tools offer a semi-automated installation of chosen sets of external predictors and an interface allowing for easy application of the prediction methods, which can be applied either to individual proteins or to datasets of a large number of proteins. In addition to access to prediction methods, the tools also provide visualization of the obtained results, calculation of consensus from results of different methods, as well as import of experimental data and their comparison with results obtained with different predictors. The tools also offer a graphical user interface and the possibility to store data and the results obtained using all of the integrated methods in the relational database or flat file for further analysis. The MassPred part enables a massive parallel application of all integrated predictors to the set of proteins. Both tools can be downloaded from http://bioinfo.matf.bg.ac.rs/home/downloads.wafl?cat=Software. Appendix A includes the technical description of the created tools and a list of supported predictors.

  7. 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.

  8. Noise produced by turbulent flow into a rotor: Users manual for atmospheric turbulence prediction and mean flow and turbulence contraction prediction

    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.

  9. Systematic review of clinical prediction tools and prognostic factors in aneurysmal subarachnoid hemorrhage.

    PubMed

    Lo, Benjamin W Y; Fukuda, Hitoshi; Nishimura, Yusuke; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

    2015-01-01

    Clinical prediction tools assist in clinical outcome prediction. They quantify the relative contributions of certain variables and condense information that identifies important indicators or predictors to a targeted condition. This systematic review synthesizes and critically appraises the methodologic quality of studies that derive both clinical predictors and clinical predictor tools used to determine outcome prognosis in patients suffering from aneurysmal subarachnoid hemorrhage (SAH). This systematic review included prospective and retrospective cohort studies, and randomized controlled trials (RCTs) investigating prognostic factors and clinical prediction tools associated with determining the neurologic outcome in adult patients with aneurysmal SAH. Twenty-two studies were included in this systemic review. Independent, confounding, and outcome variables were studied. Methodologic quality of individual studies was also analyzed. Included were 3 studies analyzing databases from RCTs, 8 prospective cohort studies, and 11 retrospective cohort studies. The most frequently retained significant clinical prognostic factors for long-term neurologic outcome prediction include age, neurological grade, blood clot thickness, and aneurysm size. Systematic reviews for clinical prognostic factors and clinical prediction tools in aneurysmal SAH face a number of methodological challenges. These include within and between study patient heterogeneity, regional variations in treatment protocols, patient referral biases, and differences in treatment, and prognosis viewpoints across different cultures.

  10. Atomic Oxygen Erosion Yield Predictive Tool for Spacecraft Polymers in Low Earth Orbit

    NASA Technical Reports Server (NTRS)

    Bank, Bruce A.; de Groh, Kim K.; Backus, Jane A.

    2008-01-01

    A predictive tool was developed to estimate the low Earth orbit (LEO) atomic oxygen erosion yield of polymers based on the results of the Polymer Erosion and Contamination Experiment (PEACE) Polymers experiment flown as part of the Materials International Space Station Experiment 2 (MISSE 2). The MISSE 2 PEACE experiment accurately measured the erosion yield of a wide variety of polymers and pyrolytic graphite. The 40 different materials tested were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The resulting erosion yield data was used to develop a predictive tool which utilizes chemical structure and physical properties of polymers that can be measured in ground laboratory testing to predict the in-space atomic oxygen erosion yield of a polymer. The properties include chemical structure, bonding information, density and ash content. The resulting predictive tool has a correlation coefficient of 0.914 when compared with actual MISSE 2 space data for 38 polymers and pyrolytic graphite. The intent of the predictive tool is to be able to make estimates of atomic oxygen erosion yields for new polymers without requiring expensive and time consumptive in-space testing.

  11. ReactPRED: a tool to predict and analyze biochemical reactions.

    PubMed

    Sivakumar, Tadi Venkata; Giri, Varun; Park, Jin Hwan; Kim, Tae Yong; Bhaduri, Anirban

    2016-11-15

    Biochemical pathways engineering is often used to synthesize or degrade target chemicals. In silico screening of the biochemical transformation space allows predicting feasible reactions, constituting these pathways. Current enabling tools are customized to predict reactions based on pre-defined biochemical transformations or reaction rule sets. Reaction rule sets are usually curated manually and tailored to specific applications. They are not exhaustive. In addition, current systems are incapable of regulating and refining data with an aim to tune specificity and sensitivity. A robust and flexible tool that allows automated reaction rule set creation along with regulated pathway prediction and analyses is a need. ReactPRED aims to address the same. ReactPRED is an open source flexible and customizable tool enabling users to predict biochemical reactions and pathways. The tool allows automated reaction rule creation from a user defined reaction set. Additionally, reaction rule degree and rule tolerance features allow refinement of predicted data. It is available as a flexible graphical user interface and a console application. ReactPRED is available at: https://sourceforge.net/projects/reactpred/ CONTACT: anirban.b@samsung.com or ty76.kim@samsung.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. Recent progresses in the exploration of machine learning methods as in-silico ADME prediction tools.

    PubMed

    Tao, L; Zhang, P; Qin, C; Chen, S Y; Zhang, C; Chen, Z; Zhu, F; Yang, S Y; Wei, Y Q; Chen, Y Z

    2015-06-23

    In-silico methods have been explored as potential tools for assessing ADME and ADME regulatory properties particularly in early drug discovery stages. Machine learning methods, with their ability in classifying diverse structures and complex mechanisms, are well suited for predicting ADME and ADME regulatory properties. Recent efforts have been directed at the broadening of application scopes and the improvement of predictive performance with particular focuses on the coverage of ADME properties, and exploration of more diversified training data, appropriate molecular features, and consensus modeling. Moreover, several online machine learning ADME prediction servers have emerged. Here we review these progresses and discuss the performances, application prospects and challenges of exploring machine learning methods as useful tools in predicting ADME and ADME regulatory properties. Copyright © 2015. Published by Elsevier B.V.

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

    NASA Astrophysics Data System (ADS)

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

    2017-05-01

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

  14. Studies on effects of boundary conditions in confined turbulent flow predictions

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Chen, C. P.

    1985-01-01

    The differences in k epsilon model predictions of plane and axisymmetric expansion flows is investigated. The prediction of the coaxial jet for different velocity ratios of the annular to central jet is presented. The effects of inlet kinetic energy and the energy dissipation rate profiles are investigated for swirling and nonswirling flows. The effects of expansion ration and Reynolds number on the reattachment length are also presented. The results show that the inlet k and epsilon profiles have the most significant effect on the reattachment length and flow redevelopment for the case of coaxial jet of high velocity ratio. A comparison of k epsilon model predictions for the pipe expansion flow by the PHOENICS and TEACH codes reveals some discrepancies in the predicted results. TEACH prediction seems to produce unrealistic kinetic energy profiles in some regions of the flow. PHOENICS code produces a long tail in the recirculation region under certain conditions.

  15. Low Dimensional Tools for Flow-Structure Interaction Problems: Application to Micro Air Vehicles

    NASA Technical Reports Server (NTRS)

    Schmit, Ryan F.; Glauser, Mark N.; Gorton, Susan A.

    2003-01-01

    A low dimensional tool for flow-structure interaction problems based on Proper Orthogonal Decomposition (POD) and modified Linear Stochastic Estimation (mLSE) has been proposed and was applied to a Micro Air Vehicle (MAV) wing. The method utilizes the dynamic strain measurements from the wing to estimate the POD expansion coefficients from which an estimation of the velocity in the wake can be obtained. For this experiment the MAV wing was set at five different angles of attack, from 0 deg to 20 deg. The tunnel velocities varied from 44 to 58 ft/sec with corresponding Reynolds numbers of 46,000 to 70,000. A stereo Particle Image Velocimetry (PIV) system was used to measure the wake of the MAV wing simultaneously with the signals from the twelve dynamic strain gauges mounted on the wing. With 20 out of 2400 POD modes, a reasonable estimation of the flow flow was observed. By increasing the number of POD modes, a better estimation of the flow field will occur. Utilizing the simultaneously sampled strain gauges and flow field measurements in conjunction with mLSE, an estimation of the flow field with lower energy modes is reasonable. With these results, the methodology for estimating the wake flow field from just dynamic strain gauges is validated.

  16. Issues and approach to develop validated analysis tools for hypersonic flows: One perspective

    NASA Technical Reports Server (NTRS)

    Deiwert, George S.

    1992-01-01

    Critical issues concerning the modeling of low-density hypervelocity flows where thermochemical nonequilibrium effects are pronounced are discussed. Emphasis is on the development of validated analysis tools. A description of the activity in the Ames Research Center's Aerothermodynamics Branch is also given. Inherent in the process is a strong synergism between ground test and real-gas computational fluid dynamics (CFD). Approaches to develop and/or enhance phenomenological models and incorporate them into computational flow-field simulation codes are discussed. These models have been partially validated with experimental data for flows where the gas temperature is raised (compressive flows). Expanding flows, where temperatures drop, however, exhibit somewhat different behavior. Experimental data for these expanding flow conditions are sparse; reliance must be made on intuition and guidance from computational chemistry to model transport processes under these conditions. Ground-based experimental studies used to provide necessary data for model development and validation are described. Included are the performance characteristics of high-enthalpy flow facilities, such as shock tubes and ballistic ranges.

  17. On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

    NASA Technical Reports Server (NTRS)

    Jen, Chian-Li; Tilwick, Leon

    2000-01-01

    This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

  18. On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

    NASA Technical Reports Server (NTRS)

    Jen, Chian-Li; Tilwick, Leon

    2000-01-01

    This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

  19. Cost Minimization Using an Artificial Neural Network Sleep Apnea Prediction Tool for Sleep Studies

    PubMed Central

    Teferra, Rahel A.; Grant, Brydon J. B.; Mindel, Jesse W.; Siddiqi, Tauseef A.; Iftikhar, Imran H.; Ajaz, Fatima; Aliling, Jose P.; Khan, Meena S.; Hoffmann, Stephen P.

    2014-01-01

    Rationale: More than a million polysomnograms (PSGs) are performed annually in the United States to diagnose obstructive sleep apnea (OSA). Third-party payers now advocate a home sleep test (HST), rather than an in-laboratory PSG, as the diagnostic study for OSA regardless of clinical probability, but the economic benefit of this approach is not known. Objectives: We determined the diagnostic performance of OSA prediction tools including the newly developed OSUNet, based on an artificial neural network, and performed a cost-minimization analysis when the prediction tools are used to identify patients who should undergo HST. Methods: The OSUNet was trained to predict the presence of OSA in a derivation group of patients who underwent an in-laboratory PSG (n = 383). Validation group 1 consisted of in-laboratory PSG patients (n = 149). The network was trained further in 33 patients who underwent HST and then was validated in a separate group of 100 HST patients (validation group 2). Likelihood ratios (LRs) were compared with two previously published prediction tools. The total costs from the use of the three prediction tools and the third-party approach within a clinical algorithm were compared. Measurements and Main Results: The OSUNet had a higher +LR in all groups compared with the STOP-BANG and the modified neck circumference (MNC) prediction tools. The +LRs for STOP-BANG, MNC, and OSUNet in validation group 1 were 1.1 (1.0–1.2), 1.3 (1.1–1.5), and 2.1 (1.4–3.1); and in validation group 2 they were 1.4 (1.1–1.7), 1.7 (1.3–2.2), and 3.4 (1.8–6.1), respectively. With an OSA prevalence less than 52%, the use of all three clinical prediction tools resulted in cost savings compared with the third-party approach. Conclusions: The routine requirement of an HST to diagnose OSA regardless of clinical probability is more costly compared with the use of OSA clinical prediction tools that identify patients who should undergo this procedure when OSA is expected to

  20. 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

  1. VU-flow: a visualization tool for analyzing navigation in virtual environments.

    PubMed

    Chittaro, Luca; Ranon, Roberto; Ieronutti, Lucio

    2006-01-01

    This paper presents a tool for the visual analysis of navigation patterns of moving entities, such as users, virtual characters, or vehicles in 3D Virtual Environments (VEs). The tool, called VU-Flow, provides a set of interactive visualizations that highlight interesting navigation behaviors of single or groups of moving entities that were the VE together or separately. The visualizations help to improve the design of VEs and to study the navigation behavior of users, e.g., during controlled experiments. Besides VEs, the proposed techniques could also be applied to visualize real-world data recorded by positioning systems, allowing one to employ VU-Flow in domains such as urban planning, transportation, and emergency response.

  2. PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites

    PubMed Central

    Perry, Andrew J.; Akutsu, Tatsuya; Webb, Geoffrey I.; Whisstock, James C.; Pike, Robert N.

    2012-01-01

    The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using

  3. Prediction of critical grout parameters: critical flow rate

    SciTech Connect

    Tallent, O.K.; McDaniel, E.W.; Godsey, T.T.; Dodson, K.E.

    1986-01-01

    Waste disposal is rapidly becoming one of the most important technological endeavors of our time and fixation of waste in cement-based materials is an important part of the endeavor. Investigations of given wastes are usually individually conducted and reported. In this study, data obtained from investigation of critical flow rates for three distinctly different wastes are correlated with apparent viscosity data via a single empirical equation. Critical flow rate, which is an important variable in waste grout work, is defined as the flow rate at which a grout must be pumped through a reference pipe to obtain turbulent flow. It is important that the grout flow be turbulent since laminar flow allows caking on pipe walls and causes eventual plugging. The three wastes used in this study can be characterized as containing: (1) high nitrate, carbonate, and sulfate; (2) high phosphate; and (3) high fluoride, ammonium, and suspended solids waste. The measurements of apparent viscosity (grouts are non-Newtonian fluids) and other measurements to obtain data to calculate the critical flow rates were made using a Fann-Direct Reading Viscometer, Model 35A.

  4. A Tool Preference Choice Method for RNA Secondary Structure Prediction by SVM with Statistical Tests

    PubMed Central

    Hor, Chiou-Yi; Yang, Chang-Biau; Chang, Chia-Hung; Tseng, Chiou-Ting; Chen, Hung-Hsin

    2013-01-01

    The Prediction of RNA secondary structures has drawn much attention from both biologists and computer scientists. Many useful tools have been developed for this purpose. These tools have their individual strengths and weaknesses. As a result, based on support vector machines (SVM), we propose a tool choice method which integrates three prediction tools: pknotsRG, RNAStructure, and NUPACK. Our method first extracts features from the target RNA sequence, and adopts two information-theoretic feature selection methods for feature ranking. We propose a method to combine feature selection and classifier fusion in an incremental manner. Our test data set contains 720 RNA sequences, where 225 pseudoknotted RNA sequences are obtained from PseudoBase, and 495 nested RNA sequences are obtained from RNA SSTRAND. The method serves as a preprocessing way in analyzing RNA sequences before the RNA secondary structure prediction tools are employed. In addition, the performance of various configurations is subject to statistical tests to examine their significance. The best base-pair accuracy achieved is 75.5%, which is obtained by the proposed incremental method, and is significantly higher than 68.8%, which is associated with the best predictor, pknotsRG. PMID:23641141

  5. The CFD calculations as a main tool for the mixed-flow pump modernization

    NASA Astrophysics Data System (ADS)

    Skrzypacz, J.; Szulc, P.

