Assessment of subchannel code ASSERT-PV for flow-distribution predictions

International Nuclear Information System (INIS)

Nava-Dominguez, A.; Rao, Y.F.; Waddington, G.M.

2014-01-01

Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles

Assessment of subchannel code ASSERT-PV for flow-distribution predictions

Energy Technology Data Exchange (ETDEWEB)

Nava-Dominguez, A., E-mail: navadoma@aecl.ca; Rao, Y.F., E-mail: raoy@aecl.ca; Waddington, G.M., E-mail: waddingg@aecl.ca

2014-08-15

Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles.

Prediction of two-phase choked-flow through safety valves

International Nuclear Information System (INIS)

Arnulfo, G; Bertani, C; De Salve, M

2014-01-01

Different models of two-phase choked flow through safety valves are applied in order to evaluate their capabilities of prediction in different thermal-hydraulic conditions. Experimental data available in the literature for two-phase fluid and subcooled liquid upstream the safety valve have been compared with the models predictions. Both flashing flows and non-flashing flows of liquid and incondensable gases have been considered. The present paper shows that for flashing flows good predictions are obtained by using the two-phase valve discharge coefficient defined by Lenzing and multiplying it by the critical flow rate in an ideal nozzle evaluated by either Omega Method or the Homogeneous Non-equilibrium Direct Integration. In case of non-flashing flows of water and air, Leung/Darby formulation of the two-phase valve discharge coefficient together with the Omega Method is more suitable to the prediction of flow rate.

The PAPAS index: a novel index for the prediction of hepatitis C-related fibrosis.

Science.gov (United States)

Ozel, Banu D; Poyrazoğlu, Orhan K; Karaman, Ahmet; Karaman, Hatice; Altinkaya, Engin; Sevinç, Eylem; Zararsiz, Gökmen

2015-08-01

Several noninvasive tests have been developed to determine the degree of hepatic fibrosis in patients with chronic hepatitis C (CHC) without performing liver biopsy. This study aimed to determine the performance of the PAPAS (Platelet/Age/Phosphatase/AFP/AST) index in patients with CHC for the prediction of significant fibrosis and cirrhosis and to compare it with other noninvasive tests. To date, no study has evaluated the application of the PAPAS index in CHC-associated liver fibrosis. This retrospective study included 137 consecutive patients with CHC who had undergone a percutaneous liver biopsy before treatment. The aspartate aminotransferase/platelet ratio (APRI), aspartate aminotransferase/alanine transaminase ratio (AAR), age-platelet index (API), FIB4, cirrhosis discriminate score (CDS), the Göteborg University cirrhosis index (GUCI), and PAPAS were calculated and compared with the diagnostic accuracies of all fibrosis indices between the groups F0-F2 (no-mild fibrosis) versus F3-F6 (significant fibrosis) and F0-F4 (no cirrhosis) versus F5-F6 (cirrhosis). To predict significant fibrosis, the area under curve (95% confidence interval) for FIB4 was 0.727 followed by GUCI (0.721), PAPAS≈APRI≈CDS (0.716), and API (0.68). To predict cirrhosis, the area under curve (95% confidence interval) for FIB4 was calculated to be 0.735, followed by GUCI (0.723), PAPAS≈APRI≈CDS≈(0.71), and API (0.66). No statistically significant difference was observed among these predictors to exclude both significant fibrosis and cirrhosis (P>0.05). The diagnostic capability of the PAPAS index has moderate efficiency and was not superior to other fibrosis markers for the identification of fibrosis in CHC patients. There is a need for more comprehensive prospective studies to help determine the diagnostic value of PAPAS for liver fibrosis.

Fabrication of rigid and flexible refractive-index-matched flow phantoms for flow visualisation and optical flow measurements

Science.gov (United States)

Geoghegan, P. H.; Buchmann, N. A.; Spence, C. J. T.; Moore, S.; Jermy, M.

2012-05-01

A method for the construction of both rigid and compliant (flexible) transparent flow phantoms of biological flow structures, suitable for PIV and other optical flow methods with refractive-index-matched working fluid is described in detail. Methods for matching the in vivo compliance and elastic wave propagation wavelength are presented. The manipulation of MRI and CT scan data through an investment casting mould is described. A method for the casting of bubble-free phantoms in silicone elastomer is given. The method is applied to fabricate flexible phantoms of the carotid artery (with and without stenosis), the carotid artery bifurcation (idealised and patient-specific) and the human upper airway (nasal cavity). The fidelity of the phantoms to the original scan data is measured, and it is shown that the cross-sectional error is less than 5% for phantoms of simple shape but up to 16% for complex cross-sectional shapes such as the nasal cavity. This error is mainly due to the application of a PVA coating to the inner mould and can be reduced by shrinking the digital model. Sixteen per cent variation in area is less than the natural patient to patient variation of the physiological geometries. The compliance of the phantom walls is controlled within physiologically realistic ranges, by choice of the wall thickness, transmural pressure and Young's modulus of the elastomer. Data for the dependence of Young's modulus on curing temperature are given for Sylgard 184. Data for the temperature dependence of density, viscosity and refractive index of the refractive-index-matched working liquid (i.e. water-glycerol mixtures) are also presented.

Prediction of monthly average global solar radiation based on statistical distribution of clearness index

International Nuclear Information System (INIS)

Ayodele, T.R.; Ogunjuyigbe, A.S.O.

2015-01-01

In this paper, probability distribution of clearness index is proposed for the prediction of global solar radiation. First, the clearness index is obtained from the past data of global solar radiation, then, the parameters of the appropriate distribution that best fit the clearness index are determined. The global solar radiation is thereafter predicted from the clearness index using inverse transformation of the cumulative distribution function. To validate the proposed method, eight years global solar radiation data (2000–2007) of Ibadan, Nigeria are used to determine the parameters of appropriate probability distribution for clearness index. The calculated parameters are then used to predict the future monthly average global solar radiation for the following year (2008). The predicted values are compared with the measured values using four statistical tests: the Root Mean Square Error (RMSE), MAE (Mean Absolute Error), MAPE (Mean Absolute Percentage Error) and the coefficient of determination (R"2). The proposed method is also compared to the existing regression models. The results show that logistic distribution provides the best fit for clearness index of Ibadan and the proposed method is effective in predicting the monthly average global solar radiation with overall RMSE of 0.383 MJ/m"2/day, MAE of 0.295 MJ/m"2/day, MAPE of 2% and R"2 of 0.967. - Highlights: • Distribution of clearnes index is proposed for prediction of global solar radiation. • The clearness index is obtained from the past data of global solar radiation. • The parameters of distribution that best fit the clearness index are determined. • Solar radiation is predicted from the clearness index using inverse transformation. • The method is effective in predicting the monthly average global solar radiation.

An Approach to Predict Debris Flow Average Velocity

Directory of Open Access Journals (Sweden)

Chen Cao

2017-03-01

Full Text Available Debris flow is one of the major threats for the sustainability of environmental and social development. The velocity directly determines the impact on the vulnerability. This study focuses on an approach using radial basis function (RBF neural network and gravitational search algorithm (GSA for predicting debris flow velocity. A total of 50 debris flow events were investigated in the Jiangjia gully. These data were used for building the GSA-based RBF approach (GSA-RBF. Eighty percent (40 groups of the measured data were selected randomly as the training database. The other 20% (10 groups of data were used as testing data. Finally, the approach was applied to predict six debris flow gullies velocities in the Wudongde Dam site area, where environmental conditions were similar to the Jiangjia gully. The modified Dongchuan empirical equation and the pulled particle analysis of debris flow (PPA approach were used for comparison and validation. The results showed that: (i the GSA-RBF predicted debris flow velocity values are very close to the measured values, which performs better than those using RBF neural network alone; (ii the GSA-RBF results and the MDEE results are similar in the Jiangjia gully debris flow velocities prediction, and GSA-RBF performs better; (iii in the study area, the GSA-RBF results are validated reliable; and (iv we could consider more variables in predicting the debris flow velocity by using GSA-RBF on the basis of measured data in other areas, which is more applicable. Because the GSA-RBF approach was more accurate, both the numerical simulation and the empirical equation can be taken into consideration for constructing debris flow mitigation works. They could be complementary and verified for each other.

Congestive index of portal vein

International Nuclear Information System (INIS)

Kim, Won Ho; Kim, H. K.; Lee, S. C.; Han, S. H.; Han, K. H.; Chung, J. B.; Choi, H. J.

1989-01-01

In patients with portal hypertension, the blood flow volume is maintained despite decreased blood flow velocity due to enlargement of the vascular cross sectional area. Thus, the 'congestion index' of the portal vein, which is the ratio between the cross sectional area (cm2) and the blood flow velocity (cm/sec) determined by a Doppler ultrasonography, may be a sensitive index by which to assess portal hypertension. We performed Doppler ultrasonography on 24 normal subjects, 14 patients with biopsy proved chronic active hepatitis and 55 patients with liver cirrhosis in order to assess the diagnostic value of the congestion index. The cross sectional area of the portal vein was significantly enlarged and the mean blood flow velocity was significantly reduced in patients with liver cirrhosis compared with controls. However, the blood flow volume was no difference. The congestion index of the portal vein was significantly increased in patients with liver cirrhosis (0.113+0.035) compared with patients with chronic active hepatitis(0.078+0.029) (p<0.001) and controls (0.053+0.016) (p<0.001). The sensitivity, specificity and predictability of the congestion index for detection of patients with the cirrhosis of the liver were 76.4%, 100% and 100% respectively, when the normal range was set at mean+2SD. The results suggest that the congestion index of the portal vein may pla a significant role in diagnosis of portal hypertensive patients

Patient state index and cerebral blood flow changes during shoulder arthroscopy in beach chair position.

Science.gov (United States)

Buget, Mehmet Ilke; Atalar, Ata Can; Edipoglu, Ipek Saadet; Sungur, Zerrin; Sivrikoz, Nukhet; Karadeniz, Meltem; Saka, Esra; Kucukay, Suleyman; Senturk, Mert N

2016-01-01

The aim of the study were to demonstrate the possible hemodynamic changes and cerebral blood flow alterations in patients who were positioned from supine to beach chair position; and to detect if the position change causes any cortical activity alteration as measured by the 4-channeled electroencephalography monitor. 35 patients were included. Before the induction, mean arterial pressure and patient state index values were recorded (T0). After the intubation, doppler-ultrasonography of the patients' internal carotid and vertebral arteries were evaluated to acquire cerebral blood flow values from the formula. In supine position, mean arterial pressure, patient state index and cerebral blood flow values were recorded (T1) and the patient was positioned to beach chair position. After 5min all measurements were repeated (T2). Measurements of patient state index and mean arterial pressure were repeated after 20 (T3), and 40 (T4)min. There was a significant decrease between T0 and T1 in heart rate (80.5±11.6 vs. 75.9±14.4beats/min), MAP (105.8±21.9 vs. 78.9±18.4mmHg) and PSI (88.5±8.3 vs. 30.3±9.7) (all pstate index values (T1-T4) showed no significant change; however, comparing only T1 and T2 resulted in a statically significant decrease in patient state index. There was a significant decrease in cerebral blood flow after beach chair position. Beach chair position was associated with a decrease in cerebral blood flow and patient state index values. Patient state index was affected by the gravitational change of the cerebral blood flow; however, both factors were not directly correlated to each other. Moreover, the decrease in patient state index value was transient and returned to normal values within 20min. Copyright © 2015 Sociedade Brasileira de Anestesiologia. Published by Elsevier Editora Ltda. All rights reserved.

[Patient state index and cerebral blood flow changes during shoulder arthroscopy in beach chair position].

Science.gov (United States)

Buget, Mehmet Ilke; Atalar, Ata Can; Edipoglu, Ipek Saadet; Sungur, Zerrin; Sivrikoz, Nukhet; Karadeniz, Meltem; Saka, Esra; Kucukay, Suleyman; Senturk, Mert N

2016-01-01

The aim of the study were to demonstrate the possible hemodynamic changes and cerebral blood flow alterations in patients who were positioned from supine to beach chair position; and to detect if the position change causes any cortical activity alteration as measured by the 4-channeled electroencephalography monitor. 35 patients were included. Before the induction, mean arterial pressure and patient state index values were recorded (T0). After the intubation, doppler-ultrasonography of the patients' internal carotid and vertebral arteries were evaluated to acquire cerebral blood flow values from the formula. In supine position, mean arterial pressure, patient state index and cerebral blood flow values were recorded (T1) and the patient was positioned to beach chair position. After 5min all measurements were repeated (T2). Measurements of patient state index and mean arterial pressure were repeated after 20 (T3), and 40 (T4)min. There was a significant decrease between T0 and T1 in heart rate (80.5±11.6 vs. 75.9±14.4beats/min), MAP (105.8±21.9 vs. 78.9±18.4mmHg) and PSI (88.5±8.3 vs. 30.3±9.7) (all pstate index values (T1-T4) showed no significant change; however, comparing only T1 and T2 resulted in a statically significant decrease in patient state index. There was a significant decrease in cerebral blood flow after beach chair position. Beach chair position was associated with a decrease in cerebral blood flow and patient state index values. Patient state index was affected by the gravitational change of the cerebral blood flow; however, both factors were not directly correlated to each other. Moreover, the decrease in patient state index value was transient and returned to normal values within 20min. Copyright © 2015 Sociedade Brasileira de Anestesiologia. Publicado por Elsevier Editora Ltda. All rights reserved.

Development of Next Generation Multiphase Pipe Flow Prediction Tools

Energy Technology Data Exchange (ETDEWEB)

Tulsa Fluid Flow

2008-08-31

The developments of fields in deep waters (5000 ft and more) is a common occurrence. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas-oil-and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of the hydrocarbon recovery from design to operation. The recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is very crucial to any multiphase separation technique that is employed either at topside, seabed or bottom-hole to know inlet conditions such as the flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. The overall objective was to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict the flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, fluid properties and flow rates). The project was conducted in two periods. In Period 1 (four years), gas-oil-water flow in pipes were investigated to understand the fundamental physical mechanisms describing the interaction between the gas-oil-water phases under flowing conditions, and a unified model was developed utilizing a novel modeling approach. A gas-oil-water pipe flow database including field and laboratory data was formed in Period 2 (one year). The database was utilized in model performance demonstration. Period 1 primarily consisted of the development of a unified model and software to predict the gas-oil-water flow, and experimental studies of the gas-oil-water project, including flow behavior description and

Accurate Multisteps Traffic Flow Prediction Based on SVM

Directory of Open Access Journals (Sweden)

Zhang Mingheng

2013-01-01

Full Text Available Accurate traffic flow prediction is prerequisite and important for realizing intelligent traffic control and guidance, and it is also the objective requirement for intelligent traffic management. Due to the strong nonlinear, stochastic, time-varying characteristics of urban transport system, artificial intelligence methods such as support vector machine (SVM are now receiving more and more attentions in this research field. Compared with the traditional single-step prediction method, the multisteps prediction has the ability that can predict the traffic state trends over a certain period in the future. From the perspective of dynamic decision, it is far important than the current traffic condition obtained. Thus, in this paper, an accurate multi-steps traffic flow prediction model based on SVM was proposed. In which, the input vectors were comprised of actual traffic volume and four different types of input vectors were compared to verify their prediction performance with each other. Finally, the model was verified with actual data in the empirical analysis phase and the test results showed that the proposed SVM model had a good ability for traffic flow prediction and the SVM-HPT model outperformed the other three models for prediction.

Mean streamline analysis for performance prediction of cross-flow fans

International Nuclear Information System (INIS)

Kim, Jae Won; Oh, Hyoung Woo

2004-01-01

This paper presents the mean streamline analysis using the empirical loss correlations for performance prediction of cross-flow fans. Comparison of overall performance predictions with test data of a cross-flow fan system with a simplified vortex wall scroll casing and with the published experimental characteristics for a cross-flow fan has been carried out to demonstrate the accuracy of the proposed method. Predicted performance curves by the present mean streamline analysis agree well with experimental data for two different cross-flow fans over the normal operating conditions. The prediction method presented herein can be used efficiently as a tool for the preliminary design and performance analysis of general-purpose cross-flow fans

Predictability of Returns and Cash Flows

OpenAIRE

Ralph S.J. Koijen; Stijn Van Nieuwerburgh

2010-01-01

We review the literature on return and cash-flow growth predictability from the perspective of the present-value identity. We focus predominantly on recent work. Our emphasis is on U.S. aggregate stock return predictability, but we also discuss evidence from other asset classes and countries.

Predicting Information Flows in Network Traffic.

Science.gov (United States)

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)

Development of Next Generation Multiphase Pipe Flow Prediction Tools

Energy Technology Data Exchange (ETDEWEB)

Cem Sarica; Holden Zhang

2006-05-31

The developments of oil and gas fields in deep waters (5000 ft and more) will become more common in the future. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas, oil and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of hydrocarbon recovery from design to operation. Recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications, including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is crucial for any multiphase separation technique, either at topside, seabed or bottom-hole, to know inlet conditions such as flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. Therefore, the development of a new generation of multiphase flow predictive tools is needed. The overall objective of the proposed study is to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, fluid properties and flow rates). In the current multiphase modeling approach, flow pattern and flow behavior (pressure gradient and phase fractions) prediction modeling are separated. Thus, different models based on different physics are employed, causing inaccuracies and discontinuities. Moreover, oil and water are treated as a pseudo single phase, ignoring the distinct characteristics of both oil and water, and often resulting in inaccurate design that leads to operational problems. In this study, a new model is being developed through a theoretical and experimental study employing a revolutionary approach. The

Pulmonary venous flow index as a predictor of pulmonary vascular resistance variability in congenital heart disease with increased pulmonary flow: a comparative study before and after oxygen inhalation.

Science.gov (United States)

Rivera, Ivan Romero; Mendonça, Maria Alayde; Andrade, José Lázaro; Moises, Valdir; Campos, Orlando; Silva, Célia Camelo; Carvalho, Antonio Carlos

2013-09-01

There is no definitive and reliable echocardiographic method for estimating the pulmonary vascular resistance (PVR) to differentiate persistent vascular disease from dynamic pulmonary hypertension. The aim of this study was to analyze the relationship between the pulmonary venous blood flow velocity-time integral (VTIpv) and PVR. Eighteen patients (10 females; 4 months to 22 years of age) with congenital heart disease and left to right shunt were studied. They underwent complete cardiac catheterization, including measurements of the PVR and Qp:Qs ratio, before and after 100% oxygen inhalation. Simultaneous left inferior pulmonary venous flow VTIpv was obtained by Doppler echocardiography. The PVR decreased significantly from 5.0 ± 2.6 W to 2.8 ± 2.2 W (P = 0.0001) with a significant increase in the Qp:Qs ratio, from 3.2 ± 1.4 to 4.9 ± 2.4 (P = 0.0008), and the VTIpv increased significantly from 22.6 ± 4.7 cm to 28.1 ± 6.2 cm (P = 0.0002) after 100% oxygen inhalation. VTIpv correlated well with the PVR and Qp:Qs ratio (r = -0.74 and 0.72, respectively). Diagnostic indexes indicated a sensitivity of 86%, specificity of 75%, accuracy of 83%, a positive predictive value of 92% and a negative predictive value of 60%. The VTIpv correlated well with the PVR. The measurement of this index before and after oxygen inhalation may become a useful noninvasive test for differentiating persistent vascular disease from dynamic and flow-related pulmonary hypertension. © 2013, Wiley Periodicals, Inc.

Sludge pipe flow pressure drop prediction using composite power ...

African Journals Online (AJOL)

Sludge pipe flow pressure drop prediction using composite power-law friction ... Water SA. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue ... When predicting pressure gradients for the flow of sludges in pipes, the ...

Effectively Indexing Uncertain Moving Objects for Predictive Queries

DEFF Research Database (Denmark)

Zhang, Meihui; Chen, Su; Jensen, Christian Søndergaard

2009-01-01

in more complex and stochastic ways. This paper investigates the possibility of a marriage between moving-object indexing and probabilistic object modelling. Given the distributions of the current locations and velocities of moving objects, we devise an efficient inference method for the prediction...

The Economic Value of Predicting Stock Index Returns and Volatility

NARCIS (Netherlands)

Marquering, W.; Verbeek, M.J.C.M.

2000-01-01

In this paper, we analyze the economic value of predicting index returns as well as volatility. On the basis of fairly simple linear models, estimated recursively, we produce genuine out-of-sample forecasts for the return on the S&P 500 index and its volatility. Using monthly data from 1954-1998, we

Construction of prediction intervals for Palmer Drought Severity Index using bootstrap

Science.gov (United States)

Beyaztas, Ufuk; Bickici Arikan, Bugrayhan; Beyaztas, Beste Hamiye; Kahya, Ercan

2018-04-01

In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations. The effects of North Atlantic and Arctic Oscillation indexes on the constructed prediction intervals are also examined. Performance of the proposed approach is evaluated for the Palmer Drought Severity Index (PDSI) obtained from Konya closed basin located in Central Anatolia, Turkey. The finite sample properties of the proposed method are further illustrated by an extensive simulation study. Our results revealed that the proposed approach is capable of producing valid prediction intervals for future PDSI values.

PASSENGER FLOWS PREDICTION IN MAJOR TRANSPORTATION HUBS

Directory of Open Access Journals (Sweden)

O. O. Ozerova

2013-11-01

Full Text Available Purpose. An effective organization of passenger traffic, due to the reliability prediction of traffic flow in passenger transport hubs. In order to determine the parameters of prospective passenger transport areas it is essential to analyze the impact of various factors and determine the most influential ones. Methodology. The article presents the method of paired linear correlation for a more influential factors on passengers in intercity and commuter and possible use in predicting the linear regression equations. Passenger transport vessel areas and branches of industry are interconnected and are in the ratio of passengers and production. Findings. It is found that the coefficient of correlation is in complex dependence on the duration of the period of retrospective analysis. Evaluation of reliability correlation coefficients and coefficients of predictive models led to the conclusion that the population gives the most accurate prediction of passenger flows, providing account of changes in Ukraine during the period of transformation. Originality. Equations of dependence on the impact of macroeconomic indicators were obtained and the evaluation of the reliability results was received. Practical value. The results of analysis and calculations will make short-term forecasting of traffic flow.

Advanced 2-dimensional quantitative coronary angiographic analysis for prediction of fractional flow reserve in intermediate coronary stenoses.

Science.gov (United States)

Opolski, Maksymilian P; Pregowski, Jerzy; Kruk, Mariusz; Kepka, Cezary; Staruch, Adam D; Witkowski, Adam

2014-07-01

The widespread clinical application of coronary computed tomography angiography (CCTA) has resulted in increased referral patterns of patients with intermediate coronary stenoses to invasive coronary angiography. We evaluated the application of advanced quantitative coronary angiography (A-QCA) for predicting fractional flow reserve (FFR) in intermediate coronary lesions detected on CCTA. Fifty-six patients with 66 single intermediate coronary lesions (≥ 50% to 80% stenosis) on CCTA prospectively underwent coronary angiography and FFR. A-QCA including calculation of the Poiseuille-based index defined as the ratio of lesion length to the fourth power of the minimal lumen diameter (MLD) was performed. Significant stenosis was defined as FFR ≤ 0.80. The mean FFR was 0.86 ± 0.09, and 18 lesions (27%) were functionally significant. FFR correlated with lesion length (R=-0.303, P=0.013), MLD (R=0.527, P44%, and >69%, respectively (maximum negative predictive value of 94% for MLA, maximum positive predictive value of 58% for diameter stenosis). The Poiseuille-based index was the most accurate (C statistic 0.86, sensitivity 100%, specificity 71%, positive predictive value 56%, and negative predictive value 100%) predictor of FFR ≤ 0.80, but showed the lowest interobserver agreement (intraclass correlation coefficient 0.37). A-QCA might be used to rule out significant ischemia in intermediate stenoses detected by CCTA. The diagnostic application of the Poiseuille-based angiographic index is precluded by its high interobserver variability.

Unified flow regime predictions at earth gravity and microgravity

International Nuclear Information System (INIS)

Crowley, C.J.

1990-01-01

This paper illustrates the mechanistic models developed to predict flow regime transitions at earth gravity for various pipe inclinations can be successfully applied to existing microgravity flow regime data from several experiments. There is a tendency in the literature for flow regime comparisons in several inclination ranges and at various gravity (acceleration) levels to be treated by separate models, resulting in a proliferation of models for the prediction of flow regimes. One set of mechanistic models can be used to model the transitions between stratified, slug, bubbly, and annular flow regimes in pipes for all acceleration vectors and magnitudes from earth gravity to microgravity

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

Directory of Open Access Journals (Sweden)

Mingyue Qiu

Full Text Available In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA. We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

Science.gov (United States)

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Climate Prediction Center (CPC) Madden-Julian Oscillation (MJO) Index

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Prediction Center (CPC) Madden Julian Oscillation index (MJO) is a dataset that allows evaluation of the strength and phase of the MJO during the dataset...

On the prediction of turbulent secondary flows

Science.gov (United States)

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.

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

Science.gov (United States)

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

2005-01-01

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

Flow-covariate prediction of stream pesticide concentrations.

Science.gov (United States)

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.

Predictive Index The Incidence Of Tuberculosis Children In South Kalimantan Province

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Bahrul Ilmi

2015-08-01

Full Text Available The research objective to formulate predictive index of Tuberculosis Children in South Kalimantan province. Research methods combined mixed methods with a combination of research model Sequential Exploratory Design qualitative approach to support quantitative and centered on quantitative Sugiono 2012 case control design. The number of qualitative sample was 16 respondents to interviews and 48 respondents for FGD. The number of quantitative research sample was 216 consisted of 62 cases and 154 controls. Qualitative sampling by purposive sampling and quantitative Multi-stage Cluster random sampling on 3 stages. The analysis technique used is descriptive qualitative and Confirmatory Factor Analysis Confirmatory Factor Analysis measure the latent of variables by using path analysis path analysis with the program Linear Structural Relationships LISREL. The results showed a positive effect on the socio-cultural environment and significantly associated with the incidence of Tuberculosis Children. While the physical environment of the house positively and significantly with biological environments and the incidence of Tuberculosis Children and immunization and nutrition status of children positively and significantly to the incidence of Tuberculosis of the Child as well as to the biological environment positive and significant effect on the incidence of TB Children. Formulation Predictive Index of Tuberculosis Children in South Kalimantan province. is index 019 Physical Environment Home 044 053 Biological Environment Social Environment Culture 019 Status Immunization and Child Nutrition. The results of all the R-square value indicates that all of the R-square values 0.5. This means that a predictive model of TB Kids index has met the required Goodness of Fit. New findings from research of this dissertation are 1. Research Variable of social networks social support and collective efficacy were associated with the incidence of Tuberculosis Children. 2

Improving urban wind flow predictions through data assimilation

Science.gov (United States)

Sousa, Jorge; Gorle, Catherine

2017-11-01

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

Matching-index-of-refraction of transparent 3D printing models for flow visualization

International Nuclear Information System (INIS)

Song, Min Seop; Choi, Hae Yoon; Seong, Jee Hyun; Kim, Eung Soo

2015-01-01

Matching-index-of-refraction (MIR) has been used for obtaining high-quality flow visualization data for the fundamental nuclear thermal-hydraulic researches. By this method, distortions of the optical measurements such as PIV and LDV have been successfully minimized using various combinations of the model materials and the working fluids. This study investigated a novel 3D printing technology for manufacturing models and an oil-based working fluid for matching the refractive indices. Transparent test samples were fabricated by various rapid prototyping methods including selective layer sintering (SLS), stereolithography (SLA), and vacuum casting. As a result, the SLA direct 3D printing was evaluated to be the most suitable for flow visualization considering manufacturability, transparency, and refractive index. In order to match the refractive indices of the 3D printing models, a working fluid was developed based on the mixture of herb essential oils, which exhibit high refractive index, high transparency, high density, low viscosity, low toxicity, and low price. The refractive index and viscosity of the working fluid range 1.453–1.555 and 2.37–6.94 cP, respectively. In order to validate the MIR method, a simple test using a twisted prism made by the SLA technique and the oil mixture (anise and light mineral oil) was conducted. The experimental results show that the MIR can be successfully achieved at the refractive index of 1.51, and the proposed MIR method is expected to be widely used for flow visualization studies and CFD validation for the nuclear thermal-hydraulic researches

Matching-index-of-refraction of transparent 3D printing models for flow visualization

Energy Technology Data Exchange (ETDEWEB)

Song, Min Seop; Choi, Hae Yoon; Seong, Jee Hyun; Kim, Eung Soo, E-mail: kes7741@snu.ac.kr

2015-04-01

Matching-index-of-refraction (MIR) has been used for obtaining high-quality flow visualization data for the fundamental nuclear thermal-hydraulic researches. By this method, distortions of the optical measurements such as PIV and LDV have been successfully minimized using various combinations of the model materials and the working fluids. This study investigated a novel 3D printing technology for manufacturing models and an oil-based working fluid for matching the refractive indices. Transparent test samples were fabricated by various rapid prototyping methods including selective layer sintering (SLS), stereolithography (SLA), and vacuum casting. As a result, the SLA direct 3D printing was evaluated to be the most suitable for flow visualization considering manufacturability, transparency, and refractive index. In order to match the refractive indices of the 3D printing models, a working fluid was developed based on the mixture of herb essential oils, which exhibit high refractive index, high transparency, high density, low viscosity, low toxicity, and low price. The refractive index and viscosity of the working fluid range 1.453–1.555 and 2.37–6.94 cP, respectively. In order to validate the MIR method, a simple test using a twisted prism made by the SLA technique and the oil mixture (anise and light mineral oil) was conducted. The experimental results show that the MIR can be successfully achieved at the refractive index of 1.51, and the proposed MIR method is expected to be widely used for flow visualization studies and CFD validation for the nuclear thermal-hydraulic researches.

A Bimodel Algorithm with Data-Divider to Predict Stock Index

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Zhaoyue Wang

2018-01-01

Full Text Available There is not yet reliable software for stock prediction, because most experts of this area have been trying to predict an exact stock index. Considering that the fluctuation of a stock index usually is no more than 1% in a day, the error between the forecasted and the actual values should be no more than 0.5%. It is too difficult to realize. However, forecasting whether a stock index will rise or fall does not need to be so exact a numerical value. A few scholars noted the fact, but their systems do not yet work very well because different periods of a stock have different inherent laws. So, we should not depend on a single model or a set of parameters to solve the problem. In this paper, we developed a data-divider to divide a set of historical stock data into two parts according to rising period and falling period, training, respectively, two neural networks optimized by a GA. Above all, the data-divider enables us to avoid the most difficult problem, the effect of unexpected news, which could hardly be predicted. Experiments show that the accuracy of our method increases 20% compared to those of traditional methods.

The c-index is not proper for the evaluation of $t$-year predicted risks.

Science.gov (United States)

Blanche, Paul; Kattan, Michael W; Gerds, Thomas A

2018-02-16

We show that the widely used concordance index for time to event outcome is not proper when interest is in predicting a $t$-year risk of an event, for example 10-year mortality. In the situation with a fixed prediction horizon, the concordance index can be higher for a misspecified model than for a correctly specified model. Impropriety happens because the concordance index assesses the order of the event times and not the order of the event status at the prediction horizon. The time-dependent area under the receiver operating characteristic curve does not have this problem and is proper in this context.

A pilot study of the relationship between Doppler-estimated carotid and brachial artery flow and cardiac index.

Science.gov (United States)

Weber, U; Glassford, N J; Eastwood, G M; Bellomo, R; Hilton, A K

2015-10-01

We measured carotid and brachial artery blood flow by Doppler ultrasound in 11 human volunteers, and related these to cardiac index and to each other. The median (IQR [range]) carotid arterial blood flow was 0.334 (0.223-0.381 [0.052-0.563]) l.min(-1) on the right and 0.315 (0.223-0.369 [0.061-0.690]) l.min(-1) on the left. The brachial arterial blood flow was 0.049 (0.033-0.062 [0.015-0.204]) l.min(-1) on the right and 0.039 (0.027-0.054 [0.011-0.116]) on the left. Cardiac index was 3.2 (2.8-3.5 [1.9-5.4]) l.min(-1) .m(-2) . There was a moderate to good correlation between right-and left-sided flows (brachial: ρ = 0.45; carotid: ρ = 0.567). Brachial and carotid flow had no or a negative correlation with cardiac index (right brachial: ρ = -0.145, left brachial: ρ = -0.349; right carotid: ρ = -0.376, left carotid: ρ = -0.285). In contrast to some previous studies, we found that Doppler-estimated peripheral arterial blood flows only show a weak correlation with cardiac index and cannot be used to provide non-invasive estimates of cardiac index in man. © 2015 The Association of Anaesthetists of Great Britain and Ireland.

Flow Simulation and Performance Prediction of Centrifugal Pumps ...

African Journals Online (AJOL)

With the aid of computational fluid dynamics, the complex internal flows in water pump impellers can be well predicted, thus facilitating the product development process of pumps. In this paper a commercial CFD code was used to solve the governing equations of the flow field. A 2-D simulation of turbulent fluid flow is ...

Traffic Flow Prediction Using MI Algorithm and Considering Noisy and Data Loss Conditions: An Application to Minnesota Traffic Flow Prediction

Directory of Open Access Journals (Sweden)

Seyed Hadi Hosseini

2014-10-01

Full Text Available Traffic flow forecasting is useful for controlling traffic flow, traffic lights, and travel times. This study uses a multi-layer perceptron neural network and the mutual information (MI technique to forecast traffic flow and compares the prediction results with conventional traffic flow forecasting methods. The MI method is used to calculate the interdependency of historical traffic data and future traffic flow. In numerical case studies, the proposed traffic flow forecasting method was tested against data loss, changes in weather conditions, traffic congestion, and accidents. The outcomes were highly acceptable for all cases and showed the robustness of the proposed flow forecasting method.

Prediction of melanoma metastasis by the Shields index based on lymphatic vessel density

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Metcalfe Chris

2010-05-01

Full Text Available Abstract Background Melanoma usually presents as an initial skin lesion without evidence of metastasis. A significant proportion of patients develop subsequent local, regional or distant metastasis, sometimes many years after the initial lesion was removed. The current most effective staging method to identify early regional metastasis is sentinel lymph node biopsy (SLNB, which is invasive, not without morbidity and, while improving staging, may not improve overall survival. Lymphatic density, Breslow's thickness and the presence or absence of lymphatic invasion combined has been proposed to be a prognostic index of metastasis, by Shields et al in a patient group. Methods Here we undertook a retrospective analysis of 102 malignant melanomas from patients with more than five years follow-up to evaluate the Shields' index and compare with existing indicators. Results The Shields' index accurately predicted outcome in 90% of patients with metastases and 84% without metastases. For these, the Shields index was more predictive than thickness or lymphatic density. Alternate lymphatic measurement (hot spot analysis was also effective when combined into the Shields index in a cohort of 24 patients. Conclusions These results show the Shields index, a non-invasive analysis based on immunohistochemistry of lymphatics surrounding primary lesions that can accurately predict outcome, is a simple, useful prognostic tool in malignant melanoma.

Prediction of groundwater flowing well zone at An-Najif Province, central Iraq using evidential belief functions model and GIS.

Science.gov (United States)

Al-Abadi, Alaa M; Pradhan, Biswajeet; Shahid, Shamsuddin

2015-10-01

The objective of this study is to delineate groundwater flowing well zone potential in An-Najif Province of Iraq in a data-driven evidential belief function model developed in a geographical information system (GIS) environment. An inventory map of 68 groundwater flowing wells was prepared through field survey. Seventy percent or 43 wells were used for training the evidential belief functions model and the reset 30 % or 19 wells were used for validation of the model. Seven groundwater conditioning factors mostly derived from RS were used, namely elevation, slope angle, curvature, topographic wetness index, stream power index, lithological units, and distance to the Euphrates River in this study. The relationship between training flowing well locations and the conditioning factors were investigated using evidential belief functions technique in a GIS environment. The integrated belief values were classified into five categories using natural break classification scheme to predict spatial zoning of groundwater flowing well, namely very low (0.17-0.34), low (0.34-0.46), moderate (0.46-0.58), high (0.58-0.80), and very high (0.80-0.99). The results show that very low and low zones cover 72 % (19,282 km(2)) of the study area mostly clustered in the central part, the moderate zone concentrated in the west part covers 13 % (3481 km(2)), and the high and very high zones extended over the northern part cover 15 % (3977 km(2)) of the study area. The vast spatial extension of very low and low zones indicates that groundwater flowing wells potential in the study area is low. The performance of the evidential belief functions spatial model was validated using the receiver operating characteristic curve. A success rate of 0.95 and a prediction rate of 0.94 were estimated from the area under relative operating characteristics curves, which indicate that the developed model has excellent capability to predict groundwater flowing well zones. The produced map of groundwater

Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN Technique

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Awatif Soaded Alsaqqar

2016-06-01

Full Text Available In this research an Artificial Neural Network (ANN technique was applied for the prediction of Ryznar Index (RI of the flowing water from WTPs in Al-Karakh side (left side in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3 have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respectively. For Al-Dora WTP, ANN 3 model could be used as R was 92.8%.

Energy index decomposition methodology at the plant level

Science.gov (United States)

Kumphai, Wisit

Scope and method of study. The dissertation explores the use of a high level energy intensity index as a facility-level energy performance monitoring indicator with a goal of developing a methodology for an economically based energy performance monitoring system that incorporates production information. The performance measure closely monitors energy usage, production quantity, and product mix and determines the production efficiency as a part of an ongoing process that would enable facility managers to keep track of and, in the future, be able to predict when to perform a recommissioning process. The study focuses on the use of the index decomposition methodology and explored several high level (industry, sector, and country levels) energy utilization indexes, namely, Additive Log Mean Divisia, Multiplicative Log Mean Divisia, and Additive Refined Laspeyres. One level of index decomposition is performed. The indexes are decomposed into Intensity and Product mix effects. These indexes are tested on a flow shop brick manufacturing plant model in three different climates in the United States. The indexes obtained are analyzed by fitting an ARIMA model and testing for dependency between the two decomposed indexes. Findings and conclusions. The results concluded that the Additive Refined Laspeyres index decomposition methodology is suitable to use on a flow shop, non air conditioned production environment as an energy performance monitoring indicator. It is likely that this research can be further expanded in to predicting when to perform a recommissioning process.

Amniotic fluid index predicts the relief of variable decelerations after amnioinfusion bolus.

Science.gov (United States)

Spong, C Y; McKindsey, F; Ross, M G

1996-10-01

Our purpose was to determine whether intrapartum amniotic fluid index before amnioinfusion can be used to predict response to therapeutic amnioinfusion. Intrapartum patients (n = 85) with repetitive variable decelerations in fetal heart rate that necessitated amnioinfusion (10 ml/min for 60 minutes) underwent determination of amniotic fluid index before and after bolus amnioinfusion. The fetal heart tracing was scored (scorer blinded to amniotic fluid index values) for number and characteristics of variable decelerations before and 1 hour after initiation of amnioinfusion. The amnioinfusion was considered successful if it resulted in a decrease of > or = 50% in total number of variable decelerations or a decrease of > or = 50% in the rate of atypical or severe variable decelerations after administration of the bolus. Spontaneous vaginal births before completion of administration of the bolus (n = 18) were excluded from analysis. The probability of success of amnioinfusion in relation to amniotic fluid index was analyzed with the chi(2) test for progressive sequence. The mean amniotic fluid index before amnioinfusion was 6.2 +/- 3.3 cm. An amniotic fluid index of amnioinfusion decreased with increasing amniotic fluid index before amnioinfusion (76% [16/21] when initial amniotic fluid index was 0 to 4 cm, 63% [17/27] when initial amniotic fluid index was 4 to 8 cm, 44% [7/16] when initial amniotic fluid index was 8 to 12 cm, and 33% [1/3] when initial amniotic fluid index was > 12 cm, p = 0.03). The incidence of nuchal cords or true umbilical cord knots increased in relation to amniotic fluid index before amnioinfusion. Amniotic fluid index before amnioinfusion can be used to predict the success of amnioinfusion for relief of variable decelerations in fetal heart rate. Failure of amnioinfusion at a high amniotic fluid index before amnioinfusion may be explained by the increased prevalence of nuchal cords or true knots in the umbilical cord.

Prediction of Massive Transfusion in Trauma Patients with Shock Index, Modified Shock Index, and Age Shock Index

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Cheng-Shyuan Rau

2016-07-01

Full Text Available Objectives: The shock index (SI and its derivations, the modified shock index (MSI and the age shock index (Age SI, have been used to identify trauma patients with unstable hemodynamic status. The aim of this study was to evaluate their use in predicting the requirement for massive transfusion (MT in trauma patients upon arrival at the hospital. Participants: A patient receiving transfusion of 10 or more units of packed red blood cells or whole blood within 24 h of arrival at the emergency department was defined as having received MT. Detailed data of 2490 patients hospitalized for trauma between 1 January 2009, and 31 December 2014, who had received blood transfusion within 24 h of arrival at the emergency department, were retrieved from the Trauma Registry System of a level I regional trauma center. These included 99 patients who received MT and 2391 patients who did not. Patients with incomplete registration data were excluded from the study. The two-sided Fisher exact test or Pearson chi-square test were used to compare categorical data. The unpaired Student t-test was used to analyze normally distributed continuous data, and the Mann-Whitney U-test was used to compare non-normally distributed data. Parameters including systolic blood pressure (SBP, heart rate (HR, hemoglobin level (Hb, base deficit (BD, SI, MSI, and Age SI that could provide cut-off points for predicting the patients’ probability of receiving MT were identified by the development of specific receiver operating characteristic (ROC curves. High accuracy was defined as an area under the curve (AUC of more than 0.9, moderate accuracy was defined as an AUC between 0.9 and 0.7, and low accuracy was defined as an AUC less than 0.7. Results: In addition to a significantly higher Injury Severity Score (ISS and worse outcome, the patients requiring MT presented with a significantly higher HR and lower SBP, Hb, and BD, as well as significantly increased SI, MSI, and Age SI. Among

[Evaluation of thermal comfort in a student population: predictive value of an integrated index (Fanger's predicted mean value].

Science.gov (United States)

Catenacci, G; Terzi, R; Marcaletti, G; Tringali, S

1989-01-01

Practical applications and predictive values of a thermal comfort index (Fanger's PRV) were verified on a sample school population (1236 subjects) by studying the relationships between thermal sensations (subjective analysis), determined by means of an individual questionnaire, and the values of thermal comfort index (objective analysis) obtained by calculating the PMV index individually in the subjects under study. In homogeneous conditions of metabolic expenditure rate and thermal impedence from clothing, significant differences were found between the two kinds of analyses. At 22 degrees C mean radiant and operative temperature, the PMV values averaged 0 and the percentage of subjects who experienced thermal comfort did not exceed 60%. The high level of subjects who were dissatisfied with their environmental thermal conditions confirms the doubts regarding the use of the PMV index as a predictive indicator of thermal comfort, especially considering that the negative answers were not homogeneous nor attributable to the small thermal fluctuations (less than 0.5 degree C) measured in the classrooms.

AIR POLLUITON INDEX PREDICTION USING MULTIPLE NEURAL NETWORKS

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Zainal Ahmad

2017-05-01

Full Text Available Air quality monitoring and forecasting tools are necessary for the purpose of taking precautionary measures against air pollution, such as reducing the effect of a predicted air pollution peak on the surrounding population and ecosystem. In this study a single Feed-forward Artificial Neural Network (FANN is shown to be able to predict the Air Pollution Index (API with a Mean Squared Error (MSE and coefficient determination, R2, of 0.1856 and 0.7950 respectively. However, due to the non-robust nature of single FANN, a selective combination of Multiple Neural Networks (MNN is introduced using backward elimination and a forward selection method. The results show that both selective combination methods can improve the robustness and performance of the API prediction with the MSE and R2 of 0.1614 and 0.8210 respectively. This clearly shows that it is possible to reduce the number of networks combined in MNN for API prediction, without losses of any information in terms of the performance of the final API prediction model.

