Designing Symmetric Gradient Honeycomb Structures with Carbon‑Coated Iron‑Based Composites for High‑Efficiency Microwave Absorption

The impedance matching of absorbers is a vital factor affecting their microwave absorption(MA)properties.In this work,we controllably synthesized Material of Institute Lavoisier 88C(MIL-88C)with varying aspect ratios(AR)as a precursor by regulating oil bath conditions,followed by one-step thermal decomposition to obtain carbon-coated iron-based composites.Modifying the precursor MIL-88C(Fe)preparation conditions,such as the molar ratio between metal ions and organic ligands(M/O),oil bath temperature,and oil bath time,influenced the phases,graphitization degree,and AR of the derivatives,enabling low filler loading,achieving well-matched impedance,and ensuring outstanding MA properties.The MOF-derivatives 2(MD_(2))/polyvinylidene Difluoride(PVDF),MD_(3)/PVDF,and MD4/PVDF absorbers all exhibited excellent MA properties with optimal filler loadings below 20 wt%and as low as 5 wt%.The MD_(2)/PVDF(5 wt%)achieved a maximum effective absorption bandwidth(EAB)of 5.52 GHz(1.90 mm).The MD_(3)/PVDF(10 wt%)possessed a minimum reflection loss(RL_(min))value of−67.4 at 12.56 GHz(2.13 mm).A symmetric gradient honeycomb structure(SGHS)was constructed utilizing the high-frequency structure simulator(HFSS)to further extend the EAB,achieving an EAB of 14.6 GHz and a RL_(min) of−59.0 dB.This research offers a viable inspiration to creating structures or materials with high-efficiency MA properties.

On-road vehicle verification based on VS-HOG and ELM

A solution is proposed for the real-time vehicle verification which is an important problem for numerous on- road vehicle applications. First, based on the vertical symmetry characteristics of vehicle images, a vertical symmetrical histograms of oriented gradients （VS-HOG） descriptor is proposed for extracting the image features. In the classification stage, an extreme learning machine （ELM） is used to improve the real-time performance. Experimental data demonstrate that, compared with other classical methods, the vehicle verification algorithm based on VS-HOG and ELM achieves a better trade-off between cost and performance. The computational cost is reduced by using the algorithm, while keeping the performance loss as low as possible. Furthermore, experimental results further show that the proposed vehicle verification method is suitable for on-road vehicle applications due to its better performance both in efficiency and accuracy.

Application of SSOR-PCGM with improved iteration format in FEM simulation of massive concrete

In this study, for the purpose of improving the efficiency and accuracy of numerical simulation of massive concrete, the symmetric successive over relaxation-preconditioned conjugate gradient method （SSOR-PCGM） with an improved iteration format was derived and applied to solution of large sparse symmetric positive definite linear equations in the computational process of the finite element analysis. A three-dimensional simulation program for massive concrete was developed based on SSOR-PCGM with an improved iteration format. Then, the programs based on the direct method and SSOR-PCGM with an improved iteration format were used for computation of the Guandi roller compacted concrete （RCC） gravity dam and an elastic cube under free expansion. The comparison and analysis of the computational results show that SSOR-PCGM with the improved iteration format occupies much less physical memory and can solve larger-scale problems with much less computing time and flexible control of accuracy.