    2017-08-01

    The primary aim of the project was to increase cavitation performance of a big mixed-flow pump. The CFD software was used as a main research tool. The two kinds of numerical models were used to solve this problem - both were presented. The results were verified on the basis of comparison with experimental results obtained for real and model pumps. The interesting way of estimating cavitation performance was presented. The pump characteristics before and after the modernisation were shown.

  6. Identifying and Validating Selection Tools for Predicting Officer Performance and Retention

    DTIC Science & Technology

    2017-05-01

    Research Note 2017-01 Identifying and Validating Selection Tools for Predicting Officer Performance and Retention...Teresa L. Russell, Editor Cheryl J. Paullin, Editor Human Resources Research Organization Peter J. Legree, Editor Robert N. Kilcullen, Editor...Mark C. Young, Editor U.S. Army Research Institute May 2017 United States Army Research Institute for the Behavioral and Social

  7. Using SWPBS Expectations as a Screening Tool to Predict Behavioral Risk in Middle School

    ERIC Educational Resources Information Center

    Burke, Mack D.; Davis, John L.; Hagan-Burke, Shanna; Lee, Yuan-Hsuan; Fogarty, Melissa Shea

    2014-01-01

    School-wide positive behavior support (SWPBS) focuses on promoting social competence through the establishment of behavior expectations that are explicitly taught and reinforced by all teachers across all settings. This study investigated the validity of using adherence to SWPBS behavior expectations as a screening tool for predicting behavior…

  8. Tools for Sequence-Based miRNA Target Prediction: What to Choose?

    PubMed Central

    Riffo-Campos, Ángela L.; Riquelme, Ismael; Brebi-Mieville, Priscilla

    2016-01-01

    MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists. PMID:27941681

  9. Tools for Sequence-Based miRNA Target Prediction: What to Choose?

    PubMed

    Riffo-Campos, Ángela L; Riquelme, Ismael; Brebi-Mieville, Priscilla

    2016-12-09

    MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists.

  10. Predictive Validity of Pressure Ulcer Risk Assessment Tools for Elderly: A Meta-Analysis.

    PubMed

    Park, Seong-Hi; Lee, Young-Shin; Kwon, Young-Mi

    2016-04-01

    Preventing pressure ulcers is one of the most challenging goals existing for today's health care provider. Currently used tools which assess risk of pressure ulcer development rarely evaluate the accuracy of predictability, especially in older adults. The current study aimed at providing a systemic review and meta-analysis of 29 studies using three pressure ulcer risk assessment tools: Braden, Norton, and Waterlow Scales. Overall predictive validities of pressure ulcer risks in the pooled sensitivity and specificity indicated a similar range with a moderate accuracy level in all three scales, while heterogeneity showed more than 80% variability among studies. The studies applying the Braden Scale used five different cut-off points representing the primary cause of heterogeneity. Results indicate that commonly used screening tools for pressure ulcer risk have limitations regarding validity and accuracy for use with older adults due to heterogeneity among studies. © The Author(s) 2015.

  11. RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

    PubMed

    Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

    2012-01-01

    RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

  12. Development of Prediction System for Environmental Burden for Machine Tool Operation

    NASA Astrophysics Data System (ADS)

    Narita, Hirohisa; Kawamura, Hiroshi; Norihisa, Takashi; Chen, Lian-Yi; Fujimoto, Hideo; Hasebe, Takao

    Recently, some activities for environmental protection have been attempted to reduce environmental burdens in many fields. The manufacturing field also requires such reduction. Hence, a prediction system for environmental burden for machining operation is proposed based on the Life Cycle Assessment (LCA) policy for the future manufacturing system in this research. This system enables the calculation of environmental burden (equivalent CO2 emission) due to the electric consumption of machine tool components, cutting tool status, coolant quantity, lubricant oil quantity and metal chip quantity, and provides accurate information of environmental burden of the machining process by considering some activities related to machine tool operation. In this paper, the development of the prediction system is described. As a case study, two Numerical Control (NC) programs that manufacture a simple shape are evaluated to show the feasibility of the proposed system.

  13. Tool design in friction stir processing: dynamic forces and material flow

    SciTech Connect

    D. E. Clark; K. S. Miller; C. R. Tolle

    2006-08-01

    Friction stir processing involves severe plastic flow within the material; the nature of this flow determines the final morphology of the weld, the resulting microstructures, and the presence or absence of defects such as internal cavities or "wormholes." The forces causing this plastic flow are a function of process parameters, including spindle speed, travel speed, and tool design and angle. Some of these forces are directly applied or a result of the mechanical constraints and compliance of the apparatus, while others are resolved forces resulting from an interaction of these applied forces and tool forces governed by processing parameters, and can be diminished or even reversed in sign with appropriate choices of process parameters. The present investigation is concerned mostly with the friction stir processing of 6061-T6 aluminum plates in a low-cost apparatus built from a commercial milling machine. A rotating dynamometer allows in-process measurement of actual spindle speed, torque, and forces in the x-, y-, and z-directions, as well as force control on these axes. Two main types of tool, both unthreaded, were used. The first had a pin about 4 mm in diameter and 4 mm in length, with a shoulder about 10 mm in diameter, and produced wormhole defects; the second, with a tapered pin about 5 mm long, a base diameter of about 6 mm, a tip diameter of about 4 mm, and a shoulder diameter (flat or dished) of about 19 mm, produced sound welds over a wide range of parameters.

  14. Development of predictive simulation capability for reactive multiphase flow

    SciTech Connect

    VanderHeyden, W.B.; Kendrick, B.K.

    1998-12-31

    This is the final report of a Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of the project was to develop a self-sustained research program for advanced computer simulation of industrial reactive multiphase flows. The prototype research problem was a three-phase alumina precipitator used in the Bayer process, a key step in aluminum refining. Accomplishments included the development of an improved reaction mechanism of the alumina precipitation growth process, the development of an efficient methods for handling particle size distribution in multiphase flow simulation codes, the incorporation of precipitation growth and agglomeration kinetics in LANL's CFDLIB multiphase flow code library and the evaluation of multiphase turbulence closure models for bubbly flow simulations.

  15. 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.

  16. 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.

  17. Intuitive Visualization of Transient Flow: Towards a Full 3D Tool

    NASA Astrophysics Data System (ADS)

    Michel, Isabel; Schröder, Simon; Seidel, Torsten; König, Christoph

    2015-04-01

    Visualization of geoscientific data is a challenging task especially when targeting a non-professional audience. In particular, the graphical presentation of transient vector data can be a significant problem. With STRING Fraunhofer ITWM (Kaiserslautern, Germany) in collaboration with delta h Ingenieurgesellschaft mbH (Witten, Germany) developed a commercial software for intuitive 2D visualization of 3D flow problems. Through the intuitive character of the visualization experts can more easily transport their findings to non-professional audiences. In STRING pathlets moving with the flow provide an intuition of velocity and direction of both steady-state and transient flow fields. The visualization concept is based on the Lagrangian view of the flow which means that the pathlets' movement is along the direction given by pathlines. In order to capture every detail of the flow an advanced method for intelligent, time-dependent seeding of the pathlets is implemented based on ideas of the Finite Pointset Method (FPM) originally conceived at and continuously developed by Fraunhofer ITWM. Furthermore, by the same method pathlets are removed during the visualization to avoid visual cluttering. Additional scalar flow attributes, for example concentration or potential, can either be mapped directly to the pathlets or displayed in the background of the pathlets on the 2D visualization plane. The extensive capabilities of STRING are demonstrated with the help of different applications in groundwater modeling. We will discuss the strengths and current restrictions of STRING which have surfaced during daily use of the software, for example by delta h. Although the software focusses on the graphical presentation of flow data for non-professional audiences its intuitive visualization has also proven useful to experts when investigating details of flow fields. Due to the popular reception of STRING and its limitation to 2D, the need arises for the extension to a full 3D tool

  18. 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.

  19. SECISearch3 and Seblastian: new tools for prediction of SECIS elements and selenoproteins.

    PubMed

    Mariotti, Marco; Lobanov, Alexei V; Guigo, Roderic; Gladyshev, Vadim N

    2013-08-01

    Selenoproteins are proteins containing an uncommon amino acid selenocysteine (Sec). Sec is inserted by a specific translational machinery that recognizes a stem-loop structure, the SECIS element, at the 3' UTR of selenoprotein genes and recodes a UGA codon within the coding sequence. As UGA is normally a translational stop signal, selenoproteins are generally misannotated and designated tools have to be developed for this class of proteins. Here, we present two new computational methods for selenoprotein identification and analysis, which we provide publicly through the web servers at http://gladyshevlab.org/SelenoproteinPredictionServer or http://seblastian.crg.es. SECISearch3 replaces its predecessor SECISearch as a tool for prediction of eukaryotic SECIS elements. Seblastian is a new method for selenoprotein gene detection that uses SECISearch3 and then predicts selenoprotein sequences encoded upstream of SECIS elements. Seblastian is able to both identify known selenoproteins and predict new selenoproteins. By applying these tools to diverse eukaryotic genomes, we provide a ranked list of newly predicted selenoproteins together with their annotated cysteine-containing homologues. An analysis of a representative candidate belonging to the AhpC family shows how the use of Sec in this protein evolved in bacterial and eukaryotic lineages.

  20. SECISearch3 and Seblastian: new tools for prediction of SECIS elements and selenoproteins

    PubMed Central

    Mariotti, Marco; Lobanov, Alexei V.; Guigo, Roderic; Gladyshev, Vadim N.

    2013-01-01

    Selenoproteins are proteins containing an uncommon amino acid selenocysteine (Sec). Sec is inserted by a specific translational machinery that recognizes a stem-loop structure, the SECIS element, at the 3′ UTR of selenoprotein genes and recodes a UGA codon within the coding sequence. As UGA is normally a translational stop signal, selenoproteins are generally misannotated and designated tools have to be developed for this class of proteins. Here, we present two new computational methods for selenoprotein identification and analysis, which we provide publicly through the web servers at http://gladyshevlab.org/SelenoproteinPredictionServer or http://seblastian.crg.es. SECISearch3 replaces its predecessor SECISearch as a tool for prediction of eukaryotic SECIS elements. Seblastian is a new method for selenoprotein gene detection that uses SECISearch3 and then predicts selenoprotein sequences encoded upstream of SECIS elements. Seblastian is able to both identify known selenoproteins and predict new selenoproteins. By applying these tools to diverse eukaryotic genomes, we provide a ranked list of newly predicted selenoproteins together with their annotated cysteine-containing homologues. An analysis of a representative candidate belonging to the AhpC family shows how the use of Sec in this protein evolved in bacterial and eukaryotic lineages. PMID:23783574

  1. Evaluation of in silico tools to predict the skin sensitization potential of chemicals.

    PubMed

    Verheyen, G R; Braeken, E; Van Deun, K; Van Miert, S

    2017-01-01

    Public domain and commercial in silico tools were compared for their performance in predicting the skin sensitization potential of chemicals. The packages were either statistical based (Vega, CASE Ultra) or rule based (OECD Toolbox, Toxtree, Derek Nexus). In practice, several of these in silico tools are used in gap filling and read-across, but here their use was limited to make predictions based on presence/absence of structural features associated to sensitization. The top 400 ranking substances of the ATSDR 2011 Priority List of Hazardous Substances were selected as a starting point. Experimental information was identified for 160 chemically diverse substances (82 positive and 78 negative). The prediction for skin sensitization potential was compared with the experimental data. Rule-based tools perform slightly better, with accuracies ranging from 0.6 (OECD Toolbox) to 0.78 (Derek Nexus), compared with statistical tools that had accuracies ranging from 0.48 (Vega) to 0.73 (CASE Ultra - LLNA weak model). Combining models increased the performance, with positive and negative predictive values up to 80% and 84%, respectively. However, the number of substances that were predicted positive or negative for skin sensitization in both models was low. Adding more substances to the dataset will increase the confidence in the conclusions reached. The insights obtained in this evaluation are incorporated in a web database www.asopus.weebly.com that provides a potential end user context for the scope and performance of different in silico tools with respect to a common dataset of curated skin sensitization data.

  2. A GIS-based Computational Tool for Multidimensional Flow Velocity by Acoustic Doppler Current Profilers

    NASA Astrophysics Data System (ADS)

    Kim, D.; Winkler, M.; Muste, M.

    2015-06-01

    Acoustic Doppler Current Profilers (ADCPs) provide efficient and reliable flow measurements compared to other tools for characteristics of the riverine environments. In addition to originally targeted discharge measurements, ADCPs are increasingly utilized to assess river flow characteristics. The newly developed VMS (Velocity Mapping Software) aims at providing an efficient process for quality assurance, mapping velocity vectors for visualization and facilitating comparison with physical and numerical model results. VMS was designed to provide efficient and smooth work flows for processing groups of transects. The software allows the user to select group of files and subsequently to conduct statistical and graphical quality assurance on the files as a group or individually as appropriate. VMS also enables spatial averaging in horizontal and vertical plane for ADCP data in a single or multiple transects over the same or consecutive cross sections. The analysis results are displayed in numerical and graphical formats.

  3. Three-dimensional computational prediction of cerebrospinal fluid flow in the human brain.

    PubMed

    Sweetman, Brian; Xenos, Michalis; Zitella, Laura; Linninger, Andreas A

    2011-02-01

    A three-dimensional model of the human cerebrospinal fluid (CSF) spaces is presented. Patient-specific brain geometries were reconstructed from magnetic resonance images. The model was validated by comparing the predicted flow rates with Cine phase-contrast MRI measurements. The model predicts the complex CSF flow patterns and pressures in the ventricular system and subarachnoid space of a normal subject. The predicted maximum rostral to caudal CSF flow in the pontine cistern precedes the maximum rostral to caudal flow in the ventricles by about 10% of the cardiac cycle. This prediction is in excellent agreement with the subject-specific flow data. The computational results quantify normal intracranial dynamics and provide a basis for analyzing diseased intracranial dynamics. Published by Elsevier Ltd.

