Extremal Structures with Embedded Pre-Failure Indicators

TL;DR

This paper introduces a novel multiscale topology optimization method to embed pre-failure indicators in structures, enabling early warning of critical buckling loads without compromising overall integrity.

Contribution

It presents a new approach to design structures with built-in failure indicators using multiscale topology optimization, bridging the gap between theory and practical safety applications.

Findings

Experimental results confirm the correlation between indicators and load conditions.

Structures successfully signal approaching failure without losing overall strength.

The method enhances safety by integrating early-warning features into structural design.

Abstract

Preemptive identification of potential failure under loading of engineering structures is a critical challenge. Our study presents an innovative approach to built-in pre-failure indicators within multiscale structural designs utilizing the design freedom of topology optimization. The indicators are engineered to visibly signal load conditions approaching the global critical buckling load. By showing non-critical local buckling when activated, the indicators provide early warning without compromising the overall structural integrity of the design. This proactive safety feature enhances design reliability. With multiscale analysis, macroscale stresses are related to microscale buckling stability. This relationship is applied through tailored stress constraints to prevent local buckling in general while deliberately triggering it at predefined locations under specific load conditions. Experimental testing of 3D-printed designs confirms a strong correlation with numerical simulations. This not only demonstrates the feasibility of creating structures that can signal the need for load reduction or maintenance but also significantly narrows the gap between theoretical optimization models and their practical application. This research contributes to the design of safer structures by introducing built-in early-warning failure systems.