Design and Optimization of Gradient Foam Core Sandwich Structures With Superior Microwave Absorption Performance
Source abstract
Abstract
ABSTRACT With the increasing demand for omnidirectional wideband radar stealth performance in fifth‐generation fighter jets, foam sandwich structures used in aerospace must possess excellent microwave absorption (MA) capabilities. In this study, 20 types of rigid closed‐cell microwave‐absorbing composite foams were prepared using a microsphere foaming method, with short carbon fibers (SCF), multi‐walled carbon nanotubes (MWCNT), and carbonyl iron powder (CIP) as absorbing agents and epoxy resin (EP) as the matrix. The effects of absorbing agents' types and contents on the microwave absorption performance of the foams in the 2–18 GHz range were analyzed. Based on the experimental data, a data enhancement method was employed to expand the material database of foams. Subsequently, a multi‐objective optimization of gradient foam sandwich structures (GFSS) was conducted using a genetic algorithm. The effective absorption bandwidth (EAB) of the sandwich structures ranged from 13.9 to 16.0 GHz, the minimum reflection loss (RL min ) reached −94.4 dB, and the ratio of EAB to density ( η ) was 34.8–50.2 GHz g −1 cm 3 . Additionally, the gradient foam with a thickness of 20 mm exhibited an EAB of 16.0 GHz and an η value of 60.1 GHz g −1 cm 3 . The effectiveness of the optimization results was validated through experimental measurements. A finite element analysis (FEA) model was established to investigate the broadband MA mechanisms of the GFSS. Finally, the bending performance of the GFSS was evaluated by conducting three‐point bending tests. This study provides an effective approach for the design and fabrication of lightweight GFSS with broadband microwave absorption functionality.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electromagnetic wave absorption materials · Advanced Antenna and Metasurface Technologies · Antenna Design and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering Northwestern Polytechnical University Xi'an People's Republic of China
Shaanxi Engineering Research Center for Digital Manufacturing Technology Xi'an China
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