  4. Three-dimensional computational prediction of cerebrospinal fluid flow in the human brain

    PubMed Central

    Sweetman, Brian; Xenos, Michalis; Zitella, Laura; Linninger, Andreas A.

    2011-01-01

    A three-dimensional model of the human cerebrospinal fluid (CSF) spaces is presented. Patient-specific brain geometries were reconstructed from magnetic resonance images. The model was validated by comparing the predicted flow rates with Cine phase-contrast MRI measurements. The model predicts the complex CSF flow patterns and pressures in the ventricular system and subarachnoid space of a normal subject. The predicted maximum rostral to caudal CSF flow in the pontine cistern precedes the maximum rostral to caudal flow in the ventricles by about 10% of the cardiac cycle. This prediction is in excellent agreement with the subject-specific flow data. The computational results quantify normal intracranial dynamics and provide a basis for analyzing diseased intracranial dynamics. PMID:21215965

  5. Statistical Tools And Artificial Intelligence Approaches To Predict Fracture In Bulk Forming Processes

    NASA Astrophysics Data System (ADS)

    Di Lorenzo, R.; Ingarao, G.; Fonti, V.

    2007-05-01

    The crucial task in the prevention of ductile fracture is the availability of a tool for the prediction of such defect occurrence. The technical literature presents a wide investigation on this topic and many contributions have been given by many authors following different approaches. The main class of approaches regards the development of fracture criteria: generally, such criteria are expressed by determining a critical value of a damage function which depends on stress and strain paths: ductile fracture is assumed to occur when such critical value is reached during the analysed process. There is a relevant drawback related to the utilization of ductile fracture criteria; in fact each criterion usually has good performances in the prediction of fracture for particular stress - strain paths, i.e. it works very well for certain processes but may provide no good results for other processes. On the other hand, the approaches based on damage mechanics formulation are very effective from a theoretical point of view but they are very complex and their proper calibration is quite difficult. In this paper, two different approaches are investigated to predict fracture occurrence in cold forming operations. The final aim of the proposed method is the achievement of a tool which has a general reliability i.e. it is able to predict fracture for different forming processes. The proposed approach represents a step forward within a research project focused on the utilization of innovative predictive tools for ductile fracture. The paper presents a comparison between an artificial neural network design procedure and an approach based on statistical tools; both the approaches were aimed to predict fracture occurrence/absence basing on a set of stress and strain paths data. The proposed approach is based on the utilization of experimental data available, for a given material, on fracture occurrence in different processes. More in detail, the approach consists in the analysis of

  6. 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.

  7. GIS-based prediction of stream chemistry using landscape composition, wet areas, and hydrological flow pathways

    NASA Astrophysics Data System (ADS)

    Tiwari, Tejshree; Lidman, Fredrik; Laudon, Hjalmar; Lidberg, William; Ågren, Anneli M.

    2017-01-01

    Landscape morphology exerts strong, scale-dependent controls on stream hydrology and biogeochemistry in heterogeneous catchments. We applied three descriptors of landscape structure at different spatial scales based on new geographic information system tools to predict variability in stream concentrations for a wide range of solutes (Al, Ba, Be, Ca, Fe, K, Mg, Na, S, Si, Sr, Sc, Co, Cr, Ni, Cu, As, Se, Rb, Y, Cd, Sb, Cs, La, Pb, Th, U, DOC, and Cl) using a linear regression analysis. Results showed that less reactive elements, which can be expected to behave more conservatively in the landscape (e.g., Na, K, Ca, Mg, Cl, and Si), generally were best predicted from the broader-scale description of landscape composition (areal coverage of peat, tills, and sorted sediments). These results highlight the importance of mineral weathering as a source of some elements, which was best captured by landscape-scale descriptors of catchment structure. By contrast, more nonconservative elements (e.g., DOC, Al, Cd, Cs, Co, Th, Y, and U), were best predicted by defining wet areas and/or flow path lengths of different patches in the landscape. This change in the predictive models reflect the importance of peat deposits, such as organic-rich riparian zones and mire ecosystems, which are favorable environments for biogeochemical reactions of more nonconservative elements. As such, using this understanding of landscape influences on stream chemistry can provide improved mitigation strategies and management plans that specifically target source areas, so as to minimize mobilization of undesired elements into streams.

  8. The predictive value of fall assessment tools for patients admitted to hospice care.

    PubMed

    Patrick, Rebecca J; Slobodian, Dana; Debanne, Sara; Huang, Ying; Wellman, Charles

    2017-09-01

    Fall assessment tools are commonly used to evaluate the likelihood of fall. For patients found to be at high risk, patient-specific fall prevention interventions are implemented. The purposes of this study were to describe the population, evaluate and compare the efficacy of fall assessment tools, and suggest the best use for these tools in hospice. Data were downloaded from the electronic medical record for all patients who were admitted to and died in hospice care in 2013. Variables included demographic, clinical and initial fall assessment scores that had been computed on admission to hospice care, using our standard fall assessment tool. To facilitate comparison among three tools, additional fall assessment calculations were made for each patient using the Morse Fall Scale and MACH-10, two tools commonly used in a variety of healthcare settings. Data were available for 3446 hospice patients. Female patients were less likely to fall than males; Fallers lived longer than Nonfallers; and patients with a primary dementia diagnosis fell 10 days sooner than those with a primary non-dementia diagnosis. A comparison of three fall assessment tools revealed that no tool had a good positive predictive value, but each demonstrated a good negative predictive value. Fall assessment scores should not be used as the sole predictor of likelihood of fall, and are best used as a supplement to clinical judgement. Patients with a primary dementia diagnosis are likely to fall earlier in their hospice care than those with other primary diagnoses. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  9. The predictive accuracy of PREDICT: a personalized decision-making tool for Southeast Asian women with breast cancer.

    PubMed

    Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M; Hartman, Mikael; Bhoo-Pathy, Nirmala

    2015-02-01

    Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged <40 years, and in those receiving neoadjuvant chemotherapy. PREDICT performed well in terms of discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.

  10. The Predictive Accuracy of PREDICT: A Personalized Decision-Making Tool for Southeast Asian Women With Breast Cancer

    PubMed Central

    Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M.; Hartman, Mikael; Bhoo-Pathy, Nirmala

    2015-01-01

    Abstract Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients’ actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: −1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged <40 years, and in those receiving neoadjuvant chemotherapy. PREDICT performed well in terms of discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74–0.81) and 0.73 (95% CI: 0.68–0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings. PMID:25715267

  11. Development of predictive simulation capability for reactive multiphase flow

    SciTech Connect

    VanderHeyden, W.B.; Kendrick, B.K.

    1998-12-31

    This is the final report of a proposed three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project was terminated after the first year due to changes in funding priorities. The objective of the project was to develop a self-sustained research program for advanced computer simulation of industrial reactive multiphase flows. The prototype research problem was a three-phase alumina precipitator used in the Bayer process, a key step in aluminum refining. Accomplishments in the first year included the development of an improved reaction mechanism of the alumina precipitation growth process, the development of an efficient method for handling particle size distribution in multiphase flow simulation codes and finally the incorporation of precipitation growth and agglomeration kinetics in LANL`s CFDLIB multiphase flow code library.

  12. In silico tools for splicing defect prediction: a survey from the viewpoint of end users.

    PubMed

    Jian, Xueqiu; Boerwinkle, Eric; Liu, Xiaoming

    2014-07-01

    RNA splicing is the process during which introns are excised and exons are spliced. The precise recognition of splicing signals is critical to this process, and mutations affecting splicing comprise a considerable proportion of genetic disease etiology. Analysis of RNA samples from the patient is the most straightforward and reliable method to detect splicing defects. However, currently, the technical limitation prohibits its use in routine clinical practice. In silico tools that predict potential consequences of splicing mutations may be useful in daily diagnostic activities. In this review, we provide medical geneticists with some basic insights into some of the most popular in silico tools for splicing defect prediction, from the viewpoint of end users. Bioinformaticians in relevant areas who are working on huge data sets may also benefit from this review. Specifically, we focus on those tools whose primary goal is to predict the impact of mutations within the 5' and 3' splicing consensus regions: the algorithms used by different tools as well as their major advantages and disadvantages are briefly introduced; the formats of their input and output are summarized; and the interpretation, evaluation, and prospection are also discussed.

  13. A systematic literature review of life expectancy prediction tools for localized prostate cancer patients

    PubMed Central

    Kent, Matthew; Vickers, Andrew J.

    2015-01-01

    Purpose We aimed to develop a clinical decision support tool for clinicians counseling patients with localized prostate cancer. The tool would provide estimates of patient life expectancy from age, comorbidities, and tumor characteristics. We reviewed the literature to find suitable prediction models. Materials and Methods We searched the literature for prediction models for life expectancy. Models were evaluated in terms of whether they provided an estimate of risk, incorporated comorbidities, were clinically feasible and gave plausible estimates. Clinical feasibility was defined in terms of whether the model provided coefficients, could be used in the initial consultation for men across a wide range of ages without an undue burden of data gathering. Results Models in the literature were characterized by the use of life years rather than a risk of death, questionable approaches to comorbidities, implausible estimates, questionable recommendations, and poor clinical feasibility. We found tools based on applying an unvalidated approach to assessing comorbidities to a clearly erroneous life expectancy table, or required a treatment decision be made before life expectancy could be calculated or gave highly implausible estimates, such as a substantial risk of prostate cancer specific mortality even for a highly comorbid 80 year old with Gleason 6 disease. Conclusions We found gross deficiencies in current tools that predict risk of death from other causes. No existing model was suitable for implementation in our clinical decision support system. PMID:25463998

  14. JOURNAL CLUB: Four-Dimensional Flow MRI-Based Splenic Flow Index for Predicting Cirrhosis-Associated Hypersplenism.

    PubMed

    Keller, Eric J; Kulik, Laura; Stankovic, Zoran; Lewandowski, Robert J; Salem, Riad; Carr, James C; Schnell, Susanne; Markl, Michael; Collins, Jeremy D

    2017-07-01

    The objective of this study is to evaluate the ability of spleen volume, blood flow, and an index incorporating multiple measures to predict cirrhosis-associated hypersplenism. A total of 39 patients (14 women and 25 men; mean [± SD] age, 52 ± 10 years) with cirrhosis and sequelae of portal hypertension underwent 4D flow MRI and anatomic 3-T MRI performed before and after contrast administration. Unenhanced 4D flow MRI was used to assess abdominal hemodynamics, and splenic volumes were measured on T1-weighted gradient-recalled echo MRI. Relationships among demographic characteristics, blood component counts, splenic volume, arterial flow, venous flow, and the percentage of shunted portal flow were assessed in 29 consecutive patients (i.e., the derivation group), to develop a splenic flow index. This index was assessed along with splenic volume and blood flow alone in 10 additional consecutive patients (i.e., the validation group) via ROC curve analysis, to identify platelet counts of less than 50 × 10(3) cells/μL, leukocyte counts of less than 3.0 × 10(3) cells/μL, or both. In the derivation cohort (platelet count, 129 ± 76 × 10(3) cells/μL), splenic volume, arterial flow, venous flow, and the percentage of shunted portal flow were inversely correlated with platelet counts (ρ = -0.68, -0.68, -0.56, and -0.36, respectively; p < 0.05). Adding splenic volume to arterial flow and the product of venous flow and the percentage of shunted portal flow indexed to the body surface area yielded superior correlations with platelet counts, leukocyte counts, and the degree of severity of hypersplenism (ρ = -0.75, -0.48, and -0.75, respectively; p ≤ 0.001) and predicted severe hypersplenism (sensitivity, 100%; specificity, 100%) in the validation cohort (platelet count, 93 ± 71 × 10(3) cells/μL). A splenic flow index that incorporates both splenic volume and blood flow is a better indicator of hypersplenism than is splenic volume alone.

  15. The Novel 10-Item Asthma Prediction Tool: External Validation in the German MAS Birth Cohort

    PubMed Central

    Grabenhenrich, Linus B.; Reich, Andreas; Fischer, Felix; Zepp, Fred; Forster, Johannes; Schuster, Antje; Bauer, Carl-Peter; Bergmann, Renate L.; Bergmann, Karl E.; Wahn, Ulrich; Keil, Thomas; Lau, Susanne

    2014-01-01

    Background A novel non-invasive asthma prediction tool from the Leicester Cohort, UK, forecasts asthma at age 8 years based on 10 predictors assessed in early childhood, including current respiratory symptoms, eczema, and parental history of asthma. Objective We aimed to externally validate the proposed asthma prediction method in a German birth cohort. Methods The MAS-90 study (Multicentre Allergy Study) recorded details on allergic diseases prospectively in about yearly follow-up assessments up to age 20 years in a cohort of 1,314 children born 1990. We replicated the scoring method from the Leicester cohort and assessed prediction, performance and discrimination. The primary outcome was defined as the combination of parent-reported wheeze and asthma drugs (both in last 12 months) at age 8. Sensitivity analyses assessed model performance for outcomes related to asthma up to age 20 years. Results For 140 children parents reported current wheeze or cough at age 3 years. Score distribution and frequencies of later asthma resembled the Leicester cohort: 9% vs. 16% (MAS-90 vs. Leicester) of children at low risk at 3 years had asthma at 8 years, at medium risk 45% vs. 48%. Performance of the asthma prediction tool in the MAS-90 cohort was similar (Brier score 0.22 vs. 0.23) and discrimination slightly better than in the original cohort (area under the curve, AUC 0.83 vs. 0.78). Prediction and discrimination were robust against changes of inclusion criteria, scoring and outcome definitions. The secondary outcome ‘physicians’ diagnosed asthma at 20 years' showed the highest discrimination (AUC 0.89). Conclusion The novel asthma prediction tool from the Leicester cohort, UK, performed well in another population, a German birth cohort, supporting its use and further development as a simple aid to predict asthma risk in clinical settings. PMID:25536057

  16. 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.

