Common features of microRNA target prediction tools

PubMed Central

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. PMID:24600468

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.

Prediction of blood pressure and blood flow in stenosed renal arteries using CFD

NASA Astrophysics Data System (ADS)

Jhunjhunwala, Pooja; Padole, P. M.; Thombre, S. B.; Sane, Atul

2018-04-01

In the present work an attempt is made to develop a diagnostive tool for renal artery stenosis (RAS) which is inexpensive and in-vitro. To analyse the effects of increase in the degree of severity of stenosis on hypertension and blood flow, haemodynamic parameters are studied by performing numerical simulations. A total of 16 stenosed models with varying degree of stenosis severity from 0-97.11% are assessed numerically. Blood is modelled as a shear-thinning, non-Newtonian fluid using the Carreau model. Computational Fluid Dynamics (CFD) analysis is carried out to compute the values of flow parameters like maximum velocity and maximum pressure attained by blood due to stenosis under pulsatile flow. These values are further used to compute the increase in blood pressure and decrease in available blood flow to kidney. The computed available blood flow and secondary hypertension for varying extent of stenosis are mapped by curve fitting technique using MATLAB and a mathematical model is developed. Based on these mathematical models, a quantification tool is developed for tentative prediction of probable availability of blood flow to the kidney and severity of stenosis if secondary hypertension is known.

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

PubMed

Nielsen, Karina; Cleal, Bryan

2010-04-01

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

A 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.

A collaborative environment for developing and validating predictive tools for protein biophysical characteristics

NASA Astrophysics Data System (ADS)

Johnston, Michael A.; Farrell, Damien; Nielsen, Jens Erik

2012-04-01

The exchange of information between experimentalists and theoreticians is crucial to improving the predictive ability of theoretical methods and hence our understanding of the related biology. However many barriers exist which prevent the flow of information between the two disciplines. Enabling effective collaboration requires that experimentalists can easily apply computational tools to their data, share their data with theoreticians, and that both the experimental data and computational results are accessible to the wider community. We present a prototype collaborative environment for developing and validating predictive tools for protein biophysical characteristics. The environment is built on two central components; a new python-based integration module which allows theoreticians to provide and manage remote access to their programs; and PEATDB, a program for storing and sharing experimental data from protein biophysical characterisation studies. We demonstrate our approach by integrating PEATSA, a web-based service for predicting changes in protein biophysical characteristics, into PEATDB. Furthermore, we illustrate how the resulting environment aids method development using the Potapov dataset of experimentally measured ΔΔGfold values, previously employed to validate and train protein stability prediction algorithms.

A Comprehensive High Performance Predictive Tool for Fusion Liquid Metal Hydromagnetics

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

Huang, Peter; Chhabra, Rupanshi; Munipalli, Ramakanth

In Phase I SBIR project, HyPerComp and Texcel initiated the development of two induction-based MHD codes as a predictive tool for fusion hydro-magnetics. The newly-developed codes overcome the deficiency of other MHD codes based on the quasi static approximation by defining a more general mathematical model that utilizes the induced magnetic field rather than the electric potential as the main electromagnetic variable. The UCLA code is a finite-difference staggered-mesh code that serves as a supplementary tool to the massively-parallel finite-volume code developed by HyPerComp. As there is no suitable experimental data under blanket-relevant conditions for code validation, code-to-code comparisons andmore » comparisons against analytical solutions were successfully performed for three selected test cases: (1) lid-driven MHD flow, (2) flow in a rectangular duct in a transverse magnetic field, and (3) unsteady finite magnetic Reynolds number flow in a rectangular enclosure. The performed tests suggest that the developed codes are accurate and robust. Further work will focus on enhancing the code capabilities towards higher flow parameters and faster computations. At the conclusion of the current Phase-II Project we have completed the preliminary validation efforts in performing unsteady mixed-convection MHD flows (against limited data that is currently available in literature), and demonstrated flow behavior in large 3D channels including important geometrical features. Code enhancements such as periodic boundary conditions, unmatched mesh structures are also ready. As proposed, we have built upon these strengths and explored a much increased range of Grashof numbers and Hartmann numbers under various flow conditions, ranging from flows in a rectangular duct to prototypic blanket modules and liquid metal PFC. Parametric studies, numerical and physical model improvements to expand the scope of simulations, code demonstration, and continued validation activities have

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

Towards a generalized energy prediction model for machine tools

PubMed Central

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

2017-01-01

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. PMID:28652687

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.

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.

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

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

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

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.more » 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.« less

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."

sedFlow - an efficient tool for simulating bedload transport, bed roughness, and longitudinal profile evolution in mountain streams

NASA Astrophysics Data System (ADS)

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

2014-07-01

Especially in mountainuous 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. The model can deal with the effects of adverse slopes and uses state of the art approaches for quantifying macro-roughness effects in steep channels. Local grain size distributions are dynamically adjusted according to the transport dynamics of each grain size fraction. The tool sedFlow features fast calculations and straightforward pre- and postprocessing of simulation data. The model is provided together with its complete source code free of charge under the terms of the GNU General Public License (Flow"target="_blank">www.wsl.ch/sedFlow). Examples of the application of sedFlow are given in a companion article by Heimann et al. (2014).

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

A thermal sensation prediction tool for use by the profession

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

Fountain, M.E.; Huizenga, C.

1997-12-31

As part of a recent ASHRAE research project (781-RP), a thermal sensation prediction tool has been developed. This paper introduces the tool, describes the component thermal sensation models, and presents examples of how the tool can be used in practice. Since the main end product of the HVAC industry is the comfort of occupants indoors, tools for predicting occupant thermal response can be an important asset to designers of indoor climate control systems. The software tool presented in this paper incorporates several existing models for predicting occupant comfort.

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.

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

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.

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)

Predictable turn-around time for post tape-out flow

NASA Astrophysics Data System (ADS)

Endo, Toshikazu; Park, Minyoung; Ghosh, Pradiptya

2012-03-01

A typical post-out flow data path at the IC Fabrication has following major components of software based processing - Boolean operations before the application of resolution enhancement techniques (RET) and optical proximity correctin (OPC), the RET and OPC step [etch retargeting, sub-resolution assist feature insertion (SRAF) and OPC], post-OPCRET Boolean operations and sometimes in the same flow simulation based verification. There are two objectives that an IC Fabrication tapeout flow manager wants to achieve with the flow - predictable completion time and fastest turn-around time (TAT). At times they may be competing. There have been studies in the literature modeling the turnaround time from historical data for runs with the same recipe and later using that to derive the resource allocation for subsequent runs. [3]. This approach is more feasible in predominantly simulation dominated tools but for edge operation dominated flow it may not be possible especially if some processing acceleration methods like pattern matching or hierarchical processing is involved. In this paper, we suggest an alternative method of providing target turnaround time and managing the priority of jobs while not doing any upfront resource modeling and resource planning. The methodology then systematically either meets the turnaround time need and potentially lets the user know if it will not as soon as possible. This builds on top of the Calibre Cluster Management (CalCM) resource management work previously published [1][2]. The paper describes the initial demonstration of the concept.

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.

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.

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.

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

Updating risk prediction tools: a case study in prostate cancer.

PubMed

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

2012-01-01

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. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

Prediction of flow duration curves for ungauged basins

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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.

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.

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…

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.

On the prediction of turbulent secondary flows

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

Flow-covariate prediction of stream pesticide concentrations.

PubMed

Mosquin, Paul L; Aldworth, Jeremy; Chen, Wenlin

2018-01-01

Potential peak functions (e.g., maximum rolling averages over a given duration) of annual pesticide concentrations in the aquatic environment are important exposure parameters (or target quantities) for ecological risk assessments. These target quantities require accurate concentration estimates on nonsampled days in a monitoring program. We examined stream flow as a covariate via universal kriging to improve predictions of maximum m-day (m = 1, 7, 14, 30, 60) rolling averages and the 95th percentiles of atrazine concentration in streams where data were collected every 7 or 14 d. The universal kriging predictions were evaluated against the target quantities calculated directly from the daily (or near daily) measured atrazine concentration at 32 sites (89 site-yr) as part of the Atrazine Ecological Monitoring Program in the US corn belt region (2008-2013) and 4 sites (62 site-yr) in Ohio by the National Center for Water Quality Research (1993-2008). Because stream flow data are strongly skewed to the right, 3 transformations of the flow covariate were considered: log transformation, short-term flow anomaly, and normalized Box-Cox transformation. The normalized Box-Cox transformation resulted in predictions of the target quantities that were comparable to those obtained from log-linear interpolation (i.e., linear interpolation on the log scale) for 7-d sampling. However, the predictions appeared to be negatively affected by variability in regression coefficient estimates across different sample realizations of the concentration time series. Therefore, revised models incorporating seasonal covariates and partially or fully constrained regression parameters were investigated, and they were found to provide much improved predictions in comparison with those from log-linear interpolation for all rolling average measures. Environ Toxicol Chem 2018;37:260-273. © 2017 SETAC. © 2017 SETAC.

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

Measurement and prediction of model-rotor flow fields

NASA Technical Reports Server (NTRS)

Owen, F. K.; Tauber, M. E.

1985-01-01

This paper shows that a laser velocimeter can be used to measure accurately the three-component velocities induced by a model rotor at transonic tip speeds. The measurements, which were made at Mach numbers from 0.85 to 0.95 and at zero advance ratio, yielded high-resolution, orthogonal velocity values. The measured velocities were used to check the ability of the ROT22 full-potential rotor code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high-speed rotor blade. The good agreement between the calculated and measured velocities established the code's ability to predict the off-blade flow field at transonic tip speeds. This supplements previous comparisons in which surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuthal blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip-region flow field, including the occurrence, strength, and location of shock waves causing high drag and noise.

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

Gaussian process regression for tool wear prediction

NASA Astrophysics Data System (ADS)

Kong, Dongdong; Chen, Yongjie; Li, Ning

2018-05-01

To realize and accelerate the pace of intelligent manufacturing, this paper presents a novel tool wear assessment technique based on the integrated radial basis function based kernel principal component analysis (KPCA_IRBF) and Gaussian process regression (GPR) for real-timely and accurately monitoring the in-process tool wear parameters (flank wear width). The KPCA_IRBF is a kind of new nonlinear dimension-increment technique and firstly proposed for feature fusion. The tool wear predictive value and the corresponding confidence interval are both provided by utilizing the GPR model. Besides, GPR performs better than artificial neural networks (ANN) and support vector machines (SVM) in prediction accuracy since the Gaussian noises can be modeled quantitatively in the GPR model. However, the existence of noises will affect the stability of the confidence interval seriously. In this work, the proposed KPCA_IRBF technique helps to remove the noises and weaken its negative effects so as to make the confidence interval compressed greatly and more smoothed, which is conducive for monitoring the tool wear accurately. Moreover, the selection of kernel parameter in KPCA_IRBF can be easily carried out in a much larger selectable region in comparison with the conventional KPCA_RBF technique, which helps to improve the efficiency of model construction. Ten sets of cutting tests are conducted to validate the effectiveness of the presented tool wear assessment technique. The experimental results show that the in-process flank wear width of tool inserts can be monitored accurately by utilizing the presented tool wear assessment technique which is robust under a variety of cutting conditions. This study lays the foundation for tool wear monitoring in real industrial settings.

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

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

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.

Modeling of the flow stress for AISI H13 Tool Steel during Hard Machining Processes

NASA Astrophysics Data System (ADS)

Umbrello, Domenico; Rizzuti, Stefania; Outeiro, José C.; Shivpuri, Rajiv

2007-04-01

In general, the flow stress models used in computer simulation of machining processes are a function of effective strain, effective strain rate and temperature developed during the cutting process. However, these models do not adequately describe the material behavior in hard machining, where a range of material hardness between 45 and 60 HRC are used. Thus, depending on the specific material hardness different material models must be used in modeling the cutting process. This paper describes the development of a hardness-based flow stress and fracture models for the AISI H13 tool steel, which can be applied for range of material hardness mentioned above. These models were implemented in a non-isothermal viscoplastic numerical model to simulate the machining process for AISI H13 with various hardness values and applying different cutting regime parameters. Predicted results are validated by comparing them with experimental results found in the literature. They are found to predict reasonably well the cutting forces as well as the change in chip morphology from continuous to segmented chip as the material hardness change.

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

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

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.

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.

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.

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.

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.

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.

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.

Prediction of Transitional Flows in the Low Pressure Turbine

NASA Technical Reports Server (NTRS)

Huang, George; Xiong, Guohua

1998-01-01

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

Unsteady jet flow computation towards noise prediction

NASA Technical Reports Server (NTRS)

Soh, Woo-Yung

1994-01-01

An attempt has been made to combine a wave solution method and an unsteady flow computation to produce an integrated aeroacoustic code to predict far-field jet noise. An axisymmetric subsonic jet is considered for this purpose. A fourth order space accurate Pade compact scheme is used for the unsteady Navier-Stokes solution. A Kirchhoff surface integral for the wave equation is employed through the use of an imaginary surface which is a circular cylinder enclosing the jet at a distance. Information such as pressure and its time and normal derivatives is provided on the surface. The sound prediction is performed side by side with the jet flow computation. Retarded time is also taken into consideration since the cylinder body is not acoustically compact. The far-field sound pressure has the directivity and spectra show that low frequency peaks shift toward higher frequency region as the observation angle increases from the jet flow axis.

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.

Status of flow separation prediction in liquid propellant rocket nozzles

NASA Technical Reports Server (NTRS)

Schmucker, R. H.

1974-01-01

Flow separation which plays an important role in the design of a rocket engine nozzle is discussed. For a given ambient pressure, the condition of no flow separation limits the area ratio and, therefore, the vacuum performance. Avoidance of performance loss due to area ratio limitation requires a correct prediction of the flow separation conditions. To provide a better understanding of the flow separation process, the principal behavior of flow separation in a supersonic overexpanded rocket nozzle is described. The hot firing separation tests from various sources are summarized, and the applicability and accuracy of the measurements are described. A comparison of the different data points allows an evaluation of the parameters that affect flow separation. The pertinent flow separation predicting methods, which are divided into theoretical and empirical correlations, are summarized and the numerical results are compared with the experimental points.

Transonic cascade flow prediction using the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Arnone, A.; Stecco, S. S.

1991-01-01

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

GAPIT: genome association and prediction integrated tool.

PubMed

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Analysis Tools for CFD Multigrid Solvers

NASA Technical Reports Server (NTRS)

Mineck, Raymond E.; Thomas, James L.; Diskin, Boris

2004-01-01

Analysis tools are needed to guide the development and evaluate the performance of multigrid solvers for the fluid flow equations. Classical analysis tools, such as local mode analysis, often fail to accurately predict performance. Two-grid analysis tools, herein referred to as Idealized Coarse Grid and Idealized Relaxation iterations, have been developed and evaluated within a pilot multigrid solver. These new tools are applicable to general systems of equations and/or discretizations and point to problem areas within an existing multigrid solver. Idealized Relaxation and Idealized Coarse Grid are applied in developing textbook-efficient multigrid solvers for incompressible stagnation flow problems.

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.

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

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

USGS Publications Warehouse

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

2008-01-01

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

Numerical prediction of 3-D ejector flows

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

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...

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.

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.

Predicting bed shear stress and its role in sediment dynamics and restoration potential of the Everglades and other vegetated flow systems

USGS Publications Warehouse

Larsen, Laurel G.; Harvey, Judson; Crimaldi, John P.

2009-01-01

Entrainment of sediment by flowing water affects topography, habitat suitability, and nutrient cycling in vegetated floodplains and wetlands, impacting ecosystem evolution and the success of restoration projects. Nonetheless, restoration managers lack simple decision-support tools for predicting shear stresses and sediment redistribution potential in different vegetation communities. Using a field-validated numerical model, we developed state-space diagrams that provide these predictions over a range of water-surface slopes, depths, and associated velocities in Everglades ridge and slough vegetation communities. Diminished bed shear stresses and a consequent decrease in bed sediment redistribution are hypothesized causes of a recent reduction in the topographic and vegetation heterogeneity of this ecosystem. Results confirmed the inability of present-day flows to entrain bed sediment. Further, our diagrams showed bed shear stresses to be highly sensitive to emergent vegetation density and water-surface slope but less sensitive to water depth and periphyton or floating vegetation abundance. These findings suggested that instituting a pulsing flow regime could be the most effective means to restore sediment redistribution to the Everglades. However, pulsing flows will not be sufficient to erode sediment from sloughs with abundant spikerush, unless spikerush density first decreases by natural or managed processes. Our methods provide a novel tool for identifying restoration parameters and performance measures in many types of vegetated aquatic environments where sediment erosion and deposition are involved.

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.

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

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.

An Exploratory Study of Interactivity in Visualization Tools: "Flow" of Interaction

ERIC Educational Resources Information Center

Liang, Hai-Ning; Parsons, Paul C.; Wu, Hsien-Chi; Sedig, Kamran

2010-01-01

This paper deals with the design of interactivity in visualization tools. There are several factors that can be used to guide the analysis and design of the interactivity of these tools. One such factor is flow, which is concerned with the duration of interaction with visual representations of information--interaction being the actions performed…

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.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Prediction of Complex Aerodynamic Flows with Explicit Algebraic Stress Models

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

Predicting performance with traffic analysis tools : final report.

DOT National Transportation Integrated Search

2008-03-01

This document provides insights into the common pitfalls and challenges associated with use of traffic analysis tools for predicting future performance of a transportation facility. It provides five in-depth case studies that demonstrate common ways ...

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

NASA Technical Reports Server (NTRS)

Levy, L. L., Jr.

1981-01-01

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

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

NASA Technical Reports Server (NTRS)

Abid, R.; Speziale, C. G.

1993-01-01

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

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

NASA Technical Reports Server (NTRS)

Abid, R.; Speziale, C. G.

1992-01-01

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

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.

Successes and Challenges of Incompressible Flow Simulation

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, Cetin

2003-01-01

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

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.

Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

PubMed

Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

2018-05-01

Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization

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

Prediction of unsteady transonic flow around missile configurations

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

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

NASA Technical Reports Server (NTRS)

Lee, Jinho; Platt, Jonathan A.

1993-01-01

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

Evaluation of the hooghoudt and kirkham tile drain equations in the soil and water assessment tool to simulate tile flow and nitrate-nitrogen.

PubMed

Moriasi, Daniel N; Gowda, Prasanna H; Arnold, Jeffrey G; Mulla, David J; Ale, Srinivasulu; Steiner, Jean L; Tomer, Mark D

2013-11-01

Subsurface tile drains in agricultural systems of the midwestern United States are a major contributor of nitrate-N (NO-N) loadings to hypoxic conditions in the Gulf of Mexico. Hydrologic and water quality models, such as the Soil and Water Assessment Tool, are widely used to simulate tile drainage systems. The Hooghoudt and Kirkham tile drain equations in the Soil and Water Assessment Tool have not been rigorously tested for predicting tile flow and the corresponding NO-N losses. In this study, long-term (1983-1996) monitoring plot data from southern Minnesota were used to evaluate the SWAT version 2009 revision 531 (hereafter referred to as SWAT) model for accurately estimating subsurface tile drain flows and associated NO-N losses. A retention parameter adjustment factor was incorporated to account for the effects of tile drainage and slope changes on the computation of surface runoff using the curve number method (hereafter referred to as Revised SWAT). The SWAT and Revised SWAT models were calibrated and validated for tile flow and associated NO-N losses. Results indicated that, on average, Revised SWAT predicted monthly tile flow and associated NO-N losses better than SWAT by 48 and 28%, respectively. For the calibration period, the Revised SWAT model simulated tile flow and NO-N losses within 4 and 1% of the observed data, respectively. For the validation period, it simulated tile flow and NO-N losses within 8 and 2%, respectively, of the observed values. Therefore, the Revised SWAT model is expected to provide more accurate simulation of the effectiveness of tile drainage and NO-N management practices. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

A method for obtaining a statistically stationary turbulent free shear flow

NASA Technical Reports Server (NTRS)

Timson, Stephen F.; Lele, S. K.; Moser, R. D.

1994-01-01

The long-term goal of the current research is the study of Large-Eddy Simulation (LES) as a tool for aeroacoustics. New algorithms and developments in computer hardware are making possible a new generation of tools for aeroacoustic predictions, which rely on the physics of the flow rather than empirical knowledge. LES, in conjunction with an acoustic analogy, holds the promise of predicting the statistics of noise radiated to the far-field of a turbulent flow. LES's predictive ability will be tested through extensive comparison of acoustic predictions based on a Direct Numerical Simulation (DNS) and LES of the same flow, as well as a priori testing of DNS results. The method presented here is aimed at allowing simulation of a turbulent flow field that is both simple and amenable to acoustic predictions. A free shear flow is homogeneous in both the streamwise and spanwise directions and which is statistically stationary will be simulated using equations based on the Navier-Stokes equations with a small number of added terms. Studying a free shear flow eliminates the need to consider flow-surface interactions as an acoustic source. The homogeneous directions and the flow's statistically stationary nature greatly simplify the application of an acoustic analogy.

Predicting Transition from Laminar to Turbulent Flow over a Surface

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

USGS Publications Warehouse

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

in each basin, particle size sorting, average storm intensity (millimeters per hour), soil organic matter content, soil permeability, and soil drainage. The results of this study demonstrate that logistic regression is a valuable tool for predicting the probability of debris flows occurring in recently-burned landscapes.

A conservative fully implicit algorithm for predicting slug flows

NASA Astrophysics Data System (ADS)

Krasnopolsky, Boris I.; Lukyanov, Alexander A.

2018-02-01

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

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

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

Marzouk, Youssef

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesianmore » inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.« less

Application of the Streamflow Prediction Tool to Estimate Sediment Dredging Volumes in Texas Coastal Waterways

NASA Astrophysics Data System (ADS)

Yeates, E.; Dreaper, G.; Afshari, S.; Tavakoly, A. A.

2017-12-01

Over the past six fiscal years, the United States Army Corps of Engineers (USACE) has contracted an average of about a billion dollars per year for navigation channel dredging. To execute these funds effectively, USACE Districts must determine which navigation channels need to be dredged in a given year. Improving this prioritization process results in more efficient waterway maintenance. This study uses the Streamflow Prediction Tool, a runoff routing model based on global weather forecast ensembles, to estimate dredged volumes. This study establishes regional linear relationships between cumulative flow and dredged volumes over a long-term simulation covering 30 years (1985-2015), using drainage area and shoaling parameters. The study framework integrates the National Hydrography Dataset (NHDPlus Dataset) with parameters from the Corps Shoaling Analysis Tool (CSAT) and dredging record data from USACE District records. Results in the test cases of the Houston Ship Channel and the Sabine and Port Arthur Harbor waterways in Texas indicate positive correlation between the simulated streamflows and actual dredging records.

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.

Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

PubMed

Zabor, Emily C; Coit, Daniel; Gershenwald, Jeffrey E; McMasters, Kelly M; Michaelson, James S; Stromberg, Arnold J; Panageas, Katherine S

2018-02-22

Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

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.

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

NASA Technical Reports Server (NTRS)

Mendenhall, Michael R.; Lesieutre, Daniel J.

1987-01-01

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

Prophinder: a computational tool for prophage prediction in prokaryotic genomes.

PubMed

Lima-Mendez, Gipsi; Van Helden, Jacques; Toussaint, Ariane; Leplae, Raphaël

2008-03-15

Prophinder is a prophage prediction tool coupled with a prediction database, a web server and web service. Predicted prophages will help to fill the gaps in the current sparse phage sequence space, which should cover an estimated 100 million species. Systematic and reliable predictions will enable further studies of prophages contribution to the bacteriophage gene pool and to better understand gene shuffling between prophages and phages infecting the same host. Softare is available at http://aclame.ulb.ac.be/prophinder

A Design Tool for Liquid Rocket Engine Injectors

NASA Technical Reports Server (NTRS)

Farmer, R.; Cheng, G.; Trinh, H.; Tucker, K.

