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The first model utilizes Genetic Algorithms (GA) while the second model utilizes Approximate Dynamic Programming (ADP).
The model utilizes electrochemical, metallurgical, and physical inputs.
The model utilizes the concept of irreversibility of crack emitted dislocation glide.
The proposed model utilizes site-dependent failure probabilities and random link disruptions.
The model utilizes empirically-determined coefficients, easily obtainable from product data sheets.
The 3D model utilizes a finite differencing (FD) heat transfer algorithm, complemented with experimental boundary conditions.
This model utilizes the k ɛ turbulence model to solve the flow equations.
The optimization model utilizes the 'Non-dominated Sorting Genetic Algorithm (NSGA-II)'.
The model utilizes the concept of planar type heat exchanger with mass transport through the membrane.
This mouse model utilizes an imperfect Cre-lox system together with a cerebellar GC-specific promoter31,32, resulting in a loss of GC output in an estimated ~75% of the GC population19.
The fatigue model utilizes standard S-N fatigue data for a lamina along with the critical energy release rate values.
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