  17. Introducing a Novel Applicant Ranking Tool to Predict Future Resident Performance: A Pilot Study.

    PubMed

    Bowe, Sarah N; Weitzel, Erik K; Hannah, William N; Fitzgerald, Brian M; Kraus, Gregory P; Nagy, Christopher J; Harrison, Stephen A

    2017-01-01

    The purposes of this study are to (1) introduce our novel Applicant Ranking Tool that aligns with the Accreditation Council for Graduate Medical Education competencies and (2) share our preliminary results comparing applicant rank to current performance. After a thorough literature review and multiple roundtable discussions, an Applicant Ranking Tool was created. Feasibility, satisfaction, and critiques were discussed via open feedback session. Inter-rater reliability was assessed using weighted kappa statistic (κ) and Kendall coefficient of concordance (W). Fisher's exact tests evaluated the ability of the tool to stratify performance into the top or bottom half of their class. Internal medicine and anesthesiology residents served as the pilot cohorts. The tool was considered user-friendly for both data input and analysis. Inter-rater reliability was strongest with intradisciplinary evaluation (W = 0.8-0.975). Resident performance was successfully stratified into those functioning in the upper vs. lower half of their class within the Clinical Anesthesia-3 grouping (p = 0.008). This novel Applicant Ranking Tool lends support for the use of both cognitive and noncognitive traits in predicting resident performance. While the ability of this instrument to accurately predict future resident performance will take years to answer, this pilot study suggests the instrument is worthy of ongoing investigation.

  18. Flow Cytometry as a Tool for Quality Control of Fluorescent Conjugates Used in Immunoassays

    PubMed Central

    de Almeida Santiago, Marta; de Paula Fonseca e Fonseca, Bruna; da Silva Marques, Christiane de Fátima; Domingos da Silva, Edimilson

    2016-01-01

    The use of antibodies in immunodiagnostic kits generally implies the conjugation of these proteins with other molecules such as chromophores or fluorochromes. The development of more sensitive quality control procedures than spectrophotometry is essential to assure the use of better fluorescent conjugates since the fluorescent conjugates are critical reagents for a variety of immunodiagnostic kits. In this article, we demonstrate a new flow cytometric protocol to evaluate conjugates by molecules of equivalent soluble fluorochromes (MESF) and by traditional flow cytometric analysis. We have coupled microspheres with anti-IgG-PE and anti-HBSAg-PE conjugates from distinct manufactures and/or different lots and evaluated by flow cytometry. Their fluorescence intensities were followed for a period of 18 months. Our results showed that there was a great difference in the fluorescence intensities between the conjugates studied. The differences were observed between manufactures and lots from both anti-IgG-PE and anti-HBSAg-PE conjugates. Coefficients of variation (CVs) showed that this parameter can be used to determine better coupling conditions, such as homogenous coupling. The MESF analysis, as well as geometric mean evaluation by traditional flow cytometry, showed a decrease in the values for all conjugates during the study and were indispensable tools to validate the results of stability tests. Our data demonstrated the feasibility of the flow cytometric method as a standard quality control of immunoassay kits. PMID:27936034

  19. Flow status of three transboundary rivers in Northern Greece as a tool for hydro-diplomacy

    NASA Astrophysics Data System (ADS)

    Hatzigiannakis, Eyaggelos; Hatzispiroglou, Ioannis; Arampatzis, Georgios; Ilia, Andreas; Pantelakis, Dimitrios; Filintas, Agathos; Panagopoulos, Andreas

    2015-04-01

    The aim of this paper is to examine how the river flow monitoring consists a tool for hydro-diplomacy. Management of transboundary catchments and the demand of common water resources, often comprise the cause of conflicts and tension threatening the peaceful coexistence of nations. The Water Framework Directive 2000/60/EU sets a base for water management contributing to common approaches, common goals, common principles as well as providing new definitions and measures for Europe's water resources. In northern Greece the main renewable resources are "imported" (over 25% of its water reserves) and for this reason the implementation of continuous flow measurements throughout the year is necessary, even though difficult to achieve. This paper focuses on the three largest transboundary rivers in Northern Greece. Axios and Strymonas river flow across the region of Central Macedonia in Northern Greece. Axios flows from FYROM to Greece, and Strymonas from Bulgaria to Greece. Nestos river flows from Bulgaria to Greece. The Greek part is in the region of Eastern Macedonia and Thrace in Northern Greece. Significant productive agricultural areas around these rivers are irrigated from them so they are very important for the local society. Measurements of the river flow velocity and the flow depth have been made at bridges. The frequency of the measurements is roughly monthly, because it is expected a significant change in the depth flow and discharge. A series of continuously flow measure-ments were performed during 2013 and 2014 using flowmeters (Valeport and OTT type). The cross-section characteristics, the river flow velocity of segments and the mean water flow velocity and discharge total profile were measured and calculated re-spectively. Measurements are conducted in the framework of the national water resources monitoring network, which is realised in compliance to the Water Framework Directive under the supervision and coordination of the Hellenic Ministry for the

  20. Laser Hardening Prediction Tool Based On a Solid State Transformations Numerical Model

    SciTech Connect

    Martinez, S.; Ukar, E.; Lamikiz, A.

    2011-01-17

    This paper presents a tool to predict hardening layer in selective laser hardening processes where laser beam heats the part locally while the bulk acts as a heat sink.The tool to predict accurately the temperature field in the workpiece is a numerical model that combines a three dimensional transient numerical solution for heating where is possible to introduce different laser sources. The thermal field was modeled using a kinetic model based on Johnson-Mehl-Avrami equation. Considering this equation, an experimental adjustment of transformation parameters was carried out to get the heating transformation diagrams (CHT). With the temperature field and CHT diagrams the model predicts the percentage of base material converted into austenite. These two parameters are used as first step to estimate the depth of hardened layer in the part.The model has been adjusted and validated with experimental data for DIN 1.2379, cold work tool steel typically used in mold and die making industry. This steel presents solid state diffusive transformations at relative low temperature. These transformations must be considered in order to get good accuracy of temperature field prediction during heating phase. For model validation, surface temperature measured by pyrometry, thermal field as well as the hardened layer obtained from metallographic study, were compared with the model data showing a good adjustment.

  1. The use of machine learning and nonlinear statistical tools for ADME prediction.

    PubMed

    Sakiyama, Yojiro

    2009-02-01

    Absorption, distribution, metabolism and excretion (ADME)-related failure of drug candidates is a major issue for the pharmaceutical industry today. Prediction of ADME by in silico tools has now become an inevitable paradigm to reduce cost and enhance efficiency in pharmaceutical research. Recently, machine learning as well as nonlinear statistical tools has been widely applied to predict routine ADME end points. To achieve accurate and reliable predictions, it would be a prerequisite to understand the concepts, mechanisms and limitations of these tools. Here, we have devised a small synthetic nonlinear data set to help understand the mechanism of machine learning by 2D-visualisation. We applied six new machine learning methods to four different data sets. The methods include Naive Bayes classifier, classification and regression tree, random forest, Gaussian process, support vector machine and k nearest neighbour. The results demonstrated that ensemble learning and kernel machine displayed greater accuracy of prediction than classical methods irrespective of the data set size. The importance of interaction with the engineering field is also addressed. The results described here provide insights into the mechanism of machine learning, which will enable appropriate usage in the future.

  2. 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.

  3. 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.

  4. GPS 2.0, a Tool to Predict Kinase-specific Phosphorylation Sites in Hierarchy *S⃞

    PubMed Central

    Xue, Yu; Ren, Jian; Gao, Xinjiao; Jin, Changjiang; Wen, Longping; Yao, Xuebiao

    2008-01-01

    Identification of protein phosphorylation sites with their cognate protein kinases (PKs) is a key step to delineate molecular dynamics and plasticity underlying a variety of cellular processes. Although nearly 10 kinase-specific prediction programs have been developed, numerous PKs have been casually classified into subgroups without a standard rule. For large scale predictions, the false positive rate has also never been addressed. In this work, we adopted a well established rule to classify PKs into a hierarchical structure with four levels, including group, family, subfamily, and single PK. In addition, we developed a simple approach to estimate the theoretically maximal false positive rates. The on-line service and local packages of the GPS (Group-based Prediction System) 2.0 were implemented in Java with the modified version of the Group-based Phosphorylation Scoring algorithm. As the first stand alone software for predicting phosphorylation, GPS 2.0 can predict kinase-specific phosphorylation sites for 408 human PKs in hierarchy. A large scale prediction of more than 13,000 mammalian phosphorylation sites by GPS 2.0 was exhibited with great performance and remarkable accuracy. Using Aurora-B as an example, we also conducted a proteome-wide search and provided systematic prediction of Aurora-B-specific substrates including protein-protein interaction information. Thus, the GPS 2.0 is a useful tool for predicting protein phosphorylation sites and their cognate kinases and is freely available on line. PMID:18463090

  5. Development of a computer simulation technique for predicting heat transfer in multiphase liquid-particle flow systems

    SciTech Connect

    Malone, Kevin F.; Xu, Bao H.; Fairweather, Michael

    2007-07-01

    Many of the highly active waste liquors that result from the reprocessing of spent nuclear fuel contain particulate solids of various materials. Operations for safe processing, handling and intermediate storage of these wastes often pose significant technical challenges due to the need for effective cooling systems to remove the heat generated by the radioactive solids. The multi-scale complexity of liquid-particle flow systems is such that investigation and prediction of their heat transfer characteristics based on experimental studies is a difficult task. Fortunately, the increasing availability of cheap computing power means that predictive simulation tools may be able to provide a means to investigate these systems without the need for expensive pilot studies. In this work we describe the development of a Combined Continuum and Discrete Model (CCDM) for predicting the heat transfer behaviour of systems of particles suspended in liquids. (authors)

  6. Use of finite volume radiation for predicting the Knudsen minimum in 2D channel flow

    SciTech Connect

    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.

  7. Using Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

    USGS Publications Warehouse

    Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

    2008-01-01

    southern California. This study demonstrates that logistic regression is a valuable tool for developing models that predict the probability of debris flows occurring in recently burned landscapes.

  8. Predictability of Wind-Driven Coastal Ocean Flow Over Topography

    NASA Astrophysics Data System (ADS)

    Kim, S.; Samelson, R. M.; Synder, C.

    2008-12-01

    The predictability of coastal ocean circulation over the central Oregon shelf is studied using ensembles of model forecasts from 50-day primitive equation ocean model simulations. The central Oregon shelf is a region of strong wind-driven currents and variable topography. The model configuration uses realistic topography, and simplified lateral boundary conditions. The forcing is an observed wind time-series representative of the summer upwelling season. The main focus on this study is on the balance between deterministic response to well-predicted forcing, uncertainty in initial conditions, and sensitivity to instabilities and topographical interactions. Simulated model forecasts are verified by standard statistics such as anomaly correlation coefficient and root mean squared error, and a new variant of relative entropy, the forecast relative entropy which quantifies the predictive information content in the forecast relative entropy relative to initial ensemble. The results suggest that the deterministic response is stronger than instability growth over the 3-7 day forecast intervals considered here. Therefore, when sufficiently accurate initializations are available, important elements of the coastal circulation should be accessible to predictive, dynamical forecasts on the nominal 7-day predictability timescale of the atmospheric forcing.

  9. Clinical Prediction Model and Tool for Assessing Risk of Persistent Pain After Breast Cancer Surgery.

    PubMed

    Meretoja, Tuomo J; Andersen, Kenneth Geving; Bruce, Julie; Haasio, Lassi; Sipilä, Reetta; Scott, Neil W; Ripatti, Samuli; Kehlet, Henrik; Kalso, Eija

    2017-05-20

    Purpose Persistent pain after breast cancer surgery is a well-recognized problem, with moderate to severe pain affecting 15% to 20% of women at 1 year from surgery. Several risk factors for persistent pain have been recognized, but tools to identify high-risk patients and preventive interventions are missing. The aim was to develop a clinically applicable risk prediction tool. Methods The prediction models were developed and tested using three prospective data sets from Finland (n = 860), Denmark (n = 453), and Scotland (n = 231). Prediction models for persistent pain of moderate to severe intensity at 1 year postoperatively were developed by logistic regression analyses in the Finnish patient cohort. The models were tested in two independent cohorts from Denmark and Scotland by assessing the areas under the receiver operating characteristics curves (ROC-AUCs). The outcome variable was moderate to severe persistent pain at 1 year from surgery in the Finnish and Danish cohorts and at 9 months in the Scottish cohort. Results Moderate to severe persistent pain occurred in 13.5%, 13.9%, and 20.3% of the patients in the three studies, respectively. Preoperative pain in the operative area ( P < .001), high body mass index ( P = .039), axillary lymph node dissection ( P = .008), and more severe acute postoperative pain intensity at the seventh postoperative day ( P = .003) predicted persistent pain in the final prediction model, which performed well in the Danish (ROC-AUC, 0.739) and Scottish (ROC-AUC, 0.740) cohorts. At the 20% risk level, the model had 32.8% and 47.4% sensitivity and 94.4% and 82.4% specificity in the Danish and Scottish cohorts, respectively. Conclusion Our validated prediction models and an online risk calculator provide clinicians and researchers with a simple tool to screen for patients at high risk of developing persistent pain after breast cancer surgery.

  10. SU-D-BRB-01: A Predictive Planning Tool for Stereotactic Radiosurgery

    SciTech Connect

    Palefsky, S; Roper, J; Elder, E; Dhabaan, A

    2015-06-15

    Purpose: To demonstrate the feasibility of a predictive planning tool which provides SRS planning guidance based on simple patient anatomical properties: PTV size, PTV shape and distance from critical structures. Methods: Ten framed SRS cases treated at Winship Cancer Institute of Emory University were analyzed to extract data on PTV size, sphericity (shape), and distance from critical structures such as the brainstem and optic chiasm. The cases consisted of five pairs. Each pair consisted of two cases with a similar diagnosis (such as pituitary adenoma or arteriovenous malformation) that were treated with different techniques: DCA, or IMRS. A Naive Bayes Classifier was trained on this data to establish the conditions under which each treatment modality was used. This model was validated by classifying ten other randomly-selected cases into DCA or IMRS classes, calculating the probability of each technique, and comparing results to the treated technique. Results: Of the ten cases used to validate the model, nine had their technique predicted correctly. The three cases treated with IMRS were all identified as such. Their probabilities of being treated with IMRS ranged between 59% and 100%. Six of the seven cases treated with DCA were correctly classified. These probabilities ranged between 51% and 95%. One case treated with DCA was incorrectly predicted to be an IMRS plan. The model’s confidence in this case was 91%. Conclusion: These findings indicate that a predictive planning tool based on simple patient anatomical properties can predict the SRS technique used for treatment. The algorithm operated with 90% accuracy. With further validation on larger patient populations, this tool may be used clinically to guide planners in choosing an appropriate treatment technique. The prediction algorithm could also be adapted to guide selection of treatment parameters such as treatment modality and number of fields for radiotherapy across anatomical sites.

  11. 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.

  12. The GOR Method of Protein Secondary Structure Prediction and Its Application as a Protein Aggregation Prediction Tool.

