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This paper explores Bayesian emulators as surrogates for expensive finite element models in structural dynamics.
This paper presents a survey on the development and use of Artificial Neural Network (ANN) models in structural reliability analysis.
This paper proposes an innovative algorithm to facilitate quantitative measures to evaluate coupled partial models in structural engineering.
The linear elastic plastic behaviour of structural timber loaded perpendicular to grain has been a problematic issue for decades which is reflected in the differences between the prediction models in structural design codes over the world.
This paper provides a critical review of the commonly used computational fracture models in structural engineering applications including: (a) Rice and Tracey void growth model; (b) stress modified critical strain criterion; (c) Gurson-Tvergaard-Needleman model and (d) weakly coupled ductile fracture model.
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For the sake of depicting the capabilities of the presented numerical model in structural verifications, the study is focused on the patch loading field, a structurally complex phenomenon.
As a second major obstacle, we identified the use of discrete FEM modeling in structural engineering.
As a consequence, restraint to shrinkage is often poorly modelled in structural design.
The use of advanced analytical and numerical modelling in structural engineering has increased rapidly in recent years.
Coupled structures under random excitation are modelled as a quasi-integrable Hamiltonian system of multi-degree-of-freedom and the reduced-order model in structural mode space is formulated.
Reciprocal influences of body weight and other factors over time will be modeled in structural equation modeling using nonrecursive models [ 43].
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