scholarly journals CREEP COMPLIANCE OF VISCOELASTIC MATERIALS AT CONSTANT TEPERATURE

2021 ◽  
Vol 10 (3) ◽  
pp. 93-111
Author(s):  
Abdulamir S. Resen ◽  
C. P. Buckley
Keyword(s):  
Stress Tensor ◽  
Free Volume ◽  
Temperature Region ◽  
Creep Compliance ◽  
Time Dependent ◽  
Viscoelastic Materials ◽  
Creep And Recovery ◽  
The Difference ◽  
Stress Dependent ◽  
Shear Compliance

Experiments were carried out to investigate the separate roles of the hydrostatic and deviatoric components of stress tensor (using the first and the second invariant  and The results were expressed in term of stress dependent shear compliance  in the time temperature region of the tests (up to seconds at  of the Relaxation). was found to increase in magnitude with increasing both hydrostatic and deviatoric  components of stress.  caused a shift in the magnitude of  and  caused an increase in  with time. The difference between the shear compliance in creep and recovery was found to decrease with  and increase with . All the different effects mentioned above could be rationalized by the idea of the time dependent free volume. If the free volume increases with time by increasing  this could explain the difference in the effect of   and on  and explain why creep is less than recovery

The Equation of State and the Temperature, Pressure, and Shear Dependence of Viscosity for a Highly Viscous Reference Liquid, Dipentaerythritol Hexaisononanoate

2016 ◽  
Vol 139 (1) ◽  
Author(s):  
Scott Bair ◽  
Tsuyoshi Yamaguchi
Keyword(s):  
Molecular Weight ◽  
Shear Stress ◽  
Equation Of State ◽  
High Molecular Weight ◽  
Free Volume ◽  
Newtonian Limit ◽  
Scaling Models ◽  
The Difference ◽  
Better Than ◽  
Low Shear

Measurements are reported for dipentaerythritol hexaisononanoate (DiPEiC9) of pressure–volume–temperature (pVT) response to pressures to 400 MPa and temperatures to 100 °C, and of viscosity at pressures to 700 MPa and temperatures to 90 °C and shear stress to 18 MPa. These data complement the low-shear viscosities published by Harris to pressures to 200 MPa and the compressions by Fandiño et al. to 70 MPa. The improved Yasutomi correlation reproduces all viscosity measurements with accuracy better than the Doolittle free volume and the Bair and Casalini thermodynamic scaling models which require an equation of state (EoS). The interaction parameter for thermodynamic scaling, γ = 3.6, is less than that reported by Harris (γ = 4.2) and the difference is primarily in the choice of EoS. The shear stress at the Newtonian limit, about 6 MPa, is exceptionally large given the high molecular weight of DiPEiC9. The large Newtonian limit is also seen in the oscillatory shear response.

scholarly journals Evolution Equation and Transport Coefficients of Swarms in Initial Relaxation Processes

1987 ◽  
Vol 40 (3) ◽  
pp. 367 ◽  
Author(s):  
Keiichi Kondo
Keyword(s):  
Evolution Equation ◽  
Transport Coefficients ◽  
Collision Operator ◽  
Operator Method ◽  
Time Dependent ◽  
Relaxation Processes ◽  
Projection Operator Method ◽  
Model Collision ◽  
The Difference ◽  
Dependent Transport

The problem of a swarm approaching the hydrodynamic regime is studied by using the projection operator method. An evolution equation for the density and the related time-dependent transport coefficient are derived. The effects of the initial condition on the transport characteristics of a swarm are separated from the intrinsic evolution of the swarms, and the difference from the continuity equation with time-dependent transport coefficients introduced by Tagashira et al. (1977, 1978) is discussed. To illustrate this method, calculations on the relaxation model collision operator have been carried out. The results are found to agree with the analysis by Robson (1975).

scholarly journals Time-dependent prediction degredation assessment of neural-networks-based TEC forecasting models

2003 ◽  
Vol 10 (6) ◽  
pp. 585-587 ◽  
Author(s):  
Th. D. Xenos ◽  
S. S. Kouris ◽  
A. Casimiro
Keyword(s):  
Neural Networks ◽  
Faraday Rotation ◽  
Prediction Error ◽  
Prediction Accuracy ◽  
Time Span ◽  
Time Dependent ◽  
Forecasting Models ◽  
Error Margin ◽  
The Difference ◽  
Tec Variability

Abstract. An estimation of the difference in TEC prediction accuracy achieved when the prediction varies from 1 h to 7 days in advance is described using classical neural networks. Hourly-daily Faraday-rotation derived TEC measurements from Florence are used. It is shown that the prediction accuracy for the examined dataset, though degrading when time span increases, is always high. In fact, when a relative prediction error margin of ± 10% is considered, the population percentage included therein is almost always well above the 55%. It is found that the results are highly dependent on season and the dataset wealth, whereas they highly depend on the foF2 - TEC variability difference and on hysteresis-like effect between these two ionospheric characteristics.