    PubMed

    Kouza, Maksim; Faraggi, Eshel; Kolinski, Andrzej; Kloczkowski, Andrzej

    2017-01-01

    The GOR method of protein secondary structure prediction is described. The original method was published by Garnier, Osguthorpe, and Robson in 1978 and was one of the first successful methods to predict protein secondary structure from amino acid sequence. The method is based on information theory, and an assumption that information function of a protein chain can be approximated by a sum of information from single residues and pairs of residues. The analysis of frequencies of occurrence of secondary structure for singlets and doublets of residues in a protein database enables prediction of secondary structure for new amino acid sequences. Because of these simple physical assumptions the GOR method has a conceptual advantage over other later developed methods such as PHD, PSIPRED, and others that are based on Machine Learning methods (like Neural Networks), give slightly better predictions, but have a "black box" nature. The GOR method has been continuously improved and modified for 30 years with the last GOR V version published in 2002, and the GOR V server developed in 2005. We discuss here the original GOR method and the GOR V program and the web server. Additionally we discuss new highly interesting and important applications of the GOR method to chameleon sequences in protein folding simulations, and for prediction of protein aggregation propensities. Our preliminary studies show that the GOR method is a promising and efficient alternative to other protein aggregation predicting tools. This shows that the GOR method despite being almost 40 years old is still important and has significant potential in application to new scientific problems.

  13. Flood Foresight: A near-real time flood monitoring and forecasting tool for rapid and predictive flood impact assessment

    NASA Astrophysics Data System (ADS)

    Revilla-Romero, Beatriz; Shelton, Kay; Wood, Elizabeth; Berry, Robert; Bevington, John; Hankin, Barry; Lewis, Gavin; Gubbin, Andrew; Griffiths, Samuel; Barnard, Paul; Pinnell, Marc; Huyck, Charles

    2017-04-01

    The hours and days immediately after a major flood event are often chaotic and confusing, with first responders rushing to mobilise emergency responders, provide alleviation assistance and assess loss to assets of interest (e.g., population, buildings or utilities). Preparations in advance of a forthcoming event are becoming increasingly important; early warning systems have been demonstrated to be useful tools for decision markers. The extent of damage, human casualties and economic loss estimates can vary greatly during an event, and the timely availability of an accurate flood extent allows emergency response and resources to be optimised, reduces impacts, and helps prioritise recovery. In the insurance sector, for example, insurers are under pressure to respond in a proactive manner to claims rather than waiting for policyholders to report losses. Even though there is a great demand for flood inundation extents and severity information in different sectors, generating flood footprints for large areas from hydraulic models in real time remains a challenge. While such footprints can be produced in real time using remote sensing, weather conditions and sensor availability limit their ability to capture every single flood event across the globe. In this session, we will present Flood Foresight (www.floodforesight.com), an operational tool developed to meet the universal requirement for rapid geographic information, before, during and after major riverine flood events. The tool provides spatial data with which users can measure their current or predicted impact from an event - at building, basin, national or continental scales. Within Flood Foresight, the Screening component uses global rainfall predictions to provide a regional- to continental-scale view of heavy rainfall events up to a week in advance, alerting the user to potentially hazardous situations relevant to them. The Forecasting component enhances the predictive suite of tools by providing a local

  14. Guidelines for reporting and using prediction tools for genetic variation analysis.

    PubMed

    Vihinen, Mauno

    2013-02-01

    Computational prediction methods are widely used for the analysis of human genome sequence variants and their effects on gene/protein function, splice site aberration, pathogenicity, and disease risk. New methods are frequently developed. We believe that guidelines are essential for those writing articles about new prediction methods, as well as for those applying these tools in their research, so that the necessary details are reported. This will enable readers to gain the full picture of technical information, performance, and interpretation of results, and to facilitate comparisons of related methods. Here, we provide instructions on how to describe new methods, report datasets, and assess the performance of predictive tools. We also discuss what details of predictor implementation are essential for authors to understand. Similarly, these guidelines for the use of predictors provide instructions on what needs to be delineated in the text, as well as how researchers can avoid unwarranted conclusions. They are applicable to most prediction methods currently utilized. By applying these guidelines, authors will help reviewers, editors, and readers to more fully comprehend prediction methods and their use. © 2012 Wiley Periodicals, Inc.

  15. 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.

  16. Predicting Human Error in Air Traffic Control Decision Support Tools and Free Flight Concepts

    NASA Technical Reports Server (NTRS)

    Mogford, Richard; Kopardekar, Parimal

    2001-01-01

    The document is a set of briefing slides summarizing the work the Advanced Air Transportation Technologies (AATT) Project is doing on predicting air traffic controller and airline pilot human error when using new decision support software tools and when involved in testing new air traffic control concepts. Previous work in this area is reviewed as well as research being done jointly with the FAA. Plans for error prediction work in the AATT Project are discussed. The audience is human factors researchers and aviation psychologists from government and industry.

  17. Predicting Human Error in Air Traffic Control Decision Support Tools and Free Flight Concepts

    NASA Technical Reports Server (NTRS)

    Mogford, Richard; Kopardekar, Parimal

    2001-01-01

    The document is a set of briefing slides summarizing the work the Advanced Air Transportation Technologies (AATT) Project is doing on predicting air traffic controller and airline pilot human error when using new decision support software tools and when involved in testing new air traffic control concepts. Previous work in this area is reviewed as well as research being done jointly with the FAA. Plans for error prediction work in the AATT Project are discussed. The audience is human factors researchers and aviation psychologists from government and industry.

  18. Considerations in predicting burnout of cylinders in flow boiling

    SciTech Connect

    Sadasivan, P.; Lienhard, J.H. )

    1992-02-01

    Previous investigations of the critical heat flux in flow boiling have resulted in widely different hydrodynamic mechanisms for the occurrence of burnout. Results of the present study indicate that existing models are not completely realistic representations of the process. The present study sorts out the influences of the far-wake bubble breakoff and vapor sheet characteristics, gravity, surface wettability, and heater surface temperature distribution on the peak heat flux in flow boiling on cylindrical heaters. The results indicate that burnout is dictated by near-surface effects. The controlling factor appears to be the vapor escape pattern close to the heater surface. It is also shown that a deficiency of liquid at the downstream end of the heater surface is not the cause of burnout.

  19. 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.

  20. Turbulence Modeling for Thrust Reverser Flow Field Prediction Methods

    DTIC Science & Technology

    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

  1. Development of nonlinear acoustic propagation analysis tool toward realization of loud noise environment prediction in aeronautics

    SciTech Connect

    Kanamori, Masashi Takahashi, Takashi Aoyama, Takashi

    2015-10-28

    Shown in this paper is an introduction of a prediction tool for the propagation of loud noise with the application to the aeronautics in mind. The tool, named SPnoise, is based on HOWARD approach, which can express almost exact multidimensionality of the diffraction effect at the cost of back scattering. This paper argues, in particular, the prediction of the effect of atmospheric turbulence on sonic boom as one of the important issues in aeronautics. Thanks to the simple and efficient modeling of the atmospheric turbulence, SPnoise successfully re-creates the feature of the effect, which often emerges in the region just behind the front and rear shock waves in the sonic boom signature.

  2. Development of nonlinear acoustic propagation analysis tool toward realization of loud noise environment prediction in aeronautics

    NASA Astrophysics Data System (ADS)

    Kanamori, Masashi; Takahashi, Takashi; Aoyama, Takashi

    2015-10-01

    Shown in this paper is an introduction of a prediction tool for the propagation of loud noise with the application to the aeronautics in mind. The tool, named SPnoise, is based on HOWARD approach, which can express almost exact multidimensionality of the diffraction effect at the cost of back scattering. This paper argues, in particular, the prediction of the effect of atmospheric turbulence on sonic boom as one of the important issues in aeronautics. Thanks to the simple and efficient modeling of the atmospheric turbulence, SPnoise successfully re-creates the feature of the effect, which often emerges in the region just behind the front and rear shock waves in the sonic boom signature.

  3. Predictions of bubbly flows in vertical pipes using two-fluid models in CFDS-FLOW3D code

    SciTech Connect

    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.

  4. Thermo-Solutal Convection in Porous Cavity: Opposing flow prediction with ANN

    NASA Astrophysics Data System (ADS)

    Jafer Kazi1, Mohammed; Yunus Khan, T. M.

    2017-08-01

    The thermos-solutal convection in porous medium can be categorized as aiding and opposing flow depending upon the value of buoyancy ratio (N) which indicates the relative buoyancy between heat and mass transfer. The positive value of buoyancy ratio leads to aiding flow whereas the negative value of N results into different pattern of flow commonly known as opposing flow. The present article is an extension of the article to predict the thermos-solutal convection for aiding flow but to focus on opposing flow. The prediction is carried out a relatively new technique known as artificial neural network. The results are discussed with respect to the Nusselt as Sherwood number along the hot wall of cavity.

  5. 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.

  6. Providing access to risk prediction tools via the HL7 XML-formatted risk web service.

    PubMed

    Chipman, Jonathan; Drohan, Brian; Blackford, Amanda; Parmigiani, Giovanni; Hughes, Kevin; Bosinoff, Phil

    2013-07-01

    Cancer risk prediction tools provide valuable information to clinicians but remain computationally challenging. Many clinics find that CaGene or HughesRiskApps fit their needs for easy- and ready-to-use software to obtain cancer risks; however, these resources may not fit all clinics' needs. The HughesRiskApps Group and BayesMendel Lab therefore developed a web service, called "Risk Service", which may be integrated into any client software to quickly obtain standardized and up-to-date risk predictions for BayesMendel tools (BRCAPRO, MMRpro, PancPRO, and MelaPRO), the Tyrer-Cuzick IBIS Breast Cancer Risk Evaluation Tool, and the Colorectal Cancer Risk Assessment Tool. Software clients that can convert their local structured data into the HL7 XML-formatted family and clinical patient history (Pedigree model) may integrate with the Risk Service. The Risk Service uses Apache Tomcat and Apache Axis2 technologies to provide an all Java web service. The software client sends HL7 XML information containing anonymized family and clinical history to a Dana-Farber Cancer Institute (DFCI) server, where it is parsed, interpreted, and processed by multiple risk tools. The Risk Service then formats the results into an HL7 style message and returns the risk predictions to the originating software client. Upon consent, users may allow DFCI to maintain the data for future research. The Risk Service implementation is exemplified through HughesRiskApps. The Risk Service broadens the availability of valuable, up-to-date cancer risk tools and allows clinics and researchers to integrate risk prediction tools into their own software interface designed for their needs. Each software package can collect risk data using its own interface, and display the results using its own interface, while using a central, up-to-date risk calculator. This allows users to choose from multiple interfaces while always getting the latest risk calculations. Consenting users contribute their data for future

  7. Establishing Minimum Flow Requirements Based on Benthic Vegetation: What are Some Issues Related to Identifying Quantity of Inflow and Tools Used to Quantify Ecosystem Response?

    NASA Astrophysics Data System (ADS)

    Hunt, M. J.; Nuttle, W. K.; Cosby, B. J.; Marshall, F. E.

    2005-05-01

    Establishing minimum flow requirements in aquatic ecosystems is one way to stipulate controls on water withdrawals in a watershed. The basis of the determination is to identify the amount of flow needed to sustain a threshold ecological function. To develop minimum flow criteria an understanding of ecological response in relation to flow is essential. Several steps are needed including: (1) identification of important resources and ecological functions, (2) compilation of available information, (3) determination of historical conditions, (4) establishment of technical relationships between inflow and resources, and (5) identification of numeric criteria that reflect the threshold at which resources are harmed. The process is interdisciplinary requiring the integration of hydrologic and ecologic principles with quantitative assessments. The tools used quantify the ecological response and key questions related to how the quantity of flow influences the ecosystem are examined by comparing minimum flow determination in two different aquatic systems in South Florida. Each system is characterized by substantial hydrologic alteration. The first, the Caloosahatchee River is a riverine system, located on the southwest coast of Florida. The second, the Everglades- Florida Bay ecotone, is a wetland mangrove ecosystem, located on the southern tip of the Florida peninsula. In both cases freshwater submerged aquatic vegetation (Vallisneria americana or Ruppia maritima), located in areas of the saltwater- freshwater interface has been identified as a basis for minimum flow criteria. The integration of field studies, laboratory studies, and literature review was required. From this information we developed ecological modeling tools to quantify and predict plant growth in response to varying environmental variables. Coupled with hydrologic modeling tools questions relating to the quantity and timing of flow and ecological consequences in relation to normal variability are addressed.

  8. Noise produced by turbulent flow into a rotor: Theory manual for atmospheric turbulence prediction and mean flow and turbulence contraction prediction

    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.

  9. En route Spacing Tool: Efficient Conflict-free Spacing to Flow-Restricted Airspace

    NASA Technical Reports Server (NTRS)

    Green, S.

    1999-01-01

    This paper describes the Air Traffic Management (ATM) problem within the U.S. of flow-restricted en route airspace, an assessment of its impact on airspace users, and a set of near-term tools and procedures to resolve the problem. The FAA is committed, over the next few years, to deploy the first generation of modem ATM decision support tool (DST) technology under the Free-Flight Phase-1 (FFp1) program. The associated en route tools include the User Request Evaluation Tool (URET) and the Traffic Management Advisor (TMA). URET is an initial conflict probe (ICP) capability that assists controllers with the detection and resolution of conflicts in en route airspace. TMA orchestrates arrivals transitioning into high-density terminal airspace by providing controllers with scheduled times of arrival (STA) and delay feedback advisories to assist with STA conformance. However, these FFPl capabilities do not mitigate the en route Miles-In-Trail (MIT) restrictions that are dynamically applied to mitigate airspace congestion. National statistics indicate that en route facilities (Centers) apply Miles-In-Trail (MIT) restrictions for approximately 5000 hours per month. Based on results from this study, an estimated 45,000 flights are impacted by these restrictions each month. Current-day practices for implementing these restrictions result in additional controller workload and an economic impact of which the fuel penalty alone may approach several hundred dollars per flight. To mitigate much of the impact of these restrictions on users and controller workload, a DST and procedures are presented. The DST is based on a simple derivative of FFP1 technology that is designed to introduce a set of simple tools for flow-rate (spacing) conformance and integrate them with conflict-probe capabilities. The tool and associated algorithms are described based on a concept prototype implemented within the CTAS baseline in 1995. A traffic scenario is used to illustrate the controller's use of

  10. En route Spacing Tool: Efficient Conflict-free Spacing to Flow-Restricted Airspace

    NASA Technical Reports Server (NTRS)

    Green, S.