Use of instantaneous streamflow measurements to improve regression estimates of index flow for the summer month of lowest streamflow in Michigan

Science.gov (United States)

Holtschlag, David J.

2011-01-01

In Michigan, index flow Q50 is a streamflow characteristic defined as the minimum of median flows for July, August, and September. The state of Michigan uses index flow estimates to help regulate large (greater than 100,000 gallons per day) water withdrawals to prevent adverse effects on characteristic fish populations. At sites where long-term streamgages are located, index flows are computed directly from continuous streamflow records as GageQ50. In an earlier study, a multiple-regression equation was developed to estimate index flows IndxQ50 at ungaged sites. The index equation explains about 94 percent of the variability of index flows at 147 (index) streamgages by use of six explanatory variables describing soil type, aquifer transmissivity, land cover, and precipitation characteristics. This report extends the results of the previous study, by use of Monte Carlo simulations, to evaluate alternative flow estimators, DiscQ50, IntgQ50, SiteQ50, and AugmQ50. The Monte Carlo simulations treated each of the available index streamgages, in turn, as a miscellaneous site where streamflow conditions are described by one or more instantaneous measurements of flow. In the simulations, instantaneous flows were approximated by daily mean flows at the corresponding site. All estimators use information that can be obtained from instantaneous flow measurements and contemporaneous daily mean flow data from nearby long-term streamgages. The efficacy of these estimators was evaluated over a set of measurement intensities in which the number of simulated instantaneous flow measurements ranged from 1 to 100 at a site. The discrete measurement estimator DiscQ50 is based on a simple linear regression developed between information on daily mean flows at five or more streamgages near the miscellaneous site and their corresponding GageQ50 index flows. The regression relation then was used to compute a DiscQ50 estimate at the miscellaneous site by use of the simulated instantaneous flow

Starch digestibility and predicted glycemic index of fried sweet potato cultivars

Directory of Open Access Journals (Sweden)

Amaka Odenigbo

2012-07-01

Full Text Available Background: Sweet potato (Ipomoea batatas L. is a very rich source of starch. There is increased interest in starch digestibility and the prevention and management of metabolic diseases.Objective: The aim of this study was to evaluate the levels of starch fractions and predicted glycemic index of different cultivars of sweet potato. Material and Method: French fries produced from five cultivars of sweet potato (‘Ginseng Red’, ‘Beauregard’, ‘White Travis’, ‘Georgia Jet clone #2010’ and ‘Georgia Jet’ were used. The level of total starch (TS, resistant starch (RS, digestible starch (DS, and starch digestion index starch digestion index in the samples were evaluated. In vitro starch hydrolysis at 30, 90, and 120 min were determined enzymatically for calculation of rapidly digestible starch (RDS, predicted glycemic index (pGI and slowly digestible starch (SDS respectively. Results: The RS content in all samples had an inversely significant correlation with pGI (-0.52; P<0.05 while RDS had positive and significant influence on both pGI (r=0.55; P<0.05 and SDI (r= 0.94; P<0.01. ‘White Travis’ and ‘Ginseng Red’ had higher levels of beneficial starch fractions (RS and SDS with low pGI and starch digestion Index (SDI, despite their higher TS content. Generally, all the cultivars had products with low to moderate GI values. Conclusion: The glycemic index of these food products highlights the health promoting characteristics of sweet potato cultivars.

Assessment of the de Hirsch Predictive Index Tests of Reading Failure.

Science.gov (United States)

Askov, Warren; And Others

The predictive validity and the general usability of a battery of 10 tests reported by de Hirsch, Jansky, and Langford, the de Hirsch Predictive Index Tests of reading failure, were examined. The de Hirsch battery was administered to 433 kindergarten children in six public schools. When the pupils entered first grade, the Metropolitan Readiness…

Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices.

Science.gov (United States)

Belfatto, Antonella; Vidal Urbinati, Ailyn M; Ciardo, Delia; Franchi, Dorella; Cattani, Federica; Lazzari, Roberta; Jereczek-Fossa, Barbara A; Orecchia, Roberto; Baroni, Guido; Cerveri, Pietro

2017-05-01

two presented poor correlations. The latter patients were the ones featuring the smallest tumor reduction throughout the treatment, typical of hypoxic conditions. Moreover, the average oxygenation value predicted by the model was close to the average vascularization-flow index (average difference: 7%). The results suggest that the modeled relation between tumor evolution and oxygen dynamics was reasonable enough to provide realistic oxygenation curves in five cases (correlation greater than 50%) out of seven. In case of nonresponsive tumors, the model failed in predicting the oxygenation trend while succeeded in reproducing the average oxygenation value according to the mean vascularization-flow index. Despite the need for deeper investigations, the outcomes of the present work support the hypothesis that a simple macroscale model of tumor response to radiotherapy is able to predict the tumor oxygenation. The possibility of an objective and quantitative validation on imaging data discloses the possibility to translate them as decision support tools in clinical practice and to move a step forward in the treatment personalization. © 2017 American Association of Physicists in Medicine.

Prediction of infarction and reperfusion in stroke by flow- and volume-weighted collateral signal in MR angiography.

Science.gov (United States)

Ernst, M; Forkert, N D; Brehmer, L; Thomalla, G; Siemonsen, S; Fiehler, J; Kemmling, A

2015-02-01

In proximal anterior circulation occlusive strokes, collateral flow is essential for good outcome. Collateralized vessel intensity in TOF- and contrast-enhanced MRA is variable due to different acquisition methods. Our purpose was to quantify collateral supply by using flow-weighted signal in TOF-MRA and blood volume-weighted signal in contrast-enhanced MRA to determine each predictive contribution to tissue infarction and reperfusion. Consecutively (2009-2013), 44 stroke patients with acute proximal anterior circulation occlusion met the inclusion criteria with TOF- and contrast-enhanced MRA and penumbral imaging. Collateralized vessels in the ischemic hemisphere were assessed by TOF- and contrast-enhanced MRA using 2 methods: 1) visual 3-point collateral scoring, and 2) collateral signal quantification by an arterial atlas-based collateral index. Collateral measures were tested by receiver operating characteristic curve and logistic regression against 2 imaging end points of tissue-outcome: final infarct volume and percentage of penumbra saved. Visual collateral scores on contrast-enhanced MRA but not TOF were significantly higher in patients with good outcome. Visual collateral scoring on contrast-enhanced MRA was the best rater-based discriminator for final infarct volume 50% (area under the curve, 0.67; P = .04). Atlas-based collateral index of contrast-enhanced MRA was the overall best independent discriminator for final infarct volume of collateral index combining the signal of TOF- and contrast-enhanced MRA was the overall best discriminator for effective reperfusion (percentage of penumbra saved >50%; area under the curve, 0.89; P collateral assessment, TOF- and contrast-enhanced MRA both contain predictive signal information for penumbral reperfusion. This could improve risk stratification in further studies. © 2015 by American Journal of Neuroradiology.

Prediction of pressure drop and CCFL breakdown in countercurrent two-phase flow

International Nuclear Information System (INIS)

Ostrogorsky, A.G.; Gay, R.R.; Lahey, R.T. Jr.

1983-01-01

A steady-state analytical has been developed to predict channel pressure drop as a function of inlet vapor flow rate and applied heat flux during conditions of countercurrent two-phase flow. The interfacial constitutive relations utilized are flow surface dependent and allow for the existence of either smooth or way liquid films. A computer code was developed to solve the analytical model. Predictions of Δp versus vapor flow rate were found to agree favorably with experimental data from adiabatic, air/water systems. In addition, the model was used to predict countercurrent flow conditions in heated channels characteristic of a BWR/4 nuclear reactor fuel assembly

Coronary flow reserve index corrected by exercise load using Tl-201 SPECT

International Nuclear Information System (INIS)

Kubota, Yasushi; Sugihara, Hiroki; Azuma, Akihiro

1990-01-01

For simple, non-invasive evaluation of coronary flow reserve during exercise, we investigated the coronary flow reserve index using the ratio of change of fractional distribution in the regional myocardium to oxygen demand. The subjects included 24 patients with effort angina pectoris and 11 normal volunteers. PTCA was peformed for 11 patients. Using the biological properties of Tl-201 single photon emission computed tomography (SPECT) was performed at submaximal exercise and at rest by two successive injections of Tl-201 within a short time interval (double dose method). The correlation between the fractional distribution in the myocardium (Δ-Fract) and the oxygen demand during exercise and at rest were evaluated. Δ-Fract correlated well with the rate of change of the pressure rate product (Δ-PRP), and Δ-Fract/Δ-PRP (CRI) was a good indicator of the coronary flow reserve index. CRI in the ischemic region correlated well with the percent area stenosis of the supplying coronary artery and improved with resolution of percent area stenosis of the target coronary artery after PTCA, but in some cases they were not above the normal range. CRI as obtained by exercise SPECT using the double dose method is useful for non-invasively estimating the coronary flow reserve during exercise, and it can be used for evaluating the effect before and after PTCA. (author)

The Renal Arterial Resistance Index Predicts Worsening Renal Function in Chronic Heart Failure Patients

Science.gov (United States)

Iacoviello, Massimo; Monitillo, Francesco; Leone, Marta; Citarelli, Gaetano; Doronzo, Annalisa; Antoncecchi, Valeria; Puzzovivo, Agata; Rizzo, Caterina; Lattarulo, Maria Silvia; Massari, Francesco; Caldarola, Pasquale; Ciccone, Marco Matteo

2016-01-01

Background/Aim The renal arterial resistance index (RRI) is a Doppler measure, which reflects abnormalities in the renal blood flow. The aim of this study was to verify the value of RRI as a predictor of worsening renal function (WRF) in a group of chronic heart failure (CHF) outpatients. Methods We enrolled 266 patients in stable clinical conditions and on conventional therapy. Peak systolic velocity and end diastolic velocity of a segmental renal artery were obtained by pulsed Doppler flow, and RRI was calculated. Creatinine serum levels were evaluated at baseline and at 1 year, and the changes were used to assess WRF occurrence. Results During follow-up, 34 (13%) patients showed WRF. RRI was associated with WRF at univariate (OR: 1.13; 95% CI: 1.07–1.20) as well as at a forward stepwise multivariate logistic regression analysis (OR: 1.09; 95% CI: 1.03–1.16; p = 0.005) including the other univariate predictors. Conclusions Quantification of arterial renal perfusion provides a new parameter that independently predicts the WRF in CHF outpatients. Its possible role in current clinical practice to better define the risk of cardiorenal syndrome progression is strengthened. PMID:27994601

Predicting bifurcation angle effect on blood flow in the microvasculature.

Science.gov (United States)

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

2016-11-01

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

Prediction of critical flow rates through power-operated relief valves

International Nuclear Information System (INIS)

Abdollahian, D.; Singh, A.

1983-01-01

Existing single-phase and two-phase critical flow models are used to predict the flow rates through the power-operated relief valves tested in the EPRI Safety and Relief Valve test program. For liquid upstream conditions, Homogeneous Equilibrium Model, Moody, Henry-Fauske and Burnell two-phase critical flow models are used for comparison with data. Under steam upstream conditions, the flow rates are predicted either by the single-phase isentropic equations or the Homogeneous Equilibrium Model, depending on the thermodynamic condition of the fluid at the choking plane. The results of the comparisons are used to specify discharge coefficients for different valves under steam and liquid upstream conditions and evaluate the existing approximate critical flow relations for a wide range of subcooled water and steam conditions

Body mass index predicts risk for complications from transtemporal cerebellopontine angle surgery.

Science.gov (United States)

Mantravadi, Avinash V; Leonetti, John P; Burgette, Ryan; Pontikis, George; Marzo, Sam J; Anderson, Douglas

2013-03-01

To determine the relationship between body mass index (BMI) and risk for specific complications from transtemporal cerebellopontine angle (CPA) surgery for nonmalignant disease. Case series with chart review. Tertiary-care academic hospital. Retrospective review of 134 consecutive patients undergoing transtemporal cerebellopontine angle surgery for nonmalignant disease from 2009 to 2011. Data were collected regarding demographics, body mass index, intraoperative details, hospital stay, and complications including cerebrospinal fluid leak, wound complications, and brachial plexopathy. One hundred thirty-four patients were analyzed with a mean preoperative body mass index of 28.58. Statistical analysis demonstrated a significant difference in body mass index between patients with a postoperative cerebrospinal fluid leak and those without (P = .04), as well as a similar significant difference between those experiencing postoperative brachial plexopathy and those with no such complication (P = .03). Logistical regression analysis confirmed that body mass index is significant in predicting both postoperative cerebrospinal fluid leak (P = .004; odds ratio, 1.10) and brachial plexopathy (P = .04; odds ratio, 1.07). Elevated body mass index was not significant in predicting wound complications or increased hospital stay beyond postoperative day 3. Risk of cerebrospinal fluid leak and brachial plexopathy is increased in patients with elevated body mass index undergoing surgery of the cerebellopontine angle. Consideration should be given to preoperative optimization via dietary and lifestyle modifications as well as intraoperative somatosensory evoked potential monitoring of the brachial plexus to decrease these risks.

Predicting nosocomial lower respiratory tract infections by a risk index based system

NARCIS (Netherlands)

Chen, Yong; Shan, Xue; Zhao, Jingya; Han, Xuelin; Tian, Shuguang; Chen, Fangyan; Su, Xueting; Sun, Yansong; Huang, Liuyu; Grundmann, Hajo; Wang, Hongyuan; Han, Li

2017-01-01

Although belonging to one of the most common type of nosocomial infection, there was currently no simple prediction model for lower respiratory tract infections (LRTIs). This study aims to develop a risk index based system for predicting nosocomial LRTIs based on data from a large point-prevalence

Prediction of coronary artery bypass graft flow

International Nuclear Information System (INIS)

Tamiya, Eiji; Hada, Yoshiyuki; Asano, Ken-ichi; Iio, Masahiro.

1991-01-01

To predict the coronary artery bypass graft (CABG) flow based on the time density curve (TDC) obtained from the digital subtraction aortograms (DSA), we developed a pulsatile CABG model (perfusion pressure 60,130 mmHg, pulse rate 53,126/min, cardiac output 3-7 l/min, diameter of the graft 2.1∼6.0 mm). After positioning the regions of interest (ROI), we injected contrast medium(5∼40 ml/sec, 5∼40 ml) into the outlet conduit. Concerning the TDCs, we calculated appearance time (Ta), peak densities (Dp), peak time (Tp), disappearance time (Td), integral of TDC, ΔTp (difference of Tp between two ROI) and ΔTa (difference of Ta between two ROI). Perfusion pressure, graft flow and output curve were similar to those of patients with CABG. Ta, Tp, Td, and ΔTp were affected by both the injection rate and the volume of the contrast medium; while Dp and the TDC integral were only affected by the latter parameter. Under the same conditions of contrast medium injection, the TDC depended strongly on graft flow, diameter of the graft, output and pulse rate. 21.6+0.92π·d 2 /4·Δ1/ΔTp·60 provided the most accurate estimation of CABG flow (r=0.865, p<0.01). We conclude that densitometric analysis of DSA may be useful in the prediction of CABG flow. (author)

Flow-dependent empirical singular vector with an ensemble Kalman filter data assimilation for El Nino prediction

Energy Technology Data Exchange (ETDEWEB)

Ham, Yoo-Geun [NASA/GSFC Code 610.1, Global Modeling and Assimilation Office, Greenbelt, MD (United States); Universities Space Research Association, Goddard Earth Sciences Technology and Research Studies and Investigations, Baltimore, MD (United States); Rienecker, Michele M. [NASA/GSFC Code 610.1, Global Modeling and Assimilation Office, Greenbelt, MD (United States)

2012-10-15

In this study, a new approach for extracting flow-dependent empirical singular vectors (FESVs) for seasonal prediction using ensemble perturbations obtained from an ensemble Kalman filter (EnKF) assimilation is presented. Due to the short interval between analyses, EnKF perturbations primarily contain instabilities related to fast weather variability. To isolate slower, coupled instabilities that would be more suitable for seasonal prediction, an empirical linear operator for seasonal time-scales (i.e. several months) is formulated using a causality hypothesis; then, the most unstable mode from the linear operator is extracted for seasonal time-scales. It is shown that the flow-dependent operator represents nonlinear integration results better than a conventional empirical linear operator static in time. Through 20 years of retrospective seasonal predictions, it is shown that the skill of forecasting equatorial SST anomalies using the FESV is systematically improved over that using Conventional ESV (CESV). For example, the correlation skill of the NINO3 SST index using FESV is higher, by about 0.1, than that of CESV at 8-month leads. In addition, the forecast skill improvement is significant over the locations where the correlation skill of conventional methods is relatively low, indicating that the FESV is effective where the initial uncertainty is large. (orig.)

Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method

Directory of Open Access Journals (Sweden)

Yuhan Jia

2017-01-01

Full Text Available Accurate traffic flow prediction is increasingly essential for successful traffic modeling, operation, and management. Traditional data driven traffic flow prediction approaches have largely assumed restrictive (shallow model architectures and do not leverage the large amount of environmental data available. Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN and long short-term memory (LSTM to predict urban traffic flow considering the impact of rainfall. The rainfall-integrated DBN and LSTM can learn the features of traffic flow under various rainfall scenarios. Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. Furthermore, the LSTM can outperform the DBN to capture the time series characteristics of traffic flow data.

An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

Energy Technology Data Exchange (ETDEWEB)

Dagg, J.; Lafleur, P.

2010-07-01

This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO{sub 2}) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO{sub 2} exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO{sub 2} fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO{sub 2} uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO{sub 2} exchange in heterogeneous Tundra vegetation is variable.

An application of plot-scale NDVI in predicting carbon dioxide exchange and leaf area index in heterogeneous subarctic tundra

International Nuclear Information System (INIS)

Dagg, J.; Lafleur, P.

2010-01-01

This paper reported on a study that examined the flow of carbon into and out of tundra ecosystems. It is necessary to accurately predict carbon dioxide (CO 2 ) exchange in the Tundra because of the impacts of climate change on carbon stored in permafrost. Understanding the relationships between the normalized difference vegetation index (NDVI) and vegetation and CO 2 exchange may explain how small-scale variation in vegetation community extends to remotely sensed estimates of landscape characteristics. In this study, CO 2 fluxes were measured with a portable chamber in a range of Tundra vegetation communities. Biomass and leaf area were measured with destructive harvest, and NDVI was obtained using a hand-held infrared camera. There was a weak correlation between NDVI and leaf area index in some vegetation communities, but a significant correlation between NDVI and biomass, including mosses. NDVI was found to be strongly related to photosynthetic activity and net CO 2 uptake in all vegetation groups. However, NDVI related to ecosystem respiration only in wet sedge. It was concluded that at plot scale, the ability of NDVI to predict ecosystem properties and CO 2 exchange in heterogeneous Tundra vegetation is variable.

Development and validation of an ICD-10-based disability predictive index for patients admitted to hospitals with trauma.

Science.gov (United States)

Wada, Tomoki; Yasunaga, Hideo; Yamana, Hayato; Matsui, Hiroki; Fushimi, Kiyohide; Morimura, Naoto

2018-03-01

There was no established disability predictive measurement for patients with trauma that could be used in administrative claims databases. The aim of the present study was to develop and validate a diagnosis-based disability predictive index for severe physical disability at discharge using the International Classification of Diseases, 10th revision (ICD-10) coding. This retrospective observational study used the Diagnosis Procedure Combination database in Japan. Patients who were admitted to hospitals with trauma and discharged alive from 01 April 2010 to 31 March 2015 were included. Pediatric patients under 15 years old were excluded. Data for patients admitted to hospitals from 01 April 2010 to 31 March 2013 was used for development of a disability predictive index (derivation cohort), while data for patients admitted to hospitals from 01 April 2013 to 31 March 2015 was used for the internal validation (validation cohort). The outcome of interest was severe physical disability defined as the Barthel Index score of predictive index for each patient was defined as the sum of the scores. The predictive performance of the index was validated using the receiver operating characteristic curve analysis in the validation cohort. The derivation cohort included 1,475,158 patients, while the validation cohort included 939,659 patients. Of the 939,659 patients, 235,382 (25.0%) were discharged with severe physical disability. The c-statistics of the disability predictive index was 0.795 (95% confidence interval [CI] 0.794-0.795), while that of a model using the disability predictive index and patient baseline characteristics was 0.856 (95% CI 0.855-0.857). Severe physical disability at discharge may be well predicted with patient age, sex, CCI score, and the diagnosis-based disability predictive index in patients admitted to hospitals with trauma. Copyright © 2018 Elsevier Ltd. All rights reserved.

Compressor Part II: Volute Flow Predictions

Directory of Open Access Journals (Sweden)

Yu-Tai Lee

1999-01-01

Full Text Available A numerical method that solves the Reynolds-averaged Navier-Stokes equations is used to study an inefficient component of a shipboard air-conditioning HCFC-124 compressor system. This high-loss component of the centrifugal compressor was identified as the volute through a series of measurements given in Part I of the paper. The predictions were made using three grid topologies. The first grid closes the connection between the cutwater and the discharge diffuser. The other two grids connect the cutwater area with the discharge diffuser. Experiments were performed to simulate both the cutwater conditions used in the predictions. Surface pressures along the outer wall and near the inlet of the volute were surveyed for comparisons with the predictions. Good agreements between the predicted results and the measurements validate the calculations. Total pressure distributions and flow stream traces from the prediction results support the loss distribution through the volute. A modified volute configuration is examined numerically for further loss comparison.

Prediction of cold flow properties of Biodiesel

Directory of Open Access Journals (Sweden)

Parag Saxena

2016-08-01

Full Text Available Biodiesel being environmentally friendly is fast gaining acceptance in the market as an alternate diesel fuel. But compared to petroleum diesel it has certain limitations and thus it requires further development on economic viability and improvement in its properties to use it as a commercial fuel. The cold flow properties play a major role in the usage of biodiesel commercially as it freezes at cold climatic conditions. In the present study, cold flow properties of various types of biodiesel were estimated by using correlations available in literature. The correlations were evaluated based on the deviation between the predicted value and experimental values of cold flow properties.

MATHEMATICAL FRAMEWORK OF THE WELL PRODUCTIVITY INDEX FOR FAST FORCHHEIMER (NON-DARCY) FLOWS IN POROUS MEDIA

KAUST Repository

AULISA, EUGENIO

2009-08-01

Motivated by the reservoir engineering concept of the well Productivity Index, we introduced and analyzed a functional, denoted as "diffusive capacity", for the solution of the initial-boundary value problem (IBVP) for a linear parabolic equation.21 This IBVP described laminar (linear) Darcy flow in porous media; the considered boundary conditions corresponded to different regimes of the well production. The diffusive capacities were then computed as steady state invariants of the solutions to the corresponding time-dependent boundary value problem. Here similar features for fast or turbulent nonlinear flows subjected to the Forchheimer equations are analyzed. It is shown that under some hydrodynamic and thermodynamic constraints, there exists a so-called pseudo steady state regime for the Forchheimer flows in porous media. In other words, under some assumptions there exists a steady state invariant over a certain class of solutions to the transient IBVP modeling the Forchheimer flow for slightly compressible fluid. This invariant is the diffusive capacity, which serves as the mathematical representation of the so-called well Productivity Index. The obtained results enable computation of the well Productivity Index by resolving a single steady state boundary value problem for a second-order quasilinear elliptic equation. Analytical and numerical studies highlight some new relations for the well Productivity Index in linear and nonlinear cases. The obtained analytical formulas can be potentially used for the numerical well block model as an analog of Piecemann. © 2009 World Scientific Publishing Company.

Spatial statistics for predicting flow through a rock fracture

International Nuclear Information System (INIS)

Coakley, K.J.

1989-03-01

Fluid flow through a single rock fracture depends on the shape of the space between the upper and lower pieces of rock which define the fracture. In this thesis, the normalized flow through a fracture, i.e. the equivalent permeability of a fracture, is predicted in terms of spatial statistics computed from the arrangement of voids, i.e. open spaces, and contact areas within the fracture. Patterns of voids and contact areas, with complexity typical of experimental data, are simulated by clipping a correlated Gaussian process defined on a N by N pixel square region. The voids have constant aperture; the distance between the upper and lower surfaces which define the fracture is either zero or a constant. Local flow is assumed to be proportional to local aperture cubed times local pressure gradient. The flow through a pattern of voids and contact areas is solved using a finite-difference method. After solving for the flow through simulated 10 by 10 by 30 pixel patterns of voids and contact areas, a model to predict equivalent permeability is developed. The first model is for patterns with 80% voids where all voids have the same aperture. The equivalent permeability of a pattern is predicted in terms of spatial statistics computed from the arrangement of voids and contact areas within the pattern. Four spatial statistics are examined. The change point statistic measures how often adjacent pixel alternate from void to contact area (or vice versa ) in the rows of the patterns which are parallel to the overall flow direction. 37 refs., 66 figs., 41 tabs

Low Transvalvular Flow Rate Predicts Mortality in Patients With Low-Gradient Aortic Stenosis Following Aortic Valve Intervention.

Science.gov (United States)

Vamvakidou, Anastasia; Jin, Wenying; Danylenko, Oleksandr; Chahal, Navtej; Khattar, Rajdeep; Senior, Roxy

2018-03-09

This study aimed to assess the value of low transvalvular flow rate (FR) for the prediction of mortality compared with low stroke volume index (SVi) in patients with low-gradient (mean gradient: gradient AS who had undergone valve intervention. We retrospectively followed prospectively assessed consecutive patients with low-gradient, low aortic valve area AS who underwent aortic valve intervention between 2010 and 2014 for all-cause mortality. Of the 218 patients with mean age 75 ± 12 years, 102 (46.8%) had low stroke volume index (SVi) (gradient, low valve area aortic stenosis undergoing aortic valve intervention, low FR, not low SVi, was an independent predictor of medium-term mortality. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Can bispectral index or auditory evoked potential index predict implicit memory during propofol-induced sedation?

Science.gov (United States)

Wang, Yun; Yue, Yun; Sun, Yong-hai; Wu, An-shi

2006-06-05

Some patients still suffer from implicit memory of intraoperative events under adequate depth of anaesthesia. The elimination of implicit memory should be a necessary aim of clinical general anaesthesia. However, implicit memory cannot be tested during anaesthesia yet. We propose bispectral index (BIS) and auditory evoked potential index (AEPI), as predictors of implicit memory during anaesthesia. Thirty-six patients were equally divided into 3 groups according to the Observer's Assessment of Alertness/Sedation Score: A, level 3; B, level 2; and C, level 1. Every patient was given the first auditory stimulus before sedation. Then every patient received the second auditory stimulus after the target level of sedation had been reached. BIS and AEPI were monitored before and after the second auditory stimulus presentation. Four hours later, the inclusion test and exclusion test were performed on the ward using process dissociation procedure and the scores of implicit memory estimated. In groups A and B but not C, implicit memory estimates were statistically greater than zero (P memory scores in group A did not differ significantly from those in group B (P > 0.05). Implicit memory scores correlated with BIS and AEPI (P AEPI. The 95% cutoff points of BIS and AEPI for predicting implicit memory are 47 and 28, respectively. Implicit memory does not disappear until the depth of sedation increases to level 1 of OAA/S score. Implicit memory scores correlate well with BIS and AEPI during sedation. BIS is a better index for predicting implicit memory than AEPI during propofol induced sedation.

Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models

Directory of Open Access Journals (Sweden)

Cheng Xu

2015-01-01

Full Text Available Free flow speed is a fundamental measure of traffic performance and has been found to affect the severity of crash risk. However, the previous studies lack analysis and modelling of impact factors on bicycles’ free flow speed. The main focus of this study is to develop multilayer back propagation artificial neural network (BPANN models for the prediction of free flow speed and crash risk on the separated bicycle path. Four different models with considering different combinations of input variables (e.g., path width, traffic condition, bicycle type, and cyclists’ characteristics were developed. 459 field data samples were collected from eleven bicycle paths in Hangzhou, China, and 70% of total samples were used for training, 15% for validation, and 15% for testing. The results show that considering the input variables of bicycle types and characteristics of cyclists will effectively improve the accuracy of the prediction models. Meanwhile, the parameters of bicycle types have more significant effect on predicting free flow speed of bicycle compared to those of cyclists’ characteristics. The findings could contribute for evaluation, planning, and management of bicycle safety.

Novel Radiobiological Gamma Index for Evaluation of 3-Dimensional Predicted Dose Distribution

Energy Technology Data Exchange (ETDEWEB)

Sumida, Iori, E-mail: sumida@radonc.med.osaka-u.ac.jp [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Yamaguchi, Hajime; Kizaki, Hisao; Aboshi, Keiko; Tsujii, Mari; Yoshikawa, Nobuhiko; Yamada, Yuji [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Suzuki, Osamu; Seo, Yuji [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Isohashi, Fumiaki [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan); Yoshioka, Yasuo [Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka (Japan); Ogawa, Kazuhiko [Department of Radiation Oncology, NTT West Osaka Hospital, Osaka (Japan)

2015-07-15

Purpose: To propose a gamma index-based dose evaluation index that integrates the radiobiological parameters of tumor control (TCP) and normal tissue complication probabilities (NTCP). Methods and Materials: Fifteen prostate and head and neck (H&N) cancer patients received intensity modulated radiation therapy. Before treatment, patient-specific quality assurance was conducted via beam-by-beam analysis, and beam-specific dose error distributions were generated. The predicted 3-dimensional (3D) dose distribution was calculated by back-projection of relative dose error distribution per beam. A 3D gamma analysis of different organs (prostate: clinical [CTV] and planned target volumes [PTV], rectum, bladder, femoral heads; H&N: gross tumor volume [GTV], CTV, spinal cord, brain stem, both parotids) was performed using predicted and planned dose distributions under 2%/2 mm tolerance and physical gamma passing rate was calculated. TCP and NTCP values were calculated for voxels with physical gamma indices (PGI) >1. We propose a new radiobiological gamma index (RGI) to quantify the radiobiological effects of TCP and NTCP and calculate radiobiological gamma passing rates. Results: The mean RGI gamma passing rates for prostate cases were significantly different compared with those of PGI (P<.03–.001). The mean RGI gamma passing rates for H&N cases (except for GTV) were significantly different compared with those of PGI (P<.001). Differences in gamma passing rates between PGI and RGI were due to dose differences between the planned and predicted dose distributions. Radiobiological gamma distribution was visualized to identify areas where the dose was radiobiologically important. Conclusions: RGI was proposed to integrate radiobiological effects into PGI. This index would assist physicians and medical physicists not only in physical evaluations of treatment delivery accuracy, but also in clinical evaluations of predicted dose distribution.

Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF.

Directory of Open Access Journals (Sweden)

Shanna L Ashley

Full Text Available Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF.Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold.A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2, cathepsin-S (Cath-S, legumain (LGMN and soluble vascular endothelial growth factor receptor 2 (VEGFsR2, but low levels of inducible T cell costimulator (ICOS or trypsin 3 (TRY3] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2 was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2-126.7, P = 0.006.This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression.

Ventilator flow data predict bronchopulmonary dysplasia in extremely premature neonates

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Mariann H. Bentsen

2018-03-01

Full Text Available Early prediction of bronchopulmonary dysplasia (BPD may facilitate tailored management for neonates at risk. We investigated whether easily accessible flow data from a mechanical ventilator can predict BPD in neonates born extremely premature (EP. In a prospective population-based study of EP-born neonates, flow data were obtained from the ventilator during the first 48 h of life. Data were logged for >10 min and then converted to flow–volume loops using custom-made software. Tidal breathing parameters were calculated and averaged from ≥200 breath cycles, and data were compared between those who later developed moderate/severe and no/mild BPD. Of 33 neonates, 18 developed moderate/severe and 15 no/mild BPD. The groups did not differ in gestational age, surfactant treatment or ventilator settings. The infants who developed moderate/severe BPD had evidence of less airflow obstruction, significantly so for tidal expiratory flow at 50% of tidal expiratory volume (TEF50 expressed as a ratio of peak tidal expiratory flow (PTEF (p=0.007. A compound model estimated by multiple logistic regression incorporating TEF50/PTEF, birthweight z-score and sex predicted moderate/severe BPD with good accuracy (area under the curve 0.893, 95% CI 0.735–0.973. This study suggests that flow data obtained from ventilators during the first hours of life may predict later BPD in premature neonates. Future and larger studies are needed to validate these findings and to determine their clinical usefulness.

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

Science.gov (United States)

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.

PDW Index - A Simple Model for the Prediction of Liver Fibrosis in Chronic Viral Hepatitis

International Nuclear Information System (INIS)

Ashraf, S.; Ali, N.

2013-01-01

Objectives: To assess the accuracy of platelets, platelet morphological parameters, mean platelet volume(MPV) and platelet distribution width, (PDW) to diagnose advanced fibrosis. Study Design: Validation study. Place and Duration of Study: Combined Military Hospital, Malir, from Jun 2008 to Jun 2009. Patients and Methods: Simple laboratory tests, aspartate aminotransferase (AST) alanine aminotransferase (ALT) platelet count and platelet morphological parameters were measured in 91 chronic viral hepatitis patients. All patients had liver biopsy performed. A new index, PDW index was derived to detect the opposing effects of liver fibrosis on platelet count, MPV, and PDW. The predictive value of the index for advanced fibrosis (F3-F4) was assessed through descriptive statistics and area under the ROC curves. Results: Two cut-offs were chosen to qualify different stages of fibrosis. A value of > 8.00 predicted advanced fibrosis, F3-F4, with a specificity of 94% and positive predictive value of 78%. A value of < 6.00 ruled out advanced fibrosis with a negative predictive value of 93% and a sensitivity of 82%. The area under the ROC curve for advanced fibrosis was 0.840. PDW Index values outside of these cut-offs correctly classified 60% of patients. Conclusion: A simple index comprising platelet as only parameters have high diagnostic value for the advanced stages of fibrosis. (author)

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

Science.gov (United States)

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.

Prediction of strongly-heated internal gas flows

International Nuclear Information System (INIS)

McEligot, D.M.; Shehata, A.M.; Kunugi, Tomoaki

1997-01-01

The purposes of the present article are to remind practitioners why the usual textbook approaches may not be appropriate for treating gas flows heated from the surface with large heat fluxes and to review the successes of some recent applications of turbulence models to this case. Simulations from various turbulence models have been assessed by comparison to the measurements of internal mean velocity and temperature distributions by Shehata for turbulent, laminarizing and intermediate flows with significant gas property variation. Of about fifteen models considered, five were judged to provide adequate predictions

Adverse Condition and Critical Event Prediction in Cranfield Multiphase Flow Facility

DEFF Research Database (Denmark)

Egedorf, Søren; Shaker, Hamid Reza

2017-01-01

, or even to the environment. To cope with these, adverse condition and critical event prediction plays an important role. Adverse Condition and Critical Event Prediction Toolbox (ACCEPT) is a tool which has been recently developed by NASA to allow for a timely prediction of an adverse event, with low false...... alarm and missed detection rates. While ACCEPT has shown to be an effective tool in some applications, its performance has not yet been evaluated on practical well-known benchmark examples. In this paper, ACCEPT is used for adverse condition and critical event prediction in a multiphase flow facility....... Cranfield multiphase flow facility is known to be an interesting benchmark which has been used to evaluate different methods from statistical process monitoring. In order to allow for the data from the flow facility to be used in ACCEPT, methods such as Kernel Density Estimation (KDE), PCA-and CVA...

Pulsatility Index as a Diagnostic Parameter of Reciprocating Wall Shear Stress Parameters in Physiological Pulsating Waveforms.

Directory of Open Access Journals (Sweden)

Idit Avrahami

Full Text Available Arterial wall shear stress (WSS parameters are widely used for prediction of the initiation and development of atherosclerosis and arterial pathologies. Traditional clinical evaluation of arterial condition relies on correlations of WSS parameters with average flow rate (Q and heart rate (HR measurements. We show that for pulsating flow waveforms in a straight tube with flow reversals that lead to significant reciprocating WSS, the measurements of HR and Q are not sufficient for prediction of WSS parameters. Therefore, we suggest adding a third quantity-known as the pulsatility index (PI-which is defined as the peak-to-peak flow rate amplitude normalized by Q. We examine several pulsating flow waveforms with and without flow reversals using a simulation of a Womersley model in a straight rigid tube and validate the simulations through experimental study using particle image velocimetry (PIV. The results indicate that clinically relevant WSS parameters such as the percentage of negative WSS (P[%], oscillating shear index (OSI and the ratio of minimum to maximum shear stress rates (min/max, are better predicted when the PI is used in conjunction with HR and Q. Therefore, we propose to use PI as an additional and essential diagnostic quantity for improved predictability of the reciprocating WSS.

Modelling hydrodynamic parameters to predict flow assisted corrosion

International Nuclear Information System (INIS)

Poulson, B.; Greenwell, B.; Chexal, B.; Horowitz, J.

1992-01-01

During the past 15 years, flow assisted corrosion has been a worldwide problem in the power generating industry. The phenomena is complex and depends on environment, material composition, and hydrodynamic factors. Recently, modeling of flow assisted corrosion has become a subject of great importance. A key part of this effort is modeling the hydrodynamic aspects of this issue. This paper examines which hydrodynamic parameter should be used to correlate the occurrence and rate of flow assisted corrosion with physically meaningful parameters, discusses ways of measuring the relevant hydrodynamic parameter, and describes how the hydrodynamic data is incorporated into the predictive model

Using the Speech Transmission Index for predicting non-native speech intelligibility

NARCIS (Netherlands)

Wijngaarden, S.J. van; Bronkhorst, A.W.; Houtgast, T.; Steeneken, H.J.M.

2004-01-01

While the Speech Transmission Index ~STI! is widely applied for prediction of speech intelligibility in room acoustics and telecommunication engineering, it is unclear how to interpret STI values when non-native talkers or listeners are involved. Based on subjectively measured psychometric functions

CFD predictions of wake-stabilised jet flames in a cross-flow

International Nuclear Information System (INIS)

Lawal, Mohammed S.; Fairweather, Michael; Gogolek, Peter; Ingham, Derek B.; Ma, Lin; Pourkashanian, Mohamed; Williams, Alan

2013-01-01

This study describes an investigation into predicting the major flow properties in wake-stabilised jet flames in a cross flow of air using first- and second-order turbulence models, applied within a RANS (Reynolds-averaged Navier–Stokes) modelling framework. Standard and RNG (re-normalisation group) versions of the k-ε turbulence model were employed at the first-order level and the results compared with a second-moment closure, or RSM (Reynolds stress model). The combustion process was modelled using the laminar flamelet approach together with a thermal radiation model using the discrete ordinate method. The ability of the various turbulence models to reproduce experimentally established flame appearance, profiles of velocity and turbulence intensity, as well as the combustion efficiency of such flames is reported. The results show that all the turbulence models predict similar velocity profiles over the majority of the flow domain considered, except in the wake region, where the predictions of the RSM and RNG k-ε models are in closer agreement with experimental data. In contrast, the standard k-ε model over-predicts the peak turbulence intensity. Also, it is found that the RSM provides superior predictions of the planar recirculation and flame zones attached to the release pipe in the wake region. - Highlights: ► We investigated the prediction of the major properties in wake-stabilised methane jet flames in a cross flow. ► The ability of the various turbulence models to reproduce experimentally established flame parameters is reported. ► All the turbulence models considered predict similar velocity profiles, except in the wake region

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

Science.gov (United States)

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

2017-12-01

Successful weaning from mechanical ventilation depends on the patient's ability to cough efficiently. Cough peak flow (CPF) could predict extubation success using a dedicated flow meter but required patient disconnection. We aimed to predict extubation outcome using an overall model, including cough performance assessed by a ventilator flow meter. This was a prospective observational study conducted from November 2014 to October 2015. Before and after a spontaneous breathing trial, subjects were encouraged to cough as strongly as possible before freezing the ventilator screen to assess CPF and tidal volume (V T ) in the preceding inspiration. Early extubation success rate was defined as the proportion of subjects not re-intubated 48 h after extubation. Diagnostic performance of CPF and V T was assessed by using the area under the curve of the receiver operating characteristic curve. Cut-off values for CPF and V T were defined according to median values and used to describe the performance of a predictive test combining them with risk factors of early extubation failure. Among 673 subjects admitted, 92 had a cough assessment before extubation. For the 81 subjects with early extubation success, the median CPF was -67.7 L/min, and median V T was 0.646 L. For the 11 subjects with early extubation failure, the median CPF was -57.3 L/min, and median V T was 0.448 L. Area under the curve was 0.61 (95% CI 0.37-0.83) for CPF and 0.64 (95% CI 0.42-0.84) for CPF/V T combined. After dichotomization (CPF 0.55 L), there was a synergistic effect to predict early extubation success ( P meter of an ICU ventilator was able to predict extubation success and to build a composite score to predict extubation failure. The results were close to that found in previous studies that used a dedicated flow meter. This could help to identify high-risk subjects to prevent extubation failure. (ClinicalTrials.gov registration NCT02847221.). Copyright © 2017 by Daedalus Enterprises.

A New Approach for Accurate Prediction of Liquid Loading of Directional Gas Wells in Transition Flow or Turbulent Flow

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Ruiqing Ming

2017-01-01

Full Text Available Current common models for calculating continuous liquid-carrying critical gas velocity are established based on vertical wells and laminar flow without considering the influence of deviation angle and Reynolds number on liquid-carrying. With the increase of the directional well in transition flow or turbulent flow, the current common models cannot accurately predict the critical gas velocity of these wells. So we built a new model to predict continuous liquid-carrying critical gas velocity for directional well in transition flow or turbulent flow. It is shown from sensitivity analysis that the correction coefficient is mainly influenced by Reynolds number and deviation angle. With the increase of Reynolds number, the critical liquid-carrying gas velocity increases first and then decreases. And with the increase of deviation angle, the critical liquid-carrying gas velocity gradually decreases. It is indicated from the case calculation analysis that the calculation error of this new model is less than 10%, where accuracy is much higher than those of current common models. It is demonstrated that the continuous liquid-carrying critical gas velocity of directional well in transition flow or turbulent flow can be predicted accurately by using this new model.

Prediction model for initial point of net vapor generation for low-flow boiling

International Nuclear Information System (INIS)

Sun Qi; Zhao Hua; Yang Ruichang

2003-01-01

The prediction of the initial point of net vapor generation is significant for the calculation of phase distribution in sub-cooled boiling. However, most of the investigations were developed in high-flow boiling, and there is no common model that could be successfully applied for the low-flow boiling. A predictive model for the initial point of net vapor generation for low-flow forced convection and natural circulation is established here, by the analysis of evaporation and condensation heat transfer. The comparison between experimental data and calculated results shows that this model can predict the net vapor generation point successfully in low-flow sub-cooled boiling

A behavioral economic reward index predicts drinking resolutions: moderation revisited and compared with other outcomes.

Science.gov (United States)

Tucker, Jalie A; Roth, David L; Vignolo, Mary J; Westfall, Andrew O

2009-04-01

Data were pooled from 3 studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1- to 2-year prospective follow-up intervals was hypothesized to involve longer term behavior regulation processes than abstinence or relapse and to be predicted by more balanced preresolution monetary allocations between short-term and longer term objectives (i.e., drinking and saving for the future). Standardized odds ratios (ORs) based on changes in standard deviation units from a multinomial logistic regression indicated that increases on this "Alcohol-Savings Discretionary Expenditure" index predicted higher rates of abstinence (OR = 1.93, p = .004) and relapse (OR = 2.89, p moderation outcomes. The index had incremental utility in predicting moderation in complex models that included other established predictors. The study adds to evidence supporting a behavioral economic analysis of drinking resolutions and shows that a systematic analysis of preresolution spending patterns aids in predicting moderation.

On the prediction of condenser plate temperatures in a cross-flow condenser

NARCIS (Netherlands)

Ganzevles, F.L.A.; Geld, van der C.W.M.

