Inspired by the evolutionary optimization of biological load-bearing systems, honeycomb structures are highly valued in applications involving impact protection and lightweight load-bearing due to their outstanding mechanical properties. This study introduces an interesting honeycomb structure known as the hybrid topological cellular honeycomb structure (HTCHS), which integrates four distinctive topological cells. To effectively fabricate HTCHS samples, the research utilized a fused deposition modeling (FDM) process, employing polyethylene terephthalate glycol-modified (PETG) as the matrix material, successfully producing the HTCHS samples. A finite element simulation model for the HTCHS is created using LS-DYNA software(LS-DYNA R11.1.0 software), and its accuracy is confirmed through a comparative analysis of experimental and simulation results. The influence of the topological cell parameters (T₁ to T₄) on compressive energy absorption, specific energy absorption, and peak crushing force through parametric modeling is investigated. The mechanical properties of honeycomb structures vary depending on the cell parameters at different positions, and monotonically increasing the design parameters does not improve the energy absorption capacity of the HTCHS. To enhance the mechanical performance of the HTCHS, the initial periodic cell configurations are transformed into non-periodic designs. A discrete optimization design framework for local parameters of the HTCHS is established, integrating cell coding with the MOPSO algorithm. The feasibility of the optimization results is validated through experimental data, demonstrating that this study offers an effective technical solution for developing a novel generation of cellular honeycomb structures with customizable mechanical properties.

This study proposes an arc-circular lightweight honeycomb structure. Three different configurations of honeycomb specimens, namely arched honeycombs (AHs), arc-circular honeycombs with a first-order hierarchical configuration (ACH-1), and arc-circular honeycombs with a second-order hierarchical configuration (ACH-2), are prepared using metal additive manufacturing technology, and quasi-static compression tests are conducted. The results show that all configurations exhibit significant multi-stage load responses, with the ACH-2 configuration, which incorporates smaller sub-cells, demonstrating higher compressive stress and energy absorption potential. The specific energy absorption (SEA) of ACH-2 is enhanced by 210% compared to the baseline AH. The effectiveness of the finite element analysis is validated against experimental results. Further parametric analysis of the wall thickness parameters, cell number, and macroscopic dimensions of ACH-2 reveals significant variations in how wall thickness at different local locations affects the mechanical properties. Additionally, although increasing the macroscopic dimension significantly enhances the energy absorption capacity, the effect of increasing the number of cells on the overall energy absorption performance at the same relative density is limited. Finally, a reverse design framework for ACH-2 with multi-stage plateau stress is established. The effectiveness of this performance design framework is validated through experiments, providing a feasible technical approach for the design of honeycomb structures with multi-stage plateau stress characteristics.

Forestry helicopter spraying requires fuel-efficient allocation of coverage tasks to successive sorties. Coverage-path generation alone does not resolve this allocation under coupled pesticide depletion and load-dependent fuel consumption. We formulate a Multi-Sortie Routing Problem with Non-synchronous Dual Resources (MSRP-NDR) and develop Sortie-Consolidation Hybrid Adaptive Large Neighborhood Search (SC-HALNS) to minimize modeled fuel consumption under pesticide-capacity and fuel constraints. For fixed coverage paths generated by convex decomposition and the Vector Modeling Method, the framework combines adaptive destroy-and-repair search and randomized variable neighborhood descent, supplemented by whole-sortie consolidation. Only merges that preserve resource feasibility and reduce total modeled fuel consumption are accepted. Six GIS-derived forest instances with 10–102 tasks were evaluated using 20 runs per stochastic algorithm and a nominal 100 s search budget. Relative to the aviation-company practice method (ACPM), SC-HALNS reduced mean modeled fuel consumption by 1.31–7.87%. Exact paired sign tests with Holm correction favored SC-HALNS in 13 of 18 external comparisons. Accepted consolidations reduced returns to the base, potentially easing replenishment workload. These results support offline scheduling under the evaluated model assumptions; reported fuel savings are model-based estimates.