2000-01-01

A practical design tool which emphasizes the analysis of flowfields near the injector face of liquid rocket engines has been developed and used to simulate preliminary configurations of NASA's Fastrac and vortex engines. This computational design tool is sufficiently detailed to predict the interactive effects of injector element impingement angles and points and the momenta of the individual orifice flows and the combusting flow which results. In order to simulate a significant number of individual orifices, a homogeneous computational fluid dynamics model was developed. To describe sub- and supercritical liquid and vapor flows, the model utilized thermal and caloric equations of state which were valid over a wide range of pressures and temperatures. The model was constructed such that the local quality of the flow was determined directly. Since both the Fastrac and vortex engines utilize RP-1/LOX propellants, a simplified hydrocarbon combustion model was devised in order to accomplish three-dimensional, multiphase flow simulations. Such a model does not identify drops or their distribution, but it does allow the recirculating flow along the injector face and into the acoustic cavity and the film coolant flow to be accurately predicted.

Substance flow analysis as a tool for urban water management.

PubMed

Chèvre, N; Guignard, C; Rossi, L; Pfeifer, H-R; Bader, H-P; Scheidegger, R

2011-01-01

Human activity results in the production of a wide range of pollutants that can enter the water cycle through stormwater or wastewater. Among others, heavy metals are still detected in high concentrations around urban areas and their impact on aquatic organisms is of major concern. In this study, we propose to use a substance flow analysis as a tool for heavy metals management in urban areas. We illustrate the approach with the case of copper in Lausanne, Switzerland. The results show that around 1,500 kg of copper enter the aquatic compartment yearly. This amount contributes to sediment enrichment, which may pose a long-term risk for benthic organisms. The major sources of copper in receiving surface water are roofs and catenaries of trolleybuses. They represent 75% of the total input of copper into the urban water system. Actions to reduce copper pollution should therefore focus on these sources. Substance flow analysis also highlights that copper enters surface water mainly during rain events, i.e., without passing through any treatment procedure. A reduction in pollution could also be achieved by improving stormwater management. In conclusion, the study showed that substance flow analysis is a very effective tool for sustainable urban water management.

CFD Validation Studies for Hypersonic Flow Prediction

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2001-01-01

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

CFD Validation Studies for Hypersonic Flow Prediction

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.

2001-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-02-01

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

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.

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.

FlowCal: A user-friendly, open source software tool for automatically converting flow cytometry data from arbitrary to calibrated units

PubMed Central

Castillo-Hair, Sebastian M.; Sexton, John T.; Landry, Brian P.; Olson, Evan J.; Igoshin, Oleg A.; Tabor, Jeffrey J.

2017-01-01

Flow cytometry is widely used to measure gene expression and other molecular biological processes with single cell resolution via fluorescent probes. Flow cytometers output data in arbitrary units (a.u.) that vary with the probe, instrument, and settings. Arbitrary units can be converted to the calibrated unit molecules of equivalent fluorophore (MEF) using commercially available calibration particles. However, there is no convenient, non-proprietary tool available to perform this calibration. Consequently, most researchers report data in a.u., limiting interpretation. Here, we report a software tool named FlowCal to overcome current limitations. FlowCal can be run using an intuitive Microsoft Excel interface, or customizable Python scripts. The software accepts Flow Cytometry Standard (FCS) files as inputs and is compatible with different calibration particles, fluorescent probes, and cell types. Additionally, FlowCal automatically gates data, calculates common statistics, and produces publication quality plots. We validate FlowCal by calibrating a.u. measurements of E. coli expressing superfolder GFP (sfGFP) collected at 10 different detector sensitivity (gain) settings to a single MEF value. Additionally, we reduce day-to-day variability in replicate E. coli sfGFP expression measurements due to instrument drift by 33%, and calibrate S. cerevisiae mVenus expression data to MEF units. Finally, we demonstrate a simple method for using FlowCal to calibrate fluorescence units across different cytometers. FlowCal should ease the quantitative analysis of flow cytometry data within and across laboratories and facilitate the adoption of standard fluorescence units in synthetic biology and beyond. PMID:27110723

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

TAS: A Transonic Aircraft/Store flow field prediction code

NASA Technical Reports Server (NTRS)

Thompson, D. S.

1983-01-01

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

Predictive model for convective flows induced by surface reactivity contrast

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Fuzzy regression modeling for tool performance prediction and degradation detection.

PubMed

Li, X; Er, M J; Lim, B S; Zhou, J H; Gan, O P; Rutkowski, L

2010-10-01

In this paper, the viability of using Fuzzy-Rule-Based Regression Modeling (FRM) algorithm for tool performance and degradation detection is investigated. The FRM is developed based on a multi-layered fuzzy-rule-based hybrid system with Multiple Regression Models (MRM) embedded into a fuzzy logic inference engine that employs Self Organizing Maps (SOM) for clustering. The FRM converts a complex nonlinear problem to a simplified linear format in order to further increase the accuracy in prediction and rate of convergence. The efficacy of the proposed FRM is tested through a case study - namely to predict the remaining useful life of a ball nose milling cutter during a dry machining process of hardened tool steel with a hardness of 52-54 HRc. A comparative study is further made between four predictive models using the same set of experimental data. It is shown that the FRM is superior as compared with conventional MRM, Back Propagation Neural Networks (BPNN) and Radial Basis Function Networks (RBFN) in terms of prediction accuracy and learning speed.

Does the uncertainty in the representation of terrestrial water flows affect precipitation predictability? A WRF-Hydro ensemble analysis for Central Europe

NASA Astrophysics Data System (ADS)

Arnault, Joel; Rummler, Thomas; Baur, Florian; Lerch, Sebastian; Wagner, Sven; Fersch, Benjamin; Zhang, Zhenyu; Kerandi, Noah; Keil, Christian; Kunstmann, Harald

2017-04-01

Precipitation predictability can be assessed by the spread within an ensemble of atmospheric simulations being perturbed in the initial, lateral boundary conditions and/or modeled processes within a range of uncertainty. Surface-related processes are more likely to change precipitation when synoptic forcing is weak. This study investigates the effect of uncertainty in the representation of terrestrial water flows on precipitation predictability. The tools used for this investigation are the Weather Research and Forecasting (WRF) model and its hydrologically-enhanced version WRF-Hydro, applied over Central Europe during April-October 2008. The WRF grid is that of COSMO-DE, with a resolution of 2.8 km. In WRF-Hydro, the WRF grid is coupled with a sub-grid at 280 m resolution to resolve lateral terrestrial water flows. Vertical flow uncertainty is considered by modifying the parameter controlling the partitioning between surface runoff and infiltration in WRF, and horizontal flow uncertainty is considered by comparing WRF with WRF-Hydro. Precipitation predictability is deduced from the spread of an ensemble based on three turbulence parameterizations. Model results are validated with E-OBS precipitation and surface temperature, ESA-CCI soil moisture, FLUXNET-MTE surface evaporation and GRDC discharge. It is found that the uncertainty in the representation of terrestrial water flows is more likely to significantly affect precipitation predictability when surface flux spatial variability is high. In comparison to the WRF ensemble, WRF-Hydro slightly improves the adjusted continuous ranked probability score of daily precipitation. The reproduction of observed daily discharge with Nash-Sutcliffe model efficiency coefficients up to 0.91 demonstrates the potential of WRF-Hydro for flood forecasting.

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

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

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.

Stability of compressible Taylor-Couette flow

NASA Technical Reports Server (NTRS)

Kao, K.; Chow, C.

1992-01-01

The objectives of this paper are to: (1) develop both analytical and numerical tools that can be used to predict the onset of instability and subsequently to simulate the transition process by which the originally laminar flow evolves into a turbulent flow; and (2) conduct the preliminary investigations with the purpose of understanding the mechanisms of the vortical structures of the compressible flow between tow concentric cylinders.

Flow in the Proximity of the Pin-Tool in Friction Stir Welding and Its Relation to Weld Homogeneity

NASA Technical Reports Server (NTRS)

Nunes, Arthur C., Jr.

2000-01-01

In the Friction Stir Welding (FSW) process a rotating pin inserted into a seam literally stirs the metal from each side of the seam together. It is proposed that the flow in the vicinity of the pin-tool comprises a primary rapid shear over a cylindrical envelope covering the pin-tool and a relatively slow secondary flow taking the form of a ring vortex about the tool circumference. This model is consistent with a plastic characterization of metal flow, where discontinuities in shear flow are allowed but not viscous effects. It is consistent with experiments employing several different kinds of tracer: atomic markers, shot, and wire. If a rotating disc with angular velocity w is superposed on a translating continuum with linear velocity omega, the trajectories of tracer points become circular arcs centered upon a point displaced laterally a distance v/omega from the center of rotation of the disc in the direction of the advancing side of the disc. In the present model a stream of metal approaching the tool (taken as the coordinate system of observation) is sheared at the slip surface, rapidly rotated around the tool, sheared again on the opposite side of the tool, and deposited in the wake of the tool. Local shearing rates are high, comparable to metal cutting in this model. The flow patterns in the vicinity of the pin-tool determine the level of homogenization and dispersal of contaminants that occurs in the FSW process. The approaching metal streams enfold one another as they are rotated around the tool. Neglecting mixing they return to the same lateral position in the wake of the tool preserving lateral tracer positions as if the metal had flowed past the tool like an extrusion instead of being rotated around it. (The seam is, however, obliterated.) The metal stream of thickness approximately that of the tool diameter D is wiped past the tool at elevated temperatures drawn out to a thickness of v/2(omega) in the wiping zone. Mixing distances in the wiping zone

Design of Environmental Flows Below Diversion Hydropower Dams: Is There Benefit to Advanced Streamflow Prediction in Sparse Data Landscapes?

NASA Astrophysics Data System (ADS)

Kibler, K. M.; Alipour, M.

2017-12-01

Diversion hydropower has been shown to significantly alter river flow regimes by dewatering diversion bypass reaches. Data scarcity is one of the foremost challenges to establishing environmental flow regimes below diversion hydropower dams, especially in regions of sparse hydro-meteorological observation. Herein, we test two prediction strategies for generating daily flows in rivers developed with diversion hydropower: a catchment similarity model, and a rainfall-runoff model selected by multi-objective optimization based on soft data. While both methods are designed for ungauged rivers embedded within large regions of sparse hydrologic observation, one is more complex and computationally-intensive. The objective of this study is to assess the benefit of using complex modeling tools in data-sparse landscapes to support design of environmental flow regimes. Models were tested in gauged catchments and then used to simulate a 28-year record of daily flows in 32 ungauged rivers. After perturbing flows with the hydropower diversion, we detect alteration using Indicators of Hydrologic Alteration (IHA) metrics and compare outcomes of the two modeling approaches. The catchment similarity model simulates low flows well (Nash-Sutcliff efficiency (NSE) = 0.91), but poorly represents moderate to high flows (overall NSE = 0.25). The multi-objective rainfall-runoff model performs well overall (NSE = 0.72). Both models agree that flow magnitudes and variability consistently decrease following diversion as temporally-dynamic flows are replaced by static minimal flows. Mean duration of events sustained below the pre-diversion Q75 and mean hydrograph rise and fall rates increase. While we see broad areas of agreement, significant effects and thresholds vary between models, particularly in the representation of moderate flows. Thus, use of simplified streamflow models may bias detected alterations or inadequately characterize pre-regulation flow regimes, providing inaccurate

Computational Challenges of Viscous Incompressible Flows

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1990-01-01

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

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

NASA Technical Reports Server (NTRS)

Moore, John; Moore, Joan G.

1989-01-01

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

Predicting tool life in turning operations using neural networks and image processing

NASA Astrophysics Data System (ADS)

Mikołajczyk, T.; Nowicki, K.; Bustillo, A.; Yu Pimenov, D.

2018-05-01

A two-step method is presented for the automatic prediction of tool life in turning operations. First, experimental data are collected for three cutting edges under the same constant processing conditions. In these experiments, the parameter of tool wear, VB, is measured with conventional methods and the same parameter is estimated using Neural Wear, a customized software package that combines flank wear image recognition and Artificial Neural Networks (ANNs). Second, an ANN model of tool life is trained with the data collected from the first two cutting edges and the subsequent model is evaluated on two different subsets for the third cutting edge: the first subset is obtained from the direct measurement of tool wear and the second is obtained from the Neural Wear software that estimates tool wear using edge images. Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements. These results confirm that the combination of image recognition software and ANN modelling could potentially be developed into a useful industrial tool for low-cost estimation of tool life in turning operations.

Streamflow Prediction in Ungauged, Irrigated Basins

NASA Astrophysics Data System (ADS)

Zhang, M.; Thompson, S. E.

2016-12-01

The international "predictions in ungauged basins" or "PUB" effort has broadened and improved the tools available to support water resources management in sparsely observed regions. These tools have, however, been primarily focused on regions with limited diversion of surface or shallow groundwater resources. Incorporating anthropogenic activity into PUB methods is essential given the high level of development of many basins. We extended an existing stochastic framework used to predict the flow duration curve to explore the effects of irrigation on streamflow dynamics. Four canonical scenarios were considered in which irrigation water was (i) primarily sourced from water imports, (ii) primarily sourced from direct in-channel diversions, (iii) sourced from shallow groundwater with direct connectivity to stream channels, or (iv) sourced from deep groundwater that is indirectly connected to surface flow via a shallow aquifer. By comparing the predicted flow duration curves to those predicted by accounting for climate and geomorphic factors in isolation, specific "fingerprints" of human water withdrawals could be identified for the different irrigation scenarios, and shown to be sensitive to irrigation volumes and scheduling. The results provide a first insight into PUB methodologies that could be employed in heavily managed basins.

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.

PolNet: A Tool to Quantify Network-Level Cell Polarity and Blood Flow in Vascular Remodeling.

PubMed

Bernabeu, Miguel O; Jones, Martin L; Nash, Rupert W; Pezzarossa, Anna; Coveney, Peter V; Gerhardt, Holger; Franco, Claudio A

2018-05-08

In this article, we present PolNet, an open-source software tool for the study of blood flow and cell-level biological activity during vessel morphogenesis. We provide an image acquisition, segmentation, and analysis protocol to quantify endothelial cell polarity in entire in vivo vascular networks. In combination, we use computational fluid dynamics to characterize the hemodynamics of the vascular networks under study. The tool enables, to our knowledge for the first time, a network-level analysis of polarity and flow for individual endothelial cells. To date, PolNet has proven invaluable for the study of endothelial cell polarization and migration during vascular patterning, as demonstrated by two recent publications. Additionally, the tool can be easily extended to correlate blood flow with other experimental observations at the cellular/molecular level. We release the source code of our tool under the Lesser General Public License. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Predictive Tools for Severe Dengue Conforming to World Health Organization 2009 Criteria

PubMed Central

Carrasco, Luis R.; Leo, Yee Sin; Cook, Alex R.; Lee, Vernon J.; Thein, Tun L.; Go, Chi Jong; Lye, David C.

2014-01-01

Background Dengue causes 50 million infections per year, posing a large disease and economic burden in tropical and subtropical regions. Only a proportion of dengue cases require hospitalization, and predictive tools to triage dengue patients at greater risk of complications may optimize usage of limited healthcare resources. For severe dengue (SD), proposed by the World Health Organization (WHO) 2009 dengue guidelines, predictive tools are lacking. Methods We undertook a retrospective study of adult dengue patients in Tan Tock Seng Hospital, Singapore, from 2006 to 2008. Demographic, clinical and laboratory variables at presentation from dengue polymerase chain reaction-positive and serology-positive patients were used to predict the development of SD after hospitalization using generalized linear models (GLMs). Principal findings Predictive tools compatible with well-resourced and resource-limited settings – not requiring laboratory measurements – performed acceptably with optimism-corrected specificities of 29% and 27% respectively for 90% sensitivity. Higher risk of severe dengue (SD) was associated with female gender, lower than normal hematocrit level, abdominal distension, vomiting and fever on admission. Lower risk of SD was associated with more years of age (in a cohort with an interquartile range of 27–47 years of age), leucopenia and fever duration on admission. Among the warning signs proposed by WHO 2009, we found support for abdominal pain or tenderness and vomiting as predictors of combined forms of SD. Conclusions The application of these predictive tools in the clinical setting may reduce unnecessary admissions by 19% allowing the allocation of scarce public health resources to patients according to the severity of outcomes. PMID:25010515

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.

iPat: intelligent prediction and association tool for genomic research.

PubMed

Chen, Chunpeng James; Zhang, Zhiwu

2018-06-01

The ultimate goal of genomic research is to effectively predict phenotypes from genotypes so that medical management can improve human health and molecular breeding can increase agricultural production. Genomic prediction or selection (GS) plays a complementary role to genome-wide association studies (GWAS), which is the primary method to identify genes underlying phenotypes. Unfortunately, most computing tools cannot perform data analyses for both GWAS and GS. Furthermore, the majority of these tools are executed through a command-line interface (CLI), which requires programming skills. Non-programmers struggle to use them efficiently because of the steep learning curves and zero tolerance for data formats and mistakes when inputting keywords and parameters. To address these problems, this study developed a software package, named the Intelligent Prediction and Association Tool (iPat), with a user-friendly graphical user interface. With iPat, GWAS or GS can be performed using a pointing device to simply drag and/or click on graphical elements to specify input data files, choose input parameters and select analytical models. Models available to users include those implemented in third party CLI packages such as GAPIT, PLINK, FarmCPU, BLINK, rrBLUP and BGLR. Users can choose any data format and conduct analyses with any of these packages. File conversions are automatically conducted for specified input data and selected packages. A GWAS-assisted genomic prediction method was implemented to perform genomic prediction using any GWAS method such as FarmCPU. iPat was written in Java for adaptation to multiple operating systems including Windows, Mac and Linux. The iPat executable file, user manual, tutorials and example datasets are freely available at http://zzlab.net/iPat. zhiwu.zhang@wsu.edu.

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.

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.

Prostate cancer: predicting high-risk prostate cancer-a novel stratification tool.

PubMed

Buck, Jessica; Chughtai, Bilal

2014-05-01

Currently, numerous systems exist for the identification of high-risk prostate cancer, but few of these systems can guide treatment strategies. A new stratification tool that uses common diagnostic factors can help to predict outcomes after radical prostatectomy. The tool aids physicians in the identification of appropriate candidates for aggressive, local treatment.

Prediction Of Abrasive And Diffusive Tool Wear Mechanisms In Machining

NASA Astrophysics Data System (ADS)

Rizzuti, S.; Umbrello, D.

2011-01-01

Tool wear prediction is regarded as very important task in order to maximize tool performance, minimize cutting costs and improve the quality of workpiece in cutting. In this research work, an experimental campaign was carried out at the varying of cutting conditions with the aim to measure both crater and flank tool wear, during machining of an AISI 1045 with an uncoated carbide tool P40. Parallel a FEM-based analysis was developed in order to study the tool wear mechanisms, taking also into account the influence of the cutting conditions and the temperature reached on the tool surfaces. The results show that, when the temperature of the tool rake surface is lower than the activation temperature of the diffusive phenomenon, the wear rate can be estimated applying an abrasive model. In contrast, in the tool area where the temperature is higher than the diffusive activation temperature, the wear rate can be evaluated applying a diffusive model. Finally, for a temperature ranges within the above cited values an adopted abrasive-diffusive wear model furnished the possibility to correctly evaluate the tool wear phenomena.

Overview of the Aeroelastic Prediction Workshop

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Chwalowski, Pawel; Schuster, David M.; Dalenbring, Mats

2013-01-01

The AIAA Aeroelastic Prediction Workshop (AePW) was held in April, 2012, bringing together communities of aeroelasticians and computational fluid dynamicists. The objective in conducting this workshop on aeroelastic prediction was to assess state-of-the-art computational aeroelasticity methods as practical tools for the prediction of static and dynamic aeroelastic phenomena. No comprehensive aeroelastic benchmarking validation standard currently exists, greatly hindering validation and state-of-the-art assessment objectives. The workshop was a step towards assessing the state of the art in computational aeroelasticity. This was an opportunity to discuss and evaluate the effectiveness of existing computer codes and modeling techniques for unsteady flow, and to identify computational and experimental areas needing additional research and development. Three configurations served as the basis for the workshop, providing different levels of geometric and flow field complexity. All cases considered involved supercritical airfoils at transonic conditions. The flow fields contained oscillating shocks and in some cases, regions of separation. The computational tools principally employed Reynolds-Averaged Navier Stokes solutions. The successes and failures of the computations and the experiments are examined in this paper.

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…

Prediction of unsteady separated flows on oscillating airfoils

NASA Technical Reports Server (NTRS)

Mccroskey, W. J.

1978-01-01

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

Understanding Interrater Reliability and Validity of Risk Assessment Tools Used to Predict Adverse Clinical Events.

PubMed

Siedlecki, Sandra L; Albert, Nancy M

This article will describe how to assess interrater reliability and validity of risk assessment tools, using easy-to-follow formulas, and to provide calculations that demonstrate principles discussed. Clinical nurse specialists should be able to identify risk assessment tools that provide high-quality interrater reliability and the highest validity for predicting true events of importance to clinical settings. Making best practice recommendations for assessment tool use is critical to high-quality patient care and safe practices that impact patient outcomes and nursing resources. Optimal risk assessment tool selection requires knowledge about interrater reliability and tool validity. The clinical nurse specialist will understand the reliability and validity issues associated with risk assessment tools, and be able to evaluate tools using basic calculations. Risk assessment tools are developed to objectively predict quality and safety events and ultimately reduce the risk of event occurrence through preventive interventions. To ensure high-quality tool use, clinical nurse specialists must critically assess tool properties. The better the tool's ability to predict adverse events, the more likely that event risk is mediated. Interrater reliability and validity assessment is relatively an easy skill to master and will result in better decisions when selecting or making recommendations for risk assessment tool use.

Vortical Flow Prediction Using an Adaptive Unstructured Grid Method

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2001-01-01

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

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.

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

Prediction Markets: Another Tool in the Intelligence Kitbag

DTIC Science & Technology

2007-02-20

the eminent British anthropologist and statistician, Francis Galton . He was passing by an English county fair when he noticed an advertisement for a...available from http://libnt4.lib.tcu.edu/staff/bellinger/essays/ untruth.htm; Internet; accessed 14 December 2006. 18 Francis Galton , Memories of My Life...USAWC STRATEGY RESEARCH PROJECT PREDICTION MARKETS: ANOTHER TOOL IN THE INTELLIGENCE KITBAG by Colonel

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.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Comparison of the Nosocomial Pneumonia Mortality Prediction (NPMP) model with standard mortality prediction tools.

PubMed

Srinivasan, M; Shetty, N; Gadekari, S; Thunga, G; Rao, K; Kunhikatta, V

2017-07-01

Severity or mortality prediction of nosocomial pneumonia could aid in the effective triage of patients and assisting physicians. To compare various severity assessment scoring systems for predicting intensive care unit (ICU) mortality in nosocomial pneumonia patients. A prospective cohort study was conducted in a tertiary care university-affiliated hospital in Manipal, India. One hundred patients with nosocomial pneumonia, admitted in the ICUs who developed pneumonia after >48h of admission, were included. The Nosocomial Pneumonia Mortality Prediction (NPMP) model, developed in our hospital, was compared with Acute Physiology and Chronic Health Evaluation II (APACHE II), Mortality Probability Model II (MPM 72  II), Simplified Acute Physiology Score II (SAPS II), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Clinical Pulmonary Infection Score (CPIS), Ventilator-Associated Pneumonia Predisposition, Insult, Response, Organ dysfunction (VAP-PIRO). Data and clinical variables were collected on the day of pneumonia diagnosis. The outcome for the study was ICU mortality. The sensitivity and specificity of the various scoring systems was analysed by plotting receiver operating characteristic (ROC) curves and computing the area under the curve for each of the mortality predicting tools. NPMP, APACHE II, SAPS II, MPM 72  II, SOFA, and VAP-PIRO were found to have similar and acceptable discrimination power as assessed by the area under the ROC curve. The AUC values for the above scores ranged from 0.735 to 0.762. CPIS and MODS showed least discrimination. NPMP is a specific tool to predict mortality in nosocomial pneumonia and is comparable to other standard scores. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

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.