2002-01-01

A prediction method is presented for the gas-sided plate temperatures at the inlet and at the outlet of a compact, cross-flow condenser. The method employs measured (or predicted) heat flow rates and temperatures of both coolant and gas, at inlet and outlet. The method is validated using infrared

Predictions of bubbly flows in vertical pipes using two-fluid models in CFDS-FLOW3D code

International Nuclear Information System (INIS)

Banas, A.O.; Carver, M.B.; Unrau, D.

1995-01-01

This paper reports the results of a preliminary study exploring the performance of two sets of two-fluid closure relationships applied to the simulation of turbulent air-water bubbly upflows through vertical pipes. Predictions obtained with the default CFDS-FLOW3D model for dispersed flows were compared with the predictions of a new model (based on the work of Lee), and with the experimental data of Liu. The new model, implemented in the CFDS-FLOW3D code, included additional source terms in the open-quotes standardclose quotes κ-ε transport equations for the liquid phase, as well as modified model coefficients and wall functions. All simulations were carried out in a 2-D axisymmetric format, collapsing the general multifluid framework of CFDS-FLOW3D to the two-fluid (air-water) case. The newly implemented model consistently improved predictions of radial-velocity profiles of both phases, but failed to accurately reproduce the experimental phase-distribution data. This shortcoming was traced to the neglect of anisotropic effects in the modelling of liquid-phase turbulence. In this sense, the present investigation should be considered as the first step toward the ultimate goal of developing a theoretically sound and universal CFD-type two-fluid model for bubbly flows in channels

Predictions of bubbly flows in vertical pipes using two-fluid models in CFDS-FLOW3D code

Energy Technology Data Exchange (ETDEWEB)

Banas, A.O.; Carver, M.B. [Chalk River Laboratories (Canada); Unrau, D. [Univ. of Toronto (Canada)

1995-09-01

This paper reports the results of a preliminary study exploring the performance of two sets of two-fluid closure relationships applied to the simulation of turbulent air-water bubbly upflows through vertical pipes. Predictions obtained with the default CFDS-FLOW3D model for dispersed flows were compared with the predictions of a new model (based on the work of Lee), and with the experimental data of Liu. The new model, implemented in the CFDS-FLOW3D code, included additional source terms in the {open_quotes}standard{close_quotes} {kappa}-{epsilon} transport equations for the liquid phase, as well as modified model coefficients and wall functions. All simulations were carried out in a 2-D axisymmetric format, collapsing the general multifluid framework of CFDS-FLOW3D to the two-fluid (air-water) case. The newly implemented model consistently improved predictions of radial-velocity profiles of both phases, but failed to accurately reproduce the experimental phase-distribution data. This shortcoming was traced to the neglect of anisotropic effects in the modelling of liquid-phase turbulence. In this sense, the present investigation should be considered as the first step toward the ultimate goal of developing a theoretically sound and universal CFD-type two-fluid model for bubbly flows in channels.

Short-term traffic flow prediction model using particle swarm optimization–based combined kernel function-least squares support vector machine combined with chaos theory

Directory of Open Access Journals (Sweden)

Qiang Shang

2016-08-01

Full Text Available Short-term traffic flow prediction is an important part of intelligent transportation systems research and applications. For further improving the accuracy of short-time traffic flow prediction, a novel hybrid prediction model (multivariate phase space reconstruction–combined kernel function-least squares support vector machine based on multivariate phase space reconstruction and combined kernel function-least squares support vector machine is proposed. The C-C method is used to determine the optimal time delay and the optimal embedding dimension of traffic variables’ (flow, speed, and occupancy time series for phase space reconstruction. The G-P method is selected to calculate the correlation dimension of attractor which is an important index for judging chaotic characteristics of the traffic variables’ series. The optimal input form of combined kernel function-least squares support vector machine model is determined by multivariate phase space reconstruction, and the model’s parameters are optimized by particle swarm optimization algorithm. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. The experimental results suggest that the new proposed model yields better predictions compared with similar models (combined kernel function-least squares support vector machine, multivariate phase space reconstruction–generalized kernel function-least squares support vector machine, and phase space reconstruction–combined kernel function-least squares support vector machine, which indicates that the new proposed model exhibits stronger prediction ability and robustness.

Predicting waist circumference from body mass index.

Science.gov (United States)

Bozeman, Samuel R; Hoaglin, David C; Burton, Tanya M; Pashos, Chris L; Ben-Joseph, Rami H; Hollenbeak, Christopher S

2012-08-03

Being overweight or obese increases risk for cardiometabolic disorders. Although both body mass index (BMI) and waist circumference (WC) measure the level of overweight and obesity, WC may be more important because of its closer relationship to total body fat. Because WC is typically not assessed in clinical practice, this study sought to develop and verify a model to predict WC from BMI and demographic data, and to use the predicted WC to assess cardiometabolic risk. Data were obtained from the Third National Health and Nutrition Examination Survey (NHANES) and the Atherosclerosis Risk in Communities Study (ARIC). We developed linear regression models for men and women using NHANES data, fitting waist circumference as a function of BMI. For validation, those regressions were applied to ARIC data, assigning a predicted WC to each individual. We used the predicted WC to assess abdominal obesity and cardiometabolic risk. The model correctly classified 88.4% of NHANES subjects with respect to abdominal obesity. Median differences between actual and predicted WC were -0.07 cm for men and 0.11 cm for women. In ARIC, the model closely estimated the observed WC (median difference: -0.34 cm for men, +3.94 cm for women), correctly classifying 86.1% of ARIC subjects with respect to abdominal obesity and 91.5% to 99.5% as to cardiometabolic risk.The model is generalizable to Caucasian and African-American adult populations because it was constructed from data on a large, population-based sample of men and women in the United States, and then validated in a population with a larger representation of African-Americans. The model accurately estimates WC and identifies cardiometabolic risk. It should be useful for health care practitioners and public health officials who wish to identify individuals and populations at risk for cardiometabolic disease when WC data are unavailable.

Post-fire debris flow prediction in Western United States: Advancements based on a nonparametric statistical technique

Science.gov (United States)

Nikolopoulos, E. I.; Destro, E.; Bhuiyan, M. A. E.; Borga, M., Sr.; Anagnostou, E. N.

2017-12-01

Fire disasters affect modern societies at global scale inducing significant economic losses and human casualties. In addition to their direct impacts they have various adverse effects on hydrologic and geomorphologic processes of a region due to the tremendous alteration of the landscape characteristics (vegetation, soil properties etc). As a consequence, wildfires often initiate a cascade of hazards such as flash floods and debris flows that usually follow the occurrence of a wildfire thus magnifying the overall impact in a region. Post-fire debris flows (PFDF) is one such type of hazards frequently occurring in Western United States where wildfires are a common natural disaster. Prediction of PDFD is therefore of high importance in this region and over the last years a number of efforts from United States Geological Survey (USGS) and National Weather Service (NWS) have been focused on the development of early warning systems that will help mitigate PFDF risk. This work proposes a prediction framework that is based on a nonparametric statistical technique (random forests) that allows predicting the occurrence of PFDF at regional scale with a higher degree of accuracy than the commonly used approaches that are based on power-law thresholds and logistic regression procedures. The work presented is based on a recently released database from USGS that reports a total of 1500 storms that triggered and did not trigger PFDF in a number of fire affected catchments in Western United States. The database includes information on storm characteristics (duration, accumulation, max intensity etc) and other auxiliary information of land surface properties (soil erodibility index, local slope etc). Results show that the proposed model is able to achieve a satisfactory prediction accuracy (threat score > 0.6) superior of previously published prediction frameworks highlighting the potential of nonparametric statistical techniques for development of PFDF prediction systems.

A conservative fully implicit algorithm for predicting slug flows

Science.gov (United States)

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.

Subchannel friction factors for rod bundles: laminar flow predictions and their application to turbulent flows

International Nuclear Information System (INIS)

Robinson, D.P.

1979-02-01

For the calculation of friction factors the use of correlations validated for smooth circular tubes along with the duct hydraulic diameter is known to be inappropriate for certain non-circular geometries. In order to test the validity and range of application of such correlations to the subchannels of rod bundles a computer programme has been written for the prediction of subchannel laminar velocity distributions and friction coefficients for fully developed flow. The theoretical basis and development of the programme is described along with comparisons between predictions and existing solutions for some simple geometries. Using the computer programme a wide range of calculations have been carried out for flow sections representing edge, corner and internal subchannels of rod bundles with particular emphasis on those of in-line pin bundle geometries. Where comparison can be made the predicted laminar coefficients are in excellent agreement with existing solutions. Although the approach adopted here could be used as the basis of a model for the subchannel axial friction factor, careful account should be taken of enhanced turbulent momentum transfer in situations where the flow is not unidirectional. (UK)

Prediction of Bispectral Index during Target-controlled Infusion of Propofol and Remifentanil: A Deep Learning Approach.

Science.gov (United States)

Lee, Hyung-Chul; Ryu, Ho-Geol; Chung, Eun-Jin; Jung, Chul-Woo

2018-03-01

The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index during total intravenous anesthesia would be more accurately predicted by a deep learning approach. Long short-term memory and the feed-forward neural network were sequenced to simulate the pharmacokinetic and pharmacodynamic parts of an empirical model, respectively, to predict intraoperative bispectral index during combined use of propofol and remifentanil. Inputs of long short-term memory were infusion histories of propofol and remifentanil, which were retrieved from target-controlled infusion pumps for 1,800 s at 10-s intervals. Inputs of the feed-forward network were the outputs of long short-term memory and demographic data such as age, sex, weight, and height. The final output of the feed-forward network was the bispectral index. The performance of bispectral index prediction was compared between the deep learning model and previously reported response surface model. The model hyperparameters comprised 8 memory cells in the long short-term memory layer and 16 nodes in the hidden layer of the feed-forward network. The model training and testing were performed with separate data sets of 131 and 100 cases. The concordance correlation coefficient (95% CI) were 0.561 (0.560 to 0.562) in the deep learning model, which was significantly larger than that in the response surface model (0.265 [0.263 to 0.266], P deep learning model-predicted bispectral index during target-controlled infusion of propofol and remifentanil more accurately compared to the traditional model. The deep learning approach in anesthetic pharmacology seems promising because of its excellent performance and extensibility.

Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

Science.gov (United States)

Manatsa, Desmond; Mushore, Terrence; Lenouo, Andre

2017-01-01

The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December-March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum's (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit

Two- and three-index formulations of the minimum cost multicommodity k-splittable flow problem

DEFF Research Database (Denmark)

Gamst, Mette; Jensen, Peter Neergaard; Pisinger, David

2010-01-01

The multicommodity flow problem (MCFP) considers the efficient routing of commodities from their origins to their destinations subject to capacity restrictions and edge costs. Baier et al. [G. Baier, E. Köhler, M. Skutella, On the k-splittable flow problem, in: 10th Annual European Symposium...... of commodities has to be satisfied at the lowest possible cost. The problem has applications in transportation problems where a number of commodities must be routed, using a limited number of distinct transportation units for each commodity. Based on a three-index formulation by Truffot et al. [J. Truffot, C...... on Algorithms, 2002, 101–113] introduced the maximum flow multicommodity k-splittable flow problem (MCkFP) where each commodity may use at most k paths between its origin and its destination. This paper studies the -hard minimum cost multicommodity k-splittable flow problem (MCMCkFP) in which a given flow...

Empirical modelling to predict the refractive index of human blood

Science.gov (United States)

Yahya, M.; Saghir, M. Z.

2016-02-01

Optical techniques used for the measurement of the optical properties of blood are of great interest in clinical diagnostics. Blood analysis is a routine procedure used in medical diagnostics to confirm a patient’s condition. Measuring the optical properties of blood is difficult due to the non-homogenous nature of the blood itself. In addition, there is a lot of variation in the refractive indices reported in the literature. These are the reasons that motivated the researchers to develop a mathematical model that can be used to predict the refractive index of human blood as a function of concentration, temperature and wavelength. The experimental measurements were conducted on mimicking phantom hemoglobin samples using the Abbemat Refractometer. The results analysis revealed a linear relationship between the refractive index and concentration as well as temperature, and a non-linear relationship between refractive index and wavelength. These results are in agreement with those found in the literature. In addition, a new formula was developed based on empirical modelling which suggests that temperature and wavelength coefficients be added to the Barer formula. The verification of this correlation confirmed its ability to determine refractive index and/or blood hematocrit values with appropriate clinical accuracy.

Prediction about chaotic times series of natural circulation flow under rolling motion

International Nuclear Information System (INIS)

Yuan Can; Cai Qi; Guo Li; Yan Feng

2014-01-01

The paper have proposed a chaotic time series prediction model, which combined phase space reconstruction with support vector machines. The model has been used to predict the coolant volume flow, in which a synchronous parameter optimization method was brought up based on particle swarm optimization algorithm, since the numerical value selection of related parameter was a key factor for the prediction precision. The average relative error of prediction values and actual observation values was l,5% and relative precision was 0.9879. The result indicated that the model could apply for the natural circulation coolant volume flow prediction under rolling motion condition with high accuracy and robustness. (authors)

CFD Validation Studies for Hypersonic Flow Prediction

Science.gov (United States)

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.

A study on effects of cash flow patterns and auditors’ opinions in predicting financial distress

Directory of Open Access Journals (Sweden)

Fatemeh Namvar

2013-07-01

Full Text Available Bankruptcy has been one of the most important issues among investors in stock market and there are literally different techniques for predicting bankruptcy. In this paper, we study on effects of cash flow patterns and auditors’ opinions in predicting financial distress on some 80 selected firms traded on Tehran Stock Exchange over the period 2005-2011. In this study, the combination of cash flow patterns represent firm’s resource allocations and operational capabilities interacted with their strategy choices. In additions, predictions about each individual cash flow components, operational, investment, financial, are derived from economic theory, which forms a basis for the life proxy. We use cash flow patterns in the decline stage and compare the results with auditors’ opinions. The results indicate that cash flow patterns could predict financial distress companies in Iran. In addition, the effective cash flow patterns in predicting financial distress is more than auditors’ feedbacks.

Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction

Directory of Open Access Journals (Sweden)

Hua-pu Lu

2015-01-01

Full Text Available With the rapid development of urban informatization, the era of big data is coming. To satisfy the demand of traffic congestion early warning, this paper studies the method of real-time traffic flow state identification and prediction based on big data-driven theory. Traffic big data holds several characteristics, such as temporal correlation, spatial correlation, historical correlation, and multistate. Traffic flow state quantification, the basis of traffic flow state identification, is achieved by a SAGA-FCM (simulated annealing genetic algorithm based fuzzy c-means based traffic clustering model. Considering simple calculation and predictive accuracy, a bilevel optimization model for regional traffic flow correlation analysis is established to predict traffic flow parameters based on temporal-spatial-historical correlation. A two-stage model for correction coefficients optimization is put forward to simplify the bilevel optimization model. The first stage model is built to calculate the number of temporal-spatial-historical correlation variables. The second stage model is present to calculate basic model formulation of regional traffic flow correlation. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods.

Options for refractive index and viscosity matching to study variable density flows

Science.gov (United States)

Clément, Simon A.; Guillemain, Anaïs; McCleney, Amy B.; Bardet, Philippe M.

2018-02-01

Variable density flows are often studied by mixing two miscible aqueous solutions of different densities. To perform optical diagnostics in such environments, the refractive index of the fluids must be matched, which can be achieved by carefully choosing the two solutes and the concentration of the solutions. To separate the effects of buoyancy forces and viscosity variations, it is desirable to match the viscosity of the two solutions in addition to their refractive index. In this manuscript, several pairs of index matched fluids are compared in terms of viscosity matching, monetary cost, and practical use. Two fluid pairs are studied in detail, with two aqueous solutions (binary solutions of water and a salt or alcohol) mixed into a ternary solution. In each case: an aqueous solution of isopropanol mixed with an aqueous solution of sodium chloride (NaCl) and an aqueous solution of glycerol mixed with an aqueous solution of sodium sulfate (Na_2SO_4). The first fluid pair allows reaching high-density differences at low cost, but brings a large difference in dynamic viscosity. The second allows matching dynamic viscosity and refractive index simultaneously, at reasonable cost. For each of these four solutes, the density, kinematic viscosity, and refractive index are measured versus concentration and temperature, as well as wavelength for the refractive index. To investigate non-linear effects when two index-matched, binary solutions are mixed, the ternary solutions formed are also analyzed. Results show that density and refractive index follow a linear variation with concentration. However, the viscosity of the isopropanol and NaCl pair deviates from the linear law and has to be considered. Empirical correlations and their coefficients are given to create index-matched fluids at a chosen temperature and wavelength. Finally, the effectiveness of the refractive index matching is illustrated with particle image velocimetry measurements performed for a buoyant jet in a

Separation prediction in two dimensional boundary layer flows using artificial neural networks

International Nuclear Information System (INIS)

Sabetghadam, F.; Ghomi, H.A.

2003-01-01

In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

A closed-form analytical model for predicting 3D boundary layer displacement thickness for the validation of viscous flow solvers

Science.gov (United States)

Kumar, V. R. Sanal; Sankar, Vigneshwaran; Chandrasekaran, Nichith; Saravanan, Vignesh; Natarajan, Vishnu; Padmanabhan, Sathyan; Sukumaran, Ajith; Mani, Sivabalan; Rameshkumar, Tharikaa; Nagaraju Doddi, Hema Sai; Vysaprasad, Krithika; Sharan, Sharad; Murugesh, Pavithra; Shankar, S. Ganesh; Nejaamtheen, Mohammed Niyasdeen; Baskaran, Roshan Vignesh; Rahman Mohamed Rafic, Sulthan Ariff; Harisrinivasan, Ukeshkumar; Srinivasan, Vivek

2018-02-01

A closed-form analytical model is developed for estimating the 3D boundary-layer-displacement thickness of an internal flow system at the Sanal flow choking condition for adiabatic flows obeying the physics of compressible viscous fluids. At this unique condition the boundary-layer blockage induced fluid-throat choking and the adiabatic wall-friction persuaded flow choking occur at a single sonic-fluid-throat location. The beauty and novelty of this model is that without missing the flow physics we could predict the exact boundary-layer blockage of both 2D and 3D cases at the sonic-fluid-throat from the known values of the inlet Mach number, the adiabatic index of the gas and the inlet port diameter of the internal flow system. We found that the 3D blockage factor is 47.33 % lower than the 2D blockage factor with air as the working fluid. We concluded that the exact prediction of the boundary-layer-displacement thickness at the sonic-fluid-throat provides a means to correctly pinpoint the causes of errors of the viscous flow solvers. The methodology presented herein with state-of-the-art will play pivotal roles in future physical and biological sciences for a credible verification, calibration and validation of various viscous flow solvers for high-fidelity 2D/3D numerical simulations of real-world flows. Furthermore, our closed-form analytical model will be useful for the solid and hybrid rocket designers for the grain-port-geometry optimization of new generation single-stage-to-orbit dual-thrust-motors with the highest promising propellant loading density within the given envelope without manifestation of the Sanal flow choking leading to possible shock waves causing catastrophic failures.

A closed-form analytical model for predicting 3D boundary layer displacement thickness for the validation of viscous flow solvers

Directory of Open Access Journals (Sweden)

V. R. Sanal Kumar

2018-02-01

Full Text Available A closed-form analytical model is developed for estimating the 3D boundary-layer-displacement thickness of an internal flow system at the Sanal flow choking condition for adiabatic flows obeying the physics of compressible viscous fluids. At this unique condition the boundary-layer blockage induced fluid-throat choking and the adiabatic wall-friction persuaded flow choking occur at a single sonic-fluid-throat location. The beauty and novelty of this model is that without missing the flow physics we could predict the exact boundary-layer blockage of both 2D and 3D cases at the sonic-fluid-throat from the known values of the inlet Mach number, the adiabatic index of the gas and the inlet port diameter of the internal flow system. We found that the 3D blockage factor is 47.33 % lower than the 2D blockage factor with air as the working fluid. We concluded that the exact prediction of the boundary-layer-displacement thickness at the sonic-fluid-throat provides a means to correctly pinpoint the causes of errors of the viscous flow solvers. The methodology presented herein with state-of-the-art will play pivotal roles in future physical and biological sciences for a credible verification, calibration and validation of various viscous flow solvers for high-fidelity 2D/3D numerical simulations of real-world flows. Furthermore, our closed-form analytical model will be useful for the solid and hybrid rocket designers for the grain-port-geometry optimization of new generation single-stage-to-orbit dual-thrust-motors with the highest promising propellant loading density within the given envelope without manifestation of the Sanal flow choking leading to possible shock waves causing catastrophic failures.

Radiotracer transit measurements as an index of regional cerebral blood flow. Pt. 1. Methodological and clinical results in chronic alcoholics cortical blood flow

International Nuclear Information System (INIS)

Dobrzanski, T.

1975-01-01

The numerical mean values of the cerebral radiorheographic index in healthy control subjects and in patients with cerebrovascular disease were not significantly different from the values of regional cerebral blood flow reported, respectively, by other authors using a modification of the Xe-133 method. In the group of chronic alcoholics there was a significant correlation between the duration of alcoholism and certain numerical values of the cerebral radiorheographic index. (author)

Numerical prediction of flow, heat transfer, turbulence and combustion

CERN Document Server

Spalding, D Brian; Pollard, Andrew; Singhal, Ashok K

1983-01-01

Numerical Prediction of Flow, Heat Transfer, Turbulence and Combustion: Selected Works of Professor D. Brian Spalding focuses on the many contributions of Professor Spalding on thermodynamics. This compilation of his works is done to honor the professor on the occasion of his 60th birthday. Relatively, the works contained in this book are selected to highlight the genius of Professor Spalding in this field of interest. The book presents various research on combustion, heat transfer, turbulence, and flows. His thinking on separated flows paved the way for the multi-dimensional modeling of turbu

An evaluation of the usefulness of cash flow ratios to predict financial distress

Directory of Open Access Journals (Sweden)

L. Jooste

2007-12-01

Full Text Available Purpose: With the introduction of the cash flow statement it became an integral part of financial reporting. A need arose to develop ratios for the effective evaluation of cash flow information. This article investigates cash flow ratios suggested by various researchers and suggests a list of ratios with the potential to predict financial failure. Design: The cash flow ratios suggested by researchers, from as early as 1966, are investigated and eight cash flow ratios selected for inclusion in an analysis to predict financial failure. Ten failed entities are selected for a cash flow evaluation by means of the selected ratios for five years prior to failure. For a comparison, non-failed entities in similar sectors are selected and also evaluated by means of the cash flow ratios. The mean values of each ratio, for each year prior to failure, were then calculated and the means of the failed entities were compared to the non-failed entities. Findings: The comparison revealed that cash flow ratios have predictive value with the cash flow to total debt identified as the best indicator of failure. It was also determined that, although failed entities have lower cash flows than non-failed entities, they also had smaller reserves of liquid assets. Furthermore, they have less capacity to meet debt obligations and they tend to incur more debt. The ratios of the failed entities were unstable and fluctuated from one year to the next. Finally, bankruptcy could be predicted three years prior to financial failure. Implications: Income statement and balance sheet ratios are not enough to measure liquidity. An entity can have positive liquidity ratios and increasing profits, yet have serious cash flow problems. Ratios developed from the cash flow statement should supplement traditional accrual-based ratios to provide additional information on the financial strengths and weaknesses of an entity .

Mechanisms and predictions for subcooled flow boiling CHF

International Nuclear Information System (INIS)

Liu, Wei; Nariai, Hideki; Inasaka, Fujio

2000-01-01

Corresponding to the two kinds of flow pattern reported in literature for subcooled flow boiling, two kinds of CHF triggering mechanism are considered existing with working in different working scope. On the base of a criterion proposed recently by the present authors, subcooled flow boiling data firstly are categorized into two groups by judging whether the first kind or the second kind of flow pattern is established. Possible CHF triggering mechanisms and prediction methods for the two kinds of flow pattern condition are discussed. By considering both the flow pattern development and CHF triggering mechanism, a detailed data categorization is carried out. The corresponding CHF occurrence properties in different data groups are summarized. Parametric trends are reviewed for the first and second kind of data group working condition respectively. Mass flux, pressure, inlet subcooling and inner diameter show almost same effects in the two different working conditions, while the ratio of heated length to diameter's effects on CHF show to be different. Research for the L/D effect on the CHF transverse the interface of the different data groups is carried out. (author)

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

Science.gov (United States)

Cappelli, Daniele; Mansour, Nagi N.

2012-01-01

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

Predictive model for convective flows induced by surface reactivity contrast

Science.gov (United States)

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.

Statistical models to predict flows at monthly level in Salvajina

International Nuclear Information System (INIS)

Gonzalez, Harold O

1994-01-01

It thinks about and models of lineal regression evaluate at monthly level that they allow to predict flows in Salvajina, with base in predictions variable, like the difference of pressure between Darwin and Tahiti, precipitation in Piendamo Cauca), temperature in Port Chicama (Peru) and pressure in Tahiti

Void fraction prediction in saturated flow boiling

International Nuclear Information System (INIS)

Francisco J Collado

2005-01-01

Full text of publication follows: An essential element in thermal-hydraulics is the accurate prediction of the vapor void fraction, or fraction of the flow cross-sectional area occupied by steam. Recently, the author has suggested to calculate void fraction working exclusively with thermodynamic properties. It is well known that the usual 'flow' quality, merely a mass flow rate ratio, is not at all a thermodynamic property because its expression in function of thermodynamic properties includes the slip ratio, which is a parameter of the process not a function of state. By the other hand, in the classic and well known expression of the void fraction - in function of the true mass fraction of vapor (also called 'static' quality), and the vapor and liquid densities - does not appear the slip ratio. Of course, this would suggest a direct procedure for calculating the void fraction, provided we had an accurate value of the true mass fraction of vapor, clearly from the heat balance. However the classic heat balance is usually stated in function of the 'flow' quality, what sounds really contradictory because this parameter, as we have noted above, is not at all a thermodynamic property. Then we should check against real data the actual relationship between the thermodynamic properties and the applied heat. For saturated flow boiling just from the inlet of the heated tube, and not having into account the kinetic and potential terms, the uniform applied heat per unit mass of inlet water and per unit length (in short, specific linear heat) should be closely related to a (constant) slope of the mixture enthalpy. In this work, we have checked the relation between the specific linear heat and the thermodynamic enthalpy of the liquid-vapor mixture using the actual mass fraction. This true mass fraction is calculated using the accurate measurements of the outlet void fraction taken during the Cambridge project by Knights and Thom in the sixties for vertical and horizontal

Bayesian inference in mass flow simulations - from back calculation to prediction

Science.gov (United States)

Kofler, Andreas; Fischer, Jan-Thomas; Hellweger, Valentin; Huber, Andreas; Mergili, Martin; Pudasaini, Shiva; Fellin, Wolfgang; Oberguggenberger, Michael

2017-04-01

Mass flow simulations are an integral part of hazard assessment. Determining the hazard potential requires a multidisciplinary approach, including different scientific fields such as geomorphology, meteorology, physics, civil engineering and mathematics. An important task in snow avalanche simulation is to predict process intensities (runout, flow velocity and depth, ...). The application of probabilistic methods allows one to develop a comprehensive simulation concept, ranging from back to forward calculation and finally to prediction of mass flow events. In this context optimized parameter sets for the used simulation model or intensities of the modeled mass flow process (e.g. runout distances) are represented by probability distributions. Existing deterministic flow models, in particular with respect to snow avalanche dynamics, contain several parameters (e.g. friction). Some of these parameters are more conceptual than physical and their direct measurement in the field is hardly possible. Hence, parameters have to be optimized by matching simulation results to field observations. This inverse problem can be solved by a Bayesian approach (Markov chain Monte Carlo). The optimization process yields parameter distributions, that can be utilized for probabilistic reconstruction and prediction of avalanche events. Arising challenges include the limited amount of observations, correlations appearing in model parameters or observed avalanche characteristics (e.g. velocity and runout) and the accurate handling of ensemble simulations, always taking into account the related uncertainties. Here we present an operational Bayesian simulation framework with r.avaflow, the open source GIS simulation model for granular avalanches and debris flows.

Accuracy of Body Mass Index Versus Lean Mass Index for Prediction of Sarcopenia in Older Women.

Science.gov (United States)

Benton, M J; Silva-Smith, A L

2018-01-01

We compared accuracy of body mass index (BMI) versus lean mass index (LMI) to predict sarcopenia in 58 community-dwelling women (74.1±0.9 years). Lean mass was measured with multi-frequency bioelectrical impedance analysis, and strength was measured with Arm Curl test, Chair Stand test, and handgrip dynamometry. Sarcopenia was defined as low LMI. When categorized by BMI, normal women had less absolute lean mass (37.6±1.0 vs. 42.6±0.9 kg; Plean mass (14.1±0.2 vs. 16.1±0.2 kg/m2; Plean mass (44.0±0.7 vs. 35.7±0.7 kg; Plean mass (16.2±0.2 vs. 13.8±0.2 kg/m2; Plean mass and strength. For clinical assessment, calculation of LMI rather than BMI is appropriate.

Empirical modelling to predict the refractive index of human blood

International Nuclear Information System (INIS)

Yahya, M; Saghir, M Z

2016-01-01

Optical techniques used for the measurement of the optical properties of blood are of great interest in clinical diagnostics. Blood analysis is a routine procedure used in medical diagnostics to confirm a patient’s condition. Measuring the optical properties of blood is difficult due to the non-homogenous nature of the blood itself. In addition, there is a lot of variation in the refractive indices reported in the literature. These are the reasons that motivated the researchers to develop a mathematical model that can be used to predict the refractive index of human blood as a function of concentration, temperature and wavelength. The experimental measurements were conducted on mimicking phantom hemoglobin samples using the Abbemat Refractometer. The results analysis revealed a linear relationship between the refractive index and concentration as well as temperature, and a non-linear relationship between refractive index and wavelength. These results are in agreement with those found in the literature. In addition, a new formula was developed based on empirical modelling which suggests that temperature and wavelength coefficients be added to the Barer formula. The verification of this correlation confirmed its ability to determine refractive index and/or blood hematocrit values with appropriate clinical accuracy. (paper)

Initial Self-Healing Temperatures of Asphalt Mastics Based on Flow Behavior Index.

Science.gov (United States)

Li, Chao; Wu, Shaopeng; Tao, Guanyu; Xiao, Yue

2018-05-29

Increasing temperature is a simple and convenient method to accelerate the self-healing process of bitumen. However, bitumen may not achieve the healing capability at lower temperature, and may be aged if temperature is too high. In addition, the bitumen is mixed with mineral filler and formed as asphalt mastic in asphalt concrete, so it is more accurate to study the initial self-healing from the perspective of asphalt mastic. The primary purpose of this research was to examine the initial self-healing temperature of asphalt mastic, which was determined by the flow behavior index obtained from the flow characteristics. Firstly, the texture and geometry characteristics of two fillers were analyzed, and then the initial self-healing temperature of nine types of asphalt mastic, pure bitumen (PB) and styrene-butadiene-styrene (SBS) modified bitumen were determined by the flow behavior index. Results demonstrate that the average standard deviation of gray-scale texture value of limestone filler (LF) is 21.24% lower than that of steel slag filler (SSF), showing that the steel slag filler has a better particle distribution and geometry characteristics. Also the initial self-healing temperatures of asphalt mastics with 0.2, 0.4 and 0.6 LF-PB volume ratio are 46.5 °C, 47.2 °C and 49.4 °C, which are 1.4 °C, 0.8 °C and 0.4 °C higher than that of asphalt mastics with SSF-PB, but not suitable for the evaluation of asphalt mastic contained SBS modified bitumen because of unique structure and performance of SBS.

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

Science.gov (United States)

Kibler, K. M.; Alipour, M.

2016-12-01

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

A Behavioral Economic Reward Index Predicts Drinking Resolutions: Moderation Re-visited and Compared with Other Outcomes

Science.gov (United States)

Tucker, Jalie A.; Roth, David L.; Vignolo, Mary J.; Westfall, Andrew O.

2014-01-01

Data were pooled from three studies of recently resolved community-dwelling problem drinkers to determine whether a behavioral economic index of the value of rewards available over different time horizons distinguished among moderation (n = 30), abstinent (n = 95), and unresolved (n = 77) outcomes. Moderation over 1-2 year prospective follow-up intervals was hypothesized to involve longer term behavior regulation processes compared to abstinence or relapse and to be predicted by more balanced pre-resolution monetary allocations between short- and longer-term objectives (i.e., drinking and saving for the future). Standardized odds ratios (OR) based on changes in standard deviation units from a multinomial logistic regression indicated that increases on this “Alcohol-Savings Discretionary Expenditure” index predicted higher rates of both abstinence (OR = 1.93, p = .004) and relapse (OR = 2.89, p moderation outcomes. The index had incremental utility in predicting moderation in complex models that included other established predictors. The study adds to evidence supporting a behavioral economic analysis of drinking resolutions and shows that a systematic analysis of pre-resolution spending patterns aids in predicting moderation. PMID:19309182

An improved liquid film model to predict the CHF based on the influence of churn flow

International Nuclear Information System (INIS)

Wang, Ke; Bai, Bofeng; Ma, Weimin

2014-01-01

The critical heat flux (CHF) for boiling crisis is one of the most important parameters in thermal management and safe operation of many engineering systems. Traditionally, the liquid film flow model for “dryout” mechanism shows a good prediction in heated annular two-phase flow. However, a general assumption that the initial entrained fraction at the onset of annular flow shows a lack of reasonable physical interpretation. Since the droplets have great momentum and the length of churn flow is short, the droplets in churn flow show an inevitable effect on the downstream annular flow. To address this, we considered the effect of churn flow and developed the original liquid film flow model in vertical upward flow by suggesting that calculation starts from the onset of churn flow rather than annular flow. The results indicated satisfactory predictions with the experimental data and the developed model provided a better understanding about the effect of flow pattern on the CHF prediction. - Highlights: •The general assumption of initial entrained fraction is unreasonable. •The droplets in churn flow show an inevitable effect on downstream annular flow. •The original liquid film flow model for prediction of CHF was developed. •The integration process was modified to start from the onset of churn flow

Predicting waist circumference from body mass index

Directory of Open Access Journals (Sweden)

Bozeman Samuel R

2012-08-01

Full Text Available Abstract Background Being overweight or obese increases risk for cardiometabolic disorders. Although both body mass index (BMI and waist circumference (WC measure the level of overweight and obesity, WC may be more important because of its closer relationship to total body fat. Because WC is typically not assessed in clinical practice, this study sought to develop and verify a model to predict WC from BMI and demographic data, and to use the predicted WC to assess cardiometabolic risk. Methods Data were obtained from the Third National Health and Nutrition Examination Survey (NHANES and the Atherosclerosis Risk in Communities Study (ARIC. We developed linear regression models for men and women using NHANES data, fitting waist circumference as a function of BMI. For validation, those regressions were applied to ARIC data, assigning a predicted WC to each individual. We used the predicted WC to assess abdominal obesity and cardiometabolic risk. Results The model correctly classified 88.4% of NHANES subjects with respect to abdominal obesity. Median differences between actual and predicted WC were − 0.07 cm for men and 0.11 cm for women. In ARIC, the model closely estimated the observed WC (median difference: − 0.34 cm for men, +3.94 cm for women, correctly classifying 86.1% of ARIC subjects with respect to abdominal obesity and 91.5% to 99.5% as to cardiometabolic risk. The model is generalizable to Caucasian and African-American adult populations because it was constructed from data on a large, population-based sample of men and women in the United States, and then validated in a population with a larger representation of African-Americans. Conclusions The model accurately estimates WC and identifies cardiometabolic risk. It should be useful for health care practitioners and public health officials who wish to identify individuals and populations at risk for cardiometabolic disease when WC data are unavailable.

Remote determination of the velocity index and mean streamwise velocity profiles

Science.gov (United States)

Johnson, E. D.; Cowen, E. A.

2017-09-01

When determining volumetric discharge from surface measurements of currents in a river or open channel, the velocity index is typically used to convert surface velocities to depth-averaged velocities. The velocity index is given by, k=Ub/Usurf, where Ub is the depth-averaged velocity and Usurf is the local surface velocity. The USGS (United States Geological Survey) standard value for this coefficient, k = 0.85, was determined from a series of laboratory experiments and has been widely used in the field and in laboratory measurements of volumetric discharge despite evidence that the velocity index is site-specific. Numerous studies have documented that the velocity index varies with Reynolds number, flow depth, and relative bed roughness and with the presence of secondary flows. A remote method of determining depth-averaged velocity and hence the velocity index is developed here. The technique leverages the findings of Johnson and Cowen (2017) and permits remote determination of the velocity power-law exponent thereby, enabling remote prediction of the vertical structure of the mean streamwise velocity, the depth-averaged velocity, and the velocity index.

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

Science.gov (United States)

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.

Prediction of postpercutaneous coronary intervention myocardial infarction: insights from intravascular imaging, coronary flow, and biomarker evaluation.

Science.gov (United States)

Hoole, Stephen P; Hernández-Sánchez, Jules; Brown, Adam J; Giblett, Joel P; Bennett, Martin R; West, Nick E J

2018-05-01

Percutaneous coronary intervention-induced myocardial infarction (PMI) has prognostic significance. Identifying patients at high risk for PMI is desirable as it may alter strategy and facilitate early preventative therapy. We therefore sought to establish whether preprocedural demographic, interventional (plaque characteristics and coronary microcirculatory function), and inflammatory, endothelial damage, and platelet-derived biomarker data could predict the risk of PMI. We performed target vessel pressure wire to assess fractional flow reserve, index of microcirculatory resistance (IMR) and coronary flow reserve, plaque characterization by virtual histology intravascular ultrasound, and assayed peripheral biomarkers before uncomplicated PCI in 88 patients. We then analyzed post-PCI cardiac troponin level to adjudicate PMI based on the third universal definition of myocardial infarction. Overall incidence of PMI was 27%. Women [10/15 (66%) vs. 14/73 (19%), PPMI. Preprocedural coronary flow reserve was lower in individuals with a subsequent PMI (1.8±1.2 vs. 2.1±1.3. P=0.03), and patients with higher pre-PCI IMR were more likely to sustain PMI [IMR>22: 10/23 (44%) vs. ≤22: 14/65 (22%), P=0.04], although neither was predictive after multivariate analysis. Plaque characterization by virtual histology intravascular ultrasound did not discriminate those at risk of PMI. However, peripheral venous interleukin (IL)-18 and IL-8 levels were independently negatively and positively associated with PMI, respectively. Women and those with low BMI, particularly when associated with high IL-8 and low IL-18 levels, appear to be at increased risk of PMI.

Early signs that predict later haemodynamically significant patent ductus arteriosus.

Science.gov (United States)

Engür, Defne; Deveci, Murat; Türkmen, Münevver K

2016-03-01

Our aim was to determine the optimal cut-off values, sensitivity, specificity, and diagnostic power of 12 echocardiographic parameters on the second day of life to predict subsequent ductal patency. We evaluated preterm infants, born at ⩽32 weeks of gestation, starting on their second day of life, and they were evaluated every other day until ductal closure or until there were clinical signs of re-opening. We measured transductal diameter; pulmonary arterial diastolic flow; retrograde aortic diastolic flow; pulsatility index of the left pulmonary artery and descending aorta; left atrium and ventricle/aortic root ratio; left ventricular output; left ventricular flow velocity time integral; mitral early/late diastolic flow; and superior caval vein diameter and flow as well as performed receiver operating curve analysis. Transductal diameter (>1.5 mm); pulmonary arterial diastolic flow (>25.6 cm/second); presence of retrograde aortic diastolic flow; ductal diameter by body weight (>1.07 mm/kg); left pulmonary arterial pulsatility index (⩽0.71); and left ventricle to aortic root ratio (>2.2) displayed high sensitivity and specificity (p0.9). Parameters with moderate sensitivity and specificity were as follows: left atrial to aortic root ratio; left ventricular output; left ventricular flow velocity time integral; and mitral early/late diastolic flow ratio (p0.05) had low diagnostic value. Left pulmonary arterial pulsatility index, left ventricle/aortic root ratio, and ductal diameter by body weight are useful adjuncts offering a broader outlook for predicting ductal patency.

A novel fibrosis index comprising a non-cholesterol sterol accurately predicts HCV-related liver cirrhosis.

Directory of Open Access Journals (Sweden)

Magdalena Ydreborg

Full Text Available Diagnosis of liver cirrhosis is essential in the management of chronic hepatitis C virus (HCV infection. Liver biopsy is invasive and thus entails a risk of complications as well as a potential risk of sampling error. Therefore, non-invasive diagnostic tools are preferential. The aim of the present study was to create a model for accurate prediction of liver cirrhosis based on patient characteristics and biomarkers of liver fibrosis, including a panel of non-cholesterol sterols reflecting cholesterol synthesis and absorption and secretion. We evaluated variables with potential predictive significance for liver fibrosis in 278 patients originally included in a multicenter phase III treatment trial for chronic HCV infection. A stepwise multivariate logistic model selection was performed with liver cirrhosis, defined as Ishak fibrosis stage 5-6, as the outcome variable. A new index, referred to as Nordic Liver Index (NoLI in the paper, was based on the model: Log-odds (predicting cirrhosis = -12.17+ (age × 0.11 + (BMI (kg/m(2 × 0.23 + (D7-lathosterol (μg/100 mg cholesterol×(-0.013 + (Platelet count (x10(9/L × (-0.018 + (Prothrombin-INR × 3.69. The area under the ROC curve (AUROC for prediction of cirrhosis was 0.91 (95% CI 0.86-0.96. The index was validated in a separate cohort of 83 patients and the AUROC for this cohort was similar (0.90; 95% CI: 0.82-0.98. In conclusion, the new index may complement other methods in diagnosing cirrhosis in patients with chronic HCV infection.

Parameter estimation techniques and uncertainty in ground water flow model predictions

International Nuclear Information System (INIS)

Zimmerman, D.A.; Davis, P.A.

1990-01-01

Quantification of uncertainty in predictions of nuclear waste repository performance is a requirement of Nuclear Regulatory Commission regulations governing the licensing of proposed geologic repositories for high-level radioactive waste disposal. One of the major uncertainties in these predictions is in estimating the ground-water travel time of radionuclides migrating from the repository to the accessible environment. The cause of much of this uncertainty has been attributed to a lack of knowledge about the hydrogeologic properties that control the movement of radionuclides through the aquifers. A major reason for this lack of knowledge is the paucity of data that is typically available for characterizing complex ground-water flow systems. Because of this, considerable effort has been put into developing parameter estimation techniques that infer property values in regions where no measurements exist. Currently, no single technique has been shown to be superior or even consistently conservative with respect to predictions of ground-water travel time. This work was undertaken to compare a number of parameter estimation techniques and to evaluate how differences in the parameter estimates and the estimation errors are reflected in the behavior of the flow model predictions. That is, we wished to determine to what degree uncertainties in flow model predictions may be affected simply by the choice of parameter estimation technique used. 3 refs., 2 figs

Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

International Nuclear Information System (INIS)

Ko, P; Kurosawa, S

2014-01-01

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

Numerical simulation of turbulence flow in a Kaplan turbine -Evaluation on turbine performance prediction accuracy-

Science.gov (United States)

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.

Using Cash Flows to Predict Bankruptcy of Chemical Companies: Case Study Approach

OpenAIRE

Siow, Hui Wen

2009-01-01

The intent of this study is to present an argument for the usefulness of cash flow information in bankruptcy prediction, and whether cash flow information provide a superior prediction of business failure over the conventional accrual accounting information. In addition, this dissertation also aim to analyze other important factors leading to bankruptcy, particularly contingent liabilities in which the obligations are not accrued and accounted for, nor are they considered in conventional bank...

