Causal Closure, Mechanism, and Rational Inference

2001 ◽  
Vol 3 (2) ◽  
pp. 473-483
Author(s):  
Victor E. Reppert ◽  
Keyword(s):  
Closure Mechanism ◽  
Causal Closure ◽  
Rational Inference

Application of the Strip Yield Model to Crack Growth Predictions for Structural Steel

2010 ◽  
Vol 57 (1) ◽  
pp. 1-20
Author(s):  
Małgorzata Skorupa ◽  
Tomasz Machniewicz
Keyword(s):  
Structural Steel ◽  
Crack Growth ◽  
Model Calibration ◽  
Load History ◽  
Yield Model ◽  
Variable Amplitude Loading ◽  
Variable Amplitude ◽  
Constraint Factors ◽  
Strip Yield Model ◽  
Closure Mechanism

Application of the Strip Yield Model to Crack Growth Predictions for Structural SteelA strip yield model implementation by the present authors is applied to predict fatigue crack growth observed in structural steel specimens under various constant and variable amplitude loading conditions. Attention is paid to the model calibration using the constraint factors in view of the dependence of both the crack closure mechanism and the material stress-strain response on the load history. Prediction capabilities of the model are considered in the context of the incompatibility between the crack growth resistance for constant and variable amplitude loading.

Rational Inference Patterns

2019 ◽  
pp. 405-417
Author(s):  
Lars-Phillip Spiegel ◽  
Gabriele Kern-Isberner ◽  
Marco Ragni
Keyword(s):  
Rational Inference

Reference-dependent risk sensitivity as rational inference.

2015 ◽  
Vol 122 (3) ◽  
pp. 461-484 ◽  
Author(s):  
Jerker C. Denrell
Keyword(s):  
Risk Sensitivity ◽  
Rational Inference

The Bayesian Transition Theory

2020 ◽  
pp. 101-154
Author(s):  
Scott Sturgeon
Keyword(s):  
Contact Point ◽  
Modus Ponens ◽  
Transition Theory ◽  
Jeffrey’S Rule ◽  
Natural Conception ◽  
Rational Inference ◽  
Conditional Credence ◽  
The Way

Chapter 4 discusses the Bayesian transition theory. The distinction is drawn between dynamics and kinematics, and it’s argued that the theory of rational inference belongs to the former rather than the latter. It’s shown that Jeffrey’s rule is thus not a rule of rational inference. Credence lent to a conditional is explained and compared to conditional credence. Two problems for Bayesian kinematics then come into focus: conditional credence is never changing in the model, nor is it ever the contact-point of rational shift-in-view. A natural conception of conditional commitment is then put forward and used to solve both these problems. Along the way it’s argued that modus-ponens-style arguments do not function in thought as logical syllogisms, since modus-ponens-style arguments specify obligatory paths forward in thought.

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