The combination of kinetic and flow cytometric semen parameters as a tool to predict fertility in cryopreserved bull semen.

PubMed

Gliozzi, T M; Turri, F; Manes, S; Cassinelli, C; Pizzi, F

2017-11-01

Within recent years, there has been growing interest in the prediction of bull fertility through in vitro assessment of semen quality. A model for fertility prediction based on early evaluation of semen quality parameters, to exclude sires with potentially low fertility from breeding programs, would therefore be useful. The aim of the present study was to identify the most suitable parameters that would provide reliable prediction of fertility. Frozen semen from 18 Italian Holstein-Friesian proven bulls was analyzed using computer-assisted semen analysis (CASA) (motility and kinetic parameters) and flow cytometry (FCM) (viability, acrosomal integrity, mitochondrial function, lipid peroxidation, plasma membrane stability and DNA integrity). Bulls were divided into two groups (low and high fertility) based on the estimated relative conception rate (ERCR). Significant differences were found between fertility groups for total motility, active cells, straightness, linearity, viability and percentage of DNA fragmented sperm. Correlations were observed between ERCR and some kinetic parameters, and membrane instability and some DNA integrity indicators. In order to define a model with high relation between semen quality parameters and ERCR, backward stepwise multiple regression analysis was applied. Thus, we obtained a prediction model that explained almost half (R 2=0.47, P<0.05) of the variation in the conception rate and included nine variables: five kinetic parameters measured by CASA (total motility, active cells, beat cross frequency, curvilinear velocity and amplitude of lateral head displacement) and four parameters related to DNA integrity evaluated by FCM (degree of chromatin structure abnormality Alpha-T, extent of chromatin structure abnormality (Alpha-T standard deviation), percentage of DNA fragmented sperm and percentage of sperm with high green fluorescence representative of immature cells). A significant relationship (R 2=0.84, P<0.05) was observed between

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.

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

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

Palefsky, S; Roper, J; Elder, E

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 Bayesmore » 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.« less

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.

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

Fundamental Study of Material Flow in Friction Stir Welds

NASA Technical Reports Server (NTRS)

Reynolds, Anthony P.

1999-01-01

The presented research project consists of two major parts. First, the material flow in solid-state, friction stir, butt-welds as been investigated using a marker insert technique. Changes in material flow due to welding parameter as well as tool geometry variations have been examined for different materials. The method provides a semi-quantitative, three-dimensional view of the material transport in the welded zone. Second, a FSW process model has been developed. The fully coupled model is based on fluid mechanics; the solid-state material transport during welding is treated as a laminar, viscous flow of a non-Newtonian fluid past a rotating circular cylinder. The heat necessary for the material softening is generated by deformation of the material. As a first step, a two-dimensional model, which contains only the pin of the FSW tool, has been created to test the suitability of the modeling approach and to perform parametric studies of the boundary conditions. The material flow visualization experiments agree very well with the predicted flow field. Accordingly, material within the pin diameter is transported only in the rotation direction around the pin. Due to the simplifying assumptions inherent in the 2-D model, other experimental data such as forces on the pin, torque, and weld energy cannot be directly used for validation. However, the 2-D model predicts the same trends as shown in the experiments. The model also predicts a deviation from the "normal" material flow at certain combinations of welding parameters, suggesting a possible mechanism for the occurrence of some typical FSW defects. The next step has been the development of a three-dimensional process model. The simplified FSW tool has been designed as a flat shoulder rotating on the top of the workpiece and a rotating, cylindrical pin, which extends throughout the total height of the flow domain. The thermal boundary conditions at the tool and at the contact area to the backing plate have been varied

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.

A systematic review on popularity, application and characteristics of protein secondary structure prediction tools.

PubMed

Kashani-Amin, Elaheh; Tabatabaei-Malazy, Ozra; Sakhteman, Amirhossein; Larijani, Bagher; Ebrahim-Habibi, Azadeh

2018-02-27

Prediction of proteins' secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple secondary structure prediction (SSP) options is challenging. The current study is an insight onto currently favored methods and tools, within various contexts. A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of 209 studies were finally found eligible to extract data. Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating a SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. This study provides a comprehensive insight about the recent usage of SSP tools which could be helpful for selecting a proper tool's choice. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

PNS predictions for supersonic/hypersonic flows over finned missile configurations

NASA Technical Reports Server (NTRS)

Bhutta, Bilal A.; Lewis, Clark H.

1992-01-01

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

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.

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

PubMed Central

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. Availability http://www.cemb.edu.pk/sw.html Abbreviations RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language. PMID:23055611

Musite, a tool for global prediction of general and kinase-specific phosphorylation sites.

PubMed

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

2010-12-01

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

Modeling and Visualizing Flow of Chemical Agents Across Complex Terrain

NASA Technical Reports Server (NTRS)

Kao, David; Kramer, Marc; Chaderjian, Neal

2005-01-01

Release of chemical agents across complex terrain presents a real threat to homeland security. Modeling and visualization tools are being developed that capture flow fluid terrain interaction as well as point dispersal downstream flow paths. These analytic tools when coupled with UAV atmospheric observations provide predictive capabilities to allow for rapid emergency response as well as developing a comprehensive preemptive counter-threat evacuation plan. The visualization tools involve high-end computing and massive parallel processing combined with texture mapping. We demonstrate our approach across a mountainous portion of North California under two contrasting meteorological conditions. Animations depicting flow over this geographical location provide immediate assistance in decision support and crisis management.

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.

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

A Comparison of Predictive Thermo and Water Solvation Property Prediction Tools and Experimental Data for Selected Traditional Chemical Warfare Agents and Simulants II: COSMO RS and COSMOTherm

DTIC Science & Technology

2017-04-01

A COMPARISON OF PREDICTIVE THERMO AND WATER SOLVATION PROPERTY PREDICTION TOOLS AND EXPERIMENTAL DATA FOR...4. TITLE AND SUBTITLE A Comparison of Predictive Thermo and Water Solvation Property Prediction Tools and Experimental Data for Selected...1  2.  EXPERIMENTAL PROCEDURE

Predicting the impact of land management decisions on overland flow generation: Implications for cesium migration in forested Fukushima watersheds

NASA Astrophysics Data System (ADS)

Siirila-Woodburn, Erica R.; Steefel, Carl I.; Williams, Kenneth H.; Birkholzer, Jens T.

2018-03-01

The effects of land use and land cover (LULC) change on environmental systems across the land surface's "critical zone" are highly uncertain, often making prediction and risk management decision difficult. In a series of numerical experiments with an integrated hydrologic model, overland flow generation is quantified for both present day and forest thinning scenarios. A typhoon storm event in a watershed near the Fukushima Dai-ichi Nuclear Power Plant is used as an example application in which the interplay between LULC change and overland flow generation is important given that sediment-bound radionuclides may cause secondary contamination via surface water transport. Results illustrate the nonlinearity of the integrated system spanning from the deep groundwater to the atmosphere, and provide quantitative tools when determining the tradeoffs of different risk-mitigation strategies.

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.

Predicting pathogen growth during short-term temperature abuse of raw pork, beef, and poultry products: use of an isothermal-based predictive tool.

PubMed

Ingham, Steven C; Fanslau, Melody A; Burnham, Greg M; Ingham, Barbara H; Norback, John P; Schaffner, Donald W

2007-06-01

A computer-based tool (available at: www.wisc.edu/foodsafety/meatresearch) was developed for predicting pathogen growth in raw pork, beef, and poultry meat. The tool, THERM (temperature history evaluation for raw meats), predicts the growth of pathogens in pork and beef (Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus) and on poultry (Salmonella serovars and S. aureus) during short-term temperature abuse. The model was developed as follows: 25-g samples of raw ground pork, beef, and turkey were inoculated with a five-strain cocktail of the target pathogen(s) and held at isothermal temperatures from 10 to 43.3 degrees C. Log CFU per sample data were obtained for each pathogen and used to determine lag-phase duration (LPD) and growth rate (GR) by DMFit software. The LPD and GR were used to develop the THERM predictive tool, into which chronological time and temperature data for raw meat processing and storage are entered. The THERM tool then predicts a delta log CFU value for the desired pathogen-product combination. The accuracy of THERM was tested in 20 different inoculation experiments that involved multiple products (coarse-ground beef, skinless chicken breast meat, turkey scapula meat, and ground turkey) and temperature-abuse scenarios. With the time-temperature data from each experiment, THERM accurately predicted the pathogen growth and no growth (with growth defined as delta log CFU > 0.3) in 67, 85, and 95% of the experiments with E. coli 0157:H7, Salmonella serovars, and S. aureus, respectively, and yielded fail-safe predictions in the remaining experiments. We conclude that THERM is a useful tool for qualitatively predicting pathogen behavior (growth and no growth) in raw meats. Potential applications include evaluating process deviations and critical limits under the HACCP (hazard analysis critical control point) system.

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.

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.

Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

NASA Astrophysics Data System (ADS)

Okokpujie, Imhade Princess; Ikumapayi, Omolayo M.; Okonkwo, Ugochukwu C.; Salawu, Enesi Y.; Afolalu, Sunday A.; Dirisu, Joseph O.; Nwoke, Obinna N.; Ajayi, Oluseyi O.

2017-12-01

In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

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.

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. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Development of a CME-associated geomagnetic storm intensity prediction tool

NASA Astrophysics Data System (ADS)

Wu, C. C.; DeHart, J. M.

2015-12-01

From 1995 to 2012, the Wind spacecraft recorded 168 magnetic cloud (MC) events. Among those events, 79 were found to have upstream shock waves and their source locations on the Sun were identified. Using a recipe of interplanetary magnetic field (IMF) Bz initial turning direction after shock (Wu et al., 1996, GRL), it is found that the north-south polarity of 66 (83.5%) out of the 79 events were accurately predicted. These events were tested and further analyzed, reaffirming that the Bz intial turning direction was accurate. The results also indicate that 37 of the 79 MCs originate from the north (of the Sun) averaged a Dst_min of -119 nT, whereas 42 of the MCs originating from the south (of the Sun) averaged -89 nT. In an effort to provide this research to others, a website was built that incorporated various tools and pictures to predict the intensity of the geomagnetic storms. The tool is capable of predicting geomagnetic storms with different ranges of Dst_min (from no-storm to gigantic storms). This work was supported by Naval Research Lab HBCU/MI Internship program and Chief of Naval Research.

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

Development of Computational Aeroacoustics Code for Jet Noise and Flow Prediction

NASA Astrophysics Data System (ADS)

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

2002-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

Lebon, Luc; Sebilleau, Julien; Limat, Laurent

2016-11-01

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

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks

PubMed Central

Puente Fernández, Jesús Antonio

2018-01-01

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches. PMID:29614049

Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.

PubMed

Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon

2018-04-03

Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

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

NASA Astrophysics Data System (ADS)

Sarkar, A.; Chakravartty, J. K.

2013-10-01

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

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

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

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

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

Tectonic predictions with mantle convection models

NASA Astrophysics Data System (ADS)

Coltice, Nicolas; Shephard, Grace E.

2018-04-01

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

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

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

MODFLOW 2.0: A program for predicting moderator flow patterns

NASA Astrophysics Data System (ADS)

Peterson, P. F.; 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 the operation of 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.

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

USGS Publications Warehouse

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

2012-01-01

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

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

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

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

2014-06-15

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

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

NASA Technical Reports Server (NTRS)

Deiwert, George S.

1993-01-01

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, and the activity in the NASA Ames Research Center's Aerothermodynamics Branch is described. 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 flowfield simulation codes are discussed. These models were 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 is sparse and 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.

Simulator predicts transient flow for Malaysian subsea pipeline

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

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

1996-04-15

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

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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...

Assessment of Near-Field Sonic Boom Simulation Tools

NASA Technical Reports Server (NTRS)

Casper, J. H.; Cliff, S. E.; Thomas, S. D.; Park, M. A.; McMullen, M. S.; Melton, J. E.; Durston, D. A.

2008-01-01

A recent study for the Supersonics Project, within the National Aeronautics and Space Administration, has been conducted to assess current in-house capabilities for the prediction of near-field sonic boom. Such capabilities are required to simulate the highly nonlinear flow near an aircraft, wherein a sonic-boom signature is generated. There are many available computational fluid dynamics codes that could be used to provide the near-field flow for a sonic boom calculation. However, such codes have typically been developed for applications involving aerodynamic configuration, for which an efficiently generated computational mesh is usually not optimum for a sonic boom prediction. Preliminary guidelines are suggested to characterize a state-of-the-art sonic boom prediction methodology. The available simulation tools that are best suited to incorporate into that methodology are identified; preliminary test cases are presented in support of the selection. During this phase of process definition and tool selection, parallel research was conducted in an attempt to establish criteria that link the properties of a computational mesh to the accuracy of a sonic boom prediction. Such properties include sufficient grid density near shocks and within the zone of influence, which are achieved by adaptation and mesh refinement strategies. Prediction accuracy is validated by comparison with wind tunnel data.

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

NASA Technical Reports Server (NTRS)

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

1991-01-01

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

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.

Closure models for transitional blunt-body flows

NASA Astrophysics Data System (ADS)

Nance, Robert Paul

1998-12-01

A mean-flow modeling approach is proposed for the prediction of high-speed blunt-body wake flows undergoing transition to turbulence. This method couples the k- /zeta (Enstrophy) compressible turbulence model with a procedure for characterizing non-turbulent fluctuations upstream of transition. Two different instability mechanisms are examined in this study. In the first model, transition is brought about by streamwise disturbance modes, whereas the second mechanism considers instabilities in the free shear layer associated with the wake flow. An important feature of this combined approach is the ability to specify or predict the location of transition onset. Solutions obtained using the new approach are presented for a variety of perfect-gas hypersonic flows over blunt- cone configurations. These results are shown to provide better agreement with experimental heating data than earlier laminar predictions by other researchers. In addition, it is demonstrated that the free-shear-layer instability mechanism is superior to the streamwise mechanism in terms of comparisons with heating measurements. The favorable comparisons are a strong indication that transition to turbulence is indeed present in the flowfields considered. They also show that the present method is a useful predictive tool for transitional blunt-body wake flows.

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.

Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

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

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Morris, Philip J.

1997-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

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

EPA Science Inventory

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

Chimera Grid Tools

NASA Technical Reports Server (NTRS)

Chan, William M.; Rogers, Stuart E.; Nash, Steven M.; Buning, Pieter G.; Meakin, Robert

2005-01-01

Chimera Grid Tools (CGT) is a software package for performing computational fluid dynamics (CFD) analysis utilizing the Chimera-overset-grid method. For modeling flows with viscosity about geometrically complex bodies in relative motion, the Chimera-overset-grid method is among the most computationally cost-effective methods for obtaining accurate aerodynamic results. CGT contains a large collection of tools for generating overset grids, preparing inputs for computer programs that solve equations of flow on the grids, and post-processing of flow-solution data. The tools in CGT include grid editing tools, surface-grid-generation tools, volume-grid-generation tools, utility scripts, configuration scripts, and tools for post-processing (including generation of animated images of flows and calculating forces and moments exerted on affected bodies). One of the tools, denoted OVERGRID, is a graphical user interface (GUI) that serves to visualize the grids and flow solutions and provides central access to many other tools. The GUI facilitates the generation of grids for a new flow-field configuration. Scripts that follow the grid generation process can then be constructed to mostly automate grid generation for similar configurations. CGT is designed for use in conjunction with a computer-aided-design program that provides the geometry description of the bodies, and a flow-solver program.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

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

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

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

USGS Publications Warehouse

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

2008-01-01

than the low-flow regression equations (such as the 95th percent exceedance and 7Q10 low-flow statistic). The regression equations predict unregulated flow conditions in Oregon. Flow estimates need to be adjusted if they are used at ungaged sites that are regulated by reservoirs or affected by water-supply and agricultural withdrawals if actual flow conditions are of interest. The regression equations are installed in the USGS StreamStats Web-based tool (http://water.usgs.gov/osw/streamstats/index.html, accessed July 16, 2008). StreamStats provides users with a set of annual and monthly flow-duration and low-flow frequency estimates for ungaged sites in Oregon in addition to the basin characteristics for the sites. Prediction intervals at the 90-percent confidence level also are automatically computed.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

PubMed

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

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

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

Zeng, X.; Pielke, R.A.

1993-09-01

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

Prediction of rarefied micro-nozzle flows using the SPARTA library

NASA Astrophysics Data System (ADS)

Deschenes, Timothy R.; Grot, Jonathan

2016-11-01

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

Predicting the impact of chromium on flow-accelerated corrosion

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

Chexal, B.; Goyette, L.F.; Horowitz, J.S.

1996-12-01

Flow-Accelerated Corrosion (FAC) continues to cause problems in nuclear and fossil power plants. Many experiments have been performed to understand the mechanism of FAC. For approximately twenty years, it has ben widely recognized that the presence of small amounts of chromium will reduce the rate of FAC. This effect was quantified in the eighties by research performed in France, Germany and the Netherlands. The results of this research has been incorporated into the computer-based tools used by utility engineers to deal with this issue. For some time, plant data from Diablo Canyon has suggested that the existing correlations relating themore » concentration of chromium to the rate of FAC are conservative. Laboratory examinations have supported this observation. It appears that the existing correlations fail to capture a change in mechanism from a FAC process with linear kinetics to a general corrosion process with parabolic kinetics. This change in mechanism occurs at a chromium level of approximately 0.1%, within the allowable alloy range of typical carbon steel (ASTM/ASME A106 Grade B) used in power piping in most domestic plants. It has been difficult to obtain plant data that has sufficient chromium to develop a new correlation. Data from Diablo Canyon and the Dukovany Power Plant in the Czech Republic will be used to develop a new chromium correlation for predicting FAC rate.« less

Cardiovascular risk prediction tools for populations in Asia.

PubMed

Barzi, F; Patel, A; Gu, D; Sritara, P; Lam, T H; Rodgers, A; Woodward, M

2007-02-01

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. 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. 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. Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US. 172,077 participants from the Asian cohorts; 25,682 participants from Chinese cohorts and 6053 participants from the Framingham Study. 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. A low-information Framingham cardiovascular risk prediction tool, which, when recalibrated with contemporary data, is likely to estimate future cardiovascular risk with similar accuracy in Asian

Current Trends in Modeling Research for Turbulent Aerodynamic Flows

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

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.

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

NASA Technical Reports Server (NTRS)

Nallasamy, M.

1987-01-01

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

PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures

PubMed Central

Lipinski, Leszek; Dziembowski, Andrzej

2018-01-01

Abstract Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets. Analysis of two samples from heavy metal-contaminated microbial mats revealed that plasmids may constitute an important fraction of their metagenomes and carry genes involved in heavy-metal homeostasis, proving the pivotal role of plasmids in microorganism adaptation to environmental conditions. PMID:29346586

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

PubMed

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

2014-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

PREDICT: a diagnostic accuracy study of a tool for predicting mortality within one year: who should have an advance healthcare directive?

PubMed

Richardson, Philip; Greenslade, Jaimi; Shanmugathasan, Sulochana; Doucet, Katherine; Widdicombe, Neil; Chu, Kevin; Brown, Anthony

2015-01-01

CARING is a screening tool developed to identify patients who have a high likelihood of death in 1 year. This study sought to validate a modified CARING tool (termed PREDICT) using a population of patients presenting to the Emergency Department. In total, 1000 patients aged over 55 years who were admitted to hospital via the Emergency Department between January and June 2009 were eligible for inclusion in this study. Data on the six prognostic indicators comprising PREDICT were obtained retrospectively from patient records. One-year mortality data were obtained from the State Death Registry. Weights were applied to each PREDICT criterion, and its final score ranged from 0 to 44. Receiver operator characteristic analyses and diagnostic accuracy statistics were used to assess the accuracy of PREDICT in identifying 1-year mortality. The sample comprised 976 patients with a median (interquartile range) age of 71 years (62-81 years) and a 1-year mortality of 23.4%. In total, 50% had ≥1 PREDICT criteria with a 1-year mortality of 40.4%. Receiver operator characteristic analysis gave an area under the curve of 0.86 (95% confidence interval: 0.83-0.89). Using a cut-off of 13 points, PREDICT had a 95.3% (95% confidence interval: 93.6-96.6) specificity and 53.9% (95% confidence interval: 47.5-60.3) sensitivity for predicting 1-year mortality. PREDICT was simpler than the CARING criteria and identified 158 patients per 1000 admitted who could benefit from advance care planning. PREDICT was successfully applied to the Australian healthcare system with findings similar to the original CARING study conducted in the United States. This tool could improve end-of-life care by identifying who should have advance care planning or an advance healthcare directive. © The Author(s) 2014.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Biodiversity in environmental assessment-current practice and tools for prediction

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

Gontier, Mikael; Balfors, Berit; Moertberg, Ulla

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 gapmore » between research in GIS-based ecological modelling and current practice in biodiversity assessment within environmental assessment.« less

Inter-kingdom prediction certainty evaluation of protein subcellular localization tools: microbial pathogenesis approach for deciphering host microbe interaction.

PubMed

Khan, Abdul Arif; Khan, Zakir; Kalam, Mohd Abul; Khan, Azmat Ali

2018-01-01

Microbial pathogenesis involves several aspects of host-pathogen interactions, including microbial proteins targeting host subcellular compartments and subsequent effects on host physiology. Such studies are supported by experimental data, but recent detection of bacterial proteins localization through computational eukaryotic subcellular protein targeting prediction tools has also come into practice. We evaluated inter-kingdom prediction certainty of these tools. The bacterial proteins experimentally known to target host subcellular compartments were predicted with eukaryotic subcellular targeting prediction tools, and prediction certainty was assessed. The results indicate that these tools alone are not sufficient for inter-kingdom protein targeting prediction. The correct prediction of pathogen's protein subcellular targeting depends on several factors, including presence of localization signal, transmembrane domain and molecular weight, etc., in addition to approach for subcellular targeting prediction. The detection of protein targeting in endomembrane system is comparatively difficult, as the proteins in this location are channelized to different compartments. In addition, the high specificity of training data set also creates low inter-kingdom prediction accuracy. Current data can help to suggest strategy for correct prediction of bacterial protein's subcellular localization in host cell. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Predicting Turbulent Convective Heat Transfer in Three-Dimensional Duct Flows

NASA Technical Reports Server (NTRS)

Rokni, M.; Gatski, T. B.

1999-01-01

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

Monthly to seasonal low flow prediction: statistical versus dynamical models

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

Variant effect prediction tools assessed using independent, functional assay-based datasets: implications for discovery and diagnostics.