Initial Self-Healing Temperatures of Asphalt Mastics Based on Flow Behavior Index

Directory of Open Access Journals (Sweden)

Chao Li

2018-05-01

Full Text Available Increasing temperature is a simple and convenient method to accelerate the self-healing process of bitumen. However, bitumen may not achieve the healing capability at lower temperature, and may be aged if temperature is too high. In addition, the bitumen is mixed with mineral filler and formed as asphalt mastic in asphalt concrete, so it is more accurate to study the initial self-healing from the perspective of asphalt mastic. The primary purpose of this research was to examine the initial self-healing temperature of asphalt mastic, which was determined by the flow behavior index obtained from the flow characteristics. Firstly, the texture and geometry characteristics of two fillers were analyzed, and then the initial self-healing temperature of nine types of asphalt mastic, pure bitumen (PB and styrene-butadiene-styrene (SBS modified bitumen were determined by the flow behavior index. Results demonstrate that the average standard deviation of gray-scale texture value of limestone filler (LF is 21.24% lower than that of steel slag filler (SSF, showing that the steel slag filler has a better particle distribution and geometry characteristics. Also the initial self-healing temperatures of asphalt mastics with 0.2, 0.4 and 0.6 LF-PB volume ratio are 46.5 °C, 47.2 °C and 49.4 °C, which are 1.4 °C, 0.8 °C and 0.4 °C higher than that of asphalt mastics with SSF-PB, but not suitable for the evaluation of asphalt mastic contained SBS modified bitumen because of unique structure and performance of SBS.

Prediction of unsteady separated flows on oscillating airfoils

Science.gov (United States)

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.

Fatty Liver Index and Lipid Accumulation Product Can Predict Metabolic Syndrome in Subjects without Fatty Liver Disease

Directory of Open Access Journals (Sweden)

Yuan-Lung Cheng

2017-01-01

Full Text Available Background. Fatty liver index (FLI and lipid accumulation product (LAP are indexes originally designed to assess the risk of fatty liver and cardiovascular disease, respectively. Both indexes have been proven to be reliable markers of subsequent metabolic syndrome; however, their ability to predict metabolic syndrome in subjects without fatty liver disease has not been clarified. Methods. We enrolled consecutive subjects who received health check-up services at Taipei Veterans General Hospital from 2002 to 2009. Fatty liver disease was diagnosed by abdominal ultrasonography. The ability of the FLI and LAP to predict metabolic syndrome was assessed by analyzing the area under the receiver operating characteristic (AUROC curve. Results. Male sex was strongly associated with metabolic syndrome, and the LAP and FLI were better than other variables to predict metabolic syndrome among the 29,797 subjects. Both indexes were also better than other variables to detect metabolic syndrome in subjects without fatty liver disease (AUROC: 0.871 and 0.879, resp., and the predictive power was greater among women. Conclusion. Metabolic syndrome increases the cardiovascular disease risk. The FLI and LAP could be used to recognize the syndrome in both subjects with and without fatty liver disease who require lifestyle modifications and counseling.

An index predictive of cognitive outcome in retired professional American Football players with a history of sports concussion.

Science.gov (United States)

Wright, Mathew J; Woo, Ellen; Birath, J Brandon; Siders, Craig A; Kelly, Daniel F; Wang, Christina; Swerdloff, Ronald; Romero, Elizabeth; Kernan, Claudia; Cantu, Robert C; Guskiewicz, Kevin

2016-01-01

Various concussion characteristics and personal factors are associated with cognitive recovery in athletes. We developed an index based on concussion frequency, severity, and timeframe, as well as cognitive reserve (CR), and we assessed its predictive power regarding cognitive ability in retired professional football players. Data from 40 retired professional American football players were used in the current study. On average, participants had been retired from football for 20 years. Current neuropsychological performances, indicators of CR, concussion history, and play data were used to create an index for predicting cognitive outcome. The sample displayed a range of concussions, concussion severities, seasons played, CR, and cognitive ability. Many of the participants demonstrated cognitive deficits. The index strongly predicted global cognitive ability (R(2) = .31). The index also predicted the number of areas of neuropsychological deficit, which varied as a function of the deficit classification system used (Heaton: R(2) = .15; Wechsler: R(2) = .28). The current study demonstrated that a unique combination of CR, sports concussion, and game-related data can predict cognitive outcomes in participants who had been retired from professional American football for an average of 20 years. Such indices may prove to be useful for clinical decision making and research.

Application of support vector regression (SVR) for stream flow prediction on the Amazon basin

CSIR Research Space (South Africa)

Du Toit, Melise

2016-10-01

Full Text Available regression technique is used in this study to analyse historical stream flow occurrences and predict stream flow values for the Amazon basin. Up to twelve month predictions are made and the coefficient of determination and root-mean-square error are used...

The predictive content of CBOE crude oil volatility index

Science.gov (United States)

Chen, Hongtao; Liu, Li; Li, Xiaolei

2018-02-01

Volatility forecasting is an important issue in the area of econophysics. The information content of implied volatility for financial return volatility has been well documented in the literature but very few studies focus on oil volatility. In this paper, we show that the CBOE crude oil volatility index (OVX) has predictive ability for spot volatility of WTI and Brent oil returns, from both in-sample and out-of-sample perspectives. Including OVX-based implied volatility in GARCH-type volatility models can improve forecasting accuracy most of time. The predictability from OVX to spot volatility is also found for longer forecasting horizons of 5 days and 20 days. The simple GARCH(1,1) and fractionally integrated GARCH with OVX performs significantly better than the other OVX models and all 6 univariate GARCH-type models without OVX. Robustness test results suggest that OVX provides different information from as short-term interest rate.

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Science.gov (United States)

Boonjing, Veera; Intakosum, Sarun

2016-01-01

This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid's prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span. PMID:27974883

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend

Directory of Open Access Journals (Sweden)

Montri Inthachot

2016-01-01

Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.

Modelling shallow landslide susceptibility by means of a subsurface flow path connectivity index and estimates of soil depth spatial distribution

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C. Lanni

2012-11-01

Full Text Available Topographic index-based hydrological models have gained wide use to describe the hydrological control on the triggering of rainfall-induced shallow landslides at the catchment scale. A common assumption in these models is that a spatially continuous water table occurs simultaneously across the catchment. However, during a rainfall event isolated patches of subsurface saturation form above an impeding layer and their hydrological connectivity is a necessary condition for lateral flow initiation at a point on the hillslope.

Here, a new hydrological model is presented, which allows us to account for the concept of hydrological connectivity while keeping the simplicity of the topographic index approach. A dynamic topographic index is used to describe the transient lateral flow that is established at a hillslope element when the rainfall amount exceeds a threshold value allowing for (a development of a perched water table above an impeding layer, and (b hydrological connectivity between the hillslope element and its own upslope contributing area. A spatially variable soil depth is the main control of hydrological connectivity in the model. The hydrological model is coupled with the infinite slope stability model and with a scaling model for the rainfall frequency–duration relationship to determine the return period of the critical rainfall needed to cause instability on three catchments located in the Italian Alps, where a survey of soil depth spatial distribution is available. The model is compared with a quasi-dynamic model in which the dynamic nature of the hydrological connectivity is neglected. The results show a better performance of the new model in predicting observed shallow landslides, implying that soil depth spatial variability and connectivity bear a significant control on shallow landsliding.

Prediction of clamp-derived insulin sensitivity from the oral glucose insulin sensitivity index

DEFF Research Database (Denmark)

Tura, Andrea; Chemello, Gaetano; Szendroedi, Julia

2018-01-01

that underwent both a clamp and an OGTT or meal test, thereby allowing calculation of both the M value and OGIS. The population was divided into a training and a validation cohort (n = 359 and n = 154, respectively). After a stepwise selection approach, the best model for M value prediction was applied......AIMS/HYPOTHESIS: The euglycaemic-hyperinsulinaemic clamp is the gold-standard method for measuring insulin sensitivity, but is less suitable for large clinical trials. Thus, several indices have been developed for evaluating insulin sensitivity from the oral glucose tolerance test (OGTT). However......, most of them yield values different from those obtained by the clamp method. The aim of this study was to develop a new index to predict clamp-derived insulin sensitivity (M value) from the OGTT-derived oral glucose insulin sensitivity index (OGIS). METHODS: We analysed datasets of people...

Sludge pipe flow pressure drop prediction using composite power ...

African Journals Online (AJOL)

2011-09-30

Sep 30, 2011 ... 3Department of Chemical Engineering, IIT Kanpur, India. Abstract. When predicting pressure gradients for the flow of sludges in pipes, the rheology of the fluid ..... implicit in the stability analysis of Ryan and Johnson (1959).

Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index

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Zhi-Chao Lai

2015-01-01

Full Text Available Background: Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA. An >100% increase in middle cerebral artery velocity (MCAV after CEA is used to predict the cerebral hyperperfusion syndrome (CHS development, but the accuracy is limited. The increase in blood pressure (BP after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. Methods: Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR] were compared for predicting CHS occurrence. Results: Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%. The area under the curve (AUC of receiver operating characteristic: AUC VBI = 0.981, 95% confidence interval [CI] 0.949-0.995; AUC VR = 0.935, 95% CI 0.890-0.966, P = 0.02. Conclusions: The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.

Prediction of Cerebral Hyperperfusion Syndrome with Velocity Blood Pressure Index.

Science.gov (United States)

Lai, Zhi-Chao; Liu, Bao; Chen, Yu; Ni, Leng; Liu, Chang-Wei

2015-06-20

Cerebral hyperperfusion syndrome is an important complication of carotid endarterectomy (CEA). An >100% increase in middle cerebral artery velocity (MCAV) after CEA is used to predict the cerebral hyperperfusion syndrome (CHS) development, but the accuracy is limited. The increase in blood pressure (BP) after surgery is a risk factor of CHS, but no study uses it to predict CHS. This study was to create a more precise parameter for prediction of CHS by combined the increase of MCAV and BP after CEA. Systolic MCAV measured by transcranial Doppler and systematic BP were recorded preoperatively; 30 min postoperatively. The new parameter velocity BP index (VBI) was calculated from the postoperative increase ratios of MCAV and BP. The prediction powers of VBI and the increase ratio of MCAV (velocity ratio [VR]) were compared for predicting CHS occurrence. Totally, 6/185 cases suffered CHS. The best-fit cut-off point of 2.0 for VBI was identified, which had 83.3% sensitivity, 98.3% specificity, 62.5% positive predictive value and 99.4% negative predictive value for CHS development. This result is significantly better than VR (33.3%, 97.2%, 28.6% and 97.8%). The area under the curve (AUC) of receiver operating characteristic: AUC(VBI) = 0.981, 95% confidence interval [CI] 0.949-0.995; AUC(VR) = 0.935, 95% CI 0.890-0.966, P = 0.02. The new parameter VBI can more accurately predict patients at risk of CHS after CEA. This observation needs to be validated by larger studies.

Numerical Predictions of Enhanced Impingement Jet Cooling with Ribs and Pins in Co-Flow and Cross-Flow Configurations

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A. M. El-Jummah

2017-02-01

Full Text Available Numerical calculations relevant to gas turbine internal wall heat transfer cooling were conducted using conjugate heat transfer (CHT computational Fluid Dynamics (CFD commercial codes. The CHT CFD predictions were carried out for impingement heat transfer with different types of obstacle walls (fins on the target surfaces. A 10 × 10 row of impingement air jet holes (or hole density n of 4306 m-2 was used, which gives ten rows of holes in the cross-flow direction and only one heat transfer enhancement obstacle per impingement jet was investigated. Previously, four different shaped obstacles were investigated experimentally and were used to validate the present predictions. The obstacle walls, which were equally spaced on the centreline between each impingement jet are of the co-flow and cross-flow configurations. The impingement jet pitch X to diameter D, X/D and gap Z to diameter, Z/D ratios were kept constant at 4.66 and 3.06 for X, Z and D of 15.24, 10.00 and 3.27 mm, respectively. The obstacles investigated were ribs and rectangular pin-fins shapes, using two obstacles height H to diameter, H/D ratio of 1.38 and 2.45. Computations were carried out for three different mass flux G of 1.08, 1.48 and 1.94 kg/sm2. Relative pressure loss ∆P/P and surface average heat transfer coefficient (HTC h predictions for the range of G, showed good agreement with the experimental results. The prediction also reveals that obstacles not only increases the turbulent flows, but also takes away most of the cooling heat transfer that produces the regions with highest thermal gradients. It also reduces the impingement gap downstream cross-flow.

Numerical predictions and measurements of Reynolds normal stresses in turbulent pipe flow of polymers

Energy Technology Data Exchange (ETDEWEB)

Resende, P.R. [Centro de Estudos de Fenomenos de Transporte, DEMEGI, Faculdade de Engenharia, Universidade do Porto, Rua Dr. Roberto Frias s/n, 4200-465 Porto (Portugal)]. E-mail: resende@fe.up.pt; Escudier, M.P. [Department of Engineering, University of Liverpool, Brownlow Street, Liverpool L69 3GH (United Kingdom)]. E-mail: escudier@liv.ac.uk; Presti, F [Department of Engineering, University of Liverpool, Brownlow Street, Liverpool L69 3GH (United Kingdom); Pinho, F.T. [Centro de Estudos de Fenomenos de Transporte, DEM, Universidade do Minho Campus de Azurem, 4800-058 Guimaraes (Portugal)]. E-mail: fpinho@dem.uminho.pt; Cruz, D.O.A. [Departamento de Engenharia Mecanica, Universidade Federal do Para-UFPa Campus Universitario do Guama, 66075-900 Belem, Para (Brazil)]. E-mail: doac@ufpa.br

2006-04-15

An anisotropic low Reynolds number k-{epsilon} turbulence model has been developed and its performance compared with experimental data for fully-developed turbulent pipe flow of four different polymer solutions. Although the predictions of friction factor, mean velocity and turbulent kinetic energy show only slight improvements over those of a previous isotropic model [Cruz, D.O.A., Pinho, F.T., Resende, P.R., 2004. Modeling the new stress for improved drag reduction predictions of viscoelastic pipe flow. J. Non-Newt. Fluid Mech. 121, 127-141], the new turbulence model is capable of predicting the enhanced anisotropy of the Reynolds normal stresses that accompanies polymer drag reduction in turbulent flow.

Numerical predictions and measurements of Reynolds normal stresses in turbulent pipe flow of polymers

International Nuclear Information System (INIS)

Resende, P.R.; Escudier, M.P.; Presti, F; Pinho, F.T.; Cruz, D.O.A.

2006-01-01

An anisotropic low Reynolds number k-ε turbulence model has been developed and its performance compared with experimental data for fully-developed turbulent pipe flow of four different polymer solutions. Although the predictions of friction factor, mean velocity and turbulent kinetic energy show only slight improvements over those of a previous isotropic model [Cruz, D.O.A., Pinho, F.T., Resende, P.R., 2004. Modeling the new stress for improved drag reduction predictions of viscoelastic pipe flow. J. Non-Newt. Fluid Mech. 121, 127-141], the new turbulence model is capable of predicting the enhanced anisotropy of the Reynolds normal stresses that accompanies polymer drag reduction in turbulent flow

Analytical method for predicting plastic flow in notched fiber composite materials

International Nuclear Information System (INIS)

Flynn, P.L.; Ebert, L.J.

1977-01-01

An analytical system was developed for prediction of the onset and progress of plastic flow of oriented fiber composite materials in which both externally applied complex stress states and stress raisers were present. The predictive system was a unique combination of two numerical systems, the ''SAAS II'' finite element analysis system and a micromechanics finite element program. The SAAS II system was used to generate the three-dimensional stress distributions, which were used as the input into the finite element micromechanics program. Appropriate yielding criteria were then applied to this latter program. The accuracy of the analytical system was demonstrated by the agreement between the analytically predicted and the experimentally measured flow values of externally notched tungsten wire reinforced copper oriented fiber composites, in which the fiber fraction was 50 vol pct

The Doppler echocardiographic myocardial performance index predicts left-ventricular dilation and cardiac death after myocardial infarction

DEFF Research Database (Denmark)

Møller, J E; Søndergaard, E; Poulsen, S H

2001-01-01

To investigate the value of the Doppler-derived myocardial performance index to predict early left-ventricular (LV) dilation and cardiac death after a first acute myocardial infarction (AMI), Doppler echocardiography was performed within 24 h of hospital admission, on day 5, 1 and 3 months after...... AMI in 125 consecutive patients. The index measured on day 1 correlated well with the change in end-diastolic volume index observed from day 1 to 3 months following AMI (r = 0.66, p 0.0001). One-year survival in patients with Doppler index index > or = 0......, we conclude that the Doppler echocardiographic myocardial performance index is a predictor of LV dilation and cardiac death after a first AMI....

Modelling for the Stripa site characterization and validation drift inflow: prediction of flow through fractured rock

International Nuclear Information System (INIS)

Herbert, A.; Gale, J.; MacLeod, R.; Lanyon, G.

1991-12-01

We present our approach to predicting flow through a fractured rock site; the site characterization and validation region in the Stripa mine. Our approach is based on discrete fracture network modelling using the NAPSAC computer code. We describe the conceptual models and assumptions that we have used to interpret the geometry and flow properties of the fracture networks, from measurements at the site. These are used to investigate large scale properties of the network and we show that for flows on scales larger than about 10 m, porous medium approximation should be used. The porous medium groundwater flow code CFEST is used to predict the large scale flows through the mine and the SCV region. This, in turn, is used to provide boundary conditions for more detailed models, which predict the details of flow, using a discrete fracture network model, on scales of less than 10 m. We conclude that a fracture network approach is feasible and that it provides a better understanding of details of flow than conventional porous medium approaches and a quantification of the uncertainty associated with predictive flow modelling characterised from field measurement in fractured rock. (au)

Predictive performance of the visceral adiposity index for a visceral adiposity-related risk: Type 2 Diabetes

Directory of Open Access Journals (Sweden)

Azizi Fereidoun

2011-05-01

Full Text Available Abstract Background Visceral adiposity index (VAI has recently been developed based on waist circumference, body mass index (BMI, triglycerides (TGs, and high-density lipoprotein cholesterol (HDL-C. We examined predictive performances for incident diabetes of the VAI per se and as compared to the metabolic syndrome (MetS and waist-to-height-ratio (WHtR. Methods Participants free of diabetes at baseline with at least one follow-up examination (5,964 were included for the current study. Weibull regression models were developed for interval-censored survival data. Absolute and relative integrated discriminatory improvement index (IDI and cut-point-based and cut-point-free net reclassification improvement index (NRI were used as measures of predictive ability for incident diabetes added by VAI, as compared to the MetS and WHtR. Results The annual incidence rate of diabetes was 0.85 per 1000 person. Mean VAI was 3.06 (95%CIs 2.99-3.13. Diabetes risk factors levels increased in stepwise fashion across VAI quintiles. Risk gradient between the highest and lowest quintile of VAI was 4.5 (95%CIs 3.0-6.9. VAI significantly improved predictive ability of the MetS. The relative IDI and cut-point free NRI for predictive ability added to MetS by VAI were 30.3% (95%CIs 18.8-41.8% and 30.7% (95%CIs 20.8-40.7%, respectively. WHtR, outperformed VAI with cut-point-free NRI of 24.6% (95%CIs 14.1-35.2%. Conclusions In conclusion, although VAI could be a prognostic tool for incident diabetes events, gathering information on its components (WC, BMI, TGs, and HDL-C is unlikely to improve the prediction ability beyond what could be achieved by the simply assessable and commonly available information on WHtR.

Contingency management of power system with Interline Power Flow Controller using Real Power Performance Index and Line Stability Index

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Akanksha Mishra

2016-03-01

Full Text Available As a result of privatization of the electrical industry the power transmission lines have to transfer power at their maximum transmission limits because of the competitive scenario of the electrical market. Hence, secured operation of power system has become one of the most important issues of modern era. In this paper, a probability of severity based placement strategy for Interline Power Flow Controller (IPFC has been proposed based on Composite Severity Index (CSI. The composite severity index provides an exact measure of stress in the line in terms of mega watt overloading and voltage instability. IPFC is placed on the line which has the highest probability of severity during the occurrence of different outages. The IPFC has been tuned for a multi-objective function using Differential Evolution (DE and the results have been compared with genetic Algorithm (GA. To verify the proposed method, it has been tested and implemented on IEEE 14 and 57 bus systems.

Contribution of spiral artery blood flow changes assessed by transvaginal color Doppler sonography for predicting endometrial pathologies

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Suna Kabil Kucur

2013-01-01

Full Text Available ive: To investigate the diagnostic value of blood flow measurements in spiral artery by transvaginal color Doppler sonography (CDS in predicting endometrial pathologies.Methods: Ninety-seven patients presenting with abnormal uterine bleeding and requiring endometrial assessment were included in this prospective observational study. Endometrial thickness, structure and echogenicity were recorded. Pulsatility index (PI and resistive index (RI of the spiral artery were measured by transvaginal CDS. Endometrial sampling was performed for all subjects. Sonographic and hystopathologic findings were compared.Results: The histopathological diagnoses were as follows; 39 cases (40.2% endometrial polyp, 9 cases (9.3% endometrial hyperplasia, 10 cases (10.3 submucous myoma, 7 cases (7.2% endometrium cancer, and 32 cases (33% nonspecific findings. The spiral artery PI in endometrium cancer group was highly significantly lower than other groups (p<0.01. The spiral artery RI was also significantly lower in the patients with malignant histology (p<0.05. Conclusion: Endometrial pathologies are associated significantly with endometrial spiral artery Doppler changes.Key words: Spiral artery, Doppler ultrasonography, endometrium

Predicting Jakarta composite index using hybrid of fuzzy time series and support vector regression models

Science.gov (United States)

Febrian Umbara, Rian; Tarwidi, Dede; Budi Setiawan, Erwin

2018-03-01

The paper discusses the prediction of Jakarta Composite Index (JCI) in Indonesia Stock Exchange. The study is based on JCI historical data for 1286 days to predict the value of JCI one day ahead. This paper proposes predictions done in two stages., The first stage using Fuzzy Time Series (FTS) to predict values of ten technical indicators, and the second stage using Support Vector Regression (SVR) to predict the value of JCI one day ahead, resulting in a hybrid prediction model FTS-SVR. The performance of this combined prediction model is compared with the performance of the single stage prediction model using SVR only. Ten technical indicators are used as input for each model.

Assessment of NASA and RAE viscous-inviscid interaction methods for predicting transonic flow over nozzle afterbodies

Science.gov (United States)

Putnam, L. E.; Hodges, J.

1983-01-01

The Langley Research Center of the National Aeronautics and Space Administration and the Royal Aircraft Establishment have undertaken a cooperative program to conduct an assessment of their patched viscous-inviscid interaction methods for predicting the transonic flow over nozzle afterbodies. The assessment was made by comparing the predictions of the two methods with experimental pressure distributions and boattail pressure drag for several convergent circular-arc nozzle configurations. Comparisons of the predictions of the two methods with the experimental data showed that both methods provided good predictions of the flow characteristics of nozzles with attached boundary layer flow. The RAE method also provided reasonable predictions of the pressure distributions and drag for the nozzles investigated that had separated boundary layers. The NASA method provided good predictions of the pressure distribution on separated flow nozzles that had relatively thin boundary layers. However, the NASA method was in poor agreement with experiment for separated nozzles with thick boundary layers due primarily to deficiencies in the method used to predict the separation location.

CFD Analysis for Predicting Flow Resistance of the Cross Flow Gap in Prismatic VHTR Core

International Nuclear Information System (INIS)

Lee, Jeong Hun; Yoon, Su Jong; Park, Goon Cherl; Park, Jong Woon

2011-01-01

The core of Very High Temperature Reactor (VHTR) consists of assemblies of hexagonal graphite blocks and its height and across-flats width are 800 mm and 360 mm respectively. They are equipped with 108 coolant holes 16 mm in diameter. Up to ten fuel blocks arranged in vertical order form a fuel element column and the neutron flux varies over the cross section of the core. It makes different axial shrinkage of fuel element and this leads to make wedge-shaped gaps between the base and top surfaces of stacked blocks. The cross flow is defined as the core flow that passes through this cross gaps. The cross flow complicates the flow distribution of reactor core. Moreover, the cross flow could lead to uneven coolant distribution and consequently to superheating of individual fuel element zones with increased fission product release. Since the core cross flow has a negative impact on safety and efficiency of VHTR, core cross flow phenomena have to be investigated to improve the core thermal margin of VHTR. In particular, to predict amount of flow at the cross flow gap obtaining accurate flow loss coefficient is important. Nevertheless, there has not been much effort in domestic. The experiment of cross flow was carried out by H. G. Groehn in 1981 Germany. For the study of cross flow the applicability of CFD code should be validated. In this paper a commercial CFD code CFX-12 validation will be carried out with this cross flow experiment. Validated data can be used for validation of other thermal-hydraulic analysis codes

An efficient link prediction index for complex military organization

Science.gov (United States)

Fan, Changjun; Liu, Zhong; Lu, Xin; Xiu, Baoxin; Chen, Qing

2017-03-01

Quality of information is crucial for decision-makers to judge the battlefield situations and design the best operation plans, however, real intelligence data are often incomplete and noisy, where missing links prediction methods and spurious links identification algorithms can be applied, if modeling the complex military organization as the complex network where nodes represent functional units and edges denote communication links. Traditional link prediction methods usually work well on homogeneous networks, but few for the heterogeneous ones. And the military network is a typical heterogeneous network, where there are different types of nodes and edges. In this paper, we proposed a combined link prediction index considering both the nodes' types effects and nodes' structural similarities, and demonstrated that it is remarkably superior to all the 25 existing similarity-based methods both in predicting missing links and identifying spurious links in a real military network data; we also investigated the algorithms' robustness under noisy environment, and found the mistaken information is more misleading than incomplete information in military areas, which is different from that in recommendation systems, and our method maintained the best performance under the condition of small noise. Since the real military network intelligence must be carefully checked at first due to its significance, and link prediction methods are just adopted to purify the network with the left latent noise, the method proposed here is applicable in real situations. In the end, as the FINC-E model, here used to describe the complex military organizations, is also suitable to many other social organizations, such as criminal networks, business organizations, etc., thus our method has its prospects in these areas for many tasks, like detecting the underground relationships between terrorists, predicting the potential business markets for decision-makers, and so on.

Simple Modification of the Bladder Outlet Obstruction Index for Better Prediction of Endoscopically-Proven Prostatic Obstruction: A Preliminary Study.

Directory of Open Access Journals (Sweden)

Jang Hee Han

Full Text Available The bladder outlet obstruction index (BOOI, also known as the Abrams-Griffiths (AG number, is the most widely used index for predicting BOO. However, the obstructed prostatic urethra determined by the BOOI is often inconsistent with endoscopically-proven obstruction. We assessed abdominal straining pattern as a novel parameter for improving the prediction of BOO.We retrospectively reviewed the pressure-flow studies (PFS and cystourethroscopy in 176 BPH/LUTS patients who were unresponsive to medical therapy. During PFS, some groups of patients tried to urinate with abdominal straining, which can increases intravesical pressure and underestimate BOOI theoretically. Accordingly, the modified BOOI was defined as (PdetQmax+ΔPabd-2Qmax.Ultimately, 130 patients were eligible for the analysis. In PFS, ΔPabd (PabdQmax-initial Pabd was 11.81±13.04 cmH2O, and it was 0-9 cmH2O in 75 (57.7%, 10-19 cmH2O in 23 (17.7% and ≥20 cmH2O in 32 (24.6% patients. An endoscopically obstructed prostatic urethra in 92 patients was correctly determined in 47 patients (51.1% by the original BOOI versus 72 patients (78.3% based on the modified BOOI. Meanwhile, an "unobstructed" urethra according to the original BOOI was present in 11 patients (12.0%, whereas according to the modified BOOI, only 2 (2.1% would be labeled as "unobstructed". In receiver operating characteristic curves, the area under the curve was 0.906 using the modified BOOI number versus 0.849 in the original BOOI (p<0.05.The change in abdominal pressure was correlated with endoscopically-proven obstruction. Our simple modification of the BOOI on the basis of this finding better predicted bladder outlet obstruction and, therefore, should be considered when evaluating BOO in patients with LUTS/BPH.

Prediction of adiabatic bubbly flows in TRACE using the interfacial area transport equation

International Nuclear Information System (INIS)

Talley, J.; Worosz, T.; Kim, S.; Mahaffy, J.; Bajorek, S.; Tien, K.

2011-01-01

The conventional thermal-hydraulic reactor system analysis codes utilize a two-field, two-fluid formulation to model two-phase flows. To close this model, static flow regime transition criteria and algebraic relations are utilized to estimate the interfacial area concentration (a i ). To better reflect the continuous evolution of two-phase flow, an experimental version of TRACE is being developed which implements the interfacial area transport equation (IATE) to replace the flow regime based approach. Dynamic estimation of a i is provided through the use of mechanistic models for bubble coalescence and disintegration. To account for the differences in bubble interactions and drag forces, two-group bubble transport is sought. As such, Group 1 accounts for the transport of spherical and distorted bubbles, while Group 2 accounts for the cap, slug, and churn-turbulent bubbles. Based on this categorization, a two-group IATE applicable to the range of dispersed two-phase flows has been previously developed. Recently, a one-group, one-dimensional, adiabatic IATE has been implemented into the TRACE code with mechanistic models accounting for: (1) bubble breakup due to turbulent impact of an eddy on a bubble, (2) bubble coalescence due to random collision driven by turbulent eddies, and (3) bubble coalescence due to the acceleration of a bubble in the wake region of a preceding bubble. To demonstrate the enhancement of the code's capability using the IATE, experimental data for a i , void fraction, and bubble velocity measured by a multi-sensor conductivity probe are compared to both the IATE and flow regime based predictions. In total, 50 air-water vertical co-current upward and downward bubbly flow conditions in pipes with diameters ranging from 2.54 to 20.32 cm are evaluated. It is found that TRACE, using the conventional flow regime relation, always underestimates a i . Moreover, the axial trend of the a i prediction is always quasi-linear because a i in the

Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

Directory of Open Access Journals (Sweden)

Zhaosheng Yang

2014-01-01

Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

Linear predictions of supercritical flow instability in two parallel channels

International Nuclear Information System (INIS)

Shah, M.

2008-01-01

A steady state linear code that can predict thermo-hydraulic instability boundaries in a two parallel channel system under supercritical conditions has been developed. Linear and non-linear solutions of the instability boundary in a two parallel channel system are also compared. The effect of gravity on the instability boundary in a two parallel channel system, by changing the orientation of the system flow from horizontal flow to vertical up-flow and vertical down-flow has been analyzed. Vertical up-flow is found to be more unstable than horizontal flow and vertical down flow is found to be the most unstable configuration. The type of instability present in each flow-orientation of a parallel channel system has been checked and the density wave oscillation type is observed in horizontal flow and vertical up-flow, while the static type of instability is observed in a vertical down-flow for the cases studied here. The parameters affecting the instability boundary, such as the heating power, inlet temperature, inlet and outlet K-factors are varied to assess their effects. This study is important for the design of future Generation IV nuclear reactors in which supercritical light water is proposed as the primary coolant. (author)

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

Science.gov (United States)

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.

Fatty liver index and hepatic steatosis index for prediction of non-alcoholic fatty liver disease in type 1 diabetes.

Science.gov (United States)

Sviklāne, Laura; Olmane, Evija; Dzērve, Zane; Kupčs, Kārlis; Pīrāgs, Valdis; Sokolovska, Jeļizaveta

2018-01-01

Little is known about the diagnostic value of hepatic steatosis index (HSI) and fatty liver index (FLI), as well as their link to metabolic syndrome in type 1 diabetes mellitus. We have screened the effectiveness of FLI and HSI in an observational pilot study of 40 patients with type 1 diabetes. FLI and HSI were calculated for 201 patients with type 1 diabetes. Forty patients with FLI/HSI values corresponding to different risk of liver steatosis were invited for liver magnetic resonance study. In-phase/opposed-phase technique of magnetic resonance was used. Accuracy of indices was assessed from the area under the receiver operating characteristic curve. Twelve (30.0%) patients had liver steatosis. For FLI, sensitivity was 90%; specificity, 74%; positive likelihood ratio, 3.46; negative likelihood ratio, 0.14; positive predictive value, 0.64; and negative predictive value, 0.93. For HSI, sensitivity was 86%; specificity, 66%; positive likelihood ratio, 1.95; negative likelihood ratio, 0.21; positive predictive value, 0.50; and negative predictive value, 0.92. Area under the receiver operating characteristic curve for FLI was 0.86 (95% confidence interval [0.72; 0.99]); for HSI 0.75 [0.58; 0.91]. Liver fat correlated with liver enzymes, waist circumference, triglycerides, and C-reactive protein. FLI correlated with C-reactive protein, liver enzymes, and blood pressure. HSI correlated with waist circumference and C-reactive protein. FLI ≥ 60 and HSI ≥ 36 were significantly associated with metabolic syndrome and nephropathy. The tested indices, especially FLI, can serve as surrogate markers for liver fat content and metabolic syndrome in type 1 diabetes. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Predicting changes in flow category in patients with severe aortic stenosis and preserved left ventricular ejection fraction on medical therapy.

Science.gov (United States)

Ngiam, Jinghao Nicholas; Kuntjoro, Ivandito; Tan, Benjamin Y Q; Sim, Hui-Wen; Kong, William K F; Yeo, Tiong-Cheng; Poh, Kian-Keong

2017-11-01

Controversy surrounds the prognosis and management of patients with paradoxical low-flow severe aortic stenosis (AS) with preserved left ventricular ejection fraction (LVEF). It was not certain if patients in a particular flow category remained in the same category as disease progressed. We investigated whether there were switches in categories and if so, their predictors. Consecutive subjects (n = 203) with isolated severe AS and paired echocardiography (>180 days apart) were studied. They were divided into 4 groups, based on their flow categories and if they progressed on subsequent echocardiography to switch or remain in the same flow category. Univariate analyses of clinical and echocardiographic parameters identified predictors of these changes in flow category. One hundred eighteen were normal flow (SVI ≥ 35 mL/m 2 ), while 85 were low flow on index echocardiography. In the patients with normal flow, 33% switched to low flow. This was associated with higher valvuloarterial impedance (Zva, P 4.77 mm Hg/mL/m 2 , AUC = 0.81 [95% CI:0.75-0.87, P < .001]). In patients with low flow, 25% switched to normal flow, which was associated with lower Zva and higher SAC and the switch was predicted by a higher initial mean transaortic pressure gradient. A significant number of patients switched flow categories in severe AS with preserved LVEF on subsequent echocardiography. Changes in flow were reflected by respective changes in Zva and SAC. Identifying echocardiographic predictors of a switch in category may guide prognostication and management of such patients. © 2017, Wiley Periodicals, Inc.

The Asymmetric Predictive Effects of Investor Sentiment

DEFF Research Database (Denmark)

Lutz, Chandler

investors only act as corrective force during certain time periods. We also show that our index predicts implied volatility, media pessimism, and mutual fund flows. Overall, our findings are consistent with both the theories and anecdotal accounts of investor sentiment in the stock market....

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

Science.gov (United States)

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.

Predicting pavement condition index using international roughness index in Washington DC.

Science.gov (United States)

2014-09-01

A number of pavement condition indices are used to conduct pavement management assessments, two of which are the : International Roughness Index (IRI) and Pavement Condition Index (PCI). The IRI is typically measured using specialized : equipment tha...

What Do They Have in Common? Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes in Ungauged Locations

Science.gov (United States)

Betterle, A.; Radny, D.; Schirmer, M.; Botter, G.

2017-12-01

The spatial correlation of daily streamflows represents a statistical index encapsulating the similarity between hydrographs at two arbitrary catchment outlets. In this work, a process-based analytical framework is utilized to investigate the hydrological drivers of streamflow spatial correlation through an extensive application to 78 pairs of stream gauges belonging to 13 unregulated catchments in the eastern United States. The analysis provides insight on how the observed heterogeneity of the physical processes that control flow dynamics ultimately affect streamflow correlation and spatial patterns of flow regimes. Despite the variability of recession properties across the study catchments, the impact of heterogeneous drainage rates on the streamflow spatial correlation is overwhelmed by the spatial variability of frequency and intensity of effective rainfall events. Overall, model performances are satisfactory, with root mean square errors between modeled and observed streamflow spatial correlation below 10% in most cases. We also propose a method for estimating streamflow correlation in the absence of discharge data, which proves useful to predict streamflow regimes in ungauged areas. The method consists in setting a minimum threshold on the modeled flow correlation to individuate hydrologically similar sites. Catchment outlets that are most correlated (ρ>0.9) are found to be characterized by analogous streamflow distributions across a broad range of flow regimes.

Simple methods for predicting gas leakage flows through cracks

International Nuclear Information System (INIS)

Ewing, D.J.F.

1989-01-01

This report presents closed-form approximate analytical formulae with which the flow rate out of a through-wall crack can be estimated. The crack is idealised as a rough, tapering, wedgeshaped channel and the fluid is idealised as an isothermal or polytropically-expanding perfect gas. In practice, uncertainties about the wall friction factor dominate over uncertainties caused by the fluid-dynamics simplifications. The formulae take account of crack taper and for outwardly-diverging cracks they predict flows within 12% of mathematically more accurate one-dimensional numerical models. Upper and lower estimates of wall friction are discussed. (author)

The TyG index may predict the development of cardiovascular events.

Science.gov (United States)

Sánchez-Íñigo, Laura; Navarro-González, David; Fernández-Montero, Alejandro; Pastrana-Delgado, Juan; Martínez, Jose Alfredo

2016-02-01

Cardiovascular disease (CVD) is the worldwide leading cause of morbidity and mortality. An early risk detection of apparently healthy people before CVD onset has clinical relevance in the prevention of cardiovascular events. We evaluated the association between the product of fasting plasma glucose and triglycerides (TyG index) and CVD. A total of 5014 patients of the Vascular Metabolic CUN cohort (VMCUN cohort) were followed up during a median period of 10 years. We used a Cox proportional-hazard ratio with repeated measures to estimate the risk of incidence of CVD across quintiles of the TyG index, calculated as ln[fasting triglycerides (mg/dL) × fasting plasma glucose (mg(dL)/2], and plotted a receiver-operating characteristics (ROC) curve to compare a prediction model fitted on the variables used in the Framingham risk score, a new model containing the Framingham variables with the TyG index, and the risk of coronary heart disease. A higher level of TyG index was significantly associated with an increased risk of developing CVD independent of confounding factors with a value of 2·32 (95% CI: 1·65-3·26) for those in the highest quintile and 1·52 (95% CI: 1·07-2·16) for those in the fourth quintile. The areas under the curve (AUC) of the ROC plots were 0·708 (0·68-0·73) for the Framingham model and 0·719 (0·70-0·74) for the Framingham + TyG index model (P = 0·014). The TyG index, a simple measure reflecting insulin resistance, might be useful to early identify individuals at a high risk of developing a cardiovascular event. © 2015 Stichting European Society for Clinical Investigation Journal Foundation.

Automated system for load flow prediction in power substations using artificial neural networks

Directory of Open Access Journals (Sweden)

Arlys Michel Lastre Aleaga

2015-09-01

Full Text Available The load flow is of great importance in assisting the process of decision making and planning of generation, distribution and transmission of electricity. Ignorance of the values in this indicator, as well as their inappropriate prediction, difficult decision making and efficiency of the electricity service, and can cause undesirable situations such as; the on demand, overheating of the components that make up a substation, and incorrect planning processes electricity generation and distribution. Given the need for prediction of flow of electric charge of the substations in Ecuador this research proposes the concept for the development of an automated prediction system employing the use of Artificial Neural Networks.

Resistive index(RI) of the intratesticular artery in orchitis: comparison with normal testis

International Nuclear Information System (INIS)

Yang, Dal Mo; Kim, Hyung Sik; Lee, Young Seok; Yoon, Myung Hwan; Lee, Jong Bouk; Yun, Jung Chul

1994-01-01

Color doppler ultrasound is ideally suited for diagnosing acute scrotal disease as it provides simultaneous display of tissue morphology and blood flow. This study was performed in order to evaluate the utility of resistive index(RI) of intratesticular arteries in orchitis. We retrospectively analyzed 18 testes of 15 patients confirmed by means of appropriate response to antibiotic treatment and 20 testes of 10 asymptomatic volunteers.The resistive indexes ranged from 0.25 to 0.60 (mean, 0.48) in orchitis, and from 0.50 to 0.71 (mean, 0.62) in volunteers. Thus, the resistive index in orchitis is significantly lower than that of the volunteers (p<0.05).With a cut-off point of resistive index at 0.6, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 94%, 90%, 89%, 95% and 92%m respectively. We conclude that decreased resistive index is a helpful finding in the diagnosis of orchitis, and we suggest the resistive index of 0.6 as a cut-off point

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

Science.gov (United States)

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.

Climate change sensitivity index for Pacific salmon habitat in southeast Alaska.

Directory of Open Access Journals (Sweden)

Colin S Shanley

Full Text Available Global climate change may become one of the most pressing challenges to Pacific Salmon conservation and management for southeast Alaska in the 21st Century. Predicted hydrologic change associated with climate change will likely challenge the ability of specific stocks to adapt to new flow regimes and resulting shifts in spawning and rearing habitats. Current research suggests egg-to-fry survival may be one of the most important freshwater limiting factors in Pacific Salmon's northern range due to more frequent flooding events predicted to scour eggs from mobile spawning substrates. A watershed-scale hydroclimatic sensitivity index was developed to map this hypothesis with an historical stream gauge station dataset and monthly multiple regression-based discharge models. The relative change from present to future watershed conditions predicted for the spawning and incubation period (September to March was quantified using an ensemble global climate model average (ECHAM5, HadCM3, and CGCM3.1 and three global greenhouse gas emission scenarios (B1, A1B, and A2 projected to the year 2080. The models showed the region's diverse physiography and climatology resulted in a relatively predictable pattern of change: northern mainland and steeper, snow-fed mountainous watersheds exhibited the greatest increases in discharge, an earlier spring melt, and a transition into rain-fed hydrologic patterns. Predicted streamflow increases for all watersheds ranged from approximately 1-fold to 3-fold for the spawning and incubation period, with increased peak flows in the spring and fall. The hydroclimatic sensitivity index was then combined with an index of currently mapped salmon habitat and species diversity to develop a research and conservation priority matrix, highlighting potentially vulnerable to resilient high-value watersheds. The resulting matrix and observed trends are put forth as a framework to prioritize long-term monitoring plans, mitigation

Predictions of the Bypass Flows in the HTR-PM Reactor Core

International Nuclear Information System (INIS)

Sun Jun; Chen Zhipeng; Zheng Yanhua; Shi Lei; Li Fu

2014-01-01

In the HTR-PM reactor core, the basic structure materials are large amount of graphite reflectors and carbon bricks. Small gaps among those graphite and carbon bricks are widespread in the reactor core so that the cold helium flow may be bypassed and not completely heated. The bypass flows in relative lower temperature would change the flow and temperature distributions in the reactor core, therefore, the accurate prediction of bypass flows need to be carried out carefully to evaluate the influence to the reactor safety. Based on the characteristics of the bypass flow problem, hybrid method of the flow network and the CFD tools was employed to represent the connections and calculate flow distributions of all the main flow and bypass flow paths. In this paper, the hybrid method was described and applied to specific bypass flow problem in the HTR-PM. Various bypass flow paths in the HTR-PM were reviewed, figured out, and modeled by the flow network and the CFD methods, including the axial vertical gaps in the side reflectors, control rod channels, absorber sphere channels and radial gap flow through keys around the hot helium plenum. The bypass flow distributions and its flow rate ratio to the total flow rate in the primary loop were also calculated, discussed and evaluated. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A [Duke University Medical Center, Durham, NC (United States); Ge, Y [University of North Carolina at Charlotte, Charlotte, NC (United States)

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 five 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

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

International Nuclear Information System (INIS)

Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

2014-01-01

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 five 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

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

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

Andrew J Reagan

Full Text Available 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.

