Results 211 to 220 of about 1,723,588 (348)

Bioinspired Design of Isotropic Lattices with Tunable and Controllable Anisotropy

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces nested isotropic lattices, integrating architectural elements like nesting orders and orientations inspired by bioarchitectures. The design enables tunable anisotropy across nine mono‐nest and twenty multi‐nest lattices with 252 parametric variations, demonstrating transitions from shear‐ to tensile‐compression‐dominant behaviors ...
Ramalingaiah Boda   +2 more
wiley   +1 more source

Revealing the γ′ and γ″ Phase Fractions of Additively Manufactured and Differently Heat‐Treated Nickel‐Base Superalloy IN718 by Atom Probe Tomography and Their Impact on Mechanical Properties

open access: yesAdvanced Engineering Materials, EarlyView.
Additive manufacturing is a promising route for the production of Ni‐base superalloys for turbine applications, such as Inconel 718. Nonetheless, it induces various changes in the microstructure and performance of these materials. One such change is the incidence of the δ‐Ni3Nb phase, whose impact on microstructure, aging precipitate fractions, and ...
Guilherme Maziero Volpato   +8 more
wiley   +1 more source

Beyond Global Mechanical Properties: Bioinspired Triply‐Periodic Minimal Surface Cellular Solids for Efficient Mechanical Design and Optimization

open access: yesAdvanced Engineering Materials, EarlyView.
Using novel probe‐based metrics, this study evaluates lattice structures on criteria critical to cellular solid optimization. Triply‐periodic minimal surface (TPMS) lattices outperform other lattices, offering more predictable mechanical behavior in complex design spaces and, as a result, higher performance in optimized models.
Firas Breish   +2 more
wiley   +1 more source

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

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