scholarly journals Predictions for the northern coast of the shear rheology map: XXLAOS

2016 ◽  
Vol 798 ◽  
pp. 1-4 ◽  
Author(s):  
Randy H. Ewoldt
Keyword(s):  
Model Selection ◽  
Constitutive Model ◽  
Complex Fluids ◽  
Rotational Diffusion ◽  
Northern Coast ◽  
Large Amplitude Oscillatory Shear ◽  
New Paradigm ◽  
Rheological Characterization ◽  
Rigid Particles ◽  
Brownian Rotational Diffusion

A new paradigm of rheological characterization, oscillatory simple shear with infinite forcing amplitudes, is introduced by Khair (J. Fluid Mech., vol. 791, 2016, R5). This pushes the technique of large-amplitude oscillatory shear (LAOS) to have two extremely large amplitudes (both strain-rate and strain), which we might call XXLAOS. Model-specific analytical predictions are derived for a suspension of nearly spherical rigid particles subject to Brownian rotational diffusion. The work illuminates a new regime of rheological characterization that may serve as a distinct proving ground for constitutive model selection and for probing the flow physics of rheologically complex fluids.

The Problem of Underdetermination in Model Selection

2018 ◽  
Vol 48 (1) ◽  
pp. 52-87
Author(s):  
Michael Schultz
Keyword(s):  
Lower Bound ◽  
Model Selection ◽  
Philosophy Of Science ◽  
Model Fit ◽  
New Paradigm ◽  
Conventional Model ◽  
Trade Off ◽  
Nested Models ◽  
Network Composition ◽  
The Relationship

Conventional model selection evaluates models on their ability to represent data accurately, ignoring their dependence on theoretical and methodological assumptions. Drawing on the concept of underdetermination from the philosophy of science, the author argues that uncritical use of methodological assumptions can pose a problem for effective inference. By ignoring the plausibility of assumptions, existing techniques select models that are poor representations of theory and are thus suboptimal for inference. To address this problem, the author proposes a new paradigm for inference-oriented model selection that evaluates models on the basis of a trade-off between model fit and model plausibility. By comparing the fits of sequentially nested models, it is possible to derive an empirical lower bound for the subjective plausibility of assumptions. To demonstrate the effectiveness of this approach, the method is applied to models of the relationship between cultural tastes and network composition.

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