Theoretical prediction method of subcooled flow boiling CHF

Energy Technology Data Exchange (ETDEWEB)

Kwon, Young Min; Chang, Soon Heung [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1999-12-31

A theoretical critical heat flux (CHF ) model, based on lateral bubble coalescence on the heated wall, is proposed to predict the subcooled flow boiling CHF in a uniformly heated vertical tube. The model is based on the concept that a single layer of bubbles contacted to the heated wall prevents a bulk liquid from reaching the wall at near CHF condition. Comparisons between the model predictions and experimental data result in satisfactory agreement within less than 9.73% root-mean-square error by the appropriate choice of the critical void fraction in the bubbly layer. The present model shows comparable performance with the CHF look-up table of Groeneveld et al.. 28 refs., 11 figs., 1 tab. (Author)

Theoretical prediction method of subcooled flow boiling CHF

Energy Technology Data Exchange (ETDEWEB)

Kwon, Young Min; Chang, Soon Heung [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1998-12-31

A theoretical critical heat flux (CHF ) model, based on lateral bubble coalescence on the heated wall, is proposed to predict the subcooled flow boiling CHF in a uniformly heated vertical tube. The model is based on the concept that a single layer of bubbles contacted to the heated wall prevents a bulk liquid from reaching the wall at near CHF condition. Comparisons between the model predictions and experimental data result in satisfactory agreement within less than 9.73% root-mean-square error by the appropriate choice of the critical void fraction in the bubbly layer. The present model shows comparable performance with the CHF look-up table of Groeneveld et al.. 28 refs., 11 figs., 1 tab. (Author)

Extremes of shock index predicts death in trauma patients

Directory of Open Access Journals (Sweden)

Stephen R Odom

2016-01-01

Full Text Available Context: We noted a bimodal relationship between mortality and shock index (SI, the ratio of heart rate to systolic blood pressure. Aims: To determine if extremes of SI can predict mortality in trauma patients. Settings and Designs: Retrospective evaluation of adult trauma patients at a tertiary care center from 2000 to 2012 in the United States. Materials and Methods: We examined the SI in trauma patients and determined the adjusted mortality for patients with and without head injuries. Statistical Analysis Used: Descriptive statistics and multivariable logistic regression. Results: SI values demonstrated a U-shaped relationship with mortality. Compared with patients with a SI between 0.5 and 0.7, patients with a SI of 1.3 had an odds ratio of death of 3.1. (95% CI 1.6–5.9. Elevated SI is associated with increased mortality in patients with isolated torso injuries, and is associated with death at both low and high values in patients with head injury. Conclusion: Our data indicate a bimodal relationship between SI and mortality in head injured patients that persists after correction for various co-factors. The distribution of mortality is different between head injured patients and patients without head injuries. Elevated SI predicts death in all trauma patients, but low SI values only predict death in head injured patients.

Supplementation of Flow Accelerated Corrosion Prediction Program Using Numerical Analysis Technique

International Nuclear Information System (INIS)

Hwang, Kyeong Mo; Jin, Tae Eun; Park, Won; Oh, Dong Hoon

2010-01-01

Flow-accelerated corrosion (FAC) leads to thinning of steel pipe walls that are exposed to flowing water or wet steam. From experience, it is seen that FAC damage to piping at fossil and nuclear plants can result in outages that require expensive repairs and can affect plant reliability and safety. CHECWORKS have been utilized in domestic nuclear plants as a predictive tool to assist FAC engineers in planning inspections and evaluating the inspection data so that piping failures caused by FAC can be prevented. However, CHECWORKS may be occasionally ignore local susceptible portions when predicting FAC damage in a group of pipelines after constructing a database for all the secondary side piping in nuclear plants. This paper describes the methodologies that can complement CHECWORKS and the verifications of CHECWORKS prediction results using numerical analysis. FAC susceptible locations determined using CHECWORKS for two pipeline groups of a nuclear plant was compared with determined using the numerical-analysis-based FLUENT

Prediction for flow boiling heat transfer in small diameter tube using deep learning

International Nuclear Information System (INIS)

Enoki, Koji; Sei, Yuichi; Okawa, Tomio; Saito, Kiyoshi

2017-01-01

The applications of Artificial Intelligence ie AI show diversity in any fields. On the other hand, research of the predicting heat transfer regardless of single-phase or two-phase flow is still untouched. Therefore, we have confirmed usefulness using AI's deep learning function on horizontal flow boiling heat transfer in flowing mini-channel that is actively researched. The effect of the surface tension in the mini-channel is large compared with conventional large tubes, and then the heat transfer mechanism is very complicated. For this reason, the numerical correlations of many existing researchers the prediction result is not good. However, the mechanistic correlation based on the visualization experiment, which the authors' research group published several years ago has very high precision. Therefore, in this research paper, we confirmed the effectiveness of using deep learning for predicting of the boiling heat transfer in mini-channel while comparing our correlation. (author)

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

Science.gov (United States)

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.

Starch digestibility and predicted glycemic index in the bread fortified with pomelo (Citrus maxima) fruit segments.

Science.gov (United States)

Reshmi, S K; Sudha, M L; Shashirekha, M N

2017-12-15

The aim of this study was to evaluate the starch digestibility and predicted glycemic index in breads incorporated with pomelo fruit (Citrus maxima) segments. Volume of the white and brown breads supplemented with pomelo fresh segments increased, while the crumb firmness decreased. Bread with 20% fresh and 5% dry pomelo segments were sensorily acceptable. Bioactive components such as phenolics, flavonoids, naringin and carotenoids were retained to a greater extent in bread containing dry pomelo segments. The pomelo incorporated bread had higher levels of resistant starch fractions (3.87-10.96%) with low predicted glycemic index (62.97-53.13%), despite their higher total starch (69.87-75.47%) content compared to control bread. Thus pomelo segments in the product formulations lowered the glycemic index probably by inhibiting carbohydrate hydrolyzing enzyme activity which could be attributed to naringin. Hence fortified bread prepared from pomelo fruit segment is recommended to gain nutritional value and to decrease the risk of diabetes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimates of evapotranspiration for riparian sites (Eucalyptus) in the Lower Murray -Darling Basin using ground validated sap flow and vegetation index scaling techniques

Science.gov (United States)

Doody, T.; Nagler, P. L.; Glenn, E. P.

2014-12-01

Water accounting is becoming critical globally, and balancing consumptive water demands with environmental water requirements is especially difficult in in arid and semi-arid regions. Within the Murray-Darling Basin (MDB) in Australia, riparian water use has not been assessed across broad scales. This study therefore aimed to apply and validate an existing U.S. riparian ecosystem evapotranspiration (ET) algorithm for the MDB river systems to assist water resource managers to quantify environmental water needs over wide ranges of niche conditions. Ground-based sap flow ET was correlated with remotely sensed predictions of ET, to provide a method to scale annual rates of water consumption by riparian vegetation over entire irrigation districts. Sap flux was measured at nine locations on the Murrumbidgee River between July 2011 and June 2012. Remotely sensed ET was calculated using a combination of local meteorological estimates of potential ET (ETo) and rainfall and MODIS Enhanced Vegetation Index (EVI) from selected 250 m resolution pixels. The sap flow data correlated well with MODIS EVI. Sap flow ranged from 0.81 mm/day to 3.60 mm/day and corresponded to a MODIS-based ET range of 1.43 mm/day to 2.42 mm/day. We found that mean ET across sites could be predicted by EVI-ETo methods with a standard error of about 20% across sites, but that ET at any given site could vary much more due to differences in aquifer and soil properties among sites. Water use was within range of that expected. We conclude that our algorithm developed for US arid land crops and riparian plants is applicable to this region of Australia. Future work includes the development of an adjusted algorithm using these sap flow validated results.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

Directory of Open Access Journals (Sweden)

Long Jiao

2015-05-01

Full Text Available The quantitative structure property relationship (QSPR for the boiling point (Tb of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs was investigated. The molecular distance-edge vector (MDEV index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR and artificial neural network (ANN, respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Methods for early prediction of lactation flow in Holstein heifers

Directory of Open Access Journals (Sweden)

Vesna Gantner

2010-12-01

Full Text Available The aim of this research was to define methods for early prediction (based on I. milk control record of lactation flow in Holstein heifers as well as to choose optimal one in terms of prediction fit and application simplicity. Total of 304,569 daily yield records automatically recorded on a 1,136 first lactation Holstein cows, from March 2003 till August 2008., were included in analysis. According to the test date, calving date, the age at first calving, lactation stage when I. milk control occurred and to the average milk yield in first 25th, T1 (and 25th-45th, T2 lactation days, measuring monthcalving month-age-production-time-period subgroups were formed. The parameters of analysed nonlinear and linear methods were estimated for each defined subgroup. As models evaluation measures,adjusted coefficient of determination, and average and standard deviation of error were used. Considering obtained results, in terms of total variance explanation (R2 adj, the nonlinear Wood’s method showed superiority above the linear ones (Wilmink’s, Ali-Schaeffer’s and Guo-Swalve’s method in both time-period subgroups (T1 - 97.5 % of explained variability; T2 - 98.1 % of explained variability. Regarding the evaluation measures based on prediction error amount (eavg±eSD, the lowest average error of daily milk yield prediction (less than 0.005 kg/day, as well as of lactation milk yield prediction (less than 50 kg/lactation (T1 time-period subgroup and less than 30 kg/lactation (T2 time-period subgroup; were determined when Wood’s nonlinear prediction method were applied. Obtained results indicate that estimated Wood’s regression parameters could be used in routine work for early prediction of Holstein heifer’s lactation flow.

Performance assessment of turbulence models for the prediction of moderator thermal flow inside CANDU calandria

International Nuclear Information System (INIS)

Lee, Gong Hee; Bang, Young Seok; Woo, Sweng Woong

2012-01-01

The moderator thermal flow in the CANDU calandria is generally complex and highly turbulent because of the interaction of the buoyancy force with the inlet jet inertia. In this study, the prediction performance of turbulence models for the accurate analysis of the moderator thermal flow are assessed by comparing the results calculated with various types of turbulence models in the commercial flow solver FLUENT with experimental data for the test vessel at Sheridan Park Engineering Laboratory (SPEL). Through this comparative study of turbulence models, it is concluded that turbulence models that include the source term to consider the effects of buoyancy on the turbulent flow should be used for the reliable prediction of the moderator thermal flow inside the CANDU calandria

Prediction of the surface roughness of AA6082 flow-formed tubes by design of experiments

International Nuclear Information System (INIS)

Srinivasulu, M.; Komaraiah, M.; Rao, C. S. Krishna Prasada

2013-01-01

Flow forming is a modern, chipless metal forming process that is employed for the production of thin-walled seamless tubes. Experiments are conducted on AA6082 alloy pre-forms to flow form into thin-walled tubes on a CNC flow-forming machine with a single roller. Design of experiments is used to predict the surface roughness of flow-formed tubes. The process parameters selected for this study are the roller axial feed, mandrel speed, and roller radius. A standard response surface methodology (RSM) called the Box Behnken design is used to perform the experimental runs. The regression model developed by RSM successfully predicts the surface roughness of AA6082 flow-formed tubes within the range of the selected process parameters.

Prediction of the surface roughness of AA6082 flow-formed tubes by design of experiments

Energy Technology Data Exchange (ETDEWEB)

Srinivasulu, M. [Government Polytechnic for Women Badangpet, Hyderabad (India); Komaraiah, M. [Sreenidhi Institute of Science and Technology, Hyderabad (India); Rao, C. S. Krishna Prasada [Bharat Dynamics Limited, Hyderabad (India)

2013-06-15

Flow forming is a modern, chipless metal forming process that is employed for the production of thin-walled seamless tubes. Experiments are conducted on AA6082 alloy pre-forms to flow form into thin-walled tubes on a CNC flow-forming machine with a single roller. Design of experiments is used to predict the surface roughness of flow-formed tubes. The process parameters selected for this study are the roller axial feed, mandrel speed, and roller radius. A standard response surface methodology (RSM) called the Box Behnken design is used to perform the experimental runs. The regression model developed by RSM successfully predicts the surface roughness of AA6082 flow-formed tubes within the range of the selected process parameters.

Study for discharge coefficient of flow nozzles. Prediction by using numerical simulation

International Nuclear Information System (INIS)

Ikeda, Hiroshi; Sakai, Norio; Yamamoto, Yasushi; Arai, Kenji; Matsumoto, Masaaki

2008-01-01

In nuclear plant, as water feeding into reactor have much effect on thermal power of plant, it is important to measure accurately the flow rate of water. Flow nozzle is on of typical differential pressure type flow meters and the discharge coefficient is used to calculate the flow rate. This coefficient is given by actual experiment and theory. We studied the theoretical assumption of the discharge coefficient curve using numerical simulation and evaluated the effect of flow nozzle configuration on the coefficient numerically and experimentally. As the result, numerical simulation can predict the discharge coefficient of theoretical curve within 0.3%. And we found that the throat length and throat tapping location of flow nozzle have much effect on the coefficient. (author)

Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

Directory of Open Access Journals (Sweden)

L. Cai

2010-02-01

Full Text Available Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF B_z, B_y and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min. This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect

Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

Directory of Open Access Journals (Sweden)

L. Cai

2010-02-01

Full Text Available Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min. This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect on average the characteristic time of ring

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

Science.gov (United States)

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.

PIV pictures of stream field predict haemolysis index of centrifugal pump with streamlined impeller.

Science.gov (United States)

Qian, K X; Feng, Z G; Ru, W M; Zeng, P; Yuan, H Y

2007-01-01

Previously it has been found by pump haemolysis testing that the flow rate has a remarkable effect on index of haemolysis (IH), while pressure head does not affect IH. Recent investigation with particle image velocimetry (PIV) technology has demonstrated that IH is directly related to the flow pattern of stream field in impeller vane channels. PIV is a visible approach showing the real flow status in the pump. The different positions of a tracer particle in two PIV pictures taken at 20 micros intervals decide the velocity value and direction. The velocity vectors of many particles draw the flow pattern of the stream field. The same pictures are taken at 2, 4 and 6 l min(-1) flow rates while the pressure head is kept unchanged at 100 mmHg; then the pictures are taken at 4 l min(-1) flow with different pressure heads of 80, 100 and 120 mmHg. Results reveal that the flow rate of 4 l min(-1) (IH = 0.030) has the best stream field, and neither turbulence nor separation can be seen. In other flow rates (IH: 0.048 - 0.082), there is obviously second flow. Meanwhile, no significant difference can be seen among the PIV pictures of different pressure heads pumped, which agrees with the results of haemolysis testing showing that pressure has no effect on pump haemolysis. It may be concluded that the haemolysis property of a centrifugal pump can be assessed approximately by PIV pictures, which are much easier to take than haemolysis tests.

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

International Nuclear Information System (INIS)

DeMuth, S.F.; Watson, J.S.

1985-01-01

A model of compressible flow through an orifice, in the region of transition from free molecular to isentropic expansion flow, has been developed and tested for accuracy. The transitional or slip regime is defined as the conditions where molecular interactions are too many for free molecular flow modeling, yet not great enough for isentropic expansion flow modeling. Due to a lack of literature establishing a well-accepted model for predicting transitional flow, it was felt such work would be beneficial. The model is nonlinear and cannot be satisfactorily linearized for a linear regression analysis. Consequently, a computer routine was developed which minimized the sum of the squares of the residual flow for the nonlinear model. The results indicate an average accuracy within 15% of the measured flow throughout the range of test conditions. Furthermore, the results of the regression analysis indicate that the transitional regime lies between Knudsen numbers of approximately 2 and 45. 4 refs., 3 figs., 1 tab

predicted peak expiratory flow in human and the clinical implication ...

African Journals Online (AJOL)

DR. AMINU

predicted PEF varied widely across formulae and choice of a particular formula may alter guideline- base care. This work has therefore accepted a recently published population-base equation proposed as the reference standard for future asthma guidelines. Keywords: Peak expiratory flow, Asthma, Practice guidelines, ...

Debris-flows scale predictions based on basin spatial parameters calculated from Remote Sensing images in Wenchuan earthquake area

International Nuclear Information System (INIS)

Zhang, Huaizhen; Chi, Tianhe; Liu, Tianyue; Wang, Wei; Yang, Lina; Zhao, Yuan; Shao, Jing; Yao, Xiaojing; Fan, Jianrong

2014-01-01

Debris flow is a common hazard in the Wenchuan earthquake area. Collapse and Landslide Regions (CLR), caused by earthquakes, could be located from Remote Sensing images. CLR are the direct material source regions for debris flow. The Spatial Distribution of Collapse and Landslide Regions (SDCLR) strongly impact debris-flow formation. In order to depict SDCLR, we referred to Strahler's Hypsometric analysis method and developed 3 functional models to depict SDCLR quantitatively. These models mainly depict SDCLR relative to altitude, basin mouth and main gullies of debris flow. We used the integral of functions as the spatial parameters of SDCLR and these parameters were employed during the process of debris-flows scale predictions. Grouping-occurring debris-flows triggered by the rainstorm, which occurred on September 24th 2008 in Beichuan County, Sichuan province China, were selected to build the empirical equations for debris-flows scale predictions. Given the existing data, only debris-flows runout zone parameters (Max. runout distance L and Lateral width B) were estimated in this paper. The results indicate that the predicted results were more accurate when the spatial parameters were used. Accordingly, we suggest spatial parameters of SDCLR should be considered in the process of debris-flows scale prediction and proposed several strategies to prevent debris flow in the future

Multivariate models for prediction of rheological characteristics of filamentous fermentation broth from the size distribution.

Science.gov (United States)

Petersen, Nanna; Stocks, Stuart; Gernaey, Krist V

2008-05-01

The main purpose of this article is to demonstrate that principal component analysis (PCA) and partial least squares regression (PLSR) can be used to extract information from particle size distribution data and predict rheological properties. Samples from commercially relevant Aspergillus oryzae fermentations conducted in 550 L pilot scale tanks were characterized with respect to particle size distribution, biomass concentration, and rheological properties. The rheological properties were described using the Herschel-Bulkley model. Estimation of all three parameters in the Herschel-Bulkley model (yield stress (tau(y)), consistency index (K), and flow behavior index (n)) resulted in a large standard deviation of the parameter estimates. The flow behavior index was not found to be correlated with any of the other measured variables and previous studies have suggested a constant value of the flow behavior index in filamentous fermentations. It was therefore chosen to fix this parameter to the average value thereby decreasing the standard deviation of the estimates of the remaining rheological parameters significantly. Using a PLSR model, a reasonable prediction of apparent viscosity (micro(app)), yield stress (tau(y)), and consistency index (K), could be made from the size distributions, biomass concentration, and process information. This provides a predictive method with a high predictive power for the rheology of fermentation broth, and with the advantages over previous models that tau(y) and K can be predicted as well as micro(app). Validation on an independent test set yielded a root mean square error of 1.21 Pa for tau(y), 0.209 Pa s(n) for K, and 0.0288 Pa s for micro(app), corresponding to R(2) = 0.95, R(2) = 0.94, and R(2) = 0.95 respectively. Copyright 2007 Wiley Periodicals, Inc.

Development of a risk index for the prediction of chronic post-surgical pain.

Science.gov (United States)

Althaus, A; Hinrichs-Rocker, A; Chapman, R; Arránz Becker, O; Lefering, R; Simanski, C; Weber, F; Moser, K-H; Joppich, R; Trojan, S; Gutzeit, N; Neugebauer, E

2012-07-01

The incidence of chronic post-surgical pain (CPSP) after various common operations is 10% to 50%. Identification of patients at risk of developing chronic pain, and the management and prevention of CPSP remains inadequate. The aim of this study was to develop an easily applicable risk index for the detection of high-risk patients that takes into account the multifactorial aetiology of CPSP. A comprehensive item pool was derived from a systematic literature search. Items that turned out significant in bivariate analyses were then analysed multivariately, using logistic regression analyses. The items that yielded significant predictors in the multivariate analyses were compiled into an index. The cut-off score for a high risk of developing CPSP with an optimal trade-off between sensitivity and specificity was identified. The data of 150 patients who underwent different types of surgery were included in the analyses. Six months after surgery, 43.3% of the patients reported CPSP. Five predictors multivariately contributed to the prediction of CPSP: capacity overload, preoperative pain in the operating field, other chronic preoperative pain, post-surgical acute pain and co-morbid stress symptoms. These results suggest that several easily assessable preoperative and perioperative patient characteristics can predict a patient's risk of developing CPSP. The risk index may help caregivers to tailor individual pain management and to assist high-risk patients with pain coping. © 2011 European Federation of International Association for the Study of Pain Chapters.

Discriminative ability of commonly used indices to predict adverse outcomes after poster lumbar fusion: a comparison of demographics, ASA, the modified Charlson Comorbidity Index, and the modified Frailty Index.

Science.gov (United States)

Ondeck, Nathaniel T; Bohl, Daniel D; Bovonratwet, Patawut; McLynn, Ryan P; Cui, Jonathan J; Shultz, Blake N; Lukasiewicz, Adam M; Grauer, Jonathan N

2018-01-01

As research tools, the American Society of Anesthesiologists (ASA) physical status classification system, the modified Charlson Comorbidity Index (mCCI), and the modified Frailty Index (mFI) have been associated with complications following spine procedures. However, with respect to clinical use for various adverse outcomes, no known study has compared the predictive performance of these indices specifically following posterior lumbar fusion (PLF). This study aimed to compare the discriminative ability of ASA, mCCI, and mFI, as well as demographic factors including age, body mass index, and gender for perioperative adverse outcomes following PLF. A retrospective review of prospectively collected data was performed. Patients undergoing elective PLF with or without interbody fusion were extracted from the 2011-2014 American College of Surgeons National Surgical Quality Improvement Program (NSQIP). Perioperative adverse outcome variables assessed included the occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, and discharge to higher-level care. Patient comorbidity indices and characteristics were delineated and assessed for discriminative ability in predicting perioperative adverse outcomes using an area under the curve analysis from the receiver operating characteristics curves. In total, 16,495 patients were identified who met the inclusion criteria. The most predictive comorbidity index was ASA and demographic factor was age. Of these two factors, age had the larger discriminative ability for three out of the six adverse outcomes and ASA was the most predictive for one out of six adverse outcomes. A combination of the most predictive demographic factor and comorbidity index resulted in improvements in discriminative ability over the individual components for five of the six outcome variables. For PLF, easily obtained patient ASA and age have overall similar or better

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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.

Fecal Calprotectin is an Accurate Tool and Correlated to Seo Index in Prediction of Relapse in Iranian Patients With Ulcerative Colitis.

Science.gov (United States)

Hosseini, Seyed Vahid; Jafari, Peyman; Taghavi, Seyed Alireza; Safarpour, Ali Reza; Rezaianzadeh, Abbas; Moini, Maryam; Mehrabi, Manoosh

2015-02-01

The natural clinical course of Ulcerative Colitis (UC) is characterized by episodes of relapse and remission. Fecal Calprotectin (FC) is a relatively new marker of intestinal inflammation and is an available, non-expensive tool for predicting relapse of quiescent UC. The Seo colitis activity index is a clinical index for assessment of the severity of UC. The present study aimed to evaluate the accuracy of FC and the Seo colitis activity index and their correlation in prediction of UC exacerbation. In this prospective cohort study, 157 patients with clinical and endoscopic diagnosis of UC selected randomly from 1273 registered patients in Fars province's IBD registry center in Shiraz, Iran, were followed from October 2012 to October 2013 for 12 months or shorter, if they had a relapse. Two patients left the study before completion and one patient had relapse because of discontinuation of drugs. The participants' clinical and serum factors were evaluated every three months. Furthermore, stool samples were collected at the beginning of study and every three months and FC concentration (commercially available enzyme linked immunoassay) and the Seo Index were assessed. Then univariate analysis, multiple variable logistic regression, Receiver Operating Characteristics (ROC) curve analysis, and Pearson's correlation test (r) were used for statistical analysis of data. According to the results, 74 patients (48.1%) relapsed during the follow-up (33 men and 41 women). Mean ± SD of FC was 862.82 ± 655.97 μg/g and 163.19 ± 215.85 μg/g in relapsing and non-relapsing patients, respectively (P Seo index were significant predictors of relapse. ROC curve analysis of FC level and Seo activity index for prediction of relapse demonstrated area under the curve of 0.882 (P Seo index was significant in prediction of relapse (r = 0.63, P Seo activity index in prediction of relapse in the course of quiescent UC in Iranian patients.

The prediction of the incidence rate of upper limb musculoskeletal disorders, with CTD risk index method on potters of Meybod city

Directory of Open Access Journals (Sweden)

Reza Khani Jazani

2012-02-01

Full Text Available Background: The objective of this study was to predict the incidence of musculoskeletal disorders in potters of Meybod city by performing CTD risk index method.Materials and Method: This is a descriptive cross-sectional study. Target society was all workers in pottery workshops which were located in the Meybod. Information related to musculoskeletal disorders was obtained by the Nordic questionnaire and we used CTD risk index method to predict the incidence of musculoskeletal disorders.Results: We observed in this study that 59.3% of the potters had symptoms of musculoskeletal disorders in at least in one of their upper extremities. Also significant differences between mean CTD risk index on potters with and without symptoms of the upper limb musculoskeletal disorders, respectively (p=0.038.Conclusion: CTD risk index method can be as a suitable method for predicting the incidence of musculoskeletal disorders used in the potters

A simplified donor risk index for predicting outcome after deceased donor kidney transplantation.

Science.gov (United States)

Watson, Christopher J E; Johnson, Rachel J; Birch, Rhiannon; Collett, Dave; Bradley, J Andrew

2012-02-15

We sought to determine the deceased donor factors associated with outcome after kidney transplantation and to develop a clinically applicable Kidney Donor Risk Index. Data from the UK Transplant Registry on 7620 adult recipients of adult deceased donor kidney transplants between 2000 and 2007 inclusive were analyzed. Donor factors potentially influencing transplant outcome were investigated using Cox regression, adjusting for significant recipient and transplant factors. A United Kingdom Kidney Donor Risk Index was derived from the model and validated. Donor age was the most significant factor predicting poor transplant outcome (hazard ratio for 18-39 and 60+ years relative to 40-59 years was 0.78 and 1.49, respectively, Pinformed consent.

Prediction of flow in mix-proof valve by use of CFD - Validation by LDA

DEFF Research Database (Denmark)

Jensen, Bo Boye Busk; Friis, Alan

2004-01-01

was done on a spherical shaped mix-proof valve (MPV). Flow were predicted by Computational Fluid Dynamics (CFD) and validated by data obtained from experiments using laser sheet visualization and laser Doppler anemometry. Correction of the measured velocities and probe location was required as refraction......-wall region is shown. Fully 3D flow patterns were identified and valuable information was obtained for further investigations concerning prediction of cleanability in the MPV based on knowledge of the hydrodynamics herein....

Monthly to seasonal low flow prediction: statistical versus dynamical models

Science.gov (United States)

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

A parallel adaptive mesh refinement algorithm for predicting turbulent non-premixed combusting flows

International Nuclear Information System (INIS)

Gao, X.; Groth, C.P.T.

2005-01-01

A parallel adaptive mesh refinement (AMR) algorithm is proposed for predicting turbulent non-premixed combusting flows characteristic of gas turbine engine combustors. The Favre-averaged Navier-Stokes equations governing mixture and species transport for a reactive mixture of thermally perfect gases in two dimensions, the two transport equations of the κ-ψ turbulence model, and the time-averaged species transport equations, are all solved using a fully coupled finite-volume formulation. A flexible block-based hierarchical data structure is used to maintain the connectivity of the solution blocks in the multi-block mesh and facilitate automatic solution-directed mesh adaptation according to physics-based refinement criteria. This AMR approach allows for anisotropic mesh refinement and the block-based data structure readily permits efficient and scalable implementations of the algorithm on multi-processor architectures. Numerical results for turbulent non-premixed diffusion flames, including cold- and hot-flow predictions for a bluff body burner, are described and compared to available experimental data. The numerical results demonstrate the validity and potential of the parallel AMR approach for predicting complex non-premixed turbulent combusting flows. (author)

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

Science.gov (United States)

Lin, Shu-Yu; Lee, Wei-Ju; Chou, Ming-Yueh; Peng, Li-Ning; Chiou, Shu-Ti; Chen, Liang-Kung

2016-01-01

Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors. Analytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form. During an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile ( 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them. Although both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

Accuracy of shock index versus ABC score to predict need for massive transfusion in trauma patients.

Science.gov (United States)

Schroll, Rebecca; Swift, David; Tatum, Danielle; Couch, Stuart; Heaney, Jiselle B; Llado-Farrulla, Monica; Zucker, Shana; Gill, Frances; Brown, Griffin; Buffin, Nicholas; Duchesne, Juan

2018-01-01

Various scoring systems have been developed to predict need for massive transfusion in traumatically injured patients. Assessments of Blood Consumption (ABC) score and Shock Index (SI) have been shown to be reliable predictors for Massive Transfusion Protocol (MTP) activation. However, no study has directly compared these two scoring systems to determine which is a better predictor for MTP activation. The primary objective was to determine whether ABC or SI better predicted the need for MTP in adult trauma patients with severe hemorrhage. This was a retrospective cohort study which included all injured patients who were trauma activations between January 1, 2009 and December 31, 2013 at an urban Level I trauma center. Patients ABC and SI were calculated for each patient. MTP was defined as need for >10 units PRBC transfusion within 24h of emergency department arrival. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) were used to evaluate scoring systems' ability to predict effective MTP utilization. A total of 645 patients had complete data for analysis. Shock Index ≥1 had sensitivity of 67.7% (95% CI 49.5%-82.6%) and specificity of 81.3% (95% CI 78.0%-84.3%) for predicting MTP, and ABC score ≥2 had sensitivity of 47.0% (95% CI 29.8%-64.9%) and specificity of 89.8% (95% CI 87.2%-92.1%). AUROC analyses showed SI to be the strongest predictor followed by ABC score with AUROC values of 0.83 and 0.74, respectively. SI had a significantly greater sensitivity (P=0.035), but a significantly weaker specificity (PABC score. ABC score and Shock Index can both be used to predict need for massive transfusion in trauma patients, however SI is more sensitive and requires less technical skill than ABC score. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationship between depression with FEV1 percent predicted and BODE index in chronic obstructive pulmonary disease

Science.gov (United States)

Gunawan, H.; Hanum, H.; Abidin, A.; Hanida, W.

2018-03-01

WHO reported more than 3 million people die from COPD in 2012 and are expected to rank third after cardiovascular and cancer diseases in the future. Recent studies reported the prevalence of depression in COPD patients was higher than in control group. So, it’s important for clinicians to understand the relationship of depression symptoms with clinical aspects of COPD. For determining the association of depression symptoms with lung function and BODE index in patients with stable COPD, a cross-sectional study was in 98 stable COPD outpatients from January to June 2017. Data were analyzed using Independent t-test, Mann-Whitney test, and Spearman’s rank correlation. COPD patients with depression had higher mMRC scores, and lower FEV1 percent predicted, and then 6-Minutes Walk Test compared to those without depression. There was a moderate strength of correlation (r=-0.43) between depression symptoms and FEV1 percent predicted, and strong correlation (r=0.614) between depression symptoms and BODE index. It indicates that BODE index is more accurate to describe symptoms of depression in COPD patients.

Error estimation for CFD aeroheating prediction under rarefied flow condition

Science.gov (United States)

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.

Numerical assessment of flow dynamics for various DI diesel engine designs considering swirl number and uniformity index

International Nuclear Information System (INIS)

Jafarmadar, S.; Taghavifar, Hadi; Taghavifar, Hamid; Navid, A.

2016-01-01

Highlights: • Swirl ratio and uniformity index was assessed for six different engine designs. • Lower bowl-depth and higher bowl radius create higher squish and swirl. • The best design for power boost and emission control strategies were identified. • The flow dynamics are considered based on TKE and also the flow field vectors. - Abstract: Geometrical features of combustion chamber are important factors in subsequent engine’s combustion and emissions. Location and configuration of bowl in diesel engine has been the dynamic field of research especially for optimization procedure. This study considers six different engine patterns with outlined parameters. It follows that different designs are characterized with different swirl motions and tumble flows within the combustion chamber. It was determined that maximum and minimum peak swirl number pertains to “Design5” and “Design1” with 1.59 and 1.1 values, respectively. By using “Design5” case instead of “Design1” (baseline case), uniformity index increased by 25.83% whereby peak soot concentration was reduced over 46.7%. The bigger bowl radius (R1) makes higher swirl ratio and this eventually leads to lower soot emission. Lower bowl depth (T), however, gives way to stronger squish pressure and engine-out power.

Chaos game representation of the D st index and prediction of geomagnetic storm events

International Nuclear Information System (INIS)

Yu, Z.G.; Anh, V.V.; Wanliss, J.A.; Watson, S.M.

2007-01-01

This paper proposes a two-dimensional chaos game representation (CGR) for the D st index. The CGR provides an effective method to characterize the multifractality of the D st time series. The probability measure of this representation is then modeled as a recurrent iterated function system in fractal theory, which leads to an algorithm for prediction of a storm event. We present an analysis and modeling of the D st time series over the period 1963-2003. The numerical results obtained indicate that the method is useful in predicting storm events one day ahead

Central venous pressure and shock index predict lack of hemodynamic response to volume expansion in septic shock: a prospective, observational study.

Science.gov (United States)

Lanspa, Michael J; Brown, Samuel M; Hirshberg, Eliotte L; Jones, Jason P; Grissom, Colin K

2012-12-01

Volume expansion is a common therapeutic intervention in septic shock, although patient response to the intervention is difficult to predict. Central venous pressure (CVP) and shock index have been used independently to guide volume expansion, although their use is questionable. We hypothesize that a combination of these measurements will be useful. In a prospective, observational study, patients with early septic shock received 10-mL/kg volume expansion at their treating physician's discretion after brief initial resuscitation in the emergency department. Central venous pressure and shock index were measured before volume expansion interventions. Cardiac index was measured immediately before and after the volume expansion using transthoracic echocardiography. Hemodynamic response was defined as an increase in a cardiac index of 15% or greater. Thirty-four volume expansions were observed in 25 patients. A CVP of 8 mm Hg or greater and a shock index of 1 beat min(-1) mm Hg(-1) or less individually had a good negative predictive value (83% and 88%, respectively). Of 34 volume expansions, the combination of both a high CVP and a low shock index was extremely unlikely to elicit hemodynamic response (negative predictive value, 93%; P = .02). Volume expansion in patients with early septic shock with a CVP of 8 mm Hg or greater and a shock index of 1 beat min(-1) mm Hg(-1) or less is unlikely to lead to an increase in cardiac index. Copyright © 2012 Elsevier Inc. All rights reserved.

New social adaptability index predicts overall mortality.

Science.gov (United States)

Goldfarb-Rumyantzev, Alexander; Barenbaum, Anna; Rodrigue, James; Rout, Preeti; Isaacs, Ross; Mukamal, Kenneth

2011-08-01

Definitions of underprivileged status based on race, gender and geographic location are neither sensitive nor specific; instead we proposed and validated a composite index of social adaptability (SAI). Index of social adaptability was calculated based on employment, education, income, marital status, and substance abuse, each factor contributing from 0 to 3 points. Index of social adaptability was validated in NHANES-3 by association with all-cause and cause-specific mortality. Weighted analysis of 19,593 subjects demonstrated mean SAI of 8.29 (95% CI 8.17-8.40). Index of social adaptability was higher in Whites, followed by Mexican-Americans and then the African-American population (ANOVA, p adaptability with a strong association with mortality, which can be used to identify underprivileged populations at risk of death.

Flow predictions for MHD channels with an approximation for three-dimensional effects

International Nuclear Information System (INIS)

Blottner, F.G.

1978-01-01

A finite-difference procedure has been formulated for predicting the flow properties across channels. A quasi-two-dimensional approach has been developed which allows the three-dimensional channel effects to be taken into account. Comparison of the numerical solutions with experimental results show that this approach is a reasonable approximation for MHD flow conditions if there is not significant merging of the wall boundary layers. The resulting code provides a technique to obtain the flow details in the symmetry plane of the channel and requires only a small amount of computer time

The effect of virtual mass on the prediction of critical flow

International Nuclear Information System (INIS)

Cheng, L.; Lahey, R.T.; Drew, D.A.

1983-01-01

By observing the results in Fig. 4 and Fig. 5 we can see that virtual mass effects are important in predicting critical flow. However, as seen in Fig. 7a, in which all three flows are predicted to be critical (Δ=0), it is difficult to distinguish one set of conditions from the other by just considering the pressure profile. Clearly more detailed data, such as the throat void fraction, is needed for discrimination between these calculations. Moreover, since the calculated critical flows have been found to be sensitive to initial mass flux, and void fraction, careful measurements of those parameters are needed before accurate virtual mass parameters can be determined from these data. It can be concluded that the existing Moby Dick data is inadequate to allow one to deduce accurate values of the virtual mass parameters C/sub VM/ and λ. Nevertheless, more careful experiments of this type are uniquely suited for the determination of these important parameters. It appears that the use of a nine equation model, such as that discussed herein, coupled with more detailed accurate critical flow data is an effective means of determining the parameters in interfacial momentum transfer models, such as virtual mass effects, which are only important during strong spatial accelerations. Indeed, there are few other methods available which can be used for such determinations

Assessment of correlations and models for prediction of CHF in subcooled flow boiling

International Nuclear Information System (INIS)

Celata, G.P.; Mariani, A.; Cumo, M.

1992-01-01

This paper provides an analysis of available correlations and models for the prediction of Critical Heat Flux (CHF) in subcooled flow boiling in the ranges of interest of fusion reactor thermal-hydraulic conditions, i.e., high inlet liquid subcooling and velocity and small channel diameter and length. The aim of the study was to establish the limits of validity of present predictive tools (most of them were proposed with reference to LWR thermal-hydraulic studies) in the above conditions. The reference data-set represents most of available data covering wide ranges of operating conditions in the framework of present interest (0.1 s ub, in < 230 K). Among the tens of predictive tools available in literature, four correlations (Levy, Westinghouse, modified-Tong and Tong-75) and three models (Weisman and Ileslamlou Lee and Mudawar and Katto) were selected. The modified-Tong correlation and the Katto model seem to be reliable predictive tools for the calculation of the CHF in subcooled flow boiling

Development of a Program for Predicting Flow Instability in a Once-through Sodium-Heated Steam Generator (III)

Energy Technology Data Exchange (ETDEWEB)

Kim, Eui Kwang; Yoon, Jung; Kim, Jong Bum; Jeong, Jiyoung [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2016-10-15

Two-phase flow systems can be subjected to several types of instability problems. Density-wave oscillation is the most common and important type of instability in boiling channels. Such instability gives difficulties in predictions of system performance and system control, and component failure due to thermal fatigue. A computer program developed for predicting two-phase flow instability in a steam generator heated by liquid sodium was presented in the previous works. Limit cycle was predicted even in a fixed node system. The amplitude of inlet flow rate is larger than that of outlet flow rate. The amplitude of phase change location oscillation within boiling-to-vapor boundary node is larger than that of liquid-to-boiling boundary node. Sodium and steam temperature are invariant at tube exit.

How long the singular value decomposed entropy predicts the stock market? - Evidence from the Dow Jones Industrial Average Index

Science.gov (United States)

Gu, Rongbao; Shao, Yanmin

2016-07-01

In this paper, a new concept of multi-scales singular value decomposition entropy based on DCCA cross correlation analysis is proposed and its predictive power for the Dow Jones Industrial Average Index is studied. Using Granger causality analysis with different time scales, it is found that, the singular value decomposition entropy has predictive power for the Dow Jones Industrial Average Index for period less than one month, but not for more than one month. This shows how long the singular value decomposition entropy predicts the stock market that extends Caraiani's result obtained in Caraiani (2014). On the other hand, the result also shows an essential characteristic of stock market as a chaotic dynamic system.

Volume fraction prediction in biphasic flow using nuclear technique and artificial neural network

International Nuclear Information System (INIS)

Salgado, Cesar M.; Brandao, Luis E.B.

2015-01-01

The volume fraction is one of the most important parameters used to characterize air-liquid two-phase flows. It is a physical value to determine other parameters, such as the phase's densities and to determine the flow rate of each phase. These parameters are important to predict the flow pattern and to determine a mathematical model for the system. To study, for example, heat transfer and pressure drop. This work presents a methodology for volume fractions prediction in water-gas stratified flow regime using the nuclear technique and artificial intelligence. The volume fractions calculate in biphasic flow systems is complex and the analysis by means of analytical equations becomes very difficult. The approach is based on gamma-ray pulse height distributions pattern recognition by means of the artificial neural network. The detection system uses appropriate broad beam geometry, comprised of a ( 137 Cs) energy gamma-ray source and a NaI(Tl) scintillation detector in order measure transmitted beam whose the counts rates are influenced by the phases composition. These distributions are directly used by the network without any parameterization of the measured signal. The ideal and static theoretical models for stratified regime have been developed using MCNP-X code, which was used to provide training, test and validation data for the network. The detector also was modeled with this code and the results were compared to experimental photopeak efficiency measurements of radiation sources. The proposed network could obtain with satisfactory prediction of the volume fraction in water-gas system, demonstrating to be a promising approach for this purpose. (author)

Volume fraction prediction in biphasic flow using nuclear technique and artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Salgado, Cesar M.; Brandao, Luis E.B., E-mail: otero@ien.gov.br, E-mail: brandao@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

2015-07-01

The volume fraction is one of the most important parameters used to characterize air-liquid two-phase flows. It is a physical value to determine other parameters, such as the phase's densities and to determine the flow rate of each phase. These parameters are important to predict the flow pattern and to determine a mathematical model for the system. To study, for example, heat transfer and pressure drop. This work presents a methodology for volume fractions prediction in water-gas stratified flow regime using the nuclear technique and artificial intelligence. The volume fractions calculate in biphasic flow systems is complex and the analysis by means of analytical equations becomes very difficult. The approach is based on gamma-ray pulse height distributions pattern recognition by means of the artificial neural network. The detection system uses appropriate broad beam geometry, comprised of a ({sup 137}Cs) energy gamma-ray source and a NaI(Tl) scintillation detector in order measure transmitted beam whose the counts rates are influenced by the phases composition. These distributions are directly used by the network without any parameterization of the measured signal. The ideal and static theoretical models for stratified regime have been developed using MCNP-X code, which was used to provide training, test and validation data for the network. The detector also was modeled with this code and the results were compared to experimental photopeak efficiency measurements of radiation sources. The proposed network could obtain with satisfactory prediction of the volume fraction in water-gas system, demonstrating to be a promising approach for this purpose. (author)

The blood flow channel index as novel predictor of abdominal aortic aneurysm impending rupture based on the intraluminal thrombus angio-CT study

International Nuclear Information System (INIS)

Wiernicki, Ireneusz; Szumilowicz, Pawel; Kazimierczak, Arkadiusz; Falkowski, Aleksander; Rutkowski, Donald; Gutowski, Piotr

2015-01-01

Objective: In this study the hypothesis that the thickness of the thinnest part of the thrombus, combined with bleeding into the intraluminal thrombus (ILT), is associated with a possible higher risk of abdominal aortic aneurysm (AAA) rupture was investigated, independently of aneurysm diameter, by using angio-CT. This article describes blood flow channel index based on the CT imaging findings that may help identify impending rupture prior to complete rupture. Methods: Computed tomographic images of 310 hospitalized patients with infrarenal AAA, were collected over a three-year period. They were divided into two main groups: 125 with bleeding into the ILT and control group 185 without the presence of blood in the thrombus. Patients were also analyzed in subgroups with ruptured, symptomatic and asymptomatic AAAs. A blood flow channel index was formulated as: maximal/minimal thickness ratio of thrombus from the same CT scan. Results: In dissected ILT group blood flow channel index was over a twofold higher than in group with intact ILT (19.0 [1.2–89.3] vs. (9.7 [1.3–38.9]; p < 0.001), respectively. Median thickness at the thinnest part of the ILT in dissected thrombus group was lower (1.3 mm [0.3–16.0]) than in group with intact ILT (1.7 mm [0.2–23.4]; p < 0.003). Conclusion: An association between a high blood flow channel index and bleeding into the ILT based on angio-CT study was demonstrated, and can suggest the aneurysm propensity for rupture

The blood flow channel index as novel predictor of abdominal aortic aneurysm impending rupture based on the intraluminal thrombus angio-CT study

Energy Technology Data Exchange (ETDEWEB)

Wiernicki, Ireneusz, E-mail: irekwie@wp.eu [Department of Vascular Surgery and Angiology, Pomeranian Medical University, Szczecin (Poland); Szumilowicz, Pawel; Kazimierczak, Arkadiusz [Department of Vascular Surgery and Angiology, Pomeranian Medical University, Szczecin (Poland); Falkowski, Aleksander; Rutkowski, Donald [Department of Interventional Radiology, Pomeranian Medical University, Szczecin (Poland); Gutowski, Piotr [Department of Vascular Surgery and Angiology, Pomeranian Medical University, Szczecin (Poland)

2015-04-15

Objective: In this study the hypothesis that the thickness of the thinnest part of the thrombus, combined with bleeding into the intraluminal thrombus (ILT), is associated with a possible higher risk of abdominal aortic aneurysm (AAA) rupture was investigated, independently of aneurysm diameter, by using angio-CT. This article describes blood flow channel index based on the CT imaging findings that may help identify impending rupture prior to complete rupture. Methods: Computed tomographic images of 310 hospitalized patients with infrarenal AAA, were collected over a three-year period. They were divided into two main groups: 125 with bleeding into the ILT and control group 185 without the presence of blood in the thrombus. Patients were also analyzed in subgroups with ruptured, symptomatic and asymptomatic AAAs. A blood flow channel index was formulated as: maximal/minimal thickness ratio of thrombus from the same CT scan. Results: In dissected ILT group blood flow channel index was over a twofold higher than in group with intact ILT (19.0 [1.2–89.3] vs. (9.7 [1.3–38.9]; p < 0.001), respectively. Median thickness at the thinnest part of the ILT in dissected thrombus group was lower (1.3 mm [0.3–16.0]) than in group with intact ILT (1.7 mm [0.2–23.4]; p < 0.003). Conclusion: An association between a high blood flow channel index and bleeding into the ILT based on angio-CT study was demonstrated, and can suggest the aneurysm propensity for rupture.