    1999-01-01

    This paper describes the Air Traffic Management (ATM) problem within the U.S. of flow-restricted en route airspace, an assessment of its impact on airspace users, and a set of near-term tools and procedures to resolve the problem. The FAA is committed, over the next few years, to deploy the first generation of modem ATM decision support tool (DST) technology under the Free-Flight Phase-1 (FFp1) program. The associated en route tools include the User Request Evaluation Tool (URET) and the Traffic Management Advisor (TMA). URET is an initial conflict probe (ICP) capability that assists controllers with the detection and resolution of conflicts in en route airspace. TMA orchestrates arrivals transitioning into high-density terminal airspace by providing controllers with scheduled times of arrival (STA) and delay feedback advisories to assist with STA conformance. However, these FFPl capabilities do not mitigate the en route Miles-In-Trail (MIT) restrictions that are dynamically applied to mitigate airspace congestion. National statistics indicate that en route facilities (Centers) apply Miles-In-Trail (MIT) restrictions for approximately 5000 hours per month. Based on results from this study, an estimated 45,000 flights are impacted by these restrictions each month. Current-day practices for implementing these restrictions result in additional controller workload and an economic impact of which the fuel penalty alone may approach several hundred dollars per flight. To mitigate much of the impact of these restrictions on users and controller workload, a DST and procedures are presented. The DST is based on a simple derivative of FFP1 technology that is designed to introduce a set of simple tools for flow-rate (spacing) conformance and integrate them with conflict-probe capabilities. The tool and associated algorithms are described based on a concept prototype implemented within the CTAS baseline in 1995. A traffic scenario is used to illustrate the controller's use of

  11. Prognostic factors and predictive tools for upper tract urothelial carcinoma: a systematic review.

    PubMed

    Mbeutcha, Aurélie; Rouprêt, Morgan; Kamat, Ashish M; Karakiewicz, Pierre I; Lawrentschuk, Nathan; Novara, Giacomo; Raman, Jay D; Seitz, Christian; Xylinas, Evanguelos; Shariat, Shahrokh F

    2017-03-01

    Upper tract urothelial carcinoma (UTUC) is a rare and heterogeneous disease. Several clinical and biological prognostic factors have been identified in multi-institutional collaborative works with the aim of helping decision-making in pursuit of tailored individual patient care. This review provides an overview of these existing prognostic factors and predictive tools for the management of patients with UTUC. A systematic literature search was performed using PubMed/MEDLINE, Web of Science and Scopus databases regarding articles published in English between January 2000 and November 2015 according to PRISMA guidelines. Thresholds of 100 and 300 patients were applied for studies on biomarkers and clinical studies, respectively. All the studies on predictive tools were included for analysis. Outcomes of interest were features associated with advanced-stage UTUC, disease recurrence and survival. A total of 116 studies were included in this review. These large and/or multi-institutional studies have confirmed the prognostic value of standard pathological factors (i.e., tumor stage, grade and lymph node metastasis) and identified novel features such as lymphovascular invasion, tumor architecture, multifocality, concomitant CIS, variant histology and biomarker status among others. Based on these variables, several predictive tools have been developed; however, they often lack of validation. The value of these features and tools needs prospective testing. Efforts provided by international collaboration groups have permitted to validate established features and identify new features of biologically and clinically aggressive UTUC. Further investigation on prognostic factors and biomarkers is still needed to assess the benefit of these features and tools on clinical decision-making.

  12. Tools for Predicting Optical Damage on Inertial Confinement Fusion-Class Laser Systems

    SciTech Connect

    Nostrand, M C; Carr, C W; Liao, Z M; Honig, J; Spaeth, M L; Manes, K R; Johnson, M A; Adams, J J; Cross, D A; Negres, R A; Widmayer, C C; Williams, W H; Matthews, M J; Jancaitis, K S; Kegelmeyer, L M

    2010-12-20

    Operating a fusion-class laser to its full potential requires a balance of operating constraints. On the one hand, the total laser energy delivered must be high enough to give an acceptable probability for ignition success. On the other hand, the laser-induced optical damage levels must be low enough to be acceptably handled with the available infrastructure and budget for optics recycle. Our research goal was to develop the models, database structures, and algorithmic tools (which we collectively refer to as ''Loop Tools'') needed to successfully maintain this balance. Predictive models are needed to plan for and manage the impact of shot campaigns from proposal, to shot, and beyond, covering a time span of years. The cost of a proposed shot campaign must be determined from these models, and governance boards must decide, based on predictions, whether to incorporate a given campaign into the facility shot plan based upon available resources. Predictive models are often built on damage ''rules'' derived from small beam damage tests on small optics. These off-line studies vary the energy, pulse-shape and wavelength in order to understand how these variables influence the initiation of damage sites and how initiated damage sites can grow upon further exposure to UV light. It is essential to test these damage ''rules'' on full-scale optics exposed to the complex conditions of an integrated ICF-class laser system. Furthermore, monitoring damage of optics on an ICF-class laser system can help refine damage rules and aid in the development of new rules. Finally, we need to develop the algorithms and data base management tools for implementing these rules in the Loop Tools. The following highlights progress in the development of the loop tools and their implementation.

  13. Numerical Prediction of the Dimensioning of Tools for the Extrusion Process of Rubber Profiles

    NASA Astrophysics Data System (ADS)

    Müllner, Herbert W.; Wieczorek, André; Eberhardsteiner, Josef

    2007-04-01

    In this contribution numerical simulations of realistic extrusion tools will be presented. Generally, the geometry of the desired rubber profile cannot be used for the dimensioning of the tool. The shape of the corresponding tool under consideration of the material behavior needs to be predicted. Therefore, simulations were performed with the finite element based CFD program POLYFLOW under usage of an inverse calculation approach. The underlying material parameters will be provided by a material characterization which is based on capillary-experiments in combination with extrudate swell measurements. Thus, more realistic simulations of the extrudate swell phenomenon and its influence on the resulting profile geometry are possible. The experimental validation of the new characterization method will be done by means of numerical simulations of the capillary-experiment.

  14. Prediction of the removal profile for tools having a finite contact patch; Technical Digest

    NASA Astrophysics Data System (ADS)

    Bouvier, Christophe; Gracewski, Sheryl M.; Fess, Edward; Burns, Stephen J.

    2005-05-01

    A new generation of compliant tools and processes called UltraForm Finishing is under development at the Center for Optics Manufacturing (COM) and OptiPro Systems (Ontario, NY). The purpose is to achieve rapid, high quality finishing of hard materials. These compliant tools exhibit a large contact patch that can be up to 1 cm wide. A numerical model was developed to account for finite contact patch geometry on removal for a flat rotating axisymmetric workpiece. This model was used to determine the depth of removal as a function of radial position after the polishing tool has completely traversed the workpiece from its center to a given radial position. The depth of removal was investigated for circular and oval contact patches and a variety of removal functions. A constant removal depth is desired to minimize the induced figure error. Predicted results were compared to experimental measurements of induced figure error.

  15. A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.

    PubMed

    Jones, Stephen; Cournane, Seán; Sheehy, Niall; Hederman, Lucy

    2016-12-01

    Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

  16. The Poseidon operational tool for the prediction of floating pollutant transport.

    PubMed

    Annika, P; George, T; George, P; Konstantinos, N; Costas, D; Koutitas, C

    2001-01-01

    In this work the development and the application of an operational management tool for the Greek Seas is described. This tool consists of a three-dimensional floating pollutant prediction model coupled with a weather, a hydrodynamic and a wave model in order to track the movements and the spreading of the pollutants and indicate those coastal areas which might be affected. The tool is part of the Poseidon system which has been designed to provide real time data and forecasts for marine environmental conditions in the Greek Seas. In this paper, we present four case studies based on realistic scenarios that show the value of the application for long-term strategic planning and short-term decision making in oil spill accidents.

  17. 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.

  18. Development of a Windbreak Dust Predictive Model and Mitigation Planning Tool

    DTIC Science & Technology

    2013-12-01

    Hwy 81 and US Interstate 84 to mitigate the effects of dust storms in the summer and snow drifts in the winter on the nearby highways. The windbreaks...FINAL REPORT Development of a Windbreak Dust Predictive Model and Mitigation Planning Tool SERDP Project RC-1730 DECEMBER 2013 Eric...From - To) 04-09-2010 To 10-09-2013 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER RC-1730 Development of a Windbreak Dust

  19. Performance of risk assessment tools for predicting osteoporosis in south Indian rural elderly men.

    PubMed

    Satyaraddi, Anil; Shetty, Sahana; Kapoor, Nitin; Cherian, Kripa Elizabeth; Naik, Dukhabandhu; Thomas, Nihal; Paul, Thomas Vizhalil

    2017-12-01

    Osteoporosis in elderly men is an under-recognized problem. In the current study, we intend to look at the performance of two risk assessment tools [OSTA and MORES] for the diagnosis of osteoporosis. Osteoporosis was seen in 1/4th of elderly men at spine and 1/6th of them at femoral neck. Both risk assessment tools were found to have good sensitivity in predicting osteoporosis at spine and femoral neck with good area under curve (AUC). This study attempts to look at the performance of osteoporosis self-assessment tool for Asians (OSTA) and male osteoporosis risk estimation score (MORES) for predicting osteoporosis in south Indian rural elderly men. Five hundred and twelve men above 65 years of age from a south Indian rural community were recruited by cluster random sampling. All subjects underwent detailed clinical, anthropometric, and bone mineral density measurement at lumbar spine and femoral neck using dual-energy X-ray absorptiometry scan. A T score ≤ - 2.5 was diagnostic of osteoporosis. Scores for OSTA and MORES were calculated at various cut offs, and their sensitivities and specificities for predicting osteoporosis were derived. The prevalence of osteoporosis was found to be 16% at femoral neck and 23% at spine. OSTA with a cut-off value of ≤2 predicted osteoporosis with a sensitivity and specificity at lumbar spine of 94 and 17% and at femoral neck of 99 and 18%. The area under ROC curve for OSTA index for spine was 0.716 and for femoral neck was 0.778. MORES with a cut-off value of ≥6 predicted osteoporosis at spine with a sensitivity of 98% and specificity of 15%, and at femoral neck, they were 98 and 13%, respectively. The area under ROC curve for MORES for spine was 0.855 and for femoral neck was 0.760. OSTA and MORES were found to be useful screening tools for predicting osteoporosis in Indian elderly men. These tools are simple, easy to perform, and cost effective in the context of rural Indian setting.

  20. 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.

  1. Three dimensional numerical prediction of two phase flow in industrial CFB boiler

    SciTech Connect

    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.

  2. Development of advanced stability theory suction prediction techniques for laminar flow control. [on swept wings

    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.

  3. Flow cytometry as a useful tool for process development: rapid evaluation of expression systems.

    PubMed

    Patkar, Anant; Vijayasankaran, Natarajan; Urry, Dan W; Srienc, Friedrich

    2002-02-28

    Flow cytometry is an established tool in fundamental studies of single-cell microbial physiology. Here we show that it can also provide valuable information for process development. Using recombinant Escherichia coli strains, which express the protein-based polymer (GVGIP)(260)GVGVP, the utility of flow cytometry in monitoring and optimization of fermentations is demonstrated. Single cell right angle light scatter was found to be significantly affected by intracellular product formation possibly due to the formation of inclusion bodies. Translational fusions with green fluorescent protein (GFP) enabled monitoring of product accumulation, as well as plasmid free cell fraction (PFCF). Such fusions also allowed rapid evaluation of induction strategies and three different expression systems based on the T7 promoter, T7-lac promoter and the P(BAD) promoter. The expression system based on the P(BAD) promoter was found to be superior to the T7-based system.

  4. An Interactive Tool for Discrete Phase Analysis in Two-Phase Flows

    NASA Technical Reports Server (NTRS)

    Dejong, Frederik J.; Thoren, Stephen J.

    1993-01-01

    Under a NASA MSFC SBIR Phase 1 effort an interactive software package has been developed for the analysis of discrete (particulate) phase dynamics in two-phase flows in which the discrete phase does not significantly affect the continuous phase. This package contains a Graphical User Interface (based on the X Window system and the Motif tool kit) coupled to a particle tracing program, which allows the user to interactively set up and run a case for which a continuous phase grid and flow field are available. The software has been applied to a solid rocket motor problem, to demonstrate its ease of use and its suitability for problems of engineering interest, and has been delivered to NASA Marshall Space Flight Center.

  5. The Acoustic Analogy: A Powerful Tool in Aeroacoustics with Emphasis on Jet Noise Prediction

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Doty, Michael J.; Hunter, Craig A.

    2004-01-01

    The acoustic analogy introduced by Lighthill to study jet noise is now over 50 years old. In the present paper, Lighthill s Acoustic Analogy is revisited together with a brief evaluation of the state-of-the-art of the subject and an exploration of the possibility of further improvements in jet noise prediction from analytical methods, computational fluid dynamics (CFD) predictions, and measurement techniques. Experimental Particle Image Velocimetry (PIV) data is used both to evaluate turbulent statistics from Reynolds-averaged Navier-Stokes (RANS) CFD and to propose correlation models for the Lighthill stress tensor. The NASA Langley Jet3D code is used to study the effect of these models on jet noise prediction. From the analytical investigation, a retarded time correction is shown that improves, by approximately 8 dB, the over-prediction of aft-arc jet noise by Jet3D. In experimental investigation, the PIV data agree well with the CFD mean flow predictions, with room for improvement in Reynolds stress predictions. Initial modifications, suggested by the PIV data, to the form of the Jet3D correlation model showed no noticeable improvements in jet noise prediction.

  6. Bigger data, collaborative tools and the future of predictive drug discovery

    NASA Astrophysics Data System (ADS)

    Ekins, Sean; Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

    2014-10-01

    Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas.

  7. Bigger Data, Collaborative Tools and the Future of Predictive Drug Discovery

    PubMed Central

    Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

    2014-01-01

    Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas. PMID:24943138

  8. Computational tools and resources for prediction and analysis of gene regulatory regions in the chick genome

    PubMed Central

    Khan, Mohsin A. F.; Soto-Jimenez, Luz Mayela; Howe, Timothy; Streit, Andrea; Sosinsky, Alona; Stern, Claudio D.