PubMed

Mahmood, Khalid; Jung, Chol-Hee; Philip, Gayle; Georgeson, Peter; Chung, Jessica; Pope, Bernard J; Park, Daniel J

2017-05-16

Genetic variant effect prediction algorithms are used extensively in clinical genomics and research to determine the likely consequences of amino acid substitutions on protein function. It is vital that we better understand their accuracies and limitations because published performance metrics are confounded by serious problems of circularity and error propagation. Here, we derive three independent, functionally determined human mutation datasets, UniFun, BRCA1-DMS and TP53-TA, and employ them, alongside previously described datasets, to assess the pre-eminent variant effect prediction tools. Apparent accuracies of variant effect prediction tools were influenced significantly by the benchmarking dataset. Benchmarking with the assay-determined datasets UniFun and BRCA1-DMS yielded areas under the receiver operating characteristic curves in the modest ranges of 0.52 to 0.63 and 0.54 to 0.75, respectively, considerably lower than observed for other, potentially more conflicted datasets. These results raise concerns about how such algorithms should be employed, particularly in a clinical setting. Contemporary variant effect prediction tools are unlikely to be as accurate at the general prediction of functional impacts on proteins as reported prior. Use of functional assay-based datasets that avoid prior dependencies promises to be valuable for the ongoing development and accurate benchmarking of such tools.

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

PubMed

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

2012-06-01

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

IMHOTEP—a composite score integrating popular tools for predicting the functional consequences of non-synonymous sequence variants

PubMed Central

Knecht, Carolin; Mort, Matthew; Junge, Olaf; Cooper, David N.; Krawczak, Michael

2017-01-01

Abstract The in silico prediction of the functional consequences of mutations is an important goal of human pathogenetics. However, bioinformatic tools that classify mutations according to their functionality employ different algorithms so that predictions may vary markedly between tools. We therefore integrated nine popular prediction tools (PolyPhen-2, SNPs&GO, MutPred, SIFT, MutationTaster2, Mutation Assessor and FATHMM as well as conservation-based Grantham Score and PhyloP) into a single predictor. The optimal combination of these tools was selected by means of a wide range of statistical modeling techniques, drawing upon 10 029 disease-causing single nucleotide variants (SNVs) from Human Gene Mutation Database and 10 002 putatively ‘benign’ non-synonymous SNVs from UCSC. Predictive performance was found to be markedly improved by model-based integration, whilst maximum predictive capability was obtained with either random forest, decision tree or logistic regression analysis. A combination of PolyPhen-2, SNPs&GO, MutPred, MutationTaster2 and FATHMM was found to perform as well as all tools combined. Comparison of our approach with other integrative approaches such as Condel, CoVEC, CAROL, CADD, MetaSVM and MetaLR using an independent validation dataset, revealed the superiority of our newly proposed integrative approach. An online implementation of this approach, IMHOTEP (‘Integrating Molecular Heuristics and Other Tools for Effect Prediction’), is provided at http://www.uni-kiel.de/medinfo/cgi-bin/predictor/. PMID:28180317

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.

A Design Tool for Liquid Rocket Engine Injectors

NASA Technical Reports Server (NTRS)

Farmer, Richard C.; Cheng, Gary; Trinh, Huu Phuoc; Tucker, P. Kevin; Hutt, John

1999-01-01

A practical design tool for the analysis of flowfields near the injector face has been developed and used to analyze the Fastrac engine. The objective was to produce a computational design tool which was detailed enough to predict the interactive effects of injector element impingement angles and points and the momenta of the individual orifice flows. To obtain a model which could be used to simulate a significant number of individual orifices, a homogeneous computational fluid dynamics model was developed. To describe liquid and vapor sub- and super-critical flows, the model included thermal and caloric equations of state which were valid over a wide range of pressures and temperatures. A homogeneous model was constructed such that the local state of the flow was determined directly, i.e. the quality of the flow was calculated. Such a model does not identify drops or their distribution, but it does allow the flow along the injector face and into the acoustic cavity to be predicted. It also allows the film coolant flow to be accurately described. The initial evaluation of the injector code was made by simulating cold flow from an unlike injector element and from a like-on-like overlapping fan (LOL) injector element. The predicted mass flux distributions of these injector elements compared well to cold flow test results. These are the same cold flow tests which serve as the data base for the JANNAF performance prediction codes. The flux distributions 1 inch downstream of the injector face are very similar; the differences were somewhat larger at further distances from the faceplate. Since the cold flow testing did not achieve good mass balances when integrations across the entire fan were made, the CFD simulation appears to be reasonable alternative to future cold flow testing. To simulate the Fastrac, an RP-1/LOX combustion model must be chosen. This submodel must be relatively simple to accomplish three-dimensional, multiphase flow simulations. Single RP-1

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

Schroeder, Christopher L; Hartmann, Mitra J Z

2012-01-01

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

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

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

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

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 variablemore » 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.« less

Validation and Use of a Predictive Modeling Tool: Employing Scientific Findings to Improve Responsible Conduct of Research Education.

PubMed

Mulhearn, Tyler J; Watts, Logan L; Todd, E Michelle; Medeiros, Kelsey E; Connelly, Shane; Mumford, Michael D

2017-01-01

Although recent evidence suggests ethics education can be effective, the nature of specific training programs, and their effectiveness, varies considerably. Building on a recent path modeling effort, the present study developed and validated a predictive modeling tool for responsible conduct of research education. The predictive modeling tool allows users to enter ratings in relation to a given ethics training program and receive instantaneous evaluative information for course refinement. Validation work suggests the tool's predicted outcomes correlate strongly (r = 0.46) with objective course outcomes. Implications for training program development and refinement are discussed.

Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows.

PubMed

Pacheco, D; Patton, R A; Parys, C; Lapierre, H

2012-02-01

The objective of this analysis was to compare the rumen submodel predictions of 4 commonly used dairy ration programs to observed values of duodenal flows of crude protein (CP), protein fractions, and essential AA (EAA). The literature was searched and 40 studies, including 154 diets, were used to compare observed values with those predicted by AminoCow (AC), Agricultural Modeling and Training Systems (AMTS), Cornell-Penn-Miner (CPM), and National Research Council 2001 (NRC) models. The models were evaluated based on their ability to predict the mean, their root mean square prediction error (RMSPE), error bias, and adequacy of regression equations for each protein fraction. The models predicted the mean duodenal CP flow within 5%, with more than 90% of the variation due to random disturbance. The models also predicted within 5% the mean microbial CP flow except CPM, which overestimated it by 27%. Only NRC, however, predicted mean rumen-undegraded protein (RUP) flows within 5%, whereas AC and AMTS underpredicted it by 8 to 9% and CPM by 24%. Regarding duodenal flows of individual AA, across all diets, CPM predicted substantially greater (>10%) mean flows of Arg, His, Ile, Met, and Lys; AMTS predicted greater flow for Arg and Met, whereas AC and NRC estimations were, on average, within 10% of observed values. Overpredictions by the CPM model were mainly related to mean bias, whereas the NRC model had the highest proportion of bias in random disturbance for flows of EAA. Models tended to predict mean flows of EAA more accurately on corn silage and alfalfa diets than on grass-based diets, more accurately on corn grain-based diets than on non-corn-based diets, and finally more accurately in the mid range of diet types. The 4 models were accurate at predicting mean dry matter intake. The AC, AMTS, and NRC models were all sufficiently accurate to be used for balancing EAA in dairy rations under field conditions. Copyright © 2012 American Dairy Science Association

Chemical reacting flows

NASA Technical Reports Server (NTRS)

Mularz, Edward J.; Sockol, Peter M.

1987-01-01

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

Chemical reacting flows

NASA Technical Reports Server (NTRS)

Mularz, Edward J.; Sockol, Peter M.

1990-01-01

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

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.

Jet-Surface Interaction Test: Flow Measurements Results

NASA Technical Reports Server (NTRS)

Brown, Cliff; Wernet, Mark

2014-01-01

Modern aircraft design often puts the engine exhaust in close proximity to the airframe surfaces. Aircraft noise prediction tools must continue to develop in order to meet the challenges these aircraft present. The Jet-Surface Interaction Tests have been conducted to provide a comprehensive quality set of experimental data suitable for development and validation of these exhaust noise prediction methods. Flow measurements have been acquired using streamwise and cross-stream particle image velocimetry (PIV) and fluctuating surface pressure data acquired using flush mounted pressure transducers near the surface trailing edge. These data combined with previously reported far-field and phased array noise measurements represent the first step toward the experimental data base. These flow data are particularly applicable to development of noise prediction methods which rely on computational fluid dynamics to uncover the flow physics. A representative sample of the large flow data set acquired is presented here to show how a surface near a jet affects the turbulent kinetic energy in the plume, the spatial relationship between the jet plume and surface needed to generate surface trailing-edge noise, and differences between heated and unheated jet flows with respect to surfaces.

Experimental resource pulses influence social-network dynamics and the potential for information flow in tool-using crows

PubMed Central

St Clair, James J. H.; Burns, Zackory T.; Bettaney, Elaine M.; Morrissey, Michael B.; Otis, Brian; Ryder, Thomas B.; Fleischer, Robert C.; James, Richard; Rutz, Christian

2015-01-01

Social-network dynamics have profound consequences for biological processes such as information flow, but are notoriously difficult to measure in the wild. We used novel transceiver technology to chart association patterns across 19 days in a wild population of the New Caledonian crow—a tool-using species that may socially learn, and culturally accumulate, tool-related information. To examine the causes and consequences of changing network topology, we manipulated the environmental availability of the crows' preferred tool-extracted prey, and simulated, in silico, the diffusion of information across field-recorded time-ordered networks. Here we show that network structure responds quickly to environmental change and that novel information can potentially spread rapidly within multi-family communities, especially when tool-use opportunities are plentiful. At the same time, we report surprisingly limited social contact between neighbouring crow communities. Such scale dependence in information-flow dynamics is likely to influence the evolution and maintenance of material cultures. PMID:26529116

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.

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.

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

Which screening tools can predict injury to the lower extremities in team sports?: a systematic review.

PubMed

Dallinga, Joan M; Benjaminse, Anne; Lemmink, Koen A P M

2012-09-01

Injuries to lower extremities are common in team sports such as soccer, basketball, volleyball, football and field hockey. Considering personal grief, disabling consequences and high costs caused by injuries to lower extremities, the importance for the prevention of these injuries is evident. From this point of view it is important to know which screening tools can identify athletes who are at risk of injury to their lower extremities. The aim of this article is to determine the predictive values of anthropometric and/or physical screening tests for injuries to the leg, anterior cruciate ligament (ACL), knee, hamstring, groin and ankle in team sports. A systematic review was conducted in MEDLINE (1966 to September 2011), EMBASE (1989 to September 2011) and CINAHL (1982 to September 2011). Based on inclusion criteria defined a priori, titles, abstracts and full texts were analysed to find relevant studies. The analysis showed that different screening tools can be predictive for injuries to the knee, ACL, hamstring, groin and ankle. For injuries in general there is some support in the literature to suggest that general joint laxity is a predictive measure for leg injuries. The anterior right/left reach distance >4 cm and the composite reach distance <4.0% of limb length in girls measured with the star excursion balance test (SEBT) may predict leg injuries. Furthermore, an increasing age, a lower hamstring/quadriceps (H : Q) ratio and a decreased range of motion (ROM) of hip abduction may predict the occurrence of leg injuries. Hyperextension of the knee, side-to-side differences in anterior-posterior knee laxity and differences in knee abduction moment between both legs are suggested to be predictive tests for sustaining an ACL injury and height was a predictive screening tool for knee ligament injuries. There is some evidence that when age increases, the probability of sustaining a hamstring injury increases. Debate exists in the analysed literature regarding

Fracture prediction and calibration of a Canadian FRAX® tool: a population-based report from CaMos

PubMed Central

Fraser, L.-A.; Langsetmo, L.; Berger, C.; Ioannidis, G.; Goltzman, D.; Adachi, J. D.; Papaioannou, A.; Josse, R.; Kovacs, C. S.; Olszynski, W. P.; Towheed, T.; Hanley, D. A.; Kaiser, S. M.; Prior, J.; Jamal, S.; Kreiger, N.; Brown, J. P.; Johansson, H.; Oden, A.; McCloskey, E.; Kanis, J. A.

2016-01-01

Summary A new Canadian WHO fracture risk assessment (FRAX®) tool to predict 10-year fracture probability was compared with observed 10-year fracture outcomes in a large Canadian population-based study (CaMos). The Canadian FRAX tool showed good calibration and discrimination for both hip and major osteoporotic fractures. Introduction The purpose of this study was to validate a new Canadian WHO fracture risk assessment (FRAX®) tool in a prospective, population-based cohort, the Canadian Multi-centre Osteoporosis Study (CaMos). Methods A FRAX tool calibrated to the Canadian population was developed by the WHO Collaborating Centre for Metabolic Bone Diseases using national hip fracture and mortality data. Ten-year FRAX probabilities with and without bone mineral density (BMD) were derived for CaMos women (N=4,778) and men (N=1,919) and compared with observed fracture outcomes to 10 years (Kaplan–Meier method). Cox proportional hazard models were used to investigate the contribution of individual FRAX variables. Results Mean overall 10-year FRAX probability with BMD for major osteoporotic fractures was not significantly different from the observed value in men [predicted 5.4% vs. observed 6.4% (95%CI 5.2–7.5%)] and only slightly lower in women [predicted 10.8% vs. observed 12.0% (95%CI 11.0–12.9%)]. FRAX was well calibrated for hip fracture assessment in women [predicted 2.7% vs. observed 2.7% (95%CI 2.2–3.2%)] but underestimated risk in men [predicted 1.3% vs. observed 2.4% (95%CI 1.7–3.1%)]. FRAX with BMD showed better fracture discrimination than FRAX without BMD or BMD alone. Age, body mass index, prior fragility fracture and femoral neck BMD were significant independent predictors of major osteoporotic fractures; sex, age, prior fragility fracture and femoral neck BMD were significant independent predictors of hip fractures. Conclusion The Canadian FRAX tool provides predictions consistent with observed fracture rates in Canadian women and men, thereby

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.

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/.

A new powerful parameterization tool for managing groundwater resources and predicting land subsidence in Las Vegas Valley

NASA Astrophysics Data System (ADS)

Zhang, M.; Nunes, V. D.; Burbey, T. J.; Borggaard, J.

2012-12-01

More than 1.5 m of subsidence has been observed in Las Vegas Valley since 1935 as a result of groundwater pumping that commenced in 1905 (Bell, 2002). The compaction of the aquifer system has led to several large subsidence bowls and deleterious earth fissures. The highly heterogeneous aquifer system with its variably thick interbeds makes predicting the magnitude and location of subsidence extremely difficult. Several numerical groundwater flow models of the Las Vegas basin have been previously developed; however none of them have been able to accurately simulate the observed subsidence patterns or magnitudes because of inadequate parameterization. To better manage groundwater resources and predict future subsidence we have updated and developed a more accurate groundwater management model for Las Vegas Valley by developing a new adjoint parameter estimation package (APE) that is used in conjunction with UCODE along with MODFLOW and the SUB (subsidence) and HFB (horizontal flow barrier) packages. The APE package is used with UCODE to automatically identify suitable parameter zonations and inversely calculate parameter values from hydraulic head and subsidence measurements, which are highly sensitive to both elastic (Ske) and inelastic (Skv) storage coefficients. With the advent of InSAR (Interferometric synthetic aperture radar), distributed spatial and temporal subsidence measurements can be obtained, which greatly enhance the accuracy of parameter estimation. This automation process can remove user bias and provide a far more accurate and robust parameter zonation distribution. The outcome of this work yields a more accurate and powerful tool for managing groundwater resources in Las Vegas Valley to date.

Evaluation of particle-based flow characteristics using novel Eulerian indices

NASA Astrophysics Data System (ADS)

Cho, Youngmoon; Kang, Seongwon

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

A human-hearing-related prediction tool for soundscapes and community noise

NASA Astrophysics Data System (ADS)

Genuit, Klaus

2002-11-01

There are several methods of calculation available for the prediction of the A-weighted sound-pressure level of environmental noise, which are, however, not suitable for a qualified prediction of the residents' annoyance and physiological strain. The subjectively felt noise quality does not only depend on the A-weighted sound-pressure level, but also on other psychoacoustical parameters, such as loudness, roughness, sharpness, etc. In addition to these physical and psychoacoustical aspects of noise, the so-called psychological or cognitive aspects have to be considered, too, which means that the listeners' expectations, their mental attitude, as well as the information content of the noise finally influence the noise quality perceived by the individual persons. Within the scope of a research project SVEN (Sound Quality of Vehicle Exterior Noise), which is promoted by the EC, a new tool has been developed which allows a binaural simulation and prediction of the environmental noise to evaluate the influence of different contributions by the sound events with respect to the psychoacoustical parameters, the spatial distribution, movement, and frequency. By means of this tool it is now possible to consider completely new aspects regarding the audible perception of noise when establishing a soundscape or when planning community noise.

Using social media as a tool to predict syphilis.

PubMed

Young, Sean D; Mercer, Neil; Weiss, Robert E; Torrone, Elizabeth A; Aral, Sevgi O

2018-04-01

Syphilis rates have been rapidly rising in the United States. New technologies, such as social media, might be used to anticipate and prevent the spread of disease. Because social media data collection is easy and inexpensive, integration of social media data into syphilis surveillance may be a cost-effective surveillance strategy, especially in low-resource regions. People are increasingly using social media to discuss health-related issues, such as sexual risk behaviors, allowing social media to be a potential tool for public health and medical research. This study mined Twitter data to assess whether social media could be used to predict syphilis cases in 2013 based on 2012 data. We collected 2012 and 2013 county-level primary and secondary (P&S) and early latent syphilis cases reported to the Center for Disease Control and Prevention, along with >8500 geolocated tweets in the United States that were filtered to include sexual risk-related keywords, including colloquial terms for intercourse. We assessed the relationship between syphilis-related tweets and actual case reports by county, controlling for socioeconomic indicators and prior year syphilis cases. We found a significant positive relationship between tweets and cases of P&S and early latent syphilis. This study shows that social media may be an additional tool to enhance syphilis prediction and surveillance. Copyright © 2017 Elsevier Inc. All rights reserved.

Flow Test to Predict Early Hypotony and Hypertensive Phase After Ahmed Glaucoma Valve (AGV) Surgical Implantation.

PubMed

Cheng, Jason; Beltran-Agullo, Laura; Buys, Yvonne M; Moss, Edward B; Gonzalez, Johanna; Trope, Graham E

2016-06-01

To assess the validity of a preimplantation flow test to predict early hypotony [intraocular pressure (IOP)≤5 mm Hg on 2 consecutive visits and hypertensive phase (HP) (IOP>21 mm Hg) after Ahmed Glaucoma Valve (AGV) implantation. Prospective interventional study on patients receiving an AGV. A preimplantation flow test using a gravity-driven reservoir and an open manometer was performed on all AGVs. Opening pressure (OP) and closing pressure (CP) were defined as the pressure at which fluid was seen to flow or stop flowing through the AGV, respectively. OP and CP were measured twice per AGV. Patients were followed for 12 weeks. In total, 20 eyes from 19 patients were enrolled. At 12 weeks the mean IOP decreased from 29.2±9.1 to 16.8±5.2 mm Hg (P<0.01). The mean AGV OP was 17.5±5.4 mm Hg and the mean CP was 6.7±2.3 mm Hg. Early (within 2 wk postoperative) HP occurred in 37% and hypotony in 16% of cases. An 18 mm Hg cutoff for the OP gave a sensitivity of 0.71, specificity of 0.83, positive predictive value of 0.71, and negative predictive value of 0.83 for predicting an early HP. A 7 mm Hg cutoff for the CP yielded a sensitivity of 1.0, specificity of 0.38, positive predictive value of 0.23, and negative predictive value of 1.0 for predicting hypotony. Preoperative OP and CP may predict early hypotony or HP and may be used as a guide as to which AGV valves to discard before implantation surgery.

Getting into the musical zone: trait emotional intelligence and amount of practice predict flow in pianists

PubMed Central

Marin, Manuela M.; Bhattacharya, Joydeep

2013-01-01

Being “in flow” or “in the zone” is defined as an extremely focused state of consciousness which occurs during intense engagement in an activity. In general, flow has been linked to peak performances (high achievement) and feelings of intense pleasure and happiness. However, empirical research on flow in music performance is scarce, although it may offer novel insights into the question of why musicians engage in musical activities for extensive periods of time. Here, we focused on individual differences in a group of 76 piano performance students and assessed their flow experience in piano performance as well as their trait emotional intelligence. Multiple regression analysis revealed that flow was predicted by the amount of daily practice and trait emotional intelligence. Other background variables (gender, age, duration of piano training and age of first piano training) were not predictive. To predict high achievement in piano performance (i.e., winning a prize in a piano competition), a seven-predictor logistic regression model was fitted to the data, and we found that the odds of winning a prize in a piano competition were predicted by the amount of daily practice and the age at which piano training began. Interestingly, a positive relationship between flow and high achievement was not supported. Further, we explored the role of musical emotions and musical styles in the induction of flow by a self-developed questionnaire. Results suggest that besides individual differences among pianists, specific structural and compositional features of musical pieces and related emotional expressions may facilitate flow experiences. Altogether, these findings highlight the role of emotion in the experience of flow during music performance and call for further experiments addressing emotion in relation to the performer and the music alike. PMID:24319434

Non-Darcian flow of shear-thinning fluids through packed beads: Experiments and predictions using Forchheimer's law and Ergun's equation

NASA Astrophysics Data System (ADS)

Rodríguez de Castro, Antonio; Radilla, Giovanni

2017-02-01

The flow of shear-thinning fluids through unconsolidated porous media is present in a number of important industrial applications such as soil depollution, Enhanced Oil Recovery or filtration of polymeric liquids. Therefore, predicting the pressure drop-flow rate relationship in model porous media has been the scope of major research efforts during the last decades. Although the flow of Newtonian fluids through packs of spherical particles is well understood in most cases, much less is known regarding the flow of shear-thinning fluids as high molecular weight polymer aqueous solutions. In particular, the experimental data for the non-Darcian flow of shear-thinning fluids are scarce and so are the current approaches for their prediction. Given the relevance of non-Darcian shear-thinning flow, the scope of this work is to perform an experimental study to systematically evaluate the effects of fluid shear rheology on the flow rate-pressure drop relationships for the non-Darcian flow through different packs of glass spheres. To do so, xanthan gum aqueous solutions with different polymer concentrations are injected through four packs of glass spheres with uniform size under Darcian and inertial flow regimes. A total of 1560 experimental data are then compared with predictions coming from different methods based on the extension of widely used Ergun's equation and Forchheimer's law to the case of shear thinning fluids, determining the accuracy of these predictions. The use of a proper definition for Reynolds number and a realistic model to represent the rheology of the injected fluids results in the porous media are shown to be key aspects to successfully predict pressure drop-flow rate relationships for the inertial shear-thinning flow in packed beads.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

The Landlab v1.0 OverlandFlow component: a Python tool for computing shallow-water flow across watersheds

NASA Astrophysics Data System (ADS)

Adams, Jordan M.; Gasparini, Nicole M.; Hobley, Daniel E. J.; Tucker, Gregory E.; Hutton, Eric W. H.; Nudurupati, Sai S.; Istanbulluoglu, Erkan

2017-04-01

Representation of flowing water in landscape evolution models (LEMs) is often simplified compared to hydrodynamic models, as LEMs make assumptions reducing physical complexity in favor of computational efficiency. The Landlab modeling framework can be used to bridge the divide between complex runoff models and more traditional LEMs, creating a new type of framework not commonly used in the geomorphology or hydrology communities. Landlab is a Python-language library that includes tools and process components that can be used to create models of Earth-surface dynamics over a range of temporal and spatial scales. The Landlab OverlandFlow component is based on a simplified inertial approximation of the shallow water equations, following the solution of de Almeida et al.(2012). This explicit two-dimensional hydrodynamic algorithm simulates a flood wave across a model domain, where water discharge and flow depth are calculated at all locations within a structured (raster) grid. Here, we illustrate how the OverlandFlow component contained within Landlab can be applied as a simplified event-based runoff model and how to couple the runoff model with an incision model operating on decadal timescales. Examples of flow routing on both real and synthetic landscapes are shown. Hydrographs from a single storm at multiple locations in the Spring Creek watershed, Colorado, USA, are illustrated, along with a map of shear stress applied on the land surface by flowing water. The OverlandFlow component can also be coupled with the Landlab DetachmentLtdErosion component to illustrate how the non-steady flow routing regime impacts incision across a watershed. The hydrograph and incision results are compared to simulations driven by steady-state runoff. Results from the coupled runoff and incision model indicate that runoff dynamics can impact landscape relief and channel concavity, suggesting that, on landscape evolution timescales, the OverlandFlow model may lead to differences in

Stability theory applications to laminar-flow control

NASA Technical Reports Server (NTRS)

Malik, Mujeeb R.