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

Science.gov (United States)

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

A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.)

Science.gov (United States)

Louis R. Iverson; Martin E. Dale; Charles T. Scott; Anantha Prasad; Anantha Prasad

1997-01-01

A geographic information system (GIS) approach was used in conjunction with forest-plot data to develop an integrated moisture index (IMI), which was then used to predict forest productivity (site index) and species composition for forests in Ohio. In this region, typical of eastern hardwoods across the Midwest and southern Appalachians, topographic aspect and position...

[Reliability of the PROFUND index to predict 4-year mortality in polypathological patients].

Science.gov (United States)

Díez-Manglano, Jesús; Del Corral Beamonte, Esther; Ramos Ibáñez, Rosa; Lambán Aranda, María Pilar; Toyas Miazza, Carla; Rodero Roldán, María Del Mar; Ortiz Domingo, Concepción; Munilla López, Eulalia; de Escalante Yangüela, Begoña

2016-09-16

To determine the usefullness of the PROFUND index to assess the risk of global death after 4 years in polypathological patients. Multicenter prospective cohort (Internal Medicine and Geriatrics) study. Polypathological patients admitted between March 1st and June 30th 2011 were included. For each patient, data concerning age, sex, living at home or in a nursing residence, polypathology categories, Charlson, Barthel and Lawton-Brody indexes, Pfeiffer questionnaire, socio-familial Gijon scale, delirium, number of drugs, hemoglobin and creatinine values were gathered, and the PROFUND index was calculated. The follow-up lasted 4 years. We included 441 patients, 324 from Internal Medicine and 117 from Geriatrics, with a mean age of 80.9 (8.7) years. Of them, 245 (55.6%) were women. Heart (62.7%), neurological (41.4%) and respiratory (37.3%) diseases were the most frequent. Geriatrics inpatients were older and more dependants and presented greater cognitive deterioration. After 4 years, 335 (76%) patients died. Mortality was associated with age, dyspnoea, Barthel index<60, delirium, advanced neoplasia and≥4 admissions in the last year. The area under the curve of the PROFUND index was 0.748, 95% CI 0.689-0.806, P<.001 in Internal Medicine and 0.517, 95% CI 0.369-0.666, P=.818 in Geriatrics patients, respectively. The PROFUND index is a reliable tool for predicting long-term global mortality in polypathological patients from Internal Medicine but not from Geriatrics departments. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

Science.gov (United States)

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

2011-01-01

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

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

Science.gov (United States)

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

2014-03-01

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

Method of critical power prediction based on film flow model coupled with subchannel analysis

International Nuclear Information System (INIS)

Tomiyama, Akio; Yokomizo, Osamu; Yoshimoto, Yuichiro; Sugawara, Satoshi.

1988-01-01

A new method was developed to predict critical powers for a wide variety of BWR fuel bundle designs. This method couples subchannel analysis with a liquid film flow model, instead of taking the conventional way which couples subchannel analysis with critical heat flux correlations. Flow and quality distributions in a bundle are estimated by the subchannel analysis. Using these distributions, film flow rates along fuel rods are then calculated with the film flow model. Dryout is assumed to occur where one of the film flows disappears. This method is expected to give much better adaptability to variations in geometry, heat flux, flow rate and quality distributions than the conventional methods. In order to verify the method, critical power data under BWR conditions were analyzed. Measured and calculated critical powers agreed to within ±7%. Furthermore critical power data for a tight-latticed bundle obtained by LeTourneau et al. were compared with critical powers calculated by the present method and two conventional methods, CISE correlation and subchannel analysis coupled with the CISE correlation. It was confirmed that the present method can predict critical powers more accurately than the conventional methods. (author)

Prediction of critical heat flux in vertical pipe flow

International Nuclear Information System (INIS)

Levy, S.; Healzer, J.M.; Abdollahian, D.

1981-01-01

A previously developed semi-empirical model for adiabatic two-phase annular flow ix extended to predict the critical heat flux (CHF) in a vertical pipe. The model exhibits a sharply declining curve of CHF versus steam quality (X) at low X, and is relatively independent of the heat flux distribution. In this region, vaporization of the liquid film controls. At high X, net deposition upon the liquid film becomes important and CHF versus X flattens considerably. In this zone, CHF is dependent upon the heat flux distribution. Model predictions are compared to test data and an empirical correlation. The agreement is generally good if one employs previously reported mass transfer coefficients. (orig.)

Predictive Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study

OpenAIRE

Lee, Da Young; Lee, Eun Seo; Kim, Ji Hyun; Park, Se Eun; Park, Cheol-Young; Oh, Ki-Won; Park, Sung-Woo; Rhee, Eun-Jung; Lee, Won-Young

2016-01-01

The Triglyceride Glucose Index (TyG index) is considered a surrogate marker of insulin resistance. The aim of this study is to investigate whether the TyG index has a predictive role in identifying individuals with a high risk of incident diabetes and to compare it with other indicators of metabolic health. A total 2900 non-diabetic adults who attended five consecutive annual health check-ups at Kangbuk Samsung Hospital was divided into four subgroups using three methods: (1) baseline TyG ind...

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

Science.gov (United States)

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.

Developing Models to Predict the Number of Fire Hotspots from an Accumulated Fuel Dryness Index by Vegetation Type and Region in Mexico

Directory of Open Access Journals (Sweden)

D. J. Vega-Nieva

2018-04-01

Full Text Available Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change. This study addresses the development of models to predict the number of 10-day observed Moderate-Resolution Imaging Spectroradiometer (MODIS active fire hotspots—expressed as a Fire Hotspot Density index (FHD—from an Accumulated Fuel Dryness Index (AcFDI, for 17 main vegetation types and regions in Mexico, for the period 2011–2015. The AcFDI was calculated by applying vegetation-specific thresholds for fire occurrence to a satellite-based fuel dryness index (FDI, which was developed after the structure of the Fire Potential Index (FPI. Linear and non-linear models were tested for the prediction of FHD from FDI and AcFDI. Non-linear quantile regression models gave the best results for predicting FHD using AcFDI, together with auto-regression from previously observed hotspot density values. The predictions of 10-day observed FHD values were reasonably good with R2 values of 0.5 to 0.7 suggesting the potential to be used as an operational tool for predicting the expected number of fire hotspots by vegetation type and region in Mexico. The presented modeling strategy could be replicated for any fire danger index in any region, based on information from MODIS or other remote sensors.

Building waste management core indicators through Spatial Material Flow Analysis: net recovery and transport intensity indexes.

Science.gov (United States)

Font Vivanco, David; Puig Ventosa, Ignasi; Gabarrell Durany, Xavier

2012-12-01

In this paper, the material and spatial characterization of the flows within a municipal solid waste (MSW) management system are combined through a Network-Based Spatial Material Flow Analysis. Using this information, two core indicators are developed for the bio-waste fraction, the Net Recovery Index (NRI) and the Transport Intensity Index (TII), which are aimed at assessing progress towards policy-related sustainable MSW management strategies and objectives. The NRI approaches the capacity of a MSW management system for converting waste into resources through a systematic metabolic approach, whereas the TII addresses efficiency in terms of the transport requirements to manage a specific waste flow throughout the entire MSW management life cycle. Therefore, both indicators could be useful in assessing key MSW management policy strategies, such as the consecution of higher recycling levels (sustainability principle) or the minimization of transport by locating treatment facilities closer to generation sources (proximity principle). To apply this methodological approach, the bio-waste management system of the region of Catalonia (Spain) has been chosen as a case study. Results show the adequacy of both indicators for identifying those points within the system with higher capacity to compromise its environmental, economic and social performance and therefore establishing clear targets for policy prioritization. Moreover, this methodological approach permits scenario building, which could be useful in assessing the outcomes of hypothetical scenarios, thus proving its adequacy for strategic planning. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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 Value of Triglyceride Glucose Index for the Risk of Incident Diabetes: A 4-Year Retrospective Longitudinal Study.

Science.gov (United States)

Lee, Da Young; Lee, Eun Seo; Kim, Ji Hyun; Park, Se Eun; Park, Cheol-Young; Oh, Ki-Won; Park, Sung-Woo; Rhee, Eun-Jung; Lee, Won-Young

The Triglyceride Glucose Index (TyG index) is considered a surrogate marker of insulin resistance. The aim of this study is to investigate whether the TyG index has a predictive role in identifying individuals with a high risk of incident diabetes and to compare it with other indicators of metabolic health. A total 2900 non-diabetic adults who attended five consecutive annual health check-ups at Kangbuk Samsung Hospital was divided into four subgroups using three methods: (1) baseline TyG index; (2) obesity status (body mass index ≥25 kg/m2) and cutoff value of TyG index; (3) obesity status and metabolic health, defined as having fewer than two of the five components of high blood pressure, fasting blood glucose, triglyceride, low high-density lipoprotein cholesterol, and highest decile of homeostasis model assessment-insulin resistance. The development of diabetes was assessed annually using self-questionnaire, fasting glucose, and glycated hemoglobin. We compared the risk of incident diabetes using multivariate Cox analysis. During 11623 person-years there were 101 case of incident diabetes. Subjects with high TyG index had a high risk of diabetes. For TyG index quartiles, hazard ratios (HRs) of quartiles 3 and 4 were 4.06 (p = 0.033) and 5.65 (p = 0.006) respectively. When the subjects were divided by obesity status and cutoff value of TyG index of 8.8, the subgroups with TyG index ≥ 8.8 regardless of obesity had a significantly high risk for diabetes (HR 2.40 [p = 0.024] and 2.25 [p = 0.048]). For obesity status and metabolic health, the two metabolically unhealthy subgroups regardless of obesity had a significantly high risk for diabetes (HRs 2.54 [p = 0.024] and 2.73 [p = 0.021]). In conclusion, the TyG index measured at a single time point may be an indicator of the risk for incident diabetes. The predictive value of the TyG index was comparable to that of metabolic health.

The Optimisation of Processing Condition for Injected Mould Polypropylene-Nanoclay-Gigantochloa Scortechinii based on Melt Flow Index

Science.gov (United States)

Othman, M. H.; Rosli, M. S.; Hasan, S.; Amin, A. M.; Hashim, M. Y.; Marwah, O. M. F.; Amin, S. Y. M.

2018-03-01

The fundamental knowledge of flow behaviour is essential in producing various plastic parts injection moulding process. Moreover, the adaptation of advanced polymer-nanocomposites such as polypropylene-nanoclay with natural fibres, for instance Gigantochloa Scortechinii may boost up the mechanical properties of the parts. Therefore, this project was proposed with the objective to optimise the processing condition of injected mould polypropylene-nanoclay-Gigantochloa Scortechini fibres based on the flow behaviour, which was melt flow index. At first, Gigantochloa Scortechinii fibres have to be preheated at temperature 120°C and then mixed with polypropylene, maleic anhydride modified polypropylene oligomers (PPgMA) and nanoclay by using Brabender Plastograph machine. Next, forms of pellets were produced from the samples by using Granulator machine for use in the injection moulding process. The design of experiments that was used in the injection moulding process was Taguchi Method Orthogonal Array -L934. Melt Flow Index (MF) was selected as the response. Based on the results, the value of MFI increased when the fiber content increase from 0% to 3%, which was 17.78 g/10min to 22.07 g/10min and decreased from 3% to 6%, which was 22.07 g/10min to 20.05 g/10min and 3%, which gives the highest value of MFI. Based on the signal to ratio analysis, the most influential parameter that affects the value of MFI was the melt temperature. The optimum parameter for 3% were 170°C melt temperature, 35% packing pressure, 30% screw speed and 3 second filling time.

Predictions of the marviken subcooled critical mass flux using the critical flow scaling parameters

Energy Technology Data Exchange (ETDEWEB)

Park, Choon Kyung; Chun, Se Young; Cho, Seok; Yang, Sun Ku; Chung, Moon Ki [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1998-12-31

A total of 386 critical flow data points from 19 runs of 27 runs in the Marviken Test were selected and compared with the predictions by the correlations based on the critical flow scaling parameters. The results show that the critical mass flux in the very large diameter pipe can be also characterized by two scaling parameters such as discharge coefficient and dimensionless subcooling (C{sub d,ref} and {Delta}{Tau}{sup *} {sub sub}). The agreement between the measured data and the predictions are excellent. 8 refs., 8 figs. 1 tab. (Author)

Predictions of the marviken subcooled critical mass flux using the critical flow scaling parameters

Energy Technology Data Exchange (ETDEWEB)

Park, Choon Kyung; Chun, Se Young; Cho, Seok; Yang, Sun Ku; Chung, Moon Ki [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1997-12-31

A total of 386 critical flow data points from 19 runs of 27 runs in the Marviken Test were selected and compared with the predictions by the correlations based on the critical flow scaling parameters. The results show that the critical mass flux in the very large diameter pipe can be also characterized by two scaling parameters such as discharge coefficient and dimensionless subcooling (C{sub d,ref} and {Delta}{Tau}{sup *} {sub sub}). The agreement between the measured data and the predictions are excellent. 8 refs., 8 figs. 1 tab. (Author)

Incorporation of Duffing Oscillator and Wigner-Ville Distribution in Traffic Flow Prediction

Directory of Open Access Journals (Sweden)

Anamarija L. Mrgole

2017-02-01

Full Text Available The main purpose of this study was to investigate the use of various chaotic pattern recognition methods for traffic flow prediction. Traffic flow is a variable, dynamic and complex system, which is non-linear and unpredictable. The emergence of traffic flow congestion in road traffic is estimated when the traffic load on a specific section of the road in a specific time period is close to exceeding the capacity of the road infrastructure. Under certain conditions, it can be seen in concentrating chaotic traffic flow patterns. The literature review of traffic flow theory and its connection with chaotic features implies that this kind of method has great theoretical and practical value. Researched methods of identifying chaos in traffic flow have shown certain restrictions in their techniques but have suggested guidelines for improving the identification of chaotic parameters in traffic flow. The proposed new method of forecasting congestion in traffic flow uses Wigner-Ville frequency distribution. This method enables the display of a chaotic attractor without the use of reconstruction phase space.

The Predictive Value of the Foot Posture Index on Dynamic Function

DEFF Research Database (Denmark)

Mølgaard, Carsten Møller; Olesen Gammelgaard, Christian; Nielsen, R. G.

2008-01-01

Keenan et. al. identified the six-item version of the Foot Posture Index (FPI) as a valid, simple and clinically useful tool. The model combines measures of the standing foot posture in multiple planes and anatomical segments. It provides an alternative to existing static clinical measures when...... dynamic measures are not feasible. Redmond et. al. found the model able to predict 41% of the variation in the complex rotation of the ankle joint, representing inversion/eversion, during midstance of walking. To our knowledge no studies have been published on the relationship between FPI and the movement...

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

Science.gov (United States)

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

Manuela Maria Marin

2013-11-01

Full Text Available 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.

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

Science.gov (United States)

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

Prediction, analysis and solution of flow inversion phenomenon in a typical MTR reactor with upward core cooling

International Nuclear Information System (INIS)

El-Morshedy, Salah El-Din

2010-01-01

Research reactors of power greater than 20 MW are usually designed to be cooled with upward coolant flow direction inside the reactor core. This is mainly to prevent flow inversion problems following a pump coast down. However, in some designs and under certain operating conditions, flow inversion phenomenon is predicted. In the present work, the best-estimate Material Testing Reactors Thermal-Hydraulic Analysis program (MTRTHA) is used to simulate a typical MTR reactor behavior with upward cooling under a hypothetical case of loss of off-site power. The flow inversion phenomenon is predicted under certain decay heat and/or pool temperature values below the design values. The reactor simulation under loss of off-site power is performed for two cases namely; two-flap valves open and one flap-valve fails to open. The model results for the flow inversion phenomenon prediction is analyzed and a solution of the problem is suggested. (orig.)

ASSERT and COBRA predictions of flow distribution in vertical bundles

International Nuclear Information System (INIS)

Tahir, A.; Carver, M.B.

1983-01-01

COBRA and ASSERT are subchannel codes which compute flow and enthalpy distributions in rod bundles. COBRA is a well known code, ASSERT is under development at CRNL. This paper gives a comparison of the two codes with boiling experiments in vertical seven rod bundles. ASSERT predictions of the void distribution are shown to be in good agreement with reported experimental results, while COBRA predictions are unsatisfactory. The mixing models in both COBRA and ASSERT are briefly discussed. The reasons for the failure of COBRA-IV and the success of ASSERT in simulating the experiments are highlighted

Epileptic Seizure Prediction Using a New Similarity Index for Chaotic Signals

Science.gov (United States)

Niknazar, Hamid; Nasrabadi, Ali Motie

Epileptic seizures are generated by abnormal activity of neurons. The prediction of epileptic seizures is an important issue in the field of neurology, since it may improve the quality of life of patients suffering from drug resistant epilepsy. In this study a new similarity index based on symbolic dynamic techniques which can be used for extracting behavior of chaotic time series is presented. Using Freiburg EEG dataset, it is found that the method is able to detect the behavioral changes of the neural activity prior to epileptic seizures, so it can be used for prediction of epileptic seizure. A sensitivity of 63.75% with 0.33 false positive rate (FPR) in all 21 patients and sensitivity of 96.66% with 0.33 FPR in eight patients were achieved using the proposed method. Moreover, the method was evaluated by applying on Logistic and Tent map with different parameters to demonstrate its robustness and ability in determining similarity between two time series with the same chaotic characterization.

Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

DEFF Research Database (Denmark)

Naveed, Muhammad; Møldrup, Per; Schaap, Marcel G

2016-01-01

was to investigate the predictive performance of previously developed empirical models for both water and air flow and to explore the potential applicability of X-ray computed tomography (CT)-derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height......Prediction and modeling of localized flow processes in macropores is of crucial importance for sustaining both soil and water quality. However, currently there are no reliable means to predict preferential flow due to its inherently large spatial variability. The aim of this study......) were extracted from the topsoil (5 cm to 8.5 cm depth) in a 15m15m grid from an agricultural field located in Silstrup, Denmark. All soil columns were scanned with an industrial X-ray CT scanner (129 μm resolution) and later employed for measurement of saturated hydraulic conductivity, air permeability...

Downstream flow top width prediction in a river system | Choudhury ...

African Journals Online (AJOL)

ANFIS, ARIMA and Hybrid Multiple Inflows Muskingum models (HMIM) were applied to simulate and forecast downstream discharge and flow top widths in a river system. The ANFIS model works on a set of linguistic rules while the ARIMA model uses a set of past values to predict the next value in a time series. The HMIM ...

Sensory prediction on a whiskered robot: A tactile analogy to "optic flow"

Directory of Open Access Journals (Sweden)

Christopher L Schroeder

2012-10-01

Full Text Available 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 1x5 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.

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

Science.gov (United States)

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

PREDICTION OF OUTCOME USING THE MANNHEIM PERITONITIS INDEX IN CASES OF PERITONITIS

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Sanjeev

2015-08-01

Full Text Available BACKGROUND: Peritonitis still presents an extremely common & dreaded problem in emergency surgery. Despite aggressive surgical techniques, the prognosis of peritonitis and intra - abdominal sepsis is very poor, especially when multiple organ failure develops. Therefore early objective & reliable classification of the severity of peritonitis and intra - abdominal sepsis is needed not only to predict prognosis & to select patients for these aggressive surgical techniques but also to evaluate & compare the results of different treatment regimens. So, in this prospective st udy of 60 cases of peritonitis, the reliability of the Mannheim peritonitis index is assessed & its predictive power evaluated. MATERIALS & METHOD S : This prospective study was carried out in the department of surgery, GMCH, Udaipur from June 2014 to June 2 015 after taking the permission from institutional ethics committee. Patients from both sexes of various age groups having peritonitis of varied aetiology & who had undergone laparotomy were taken. A detailed history, thorough clinical examination & necess ary investigations were performed in e ach case according to planned p r o forma. After resuscitation laparotomy was done & operative findings were noted carefully and a proper note on the progress of each patient was maintained and any complications encounter ed were noted. So, early classification of patients presenting with peritonitis by means of objective scoring system was done to select patients for aggressive surgery & overall morbidity & mortality were analyzed. RESULTS: Total 60 patients of peritonitis were examined and common causes were peptic (61.6%, typhoid (21.6% and appendicular (8.3 %. Most common age group was found to be 21 to 50 years and male to female ratio was 4:1. Peritonitis was more common in patients involved in hard work and chronic Be di smokers (61.6%. About 46% of patients who presented for treatment within 48 hours of onset of illness

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

Science.gov (United States)

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.

Multi-physics Model for the Aging Prediction of a Vanadium Redox Flow Battery System

International Nuclear Information System (INIS)

Merei, Ghada; Adler, Sophie; Magnor, Dirk; Sauer, Dirk Uwe

2015-01-01

Highlights: • Present a multi-physics model of vanadium redox-flow battery. • This model is essential for aging prediction. • It is applicable for VRB system of different power and capacity ratings. • Good results comparing with current research in this field. - Abstract: The all-vanadium redox-flow battery is an attractive candidate to compensate the fluctuations of non-dispatchable renewable energy generation. While several models for vanadium redox batteries have been described yet, no model has been published, which is adequate for the aging prediction. Therefore, the present paper presents a multi-physics model which determines all parameters that are essential for an aging prediction. In a following paper, the corresponding aging model of vanadium redox flow battery (VRB) is described. The model combines existing models for the mechanical losses and temperature development with new approaches for the batteries side reactions. The model was implemented in Matlab/Simulink. The modeling results presented in the paper prove to be consistent with the experimental results of other research groups

Investigations of internal turbulent flows in a low-head tubular pump and its performance predictions

International Nuclear Information System (INIS)

Tang, X L; Chen, X S; Wang, F J; Yang, W; Wu, Y L

2012-01-01

Based on the RANS equations, standard k−ε turbulence model and SIMPLE algorithm, the internal turbulent flows in a low-head tubular pump were simulated by using the FLUENT software. Based on the predicted flow fields, the external performance curves including the head-discharge, efficiency-discharge and power-discharge curves were further obtained. The calculated results indicate that the internal flow pattern is smooth at the best efficiency point (BEP). When it works under off-design operating cases, the flow pattern inside the diffuser and the discharge passage is disorder, and at the same time, the hydraulic losses mainly come from the secondary flows. At large flow rates, the minimum static pressure near the inlet of the blade pressure surfaces due to the negative attack angle. At small flow rates, the minimum value happens near the inlet of the suction surfaces. At the BEP, the lowest static pressure appears in the region behind the suction surfaces inlet. The newly-designed model is validated by the comparisons between its predicted external performance and the experimental data of the JGM-3 model. This research provides some important references for the optimization of a low-head tubular pump.

Evaluation of renal resistive index in cirrhotic patients for predicting the hepatirenal syndrome

Energy Technology Data Exchange (ETDEWEB)

Baek, Seung Yon; Kim, Hyae young; Yi, Sun Young [Ewha WoMans Univ. Mokdong Hospital, Seoul (Korea, Republic of)

1996-04-01

To evaluate the usefulness of renal resistive index(RI) in patients with liver cirrhosis as an indicator for predicting hepatorenal syndrome. Renal RIs of thirty cirrhotic patients were analyzed using the gray-scale and Doppler ultrasonograms. As a control group, eight normal subjects were included. Renal RIs were measured at three sites of interlobar or arcuate arteries of both kidneys. The patients were divided into three groups (A, B, or C) according to the Child-Turcotte-Pugh classification and their serum BUN and creatinine levels were compared. We determined whether RIs of normal controls differed from those of cirrhotic patients or whether RIs of cirrhotic patients correlated with the Child-Turcotte-Pugh classification or BUN and creatinine levels. Mean RIs(0.63 {+-}0.33) of normal subjects were statistically different from those(0.67 {+-} 0.05) of cirrhotic patients(P=0.009). RIs of group A(n=6), B(n=9) and C(n=15) were 0.65 {+-} 0.03, 0.65 {+-} 0.04 and 0.70 {+-} 0.04, respectively. The ANOVA test revealed statistically significant differences between the three groups(F ratio=4.472, P=0.021). RIs did not correlate with BUN or creatinine levels. RI could be used as an index for predicting hepatorenal syndrome before the renal function becomes impaired.

Short-range dynamics and prediction of mesoscale flow patterns in the MISTRAL field experiment

Energy Technology Data Exchange (ETDEWEB)

Weber, R.O.; Kaufmann, P.; Talkner, P. [Paul Scherrer Inst. (PSI), Villigen (Switzerland)

1997-06-01

In a limited area of about 50 km by 50 km with complex topography, wind measurements on a dense network were performed during the MISTRAL field experiment in 1991-1992. From these data the characteristic wind fields were identified by an automated classification method. The dynamics of the resulting twelve typical regional flow patterns is studied. It is discussed how transitions between the flow patterns take place and how well the transition probabilities can be described in the framework of a Markov model. Guided by this discussion, a variety of prediction models were tested which allow a short-term forecast of the flow pattern type. It is found that a prediction model which uses forecast information from the synoptic scale has the best forecast skill. (author) 2 figs., 7 refs.

Neural Network Predictive Control for Vanadium Redox Flow Battery

Directory of Open Access Journals (Sweden)

Hai-Feng Shen

2013-01-01

Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

International Nuclear Information System (INIS)

Goudarzi, Sobhan; Jafari, Sajad; Moradi, Mohammad Hassan; Sprott, J.C.

2016-01-01

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

NARX prediction of some rare chaotic flows: Recurrent fuzzy functions approach

Energy Technology Data Exchange (ETDEWEB)

Goudarzi, Sobhan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Jafari, Sajad, E-mail: sajadjafari@aut.ac.ir [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Moradi, Mohammad Hassan [Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413 (Iran, Islamic Republic of); Sprott, J.C. [Department of Physics, University of Wisconsin–Madison, Madison, WI 53706 (United States)

2016-02-15

The nonlinear and dynamic accommodating capability of time domain models makes them a useful representation of chaotic time series for analysis, modeling and prediction. This paper is devoted to the modeling and prediction of chaotic time series with hidden attractors using a nonlinear autoregressive model with exogenous inputs (NARX) based on a novel recurrent fuzzy functions (RFFs) approach. Case studies of recently introduced chaotic systems with hidden attractors plus classical chaotic systems demonstrate that the proposed modeling methodology exhibits better prediction performance from different viewpoints (short term and long term) compared to some other existing methods. - Highlights: • A new method is proposed for prediction of chaotic time series. • This method is based on novel recurrent fuzzy functions (RFFs) approach. • Some rare chaotic flows are used as test systems. • The new method shows proper performance in short-term prediction. • It also shows proper performance in prediction of attractor's topology.

PIV study of flow through porous structure using refractive index matching

Science.gov (United States)

Häfeli, Richard; Altheimer, Marco; Butscher, Denis; Rudolf von Rohr, Philipp

2014-05-01

An aqueous solution of sodium iodide and zinc iodide is proposed as a fluid that matches the refractive index of a solid manufactured by rapid prototyping. This enabled optical measurements in single-phase flow through porous structures. Experiments were also done with an organic index-matching fluid (anisole) in porous structures of different dimensions. To compare experiments with different viscosities and dimensions, we employed Reynolds similarity to deduce the scaling laws. One of the target quantities of our investigation was the dissipation rate of turbulent kinetic energy. Different models for the dissipation rate estimation were evaluated by comparing isotropy ratios. As in many other studies also, our experiments were not capable of resolving the velocity field down to the Kolmogorov length scale, and therefore, the dissipation rate has to be considered as underestimated. This is visible in experiments of different relative resolutions. However, being near the Kolmogorov scale allows estimating a reproducible, yet underestimated spatial distribution of dissipation rate inside the porous structure. Based on these results, the model was used to estimate the turbulent diffusivity. Comparing it to the dispersion coefficient obtained in the same porous structure, we conclude that even at the turbulent diffusivity makes up only a small part of mass transfer in axial direction. The main part is therefore attributed to Taylor dispersion.

Turbulence prediction in two-dimensional bundle flows using large eddy simulation

Energy Technology Data Exchange (ETDEWEB)

Ibrahim, W.A.; Hassan, Y.A. [Texas A& M Univ., College Station, TX (United States)

1995-09-01

Turbulent flow is characterized by random fluctuations in the fluid velocity and by intense mixing of the fluid. Due to velocity fluctuations, a wide range of eddies exists in the flow field. Because these eddies carry mass, momentum, and energy, this enhanced mixing can sometimes lead to serious problems, such as tube vibrations in many engineering systems that include fluid-tube bundle combinations. Nuclear fuel bundles and PWR steam generators are existing examples in nuclear power plants. Fluid-induced vibration problems are often discovered during the operation of such systems because some of the fluid-tube interaction characteristics are not fully understood. Large Eddy Simulation, incorporated in a three dimensional computer code, became one of the promising techniques to estimate flow turbulence, predict and prevent of long-term tube fretting affecting PWR steam generators. the present turbulence investigations is a step towards more understanding of fluid-tube interaction characteristics by comparing the tube bundles with various pitch-to-diameter ratios were performed. Power spectral densities were used for comparison with experimental data. Correlations, calculations of different length scales in the flow domain and other important turbulent-related parameters were calculated. Finally, important characteristics of turbulent flow field were presented with the aid of flow visualization with tracers impeded in the flow field.

Strain dyssynchrony index determined by three-dimensional speckle area tracking can predict response to cardiac resynchronization therapy

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Onishi Tetsuari

2011-04-01

Full Text Available Abstract Background We have previously reported strain dyssynchrony index assessed by two-dimensional speckle tracking strain, and a marker of both dyssynchrony and residual myocardial contractility, can predict response to cardiac resynchronization therapy (CRT. A newly developed three-dimensional (3-D speckle tracking system can quantify endocardial area change ratio (area strain, which coupled with the factors of both longitudinal and circumferential strain, from all 16 standard left ventricular (LV segments using complete 3-D pyramidal datasets. Our objective was to test the hypothesis that strain dyssynchrony index using area tracking (ASDI can quantify dyssynchrony and predict response to CRT. Methods We studied 14 heart failure patients with ejection fraction of 27 ± 7% (all≤35% and QRS duration of 172 ± 30 ms (all≥120 ms who underwent CRT. Echocardiography was performed before and 6-month after CRT. ASDI was calculated as the average difference between peak and end-systolic area strain of LV endocardium obtained from 3-D speckle tracking imaging using 16 segments. Conventional dyssynchrony measures were assessed by interventricular mechanical delay, Yu Index, and two-dimensional radial dyssynchrony by speckle-tracking strain. Response was defined as a ≥15% decrease in LV end-systolic volume 6-month after CRT. Results ASDI ≥ 3.8% was the best predictor of response to CRT with a sensitivity of 78%, specificity of 100% and area under the curve (AUC of 0.93 (p Conclusions ASDI can predict responders and LV reverse remodeling following CRT. This novel index using the 3-D speckle tracking system, which shows circumferential and longitudinal LV dyssynchrony and residual endocardial contractility, may thus have clinical significance for CRT patients.

Ski jump takeoff performance predictions for a mixed-flow, remote-lift STOVL aircraft

Science.gov (United States)

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.

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

Science.gov (United States)

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 droplet deposition around BWR fuel spacer by FEM flow analysis

International Nuclear Information System (INIS)

Yamamoto, Yasushi; Morooka, Shinichi

1997-01-01

The critical power of the BWR fuel assembly has been remarkably increased. That increase mainly depends on the improvement of the spacer which keeps fixed gaps between fuel rods. So far, these improvements have been carried out on the basis of what developers consider to be appropriate and the results of mockup tests of the BWR fuel assembly. However, continued reliance on these approaches for the development of a higher performance fuel assembly will prove time-consuming and costly. Therefore, it is hoped that the spacer effects for the critical power can be investigated by computer simulation, and it is significantly important to develop the critical power prediction method. Direct calculation of the two-phase flow in a BWR fuel channel s still difficult. Accordingly, a new method for predicting the critical power was proposed. Our method consists of CFD (computer fluid dynamics) code based on the single-phase flow analysis method and the subchannel analysis code. To verify our method, the critical power predictions for various spacer geometries were performed. The predicted results of the critical power were compared with the experimental data. The result of the comparison showed a good agreement and the applicability of our method for various spacer geometries. (author)

Experimental comparison between speech transmission index, rapid speech transmission index, and speech intelligibility index.

Science.gov (United States)

Larm, Petra; Hongisto, Valtteri

2006-02-01

During the acoustical design of, e.g., auditoria or open-plan offices, it is important to know how speech can be perceived in various parts of the room. Different objective methods have been developed to measure and predict speech intelligibility, and these have been extensively used in various spaces. In this study, two such methods were compared, the speech transmission index (STI) and the speech intelligibility index (SII). Also the simplification of the STI, the room acoustics speech transmission index (RASTI), was considered. These quantities are all based on determining an apparent speech-to-noise ratio on selected frequency bands and summing them using a specific weighting. For comparison, some data were needed on the possible differences of these methods resulting from the calculation scheme and also measuring equipment. Their prediction accuracy was also of interest. Measurements were made in a laboratory having adjustable noise level and absorption, and in a real auditorium. It was found that the measurement equipment, especially the selection of the loudspeaker, can greatly affect the accuracy of the results. The prediction accuracy of the RASTI was found acceptable, if the input values for the prediction are accurately known, even though the studied space was not ideally diffuse.

Can transient elastography, Fib-4, Forns Index, and Lok Score predict esophageal varices in HCV-related cirrhotic patients?

Science.gov (United States)

Hassan, Eman M; Omran, Dalia A; El Beshlawey, Mohamad L; Abdo, Mahmoud; El Askary, Ahmad

2014-02-01

Gastroesophageal varices are present in approximately 50% of patients with liver cirrhosis. The aim of this study was to evaluate liver stiffness measurement (LSM), Fib-4, Forns Index and Lok Score as noninvasive predictors of esophageal varices (EV). This prospective study included 65 patients with HCV-related liver cirrhosis. All patients underwent routine laboratory tests, transient elastograhy (TE) and esophagogastroduodenoscopy. FIB-4, Forns Index and Lok Score were calculated. The diagnostic performances of these methods were assessed using sensitivity, specificity, positive predictive value, negative predictive value, accuracy and receiver operating characteristic curves. All predictors (LSM, FIB-4, Forns Index and Lok Score) demonstrated statistically significant correlation with the presence and the grade of EV. TE could diagnose EV at a cutoff value of 18.2kPa. Fib-4, Forns Index, and Lok Score could diagnose EV at cutoff values of 2.8, 6.61 and 0.63, respectively. For prediction of large varices (grade 2, 3), LSM showed the highest accuracy (80%) with a cutoff of 22.4kPa and AUROC of 0.801. Its sensitivity was 84%, specificity 72%, PPV 84% and NPV 72%. The diagnostic accuracies of FIB-4, Forns Index and Lok Score were 70%, 70% and76%, respectively, at cutoffs of 3.3, 6.9 and 0.7, respectively. For diagnosis of large esophageal varices, adding TE to each of the other diagnostic indices (serum fibrosis scores) increased their sensitivities with little decrease in their specificities. Moreover, this combination decreased the LR- in all tests. Noninvasive predictors can restrict endoscopic screening. This is very important as non invasiveness is now a major goal in hepatology. Copyright © 2013 Elsevier España, S.L. and AEEH y AEG. All rights reserved.

Numerical predictions of particle dispersed two-phase flows, using the LSD and SSF models

International Nuclear Information System (INIS)

Avila, R.; Cervantes de Gortari, J.; Universidad Nacional Autonoma de Mexico, Mexico City. Facultad de Ingenieria)

1988-01-01

A modified version of a numerical scheme which is suitable to predict parabolic dispersed two-phase flow, is presented. The original version of this scheme was used to predict the test cases discussed during the 3rd workshop on TPF predictions in Belgrade, 1986. In this paper, two particle dispersion models are included which use the Lagrangian approach predicting test case 1 and 3 of the 4th workshop. For the prediction of test case 1 the Lagrangian Stochastic Deterministic model (LSD) is used providing acceptable good results of mean and turbulent quantities for both solid and gas phases; however, the computed void fraction distribution is not in agreement with the measurements at locations away from the inlet, especially near the walls. Test case 3 is predicted using both the LSD and the Stochastic Separated Flow (SSF) models. It was found that the effects of turbulence modulation are large when the LSD model is used, whereas the particles have a negligible influence on the continuous phase if the SSF model is utilized for the computations. Predictions of gas phase properties based on both models agree well with measurements; however, the agreement between calculated and measured solid phase properties is less satisfactory. (orig.)

Prediction of flow and drawdown for the site characterization and validation site in the Stripa Mine

International Nuclear Information System (INIS)

Long, J.C.S.; Mauldon, A.D.; Nelson, K.; Martel, S.; Fuller, P.; and Karasaki, K.

1992-01-01

Geophysical and hydrologic data from a location in the Stripa Mine in Sweden, called the Site Characterization and Validation (SCV) block, has been used to create a series of models for flow through the fracture network. The models can be characterized as ''equivalent discontinuum'' models. Equivalent discontinuum models are derived starting from a specified lattice or 6 ''template''. An inverse analysis called ''Simulated Annealing'' is used to make a random search through the elements of the lattice to find a configuration that can reproduce the measured responses. Evidence at Stripa points to hydrology which is dominated by fracture zones. These have been identified and located through extensive characterization efforts. Lattice templates were arranged to lie on the fracture zones identified by Black and Olsson. The fundamental goal of this project was to build a fracture flow model based an initial data set, and use this model to make predictions of the flow behavior during a new test. Then given data from the new test, predict a second test, etc. The first data set was an interference test called C1-2. Both a two-dimensional and a three-dimensional model were annealed to the C1-2 data and use this model to predict the behavior of the Simulated Drift Experiment (SDE). The SDE measured the flow into, and drawdown due to reducing the pressure in a group of 6 parallel boreholes. Then both the C1-2 and SDE data were used to predict the flow into and drawdown due to an excavation, the Validation Drift (VD), made through the boreholes. Finally, all the data was used to predict the hydrologic response to opening another hole, T1

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

Science.gov (United States)

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.

Science.gov (United States)

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.

Implementation of a phenomenological DNB prediction model based on macroscale boiling flow processes in PWR fuel bundles

International Nuclear Information System (INIS)

Mohitpour, Maryam; Jahanfarnia, Gholamreza; Shams, Mehrzad

2014-01-01

Highlights: • A numerical framework was developed to mechanistically predict DNB in PWR bundles. • The DNB evaluation module was incorporated into the two-phase flow solver module. • Three-dimensional two-fluid model was the basis of two-phase flow solver module. • Liquid sublayer dryout model was adapted as CHF-triggering mechanism in DNB module. • Ability of DNB modeling approach was studied based on PSBT DNB tests in rod bundle. - Abstract: In this study, a numerical framework, comprising of a two-phase flow subchannel solver module and a Departure from Nucleate Boiling (DNB) evaluation module, was developed to mechanistically predict DNB in rod bundles of Pressurized Water Reactor (PWR). In this regard, the liquid sublayer dryout model was adapted as the Critical Heat Flux (CHF) triggering mechanism to reduce the dependency of the model on empirical correlations in the DNB evaluation module. To predict local flow boiling processes, a three-dimensional two-fluid formalism coupled with heat conduction was selected as the basic tool for the development of the two-phase flow subchannel analysis solver. Evaluation of the DNB modeling approach was performed against OECD/NRC NUPEC PWR Bundle tests (PSBT Benchmark) which supplied an extensive database for the development of truly mechanistic and consistent models for boiling transition and CHF. The results of the analyses demonstrated the need for additional assessment of the subcooled boiling model and the bulk condensation model implemented in the two-phase flow solver module. The proposed model slightly under-predicts the DNB power in comparison with the ones obtained from steady-state benchmark measurements. However, this prediction is acceptable compared with other codes. Another point about the DNB prediction model is that it has a conservative behavior. Examination of the axial and radial position of the first detected DNB using code-to-code comparisons on the basis of PSBT data indicated that the our

Prediction of stably stratified homogeneous shear flows with second-order turbulence models

International Nuclear Information System (INIS)

Pereira, J C F; Rocha, J M P

2010-01-01

The present study investigated the role of pressure-correlation second-order turbulence modelling schemes on the predicted behaviour of stably stratified homogeneous vertical-sheared turbulence. The pressure-correlation terms were modelled with a nonlinear formulation (Craft 1991), which was compared with a linear pressure-strain model and the 'isotropization of production' model for the pressure-scalar correlation. Two additional modelling issues were investigated: the influence of the buoyancy term in the kinetic energy dissipation rate equation and the time scale in the thermal production term in the scalar variance dissipation equation. The predicted effects of increasing the Richardson number on turbulence characteristics were compared against a comprehensive set of direct numerical simulation databases. The linear models provide a broadly satisfactory description of the major effects of the Richardson number on stratified shear flow. The buoyancy term in the dissipation equation of the turbulent kinetic energy generates excessively low levels of dissipation. For moderate and large Richardson numbers, the term yields unrealistic linear oscillations in the shear and buoyancy production terms, and therefore should be dropped in this flow (or at least their coefficient c ε3 should be substantially reduced from its standard value). The mechanical dissipation time scale provides marginal improvements in comparison to the scalar time scale in the production. The observed inaccuracy of the linear model in predicting the magnitude of the effects on the velocity anisotropy was demonstrated to be attributed mainly to the defective behaviour of the pressure-correlation model, especially for stronger stratification. The turbulence closure embodying a nonlinear formulation for the pressure-correlations and specific versions of the dissipation equations failed to predict the tendency of the flow to anisotropy with increasing stratification. By isolating the effects of the

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

Directory of Open Access Journals (Sweden)

Qiang Shang

Full Text Available 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.

