An Investigation of the Effect of Elongational Viscosity on Entrance Flow

2000 ◽  
Author(s):  
Debabrata Sarkar ◽  
Mahesh Gupta
Keyword(s):  
Elongational Viscosity ◽  
Rheological Parameters ◽  
Fully Developed Flow ◽  
New Model ◽  
Proposed Model ◽  
Trouton Ratio ◽  
Abrupt Contraction ◽  
Entrance Pressure ◽  
Entrance Pressure Loss ◽  
Entrance Flow

Abstract A new model for strain-rate dependence of elongational viscosity of a polymer is introduced. The proposed model can capture the initial strain thickening, which is followed by a descent in elongational viscosity as the elongation rate is further increased. Effect of the four rheological parameters in the new model on a 4:1 entrance flow is analyzed. It is confirmed that the entrance pressure loss and recirculating vortices in an entrance flow grow significantly as the Trouton ratio is increased. The center-line velocity near the abrupt contraction in a 4:1 entrance flow is found to overshoot its value for a fully developed flow in the downstream channel, if the Trouton ratio has a local minima beyond the Newtonian limit of the polymer.

Estimation of Elongational Viscosity Using Entrance Flow Simulation

2000 ◽  
Author(s):  
Debabrata Sarkar ◽  
Mahesh Gupta
Keyword(s):  
Experimental Data ◽  
Finite Element ◽  
Shear Viscosity ◽  
Flow Simulation ◽  
Elongational Viscosity ◽  
Viscosity Model ◽  
Capillary Rheometer ◽  
Element Simulation ◽  
Entrance Pressure ◽  
Entrance Pressure Loss

Abstract A new elongational viscosity model along with the Carreau-Yasuda model for shear viscosity is used for a finite element simulation of the flow in a capillary rheometer die. The entrance pressure loss predicted by the finite element flow simulation is matched with the corresponding experimental data to predict the parameters in the new elongational viscosity model. For two different polymers, the predicted elongational viscosity is compared with the corresponding predictions from Cogswell’s analysis and K-BKZ model.

RoRePo: Detecting the role information and relative position information for contexts in multi-turn dialogue generation

2021 ◽  
Vol 40 (5) ◽  
pp. 10003-10015
Author(s):  
Zibang Gan ◽  
Biqing Zeng ◽  
Lianglun Cheng ◽  
Shuai Liu ◽  
Heng Yang ◽  
...  
Keyword(s):  
Relative Position ◽  
Latent Variables ◽  
Role Ambiguity ◽  
Position Information ◽  
New Model ◽  
Proposed Model ◽  
Relevant Context ◽  
Position Representation ◽  
Current Speaker ◽  
Relative Position Information

In multi-turn dialogue generation, dialogue contexts have been shown to have an important influence on the reasoning of the next round of dialogue. A multi-turn dialogue between two people should be able to give a reasonable response according to the relevant context. However, the widely used hierarchical recurrent encoder-decoder model and the latest model that detecting the relevant contexts with self-attention are facing the same problem. Their given response doesn’t match the identity of the current speaker, which we call it role ambiguity. In this paper, we propose a new model, named RoRePo, to tackle this problem by detecting the role information and relative position information. Firstly, as a part of the decoder input, we add a role embedding to identity different speakers. Secondly, we incorporate self-attention mechanism with relative position representation to dialogue context understanding. Besides, the design of our model architecture considers the influence of latent variables in generating more diverse responses. Experimental results of our evaluations on the DailyDialog and DSTC7_AVSD datasets show that our proposed model advances in multi-turn dialogue generation.

A Novel Iterated Function System-Based Model for Coloured Image Encryption

2021 ◽  
Vol 12 (2) ◽  
pp. 1-10
Author(s):  
Amine Rahmani
Keyword(s):  
Image Encryption ◽  
Iterated Function System ◽  
Mathematical Concept ◽  
Logistic Equation ◽  
Encryption Scheme ◽  
Symmetric Encryption ◽  
New Model ◽  
Proposed Model ◽  
Iterated Function ◽  
Chaotic Cryptography

Chaotic cryptography has been a well-studied domain over the last few years. Many works have been done, and the researchers are still getting benefit from this incredible mathematical concept. This paper proposes a new model for coloured image encryption using simple but efficient chaotic equations. The proposed model consists of a symmetric encryption scheme in which it uses the logistic equation to generate secrete keys then an affine recursive transformation to encrypt pixels' values. The experimentations show good results, and theoretic discussion proves the efficiency of the proposed model.