1987-01-01

In order to design Laminar Flow Control (LFC) configurations, reliable methods are needed for boundary-layer transition predictions. Among the available methods, there are correlations based upon R sub e, shape factors, Goertler number and crossflow Reynolds number. The most advanced transition prediction method is based upon linear stability theory in the form of the e sup N method which has proven to be successful in predicting transition in two- and three-dimensional boundary layers. When transition occurs in a low disturbance environment, the e sup N method provides a viable design tool for transition prediction and LFC in both 2-D and 3-D subsonic/supersonic flows. This is true for transition dominated by either TS, crossflow, or Goertler instability. If Goertler/TS or crossflow/TS interaction is present, the e sup N will fail to predict transition. However, there is no evidence of such interaction at low amplitudes of Goertler and crossflow vortices.

High resolution flow field prediction for tail rotor aeroacoustics

NASA Technical Reports Server (NTRS)

Quackenbush, Todd R.; Bliss, Donald B.

1989-01-01

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

Burridge-Knopoff Model as an Educational and Demonstrational Tool in Seismicity Prediction

NASA Astrophysics Data System (ADS)

Kato, M.

2007-12-01

While our effort is ongoing, the fact that predicting destructive earthquakes is not a straightforward business is hard to sell to the general public. Japan is prone to two types of destructive earthquakes; interplate events along Japan Trench and Nankai Trough, and intraplate events that often occur beneath megacities. Periodicity of interplate earthquakes is usually explained by the elastic rebound theory, but we are aware that the historical seismicity along Nankai Trough is not simply periodic. Inland intraplate events have geologically postulated recurrence intervals that are far longer than human lifetime, and we do not have ample knowledge to model their behavior that includes interaction among intraplate and interplate events. To demonstrate that accumulation and release of elastic energy is complex even in a simple system, we propose to utilize the Burridge-Knopoff (BK) model as a demonstrational tool. This original one-dimensional model is easy to construct and handle so that this is also an effective educational tool for classroom use. Our simulator is a simple realization of the original one dimensional BK, which consists of small blocks, springs and a motor. Accumulation and release of strain is visibly observable, and by guessing when the next large events occur we are able to intuitively learn that observation of strain accumulation is only one element in predicting large events. Quantitative analysis of the system is also possible by measuring the movement of blocks. While the long term average of strain energy is controlled by the loading rate, observed seismicity is neither time-predictable nor slip-predictable. Time between successive events is never a constant. Distribution of released energy obeys the power law, similar to Ishimoto- Iida and Gutenberg-Richter Law. This tool is also useful in demonstration of nonlinear behavior of complex system.

The Predictability of Extratropical Transition and of its Impact on the Downstream Flow

DTIC Science & Technology

2008-03-28

is predicted to reach a continent as an extratropical storm . Arguably the larger impact on predictability, however, occurs due to the above mentioned...Office of Naval Research Project The Predictability of Extratropical Transition and of its Impact on the Downstream Flow Award Number: N00014-06-1...12 0 76128 Karlsruhe 0 March 28, 2008 1 * 4 -d 60-( CONTENTS 3 Contents 1 Objectives 5 2 Scientific Importance 6 3 Extratropical Transition in

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Development and Validation of an Empiric Tool to Predict Favorable Neurologic Outcomes Among PICU Patients.

PubMed

Gupta, Punkaj; Rettiganti, Mallikarjuna; Gossett, Jeffrey M; Daufeldt, Jennifer; Rice, Tom B; Wetzel, Randall C

2018-01-01

To create a novel tool to predict favorable neurologic outcomes during ICU stay among children with critical illness. Logistic regression models using adaptive lasso methodology were used to identify independent factors associated with favorable neurologic outcomes. A mixed effects logistic regression model was used to create the final prediction model including all predictors selected from the lasso model. Model validation was performed using a 10-fold internal cross-validation approach. Virtual Pediatric Systems (VPS, LLC, Los Angeles, CA) database. Patients less than 18 years old admitted to one of the participating ICUs in the Virtual Pediatric Systems database were included (2009-2015). None. A total of 160,570 patients from 90 hospitals qualified for inclusion. Of these, 1,675 patients (1.04%) were associated with a decline in Pediatric Cerebral Performance Category scale by at least 2 between ICU admission and ICU discharge (unfavorable neurologic outcome). The independent factors associated with unfavorable neurologic outcome included higher weight at ICU admission, higher Pediatric Index of Morality-2 score at ICU admission, cardiac arrest, stroke, seizures, head/nonhead trauma, use of conventional mechanical ventilation and high-frequency oscillatory ventilation, prolonged hospital length of ICU stay, and prolonged use of mechanical ventilation. The presence of chromosomal anomaly, cardiac surgery, and utilization of nitric oxide were associated with favorable neurologic outcome. The final online prediction tool can be accessed at https://soipredictiontool.shinyapps.io/GNOScore/. Our model predicted 139,688 patients with favorable neurologic outcomes in an internal validation sample when the observed number of patients with favorable neurologic outcomes was among 139,591 patients. The area under the receiver operating curve for the validation model was 0.90. This proposed prediction tool encompasses 20 risk factors into one probability to predict

Arc Jet Facility Test Condition Predictions Using the ADSI Code

NASA Technical Reports Server (NTRS)

Palmer, Grant; Prabhu, Dinesh; Terrazas-Salinas, Imelda

2015-01-01

The Aerothermal Design Space Interpolation (ADSI) tool is used to interpolate databases of previously computed computational fluid dynamic solutions for test articles in a NASA Ames arc jet facility. The arc jet databases are generated using an Navier-Stokes flow solver using previously determined best practices. The arc jet mass flow rates and arc currents used to discretize the database are chosen to span the operating conditions possible in the arc jet, and are based on previous arc jet experimental conditions where possible. The ADSI code is a database interpolation, manipulation, and examination tool that can be used to estimate the stagnation point pressure and heating rate for user-specified values of arc jet mass flow rate and arc current. The interpolation is performed in the other direction (predicting mass flow and current to achieve a desired stagnation point pressure and heating rate). ADSI is also used to generate 2-D response surfaces of stagnation point pressure and heating rate as a function of mass flow rate and arc current (or vice versa). Arc jet test data is used to assess the predictive capability of the ADSI code.

Predicting SKS-splitting from 35 Myr of subduction and mantle flow evolution in the western Mediterranean

NASA Astrophysics Data System (ADS)

Chertova, Maria; Spakman, Wim; Faccenda, Manuele

2017-04-01

We investigate the development of mantle anisotropy associated with the evolution of the Rif-Gibraltar-Betic (RGB) slab of the western Mediterranean and predict SKS-splitting directions for comparison with the recent observations compiled in Diaz and Gallart (2014). Our numerical model of slab evolution starts at 35 Ma and builds on our on recent work (Chertova et al., 2014) with the extension of imposing mantle flow velocities on the side boundaries of the model (Chertova et al., 2017). For the calculation of the evolution of finite strain deformation from the mantle flow field and for prediction of SKS-splitting directions we use the modified D-Rex program of Faccenda (2014). We test the predicted splitting observations against present-day shear wave splitting observations for subduction models with open boundary conditions (Chertova, 2014) and for models with various prescribed mantle flow conditions on the model side boundaries. The latter are predicted time-dependent (1 Myr time steps) velocity boundary conditions computed from back-advection of a temperature and density model of the present-day mantle scaled from a global seismic tomography model (Steinberger et al., 2015). These boundary conditions where used recently to demonstrate the relative insensitivity of RGB slab position and overall slab morphology for external mantle flow (Chertova et al., 2017). Using open boundaries only we obtain a poor to moderate fit between predicted and observed splitting directions after 35 Myr of slab and mantle flow evolution. In contrast, a good fit is obtained when imposing the computed mantle flow velocities on the western, southern, and northern boundaries during 35 Myr of model evolution. This successful model combines local slab-driven mantle flow with remotely forced mantle flow. We are in the process to repeat these calculations for shorter periods of mantle flow evolution to determine how much of past mantle flow is implicitly recorded in present-day observation

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

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.

Clinical application of the Melbourne risk prediction tool in a high-risk upper abdominal surgical population: an observational cohort study.

PubMed

Parry, S; Denehy, L; Berney, S; Browning, L

2014-03-01

(1) To determine the ability of the Melbourne risk prediction tool to predict a pulmonary complication as defined by the Melbourne Group Scale in a medically defined high-risk upper abdominal surgery population during the postoperative period; (2) to identify the incidence of postoperative pulmonary complications; and (3) to examine the risk factors for postoperative pulmonary complications in this high-risk population. Observational cohort study. Tertiary Australian referral centre. 50 individuals who underwent medically defined high-risk upper abdominal surgery. Presence of postoperative pulmonary complications was screened daily for seven days using the Melbourne Group Scale (Version 2). Postoperative pulmonary risk prediction was calculated according to the Melbourne risk prediction tool. (1) Melbourne risk prediction tool; and (2) the incidence of postoperative pulmonary complications. Sixty-six percent (33/50) underwent hepatobiliary or upper gastrointestinal surgery. Mean (SD) anaesthetic duration was 377.8 (165.5) minutes. The risk prediction tool classified 84% (42/50) as high risk. Overall postoperative pulmonary complication incidence was 42% (21/50). The tool was 91% sensitive and 21% specific with a 50% chance of correct classification. This is the first study to externally validate the Melbourne risk prediction tool in an independent medically defined high-risk population. There was a higher incidence of pulmonary complications postoperatively observed compared to that previously reported. Results demonstrated poor validity of the tool in a population already defined medically as high risk and when applied postoperatively. This observational study has identified several important points to consider in future trials. Copyright © 2013 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

3D Markov Process for Traffic Flow Prediction in Real-Time.

PubMed

Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

2016-01-25

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.

3D Markov Process for Traffic Flow Prediction in Real-Time

PubMed Central

Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

2016-01-01

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further. PMID:26821025

Using high-performance mathematical modelling tools to predict erosion and sediment fluxes in peri-urban catchments

NASA Astrophysics Data System (ADS)

Pereira, André; Conde, Daniel; Ferreira, Carla S. S.; Walsh, Rory; Ferreira, Rui M. L.

2017-04-01

Deforestation and urbanization generally lead to increased soil erosion andthrough the indirect effect of increased overland flow and peak flood discharges. Mathematical modelling tools can be helpful for predicting the spatial distribution of erosion and the morphological changes on the channel network. This is especially useful to predict the impacts of land-use changes in parts of the watershed, namely due to urbanization. However, given the size of the computational domain (normally the watershed itself), the need for high spatial resolution data to model accurately sediment transport processes and possible need to model transcritical flows, the computational cost is high and requires high-performance computing techniques. The aim of this work is to present the latest developments of the hydrodynamic and morphological model STAV2D and its applicability to predict runoff and erosion at watershed scale. STAV2D was developed at CEris - Instituto Superior Técnico, Universidade de Lisboa - as a tool particularly appropriated to model strong transient flows in complex and dynamic geometries. It is based on an explicit, first-order 2DH finite-volume discretization scheme for unstructured triangular meshes, in which a flux-splitting technique is paired with a reviewed Roe-Riemann solver, yielding a model applicable to discontinuous flows over time-evolving geometries. STAV2D features solid transport in both Euleran and Lagrangian forms, with the aim of describing the transport of fine natural sediments and then the large individual debris. The model has been validated with theoretical solutions and laboratory experiments (Canelas et al., 2013 & Conde et al., 2015). STAV-2D now supports fully distributed and heterogeneous simulations where multiple different hardware devices can be used to accelerate computation time within a unified Object-Oriented approach: the source code for CPU and GPU has the same compilation units and requires no device specific branches, like

Prediction of overall and blade-element performance for axial-flow pump configurations

NASA Technical Reports Server (NTRS)

Serovy, G. K.; Kavanagh, P.; Okiishi, T. H.; Miller, M. J.

1973-01-01

A method and a digital computer program for prediction of the distributions of fluid velocity and properties in axial flow pump configurations are described and evaluated. The method uses the blade-element flow model and an iterative numerical solution of the radial equilbrium and continuity conditions. Correlated experimental results are used to generate alternative methods for estimating blade-element turning and loss characteristics. Detailed descriptions of the computer program are included, with example input and typical computed results.

Impact of polymer film thickness and cavity size on polymer flow during embossing : towards process design rules for nanoimprint lithography.

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

Schunk, Peter Randall; King, William P.; Sun, Amy Cha-Tien

2006-08-01

This paper presents continuum simulations of polymer flow during nanoimprint lithography (NIL). The simulations capture the underlying physics of polymer flow from the nanometer to millimeter length scale and examine geometry and thermophysical process quantities affecting cavity filling. Variations in embossing tool geometry and polymer film thickness during viscous flow distinguish different flow driving mechanisms. Three parameters can predict polymer deformation mode: cavity width to polymer thickness ratio, polymer supply ratio, and Capillary number. The ratio of cavity width to initial polymer film thickness determines vertically or laterally dominant deformation. The ratio of indenter width to residual film thickness measuresmore » polymer supply beneath the indenter which determines Stokes or squeeze flow. The local geometry ratios can predict a fill time based on laminar flow between plates, Stokes flow, or squeeze flow. Characteristic NIL capillary number based on geometry-dependent fill time distinguishes between capillary or viscous driven flows. The three parameters predict filling modes observed in published studies of NIL deformation over nanometer to millimeter length scales. The work seeks to establish process design rules for NIL and to provide tools for the rational design of NIL master templates, resist polymers, and process parameters.« less

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.

Spatiotemporal floodplain mapping and prediction using HEC-RAS - GIS tools: Case of the Mejerda river, Tunisia

NASA Astrophysics Data System (ADS)

Ben Khalfallah, C.; Saidi, S.

2018-06-01

The floods have become a scourge in recent years (Floods of, 2003, 2006, 2009, 2011, and 2012), increasingly frequent and devastating. Tunisia does not escape flooding problems, the flood management requires basically a better knowledge of the phenomenon (flood), and the use of predictive methods. In order to limit this risk, we became interested in hydrodynamics modeling of Medjerda basin. To reach this aim, rainfall distribution is studied and mapped using GIS tools. In addition, flood and return period estimation of rainfall are calculated using Hyfran. Also, Simulations of recent floods are calculated and mapped using HEC-RAS and HEC-GeoRAS for the most recent flood occurred in February-March 2015 in Medjerda basin. The analysis of the results shows a good correlation between simulated parameters and those measured. There is a flood of the river exceeding 240 m3/s (DGRE, 2015) and more flowing sections are observed in the future simulations; for return periods of 10yr, 20yr and 50yr.

Vorticity, backscatter and counter-gradient transport predictions using two-level simulation of turbulent flows

NASA Astrophysics Data System (ADS)

Ranjan, R.; Menon, S.

2018-04-01

The two-level simulation (TLS) method evolves both the large-and the small-scale fields in a two-scale approach and has shown good predictive capabilities in both isotropic and wall-bounded high Reynolds number (Re) turbulent flows in the past. Sensitivity and ability of this modelling approach to predict fundamental features (such as backscatter, counter-gradient turbulent transport, small-scale vorticity, etc.) seen in high Re turbulent flows is assessed here by using two direct numerical simulation (DNS) datasets corresponding to a forced isotropic turbulence at Taylor's microscale-based Reynolds number Reλ ≈ 433 and a fully developed turbulent flow in a periodic channel at friction Reynolds number Reτ ≈ 1000. It is shown that TLS captures the dynamics of local co-/counter-gradient transport and backscatter at the requisite scales of interest. These observations are further confirmed through a posteriori investigation of the flow in a periodic channel at Reτ = 2000. The results reveal that the TLS method can capture both the large- and the small-scale flow physics in a consistent manner, and at a reduced overall cost when compared to the estimated DNS or wall-resolved LES cost.

Prediction of mean flow data for adiabatic 2-D compressible turbulent boundary layers

NASA Astrophysics Data System (ADS)

Motallebi, Fariborz

1995-02-01

This report presents a method for the prediction of mean flow data (i.e. , skin friction, velocity profile, and shape parameter) for adiabatic two-dimensional compressible turbulent boundary layers at zero pressure gradient. The transformed law of the wall, law of the wake, the van Driest model for the complete inner region, and a correlation between the Reynolds number based on the boundary layer integral length scale (Re(sub Delta*)) and the Reynolds number based on the boundary layer momentum thickness (Re(sub theta)) were used to predict the mean flow quantities. The results for skin friction coefficient show good agreement with a number of existing theories including those of van Driest and Huang et al. Comparison with a large number of experimental data suggests that at least for transonic and supersonic flows, the velocity profile as described by van Driest and Coles is Reynolds number dependent and should not be presumed universal. Extra information or perhaps a better physical approach to the formulation of the mean structure of compressible turbulent boundary layers, even in zero pressure gradient and adiabatic condition, is required in order to achieve complete (physical and mathematical) convergence when it is applied in any prediction methods.

Predicting SPE Fluxes: Coupled Simulations and Analysis Tools

NASA Astrophysics Data System (ADS)

Gorby, M.; Schwadron, N.; Linker, J.; Caplan, R. M.; Wijaya, J.; Downs, C.; Lionello, R.

2017-12-01

Presented here is a nuts-and-bolts look at the coupled framework of Predictive Science Inc's Magnetohydrodynamics Around a Sphere (MAS) code and the Energetic Particle Radiation Environment Module (EPREM). MAS simulated coronal mass ejection output from a variety of events can be selected as the MHD input to EPREM and a variety of parameters can be set to run against: bakground seed particle spectra, mean free path, perpendicular diffusion efficiency, etc.. A standard set of visualizations are produced as well as a library of analysis tools for deeper inquiries. All steps will be covered end-to-end as well as the framework's user interface and availability.

Using exposure prediction tools to link exposure and ...

EPA Pesticide Factsheets

A few different exposure prediction tools were evaluated for use in the new in vitro-based safety assessment paradigm using di-2-ethylhexyl phthalate (DEHP) and dibutyl phthalate (DnBP) as case compounds. Daily intake of each phthalate was estimated using both high-throughput (HT) prediction models such as the HT Stochastic Human Exposure and Dose Simulation model (SHEDS-HT) and the ExpoCast heuristic model and non-HT approaches based on chemical specific exposure estimations in the environment in conjunction with human exposure factors. Reverse dosimetry was performed using a published physiologically based pharmacokinetic (PBPK) model for phthalates and their metabolites to provide a comparison point. Daily intakes of DEHP and DnBP were estimated based on the urinary concentrations of their respective monoesters, mono-2-ethylhexyl phthalate (MEHP) and monobutyl phthalate (MnBP), reported in NHANES (2011–2012). The PBPK-reverse dosimetry estimated daily intakes at the 50th and 95th percentiles were 0.68 and 9.58 μg/kg/d and 0.089 and 0.68 μg/kg/d for DEHP and DnBP, respectively. For DEHP, the estimated median from PBPK-reverse dosimetry was about 3.6-fold higher than the ExpoCast estimate (0.68 and 0.18 μg/kg/d, respectively). For DnBP, the estimated median was similar to that predicted by ExpoCast (0.089 and 0.094 μg/kg/d, respectively). The SHEDS-HT prediction of DnBP intake from consumer product pathways alone was higher at 0.67 μg/kg/d. The PBPK-reve

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

NASA Astrophysics Data System (ADS)

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

2006-06-01

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

Capillary Flow in Containers of Polygonal Section: Theory and Experiment

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

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

USGS Publications Warehouse

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

2009-01-01

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

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

PubMed

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

2013-06-01

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

Predicting outcomes of restored Everglades high flow: A model system for scientifically managed floodplains

USGS Publications Warehouse

Choi, Jay; Harvey, Judson

2017-01-01

Restoration of higher flows through the Everglades is intended to reestablish sheetflow to rebuild a well-functioning ridge and slough landscape that supports a productive and diverse ecosystem. Our objective of the study was to use hydrologic simulations and biophysical analysis to predict restoration outcomes for five major subbasins of the Everglades. Five different scenarios of restoration were examined, and for each we predicted an outcome based on metrics describing the present-day condition of the landscape and additional metrics determined by modeling the hydrologic changes accompanying restoration. Restoration scenarios spanned from a baseline case with average annual flows of about 52% of the predrainage flow to the most aggressive scenario that permits 91% of the predrainage flow. Our predictions indicated that all restoration scenarios could benefit the functionality of the ridge-slough ecosystem. However, the difference between any single restoration scenario and the “no restoration” baseline was far greater than was the difference between any two levels of restoration. Interestingly, our analysis suggested that the most extensive (and highest cost) restoration scenarios are not likely to improve ridge and slough function more than less extensive restoration options. However, the value of more aggressive restoration may lie in factors not considered directly in our analysis. For example, an important reason to implement the more aggressive restoration scenarios could be additional flexibility that permitting greater flow allows for adaptively managing the ecosystem while also serving water needs for southeastern Florida in what could be a drier Everglades in the coming decades.

Prediction of the wear and evolution of cutting tools in a carbide / titanium-aluminum-vanadium machining tribosystem by volumetric tool wear characterization and modeling

NASA Astrophysics Data System (ADS)

Kuttolamadom, Mathew Abraham

The objective of this research work is to create a comprehensive microstructural wear mechanism-based predictive model of tool wear in the tungsten carbide / Ti-6Al-4V machining tribosystem, and to develop a new topology characterization method for worn cutting tools in order to validate the model predictions. This is accomplished by blending first principle wear mechanism models using a weighting scheme derived from scanning electron microscopy (SEM) imaging and energy dispersive x-ray spectroscopy (EDS) analysis of tools worn under different operational conditions. In addition, the topology of worn tools is characterized through scanning by white light interferometry (WLI), and then application of an algorithm to stitch and solidify data sets to calculate the volume of the tool worn away. The methodology was to first combine and weight dominant microstructural wear mechanism models, to be able to effectively predict the tool volume worn away. Then, by developing a new metrology method for accurately quantifying the bulk-3D wear, the model-predicted wear was validated against worn tool volumes obtained from corresponding machining experiments. On analyzing worn crater faces using SEM/EDS, adhesion was found dominant at lower surface speeds, while dissolution wear dominated with increasing speeds -- this is in conformance with the lower relative surface speed requirement for micro welds to form and rupture, essentially defining the mechanical load limit of the tool material. It also conforms to the known dominance of high temperature-controlled wear mechanisms with increasing surface speed, which is known to exponentially increase temperatures especially when machining Ti-6Al-4V due to its low thermal conductivity. Thus, straight tungsten carbide wear when machining Ti-6Al-4V is mechanically-driven at low surface speeds and thermally-driven at high surface speeds. Further, at high surface speeds, craters were formed due to carbon diffusing to the tool surface and

Tools for outcome prediction in patients with community acquired pneumonia.