Frequency prediction by linear stability analysis around mean flow

Science.gov (United States)

Bengana, Yacine; Tuckerman, Laurette

2017-11-01

The frequency of certain limit cycles resulting from a Hopf bifurcation, such as the von Karman vortex street, can be predicted by linear stability analysis around their mean flows. Barkley (2006) has shown this to yield an eigenvalue whose real part is zero and whose imaginary part matches the nonlinear frequency. This property was named RZIF by Turton et al. (2015); moreover they found that the traveling waves (TW) of thermosolutal convection have the RZIF property. They explained this as a consequence of the fact that the temporal Fourier spectrum is dominated by the mean flow and first harmonic. We could therefore consider that only the first mode is important in the saturation of the mean flow as presented in the Self-Consistent Model (SCM) of Mantic-Lugo et al. (2014). We have implemented a full Newton's method to solve the SCM for thermosolutal convection. We show that while the RZIF property is satisfied far from the threshold, the SCM model reproduces the exact frequency only very close to the threshold. Thus, the nonlinear interaction of only the first mode with itself is insufficiently accurate to estimate the mean flow. Our next step will be to take into account higher harmonics and to apply this analysis to the standing waves, for which RZIF does not hold.

Predicting transition in two- and three-dimensional separated flows

International Nuclear Information System (INIS)

Cutrone, L.; De Palma, P.; Pascazio, G.; Napolitano, M.

2008-01-01

This paper is concerned with the numerical prediction of two- and three-dimensional transitional separated flows of turbomachinery interest. The recently proposed single-point transition model based on the use of a laminar kinetic energy transport equation is considered, insofar as it does not require to evaluate any integral parameter, such as boundary-layer thickness, and is thus directly applicable to three-dimensional flows. A well established model, combining a transition-onset correlation with an intermittency transport equation, is also used for comparison. Both models are implemented within a Reynolds-averaged Navier-Stokes solver employing a low-Reynolds-number k-ω turbulence model. The performance of the transition models have been evaluated and tested versus well-documented incompressible flows past a flat plate with semi-circular leading edge, namely: tests T3L2, T3L3, T3L5, and T3LA1 of ERCOFTAC, with different Reynolds numbers and free-stream conditions, the last one being characterized by a non-zero pressure gradient. In all computations, the first model has proven as adequate as or superior to the second one and has been then applied with success to two more complex test cases, for which detailed experimental data are available in the literature, namely: the two- and three-dimensional flows through the T106 linear turbine cascade

Assessment of a turbulence model for numerical predictions of sheet-cavitating flows in centrifugal pumps

Energy Technology Data Exchange (ETDEWEB)

Liu, Houlin; Wang, Yong; Liu, Dongxi; Yuan, Shouqi; Wang, Jian [Jiangsu University, Zhenjiang (China)

2013-09-15

Various approaches have been developed for numerical predictions of unsteady cavitating turbulent flows. To verify the influence of a turbulence model on the simulation of unsteady attached sheet-cavitating flows in centrifugal pumps, two modified RNG k-ε models (DCM and FBM) are implemented in ANSYS-CFX 13.0 by second development technology, so as to compare three widespread turbulence models in the same platform. The simulation has been executed and compared to experimental results for three different flow coefficients. For four operating conditions, qualitative comparisons are carried out between experimental and numerical cavitation patterns, which are visualized by a high-speed camera and depicted as isosurfaces of vapor volume fraction α{sub v} = 0.1, respectively. The comparison results indicate that, for the development of the sheet attached cavities on the suction side of the impeller blades, the numerical results with different turbulence models are very close to each other and overestimate the experiment ones slightly. However, compared to the cavitation performance experimental curves, the numerical results have obvious difference: the prediction precision with the FBM is higher than the other two turbulence models. In addition, the loading distributions around the blade section at midspan are analyzed in detail. The research results suggest that, for numerical prediction of cavitating flows in centrifugal pumps, the turbulence model has little influence on the development of cavitation bubbles, but the advanced turbulence model can significantly improve the prediction precision of head coefficients and critical cavitation numbers.

Development of a model to predict flow oscillations in low-flow sodium boiling

International Nuclear Information System (INIS)

Levin, A.E.; Griffith, P.

1980-04-01

Tests performed in a small scale water loop showed that voiding oscillations, similar to those observed in sodium, were present in water, as well. An analytical model, appropriate for either sodium or water, was developed and used to describe the water flow behavior. The experimental results indicate that water can be successfully employed as a sodium simulant, and further, that the condensation heat transfer coefficient varies significantly during the growth and collapse of vapor slugs during oscillations. It is this variation, combined with the temperature profile of the unheated zone above the heat source, which determines the oscillatory behavior of the system. The analytical program has produced a model which qualitatively does a good job in predicting the flow behavior in the wake experiment. The amplitude discrepancies are attributable to experimental uncertainties and model inadequacies. Several parameters (heat transfer coefficient, unheated zone temperature profile, mixing between hot and cold fluids during oscillations) are set by the user. Criteria for the comparison of water and sodium experiments have been developed

Experimental investigation of gas flow rate and electric field effect on refractive index and electron density distribution of cold atmospheric pressure-plasma by optical method, Moiré deflectometry

Science.gov (United States)

Khanzadeh, Mohammad; Jamal, Fatemeh; Shariat, Mahdi

2018-04-01

Nowadays, cold atmospheric-pressure (CAP) helium plasma jets are widely used in material processing devices in various industries. Researchers often use indirect and spectrometric methods for measuring the plasma parameters which are very expensive. In this paper, for the first time, characterization of CAP, i.e., finding its parameters such as refractive index and electron density distribution, was carried out using an optical method, Moiré deflectometry. This method is a wave front analysis technique based on geometric optics. The advantages of this method are simplicity, high accuracy, and low cost along with the non-contact, non-destructive, and direct measurement of CAP parameters. This method demonstrates that as the helium gas flow rate decreases, the refractive index increases. Also, we must note that the refractive index is larger in the gas flow consisting of different flow rates of plasma comparing with the gas flow without the plasma.

Screening for Sleep Apnoea in Mild Cognitive Impairment: The Utility of the Multivariable Apnoea Prediction Index

Directory of Open Access Journals (Sweden)

Georgina Wilson

2014-01-01

Full Text Available Purpose. Mild cognitive impairment (MCI is considered an “at risk” state for dementia and efforts are needed to target modifiable risk factors, of which Obstructive sleep apnoea (OSA is one. This study aims to evaluate the predictive utility of the multivariate apnoea prediction index (MAPI, a patient self-report survey, to assess OSA in MCI. Methods. Thirty-seven participants with MCI and 37 age-matched controls completed the MAPI and underwent polysomnography (PSG. Correlations were used to compare the MAPI and PSG measures including oxygen desaturation index and apnoea-hypopnoea index (AHI. Receiver-operating characteristics (ROC curve analyses were performed using various cut-off scores for apnoea severity. Results. In controls, there was a significant moderate correlation between higher MAPI scores and more severe apnoea (AHI: r=0.47, P=0.017. However, this relationship was not significant in the MCI sample. ROC curve analysis indicated much lower area under the curve (AUC in the MCI sample compared to the controls across all AHI severity cut-off scores. Conclusions. In older people, the MAPI moderately correlates with AHI severity but only in those who are cognitively intact. Development of further screening tools is required in order to accurately screen for OSA in MCI.

Power flow prediction in vibrating systems via model reduction

Science.gov (United States)

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.

CFD prediction of flow and phase distribution in fuel assemblies with spacers

Energy Technology Data Exchange (ETDEWEB)

Anglart, H.; Nylund, O. [ABB Atom AB, Vasteras (Switzerland); Kurul, N. [Rensselaer Polytechnic Institute, Troy, NY (United States)] [and others

1995-09-01

This paper is concerned with the modeling and computation of multi-dimensional two-phase flows in BWR fuel assemblies. The modeling principles are presented based on using a two-fluid model in which lateral interfacial effects are accounted for. This model has been used to evaluate the velocity fields of both vapor and liquid phases, as well as phase distribution, between fuel elements in geometries similar to BWR fuel bundles. Furthermore, this model has been used to predict, in a detailed mechanistic manner, the effects of spacers on flow and phase distribution between, and pressure drop along, fuel elements. The related numerical simulations have been performed using a CFD computer code, CFDS-FLOW3D.

A new methodology for predicting flow induced vibration in industrial components

International Nuclear Information System (INIS)

Gay, N.

1997-12-01

Flow induced vibration damage is a major concern for designers and operators of industrial components. For example, nuclear power plant operators have currently to deal with such flow induced vibration problems, in steam generator tube bundles, control rods or nuclear fuel assemblies. Some methodologies have thus been recently proposed to obtain an accurate description of the flow induced vibration phenomena. These methodologies are based on unsteady semi-analytical models for fluid-dynamic forces, associated with non-dimensional fluid force coefficients generally obtained from experiments. The aim is to determine the forces induced by the flow on the structure, and then to take account of these forces to derive the dynamic behaviour of the component under flow excitation. The approach is based on a general model for fluid-dynamic forces, using several non-dimensional parameters that cannot be reached through computation. These parameters are then determined experimentally on simplified test sections, representative of the component, of the flow and of the fluid-elastic coupling phenomena. Predicting computations of the industrial component can then be performed for various operating configurations, by applying laws of similarity. The major physical mechanisms involved in complex fluid-structure interaction phenomena have been understood and modelled. (author)

Evaluation of renal resistive index in cirrhotic patients for predicting the hepatirenal syndrome

International Nuclear Information System (INIS)

Baek, Seung Yon; Kim, Hyae young; Yi, Sun Young

1996-01-01

To evaluate the usefulness of renal resistive index(RI) in patients with liver cirrhosis as an indicator for predicting hepatorenal syndrome. Renal RIs of thirty cirrhotic patients were analyzed using the gray-scale and Doppler ultrasonograms. As a control group, eight normal subjects were included. Renal RIs were measured at three sites of interlobar or arcuate arteries of both kidneys. The patients were divided into three groups (A, B, or C) according to the Child-Turcotte-Pugh classification and their serum BUN and creatinine levels were compared. We determined whether RIs of normal controls differed from those of cirrhotic patients or whether RIs of cirrhotic patients correlated with the Child-Turcotte-Pugh classification or BUN and creatinine levels. Mean RIs(0.63 ±0.33) of normal subjects were statistically different from those(0.67 ± 0.05) of cirrhotic patients(P=0.009). RIs of group A(n=6), B(n=9) and C(n=15) were 0.65 ± 0.03, 0.65 ± 0.04 and 0.70 ± 0.04, respectively. The ANOVA test revealed statistically significant differences between the three groups(F ratio=4.472, P=0.021). RIs did not correlate with BUN or creatinine levels. RI could be used as an index for predicting hepatorenal syndrome before the renal function becomes impaired

The predictive effect of inflammatory markers and lipid accumulation product index on clinical symptoms associated with polycystic ovary syndrome in nonobese adolescents and younger aged women.

Science.gov (United States)

Tola, Esra Nur; Yalcin, Serenat Eris; Dugan, Nadiye

2017-07-01

The aim of our study is to analyse the inflammatory markers and lipid accumulation product (LAP) index in nonobese adolescents and younger aged women with polycystic ovary syndrome (PCOS) compared with age and body mass index (BMI)-matched healthy controls and to determine whether the investigated parameters are potential markers for the etiopathogenesis of PCOS. We also aim to determine whether these inflammatory markers are predictive for developing some clinical implications, such as cardiovascular disease (CVD) and insulin resistance (IR), associated with PCOS. A total of 34 adolescents and younger aged females with PCOS, and 33 age and BMI-matched healthy controls were recruited for our study. All participants were nonobese (BMIpredictive effect of investigated inflammatory markers and LAP index on CVD risk among PCOS patients after adjustment for abdominal obesity. We also found a positive predictive effect of WBC and a negative predictive effect of lymphocytes on IR in PCOS patients after adjustment for abdominal obesity. We did not find any predictor effect of NEO on IR, but it was a positive predictive marker for an elevated HOMA-IR index. Elevated NEO, CRP levels and LAP index could have potential roles in the etiopathogenesis of PCOS in nonobese adolescents and younger aged females,NEO could be a predictive marker for elevated HOMA-IR index, and WBC and lymphocytes could be predictive for the development of IR among nonobese adolescents and younger aged females with PCOS. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting critical heat flux in slug flow regime of uniformly heated ...

African Journals Online (AJOL)

Numerical computation code (PWR-DNBP) has been developed to predict Critical Heat Flux (CHF) of forced convective flow of water in a vertical heated channel. The code was based on the liquid sub-layer model, with the assumption that CHF occurred when the liquid film thickness between the heated surface and vapour ...

Nuclear Division Index may Predict Neoplastic Colorectal Lesions.

Science.gov (United States)

Ionescu, Mirela E; Ciocirlan, Mihai; Becheanu, Gabriel; Nicolaie, Tudor; Ditescu, Cristina; Teiusanu, Adriana G; Gologan, Serban I; Arbanas, Tudor; Diculescu, Mircea M

2011-07-01

Colorectal cancer (CRC) develops by accumulation of multiple genetic damages leading to genetic instability that can be evaluated by cytogenetic methods. In the current study we used Cytokinesis-Blocked Micronucleus Assay (CBMN) technique to assess the behavior of Nuclear Division Index(NDI) in peripheral lymphocytes of patients with CRC and polyps versus patients with normal colonoscopy. Blood samples were collected from patients after informed consent. By CBMN technique we assessed the proportion of mono-nucleated, bi-nucleated, tri-nucleated and tetra-nucleated cells/500 cells, to calculate NDI. Data were statistically analyzed using the SPSS 11.0 package. 45 patients were available for analysis, 23 men and 22 women, with a mean age of 58.7±13.5. 17 had normal colonoscopy, 17 colonic polyps and 11 CRC. The mean NDI values were significantly smaller for patients with CRC or polyps than in patients with normal colonoscopy (1.57 vs 1.73, p=0.013). The difference persisted for patients with neoplastic lesions (adenomas and carcinomas) when compared with patients with normal colonoscopy or non neoplastic (hyperplastic) polyps (1.56 vs.1.71, p=0.018). The NDI cut-off value to predict the presence of adenomas or carcinomas was equal to 1.55 with a 54.2% sensitivity and 81% specificity of lower values (p=0.019). The NDI cut off value to predict the presence of advanced adenomas or cancer was 1.525 for a sensitivity of 56.3% and a specificity of 82.8% (p=0.048). NDI may be useful in screening strategies for colorectal cancer as simple, noninvasive, inexpensive cytogenetic biomarker.

Predictive value of European Scleroderma Group Activity Index in an early scleroderma cohort.

Science.gov (United States)

Nevskaya, Tatiana; Baron, Murray; Pope, Janet E

2017-07-01

To estimate the effect of disease activity, as measured by the European Scleroderma Research Group Activity Index (EScSG-AI), on the risk of subsequent organ damage in a large systemic sclerosis (SSc) cohort. Of 421 SSc patients from the Canadian Scleroderma Research Group database with disease duration of ⩽ 3 years, 197 who had no evidence of end-stage organ damage initially and available 3 year follow-up were included. Disease activity was assessed by the EScSG-AI with two variability measures: the adjusted mean EScSG-AI (the area under the curve of the EScSG-AI over the observation period) and persistently active disease/flare. Outcomes were based on the Medsger severity scale and included accrual of a new severity score (Δ ⩾ 1) overall and within organ systems or reaching a significant level of deterioration in health status. After adjustment for covariates, the adjusted mean EScSG-AI was the most consistent predictor of risk across the study outcomes over 3 years in dcSSc: disease progression defined as Δ ⩾ 1 in any major internal organ, significant decline in forced vital capacity and diffusing capacity of carbon monoxide, severity of visceral disease and HAQ Disability Index worsening. In multivariate analysis, progression of lung disease was predicted solely by adjusted mean EScSG-AI, while the severity of lung disease was predicted the adjusted mean EScSG-AI, older age, modified Rodnan skin score (mRSS) and initial severity. The EScSG-AI was associated with patient- and physician-assessed measures of health status and overpowered the mRSS in predicting disease outcomes. Disease activity burden quantified with the adjusted mean EScSG-AI predicted the risk of deterioration in health status and severe organ involvement in dcSSc. The EScSG-AI is more responsive when done repeatedly and averaged. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email

An index-based framework for assessing patterns and trends in river fragmentation and flow regulation by global dams at multiple scales

International Nuclear Information System (INIS)

Grill, Günther; Lehner, Bernhard; Lumsdon, Alexander E; Zarfl, Christiane; MacDonald, Graham K; Reidy Liermann, Catherine

2015-01-01

The global number of dam constructions has increased dramatically over the past six decades and is forecast to continue to rise, particularly in less industrialized regions. Identifying development pathways that can deliver the benefits of new infrastructure while also maintaining healthy and productive river systems is a great challenge that requires understanding the multifaceted impacts of dams at a range of scales. New approaches and advanced methodologies are needed to improve predictions of how future dam construction will affect biodiversity, ecosystem functioning, and fluvial geomorphology worldwide, helping to frame a global strategy to achieve sustainable dam development. Here, we respond to this need by applying a graph-based river routing model to simultaneously assess flow regulation and fragmentation by dams at multiple scales using data at high spatial resolution. We calculated the cumulative impact of a set of 6374 large existing dams and 3377 planned or proposed dams on river connectivity and river flow at basin and subbasin scales by fusing two novel indicators to create a holistic dam impact matrix for the period 1930–2030. Static network descriptors such as basin area or channel length are of limited use in hierarchically nested and dynamic river systems, so we developed the river fragmentation index and the river regulation index, which are based on river volume. These indicators are less sensitive to the effects of network configuration, offering increased comparability among studies with disparate hydrographies as well as across scales. Our results indicate that, on a global basis, 48% of river volume is moderately to severely impacted by either flow regulation, fragmentation, or both. Assuming completion of all dams planned and under construction in our future scenario, this number would nearly double to 93%, largely due to major dam construction in the Amazon Basin. We provide evidence for the importance of considering small to medium

IN-CYLINDER MASS FLOW ESTIMATION AND MANIFOLD PRESSURE DYNAMICS FOR STATE PREDICTION IN SI ENGINES

Directory of Open Access Journals (Sweden)

Wojnar Sławomir

2014-06-01

Full Text Available The aim of this paper is to present a simple model of the intake manifold dynamics of a spark ignition (SI engine and its possible application for estimation and control purposes. We focus on pressure dynamics, which may be regarded as the foundation for estimating future states and for designing model predictive control strategies suitable for maintaining the desired air fuel ratio (AFR. The flow rate measured at the inlet of the intake manifold and the in-cylinder flow estimation are considered as parts of the proposed model. In-cylinder flow estimation is crucial for engine control, where an accurate amount of aspired air forms the basis for computing the manipulated variables. The solutions presented here are based on the mean value engine model (MVEM approach, using the speed-density method. The proposed in-cylinder flow estimation method is compared to measured values in an experimental setting, while one-step-ahead prediction is illustrated using simulation results.

Efficacy of the Omega-3 Index in predicting non-alcoholic fatty liver disease in overweight and obese adults: a pilot study.

Science.gov (United States)

Parker, Helen M; O'Connor, Helen T; Keating, Shelley E; Cohn, Jeffrey S; Garg, Manohar L; Caterson, Ian D; George, Jacob; Johnson, Nathan A

2015-09-14

Non-alcoholic fatty liver disease (NAFLD) is an independent predictor of CVD in otherwise healthy individuals. Low n-3 PUFA intake has been associated with the presence of NAFLD; however, the relationship between a biomarker of n-3 status - the Omega-3 Index - and liver fat is yet to be elucidated. A total of eighty overweight adults (fifty-six men) completed the anthropometric and biochemical measurements, including the Omega-3 Index, and underwent proton magnetic resonance spectroscopy assessment of liver fat. Bivariate correlations and multiple regression analyses were performed with reference to prediction of liver fat percentage. The mean Omega-3 Index was high in both NAFLD (intrahepatic lipid concentration≥5·5 %) and non-NAFLD groups. The Omega-3 Index, BMI, waist circumference, glucose, insulin, TAG, high-sensitive C-reactive protein (hsCRP) and alanine aminotransferase (ALT) were positively correlated, and HDL and erythrocyte n-6:n-3 ratio negatively correlated with liver fat concentration. Regression analysis found that simple anthropometric and demographic variables (waist, age) accounted for 31 % of the variance in liver fat and the addition of traditional cardiometabolic blood markers (TAG, HDL, hsCRP and ALT) increased the predictive power to 43 %. The addition of the novel erythrocyte fatty acid variable (Omega-3 Index) to the model only accounted for a further 3 % of the variance (P=0·049). In conclusion, the Omega-3 Index was associated with liver fat concentration but did not improve the overall capacity of demographic, anthropometric and blood markers to predict NAFLD.

Numerical predictions of bubbly two-phase flows with OpenFOAM

International Nuclear Information System (INIS)

Michta, E.; Fu, K.; Anglart, H.; Angele, K.

2011-01-01

A new model for simulation of bubbly two-phase flows has been developed and implemented into an open-source Computational Fluid Dynamics (CFD) code OpenFOAM. The model employs the two-fluid framework with closure relationships for the interfacial momentum transfer. The bubble size is calculated based on the solution of the interfacial area concentration equations. The predictions are validated against a wide range of experimental data containing measured void fraction, the phasic velocity and the interfacial area concentration. The new model demonstrates the ability to capture the wall peaking of void fraction for small bubbles. The predicted levels of void fraction and phasic velocities are in good agreement with measured data. (author)

An Extended Assessment of Fluid Flow Models for the Prediction of Two-Dimensional Steady-State Airfoil Aerodynamics

Directory of Open Access Journals (Sweden)

José F. Herbert-Acero

2015-01-01

Full Text Available This work presents the analysis, application, and comparison of thirteen fluid flow models in the prediction of two-dimensional airfoil aerodynamics, considering laminar and turbulent subsonic inflow conditions. Diverse sensitivity analyses of different free parameters (e.g., the domain topology and its discretization, the flow model, and the solution method together with its convergence mechanisms revealed important effects on the simulations’ outcomes. The NACA 4412 airfoil was considered throughout the work and the computational predictions were compared with experiments conducted under a wide range of Reynolds numbers (7e5≤Re≤9e6 and angles-of-attack (-10°≤α≤20°. Improvements both in modeling accuracy and processing time were achieved by considering the RS LP-S and the Transition SST turbulence models, and by considering finite volume-based solution methods with preconditioned systems, respectively. The RS LP-S model provided the best lift force predictions due to the adequate modeling of the micro and macro anisotropic turbulence at the airfoil’s surface and at the nearby flow field, which in turn allowed the adequate prediction of stall conditions. The Transition-SST model provided the best drag force predictions due to adequate modeling of the laminar-to-turbulent flow transition and the surface shear stresses. Conclusions, recommendations, and a comprehensive research agenda are presented based on validated computational results.

The StreamCat Dataset: Accumulated Attributes for NHDPlusV2 (Version 2.1) Catchments for the Conterminous United States: Base Flow Index

Data.gov (United States)

U.S. Environmental Protection Agency — This dataset represents the base flow index values within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape...

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

Directory of Open Access Journals (Sweden)

Eunjeong Ko

2016-01-01

Full Text Available 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.

An experimental evaluation of powder flow predictions in small-scale process equipment based on Jenike's hopper design methodology

DEFF Research Database (Denmark)

Søgaard, Søren Vinter; Olesen, Niels Erik; Hirschberg, Cosima

2017-01-01

. The comparison of the observed and predicted critical outlet diameters showed good agreement for the powder with the best flowability when linear extrapolation of the flow function was applied. In contrast, the predicted critical outlet diameter was slightly overestimated compared to the experimentally observed...... diameter for the two more cohesive powders. A likely reason for this overestimation is that the flow function probably has a non-linear convex upward shape for these two powders at very small consolidation stresses. These findings illustrate the relevance of measuring shear and wall shear stresses at very...... small consolidation stresses to improve the flow behavior predictions for small-scale process equipment typically used during production of solid state pharmaceuticals....

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

Science.gov (United States)

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.

Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

Science.gov (United States)

Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

2017-10-01

To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-valuemodel is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP

G-index: A new metric to describe dynamic refractive index effects in HPLC absorbance detection.

Science.gov (United States)

Kraiczek, Karsten G; Rozing, Gerard P; Zengerle, Roland

2018-09-01

High performance liquid chromatography (HPLC) with a solvent gradient and absorbance detection is one of the most widely used methods in analytical chemistry. The observed absorbance baseline is affected by the changes in the refractive index (RI) of the mobile phase. Near the limited of detection, this complicates peak quantitation. The general aspects of these RI-induced apparent absorbance effects are discussed. Two different detectors with fundamentally different optics and flow cell concepts, a variable-wavelength detector equipped with a conventional flow cell and a diode-array detector equipped with a liquid core waveguide flow cell, are compared with respect to their RI behavior. A simple method to separate static - partly unavoidable - RI effects from dynamic RI effects is presented. It is shown that the dynamic RI behavior of an absorbance detector can be well described using a single, relatively easy-to-determine metric called the G-index. The G-index is typically in the order of a few seconds and its sign depends on the optical flow cell concept. Copyright © 2018 Elsevier B.V. All rights reserved.

Numerical prediction of local transitional features of turbulent forced gas flows in circular tubes with strong heating

International Nuclear Information System (INIS)

Ezato, Koichiro; Kunugi, Tomoaki; Shehata, A.M.; McEligot, D.M.

1997-03-01

Previous numerical simulation for the laminarization due to heating of the turbulent flow in pipe were assessed by comparison with only macroscopic characteristics such as heat transfer coefficient and pressure drop, since no experimental data on the local distributions of the velocity and temperature in such flow situation was available. Recently, Shehata and McEligot reported the first measurements of local distributions of velocity and temperature for turbulent forced air flow in a vertical circular tube with strongly heating. They carried out the experiments in three situations from turbulent flow to laminarizing flow according to the heating rate. In the present study, we analyzed numerically the local transitional features of turbulent flow evolving laminarizing due to strong heating in their experiments by using the advanced low-Re two-equation turbulence model. As the result, we successfully predicted the local distributions of velocity and temperature as well as macroscopic characteristics in three turbulent flow conditions. By the present study, a numerical procedure has been established to predict the local characteristics such as velocity distribution of the turbulent flow with large thermal-property variation and laminarizing flow due to strong heating with enough accuracy. (author). 60 refs

Prediction Center (CPC) Polar Eurasia Teleconnection Pattern Index

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Polar-Eurasia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal...

Climate Prediction Center (CPC) Scandinavia Teleconnection Pattern Index

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Monthly tabulated index of the Scandinavia teleconnection pattern. The data spans the period 1950 to present. The index is derived from a rotated principal component...

Reticulocyte maturity index by flow cytometry: its applicability in radioinduced bone marrow aplasia

International Nuclear Information System (INIS)

Dubner, D.; Gisone, P.; Perez, M.R.

1995-01-01

Flow cytometric reticulocyte quantification was assayed in ten patients undergoing bone marrow transplantation (BMT) with previous conditioning chemotherapy and total body irradiation (TBI). A reticulocyte maturity index (RMI) was determined taking into account the RNA content. With de aim of testing the utility of RMI as an early predictor of functional recovery in marrow aplasia, other haematological indicators as neutrophils count were comparatively evaluated. Mean time elapsed between BMT and engraftment evidence by RMI was 17,6 days. In six patients the RMI was the earliest indicator of functional recovery. The applicability of this assay in the following of radioinduced bone marrow aplasia is discussed. (author). 4 refs., 4 figs., 2 tabs

Prediction of the critical heat flux for saturated upward flow boiling water in vertical narrow rectangular channels

International Nuclear Information System (INIS)

Choi, Gil Sik; Chang, Soon Heung; Jeong, Yong Hoon

2016-01-01

A study, on the theoretical method to predict the critical heat flux (CHF) of saturated upward flow boiling water in vertical narrow rectangular channels, has been conducted. For the assessment of this CHF prediction method, 608 experimental data were selected from the previous researches, in which the heated sections were uniformly heated from both wide surfaces under the high pressure condition over 41 bar. For this purpose, representative previous liquid film dryout (LFD) models for circular channels were reviewed by using 6058 points from the KAIST CHF data bank. This shows that it is reasonable to define the initial condition of quality and entrainment fraction at onset of annular flow (OAF) as the transition to annular flow regime and the equilibrium value, respectively, and the prediction error of the LFD model is dependent on the accuracy of the constitutive equations of droplet deposition and entrainment. In the modified Levy model, the CHF data are predicted with standard deviation (SD) of 14.0% and root mean square error (RMSE) of 14.1%. Meanwhile, in the present LFD model, which is based on the constitutive equations developed by Okawa et al., the entire data are calculated with SD of 17.1% and RMSE of 17.3%. Because of its qualitative prediction trend and universal calculation convergence, the present model was finally selected as the best LFD model to predict the CHF for narrow rectangular channels. For the assessment of the present LFD model for narrow rectangular channels, effective 284 data were selected. By using the present LFD model, these data are predicted with RMSE of 22.9% with the dryout criterion of zero-liquid film flow, but RMSE of 18.7% with rivulet formation model. This shows that the prediction error of the present LFD model for narrow rectangular channels is similar with that for circular channels.

Application of Intelligent Dynamic Bayesian Network with Wavelet Analysis for Probabilistic Prediction of Storm Track Intensity Index

Directory of Open Access Journals (Sweden)

Ming Li

2018-06-01

Full Text Available The effective prediction of storm track (ST is greatly beneficial for analyzing the development and anomalies of mid-latitude weather systems. For the non-stationarity, nonlinearity, and uncertainty of ST intensity index (STII, a new probabilistic prediction model was proposed based on dynamic Bayesian network (DBN and wavelet analysis (WA. We introduced probability theory and graph theory for the first time to quantitatively describe the nonlinear relationship and uncertain interaction of the ST system. Then a casual prediction network (i.e., DBN was constructed through wavelet decomposition, structural learning, parameter learning, and probabilistic inference, which was used for expression of relation among predictors and probabilistic prediction of STII. The intensity prediction of the North Pacific ST with data from 1961–2010 showed that the new model was able to give more comprehensive prediction information and higher prediction accuracy and had strong generalization ability and good stability.

Climate Prediction Center Southern Oscillation Index

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This is one of the CPC?s Monthly Atmospheric and Sea Surface Temperature (SST)Indices. It contains Southern Oscillation Index which is standardized sea level...

The index of a holomorphic flow with an isolated singularity

International Nuclear Information System (INIS)

Verjovsky, A.; Gomez-Mont, X.; Seade, J.

1987-05-01

The index of a holomorphic vector field Z defined on a germ of a hypersurface V with an isolated singularity is defined. The index coincides with the Hopf index in the smooth case. Formulae for the index in terms of the ideals defining Z and V are given. Topological invariance of the index and the Chern class as well as formulae relating global invariants of the Poincare-Hopf type are proven. (author). 26 refs

Flow discharge prediction in compound channels using linear genetic programming

Science.gov (United States)

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.

Impact of Direct Soil Moisture and Revised Soil Moisture Index Methods on Hydrologic Predictions in an Arid Climate

Directory of Open Access Journals (Sweden)

Milad Jajarmizadeh

2014-01-01

Full Text Available The soil and water assessment tool (SWAT is a physically based model that is used extensively to simulate hydrologic processes in a wide range of climates around the world. SWAT uses spatial hydrometeorological data to simulate runoff through the computation of a retention curve number. The objective of the present study was to compare the performance of two approaches used for the calculation of curve numbers in SWAT, that is, the Revised Soil Moisture Index (SMI, which is based on previous meteorological conditions, and the Soil Moisture Condition II (SMCII, which is based on soil features for the prediction of flow. The results showed that the sensitive parameters for the SMI method are land-use and land-cover features. However, for the SMCII method, the soil and the channel are the sensitive parameters. The performances of the SMI and SMCII methods were analyzed using various indices. We concluded that the fair performance of the SMI method in an arid region may be due to the inherent characteristics of the method since it relies mostly on previous meteorological conditions and does not account for the soil features of the catchment.

Prediction of strongly-heated gas flows in a vertical tube using explicit algebraic stress/heat-flux models

International Nuclear Information System (INIS)

Baek, Seong Gu; Park, Seung O.

2003-01-01

This paper provides the assessment of prediction performance of explicit algebraic stress and heat-flux models under conditions of mixed convective gas flows in a strongly-heated vertical tube. Two explicit algebraic stress models and four algebraic heat-flux models are selected for assessment. Eight combinations of explicit algebraic stress and heat-flux models are used in predicting the flows experimentally studied by Shehata and McEligot (IJHMT 41(1998) p.4333) in which property variation was significant. Among the various model combinations, the Wallin and Johansson (JFM 403(2000) p. 89) explicit algebraic stress model-Abe, Kondo, and Nagano (IJHFF 17(1996) p. 228) algebraic heat-flux model combination is found to perform best. We also found that the dimensionless wall distance y + should be calculated based on the local property rather than the property at the wall for property-variation flows. When the buoyancy or the property variation effects are so strong that the flow may relaminarize, the choice of the basic platform two-equation model is a most important factor in improving the predictions

Numerical Predictions of Bubbly Two-Phase Flows with OpenFOAM

Directory of Open Access Journals (Sweden)

Edouard Michta

2012-12-01

Full Text Available A new model for simulation of bubbly two-phase flows has been developed and implemented into an open-source Computational Fluid Dynamics (CFD code OpenFOAM. The model employs the two-fluid framework with closure relationships for the interfacial momentum transfer. The bubble size is calculated based on the solution of the transport equation of the interfacial area concentration. The predictions are validated against selected data obtained in the DEDALE experiment and containing the measured void fraction, the phasic velocities and the interfacial area concentration. In general, good agreement between calculated and measured data is demonstrated; however, the relative phasic velocity is systematically over-predicted. The levels of void fraction and the observed wall void peaking are well captured in the calculations.

Development of the statistical ARIMA model: an application for predicting the upcoming of MJO index

Science.gov (United States)

Hermawan, Eddy; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Gede Nyoman Mindra Jaya, I.; Berliana Sipayung, Sinta; Rustiana, Shailla

2017-10-01

This study is mainly concerned in development one of the most important equatorial atmospheric phenomena that we call as the Madden Julian Oscillation (MJO) which having strong impacts to the extreme rainfall anomalies over the Indonesian Maritime Continent (IMC). In this study, we focused to the big floods over Jakarta and surrounded area that suspecting caused by the impacts of MJO. We concentrated to develop the MJO index using the statistical model that we call as Box-Jenkis (ARIMA) ini 1996, 2002, and 2007, respectively. They are the RMM (Real Multivariate MJO) index as represented by RMM1 and RMM2, respectively. There are some steps to develop that model, starting from identification of data, estimated, determined model, before finally we applied that model for investigation some big floods that occurred at Jakarta in 1996, 2002, and 2007 respectively. We found the best of estimated model for the RMM1 and RMM2 prediction is ARIMA (2,1,2). Detailed steps how that model can be extracted and applying to predict the rainfall anomalies over Jakarta for 3 to 6 months later is discussed at this paper.

Cavitation simulation and NPSH prediction of a double suction centrifugal pump

International Nuclear Information System (INIS)

Li, P; Huang, Y F; Li, J

2012-01-01

This paper illustrates the flow field numerical analysis of the double-suction centrifugal pump. For the study of the cavitation flow inside the double-suction centrifugal pump, the professional pump/motor simulation software PumpLinx and its Full Cavitation Model has been employed. According to the PumpLinx calculation result and the Cavitation damage index, the cavitation position, level and the cavitation characteristics of the double-suction centrifugal pump has been predicted. For the further objective, the simulation of the flow field in the double-suction centrifugal pump under different inlet conditions has been carried out. By the result analysis, NPSHr has been predicted; the reliability of the results has been verified by comparing with the experimental data. At the same time, this practice can provide guidance for the optimal design of double-suction pump.

On vortex loops and filaments: three examples of numerical predictions of flows containing vortices.

Science.gov (United States)

Krause, Egon

2003-01-01

Vortex motion plays a dominant role in many flow problems. This article aims at demonstrating some of the characteristic features of vortices with the aid of numerical solutions of the governing equations of fluid mechanics, the Navier-Stokes equations. Their discretized forms will first be reviewed briefly. Thereafter three problems of fluid flow involving vortex loops and filaments are discussed. In the first, the time-dependent motion and the mutual interaction of two colliding vortex rings are discussed, predicted in good agreement with experimental observations. The second example shows how vortex rings are generated, move, and interact with each other during the suction stroke in the cylinder of an automotive engine. The numerical results, validated with experimental data, suggest that vortex rings can be used to influence the spreading of the fuel droplets prior to ignition and reduce the fuel consumption. In the third example, it is shown that vortices can also occur in aerodynamic flows over delta wings at angle of attack as well as pipe flows: of particular interest for technical applications of these flows is the situation in which the vortex cores are destroyed, usually referred to as vortex breakdown or bursting. Although reliable breakdown criteria could not be established as yet, the numerical predictions obtained so far are found to agree well with the few experimental data available in the recent literature.

Void fraction prediction in two-phase flows independent of the liquid phase density changes

International Nuclear Information System (INIS)

Nazemi, E.; Feghhi, S.A.H.; Roshani, G.H.

2014-01-01

Gamma-ray densitometry is a frequently used non-invasive method to determine void fraction in two-phase gas liquid pipe flows. Performance of flow meters using gamma-ray attenuation depends strongly on the fluid properties. Variations of the fluid properties such as density in situations where temperature and pressure fluctuate would cause significant errors in determination of the void fraction in two-phase flows. A conventional solution overcoming such an obstacle is periodical recalibration which is a difficult task. This paper presents a method based on dual modality densitometry using Artificial Neural Network (ANN), which offers the advantage of measuring the void fraction independent of the liquid phase changes. An experimental setup was implemented to generate the required input data for training the network. ANNs were trained on the registered counts of the transmission and scattering detectors in different liquid phase densities and void fractions. Void fractions were predicted by ANNs with mean relative error of less than 0.45% in density variations range of 0.735 up to 0.98 gcm −3 . Applying this method would improve the performance of two-phase flow meters and eliminates the necessity of periodical recalibration. - Highlights: • Void fraction was predicted independent of density changes. • Recorded counts of detectors/void fraction were used as inputs/output of ANN. • ANN eliminated necessity of recalibration in changeable density of two-phase flows

Feasibility Study on the Satellite Rainfall Data for Prediction of Sediment- Related Disaster by the Japanese Prediction Methodology

Science.gov (United States)

Shimizu, Y.; Ishizuka, T.; Osanai, N.; Okazumi, T.

2014-12-01

In this study, the sediment-related disaster prediction method which based ground gauged rainfall-data, currently practiced in Japan was coupled with satellite rainfall data and applied to domestic large-scale sediment-related disasters. The study confirmed the feasibility of this integrated method. In Asia, large-scale sediment-related disasters which can sweep away an entire settlement occur frequently. Leyte Island suffered from a huge landslide in 2004, and Typhoon Molakot in 2009 caused huge landslides in Taiwan. In the event of these sediment-related disasters, immediate responses by central and local governments are crucial in crisis management. In general, there are not enough rainfall gauge stations in developing countries. Therefore national and local governments have little information to determine the risk level of water induced disasters in their service areas. In the Japanese methodology, a criterion is set by combining two indices: the short-term rainfall index and long-term rainfall index. The short-term rainfall index is defined as the 60-minute total rainfall; the long-term rainfall index as the soil-water index, which is an estimation of the retention status of fallen rainfall in soil. In July 2009, a high-density sediment related disaster, or a debris flow, occurred in Hofu City of Yamaguchi Prefecture, in the western region of Japan. This event was calculated by the Japanese standard methodology, and then analyzed for its feasibility. Hourly satellite based rainfall has underestimates compared with ground based rainfall data. Long-term index correlates with each other. Therefore, this study confirmed that it is possible to deliver information on the risk level of sediment-related disasters such as shallow landslides and debris flows. The prediction method tested in this study is expected to assist for timely emergency responses to rainfall-induced natural disasters in sparsely gauged areas. As the Global Precipitation Measurement (GPM) Plan

Prediction of the impacts of climate changes on the stream flow of ...

African Journals Online (AJOL)

Abstract. Soil and Water Assessment Tool, (SWAT) model was used to predict the impacts of Climate Change on Ajali River watershed, Aguobu-Umumba, Ezeagu, Enugu State, Nigeria. The model was first used to simulate stream flow using observed data. After model run, parameterization, sensitivity analysis, the monthly ...

Analysis of Margin Index as a Method for Predicting Residual Disease After Breast-Conserving Surgery in a European Cancer Center.

LENUS (Irish Health Repository)

Bolger, Jarlath C

2011-06-03

INTRODUCTION: Breast-conserving surgery (BCS), followed by appropriate adjuvant therapies is established as a standard treatment option for women with early-stage invasive breast cancers. A number of factors have been shown to correlate with local and regional disease recurrence. Although margin status is a strong predictor of disease recurrence, consensus is yet to be established on the optimum margin necessary. Margenthaler et al. recently proposed the use of a "margin index," combining tumor size and margin status as a predictor of residual disease after BCS. We applied this new predictive tool to a population of patients with primary breast cancer who presented to a symptomatic breast unit to determine its suitability in predicting those who require reexcision surgery. METHODS: Retrospective analysis of our breast cancer database from January 1, 2000 to June 30, 2010 was performed, including all patients who underwent BCS. Of 531 patients who underwent BCS, 27.1% (144\\/531) required further reexcision procedures, and 55 were eligible for inclusion in the study. Margin index was calculated as: margin index = closest margin (mm)\\/tumor size (mm) × 100, with index >5 considered optimum. RESULTS: Of the 55 patients included, 31% (17\\/55) had residual disease. Fisher\\'s exact test showed margin index not to be a significant predictor of residual disease on reexcision specimen (P = 0.57). Of note, a significantly higher proportion of our patients presented with T2\\/3 tumors (60% vs. 38%). CONCLUSIONS: Although an apparently elegant tool for predicting residual disease after BCS, we have shown that it is not applicable to a symptomatic breast unit in Ireland.

Analysis of margin index as a method for predicting residual disease after breast-conserving surgery in a European cancer center.

LENUS (Irish Health Repository)

Bolger, Jarlath C

2012-02-01

INTRODUCTION: Breast-conserving surgery (BCS), followed by appropriate adjuvant therapies is established as a standard treatment option for women with early-stage invasive breast cancers. A number of factors have been shown to correlate with local and regional disease recurrence. Although margin status is a strong predictor of disease recurrence, consensus is yet to be established on the optimum margin necessary. Margenthaler et al. recently proposed the use of a "margin index," combining tumor size and margin status as a predictor of residual disease after BCS. We applied this new predictive tool to a population of patients with primary breast cancer who presented to a symptomatic breast unit to determine its suitability in predicting those who require reexcision surgery. METHODS: Retrospective analysis of our breast cancer database from January 1, 2000 to June 30, 2010 was performed, including all patients who underwent BCS. Of 531 patients who underwent BCS, 27.1% (144\\/531) required further reexcision procedures, and 55 were eligible for inclusion in the study. Margin index was calculated as: margin index = closest margin (mm)\\/tumor size (mm) x 100, with index >5 considered optimum. RESULTS: Of the 55 patients included, 31% (17\\/55) had residual disease. Fisher\\'s exact test showed margin index not to be a significant predictor of residual disease on reexcision specimen (P = 0.57). Of note, a significantly higher proportion of our patients presented with T2\\/3 tumors (60% vs. 38%). CONCLUSIONS: Although an apparently elegant tool for predicting residual disease after BCS, we have shown that it is not applicable to a symptomatic breast unit in Ireland.