    2013-01-01

    The discovery of cis-regulatory elements is a challenging problem in bioinformatics, owing to distal locations and context-specific roles of these elements in controlling gene regulation. Here we review the current bioinformatics methodologies and resources available for systematic discovery of cis-acting regulatory elements and conserved transcription factor binding sites in the chick genome. In addition, we propose and make available, a novel workflow using computational tools that integrate CTCF analysis to predict putative insulator elements, enhancer prediction and TFBS analysis. To demonstrate the usefulness of this computational workflow, we then use it to analyze the locus of the gene Sox2 whose developmental expression is known to be controlled by a complex array of cis-acting regulatory elements. The workflow accurately predicts most of the experimentally verified elements along with some that have not yet been discovered. A web version of the CTCF tool, together with instructions for using the workflow can be accessed from http://toolshed.g2.bx.psu.edu/view/mkhan1980/ctcf_analysis. For local installation of the tool, relevant Perl scripts and instructions are provided in the directory named “code” in the supplementary materials. PMID:23355428

  9. Computational tools and resources for prediction and analysis of gene regulatory regions in the chick genome.

    PubMed

    Khan, Mohsin A F; Soto-Jimenez, Luz Mayela; Howe, Timothy; Streit, Andrea; Sosinsky, Alona; Stern, Claudio D

    2013-05-01

    The discovery of cis-regulatory elements is a challenging problem in bioinformatics, owing to distal locations and context-specific roles of these elements in controlling gene regulation. Here we review the current bioinformatics methodologies and resources available for systematic discovery of cis-acting regulatory elements and conserved transcription factor binding sites in the chick genome. In addition, we propose and make available, a novel workflow using computational tools that integrate CTCF analysis to predict putative insulator elements, enhancer prediction, and TFBS analysis. To demonstrate the usefulness of this computational workflow, we then use it to analyze the locus of the gene Sox2 whose developmental expression is known to be controlled by a complex array of cis-acting regulatory elements. The workflow accurately predicts most of the experimentally verified elements along with some that have not yet been discovered. A web version of the CTCF tool, together with instructions for using the workflow can be accessed from http://toolshed.g2.bx.psu.edu/view/mkhan1980/ctcf_analysis. For local installation of the tool, relevant Perl scripts and instructions are provided in the directory named "code" in the supplementary materials.

  10. Matrix metalloproteinases - From the cleavage data to the prediction tools and beyond.

    PubMed

    Cieplak, Piotr; Strongin, Alex Y

    2017-03-24

    Understanding the physiological role of any protease requires identification of both its cleavage substrates and their relative cleavage efficacy as compared with other substrates and other proteinases. Our review manuscript is focused on the cleavage preferences of the individual matrix metalloproteinases (MMPs) and the cleavage similarity and distinction that exist in the human MMP family. The recent in-depth analysis of MMPs by us and many others greatly increased knowledge of the MMP biology and structural-functional relationships among this protease family members. A better knowledge of cleavage preferences of MMPs has led us to the development of the prediction tools that are now capable of the high throughput reliable prediction and ranking the MMP cleavage sites in the peptide sequences in silico. Our software unifies and consolidates volumes of the pre-existing data. Now this prediction-ranking in silico tool is ready to be used by others. The software we developed may facilitate both the identification of the novel proteolytic regulatory pathways and the discovery of the previously uncharacterized substrates of the individual MMPs. Because now the MMP research may be based on the mathematical probability parameters rather than on either random luck or common sense alone, the researchers armed with this novel in silico tool will be better equipped to fine-tune or, at least, to sharply focus their wet chemistry experiments. This article is part of a Special Issue entitled: Matrix Metalloproteinases edited by Rafael Fridman.

  11. Correlation of lava flows on Cascade volcanoes: Tool development and example from Burney Spring Mountain, California

    NASA Astrophysics Data System (ADS)

    O'Brien, Timothy Michael

    Bedrock mapping in volcanic terrains is a challenge, and generally requires extensive field work and petrographic and geochemical analysis. Paleomagnetism, when used in conjunction with field, geochemical and petrographic data offers a complimentary geophysical tool to field mapping, assisting in the correlation of lava flows across faults and aiding in determination of fault kinematics. Secular variation of the Earth's magnetic field imprints individually distinguishable magnetic orientations in igneous rocks emplaced >100 years apart, resulting in magnetic fingerprints that can be used to correlate lava flows across eroded areas, or that have been displaced by faulting or modified by weathering. A successful paleomagnetic study requires establishment of a well constrained magnetic orientation for individual lava flows, against which structural corrections can be made for sample sites in rotated blocks. The resulting structural corrections provide insight into the mode and degree of movement along the fault since emplacement of the lava flows. This methodology was applied to mapping a tectonically modified Pliocene-Pleistocene volcanic edifice, Burney Spring Mountain, within the Hat Creek Graben of northeastern California. The establishment of a general range of paleomagnetic orientations for Burney Spring Mountain serves to distinguish between lava flows sourced from Burney Spring Mountain and those that overlap the edifice from surrounding volcanic vents. Paleomagnetic results have thus assisted in delineating the areal extent of Burney Spring Mountain and have furthermore revealed the presence of local block rotations adjacent to the fault, clarifying the kinematics of the faults themselves. Supporting geochemical analyses were conducted to assist in the correlation of Burney Spring Mountain lava flows involving the use of an electron-dispersive x-ray spectrometer (EDS) outfitted scanning electron microscope (SEM) and a portable x-ray fluorescence (pXRF) device

  12. PredAlgo: a new subcellular localization prediction tool dedicated to green algae.

    PubMed

    Tardif, Marianne; Atteia, Ariane; Specht, Michael; Cogne, Guillaume; Rolland, Norbert; Brugière, Sabine; Hippler, Michael; Ferro, Myriam; Bruley, Christophe; Peltier, Gilles; Vallon, Olivier; Cournac, Laurent

    2012-12-01

    The unicellular green alga Chlamydomonas reinhardtii is a prime model for deciphering processes occurring in the intracellular compartments of the photosynthetic cell. Organelle-specific proteomic studies have started to delineate its various subproteomes, but sequence-based prediction software is necessary to assign proteins subcellular localizations at whole genome scale. Unfortunately, existing tools are oriented toward land plants and tend to mispredict the localization of nuclear-encoded algal proteins, predicting many chloroplast proteins as mitochondrion targeted. We thus developed a new tool called PredAlgo that predicts intracellular localization of those proteins to one of three intracellular compartments in green algae: the mitochondrion, the chloroplast, and the secretory pathway. At its core, a neural network, trained using carefully curated sets of C. reinhardtii proteins, divides the N-terminal sequence into overlapping 19-residue windows and scores the probability that they belong to a cleavable targeting sequence for one of the aforementioned organelles. A targeting prediction is then deduced for the protein, and a likely cleavage site is predicted based on the shape of the scoring function along the N-terminal sequence. When assessed on an independent benchmarking set of C. reinhardtii sequences, PredAlgo showed a highly improved discrimination capacity between chloroplast- and mitochondrion-localized proteins. Its predictions matched well the results of chloroplast proteomics studies. When tested on other green algae, it gave good results with Chlorophyceae and Trebouxiophyceae but tended to underpredict mitochondrial proteins in Prasinophyceae. Approximately 18% of the nuclear-encoded C. reinhardtii proteome was predicted to be targeted to the chloroplast and 15% to the mitochondrion.

  13. GAPIT Version 2: An Enhanced Integrated Tool for Genomic Association and Prediction.

    PubMed

    Tang, You; Liu, Xiaolei; Wang, Jiabo; Li, Meng; Wang, Qishan; Tian, Feng; Su, Zhongbin; Pan, Yuchun; Liu, Di; Lipka, Alexander E; Buckler, Edward S; Zhang, Zhiwu

    2016-07-01

    Most human diseases and agriculturally important traits are complex. Dissecting their genetic architecture requires continued development of innovative and powerful statistical methods. Corresponding advances in computing tools are critical to efficiently use these statistical innovations and to enhance and accelerate biomedical and agricultural research and applications. The genome association and prediction integrated tool (GAPIT) was first released in 2012 and became widely used for genome-wide association studies (GWAS) and genomic prediction. The GAPIT implemented computationally efficient statistical methods, including the compressed mixed linear model (CMLM) and genomic prediction by using genomic best linear unbiased prediction (gBLUP). New state-of-the-art statistical methods have now been implemented in a new, enhanced version of GAPIT. These methods include factored spectrally transformed linear mixed models (FaST-LMM), enriched CMLM (ECMLM), FaST-LMM-Select, and settlement of mixed linear models under progressively exclusive relationship (SUPER). The genomic prediction methods implemented in this new release of the GAPIT include gBLUP based on CMLM, ECMLM, and SUPER. Additionally, the GAPIT was updated to improve its existing output display features and to add new data display and evaluation functions, including new graphing options and capabilities, phenotype simulation, power analysis, and cross-validation. These enhancements make the GAPIT a valuable resource for determining appropriate experimental designs and performing GWAS and genomic prediction. The enhanced R-based GAPIT software package uses state-of-the-art methods to conduct GWAS and genomic prediction. The GAPIT also provides new functions for developing experimental designs and creating publication-ready tabular summaries and graphs to improve the efficiency and application of genomic research.

  14. Evaluation of an ARPS-based canopy flow modeling system for use in future operational smoke prediction efforts

    NASA Astrophysics Data System (ADS)

    Kiefer, M. T.; Zhong, S.; Heilman, W. E.; Charney, J. J.; Bian, X.

    2013-06-01

    Efforts to develop a canopy flow modeling system based on the Advanced Regional Prediction System (ARPS) model are discussed. The standard version of ARPS is modified to account for the effect of drag forces on mean and turbulent flow through a vegetation canopy, via production and sink terms in the momentum and subgrid-scale turbulent kinetic energy (TKE) equations. Additionally, a downward decaying net radiation profile inside the canopy is used to account for the attenuation of net radiation by vegetation elements. As a critical step in the model development process, simulations performed with the new canopy model, termed ARPS-CANOPY, are examined and compared to observations from the Canopy Horizontal Array Turbulence Study (CHATS) experiment. Comparisons of mean and turbulent flow properties in a statistically homogeneous atmosphere are presented for two cases, one when the trees are dormant without leaves and another when the trees are full of mature leaves. The model is shown to reproduce the shape of the vertical profiles of mean wind, temperature, and TKE observed during the CHATS experiment, with errors generally smaller in the afternoon and in the case with stronger mean flow. Sensitivity experiments with relatively coarse (90 m) horizontal grid spacing retain the overall mean profile shapes and diurnal trends seen in the finer-resolution simulations. The work described herein is part of a larger effort to develop predictive tools for close-range (on the order of 1 km from the source) smoke dispersion from low-intensity fires within forested areas.

  15. Validation of a pediatric bedside tool to predict time to death after withdrawal of life support.

    PubMed

    Das, Ashima; Anderson, Ingrid M; Speicher, David G; Speicher, Richard H; Shein, Steven L; Rotta, Alexandre T

    2016-02-08

    To evaluate the accuracy of a tool developed to predict timing of death following withdrawal of life support in children. Pertinent variables for all pediatric deaths (age ≤ 21 years) from 1/2009 to 6/2014 in our pediatric intensive care unit (PICU) were extracted through a detailed review of the medical records. As originally described, a recently developed tool that predicts timing of death in children following withdrawal of life support (dallas predictor tool [DPT]) was used to calculate individual scores for each patient. Individual scores were calculated for prediction of death within 30 min (DPT30) and within 60 min (DPT60). For various resulting DPT30 and DPT60 scores, sensitivity, specificity and area under the receiver operating characteristic curve were calculated. There were 8829 PICU admissions resulting in 132 (1.5%) deaths. Death followed withdrawal of life support in 70 patients (53%). After excluding subjects with insufficient data to calculate DPT scores, 62 subjects were analyzed. Average age of patients was 5.3 years (SD: 6.9), median time to death after withdrawal of life support was 25 min (range; 7 min to 16 h 54 min). Respiratory failure, shock and sepsis were the most common diagnoses. Thirty-seven patients (59.6%) died within 30 min of withdrawal of life support and 52 (83.8%) died within 60 min. DPT30 scores ranged from -17 to 16. A DPT30 score ≥ -3 was most predictive of death within that time period, with sensitivity = 0.76, specificity = 0.52, AUC = 0.69 and an overall classification accuracy = 66.1%. DPT60 scores ranged from -21 to 28. A DPT60 score ≥ -9 was most predictive of death within that time period, with sensitivity = 0.75, specificity = 0.80, AUC = 0.85 and an overall classification accuracy = 75.8%. In this external cohort, the DPT is clinically relevant in predicting time from withdrawal of life support to death. In our patients, the DPT is more useful in predicting death within 60 min of withdrawal of life support

  16. V3 net charge: additional tool in HIV-1 tropism prediction.

    PubMed

    Montagna, Claudia; De Crignis, Elisa; Bon, Isabella; Re, Maria Carla; Mezzaroma, Ivano; Turriziani, Ombretta; Graziosi, Cecilia; Antonelli, Guido

    2014-12-01

    Genotype-based algorithms are valuable tools for the identification of patients eligible for CCR5 inhibitors administration in clinical practice. Among the available methods, geno2pheno[coreceptor] (G2P) is the most used online tool for tropism prediction. This study was conceived to assess if the combination of G2P prediction with V3 peptide net charge (NC) value could improve the accuracy of tropism prediction. A total of 172 V3 bulk sequences from 143 patients were analyzed by G2P and NC values. A phenotypic assay was performed by cloning the complete env gene and tropism determination was assessed on U87_CCR5(+)/CXCR4(+) cells. Sequences were stratified according to the agreement between NC values and G2P results. Of sequences predicted as X4 by G2P, 61% showed NC values higher than 5; similarly, 76% of sequences predicted as R5 by G2P had NC values below 4. Sequences with NC values between 4 and 5 were associated with different G2P predictions: 65% of samples were predicted as R5-tropic and 35% of sequences as X4-tropic. Sequences identified as X4 by NC value had at least one positive residue at positions known to be involved in tropism prediction and positive residues in position 32. These data supported the hypothesis that NC values between 4 and 5 could be associated with the presence of dual/mixed-tropic (DM) variants. The phenotypic assay performed on a subset of sequences confirmed the tropism prediction for concordant sequences and showed that NC values between 4 and 5 are associated with DM tropism. These results suggest that the combination of G2P and NC could increase the accuracy of tropism prediction. A more reliable identification of X4 variants would be useful for better selecting candidates for Maraviroc (MVC) administration, but also as a predictive marker in coreceptor switching, strongly associated with the phase of infection.

  17. 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.

  18. 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.

  19. 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.

