The challenge of lattice structures: balancing lightness and strength

In recent years, engineering has undergone a radical shift in the design of materials and mechanical components, thanks to the introduction of lattice structures. But what exactly are they? We can imagine them as three-dimensional grids made up of a dense network of thin struts and nodes, repeated in regular cells, which makes them both lightweight and strong. Nature offers us models to draw inspiration from: from bone sponges to sea urchin shells, structures optimized for lightness and strength are everywhere.

Today, thanks to 3D printing, we can reproduce and control these geometries at an industrial scale. Lattice structures are being applied in strategic sectors—from aerospace to biomedical—allowing components to be lightened, mechanical properties to be optimized, and even improving the biological interaction of medical implants, such as bone prostheses.

However, a key challenge still limits their widespread adoption: the difficulty in accurately predicting the mechanical behavior of such complex structures. Their intricate geometries make traditional simulation methods either unreliable or extremely costly, both in terms of computation time and accuracy.

In this project, the study was approached using three different simulation strategies, each designed to effectively balance precision and computational cost.

First approach: numerical homogenization

This technique models the intricate geometry of a lattice structure using an equivalent material that replicates its average elastic behavior. The main advantage is the drastic reduction in the number of elements to be simulated, and therefore the simulation time. To validate this methodology, a study was conducted on a hip prosthesis, selecting the optimal lattice configurations through experimental tests on 3D-printed specimens. The analysis confirmed that, despite some limitations, homogenization provides reliable estimates of elastic properties, making it an effective choice in the early stages of design.

Second approach: simplified one-dimensional models

Since lattice structures are made up of thin struts, their behavior can be represented using beam models, which are far less computationally demanding. Two main applications were explored:

• Fatigue life optimization: The surface quality of 3D-printed components is strongly influenced by the printing orientation, which directly affects their fatigue resistance. An orientation optimization algorithm was developed, reducing critical points prone to early failure.
  
• Correction of elastic properties: Beam models tend to underestimate the stiffness of flexure-dominated structures. To correct this discrepancy, compensation factors were introduced, thereby improving the accuracy of simulations without compromising efficiency. 

Third approach: detailed models based on CT Scans

To obtain highly accurate predictions of fatigue life, the actual geometry of the specimens was reconstructed using CT scans. This made it possible to capture microscopic surface details that critically influence crack initiation. However, simulating such detailed models using traditional solid elements would entail very high computational costs. To mitigate this issue, the Finite Cell Method was used—an innovative technique that enables the simulation of complex geometries while maintaining high precision and manageable computation times. The numerical results obtained were in excellent agreement with experimental predictions, making this method promising for advanced applications.

Toward more efficient design

The results of this research demonstrate that it is possible to reliably and efficiently simulate the mechanical behavior of lattice structures by selecting the most appropriate approach based on design requirements.
Lattice structures thus represent a more concrete and sustainable alternative for many industrial applications, from biomedical to aerospace.