A Flow Theory Integrated Model of Web IS Success

2011 ◽  
pp. 86-106
Author(s):  
Edward J. Garrity ◽  
Yong Jin Kim ◽  
Joseph B. O’Donnell ◽  
Cheul Rhee ◽  
G. Lawrence Sanders
Keyword(s):  
Success Factors ◽  
Flow Theory ◽  
Integrated Model ◽  
Motivating Factors ◽  
Nomological Network ◽  
Is Success ◽  
New Model ◽  
Proposed Model

This chapter develops a new model of web IS success that takes into account both intrinsic and extrinsic motivating factors. The proposed model begins with the Garrity and Sanders model of technologic acceptance and develops an extended nomological network of success factors that draws on motivation and flow theory.

scholarly journals A Hybrid Grey Prediction Model for Small Oscillation Sequence Based on Information Decomposition

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Meng Zhou ◽  
Bo Zeng ◽  
Wenhao Zhou
Keyword(s):  
Prediction Model ◽  
Small Oscillation ◽  
New Method ◽  
Superior Performance ◽  
Small Data ◽  
Grey Prediction ◽  
New Model ◽  
Grey Prediction Model ◽  
Proposed Model ◽  
Oscillation Characteristic

Grey prediction model has good performance in solving small data problem, and has been widely used in various research fields. However, when the data show oscillation characteristic, the effect of grey prediction model performs poor. To this end, a new method was proposed to solve the problem of modelling small data oscillation sequence with grey prediction model. Based on the idea of information decomposition, the new method employed grey prediction model to capture the trend characteristic of complex system, and ARMA model was applied to describe the random oscillation characteristic of the system. Crops disaster area in China was selected as a case study and the relevant historical eight-year data published by government department were substituted to the proposed model. The modelling results of the new model were compared with those of other traditional mainstream prediction models. The results showed that the new model had evidently superior performance. It indicated that the proposed model will contribute to solve small oscillation problems and have positive significance for improving the applicability of grey prediction model.

Analysis and Validation of Cutting Forces Prediction Models in Micromachining

2006 ◽  
Vol 526 ◽  
pp. 13-18 ◽  
Author(s):  
H. Perez ◽  
Antonio Vizan Idoipe ◽  
J. Perez ◽  
J. Labarga
Keyword(s):  
Experimental Data ◽  
Cutting Force ◽  
Cutting Forces ◽  
Prediction Models ◽  
Precision Machining ◽  
New Model ◽  
Proposed Model ◽  
On Line ◽  
Machine Control ◽  
Good Agreement

Many investigations have been developed related to precision machining with features in the millimetre scale. In this paper different cutting force models for micromilling are analyzed and compared. A new model based on specific cutting force that also considers run-out errors has been developed. The estimated cutting forces obtained with this model had good agreement with the experimental data. Also, the proposed model allows to be implemented within the machine control for the on-line optimization of the micromilling process.

scholarly journals Forecasting Realized Volatility Using a Nonnegative Semiparametric Model

2019 ◽  
Vol 12 (3) ◽  
pp. 139 ◽  
Author(s):  
Anders Eriksson ◽  
Daniel P. A. Preve ◽  
Jun Yu
Keyword(s):  
Predictive Accuracy ◽  
Estimation Method ◽  
Semiparametric Model ◽  
Error Component ◽  
New Model ◽  
Finite Samples ◽  
Proposed Model ◽  
Forecasting Performance ◽  
Out Of Sample ◽  
Using Data

This paper introduces a parsimonious and yet flexible semiparametric model to forecast financial volatility. The new model extends a related linear nonnegative autoregressive model previously used in the volatility literature by way of a power transformation. It is semiparametric in the sense that the distributional and functional form of its error component is partially unspecified. The statistical properties of the model are discussed and a novel estimation method is proposed. Simulation studies validate the new method and suggest that it works reasonably well in finite samples. The out-of-sample forecasting performance of the proposed model is evaluated against a number of standard models, using data on S&P 500 monthly realized volatilities. Some commonly used loss functions are employed to evaluate the predictive accuracy of the alternative models. It is found that the new model generally generates highly competitive forecasts.

Time-dependent pullout behavior of glass fiber reinforced polymer (GFRP) soil nail in sand

2015 ◽  
Vol 52 (6) ◽  
pp. 671-681 ◽  
Author(s):  
Cheng-Cheng Zhang ◽  
Hong-Hu Zhu ◽  
Qiang Xu ◽  
Bin Shi ◽  
Guo-Xiong Mei
Keyword(s):  
Glass Fiber ◽  
Fiber Reinforced Polymer ◽  
Time Dependent ◽  
Rheological Parameters ◽  
Fiber Reinforced ◽  
Glass Fiber Reinforced Polymer ◽  
Soil Nail ◽  
Reinforced Polymer ◽  
Glass Fiber Reinforced ◽  
Proposed Model

