Mechanics of Solids, Journal Year: 2024, Volume and Issue: 59(8), P. 4085 - 4099
Published: Dec. 1, 2024
Language: Английский
Mechanics of Solids, Journal Year: 2024, Volume and Issue: 59(8), P. 4085 - 4099
Published: Dec. 1, 2024
Language: Английский
Archives of Civil and Mechanical Engineering, Journal Year: 2025, Volume and Issue: 25(2)
Published: Feb. 20, 2025
Language: Английский
Citations
0Advanced Materials Technologies, Journal Year: 2025, Volume and Issue: unknown
Published: March 11, 2025
Abstract The imperative for lattice structures to excel in both sound absorption and mechanical properties arises from the increasing demand materials that offer multifunctional solutions. However, relationship between these two properties, on how design both, remains uncertain. Here, a perspective is presented interplay structures, focusing their mechanisms, limitations, recommendations. First, new term acoustical geometry introduced describe features influencing structures. Identified resonance's structural requirements, geometries are derived actual lattices’ features. Using this, links drawn. It found truss triply periodic minimal surface lattices lack freedom needed simultaneously customize as inherently tied same structure. For inherent capability of introducing pores strategically, this less intertwined plate lattices. Therefore, it advocated development hybrid with decouple paving way meta enable customizable multifunctionality.
Language: Английский
Citations
0Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113801 - 113801
Published: March 1, 2025
Language: Английский
Citations
0Applied Acoustics, Journal Year: 2025, Volume and Issue: 235, P. 110681 - 110681
Published: March 20, 2025
Language: Английский
Citations
0Materials & Design, Journal Year: 2025, Volume and Issue: unknown, P. 113987 - 113987
Published: April 1, 2025
Language: Английский
Citations
0Materials, Journal Year: 2024, Volume and Issue: 17(17), P. 4222 - 4222
Published: Aug. 27, 2024
The yield strength and Young’s modulus of lattice structures are essential mechanical parameters that influence the utilization materials in aerospace medical fields. Currently, accurately determining often requires conduction a large number experiments for prediction validation purposes. To save time effort to predict material modulus, based on existing experimental data, finite element analysis is employed expand dataset. An artificial neural network algorithm then used establish relationship model between topology structure (the strength), which analyzed verified. Gibson–Ashby indicates different can be classified into two main deformation forms. obtain an deployed BCC-FCC structures, further optimized validated. Concurrently, disparate gives rise certain discrete form their dominant deformation, consequently affects prediction. In conclusion, using networks feasible approach contribute development
Language: Английский
Citations
1Mechanics of Solids, Journal Year: 2024, Volume and Issue: 59(8), P. 4085 - 4099
Published: Dec. 1, 2024
Language: Английский
Citations
0