PubMed

Khan, Faheem; Owens, Mark B; Restrepo, Marcos; Povoa, Pedro; Martin-Loeches, Ignacio

2017-02-01

Community-acquired pneumonia (CAP) is one of the most common causes of mortality world-wide. The mortality rate of patients with CAP is influenced by the severity of the disease, treatment failure and the requirement for hospitalization and/or intensive care unit (ICU) management, all of which may be predicted by biomarkers and clinical scoring systems. Areas covered: We review the recent literature examining the efficacy of established and newly-developed clinical scores, biological and inflammatory markers such as C-Reactive protein (CRP), procalcitonin (PCT) and Interleukin-6 (IL-6), whether used alone or in conjunction with clinical severity scores to assess the severity of CAP, predict treatment failure, guide acute in-hospital or ICU admission and predict mortality. Expert commentary: The early prediction of treatment failure using clinical scores and biomarkers plays a developing role in improving survival of patients with CAP by identifying high-risk patients requiring hospitalization or ICU admission; and may enable more efficient allocation of resources. However, it is likely that combinations of scoring systems and biomarkers will be of greater use than individual markers. Further larger studies are needed to corroborate the additive value of these markers to clinical prediction scores to provide a safer and more effective assessment tool for clinicians.

Can we predict Acute Medical readmissions using the BOOST tool? A retrospective case note review.

PubMed

Lee, Geraldine A; Freedman, Daniel; Beddoes, Penelope; Lyness, Emily; Nixon, Imogen; Srivastava, Vivek

2016-01-01

Readmissions within 30-days of hospital discharge are a problem. The aim was to determine if the Better Outcomes for Older Adults through Safe Transitions (BOOST) risk assessment tool was applicable within the UK. Patients over 65 readmitted were identified retrospectively via a casenote review. BOOST assessment was applied with 1 point for each risk factor. 324 patients were readmitted (mean age 77 years) with a median of 7 days between discharge and readmission. The median BOOST score was 3 (IQR 2-4) with polypharmacy evident in 88% and prior hospitalisation in 70%. The tool correctly predicted 90% of readmissions using two or more risk factors and 99.1% if one risk factor was included. The BOOST assessment tool appears appropriate in predicting readmissions however further analysis is required to determine its precision.

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.

Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

NASA Technical Reports Server (NTRS)

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

1986-01-01

The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

PubMed

Shang, Qiang; Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

2016-01-01

Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine

PubMed Central

Lin, Ciyun; Yang, Zhaosheng; Bing, Qichun; Zhou, Xiyang

2016-01-01

Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS). Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM) is proposed based on singular spectrum analysis (SSA) and kernel extreme learning machine (KELM). SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA). Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust. PMID:27551829

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

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.

Automated structure and flow measurement - a promising tool in nailfold capillaroscopy.

PubMed

Berks, Michael; Dinsdale, Graham; Murray, Andrea; Moore, Tonia; Manning, Joanne; Taylor, Chris; Herrick, Ariane L

2018-07-01

Despite increasing interest in nailfold capillaroscopy, objective measures of capillary structure and blood flow have been little studied. We aimed to test the hypothesis that structural measurements, capillary flow, and a combined measure have the predictive power to separate patients with systemic sclerosis (SSc) from those with primary Raynaud's phenomenon (PRP) and healthy controls (HC). 50 patients with SSc, 12 with PRP, and 50 HC were imaged using a novel capillaroscopy system that generates high-quality nailfold images and provides fully-automated measurements of capillary structure and blood flow (capillary density, mean width, maximum width, shape score, derangement and mean flow velocity). Population statistics summarise the differences between the three groups. Areas under ROC curves (A Z ) were used to measure classification accuracy when assigning individuals to SSc and HC/PRP groups. Statistically significant differences in group means were found between patients with SSc and both HC and patients with PRP, for all measurements, e.g. mean width (μm) ± SE: 15.0 ± 0.71, 12.7 ± 0.74 and 11.8 ± 0.23 for SSc, PRP and HC respectively. Combining the five structural measurements gave better classification (A Z  = 0.919 ± 0.026) than the best single measurement (mean width, A Z  = 0.874 ± 0.043), whilst adding flow further improved classification (A Z  = 0.930 ± 0.024). Structural and blood flow measurements are both able to distinguish patients with SSc from those with PRP/HC. Importantly, these hold promise as clinical trial outcome measures for treatments aimed at improving finger blood flow or microvascular remodelling. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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.

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

Tools for beach health data management, data processing, and predictive model implementation

USGS Publications Warehouse

,

2013-01-01

This fact sheet describes utilities created for management of recreational waters to provide efficient data management, data aggregation, and predictive modeling as well as a prototype geographic information system (GIS)-based tool for data visualization and summary. All of these utilities were developed to assist beach managers in making decisions to protect public health. The Environmental Data Discovery and Transformation (EnDDaT) Web service identifies, compiles, and sorts environmental data from a variety of sources that help to define climatic, hydrologic, and hydrodynamic characteristics including multiple data sources within the U.S. Geological Survey and the National Oceanic and Atmospheric Administration. The Great Lakes Beach Health Database (GLBH-DB) and Web application was designed to provide a flexible input, export, and storage platform for beach water quality and sanitary survey monitoring data to compliment beach monitoring programs within the Great Lakes. A real-time predictive modeling strategy was implemented by combining the capabilities of EnDDaT and the GLBH-DB for timely, automated prediction of beach water quality. The GIS-based tool was developed to map beaches based on their physical and biological characteristics, which was shared with multiple partners to provide concepts and information for future Web-accessible beach data outlets.

UPIOM: a new tool of MFA and its application to the flow of iron and steel associated with car production.

PubMed

Nakamura, Shinichiro; Kondo, Yasushi; Matsubae, Kazuyo; Nakajima, Kenichi; Nagasaka, Tetsuya

2011-02-01

Identification of the flow of materials and substances associated with a product system provides useful information for Life Cycle Analysis (LCA), and contributes to extending the scope of complementarity between LCA and Materials Flow Analysis/Substances Flow Analysis (MFA/SFA), the two major tools of industrial ecology. This paper proposes a new methodology based on input-output analysis for identifying the physical input-output flow of individual materials that is associated with the production of a unit of given product, the unit physical input-output by materials (UPIOM). While the Sankey diagram has been a standard tool for the visualization of MFA/SFA, with an increase in the complexity of the flows under consideration, which will be the case when economy-wide intersectoral flows of materials are involved, the Sankey diagram may become too complex for effective visualization. An alternative way to visually represent material flows is proposed which makes use of triangulation of the flow matrix based on degrees of fabrication. The proposed methodology is applied to the flow of pig iron and iron and steel scrap that are associated with the production of a passenger car in Japan. Its usefulness to identify a specific MFA pattern from the original IO table is demonstrated.

RANS Simulation of the Separated Flow over a Bump with Active Control

NASA Technical Reports Server (NTRS)

Iaccarino, Gianluca; Marongiu, Claudio; Catalano, Pietro; Amato, Marcello

2003-01-01

The objective of this paper is to investigate the accuracy of Reynolds-Averaged Navier- Stokes (RANS) techniques in predicting the effect of steady and unsteady flow control devices. This is part of a larger effort in applying numerical simulation tools to investigate of the performance of synthetic jets in high Reynolds number turbulent flows. RANS techniques have been successful in predicting isolated synthetic jets as reported by Kral et al. Nevertheless, due to the complex, and inherently unsteady nature of the interaction between the synthetic jet and the external boundary layer flow, it is not clear whether RANS models can represent the turbulence statistics correctly.

High-order computational fluid dynamics tools for aircraft design

PubMed Central

Wang, Z. J.

2014-01-01

Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419

A method of predicting flow rates required to achieve anti-icing performance with a porous leading edge ice protection system

NASA Technical Reports Server (NTRS)

Kohlman, D. L.; Albright, A. E.

1983-01-01

An analytical method was developed for predicting minimum flow rates required to provide anti-ice protection with a porous leading edge fluid ice protection system. The predicted flow rates compare with an average error of less than 10 percent to six experimentally determined flow rates from tests in the NASA Icing Research Tunnel on a general aviation wing section.

A Clinical Tool for the Prediction of Venous Thromboembolism in Pediatric Trauma Patients.

PubMed

Connelly, Christopher R; Laird, Amy; Barton, Jeffrey S; Fischer, Peter E; Krishnaswami, Sanjay; Schreiber, Martin A; Zonies, David H; Watters, Jennifer M

2016-01-01

Although rare, the incidence of venous thromboembolism (VTE) in pediatric trauma patients is increasing, and the consequences of VTE in children are significant. Studies have demonstrated increasing VTE risk in older pediatric trauma patients and improved VTE rates with institutional interventions. While national evidence-based guidelines for VTE screening and prevention are in place for adults, none exist for pediatric patients, to our knowledge. To develop a risk prediction calculator for VTE in children admitted to the hospital after traumatic injury to assist efforts in developing screening and prophylaxis guidelines for this population. Retrospective review of 536,423 pediatric patients 0 to 17 years old using the National Trauma Data Bank from January 1, 2007, to December 31, 2012. Five mixed-effects logistic regression models of varying complexity were fit on a training data set. Model validity was determined by comparison of the area under the receiver operating characteristic curve (AUROC) for the training and validation data sets from the original model fit. A clinical tool to predict the risk of VTE based on individual patient clinical characteristics was developed from the optimal model. Diagnosis of VTE during hospital admission. Venous thromboembolism was diagnosed in 1141 of 536,423 children (overall rate, 0.2%). The AUROCs in the training data set were high (range, 0.873-0.946) for each model, with minimal AUROC attenuation in the validation data set. A prediction tool was developed from a model that achieved a balance of high performance (AUROCs, 0.945 and 0.932 in the training and validation data sets, respectively; P = .048) and parsimony. Points are assigned to each variable considered (Glasgow Coma Scale score, age, sex, intensive care unit admission, intubation, transfusion of blood products, central venous catheter placement, presence of pelvic or lower extremity fractures, and major surgery), and the points total is converted to a VTE

Risk determination after an acute myocardial infarction: review of 3 clinical risk prediction tools.

PubMed

Scruth, Elizabeth Ann; Page, Karen; Cheng, Eugene; Campbell, Michelle; Worrall-Carter, Linda

2012-01-01

The objective of the study was to provide comprehensive information for the clinical nurse specialist (CNS) on commonly used clinical prediction (risk assessment) tools used to estimate risk of a secondary cardiac or noncardiac event and mortality in patients undergoing primary percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction (STEMI). The evolution and widespread adoption of primary PCI represent major advances in the treatment of acute myocardial infarction, specifically STEMI. The American College of Cardiology and the American Heart Association have recommended early risk stratification for patients presenting with acute coronary syndromes using several clinical risk scores to identify patients' mortality and secondary event risk after PCI. Clinical nurse specialists are integral to any performance improvement strategy. Their knowledge and understandings of clinical prediction tools will be essential in carrying out important assessment, identifying and managing risk in patients who have sustained a STEMI, and enhancing discharge education including counseling on medications and lifestyle changes. Over the past 2 decades, risk scores have been developed from clinical trials to facilitate risk assessment. There are several risk scores that can be used to determine in-hospital and short-term survival. This article critiques the most common tools: the Thrombolytic in Myocardial Infarction risk score, the Global Registry of Acute Coronary Events risk score, and the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications risk score. The importance of incorporating risk screening assessment tools (that are important for clinical prediction models) to guide therapeutic management of patients cannot be underestimated. The ability to forecast secondary risk after a STEMI will assist in determining which patients would require the most aggressive level of treatment and monitoring postintervention including

Parameter selection for and implementation of a web-based decision-support tool to predict extubation outcome in premature infants.

PubMed

Mueller, Martina; Wagner, Carol L; Annibale, David J; Knapp, Rebecca G; Hulsey, Thomas C; Almeida, Jonas S

2006-03-01

Approximately 30% of intubated preterm infants with respiratory distress syndrome (RDS) will fail attempted extubation, requiring reintubation and mechanical ventilation. Although ventilator technology and monitoring of premature infants have improved over time, optimal extubation remains challenging. Furthermore, extubation decisions for premature infants require complex informational processing, techniques implicitly learned through clinical practice. Computer-aided decision-support tools would benefit inexperienced clinicians, especially during peak neonatal intensive care unit (NICU) census. A five-step procedure was developed to identify predictive variables. Clinical expert (CE) thought processes comprised one model. Variables from that model were used to develop two mathematical models for the decision-support tool: an artificial neural network (ANN) and a multivariate logistic regression model (MLR). The ranking of the variables in the three models was compared using the Wilcoxon Signed Rank Test. The best performing model was used in a web-based decision-support tool with a user interface implemented in Hypertext Markup Language (HTML) and the mathematical model employing the ANN. CEs identified 51 potentially predictive variables for extubation decisions for an infant on mechanical ventilation. Comparisons of the three models showed a significant difference between the ANN and the CE (p = 0.0006). Of the original 51 potentially predictive variables, the 13 most predictive variables were used to develop an ANN as a web-based decision-tool. The ANN processes user-provided data and returns the prediction 0-1 score and a novelty index. The user then selects the most appropriate threshold for categorizing the prediction as a success or failure. Furthermore, the novelty index, indicating the similarity of the test case to the training case, allows the user to assess the confidence level of the prediction with regard to how much the new data differ from the data

XBeach-G: a tool for predicting gravel barrier response to extreme storm conditions

NASA Astrophysics Data System (ADS)

Masselink, Gerd; Poate, Tim; McCall, Robert; Roelvink, Dano; Russell, Paul; Davidson, Mark

2014-05-01

Gravel beaches protect low-lying back-barrier regions from flooding during storm events and their importance to society is widely acknowledged. Unfortunately, breaching and extensive storm damage has occurred at many gravel sites and this is likely to increase as a result of sea-level rise and enhanced storminess due to climate change. Limited scientific guidance is currently available to provide beach managers with operational management tools to predict the response of gravel beaches to storms. The New Understanding and Prediction of Storm Impacts on Gravel beaches (NUPSIG) project aims to improve our understanding of storm impacts on gravel coastal environments and to develop a predictive capability by modelling these impacts. The NUPSIG project uses a 5-pronged approach to address its aim: (1) analyse hydrodynamic data collected during a proto-type laboratory experiment on a gravel beach; (2) collect hydrodynamic field data on a gravel beach under a range of conditions, including storm waves with wave heights up to 3 m; (3) measure swash dynamics and beach response on 10 gravel beaches during extreme wave conditions with wave heights in excess of 3 m; (4) use the data collected under 1-3 to develop and validate a numerical model to model hydrodynamics and morphological response of gravel beaches under storm conditions; and (5) develop a tool for end-users, based on the model formulated under (4), for predicting storm response of gravel beaches and barriers. The aim of this presentation is to present the key results of the NUPSIG project and introduce the end-user tool for predicting storm response on gravel beaches. The model is based on the numerical model XBeach, and different forcing scenarios (wave and tides), barrier configurations (dimensions) and sediment characteristics are easily uploaded for model simulations using a Graphics User Interface (GUI). The model can be used to determine the vulnerability of gravel barriers to storm events, but can also be

Prediction of unsaturated flow and water backfill during infiltration in layered soils

NASA Astrophysics Data System (ADS)

Cui, Guotao; Zhu, Jianting

2018-02-01

We develop a new analytical infiltration model to determine water flow dynamics around layer interfaces during infiltration process in layered soils. The model mainly involves the analytical solutions to quadratic equations to determine the flux rates around the interfaces. Active water content profile behind the wetting front is developed based on the solution of steady state flow to dynamically update active parameters in sharp wetting front infiltration equations and to predict unsaturated flow in coarse layers before the front reaches an impeding fine layer. The effect of water backfill to saturate the coarse layers after the wetting front encounters the impeding fine layer is analytically expressed based on the active water content profiles. Comparison to the numerical solutions of the Richards equation shows that the new model can well capture water dynamics in relation to the arrangement of soil layers. The steady state active water content profile can be used to predict the saturation state of all layers when the wetting front first passes through these layers during the unsteady infiltration process. Water backfill effect may occur when the unsaturated wetting front encounters a fine layer underlying a coarse layer. Sensitivity analysis shows that saturated hydraulic conductivity is the parameter dictating the occurrence of unsaturated flow and water backfill and can be used to represent the coarseness of soil layers. Water backfill effect occurs in coarse layers between upper and lower fine layers when the lower layer is not significantly coarser than the upper layer.

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

NASA Astrophysics Data System (ADS)

Alipour, M.; Kibler, K. M.

2017-12-01

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

Laharz_py: GIS tools for automated mapping of lahar inundation hazard zones

USGS Publications Warehouse

Schilling, Steve P.

2014-01-01

Laharz_py is written in the Python programming language as a suite of tools for use in ArcMap Geographic Information System (GIS). Primarily, Laharz_py is a computational model that uses statistical descriptions of areas inundated by past mass-flow events to forecast areas likely to be inundated by hypothetical future events. The forecasts use physically motivated and statistically calibrated power-law equations that each has a form A = cV2/3, relating mass-flow volume (V) to planimetric or cross-sectional areas (A) inundated by an average flow as it descends a given drainage. Calibration of the equations utilizes logarithmic transformation and linear regression to determine the best-fit values of c. The software uses values of V, an algorithm for idenitifying mass-flow source locations, and digital elevation models of topography to portray forecast hazard zones for lahars, debris flows, or rock avalanches on maps. Laharz_py offers two methods to construct areas of potential inundation for lahars: (1) Selection of a range of plausible V values results in a set of nested hazard zones showing areas likely to be inundated by a range of hypothetical flows; and (2) The user selects a single volume and a confidence interval for the prediction. In either case, Laharz_py calculates the mean expected A and B value from each user-selected value of V. However, for the second case, a single value of V yields two additional results representing the upper and lower values of the confidence interval of prediction. Calculation of these two bounding predictions require the statistically calibrated prediction equations, a user-specified level of confidence, and t-distribution statistics to calculate the standard error of regression, standard error of the mean, and standard error of prediction. The portrayal of results from these two methods on maps compares the range of inundation areas due to prediction uncertainties with uncertainties in selection of V values. The Open-File Report

Flow unit modeling and fine-scale predicted permeability validation in Atokan sandstones: Norcan East Kansas

USGS Publications Warehouse

Bhattacharya, S.; Byrnes, A.P.; Watney, W.L.; Doveton, J.H.

2008-01-01

Characterizing the reservoir interval into flow units is an effective way to subdivide the net-pay zone into layers for reservoir simulation. Commonly used flow unit identification techniques require a reliable estimate of permeability in the net pay on a foot-by-foot basis. Most of the wells do not have cores, and the literature is replete with different kinds of correlations, transforms, and prediction methods for profiling permeability in pay. However, for robust flow unit determination, predicted permeability at noncored wells requires validation and, if necessary, refinement. This study outlines the use o f a spreadsheet-based permeability validation technique to characterize flow units in wells from the Norcan East field, Clark County, Kansas, that produce from Atokan aged fine- to very fine-grained quartzarenite sandstones interpreted to have been deposited in brackish-water, tidally dominated restricted tidal-flat, tidal-channel, tidal-bar, and estuary bay environments within a small incised-valley-fill system. The methodology outlined enables the identification of fieldwide free-water level and validates and refines predicted permeability at 0.5-ft (0.15-m) intervals by iteratively reconciling differences in water saturation calculated from wire-line log and a capillary-pressure formulation that models fine- to very fine-grained sandstone with diagenetic clay and silt or shale laminae. The effectiveness of this methodology was confirmed by successfully matching primary and secondary production histories using a flow unit-based reservoir model of the Norcan East field without permeability modifications. The methodologies discussed should prove useful for robust flow unit characterization of different kinds of reservoirs. Copyright ?? 2008. The American Association of Petroleum Geologists. All rights reserved.

In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

EPA Science Inventory

The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

Prediction of Thermal Fatigue in Tooling for Die-casting Copper via Finite Element Analysis

NASA Astrophysics Data System (ADS)

Sakhuja, Amit; Brevick, Jerald R.

2004-06-01

Recent research by the Copper Development Association (CDA) has demonstrated the feasibility of die-casting electric motor rotors using copper. Electric motors using copper rotors are significantly more energy efficient relative to motors using aluminum rotors. However, one of the challenges in copper rotor die-casting is low tool life. Experiments have shown that the higher molten metal temperature of copper (1085 °C), as compared to aluminum (660 °C) accelerates the onset of thermal fatigue or heat checking in traditional H-13 tool steel. This happens primarily because the mechanical properties of H-13 tool steel decrease significantly above 650 °C. Potential approaches to mitigate the heat checking problem include: 1) identification of potential tool materials having better high temperature mechanical properties than H-13, and 2) reduction of the magnitude of cyclic thermal excursions experienced by the tooling by increasing the bulk die temperature. A preliminary assessment of alternative tool materials has led to the selection of nickel-based alloys Haynes 230 and Inconel 617 as potential candidates. These alloys were selected based on their elevated temperature physical and mechanical properties. Therefore, the overall objective of this research work was to predict the number of copper rotor die-casting cycles to the onset of heat checking (tool life) as a function of bulk die temperature (up to 650 °C) for Haynes 230 and Inconel 617 alloys. To achieve these goals, a 2D thermo-mechanical FEA was performed to evaluate strain ranges on selected die surfaces. The method of Universal Slopes (Strain Life Method) was then employed for thermal fatigue life predictions.

A new methodology for predictive tool wear

NASA Astrophysics Data System (ADS)

Kim, Won-Sik

turned with various cutting conditions and the results were compared with the proposed analytical wear models. The crater surfaces after machining have been carefully studied to shed light on the physics behind the crater wear. In addition, the abrasive wear mechanism plays a major role in the development of crater wear. Laser shock processing (LSP) has been applied to locally relieve the deleterious tensile residual stresses on the crater surface of a coated tool, thus to improve the hardness of the coating. This thesis shows that LSP has indeed improve wear resistance of CVD coated alumina tool inserts, which has residual stress due to high processing temperature. LSP utilizes a very short laser pulse with high energy density, which induces high-pressure stress wave propagation. The residual stresses are relieved by incident shock waves on the coating surface. Residual stress levels of LSP CVD alumina-coated carbide insert were evaluated by the X-ray diffractometer. Based on these results, LSP parameters such as number of laser pulses and laser energy density can be controlled to reduce residual stress. Crater wear shows that the wear resistance increase with LSP treated tool inserts. Because the hardness data are used to predict the wear, the improvement in hardness and wear resistance shows that the mechanism of crater wear also involves abrasive wear.

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

NASA Astrophysics Data System (ADS)

Weihmann, S. A.; Healy, D.

2015-12-01

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

An Engineering Tool for the Prediction of Internal Dielectric Charging

NASA Astrophysics Data System (ADS)

Rodgers, D. J.; Ryden, K. A.; Wrenn, G. L.; Latham, P. M.; Sorensen, J.; Levy, L.

1998-11-01

A practical internal charging tool has been developed. It provides an easy-to-use means for satellite engineers to predict whether on-board dielectrics are vulnerable to electrostatic discharge in the outer radiation belt. The tool is designed to simulate irradiation of single-dielectric planar or cylindrical structures with or without shielding. Analytical equations are used to describe current deposition in the dielectric. This is fast and gives charging currents to sufficient accuracy given the uncertainties in other aspects of the problem - particularly material characteristics. Time-dependent internal electric fields are calculated, taking into account the effect on conductivity of electric field, dose rate and temperature. A worst-case model of electron fluxes in the outer belt has been created specifically for the internal charging problem and is built into the code. For output, the tool gives a YES or NO decision on the susceptibility of the structure to internal electrostatic breakdown and if necessary, calculates the required changes to bring the system below the breakdown threshold. A complementary programme of laboratory irradiations has been carried out to validate the tool. The results for Epoxy-fibreglass samples show that the code models electric field realistically for a wide variety of shields, dielectric thicknesses and electron spectra. Results for Teflon samples indicate that some further experimentation is required and the radiation-induced conductivity aspects of the code have not been validated.

CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS.

USGS Publications Warehouse

Cooley, Richard L.; Vecchia, Aldo V.

1987-01-01

A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that inclusion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.

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.

Assembly flow simulation of a radar

NASA Technical Reports Server (NTRS)

Rutherford, W. C.; Biggs, P. M.

1994-01-01

A discrete event simulation model has been developed to predict the assembly flow time of a new radar product. The simulation was the key tool employed to identify flow constraints. The radar, production facility, and equipment complement were designed, arranged, and selected to provide the most manufacturable assembly possible. A goal was to reduce the assembly and testing cycle time from twenty-six weeks. A computer software simulation package (SLAM 2) was utilized as the foundation for simulating the assembly flow time. FORTRAN subroutines were incorporated into the software to deal with unique flow circumstances that were not accommodated by the software. Detailed information relating to the assembly operations was provided by a team selected from the engineering, manufacturing management, inspection, and production assembly staff. The simulation verified that it would be possible to achieve the cycle time goal of six weeks. Equipment and manpower constraints were identified during the simulation process and adjusted as required to achieve the flow with a given monthly production requirement. The simulation is being maintained as a planning tool to be used to identify constraints in the event that monthly output is increased. 'What-if' studies have been conducted to identify the cost of reducing constraints caused by increases in output requirement.

Flow discharge prediction in compound channels using linear genetic programming

NASA Astrophysics Data System (ADS)

Azamathulla, H. Md.; Zahiri, A.

2012-08-01

SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

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

Base flow investigation of the Apollo AS-202 Command Module

NASA Astrophysics Data System (ADS)

Walpot, Louis M. G.; Wright, Michael J.; Noeding, Peter; Schrijer, Ferry

2012-01-01

A major contributor to the overall vehicle mass of re-entry vehicles is the afterbody thermal protection system. This is due to the large acreage (equal or bigger than that of the forebody) to be protected. The present predictive capabilities for base flows are comparatively lower than those for windward flowfields and offer therefore a substantial potential for improving the design of future re-entry vehicles. To that end, it is essential to address the accuracy of high fidelity CFD tools exercised in the US and EU, which motivates a thorough investigation of the present status of hypersonic flight afterbody heating. This paper addresses the predictive capabilities of afterbody flow fields of re-entry vehicles investigated in the frame of the NATO/RTO-RTG-043 task group. First, the verification of base flow topologies on the basis of available wind-tunnel results performed under controlled supersonic conditions (i.e. cold flows devoid of reactive effects) is performed. Such tests address the detailed characterization of the base flow with particular emphasis on separation/reattachment and their relation to Mach number effects. The tests have been performed on an Apollo-like re-entry capsule configuration. Second, the tools validated in the frame of the previous effort are exercised and appraised against flight-test data collected during the Apollo AS-202 re-entry.

External validation of a simple clinical tool used to predict falls in people with Parkinson disease

PubMed Central

Duncan, Ryan P.; Cavanaugh, James T.; Earhart, Gammon M.; Ellis, Terry D.; Ford, Matthew P.; Foreman, K. Bo; Leddy, Abigail L.; Paul, Serene S.; Canning, Colleen G.; Thackeray, Anne; Dibble, Leland E.

2015-01-01

Background Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. METHODS We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. RESULTS The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76 –0.89), comparable to the developmental study. CONCLUSION The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual’s risk of an impending fall. PMID:26003412

External validation of a simple clinical tool used to predict falls in people with Parkinson disease.

PubMed

Duncan, Ryan P; Cavanaugh, James T; Earhart, Gammon M; Ellis, Terry D; Ford, Matthew P; Foreman, K Bo; Leddy, Abigail L; Paul, Serene S; Canning, Colleen G; Thackeray, Anne; Dibble, Leland E

2015-08-01

Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76-0.89), comparable to the developmental study. The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual's risk of an impending fall. Copyright © 2015 Elsevier Ltd. All rights reserved.

Geriatric Assessment and Tools for Predicting Treatment Toxicity in Older Adults With Cancer.

PubMed

Li, Daneng; Soto-Perez-de-Celis, Enrique; Hurria, Arti

Cancer is a disease of older adults, and the majority of new cancer cases and deaths occur in people 65 years or older. However, fewer data are available regarding the risks and benefits of cancer treatment in older adults, and commonly used assessments in oncology fail to adequately evaluate factors that affect treatment efficacy and outcomes in the older patients. The geriatric assessment is a multidisciplinary evaluation that provides detailed information about a patient's functional status, comorbidities, psychological state, social support, nutritional status, and cognitive function. Among older patients with cancer, geriatric assessment has been shown to identify patients at risk of poorer overall survival, and geriatric assessment-based tools are significantly more effective in predicting chemotherapy toxicity than other currently utilized measures. In this review, we summarize the components of the geriatric assessment and provide information about existing tools used to predict treatment toxicity in older patients with cancer.

A numerical tool for reproducing driver behaviour: experiments and predictive simulations.

PubMed

Casucci, M; Marchitto, M; Cacciabue, P C

2010-03-01

This paper presents the simulation tool called SDDRIVE (Simple Simulation of Driver performance), which is the numerical computerised implementation of the theoretical architecture describing Driver-Vehicle-Environment (DVE) interactions, contained in Cacciabue and Carsten [Cacciabue, P.C., Carsten, O. A simple model of driver behaviour to sustain design and safety assessment of automated systems in automotive environments, 2010]. Following a brief description of the basic algorithms that simulate the performance of drivers, the paper presents and discusses a set of experiments carried out in a Virtual Reality full scale simulator for validating the simulation. Then the predictive potentiality of the tool is shown by discussing two case studies of DVE interactions, performed in the presence of different driver attitudes in similar traffic conditions.

Projected effects of Climate-change-induced flow alterations on stream macroinvertebrate abundances.

PubMed

Kakouei, Karan; Kiesel, Jens; Domisch, Sami; Irving, Katie S; Jähnig, Sonja C; Kail, Jochem

2018-03-01

Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species' response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower-mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present-day gauging data. Species' abundances were predicted for three periods: (1) baseline (1998-2017), (2) horizon 2050 (2046-2065) and (3) horizon 2090 (2080-2099) based on these empirical relationships and using high-resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low-flow conditions, leading to decreased abundances of species up to -42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower-mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate-change impacts on species

Hinge Moment Coefficient Prediction Tool and Control Force Analysis of Extra-300 Aerobatic Aircraft

NASA Astrophysics Data System (ADS)

Nurohman, Chandra; Arifianto, Ony; Barecasco, Agra

2018-04-01

This paper presents the development of tool that is applicable to predict hinge moment coefficients of subsonic aircraft based on Roskam’s method, including the validation and its application to predict hinge moment coefficient of an Extra-300. The hinge moment coefficients are used to predict the stick forces of the aircraft during several aerobatic maneuver i.e. inside loop, half cuban 8, split-s, and aileron roll. The maximum longitudinal stick force is 566.97 N occurs in inside loop while the maximum lateral stick force is 340.82 N occurs in aileron roll. Furthermore, validation hinge moment prediction method is performed using Cessna 172 data.

ASTRYD: A new numerical tool for aircraft cabin and environmental noise prediction

NASA Astrophysics Data System (ADS)

Berhault, J.-P.; Venet, G.; Clerc, C.

ASTRYD is an analytical tool, developed originally for underwater applications, that computes acoustic pressure distribution around three-dimensional bodies in closed spaces like aircraft cabins. The program accepts data from measurements or other simulations, processes them in the time domain, and delivers temporal evolutions of the acoustic pressures and accelerations, as well as the radiated/diffracted pressure at arbitrary points located in the external/internal space. A typical aerospace application is prediction of acoustic load on satellites during the launching phase. An aeronautic application is engine noise distribution on a business jet body for prediction of environmental and cabin noise.

A geographic information system tool to solve regression equations and estimate flow-frequency characteristics of Vermont Streams

USGS Publications Warehouse

Olson, Scott A.; Tasker, Gary D.; Johnston, Craig M.

2003-01-01

Estimates of the magnitude and frequency of streamflow are needed to safely and economically design bridges, culverts, and other structures in or near streams. These estimates also are used for managing floodplains, identifying flood-hazard areas, and establishing flood-insurance rates, but may be required at ungaged sites where no observed flood data are available for streamflow-frequency analysis. This report describes equations for estimating flow-frequency characteristics at ungaged, unregulated streams in Vermont. In the past, regression equations developed to estimate streamflow statistics required users to spend hours manually measuring basin characteristics for the stream site of interest. This report also describes the accompanying customized geographic information system (GIS) tool that automates the measurement of basin characteristics and calculation of corresponding flow statistics. The tool includes software that computes the accuracy of the results and adjustments for expected probability and for streamflow data of a nearby stream-gaging station that is either upstream or downstream and within 50 percent of the drainage area of the site where the flow-frequency characteristics are being estimated. The custom GIS can be linked to the National Flood Frequency program, adding the ability to plot peak-flow-frequency curves and synthetic hydrographs and to compute adjustments for urbanization.

Combining LCT tools for the optimization of an industrial process: material and energy flow analysis and best available techniques.

PubMed

Rodríguez, M T Torres; Andrade, L Cristóbal; Bugallo, P M Bello; Long, J J Casares

2011-09-15

Life cycle thinking (LCT) is one of the philosophies that has recently appeared in the context of the sustainable development. Some of the already existing tools and methods, as well as some of the recently emerged ones, which seek to understand, interpret and design the life of a product, can be included into the scope of the LCT philosophy. That is the case of the material and energy flow analysis (MEFA), a tool derived from the industrial metabolism definition. This paper proposes a methodology combining MEFA with another technique derived from sustainable development which also fits the LCT philosophy, the BAT (best available techniques) analysis. This methodology, applied to an industrial process, seeks to identify the so-called improvable flows by MEFA, so that the appropriate candidate BAT can be selected by BAT analysis. Material and energy inputs, outputs and internal flows are quantified, and sustainable solutions are provided on the basis of industrial metabolism. The methodology has been applied to an exemplary roof tile manufacture plant for validation. 14 Improvable flows have been identified and 7 candidate BAT have been proposed aiming to reduce these flows. The proposed methodology provides a way to detect improvable material or energy flows in a process and selects the most sustainable options to enhance them. Solutions are proposed for the detected improvable flows, taking into account their effectiveness on improving such flows. Copyright © 2011 Elsevier B.V. All rights reserved.

Perioperative Respiratory Adverse Events in Pediatric Ambulatory Anesthesia: Development and Validation of a Risk Prediction Tool.

PubMed

Subramanyam, Rajeev; Yeramaneni, Samrat; Hossain, Mohamed Monir; Anneken, Amy M; Varughese, Anna M

2016-05-01

Perioperative respiratory adverse events (PRAEs) are the most common cause of serious adverse events in children receiving anesthesia. Our primary aim of this study was to develop and validate a risk prediction tool for the occurrence of PRAE from the onset of anesthesia induction until discharge from the postanesthesia care unit in children younger than 18 years undergoing elective ambulatory anesthesia for surgery and radiology. The incidence of PRAE was studied. We analyzed data from 19,059 patients from our department's quality improvement database. The predictor variables were age, sex, ASA physical status, morbid obesity, preexisting pulmonary disorder, preexisting neurologic disorder, and location of ambulatory anesthesia (surgery or radiology). Composite PRAE was defined as the presence of any 1 of the following events: intraoperative bronchospasm, intraoperative laryngospasm, postoperative apnea, postoperative laryngospasm, postoperative bronchospasm, or postoperative prolonged oxygen requirement. Development and validation of the risk prediction tool for PRAE were performed using a split sampling technique to split the database into 2 independent cohorts based on the year when the patient received ambulatory anesthesia for surgery and radiology using logistic regression. A risk score was developed based on the regression coefficients from the validation tool. The performance of the risk prediction tool was assessed by using tests of discrimination and calibration. The overall incidence of composite PRAE was 2.8%. The derivation cohort included 8904 patients, and the validation cohort included 10,155 patients. The risk of PRAE was 3.9% in the development cohort and 1.8% in the validation cohort. Age ≤ 3 years (versus >3 years), ASA physical status II or III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) significantly predicted the occurrence of PRAE in a multivariable logistic regression

The Achievement Flow Motive as an Element of the Autotelic Personality: Predicting Educational Attainment in Three Cultures

ERIC Educational Resources Information Center

Busch, Holger; Hofer, Jan; Chasiotis, Athanasios; Campos, Domingo

2013-01-01

Human behavior is directed by an implicit and an explicit motivational system. The intrinsic form of the implicit achievement motive has been demonstrated to predict the experience of flow. Thus, this achievement flow motive can be considered an integral component of the autotelic personality, posited in Flow Theory as dispositional difference in…

LFSTAT - Low-Flow Analysis in R

NASA Astrophysics Data System (ADS)

Koffler, Daniel; Laaha, Gregor

2013-04-01

The calculation of characteristic stream flow during dry conditions is a basic requirement for many problems in hydrology, ecohydrology and water resources management. As opposed to floods, a number of different indices are used to characterise low flows and streamflow droughts. Although these indices and methods of calculation have been well documented in the WMO Manual on Low-flow Estimation and Prediction [1], a comprehensive software was missing which enables a fast and standardized calculation of low flow statistics. We present the new software package lfstat to fill in this obvious gap. Our software package is based on the statistical open source software R, and expands it to analyse daily stream flow data records focusing on low-flows. As command-line based programs are not everyone's preference, we also offer a plug-in for the R-Commander, an easy to use graphical user interface (GUI) provided for R which is based on tcl/tk. The functionality of lfstat includes estimation methods for low-flow indices, extreme value statistics, deficit characteristics, and additional graphical methods to control the computation of complex indices and to illustrate the data. Beside the basic low flow indices, the baseflow index and recession constants can be computed. For extreme value statistics, state-of-the-art methods for L-moment based local and regional frequency analysis (RFA) are available. The tools for deficit characteristics include various pooling and threshold selection methods to support the calculation of drought duration and deficit indices. The most common graphics for low flow analysis are available, and the plots can be modified according to the user preferences. Graphics include hydrographs for different periods, flexible streamflow deficit plots, baseflow visualisation, recession diagnostic, flow duration curves as well as double mass curves, and many more. From a technical point of view, the package uses a S3-class called lfobj (low-flow objects). This

Numerical method for predicting flow characteristics and performance of nonaxisymmetric nozzles, theory

NASA Technical Reports Server (NTRS)

Thomas, P. D.

1979-01-01

The theoretical foundation and formulation of a numerical method for predicting the viscous flowfield in and about isolated three dimensional nozzles of geometrically complex configuration are presented. High Reynolds number turbulent flows are of primary interest for any combination of subsonic, transonic, and supersonic flow conditions inside or outside the nozzle. An alternating-direction implicit (ADI) numerical technique is employed to integrate the unsteady Navier-Stokes equations until an asymptotic steady-state solution is reached. Boundary conditions are computed with an implicit technique compatible with the ADI technique employed at interior points of the flow region. The equations are formulated and solved in a boundary-conforming curvilinear coordinate system. The curvilinear coordinate system and computational grid is generated numerically as the solution to an elliptic boundary value problem. A method is developed that automatically adjusts the elliptic system so that the interior grid spacing is controlled directly by the a priori selection of the grid spacing on the boundaries of the flow region.

Gestational Diabetes Mellitus Risk score: A practical tool to predict Gestational Diabetes Mellitus risk in Tanzania.

PubMed

Patrick Nombo, Anna; Wendelin Mwanri, Akwilina; Brouwer-Brolsma, Elske M; Ramaiya, Kaushik L; Feskens, Edith

2018-05-28

Universal screening for hyperglycemia during pregnancy may be in-practical in resource constrained countries. Therefore, the aim of this study was to develop a simple, non-invasive practical tool to predict undiagnosed Gestational diabetes mellitus (GDM) in Tanzania. We used cross-sectional data of 609 pregnant women, without known diabetes, collected in six health facilities from Dar es Salaam city (urban). Women underwent screening for GDM during ante-natal clinics visit. Smoking habit, alcohol consumption, pre-existing hypertension, birth weight of the previous child, high parity, gravida, previous caesarean section, age, MUAC ≥28 cm, previous stillbirth, haemoglobin level, gestational age (weeks), family history of type 2 diabetes, intake of sweetened drinks (soda), physical activity, vegetables and fruits consumption were considered as important predictors for GDM. Multivariate logistic regression modelling was used to create the prediction model, using a cut-off value of 2.5 to minimise the number of undiagnosed GDM (false negatives). Mid-upper arm circumference (MUAC) ≥28 cm, previous stillbirth, and family history of type 2 diabetes were identified as significant risk factors of GDM with a sensitivity, specificity, positive predictive value, and negative predictive value of 69%, 53%, 12% and 95%, respectively. Moreover, the inclusion of these three predictors resulted in an area under the curve (AUC) of 0.64 (0.56-0.72), indicating that the current tool correctly classifies 64% of high risk individuals. The findings of this study indicate that MUAC, previous stillbirth, and family history of type 2 diabetes significantly predict GDM development in this Tanzanian population. However, the developed non-invasive practical tool to predict undiagnosed GDM only identified 6 out of 10 individuals at risk of developing GDM. Thus, further development of the tool is warranted, for instance by testing the impact of other known risk factors such as maternal age

Network-wide BGP route prediction for traffic engineering

NASA Astrophysics Data System (ADS)

Feamster, Nick; Rexford, Jennifer

2002-07-01

The Internet consists of about 13,000 Autonomous Systems (AS's) that exchange routing information using the Border Gateway Protocol (BGP). The operators of each AS must have control over the flow of traffic through their network and between neighboring AS's. However, BGP is a complicated, policy-based protocol that does not include any direct support for traffic engineering. In previous work, we have demonstrated that network operators can adapt the flow of traffic in an efficient and predictable fashion through careful adjustments to the BGP policies running on their edge routers. Nevertheless, many details of the BGP protocol and decision process make predicting the effects of these policy changes difficult. In this paper, we describe a tool that predicts traffic flow at network exit points based on the network topology, the import policy associated with each BGP session, and the routing advertisements received from neighboring AS's. We present a linear-time algorithm that computes a network-wide view of the best BGP routes for each destination prefix given a static snapshot of the network state, without simulating the complex details of BGP message passing. We describe how to construct this snapshot using the BGP routing tables and router configuration files available from operational routers. We verify the accuracy of our algorithm by applying our tool to routing and configuration data from AT&T's commercial IP network. Our route prediction techniques help support the operation of large IP backbone networks, where interdomain routing is an important aspect of traffic engineering.

"In silico" mechanistic studies as predictive tools in microwave-assisted organic synthesis.

PubMed

Rodriguez, A M; Prieto, P; de la Hoz, A; Díaz-Ortiz, A

2011-04-07

Computational calculations can be used as a predictive tool in Microwave-Assisted Organic Synthesis (MAOS). A DFT study on Intramolecular Diels-Alder reactions (IMDA) indicated that the activation energy of the reaction and the polarity of the stationary points are two fundamental parameters to determine "a priori" if a reaction can be improved by using microwave irradiation.

The predictive validity of common risk assessment tools in men with intellectual disabilities and problematic sexual behaviors.

PubMed

Fedoroff, J Paul; Richards, Deborah; Ranger, Rebekah; Curry, Susan

2016-10-01

This CIHR-funded study examined whether certain current risk assessment tools were effective in appraising risk of recidivism in a sample of sex offenders with intellectual disabilities (ID). Fifty men with ID who had engaged in problematic sexual behavior (PSB) were followed for an average of 2.5 years. Recidivism was defined and measured as any illegal or problematic behavior, as well as any problematic but not necessarily illegal behavior. At the beginning of the study, each participant was rated on two risk assessment tools: the Violence Risk Appraisal Guide (VRAG) and the Sex Offender Risk Appraisal Guide (SORAG). During each month of follow-up, participants were also rated on the Short-Dynamic Risk Scale (SDRS), an assessment tool intended to measure the risk of future problematic behaviors. Data was analyzed using t-tests, Cohen's d and area under the curve (AUC) to test predictive validity of the assessment tools. Using the AUC, results showed that the VRAG was predictive of sexual (AUC=0.74), sexual and/or violent (AUC=0.71) and of any criminally chargeable event (AUC=0.69). The SORAG was only significantly predictive of sexual events (AUC=0.70) and the SDRS was predictive of violent events (AUC=0.71). The t-test and Cohen's d analyses, which are less robust to deviations from the assumptions of normal and continuous distribution than AUC, did not yield significant results in each category, and therefore, while the results of this study suggest that the VRAG and the SORAG may be effective tools in measuring the short term risk of sexual recidivism; and the VRAG and SDRS may be effective tools in appraising long term risk of sexual and/or violent recidivism in this population, it should be used with caution. Regardless of the assessment tool used, risk assessments should take into account the differences between sex offenders with and without ID to ensure effective measurement. Copyright © 2016. Published by Elsevier Ltd.

Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.

PubMed

Ernst, Corinna; Hahnen, Eric; Engel, Christoph; Nothnagel, Michael; Weber, Jonas; Schmutzler, Rita K; Hauke, Jan

2018-03-27

The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. We show that due to low specificities state-of-the-art in silico

Comparison of Hydrodynamic Load Predictions Between Engineering Models and Computational Fluid Dynamics for the OC4-DeepCwind Semi-Submersible: Preprint

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

Benitz, M. A.; Schmidt, D. P.; Lackner, M. A.

Hydrodynamic loads on the platforms of floating offshore wind turbines are often predicted with computer-aided engineering tools that employ Morison's equation and/or potential-flow theory. This work compares results from one such tool, FAST, NREL's wind turbine computer-aided engineering tool, and the computational fluid dynamics package, OpenFOAM, for the OC4-DeepCwind semi-submersible analyzed in the International Energy Agency Wind Task 30 project. Load predictions from HydroDyn, the offshore hydrodynamics module of FAST, are compared with high-fidelity results from OpenFOAM. HydroDyn uses a combination of Morison's equations and potential flow to predict the hydrodynamic forces on the structure. The implications of the assumptionsmore » in HydroDyn are evaluated based on this code-to-code comparison.« less

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.

Predictive modelling of flow in a two-dimensional intermediate-scale, heterogeneous porous media

USGS Publications Warehouse

Barth, Gilbert R.; Hill, M.C.; Illangasekare, T.H.; Rajaram, H.

2000-01-01

To better understand the role of sedimentary structures in flow through porous media, and to determine how small-scale laboratory-measured values of hydraulic conductivity relate to in situ values this work deterministically examines flow through simple, artificial structures constructed for a series of intermediate-scale (10 m long), two-dimensional, heterogeneous, laboratory experiments. Nonlinear regression was used to determine optimal values of in situ hydraulic conductivity, which were compared to laboratory-measured values. Despite explicit numerical representation of the heterogeneity, the optimized values were generally greater than the laboratory-measured values. Discrepancies between measured and optimal values varied depending on the sand sieve size, but their contribution to error in the predicted flow was fairly consistent for all sands. Results indicate that, even under these controlled circumstances, laboratory-measured values of hydraulic conductivity need to be applied to models cautiously.To better understand the role of sedimentary structures in flow through porous media, and to determine how small-scale laboratory-measured values of hydraulic conductivity relate to in situ values this work deterministically examines flow through simple, artificial structures constructed for a series of intermediate-scale (10 m long), two-dimensional, heterogeneous, laboratory experiments. Nonlinear regression was used to determine optimal values of in situ hydraulic conductivity, which were compared to laboratory-measured values. Despite explicit numerical representation of the heterogeneity, the optimized values were generally greater than the laboratory-measured values. Discrepancies between measured and optimal values varied depending on the sand sieve size, but their contribution to error in the predicted flow was fairly consistent for all sands. Results indicate that, even under these controlled circumstances, laboratory-measured values of hydraulic

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

PubMed

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

2016-12-01

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

Aortic flow conditions predict ejection efficiency in the NHLBI-Sponsored Women's Ischemia Syndrome Evaluation (WISE).