Time-dependent mechanical response of paper during web-fed high-speed inkjet printing

2019 ◽  
Vol 34 (1) ◽  
pp. 107-116
Author(s):  
Jussi Lahti ◽  
Jarmo Kouko ◽  
Ulrich Hirn
Keyword(s):  
Inkjet Printing ◽  
High Speed ◽  
Mechanical Response ◽  
Creep Compliance ◽  
Time Dependent ◽  
Print Quality ◽  
Wetting And Drying ◽  
Process Step ◽  
Tensile Tester ◽  
The Web

Abstract The influence of wetting and drying during high-speed inkjet (HSI) printing on the time-dependent mechanical behavior of commercial HSI papers was investigated using a custom-built C-Impact tensile tester. In HSI printing the water based ink solvent penetrates into the paper while the colorants adhere onto the surface. We found that water strongly affected paper stiffness and strength already 0.1 s after wetting. Creep compliance and paper strain at a typical HSI printing input tension of 180 N/m are varying strongly during the different process steps of HSI printing. In order to achieve a good color registration and print quality, we thus recommend that the web tension should be dynamically controlled in each process step to prevent straining after wetting or shrinkage during drying.

TIME-DEPENDENT DENSITY FUNCTIONAL STUDY OF MULTIELECTRON TRANSFER IN Cq+–Na4 COLLISIONS

2010 ◽  
Vol 24 (24) ◽  
pp. 4811-4820
Author(s):  
Y. P. ZHANG ◽  
F. S. ZHANG ◽  
Y. GAO ◽  
H. W. CHANG ◽  
G. Q. XIAO
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Local Density ◽  
Time Dependent ◽  
Functional Study ◽  
Density Approximation ◽  
Functional Theory ◽  
The Difference ◽  
Multielectron Transfer ◽  
Dependent Density

The process of multielectron transfer from a Na 4 cluster induced by highly charged C 6+, C 4+, C 2+ and C + ions is studied using the method of time-dependent density functional theory within the local density approximation combined with the use of pseudopotential. The evolution of dipole moment changes and emitted electrons in Na 4 is obtained and the time-dependent probabilities with various charges are deduced. It is shown that the Na 4 cluster is strongly ionized by C 6+ and that the number of emitted electrons per atom of Na 4 is larger than that of Na 2 under the same condition. One can find that the detailed information of the emitted electrons from Na 4 is different from the same from Na 2, which is possibly related to the difference in structure between the two clusters.

Characterizing viscoelastic materials using the free volume microprobe

1989 ◽  
Vol 86 (S1) ◽  
pp. S52-S52
Author(s):  
Bret A. Mayo ◽  
James P. Pfau ◽  
Duryodhan Mangaraj
Keyword(s):  
Free Volume ◽  
Viscoelastic Materials

scholarly journals Theoretical analysis of mixing in liquid clouds – Part IV: DSD evolution and mixing diagrams

2018 ◽  
Vol 18 (5) ◽  
pp. 3659-3676 ◽  
Author(s):  
Mark Pinsky ◽  
Alexander Khain
Keyword(s):  
Relative Humidity ◽  
Droplet Size Distribution ◽  
Droplet Evaporation ◽  
Cloud Fraction ◽  
Time Dependent ◽  
Droplet Concentration ◽  
The Mean ◽  
The Difference ◽  
Mixing Diagrams ◽  
Dependent Processes

Abstract. Evolution of droplet size distribution (DSD) due to mixing between cloudy and dry volumes is investigated for different values of the cloud fraction and for different initial DSD shapes. The analysis is performed using a diffusion–evaporation model which describes time-dependent processes of turbulent diffusion and droplet evaporation within a mixing volume. Time evolution of the DSD characteristics such as droplet concentration, LWC and mean volume radii is analyzed. The mixing diagrams are plotted for the final mixing stages. It is shown that the difference between the mixing diagrams for homogeneous and inhomogeneous mixing is insignificant and decreases with an increase in the DSD width. The dependencies of the normalized cube of the mean volume radius on the cloud fraction were compared with those on normalized droplet concentration and found to be quite different. If the normalized droplet concentration is used, mixing diagrams do not show any significant dependence on relative humidity in the dry volume. The main conclusion of the study is that traditional mixing diagrams cannot serve as a reliable tool for analysis of mixing type.

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