2H NMR and Simulation Studies of Chain Segment Orientation in PDMS Bimodal Networks

2010 ◽  
Vol 43 (17) ◽  
pp. 7173-7184 ◽  
Author(s):  
Bernardo M. Aguilera-Mercado ◽  
Geoffrey D. Genesky ◽  
T. Michael Duncan ◽  
Claude Cohen ◽  
Fernando A. Escobedo
Keyword(s):  
2H Nmr ◽  
Simulation Studies ◽  
Chain Segment ◽  
Bimodal Networks ◽  
Segment Orientation

Polymer chain segment orientation during stress relaxation

1986 ◽  
Vol 24 (1) ◽  
pp. 203-208 ◽  
Author(s):  
B. D. Lawrey ◽  
R. K. Prud'Homme ◽  
J. T. Koberstein
Keyword(s):  
Stress Relaxation ◽  
Polymer Chain ◽  
Chain Segment ◽  
Segment Orientation

Nature of the Cohesional Strength of Synthetic Cis-Polyisoprene SKI-3 and Carbon Black Compounds Based on It

1973 ◽  
Vol 46 (5) ◽  
pp. 1234-1238 ◽  
Author(s):  
V. A. Grechanovskii ◽  
L. S. Ivanova ◽  
I. Ya Poddubnyi
Keyword(s):  
Molecular Weight ◽  
Carbon Black ◽  
High Molecular Weight ◽  
Chain Segment ◽  
Segment Orientation

Abstract SKI-3 gum rubbers containing tight gel have high cohesional strength (up to 12 kg/cm2) at the same time that sol fractions of these rubbers and also of NR have low cohesional strength (˜2 kg/cm2). The loss by black compounds based on SKI-3 of cohesional strength is explained by the breakdown during milling of networks of physical entanglements existing in these rubbers. For the production of carbon black compounds based on crystallizing elastomers with high cohesional strength, the presence of sufficiently stable networks able to insure the initial chain segment orientation during extension and a high molecular weight of the macromolecule are necessary.

Benefits from Computerized Adaptive Testing as Seen in Simulation Studies

1999 ◽  
Vol 15 (2) ◽  
pp. 91-98 ◽  
Author(s):  
Lutz F. Hornke
Keyword(s):  
Measurement Error ◽  
Computerized Adaptive Testing ◽  
Test Procedure ◽  
Adaptive Testing ◽  
Parameter Estimates ◽  
Simulation Studies ◽  
Computerized Adaptive Test ◽  
Item Banks ◽  
Item Parameters ◽  
General Reliability

Summary: Item parameters for several hundreds of items were estimated based on empirical data from several thousands of subjects. The logistic one-parameter (1PL) and two-parameter (2PL) model estimates were evaluated. However, model fit showed that only a subset of items complied sufficiently, so that the remaining ones were assembled in well-fitting item banks. In several simulation studies 5000 simulated responses were generated in accordance with a computerized adaptive test procedure along with person parameters. A general reliability of .80 or a standard error of measurement of .44 was used as a stopping rule to end CAT testing. We also recorded how often each item was used by all simulees. Person-parameter estimates based on CAT correlated higher than .90 with true values simulated. For all 1PL fitting item banks most simulees used more than 20 items but less than 30 items to reach the pre-set level of measurement error. However, testing based on item banks that complied to the 2PL revealed that, on average, only 10 items were sufficient to end testing at the same measurement error level. Both clearly demonstrate the precision and economy of computerized adaptive testing. Empirical evaluations from everyday uses will show whether these trends will hold up in practice. If so, CAT will become possible and reasonable with some 150 well-calibrated 2PL items.

Anisotropic 2H-NMR spin-lattice relaxation in oriented bilayers of DMPC and DMPC + cholesterol

1992 ◽  
Vol 89 ◽  
pp. 237-242 ◽  
Author(s):  
MA Krajewski-Bertrand ◽  
Y Nakatani ◽  
G Ourisson ◽  
EJ Dufourc ◽  
A Milon
Keyword(s):  
Lattice Relaxation ◽  
Spin Lattice Relaxation ◽  
2H Nmr ◽  
Spin Lattice

Adaptive Control Scheme for Coupled Tank Process

2018 ◽  
pp. 89-95
Author(s):  
Vinodhini M.
Keyword(s):  
Adaptive Control ◽  
Nonlinear Behaviour ◽  
Simulation Studies ◽  
Input Output ◽  
Control Scheme ◽  
Direct Model ◽  
Multivariable Process ◽  
Model Reference Adaptive ◽  
Siso System ◽  
Adaptive Control Scheme

The objective of this paper is to develop a Direct Model Reference Adaptive Control (DMRAC) algorithm for a MIMO process by extending the MIT rule adopted for a SISO system. The controller thus developed is implemented on Laboratory interacting coupled tank process through simulation. This can be regarded as the relevant process control in petrol and chemical industries. These industries involve controlling the liquid level and the flow rate in the presence of nonlinearity and disturbance which justifies the use of adaptive techniques such as DMRAC control scheme. For this purpose, mathematical models are obtained for each of the input-output combinations using white box approach and the respective controllers are developed. A detailed analysis on the performance of the chosen process with these controllers is carried out. Simulation studies reveal the effectiveness of proposed controller for multivariable process that exhibits nonlinear behaviour.

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