PubMed

Doyle, Mark; Pohost, Gerald M; Bairey Merz, C Noel; Farah, Victor; Shaw, Leslee J; Sopko, George; Rogers, William J; Sharaf, Barry L; Pepine, Carl J; Thompson, Diane V; Rayarao, Geetha; Tauxe, Lindsey; Kelsey, Sheryl F; Biederman, Robert W W

2017-06-01

The Windkessel model of the cardiovascular system, both in its original wind-chamber and flow-pipe form, and in its electrical circuit analog has been used for over a century to modeled left ventricular ejection conditions. Using parameters obtained from aortic flow we formed a Flow Index that is proportional to the impedance of such a "circuit". We show that the impedance varies with ejection fraction (EF) in a manner characteristic of a resonant circuit with multiple resonance points, with each resonance point centrally located in a small range of EF values, i.e., corresponding to multiple contiguous EF bands. Two target populations were used: (I) a development group comprising male and female subjects (n=112) undergoing cardiovascular magnetic resonance (CMR) imaging for a variety of cardiac conditions. The Flow Index was developed using aortic flow data and its relationship to left ventricular EF was shown. (II) An illustration group comprised of female subjects from the Women's Ischemia Syndrome Evaluation (WISE) (n=201) followed for 5 years for occurrence of major adverse cardiovascular events (MACE). Flow data was not available in this group but since the Flow Index was related to the EF we noted the MACE rate with respect to EF. The EFs of the development population covered a wide range (9%-76%) traversing six Flow Index resonance bands. Within each Flow Index resonance band the impedance varied from highly capacitive at the lower range of EF through minimal impedance at resonance, to highly inductive at the higher range of EF, which is characteristic of a resonant circuit. When transitioning from one EF band to a higher band, the Flow Index made a sudden transition from highly inductive to capacitive impedance modes. MACE occurred in 26 (13%) of the WISE (illustration) population. Distance in EF units (Delta center ) from the central location between peaks of MACE activity was derived from EF data and was predictive of MACE rate with an area under the

Prediction of Transonic Vortex Flows Using Linear and Nonlinear Turbulent Eddy Viscosity Models

NASA Technical Reports Server (NTRS)

Bartels, Robert E.; Gatski, Thomas B.

2000-01-01

Three-dimensional transonic flow over a delta wing is investigated with a focus on the effect of transition and influence of turbulence stress anisotropies. The performance of linear eddy viscosity models and an explicit algebraic stress model is assessed at the start of vortex flow, and the results compared with experimental data. To assess the effect of transition location, computations that either fix transition or are fully turbulent are performed. To assess the effect of the turbulent stress anisotropy, comparisons are made between predictions from the algebraic stress model and the linear eddy viscosity models. Both transition location and turbulent stress anisotropy significantly affect the 3D flow field. The most significant effect is found to be the modeling of transition location. At a Mach number of 0.90, the computed solution changes character from steady to unsteady depending on transition onset. Accounting for the anisotropies in the turbulent stresses also considerably impacts the flow, most notably in the outboard region of flow separation.

Near-Surface Wind Predictions in Complex Terrain with a CFD Approach Optimized for Atmospheric Boundary Layer Flows

NASA Astrophysics Data System (ADS)

Wagenbrenner, N. S.; Forthofer, J.; Butler, B.; Shannon, K.

2014-12-01

Near-surface wind predictions are important for a number of applications, including transport and dispersion, wind energy forecasting, and wildfire behavior. Researchers and forecasters would benefit from a wind model that could be readily applied to complex terrain for use in these various disciplines. Unfortunately, near-surface winds in complex terrain are not handled well by traditional modeling approaches. Numerical weather prediction models employ coarse horizontal resolutions which do not adequately resolve sub-grid terrain features important to the surface flow. Computational fluid dynamics (CFD) models are increasingly being applied to simulate atmospheric boundary layer (ABL) flows, especially in wind energy applications; however, the standard functionality provided in commercial CFD models is not suitable for ABL flows. Appropriate CFD modeling in the ABL requires modification of empirically-derived wall function parameters and boundary conditions to avoid erroneous streamwise gradients due to inconsistences between inlet profiles and specified boundary conditions. This work presents a new version of a near-surface wind model for complex terrain called WindNinja. The new version of WindNinja offers two options for flow simulations: 1) the native, fast-running mass-consistent method available in previous model versions and 2) a CFD approach based on the OpenFOAM modeling framework and optimized for ABL flows. The model is described and evaluations of predictions with surface wind data collected from two recent field campaigns in complex terrain are presented. A comparison of predictions from the native mass-consistent method and the new CFD method is also provided.

Detailed predictions of climate induced changes in the thermal and flow regimes in mountain streams of the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Santiago, José M.; Muñoz-Mas, Rafael; García de Jalón, Diego; Solana, Joaquín; Alonso, Carlos; Martínez-Capel, Francisco; Ribalaygua, Jaime; Pórtoles, Javier; Monjo, Robert

2016-04-01

Streamflow and temperature regimes are well-known to influence on the availability of suitable physical habitat for instream biological communities. General Circulation Models (GCMs) have predicted significant changes in timing and geographic distribution of precipitation and atmospheric temperature for the ongoing century. However, differences in these predictions may arise when focusing on different spatial and temporal scales. Therefore, to perform substantiated mitigation and management actions detailed scales are necessary to adequately forecast the consequent thermal and flow regimes. Regional predictions are relatively abundant but detailed ones, both spatially and temporally, are still scarce. The present study aimed at predicting the effects of climate change on the thermal and flow regime in the Iberian Peninsula, refining the resolution of previous studies. For this purpose, the study encompassed 28 sites at eight different mountain rivers and streams in the central part of the Iberian Peninsula (Spain). The daily flow was modelled using different daily, monthly and quarterly lags of the historical precipitation and temperature time series. These precipitation-runoff models were developed by means of M5 model trees. On the other hand water temperature was modelled at similar time scale by means of nonlinear regression from dedicated site-specific data. The developed models were used to simulate the temperature and flow regime under two Representative Concentration Pathway (RCPs) climate change scenarios (RCP 4.5 and RCP 8.5) until the end of the present century by considering nine different GCMs, which were pertinently downscaled. The precipitation-runoff models achieved high accuracy (NSE>0.7), especially in regards of the low flows of the historical series. Results concomitantly forecasted flow reductions between 7 and 17 % (RCP4.5) and between 8 and 49% (RCP8.5) of the annual average in the most cases, being variable the magnitude and timing at each

Computer prediction of three-dimensional potential flow fields in which aircraft propellers operate: Computer program description and users manual

NASA Technical Reports Server (NTRS)

Jumper, S. J.

1979-01-01

A method was developed for predicting the potential flow velocity field at the plane of a propeller operating under the influence of a wing-fuselage-cowl or nacelle combination. A computer program was written which predicts the three dimensional potential flow field. The contents of the program, its input data, and its output results are described.

Effects of Cerebral Blood Flow and Vessel Conditions on Speech Recognition in Patients With Postlingual Adult Cochlear Implant: Predictable Factors for the Efficacy of Cochlear Implant.

PubMed

Ishino, Takashi; Ragaee, Mahmoud Ali; Maruhashi, Tatsuya; Kajikawa, Masato; Higashi, Yukihito; Sonoyama, Toru; Takeno, Sachio; Hirakawa, Katsuhiro

Cochlear implantation (CI) has been the most successful procedure for restoring hearing in a patient with severe and profound hearing loss. However, possibly owing to the variable brain functions of each patient, its performance and the associated patient satisfaction are widely variable. The authors hypothesize that peripheral and cerebral circulation can be assessed by noninvasive and globally available methods, yielding superior presurgical predictive factors of the performance of CI in adult patients with postlingual hearing loss who are scheduled to undergo CI. Twenty-two adult patients with cochlear implants for postlingual hearing loss were evaluated using Doppler sonography measurement of the cervical arteries (reflecting cerebral blood flow), flow-mediated dilation (FMD; reflecting the condition of cerebral arteries), and their pre-/post-CI best score on a monosyllabic discrimination test (pre-/post-CI best monosyllabic discrimination [BMD] score). Correlations between post-CI BMD score and the other factors were examined using univariate analysis and stepwise multiple linear regression analysis. The prediction factors were calculated by examining the receiver-operating characteristic curve between post-CI BMD score and the significantly positively correlated factors. Age and duration of deafness had a moderately negative correlation. The mean velocity of the internal carotid arteries and FMD had a moderate-to-strong positive correlation with the post-CI BMD score in univariate analysis. Stepwise multiple linear regression analysis revealed that only FMD was significantly positively correlated with post-CI BMD score. Analysis of the receiver-operating characteristic curve showed that a FMD cutoff score of 1.8 significantly predicted post-CI BMD score. These data suggest that FMD is a convenient, noninvasive, and widely available tool for predicting the efficacy of cochlear implants. An FMD cutoff score of 1.8 could be a good index for determining whether

Using Flow Characteristics in Three-Dimensional Power Doppler Ultrasound Imaging to Predict Complete Responses in Patients Undergoing Neoadjuvant Chemotherapy.

PubMed

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

2017-05-01

Strategies are needed for the identification of a poor response to treatment and determination of appropriate chemotherapy strategies for patients in the early stages of neoadjuvant chemotherapy for breast cancer. We hypothesize that power Doppler ultrasound imaging can provide useful information on predicting response to neoadjuvant chemotherapy. The solid directional flow of vessels in breast tumors was used as a marker of pathologic complete responses (pCR) in patients undergoing neoadjuvant chemotherapy. Thirty-one breast cancer patients who received neoadjuvant chemotherapy and had tumors of 2 to 5 cm were recruited. Three-dimensional power Doppler ultrasound with high-definition flow imaging technology was used to acquire the indices of tumor blood flow/volume, and the chemotherapy response prediction was established, followed by support vector machine classification. The accuracy of pCR prediction before the first chemotherapy treatment was 83.87% (area under the ROC curve [AUC] = 0.6957). After the second chemotherapy treatment, the accuracy of was 87.9% (AUC = 0.756). Trend analysis showed that good and poor responders exhibited different trends in vascular flow during chemotherapy. This preliminary study demonstrates the feasibility of using the vascular flow in breast tumors to predict chemotherapeutic efficacy. © 2017 by the American Institute of Ultrasound in Medicine.

Modeling and evaluating of surface roughness prediction in micro-grinding on soda-lime glass considering tool characterization

NASA Astrophysics Data System (ADS)

Cheng, Jun; Gong, Yadong; Wang, Jinsheng

2013-11-01

The current research of micro-grinding mainly focuses on the optimal processing technology for different materials. However, the material removal mechanism in micro-grinding is the base of achieving high quality processing surface. Therefore, a novel method for predicting surface roughness in micro-grinding of hard brittle materials considering micro-grinding tool grains protrusion topography is proposed in this paper. The differences of material removal mechanism between convention grinding process and micro-grinding process are analyzed. Topography characterization has been done on micro-grinding tools which are fabricated by electroplating. Models of grain density generation and grain interval are built, and new predicting model of micro-grinding surface roughness is developed. In order to verify the precision and application effect of the surface roughness prediction model proposed, a micro-grinding orthogonally experiment on soda-lime glass is designed and conducted. A series of micro-machining surfaces which are 78 nm to 0.98 μm roughness of brittle material is achieved. It is found that experimental roughness results and the predicting roughness data have an evident coincidence, and the component variable of describing the size effects in predicting model is calculated to be 1.5×107 by reverse method based on the experimental results. The proposed model builds a set of distribution to consider grains distribution densities in different protrusion heights. Finally, the characterization of micro-grinding tools which are used in the experiment has been done based on the distribution set. It is concluded that there is a significant coincidence between surface prediction data from the proposed model and measurements from experiment results. Therefore, the effectiveness of the model is demonstrated. This paper proposes a novel method for predicting surface roughness in micro-grinding of hard brittle materials considering micro-grinding tool grains protrusion

Experimental Investigation of Flow Condensation in Microgravity

NASA Technical Reports Server (NTRS)

Lee, Hyoungsoon; Park, Ilchung; Konishi, Christopher; Mudawar, Issam; May, Rochelle I.; Juergens, Jeffery R.; Wagner, James D.; Hall, Nancy R.; Nahra, Henry K.; Hasan, Mohammed M.;

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.

Aerodynamic Flow Field Measurements for Automotive Systems

NASA Technical Reports Server (NTRS)

Hepner, Timothy E.

1999-01-01

The design of a modern automotive air handling system is a complex task. The system is required to bring the interior of the vehicle to a comfortable level in as short a time as possible. A goal of the automotive industry is to predict the interior climate of an automobile using advanced computational fluid dynamic (CFD) methods. The development of these advanced prediction tools will enable better selection of engine and accessory components. The goal of this investigation was to predict methods used by the automotive industry. To accomplish this task three separate experiments were performed. The first was a laboratory setup where laser velocimeter (LV) flow field measurements were made in the heating and air conditioning unit of a Ford Windstar. The second involved flow field measurements in the engine compartment of a Ford Explorer, with the engine running idle. The third mapped the flow field exiting the center dashboard panel vent inside the Explorer, while the circulating fan operated at 14 volts. All three experiments utilized full-coincidence three-component LV systems. This enabled the mean and fluctuating velocities to be measured along with the Reynolds stress terms.

A low order flow/acoustics interaction method for the prediction of sound propagation using 3D adaptive hybrid grids

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

Kallinderis, Yannis, E-mail: kallind@otenet.gr; Vitsas, Panagiotis A.; Menounou, Penelope

2012-07-15

A low-order flow/acoustics interaction method for the prediction of sound propagation and diffraction in unsteady subsonic compressible flow using adaptive 3-D hybrid grids is investigated. The total field is decomposed into the flow field described by the Euler equations, and the acoustics part described by the Nonlinear Perturbation Equations. The method is shown capable of predicting monopole sound propagation, while employment of acoustics-guided adapted grid refinement improves the accuracy of capturing the acoustic field. Interaction of sound with solid boundaries is also examined in terms of reflection, and diffraction. Sound propagation through an unsteady flow field is examined using staticmore » and dynamic flow/acoustics coupling demonstrating the importance of the latter.« less

Prediction of inspiratory flow shapes during sleep with a mathematic model of upper airway forces.

PubMed

Aittokallio, Tero; Gyllenberg, Mats; Saaresranta, Tarja; Polo, Olli

2003-11-01

To predict the airflow dynamics during sleep using a mathematic model that incorporates a number of static and dynamic upper airway forces, and to compare the numerical results to clinical flow data recorded from patients with sleep-disordered breathing on and off various treatment options. Upper airway performance was modeled in virtual subjects characterized by parameter settings that describe common combinations of risk factors predisposing to upper airway collapse during sleep. The treatments effect were induced by relevant changes of the initial parameter values. Computer simulations at our website (http://www.utu.fi/ml/sovmat/bio/). Risk factors considered in the simulation settings were sex, obesity, pharyngeal collapsibility, and decreased phasic activity of pharyngeal muscles. The effects of weight loss, pharyngeal surgery, nasal continuous positive airway pressure, and respiratory stimulation on the inspiratory flow characteristics were tested with the model. Numerical predictions were investigated by means of 3 measurable inspiratory airflow characteristics: initial slope, total volume, and flow shape. The model was able to reproduce the inspiratory flow shape characteristics that have previously been described in the literature. Simulation results also supported the observations that a multitude of factors underlie the pharyngeal collapse and, therefore, certain medical therapies that are effective in some conditions may prove ineffective in others. A mathematic model integrating the current knowledge of upper airway physiology is able to predict individual treatment responses. The model provides a framework for designing novel and potentially feasible treatment alternatives for sleep-disordered breathing.

Aeroacoustic Prediction Codes

NASA Technical Reports Server (NTRS)

Gliebe, P; Mani, R.; Shin, H.; Mitchell, B.; Ashford, G.; Salamah, S.; Connell, S.; Huff, Dennis (Technical Monitor)

2000-01-01

This report describes work performed on Contract NAS3-27720AoI 13 as part of the NASA Advanced Subsonic Transport (AST) Noise Reduction Technology effort. Computer codes were developed to provide quantitative prediction, design, and analysis capability for several aircraft engine noise sources. The objective was to provide improved, physics-based tools for exploration of noise-reduction concepts and understanding of experimental results. Methods and codes focused on fan broadband and 'buzz saw' noise and on low-emissions combustor noise and compliment work done by other contractors under the NASA AST program to develop methods and codes for fan harmonic tone noise and jet noise. The methods and codes developed and reported herein employ a wide range of approaches, from the strictly empirical to the completely computational, with some being semiempirical analytical, and/or analytical/computational. Emphasis was on capturing the essential physics while still considering method or code utility as a practical design and analysis tool for everyday engineering use. Codes and prediction models were developed for: (1) an improved empirical correlation model for fan rotor exit flow mean and turbulence properties, for use in predicting broadband noise generated by rotor exit flow turbulence interaction with downstream stator vanes: (2) fan broadband noise models for rotor and stator/turbulence interaction sources including 3D effects, noncompact-source effects. directivity modeling, and extensions to the rotor supersonic tip-speed regime; (3) fan multiple-pure-tone in-duct sound pressure prediction methodology based on computational fluid dynamics (CFD) analysis; and (4) low-emissions combustor prediction methodology and computer code based on CFD and actuator disk theory. In addition. the relative importance of dipole and quadrupole source mechanisms was studied using direct CFD source computation for a simple cascadeigust interaction problem, and an empirical combustor

Will it rise or will it fall? Managing the complex effects of urbanization on base flow

USGS Publications Warehouse

Bhaskar, Aditi; Beesley, Leah; Burns, Matthew J.; Fletcher, T. D.; Hamel, Perrine; Oldham, Carolyn; Roy, Allison

2016-01-01

Sustaining natural levels of base flow is critical to maintaining ecological function as stream catchments are urbanized. Research shows a variable response of stream base flow to urbanization, with base flow or water tables rising in some locations, falling in others, or elsewhere remaining constant. The variable baseflow response is due to the array of natural (e.g., physiographic setting and climate) and anthropogenic (e.g., urban development and infrastructure) factors that influence hydrology. Perhaps as a consequence of this complexity, few simple tools exist to assist managers to predict baseflow change in their local urban area. This paper addresses this management need by presenting a decision support tool. The tool considers the natural vulnerability of the landscape, together with aspects of urban development in predicting the likelihood and direction of baseflow change. Where the tool identifies a likely increase or decrease it guides managers toward strategies that can reduce or increase groundwater recharge, respectively. Where the tool finds an equivocal result, it suggests a detailed water balance be performed. The decision support tool is embedded within an adaptive-management framework that encourages managers to define their ecological objectives, assess the vulnerability of their ecological objectives to changes in water table height, and monitor baseflow responses to urbanization. We trial our framework using two very different case studies: Perth, Western Australia, and Baltimore, Maryland, USA. Together, these studies show how pre-development water table height, climate and geology together with aspects of urban infrastructure (e.g., stormwater practices, leaky pipes) interact such that urbanization has overall led to rising base flow (Perth) and falling base flow (Baltimore). Greater consideration of subsurface components of the water cycle will help to protect and restore the ecology of urban freshwaters.

Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

NASA Astrophysics Data System (ADS)

Wu, Yanling

2018-05-01

In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

PubMed

DiMaio, Frank

2017-01-01

Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

Using artificial intelligence to control fluid flow computations

NASA Technical Reports Server (NTRS)

Gelsey, Andrew

1992-01-01

Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

Numerical method for predicting flow characteristics and performance of nonaxisymmetric nozzles. Part 2: Applications

NASA Technical Reports Server (NTRS)

Thomas, P. D.

1980-01-01

A computer implemented numerical method for predicting the flow in and about an isolated three dimensional jet exhaust nozzle is summarized. The approach is based on an implicit numerical method to solve the unsteady Navier-Stokes equations in a boundary conforming curvilinear coordinate system. Recent improvements to the original numerical algorithm are summarized. Equations are given for evaluating nozzle thrust and discharge coefficient in terms of computed flowfield data. The final formulation of models that are used to simulate flow turbulence effect is presented. Results are presented from numerical experiments to explore the effect of various quantities on the rate of convergence to steady state and on the final flowfield solution. Detailed flowfield predictions for several two and three dimensional nozzle configurations are presented and compared with wind tunnel experimental data.

Log D versus HPLC derived hydrophobicity: The development of predictive tools to aid in the rational design of bioactive peptoids

DOE PAGES

Bolt, H. L.; Williams, C. E. J.; Brooks, R. V.; ...

2017-01-13

Hydrophobicity has proven to be an extremely useful parameter in small molecule drug discovery programmes given that it can be used as a predictive tool to enable rational design. For larger molecules, including peptoids, where folding is possible, the situation is more complicated and the average hydrophobicity (as determined by RP-HPLC retention time) may not always provide an effective predictive tool for rational design. Herein, we report the first ever application of partitioning experiments to determine the log D values for a series of peptoids. By comparing log D and average hydrophobicities we highlight the potential advantage of employing themore » former as a predictive tool in the rational design of biologically active peptoids.« less

Log D versus HPLC derived hydrophobicity: The development of predictive tools to aid in the rational design of bioactive peptoids

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

Bolt, H. L.; Williams, C. E. J.; Brooks, R. V.

Hydrophobicity has proven to be an extremely useful parameter in small molecule drug discovery programmes given that it can be used as a predictive tool to enable rational design. For larger molecules, including peptoids, where folding is possible, the situation is more complicated and the average hydrophobicity (as determined by RP-HPLC retention time) may not always provide an effective predictive tool for rational design. Herein, we report the first ever application of partitioning experiments to determine the log D values for a series of peptoids. By comparing log D and average hydrophobicities we highlight the potential advantage of employing themore » former as a predictive tool in the rational design of biologically active peptoids.« less

Lung cancer in symptomatic patients presenting in primary care: a systematic review of risk prediction tools

PubMed Central

Schmidt-Hansen, Mia; Berendse, Sabine; Hamilton, Willie; Baldwin, David R

2017-01-01

Background Lung cancer is the leading cause of cancer deaths. Around 70% of patients first presenting to specialist care have advanced disease, at which point current treatments have little effect on survival. The issue for primary care is how to recognise patients earlier and investigate appropriately. This requires an assessment of the risk of lung cancer. Aim The aim of this study was to systematically review the existing risk prediction tools for patients presenting in primary care with symptoms that may indicate lung cancer Design and setting Systematic review of primary care data. Method Medline, PreMedline, Embase, the Cochrane Library, Web of Science, and ISI Proceedings (1980 to March 2016) were searched. The final list of included studies was agreed between two of the authors, who also appraised and summarised them. Results Seven studies with between 1482 and 2 406 127 patients were included. The tools were all based on UK primary care data, but differed in complexity of development, number/type of variables examined/included, and outcome time frame. There were four multivariable tools with internal validation area under the curves between 0.88 and 0.92. The tools all had a number of limitations, and none have been externally validated, or had their clinical and cost impact examined. Conclusion There is insufficient evidence for the recommendation of any one of the available risk prediction tools. However, some multivariable tools showed promising discrimination. What is needed to guide clinical practice is both external validation of the existing tools and a comparative study, so that the best tools can be incorporated into clinical decision tools used in primary care. PMID:28483820