Glass fiber reinforced polymer (GFRP) materials are gaining increasing use in geotechnical engineering applications in recent years. The long-term performance of reinforced geostructures may be influenced by the rheological properties of GFRP soil nails or anchors. However, a clear understanding of this effect is lacking. This work aims to investigate the interaction between GFRP soil nail and sand under pullout conditions considering the time-dependent effect. A time-dependent model was proposed to describe the load–deformation characteristics of a GFRP soil nail during pullout. Laboratory pullout tests were performed using a load-controlled pullout apparatus to verify the effectiveness of the proposed model. Quasi-distributed fiber Bragg grating (FBG) optical fiber sensors were adhered on the pre-grooved GFRP soil nail to capture the variations of axial strain during testing. The test results are presented, interpreted, and discussed. It is shown that there is good agreement between the simulation results and the experimental data under low stress levels. Additionally, the impacts of model parameters on the predicted time-dependent pullout behavior of a GFRP soil nail were examined through parametric studies. The results indicate that the distributions of tensile force and GFRP–sand interfacial shear stress along the nail length are highly time dependent. The creep displacement of a GFRP soil nail is significantly influenced by the rheological parameters of the proposed model.

Flexible Interaction Model for Complex Interactions of Multiple Anesthetics

2006 ◽  
Vol 105 (2) ◽  
pp. 286-296 ◽  
Author(s):  
Matthew Fidler ◽  
Steven E. Kern
Keyword(s):  
Drug Interactions ◽  
Interaction Model ◽  
Data Sets ◽  
Additive Interaction ◽  
New Model ◽  
Complex Interactions ◽  
Anesthetic Drugs ◽  
Proposed Model ◽  
Quantitative Manner ◽  
Using Data

Background Minto et al. (Anesthesiology 2000) described a mathematical approach based on response surface methods for characterizing drug-drug interactions between several intravenous anesthetic drugs. To extend this effort, the authors developed a flexible interaction model based on the general Hill dose-response relation that includes a set of parameters that can be statistically assessed for interaction significance. Methods This new model was developed to identify pharmacologically meaningful interaction-related parameters and address mathematical limitations in previous models. The flexible interaction model and the model of Minto et al. were compared in their assessment of additivity using simulated sample data sets. The flexible interaction model was also compared with the Minto model in describing drug interactions using data from several other clinical studies of propofol, opioids, and benzodiazepines from Short et al. (Anesthesiology 2002) and Kern et al. (Anesthesiology 2004). Results The flexible interaction model was able to accurately classify an additive interaction based on the classic definition proposed by Loewe, with at most an 8% difference between the two surfaces. Also, the proposed model fit the clinical interaction data as well or slightly better than that of Minto et al. Conclusions The new model can accurately classify additive and synergistic drug interactions. It also can classify antagonistic interactions with biologically rational surfaces. This has been a problem for other interaction models in the past. The statistically assessable interaction parameters provide a quantitative manner to assess the interaction significance.

A Robust Asymptotically Based Modeling Approach for Two-Phase Flow in Porous Media

2009 ◽  
Vol 131 (10) ◽  
Author(s):  
M. M. Awad ◽  
S. D. Butt
Keyword(s):  
Porous Media ◽  
Pressure Gradient ◽  
Single Phase ◽  
Present Model ◽  
Flow In Porous Media ◽  
Pressure Gradients ◽  
Two Phase ◽  
New Model ◽  
Proposed Model ◽  
Phase Liquid

A simple semitheoretical method for calculating the two-phase frictional pressure gradient in porous media using asymptotic analysis is presented. The two-phase frictional pressure gradient is expressed in terms of the asymptotic single-phase frictional pressure gradients for liquid and gas flowing alone. In the present model, the two-phase frictional pressure gradient for x≅0 is nearly identical to the single-phase liquid frictional pressure gradient. Also, the two-phase frictional pressure gradient for x≅1 is nearly identical to the single-phase gas frictional pressure gradient. The proposed model can be transformed into either a two-phase frictional multiplier for liquid flowing alone (ϕl2) or a two-phase frictional multiplier for gas flowing alone (ϕg2) as a function of the Lockhart–Martinelli parameter X. The advantage of the new model is that it has only one fitting parameter (p), while the other existing correlations, such as the correlation of Larkins et al., Sato et al., and Goto and Gaspillo, have three constants. Therefore, calibration of the new model to the experimental data is greatly simplified. The new model is able to model the existing multiparameter correlations by fitting the single parameter p. Specifically, p=1/3.25 for the correlation of Midoux et al., p=1/3.25 for the correlation of Rao et al., p=1/3.5 for the Tosun correlation, p=1/3.25 for the correlation of Larkins et al., p=1/3.75 for the correlation of Sato et al., and p=1/3.5 for the Goto and Gaspillo correlation.

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