Performance Assessment of Turbulence Models for the Prediction of the Reactor Internal Flow in the Scale-down APR+

International Nuclear Information System (INIS)

Lee, Gonghee; Bang, Youngseok; Woo, Swengwoong; Kim, Dohyeong; Kang, Minku

2013-01-01

The types of errors in CFD simulation can be divided into the two main categories: numerical errors and model errors. Turbulence model is one of the important sources for model errors. In this study, in order to assess the prediction performance of Reynolds-averaged Navier-Stokes (RANS)-based two equations turbulence models for the analysis of flow distribution inside a 1/5 scale-down APR+, the simulation was conducted with the commercial CFD software, ANSYS CFX V. 14. In this study, in order to assess the prediction performance of turbulence models for the analysis of flow distribution inside a 1/5 scale-down APR+, the simulation was conducted with the commercial CFD software, ANSYS CFX V. 14. Both standard k-ε model and SST model predicted the similar flow pattern inside reactor. Therefore it was concluded that the prediction performance of both turbulence models was nearly same. Complex thermal-hydraulic characteristics exist inside reactor because the reactor internals consist of fuel assembly, control rod assembly, and the internal structures. Either flow distribution test for the scale-down reactor model or computational fluid dynamics (CFD) simulation have been conducted to understand these complex thermal-hydraulic features inside reactor

Maslov index for Hamiltonian systems

Directory of Open Access Journals (Sweden)

Alessandro Portaluri

2008-01-01

Full Text Available The aim of this article is to give an explicit formula for computing the Maslov index of the fundamental solutions of linear autonomous Hamiltonian systems in terms of the Conley-Zehnder index and the map time one flow.

Index to Predict In-hospital Mortality in Older Adults after Non-traumatic Emergency Department Intubations

Directory of Open Access Journals (Sweden)

Kei Ouchi

2017-04-01

Full Text Available Introduction: Our goal was to develop and validate an index to predict in-hospital mortality in older adults after non-traumatic emergency department (ED intubations. Methods: We used Vizient administrative data from hospitalizations of 22,374 adults ≥75 years who underwent non-traumatic ED intubation from 2008–2015 at nearly 300 U.S. hospitals to develop and validate an index to predict in-hospital mortality. We randomly selected one half of participants for the development cohort and one half for the validation cohort. Considering 25 potential predictors, we developed a multivariable logistic regression model using least absolute shrinkage and selection operator method to determine factors associated with in-hospital mortality. We calculated risk scores using points derived from the final model’s beta coefficients. To evaluate calibration and discrimination of the final model, we used Hosmer-Lemeshow chi-square test and receiver-operating characteristic analysis and compared mortality by risk groups in the development and validation cohorts. Results: Death during the index hospitalization occurred in 40% of cases. The final model included six variables: history of myocardial infarction, history of cerebrovascular disease, history of metastatic cancer, age, admission diagnosis of sepsis, and admission diagnosis of stroke/ intracranial hemorrhage. Those with low-risk scores (10 had 58% risk of in-hospital mortality. The Hosmer-Lemeshow chi-square of the model was 6.47 (p=0.09, and the c-statistic was 0.62 in the validation cohort. Conclusion: The model may be useful in identifying older adults at high risk of death after ED intubation.

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

Science.gov (United States)

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

2007-10-01

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

Prediction of Separation Length of Turbulent Multiphase Flow Using Radiotracer and Computational Fluid Dynamics Simulation

International Nuclear Information System (INIS)

Sugiharto, S.; Kurniadi, R.; Abidin, Z.; Stegowski, Z.; Furman, L.

2013-01-01

Multiphase flow modeling presents great challenges due to its extreme importance in various industrial and environmental applications. In the present study, prediction of separation length of multiphase flow is examined experimentally by injection of two kinds of iodine-based radiotracer solutions into a hydrocarbon transport pipeline (HCT) having an inner diameter of 24 in (60,96 m). The main components of fluids in the pipeline are water 95%, crude oil 3% and gas 2%. A radiotracing experiment was carried out at the segment of pipe which is located far from branch points with assumptions that stratified flows in such segment were achieved. Two radiation detectors located at 80 and 100 m from injection point were used to generate residence time distribution (RTD) curve resulting from injection of radiotracer solutions. Multiphase computational fluid dynamics (CFD) simulations using Eulerian-Eulerian control volume and commercial CFD package Fluent 6.2 were employed to simulate separation length of multiphase flow. The results of study shows that the flow velocity of water is higher than the flow rate of crude oil in water-dominated system despite the higher density of water than the density of the crude oil. The separation length in multiphase flow predicted by Fluent mixture model is approximately 20 m, measured from injection point. This result confirms that the placement of the first radiation detector at the distance 80 m from the injection point was correct. (author)

Prediction of Separation Length of Turbulent Multiphase Flow Using Radiotracer and Computational Fluid Dynamics Simulation

Directory of Open Access Journals (Sweden)

S. Sugiharto1

2013-04-01

Full Text Available Multiphase flow modeling presents great challenges due to its extreme importance in various industrial and environmental applications. In the present study, prediction of separation length of multiphase flow is examined experimentally by injection of two kinds of iodine-based radiotracer solutions into a hydrocarbon transport pipeline (HCT having an inner diameter of 24 in (60,96 m. The main components of fluids in the pipeline are water 95%, crude oil 3% and gas 2%. A radiotracing experiment was carried out at the segment of pipe which is located far from branch points with assumptions that stratified flows in such segment were achieved. Two radiation detectors located at 80 and 100 m from injection point were used to generate residence time distribution (RTD curve resulting from injection of radiotracer solutions. Multiphase computational fluid dynamics (CFD simulations using Eulerian-Eulerian control volume and commercial CFD package Fluent 6.2 were employed to simulate separation length of multiphase flow. The results of study shows that the flow velocity of water is higher than the flow rate of crude oil in water-dominated system despite the higher density of water than the density of the crude oil. The separation length in multiphase flow predicted by Fluent mixture model is approximately 20 m, measured from injection point. This result confirms that the placement of the first radiation detector at the distance 80 m from the injection point was correct

Evaluation of flow-induced vibration prediction techniques for in-reactor components

International Nuclear Information System (INIS)

Mulcahy, T.M.; Turula, P.

1975-05-01

Selected in-reactor components of a hydraulic and structural dynamic scale model of the U. S. Energy Research and Development Administration experimental Fast Test Reactor have been studied in an effort to develop and evaluate techniques for predicting vibration behavior of elastic structures exposed to a moving fluid. Existing analysis methods are used to compute the natural frequencies and modal shapes of submerged beam and shell type components. Component response is calculated, assuming as fluid forcing mechanisms both vortex shedding and random excitations characterized by the available hydraulic data. The free and force vibration response predictions are compared with extensive model flow and shaker test data. (U.S.)

Building waste management core indicators through Spatial Material Flow Analysis: Net recovery and transport intensity indexes

International Nuclear Information System (INIS)

Font Vivanco, David; Puig Ventosa, Ignasi; Gabarrell Durany, Xavier

2012-01-01

Highlights: ► Sustainability and proximity principles have a key role in waste management. ► Core indicators are needed in order to quantify and evaluate them. ► A systematic, step-by-step approach is developed in this study for their development. ► Transport may play a significant role in terms of environmental and economic costs. ► Policy action is required in order to advance in the consecution of these principles. - Abstract: In this paper, the material and spatial characterization of the flows within a municipal solid waste (MSW) management system are combined through a Network-Based Spatial Material Flow Analysis. Using this information, two core indicators are developed for the bio-waste fraction, the Net Recovery Index (NRI) and the Transport Intensity Index (TII), which are aimed at assessing progress towards policy-related sustainable MSW management strategies and objectives. The NRI approaches the capacity of a MSW management system for converting waste into resources through a systematic metabolic approach, whereas the TII addresses efficiency in terms of the transport requirements to manage a specific waste flow throughout the entire MSW management life cycle. Therefore, both indicators could be useful in assessing key MSW management policy strategies, such as the consecution of higher recycling levels (sustainability principle) or the minimization of transport by locating treatment facilities closer to generation sources (proximity principle). To apply this methodological approach, the bio-waste management system of the region of Catalonia (Spain) has been chosen as a case study. Results show the adequacy of both indicators for identifying those points within the system with higher capacity to compromise its environmental, economic and social performance and therefore establishing clear targets for policy prioritization. Moreover, this methodological approach permits scenario building, which could be useful in assessing the outcomes of

Development of advanced stability theory suction prediction techniques for laminar flow control. [on swept wings

Science.gov (United States)

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.

Prediction of Baseflow Index of Catchments using Machine Learning Algorithms

Science.gov (United States)

Yadav, B.; Hatfield, K.

2017-12-01

We present the results of eight machine learning techniques for predicting the baseflow index (BFI) of ungauged basins using a surrogate of catchment scale climate and physiographic data. The tested algorithms include ordinary least squares, ridge regression, least absolute shrinkage and selection operator (lasso), elasticnet, support vector machine, gradient boosted regression trees, random forests, and extremely randomized trees. Our work seeks to identify the dominant controls of BFI that can be readily obtained from ancillary geospatial databases and remote sensing measurements, such that the developed techniques can be extended to ungauged catchments. More than 800 gauged catchments spanning the continental United States were selected to develop the general methodology. The BFI calculation was based on the baseflow separated from daily streamflow hydrograph using HYSEP filter. The surrogate catchment attributes were compiled from multiple sources including digital elevation model, soil, landuse, climate data, other publicly available ancillary and geospatial data. 80% catchments were used to train the ML algorithms, and the remaining 20% of the catchments were used as an independent test set to measure the generalization performance of fitted models. A k-fold cross-validation using exhaustive grid search was used to fit the hyperparameters of each model. Initial model development was based on 19 independent variables, but after variable selection and feature ranking, we generated revised sparse models of BFI prediction that are based on only six catchment attributes. These key predictive variables selected after the careful evaluation of bias-variance tradeoff include average catchment elevation, slope, fraction of sand, permeability, temperature, and precipitation. The most promising algorithms exceeding an accuracy score (r-square) of 0.7 on test data include support vector machine, gradient boosted regression trees, random forests, and extremely randomized

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

Science.gov (United States)

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.

Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

Science.gov (United States)

Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

2013-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

A phenomenological prediction of dryout based on the churn-to-annular flow transition criterion in uniformly heated vertical tubes

International Nuclear Information System (INIS)

Hong, Sung-Deok; Chun, Se-Young; Yang, Sun-Kyu; Chung, Moon-Ki; Lashgari, Farbod

2000-01-01

A phenomenological model is proposed to predict dryout in uniformly heated vertical tubes. The major point of the study was refining the initial conditions at the onset of annular flow location that starts the liquid film dryout process. The void fraction at the onset of the annular flow location has been derived from the vapor superficial velocity obtained by the churn-to-annular flow criterion with the help of the void-quality relationship. The thermodynamic equilibrium quality calculated through the iteration of flow quality using the profile-fit model to find the accurate starting point of the annular-flow in a tube. The present method was validated by worldwide data covering wide parametric ranges, a diameter of 5.1-37.5, exit quality over 10%, a flow rate of 183-5261 kg/m 2 -s and a system pressure of 0.5-17.7 MPa. The churn-to-annular flow transition criterion of Taitel et al.'s shows better prediction results than the other transition criteria. The present model improved the CHF prediction capability as a mean of 0.97 and root mean square error of 11% for the 3883 experimental data and extended the applicable range to the relatively low quality region. (author)

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

Science.gov (United States)

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.

Comparison of short-term rainfall forecasts for modelbased flow prediction in urban drainage systems

DEFF Research Database (Denmark)

Thorndahl, Søren; Ahm, Malte; Nielsen, Jesper Ellerbek

2013-01-01

Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied...... performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times....

CFD Prediction of Airfoil Drag in Viscous Flow Using the Entropy Generation Method

Directory of Open Access Journals (Sweden)

Wei Wang

2018-01-01

Full Text Available A new aerodynamic force of drag prediction approach was developed to compute the airfoil drag via entropy generation rate in the flow field. According to the momentum balance, entropy generation and its relationship to drag were derived for viscous flow. Model equations for the calculation of the local entropy generation in turbulent flows were presented by extending the RANS procedure to the entropy balance equation. The accuracy of algorithm and programs was assessed by simulating the pressure coefficient distribution and dragging coefficient of different airfoils under different Reynolds number at different attack angle. Numerical data shows that the total entropy generation rate in the flow field and the drag coefficient of the airfoil can be related by linear equation, which indicates that the total drag could be resolved into entropy generation based on its physical mechanism of energy loss.

River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

Directory of Open Access Journals (Sweden)

H. Sanikhani

2016-02-01

Full Text Available Introduction: In the recent years, researchers interested on probabilistic forecasting of hydrologic variables such river flow.A probabilistic approach aims at quantifying the prediction reliability through a probability distribution function or a prediction interval for the unknown future value. The evaluation of the uncertainty associated to the forecast is seen as a fundamental information, not only to correctly assess the prediction, but also to compare forecasts from different methods and to evaluate actions and decisions conditionally on the expected values. Several probabilistic approaches have been proposed in the literature, including (1 methods that use resampling techniques to assess parameter and model uncertainty, such as the Metropolis algorithm or the Generalized Likelihood Uncertainty Estimation (GLUE methodology for an application to runoff prediction, (2 methods based on processing the forecast errors of past data to produce the probability distributions of future values and (3 methods that evaluate how the uncertainty propagates from the rainfall forecast to the river discharge prediction, as the Bayesian forecasting system. Materials and Methods: In this study, two different probabilistic methods are used for river flow prediction.Then the uncertainty related to the forecast is quantified. One approach is based on linear predictors and in the other, nearest neighbor was used. The nonlinear probabilistic ensemble can be used for nonlinear time series analysis using locally linear predictors, while NNPE utilize a method adapted for one step ahead nearest neighbor methods. In this regard, daily river discharge (twelve years of Dizaj and Mashin Stations on Baranduz-Chay basin in west Azerbijan and Zard-River basin in Khouzestan provinces were used, respectively. The first six years of data was applied for fitting the model. The next three years was used to calibration and the remained three yeas utilized for testing the models

Cerebral tissue oxygenation index and superior vena cava blood flow in the very low birth weight infant.

LENUS (Irish Health Repository)

Moran, M

2012-02-01

BACKGROUND: Superior vena cava (SVC) flow assesses blood flow from the upper body, including the brain. Near infrared spectroscopy (NIRS) provides information on brain perfusion and oxygenation. AIM: To assess the relationship between cerebral tissue oxygenation index (cTOI) and cardiac output measures in the very low birth weight (VLBW) infant in the first day of life. METHODS: A prospective observational cohort study. Neonates with birth weight less than 1500 g (VLBW) were eligible for enrollment. Newborns with congenital heart disease, major congenital malformations and greater than Papile grade1 Intraventricular Haemorrhage on day 1 of life were excluded. Echocardiographic evaluation of SVC flow was performed in the first 24 h of life. Low SVC flow states were defined as a flow less than 40 mL\\/kg\\/min. cTOI was measured using NIRO 200 Hamamatsu. RESULTS: Twenty-seven VLBW neonates had both echocardiography and NIRS performed. The median (range) gestation was 29\\/40 (25 + 3 to 31 + 5 weeks) and median birth weight was 1.2 kg (0.57-1.48 kg). The mean (SD) TOI was 68.1 (7.9)%. The mean (SD) SVC flow was 70.36(39.5) mLs\\/kg\\/min. The correlation coefficient of cerebral tissue oxygenation and SVC flow was r = 0.53, p-value 0.005. There was a poor correlation between right and left ventricular output and cTOI which is not surprising considering the influence of intra- and extracardiac shunts. CONCLUSION: There is a positive relationship between cerebral TOI values and SVC flow in the very low birth infant on day one of life.

Flow-induced vibration and flow characteristics prediction for a sliding roller gate by two-dimensional unsteady CFD simulation

Energy Technology Data Exchange (ETDEWEB)

Kim, Nak-Geun; Lee, Kye-Bock [Chungbuk National University, Cheongju (Korea, Republic of); Cho, Yong [Korea Water Resources Corporation, Daejeon (Korea, Republic of)

2017-07-15

Numerical analysis on the flow induced vibration and flow characteristics in the water gate has been carried out by 2-dimensional unsteady CFD simulation when sea water flows into the port in the river. Effect of gate opening on the frequency and the mean velocity and the vortex shedding under the water gate were studied. The streamlines were compared for various gate openings. To get the frequency spectrum, Fourier transform should be performed. Spectral analysis of the excitation force signals permitted identification of the main characteristics of the interaction process. The results show that the sources of disturbed frequency are the vortex shedding from under the water gate. As the gate opening ratio increases, the predicted vibration frequency decreases. The bottom scouring occurs for large gate opening rather than smaller one. The unstable operation conditions can be estimated by using the CFD results and the Strouhal number results for various gate opening gaps.

Flow-induced vibration and flow characteristics prediction for a sliding roller gate by two-dimensional unsteady CFD simulation

International Nuclear Information System (INIS)

Kim, Nak-Geun; Lee, Kye-Bock; Cho, Yong

2017-01-01

Numerical analysis on the flow induced vibration and flow characteristics in the water gate has been carried out by 2-dimensional unsteady CFD simulation when sea water flows into the port in the river. Effect of gate opening on the frequency and the mean velocity and the vortex shedding under the water gate were studied. The streamlines were compared for various gate openings. To get the frequency spectrum, Fourier transform should be performed. Spectral analysis of the excitation force signals permitted identification of the main characteristics of the interaction process. The results show that the sources of disturbed frequency are the vortex shedding from under the water gate. As the gate opening ratio increases, the predicted vibration frequency decreases. The bottom scouring occurs for large gate opening rather than smaller one. The unstable operation conditions can be estimated by using the CFD results and the Strouhal number results for various gate opening gaps.

A noninvasive method for measuring the velocity of diffuse hydrothermal flow by tracking moving refractive index anomalies

Science.gov (United States)

Mittelstaedt, Eric; Davaille, Anne; van Keken, Peter E.; Gracias, Nuno; Escartin, Javier

2010-10-01

Diffuse flow velocimetry (DFV) is introduced as a new, noninvasive, optical technique for measuring the velocity of diffuse hydrothermal flow. The technique uses images of a motionless, random medium (e.g., rocks) obtained through the lens of a moving refraction index anomaly (e.g., a hot upwelling). The method works in two stages. First, the changes in apparent background deformation are calculated using particle image velocimetry (PIV). The deformation vectors are determined by a cross correlation of pixel intensities across consecutive images. Second, the 2-D velocity field is calculated by cross correlating the deformation vectors between consecutive PIV calculations. The accuracy of the method is tested with laboratory and numerical experiments of a laminar, axisymmetric plume in fluids with both constant and temperature-dependent viscosity. Results show that average RMS errors are ˜5%-7% and are most accurate in regions of pervasive apparent background deformation which is commonly encountered in regions of diffuse hydrothermal flow. The method is applied to a 25 s video sequence of diffuse flow from a small fracture captured during the Bathyluck'09 cruise to the Lucky Strike hydrothermal field (September 2009). The velocities of the ˜10°C-15°C effluent reach ˜5.5 cm/s, in strong agreement with previous measurements of diffuse flow. DFV is found to be most accurate for approximately 2-D flows where background objects have a small spatial scale, such as sand or gravel.

Combining Spatial Models for Shallow Landslides and Debris-Flows Prediction

Directory of Open Access Journals (Sweden)

Eurípedes Vargas do Amaral

2013-05-01

Full Text Available Mass movements in Brazil are common phenomena, especially during strong rainfall events that occur frequently in the summer season. These phenomena cause losses of lives and serious damage to roads, bridges, and properties. Moreover, the illegal occupation by slums on the slopes around the cities intensifies the effect of the mass movement. This study aimed to develop a methodology that combines models of shallow landslides and debris-flows in order to create a map with landslides initiation and debris-flows volume and runout distance. The study area comprised of two catchments in Rio de Janeiro city: Quitite and Papagaio that drained side by side the west flank of the Maciço da Tijuca, with an area of 5 km2. The method included the following steps: (a location of the susceptible areas to landslides using SHALSTAB model; (b determination of rheological parameters of debris-flow from the back-analysis technique; and (c combination of SHALSTAB and FLO-2D models to delineate the areas more susceptible to mass movements. These scenarios were compared with the landslide and debris-flow event of February 1996. Many FLO-2D simulations were exhaustively made to estimate the rheological parameters from the back-analysis technique. Those rheological coefficients of single simulation were back-calculated by adjusting with area and depth of the debris-flow obtained from field data. The initial material volume in the FLO-2D simulations was estimated from SHALSTAB model. The combination of these two mathematical models, SHALSTAB and FLO-2D, was able to predict both landslides and debris-flow events. Such procedures can reduce the casualties and property damage, delineating hazard areas, to estimate hazard intensities for input into risk studies providing information for public policy and planning.

A new daily dividend-adjusted index for the Danish stock market, 1985-2002: Construction, statistical properties, and return predictability

DEFF Research Database (Denmark)

Belter, Klaus; Engsted, Tom; Tanggaard, Carsten

2005-01-01

is given. In the second part of the paper we analyze the time-series properties of daily, weekly, and monthly returns, and we present evidence on predictability of multi-period returns. We also compare stock returns with the returns on long-term bonds and short-term money market instruments (that is......We present a new dividend-adjusted blue chip index for the Danish stock market covering the period 1985-2002. In contrast to other indices on the Danish stock market, the index is calculated on a daily basis. In the first part of the paper a detailed description of the construction of the index...

Value Of Three Dimensional Power Doppler Ultrasound In Prediction Of Endometrial Carcinoma In Patients With Postmenopausal Bleeding

International Nuclear Information System (INIS)

Abou-Gabal, A.; Akl, Sh.A.; Hussain, Sh.H.; Allam, H.A.

2013-01-01

Objective: to determine whether endometrial volume or power Doppler indices as measured by 3D ultrasound imaging can discriminate between benign and malignant endometrium in women with postmenopausal bleeding and endometrial thickness > 5 mm. Study design: Eighty-four patients with postmenopausal bleeding and endometrial thickness > 5 mm underwent 3D power Doppler ultrasound examination of the corpus uteri. The endometrial volume was calculated, along with the vascularisation index (VI), flow index and vascularisation flow index (VFI) in the endometrium. The gold standard was the histological diagnosis of the endometrium. Results: There were 56 benign and 28 malignant endometrial. Endometrial thickness and volume were significantly larger in malignant than in benign endometrial, and flow indices in the endometrium were Significantly higher. The area under the ROC curve (AUC) of endometrial thickness was 0.83, that of endometrial volume 0.73, and that of the best power Doppler variable FI 0.93. The best logistic regression model for predicting malignancy contained the variables endometrial thickness and FI. Its AUC was 0.93. Conclusion: the diagnostic performance of endometrial volume measured by 3d imaging with regard to discriminating between benign and malignant endometrium was not superior to that of endometrial thickness measured by 2D ultrasound examination, but 3D power Doppler flow indices are good diagnostic tool in predicting endometrial carcinoma

Flashing inception in flowing liquids

International Nuclear Information System (INIS)

Jones, O.C. Jr.

1980-01-01

The inception of net vaporization in flashing flows is examined. It is suggested that the flashing inception can be expressed as two additive effects. One is due to the static decompression which is a function of the initial temperature and also the expansion rate. The other effect which is a function of Reynolds number and flashing index, is due to the turbulent fluctuations of the flowing liquid. It is shown that by taking a three standard deviation band on the turbulent velocity fluctuations, an adequate representation of the inverse mass flux effect on flashing inception for existing data is obtained. The turbulence effects are combined with the correlation of Alamgir and Lienhard to provide predictive methods recommended for the case where both static and convective decompression effects exist

The predictive value of the baseline Oswestry Disability Index in lumbar disc arthroplasty.

Science.gov (United States)

Deutsch, Harel

2010-06-01

The goal of the study was to determine patient factors predictive of good outcome after lumbar disc arthroplasty. Specifically, the paper examines the relationship of the preoperative Oswestry Disability Index (ODI) to patient outcome at 1 year. The study is a retrospective review of 20 patients undergoing a 1-level lumbar disc arthroplasty at the author's institution between 2004 and 2008. All data were collected prospectively. Data included the ODI, visual analog scale scores, and patient demographics. All patients underwent a 1-level disc arthroplasty at L4-5 or L5-S1. The patients were divided into 2 groups based on their baseline ODI. Patients with an ODI between 38 and 59 demonstrated better outcomes with lumbar disc arthroplasty. Only 1 (20%) of 5 patients with a baseline ODI higher than 60 reported a good outcome. In contrast, 13 (87%) of 15 patients with an ODI between 38 and 59 showed a good outcome (p = 0.03). The negative predictive value of using ODI > 60 is 60% in patients who are determined to be candidates for lumbar arthroplasty. Lumbar arthroplasty is very effective in some patients. Other patients do not improve after surgery. The baseline ODI results are predictive of outcome in patients selected for lumbar disc arthroplasty. A baseline ODI > 60 is predictive of poor outcome. A high ODI may be indicative of psychosocial overlay.

Fast reconstruction and prediction of frozen flow turbulence based on structured Kalman filtering

NARCIS (Netherlands)

Fraanje, P.R.; Rice, J.; Verhaegen, M.; Doelman, N.J.

2010-01-01

Efficient and optimal prediction of frozen flow turbulence using the complete observation history of the wavefront sensor is an important issue in adaptive optics for large ground-based telescopes. At least for the sake of error budgeting and algorithm performance, the evaluation of an accurate

Prediction of low birth weight: the placental T2* estimated by MRI versus the uterine artery pulsatility index

DEFF Research Database (Denmark)

Sinding, Marianne Munk; Peters, David Alberg; Frøkjær, Jens Brøndum

(MRI) variable T2* reflects the placental oxygenation and thereby placental function. Therefore, we aimed to evaluate the performance of placental T2* in the prediction of low birth weight using the uterine artery (UtA) pulsatility index (PI) as gold standard. Methods: The study population......CONTROL ID: 2516296 ABSTRACT FINAL ID: P22.05 TITLE: Prediction of low birth weight: the placental T2* estimated by MRI versus the uterine artery pulsatility index AUTHORS (FIRST NAME, LAST NAME): Marianne Sinding1, David Peters2, Jens B. Frøkjær3, 4, Ole B. Christiansen1, 4, Astrid Petersen5...... had an EFW T2* was measured by MRI at 1.5T. A gradient recalled echo MRI sequence with readout at 16 echo times was used, and the placental T2* value was obtained by fitting the signal intensity as a function of the echo times...

Comparison of the significance of the RENAL, PADUA, and C-index nephrometric scales for the prediction of the complexity of laparoscopic nephrectomy

Directory of Open Access Journals (Sweden)

Yu. G. Alyaev

2018-01-01

Full Text Available Objective: to compare the predictive value of RENAL, PADUA, C-index nephrometry score systems according to projection of complexity  of operative measure in terms of warm ischaemic time, extent of blood loss and rate of postoperative complications.Materials and methods. Information for the research was collected from 314 patients with localized kidney cancer, who had laparoscopic partial nephrectomy from January 2012 to May 2017. In 210 (66.8 % cases, in addition to the routine examinations, 3D modelling and operative measure planning were carried out. The average tumor volume of the patients was equal to 62.5 ± 33.5 mm3. All patients before  the operation were estimated the complexity of operative measure on the nephrometry score systems: PADUA, RENAL, C-index. The average sum of balls according to scale RENAL – 7.56 ± 1.12, on scale PADUA – 7.98 ± 1.55, on scale C-index – 2.76 ± 1.14. Then in retrospect by the method of logistic regression analysis was determined predictive value of RENAL, PADUA, C-index nephrometry score systems for prediction of warm ischaemic time, duration of operative measure, extent of intraoperative blood loss and possibility of rate of postoperative complications.Results. In 265 (84.4 cases transperitoneal approach was perfomed and in 49 (15.6 % cases it was retroperitoneal approach. The average time of laparoscopic partial nephrectomy is 140.15 ± 55.8 min, the average time of ischaemic warm is 13.35 ± 7,65 min. The average extent of blood loss during the laparoscopic partial nephrectomy is 291.95 ± 196.5 ml. Intraoperative complications were found in 8 (2.54 % cases. Postoperative complications were estimated according to the Clavien–Dindo classification of surgical complications and were found in 31  (9.9 % cases, among them 12 (3.8 % patients had surgical complications. The index of the RENAL nephrometry scoring system had the highest predictive value in the multivariant analysis for warm ischaemic

Prediction of gas volume fraction in fully-developed gas-liquid flow in a vertical pipe

International Nuclear Information System (INIS)

Islam, A.S.M.A.; Adoo, N.A.; Bergstrom, D.J.; Wang, D.F.

2015-01-01

An Eulerian-Eulerian two-fluid model has been implemented for the prediction of the gas volume fraction profile in turbulent upward gas-liquid flow in a vertical pipe. The two-fluid transport equations are discretized using the finite volume method and a low Reynolds number κ-ε turbulence model is used to predict the turbulence field for the liquid phase. The contribution to the effective turbulence by the gas phase is modeled by a bubble induced turbulent viscosity. For the fully-developed flow being considered, the gas volume fraction profile is calculated using the radial momentum balance for the bubble phase. The model potentially includes the effect of bubble size on the interphase forces and turbulence model. The results obtained are in good agreement with experimental data from the literature. The one-dimensional formulation being developed allows for the efficient assessment and further development of both turbulence and two-fluid models for multiphase flow applications in the nuclear industry. (author)

Prediction of gas volume fraction in fully-developed gas-liquid flow in a vertical pipe

Energy Technology Data Exchange (ETDEWEB)

Islam, A.S.M.A.; Adoo, N.A.; Bergstrom, D.J., E-mail: nana.adoo@usask.ca [University of Saskatchewan, Department of Mechanical Engineering, Saskatoon, SK (Canada); Wang, D.F. [Canadian Nuclear Laboratories, Chalk River, ON (Canada)

2015-07-01

An Eulerian-Eulerian two-fluid model has been implemented for the prediction of the gas volume fraction profile in turbulent upward gas-liquid flow in a vertical pipe. The two-fluid transport equations are discretized using the finite volume method and a low Reynolds number κ-ε turbulence model is used to predict the turbulence field for the liquid phase. The contribution to the effective turbulence by the gas phase is modeled by a bubble induced turbulent viscosity. For the fully-developed flow being considered, the gas volume fraction profile is calculated using the radial momentum balance for the bubble phase. The model potentially includes the effect of bubble size on the interphase forces and turbulence model. The results obtained are in good agreement with experimental data from the literature. The one-dimensional formulation being developed allows for the efficient assessment and further development of both turbulence and two-fluid models for multiphase flow applications in the nuclear industry. (author)

Analytic solution to verify code predictions of two-phase flow in a boiling water reactor core channel

International Nuclear Information System (INIS)

Chen, K.F.; Olson, C.A.

1983-01-01

One reliable method that can be used to verify the solution scheme of a computer code is to compare the code prediction to a simplified problem for which an analytic solution can be derived. An analytic solution for the axial pressure drop as a function of the flow was obtained for the simplified problem of homogeneous equilibrium two-phase flow in a vertical, heated channel with a cosine axial heat flux shape. This analytic solution was then used to verify the predictions of the CONDOR computer code, which is used to evaluate the thermal-hydraulic performance of boiling water reactors. The results show excellent agreement between the analytic solution and CONDOR prediction

Prediction of subcooled flow boiling characteristics using two-fluid Eulerian CFD model

Energy Technology Data Exchange (ETDEWEB)

Braz Filho, Francisco A.; Ribeiro, Guilherme B., E-mail: gbribeiro@ieav.cta.br; Caldeira, Alexandre D.

2016-11-15

Highlights: • CFD multiphase model is used to predict subcooled flow boiling characteristics. • Better agreement is achieved for higher saturation pressures. • Onset of nucleate boiling and saturated boiling are well predicted. • CFD multiphase model tends to underestimate the void fraction. • Factors were adjusted in order to improve the void fraction results. - Abstract: The present study concerns a detailed analysis of flow boiling phenomena under high pressure systems using a two-fluid Eulerian approach provided by a Computational Fluid Dynamics (CFD) solver. For this purpose, a vertical heated pipe made of stainless steel with an internal diameter of 15.4 mm was considered as the modeled domain. Two different uniform heat fluxes and three saturation pressures were applied to the channel wall, whereas water mass flux of 900 kg/m{sup 2} s was considered for all simulation cases. The model was validated against a set of experimental data and results have indicated a promising use of the CFD technique for estimation of the wall temperature, the liquid bulk temperature and the location of the departure of nucleate boiling. Changes in factors applied in the modeling of the interfacial heat transfer coefficient and bubble departure frequency were suggested, allowing a better prediction of the void fraction along the heated channel. The commercial CFD solver FLUENT 14.5 was used for the model implementation.

Prediction of subcooled flow boiling characteristics using two-fluid Eulerian CFD model

International Nuclear Information System (INIS)

Braz Filho, Francisco A.; Ribeiro, Guilherme B.; Caldeira, Alexandre D.

2016-01-01

Highlights: • CFD multiphase model is used to predict subcooled flow boiling characteristics. • Better agreement is achieved for higher saturation pressures. • Onset of nucleate boiling and saturated boiling are well predicted. • CFD multiphase model tends to underestimate the void fraction. • Factors were adjusted in order to improve the void fraction results. - Abstract: The present study concerns a detailed analysis of flow boiling phenomena under high pressure systems using a two-fluid Eulerian approach provided by a Computational Fluid Dynamics (CFD) solver. For this purpose, a vertical heated pipe made of stainless steel with an internal diameter of 15.4 mm was considered as the modeled domain. Two different uniform heat fluxes and three saturation pressures were applied to the channel wall, whereas water mass flux of 900 kg/m"2 s was considered for all simulation cases. The model was validated against a set of experimental data and results have indicated a promising use of the CFD technique for estimation of the wall temperature, the liquid bulk temperature and the location of the departure of nucleate boiling. Changes in factors applied in the modeling of the interfacial heat transfer coefficient and bubble departure frequency were suggested, allowing a better prediction of the void fraction along the heated channel. The commercial CFD solver FLUENT 14.5 was used for the model implementation.

Prediction of flow recirculation in a blanket assembly under worst-case natural-convection conditions

International Nuclear Information System (INIS)

Khan, E.U.; Rector, D.R.

1982-01-01

Reactor fuel and blanket assemblies within a Liquid Metal Fast Breeder Reactor (LMFBR) can be subjected to severe radial heat flux gradients. At low-flow conditions, with power-to-flow ratios of nearly the same magnitude as design conditions, buoyancy forces cause flow redistribution to the side of a bundle with the higher heat generation rate. Recirculation of fluid within a rod bundle can occur during a natural convection transient because of the combined effect of flow coastdown and buoyancy-induced redistribution. An important concern is whether recirculation leads to high coolant temperatures. For this reason, the COBRA-WC code was developed with the capability of modeling recirculating flows. Experiments have been conducted in a 2 x 6 rod bundle for flow and power transients to study recirculation in the mixed-convection (forced cooled) and natural-convection regimes. The data base developed was used to validate the recirculation module in the COBRA-WC code. COBRA-WC code calculations were made to predict flow and temperature distributions in a typical LMFBR blanket assembly for the worst-case, natural-circulation transient

Application of a two-dimensional model for predicting the pressure-flow and compression properties during column packing scale-up.

Science.gov (United States)

McCue, Justin T; Cecchini, Douglas; Chu, Cathy; Liu, Wei-Han; Spann, Andrew

2007-03-23

A two-dimensional model was formulated to describe the pressure-flow behavior of compressible stationary phases for protein chromatography at different temperatures and column scales. The model was based on the assumption of elastic deformation of the solid phase and steady-state Darcy flow. Using a single fitted value for the empirical modulus parameters, the model was applied to describe the pressure-flow behavior of several adsorbents packed using both fluid flow and mechanical compression. Simulations were in agreement with experimental data and accurately predicted the pressure-flow and compression behavior of three adsorbents over a range of column scales and operating temperatures. Use of the described theoretical model potentially improves the accuracy of the column scale-up process, allowing the use of limited laboratory scale data to predict column performance in large scale applications.

A quantitative index of regional blood flow in canine myocardium derived noninvasively with N-13 ammonia and dynamic positron emission tomography

Energy Technology Data Exchange (ETDEWEB)

Nienaber, C.A.; Ratib, O.; Gambhir, S.S.; Krivokapich, J.; Huang, S.C.; Phelps, M.E.; Schelbert, H.R. (Univ. of California, Los Angeles School of Medicine (USA))

1991-01-01

To derive a quantitative index of regional myocardial blood flow, the arterial input function of the flow tracer N-13 ammonia and the regional myocardial N-13 activity concentrations were noninvasively determined in 29 experiments in eight dogs. N-13 ammonia was administered intravenously and cross-sectional images were acquired dynamically using an ECAT III positron emission tomograph with an effective in-plane resolution of 13.46 mm full-width half-maximum. Time-activity curves were derived from the serial images by assigning regions of interest to the left ventricular myocardium and left ventricular blood pool. Tracer net extractions were estimated from the myocardial time-activity concentrations at various times after tracer injection and the integral of the arterial input function. Myocardial blood flow was altered by intravenous dipyridamole, morphine, propranolol and partial or complete occlusion of the left anterior descending coronary artery, and ranged from 9 to 860 ml/min per 100 g. Estimates of tracer net extractions were most accurate when determined from the myocardial N-13 activity concentrations at 60 s divided by the integral of the arterial input function to that time. These estimates correlated with regional myocardial blood flows determined independently by the microsphere technique by y = x (1 - 0.64(e-114/x); SEE = 22.9; r = 0.94). First pass extraction fractions of N-13 ammonia determined noninvasively with this approach declined with higher flows in a nonlinear fashion and were similar to those determined invasively by direct intracoronary N-13 ammonia injections. The findings indicate that an accurate index of regional myocardial blood flow can be obtained noninvasively by high temporal sampling of arterial and myocardial tracer activity concentrations with positron emission tomography.

Prostate Health Index improves multivariable risk prediction of aggressive prostate cancer.

Science.gov (United States)

Loeb, Stacy; Shin, Sanghyuk S; Broyles, Dennis L; Wei, John T; Sanda, Martin; Klee, George; Partin, Alan W; Sokoll, Lori; Chan, Daniel W; Bangma, Chris H; van Schaik, Ron H N; Slawin, Kevin M; Marks, Leonard S; Catalona, William J

2017-07-01

To examine the use of the Prostate Health Index (PHI) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. The study population included 728 men, with prostate-specific antigen (PSA) levels of 2-10 ng/mL and a negative digital rectal examination, enrolled in a prospective, multi-site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [PCPT] and European Randomised Study of Screening for Prostate Cancer [ERSPC] risk calculators). We also designed and internally validated a new PHI-based multivariable predictive model, and created a nomogram. Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI, with an area under the curve of 0.746. The bootstrap-corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision-curve analysis. Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis. © 2016 The Authors BJU International © 2016 BJU International Published by John Wiley & Sons Ltd.

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

Science.gov (United States)

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

2013-03-15

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

A dry-spot model for the prediction of critical heat flux in water boiling in bubbly flow regime

International Nuclear Information System (INIS)

Ha, Sang Jun; No, Hee Cheon

1997-01-01

This paper presents a prediction of critical heat flux (CHF) in bubbly flow regime using dry-spot model proposed recently by authors for pool and flow boiling CHF and existing correlations for forced convective heat transfer coefficient, active site density and bubble departure diameter in nucleate boiling region. Without any empirical constants always present in earlier models, comparisons of the model predictions with experimental data for upward flow of water in vertical, uniformly-heated round tubes are performed and show a good agreement. The parametric trends of CHF have been explored with respect to variation in pressure, tube diameter and length, mass flux and inlet subcooling

Application of flow-induced vibration predictive techniques to operating steam generators

International Nuclear Information System (INIS)

Sauve, R.G.; Tabatabai, M.; Morandin, G.; Kozluk, M.J.

1998-01-01

Analytical techniques for flow-induced vibration (FIV), such as those incorporated in available design tools, are routinely applied to process equipment at the initial design stage. Unfortunately, this does not always apply to the situation when problems, related to FIV, develop in crucial operating equipment, since design uses conservative methods, whereas in-service applications require more realistic assessments. Usually these problems appear in the form of severe through wall fret flaws or fatigue cracks that compromise the integrity of the tubes and possibly the complete unit. It is here where a somewhat different approach must be taken in the evaluation of tube response to FIV. Tube damage from fretting wear or fatigue crack growth must be estimated from actual in situ operating conditions. In this paper, an overview of the predictive methods used in the development and/or qualification of remedial measures for problems that occur in operating process equipment along with applications are described. The steps in the evaluation procedure, from the prediction of flow regimes, the development of the nonlinear computer models and associated fluid forcing functions through to the estimates of tube damage in operating heat exchangers and steam generators are presented. A probabilistic (i.e. Monte Carlo simulation) FIV approach that readily accommodates uncertainties associated with damage predictions is summarized. The efficacy of this approach comes from the fact that probabilistic methods facilitate the incorporation of field data, and that a large number of tubes and possible variations in geometry, process and support conditions, usually present in such equipment, can be addressed effectively. (author)

Limited accuracy of the hyperbaric index, ambulatory blood pressure and sphygmomanometry measurements in predicting gestational hypertension and preeclampsia

NARCIS (Netherlands)

Vollebregt, Karlijn Corien; Gisolf, Janneke; Guelen, Ilja; Boer, Kees; van Montfrans, Gert; Wolf, Hans

2010-01-01

Objective The aim of this study was to validate the hyperbaric index (HBI) for first trimester prediction of preeclampsia and gestational hypertension. Methods Participants were low-risk and high-risk nulliparous women and high-risk multiparous women, and were recruited between April 2004 and June

PREDICTION OF LEAKAGE FLOW AND ROTORDYNAMIC CHARACTERISTICS FOR AN ECCENTRIC LABYRINTH GAS SEAL

Directory of Open Access Journals (Sweden)

MOHAMED KAMOUNI

2017-11-01

Full Text Available Labyrinth seals are key elements to limit leakage flow between rotating and stationary parts of turbo machines. However, these seals can modify the rotordynamic stability of machines. Thus, accurate predictions of static and dynamic behaviour for labyrinth seals are very important to optimize efficiency and operating conditions of rotating machines using this kind of seals. The present work contributes by a numerical model based on CFD computation to predict leakage flow and rotordynamic coefficients for a short eccentric labyrinth seal with four teeth fixed on the rotor. The developed model accuracy has been validated on experimental measurements of the pressure distribution along and around the seal which drops from 110770 Pa at the seal inlet to 103300 Pa at the seal outlet. A parametric study has been conducted to show the effect of pressure ratio and inlet swirl ratio on leakage flow and rotordynamic coefficients of the seal. In this study, the outlet pressure is kept constant but the inlet/outlet pressure ratio varies from 1.072 to 8 while three inlet swirl ratios (0, 0.5 and 1 are considered. Obtained results of this work are presented to help designers and industrials optimizing operating conditions and improving performances of this kind of seals.

Low-flow characteristics of streams in the Puget Sound region, Washington

Science.gov (United States)

Hidaka, F.T.

1973-01-01

Periods of low streamflow are usually the most critical factor in relation to most water uses. The purpose of this report is to present data on low-flow characteristics of streams in the Puget Sound region, Washington, and to briefly explain some of the factors that influence low flow in the various basins. Presented are data on low-flow frequencies of streams in the Puget Sound region, as gathered at 150 gaging stations. Four indexes were computed from the flow-flow-frequency curves and were used as a basis to compare the low-flow characteristics of the streams. The indexes are the (1) low-flow-yield index, expressed in unit runoff per square mile; (2) base-flow index, or the ratio of the median 7-day low flow to the average discharge; (3) slope index, or slope of annual 7-day low-flow-frequency curve; and (4) spacing index, or spread between the 7-day and 183-day low-flow-frequency curves. The indexes showed a wide variation between streams due to the complex interrelation between climate, topography, and geology. The largest low-flow-yield indexes determined--greater than 1.5 cfs (cubic feet per second) per square mile--were for streams that head at high altitudes in the Cascade and Olympic Mountains and have their sources at glaciers. The smallest low-flow-yield indexes--less than 0.5 cfs per square mile--were for the small streams that drain the lowlands adjacent to Puget Sound. Indexes between the two extremes were for nonglacial streams that head at fairly high altitudes in areas of abundant precipitation. The base-flow index has variations that can be attributed to a basin's hydrogeology, with very little influence from climate. The largest base-flow indexes were obtained for streams draining permeable unconsolidated glacial and alluvial sediments in parts of the lowlands adjacent to Puget Sound. Large volume of ground water in these materials sustain flows during late summer. The smallest indexes were computed for streams draining areas underlain by