  20. Comparison of Predictions of Three Two-Phase Flow Codes

    DTIC Science & Technology

    1977-02-01

    cylinder formula Pzloher, J 0., Wineholt, E. M.s "Analysis of the Friation Behavior at Hxgh Sliding Velocities and Pressure for Gilding Metal, Annealed...Calspan artillery code has been used to simulate several guns. Fisher et aliZ󈧎 reported simulation of a 155mm howitzer with coding adapted to the 155mm...take at least 100 times more computer time than a lumped parameter code. Figure 2 examines the predictions of pressure wave behavior for21 nominal

  1. Kinetic Methods for Predicting Flow Physics of Small Thruster Expansions

    DTIC Science & Technology

    2011-01-24

    K inetic Metho ds for Predicting F low Phys ics of Small Thrus ter Expans ions Deborah A. Levin ∗ The Pennsylvania State University, University Park...dimensional Gaussian , fG, referred to as the Ellipsoidal Statistical (ES) distribution, and the collision term is approximated as [ ∂ ∂t (nf) ] collision = νn...approach. The condensation models included CNT-based nucleation and evapora- tion models as well as coalescence and sticking. In addition a new weighting

  2. Direct comparison of eight national FRAX® tools for fracture prediction and treatment qualification in Canadian women.

    PubMed

    Leslie, W D; Brennan, S L; Lix, L M; Johansson, H; Oden, A; McCloskey, E; Kanis, J A

    2013-01-01

    We compared the calibration of FRAX tools from Canada, the US (white), UK, Sweden, France, Australia, New Zealand, and China when used to assess fracture risk in 36,730 Canadian women. Our data underscores the importance of applying country-specific FRAX tools that are based upon high-quality national fracture epidemiology. A FRAX® model for Canada was constructed for prediction of hip fracture and major osteoporotic fracture (MOF) using national hip fracture and mortality data. We examined the calibration of this model in Canadian women and compared it with seven other FRAX tools. In women aged ≥50 years with baseline bone mineral density (BMD) measures identified from the Manitoba Bone Density Program, Canada (n = 36,730), 10-year fracture probabilities were calculated with and without BMD using selected country-specific FRAX tools. FRAX risk estimates were compared with observed fractures ≤10 years (506 hip, 2,380 MOF). Ten-year fracture risk was compared with predicted probabilities, and proportions exceeding specific treatment thresholds contrasted. For hip fracture prediction, good calibration was observed for FRAX Canada and most other country-specific FRAX tools, excepting Sweden (risk overestimated) and China (risk underestimated). For MOF prediction, greater between-country differences were seen; FRAX Sweden and FRAX China showed the largest over- and underestimation in this Canadian population. Relative to treatment qualification based upon FRAX Canada, treatment of high-hip fracture probability (≥3%) was greater by FRAX Sweden (ratio 1.41 without and 1.55 with BMD), and markedly less by FRAX China (ratio 0.09 without and 0.11 with BMD). Greater between-country differences were observed for treatment of high MOF (≥20%); FRAX Sweden again greatly increased (ratio 1.76 without and 1.83 with BMD), and FRAX China severely reduced treatment qualification (ratio 0.00 without and 0.01 with BMD). The use of country-specific FRAX tools, accurately

  3. 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.

  4. A comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life

    PubMed Central

    Gardner, Paul P.

    2017-01-01

    Abstract Motivation: The aim of this study is to assess the performance of RNA–RNA interaction prediction tools for all domains of life. Results: Minimum free energy (MFE) and alignment methods constitute most of the current RNA interaction prediction algorithms. The MFE tools that include accessibility (i.e. RNAup, IntaRNA and RNAplex) to the final predicted binding energy have better true positive rates (TPRs) with a high positive predictive values (PPVs) in all datasets than other methods. They can also differentiate almost half of the native interactions from background. The algorithms that include effects of internal binding energies to their model and alignment methods seem to have high TPR but relatively low associated PPV compared to accessibility based methods. Availability and Implementation: We shared our wrapper scripts and datasets at Github (github.com/UCanCompBio/RNA_Interactions_Benchmark). All parameters are documented for personal use. Contact: sinan.umu@pg.canterbury.ac.nz Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27993777

  5. Application of grey prediction model to short-time passenger flow forecast

    NASA Astrophysics Data System (ADS)

    Zhang, Zhen; Xu, Xiao; Wang, Zhan

    2017-05-01

    The forecast of passenger flow related to the economic and social benefits of transit enterprise is one of the vehicle dispatching problems which should be solved. This paper put forward a time-division forecasting method of passenger flow. Combining this method with grey system theory, we build a grey prediction model GM(1,1). Its correctness has been tested by some residual test and posterior-variance-test. The method is suitable to the passenger flow forecast of a trip, with high prediction accuracy.

  6. Biodiversity in environmental assessment-current practice and tools for prediction

    SciTech Connect

    Gontier, Mikael . E-mail: gontier@kth.se; Balfors, Berit . E-mail: balfors@kth.se; Moertberg, Ulla . E-mail: mortberg@kth.se

    2006-04-15

    Habitat loss and fragmentation are major threats to biodiversity. Environmental impact assessment and strategic environmental assessment are essential instruments used in physical planning to address such problems. Yet there are no well-developed methods for quantifying and predicting impacts of fragmentation on biodiversity. In this study, a literature review was conducted on GIS-based ecological models that have potential as prediction tools for biodiversity assessment. Further, a review of environmental impact statements for road and railway projects from four European countries was performed, to study how impact prediction concerning biodiversity issues was addressed. The results of the study showed the existing gap between research in GIS-based ecological modelling and current practice in biodiversity assessment within environmental assessment.

  7. Measurement and multidimensional prediction of flow in a axisymmetric port/valve assembly

    SciTech Connect

    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.

  8. Using a unit assessment tool to optimize patient flow and staffing in a community hospital.

    PubMed

    Rozich, John D; Resar, Roger K

    2002-01-01

    Hospital environments are too often characterized by delays for patients receiving diagnostic testing and prolonged waiting times to complete needed therapy. Frequently there is confusion in scheduling, related at least in part to the complex interplay of clinical acuity and highly individualized care. Luther Midelfort recently began to change the process of patient flow to improve access to care, optimize outcomes by enabling timely intervention, and decrease the wasting of resources. The hospital developed a unit assessment tool based on the traffic light concept, which consisted of an assessment of current capacity and a graded, color-coded "workload tolerance" for each hospital unit. Each unit can instantly update its own status and query those of other work environments in the hospital. For most of the January-July 2001 period, there was generally a progressive decrease in the percentage of time that the units were coded as red (unit closed to new admissions), with concurrent increases in the percentage of time that the units were coded as green (unit open). Use of the tool appears to have contributed to a dramatic increase in staff satisfaction. The key to regulating patient flow has been to adopt a nursing-initiated capping trust policy whereby nurses are given the authority to limit new admissions. Initiatives are now under way to provide different units with novel models of resource sharing, ranging from flexible housekeeping to "flying nurse squads" to assist units that have become red.

  9. Residual bias in a multiphase flow model calibration and prediction

    USGS Publications Warehouse

    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.

  10. Predicting regime shifts in flow of the Colorado River

    USGS Publications Warehouse

    Gangopadhyay, Subhrendu; McCabe, Gregory J.

    2010-01-01

    The effects of continued global warming on water resources are a concern for water managers and stake holders. In the western United States, where the combined climatic demand and consumptive use of water is equal to or greater than the natural supply of water for some locations, there is growing concern regarding the sustainability of future water supplies. In addition to the adverse effects of warming on water supply, another issue for water managers is accounting for, and managing, the effects of natural climatic variability, particularly persistently dry and wet periods. Analyses of paleo-reconstructions of Upper Colorado River basin (UCRB) flow demonstrate that severe sustained droughts, and persistent pluvial periods, are a recurring characteristic of hydroclimate in the Colorado River basin. Shifts between persistently dry and wet regimes (e.g., decadal to multi-decadal variability (D2M)) have important implications for water supply and water management. In this study paleo-reconstructions of UCRB flow are used to compute the risks of shifts between persistently wet and dry regimes given the length of time in a specific regime. Results indicate that low frequency variability of hydro-climatic conditions and the statistics that describe this low frequency variability can be useful to water managers by providing information about the risk of shifting from one hydrologic regime to another. To manage water resources in the future water managers will have to understand the joint hydrologic effects of natural climate variability and global warming. These joint effects may produce future hydrologic conditions that are unprecedented in both the instrumental and paleoclimatic records.

  11. Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

    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.

  12. 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.

  13. The removal of nitrogen and organics in vertical flow wetland reactors: predictive models.

    PubMed

    Saeed, Tanveer; Sun, Guangzhi

    2011-01-01

    Three kinetic models, for predicting the removal of nitrogen and organics in vertical flow wetlands, have been developed and evaluated. These models were established by combining first-order, Monod and multiple Monod kinetics with continuous stirred-tank reactor (CSTR) flow pattern. Critical evaluations of these models using three statistical parameters, coefficient of determination, relative root mean square error and model efficiency, indicated that when the Monod/multiple Monod kinetics was combined with CSTR flow pattern it allowed close match between theoretical prediction and experiment data of nitrogen and organics removal. The kinetic coefficients (derived from Monod/multiple Monod kinetics) was found to increase with pollutant loading, indicating that the coefficients may vary based on different factors, such as influent pollutant concentration, hydraulic loading, and water depth. Overall, this study demonstrated the validity of combining Monod and multiple Monod kinetics with CSTR flow pattern for the modelling and design of vertical flow wetland systems.

  14. RAXJET: A computer program for predicting transonic, axisymmetric flow over nozzle afterbodies with supersonic jet exhausts

    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.

  15. Predicting single-phase and two-phase non-Newtonian flow behavior in pipes

    SciTech Connect

    Kaminsky, R.D.

    1998-12-31

    Improved and novel prediction methods are described for single-phase and two-phase flow of non-Newtonian fluids in pipes. Good predictions are achieved for pressure drop, liquid holdup fraction, and two-phase flow regime. The methods are applicable to any visco-inelastic non-Newtonian fluid and include the effect of surface roughness. The methods utilize a reference fluid for which validated models exist. For single-phase flow the use of Newtonian and power-law reference fluids are illustrated. For two-phase flow a Newtonian reference fluid is used. Focus is given to shear-thinning fluids. The approach is theoretically based and is better suited than correlation methods for two-phase flow in high pressure pipelines, for which no experimental data is available in the literature.

  16. Inflammation-driven malnutrition: a new screening tool predicts outcome in Crohn's disease.

    PubMed

    Jansen, Irene; Prager, Matthias; Valentini, Luzia; Büning, Carsten

    2016-09-01

    Malnutrition is a frequent feature in Crohn's disease (CD), affects patient outcome and must be recognised. For chronic inflammatory diseases, recent guidelines recommend the development of combined malnutrition and inflammation risk scores. We aimed to design and evaluate a new screening tool that combines both malnutrition and inflammation parameters that might help predict clinical outcome. In a prospective cohort study, we examined fifty-five patients with CD in remission (Crohn's disease activity index (CDAI) <200) at 0 and 6 months. We assessed disease activity (CDAI, Harvey-Bradshaw index), inflammation (C-reactive protein (CRP), faecal calprotectin (FC)), malnutrition (BMI, subjective global assessment (SGA), serum albumin, handgrip strength), body composition (bioelectrical impedance analysis) and administered the newly developed 'Malnutrition Inflammation Risk Tool' (MIRT; containing BMI, unintentional weight loss over 3 months and CRP). All parameters were evaluated regarding their ability to predict disease outcome prospectively at 6 months. At baseline, more than one-third of patients showed elevated inflammatory markers despite clinical remission (36·4 % CRP ≥5 mg/l, 41·5 % FC ≥100 µg/g). Prevalence of malnutrition at baseline according to BMI, SGA and serum albumin was 2-16 %. At 6 months, MIRT significantly predicted outcome in numerous nutritional and clinical parameters (SGA, CD-related flares, hospitalisations and surgeries). In contrast, SGA, handgrip strength, BMI, albumin and body composition had no influence on the clinical course. The newly developed MIRT was found to reliably predict clinical outcome in CD patients. This screening tool might be used to facilitate clinical decision making, including treatment of both inflammation and malnutrition in order to prevent complications.

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

    NASA Technical Reports Server (NTRS)

    Kandil, Osama

    1993-01-01

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

  18. Results of AGARD assessment of prediction capabilities for nozzle afterbody flows

    NASA Technical Reports Server (NTRS)

    Putnam, L. E.; Bissinger, N. C.

    1985-01-01

    This paper presents a brief review of an assessment conducted by AGARD Working Group 08 to determine the capabilities of theoretical methods for predicting the flow over nozzle afterbody configurations. A series of test cases were selected for which extensive experimental data were available. The assessment was limited to axisymmetric nozzle configurations with a jet simulated with high-pressure air. Contributions were solicited from researchers, identified by a literature search, who had developed methods for predicting such flows. Predictions made with methods that varied in complexity from multicomponent techniques to solutions of the Navier Stokes equations were received. The status of the theoretical methods for predicting nozzle afterbody flows is illustrated by comparison with the experimental measurements.

  19. 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 flows. Spring flow prediction errors associated with the type of hydrological model used are significantly larger than those related to the meteorological predictions, particularly for 1 to 4 days ahead forecasts. The experimental results also indicate that multiple model-based forecasting using an iterative prediction approach appears to be the most effective method for an adequate use of weather predictions. Copyright

  20. Diurnal and seasonal variability in the radial distribution of sap flow: predicting total stem flow in Pinus taeda trees.

    PubMed

    Ford, Chelcy R; Goranson, Carol E; Mitchell, Robert J; Will, Rodney E; Teskey, Robert O

    2004-09-01

    We monitored the radial distribution of sap flux density (v; g H2O m(-2) s(-1)) in the sapwood of six plantation-grown Pinus taeda L. trees during wet and dry soil periods. Mean basal diameter of the 32-year-old trees was 33.3 cm. For all trees, the radial distribution of sap flow in the base of the stem (i.e., radial profile) was Gaussian in shape. Sap flow occurred maximally in the outer 4 cm of sapwood, comprising 50-60% of total stem flow (F), and decreased toward the center, with the innermost 4 cm of sapwood (11-15 cm) comprising less than 10% of F. The percent of flow occurring in the outer 4 cm of sapwood was stable with time (average CV < 10%); however, the percentage of flow occurring in the remaining sapwood was more variable over time (average CV > 40%). Diurnally, the radial profile changed predictably with time and with total stem flow. Seasonally, the radial profile became less steep as the soil water content (theta) declined from 0.38 to 0.21. Throughout the season, daytime sap flow also decreased as theta decreased; however, nighttime sap flow (an estimate of stored water use) remained relatively constant. As a result, the percentage of stored water use increased as theta declined. Time series analysis of 15-min values of F, theta, photosynthetically active radiation (PAR) and vapor pressure deficit (D) showed that F lagged behind D by 0-15 min and behind PAR by 15-30 min. Diurnally, the relation