Development of Formulas Predicting Bending Moments of Elastic–Plastic and Bi-Modular-Layered Particleboards
Year: 2025
Type: article
Abstract: Four mechanical models were proposed to derive formulas predicting the bending moment capacities of layered particleboard under simply supported center-loading. Experimental validation confirmed these models are effective tools for describing the bending moment development process, including proportional limit, yield, and ultimate points. With predicted and experimental ratios ranging from 0.88 to 1.04, Model 4 can reasonably predict the ultimate bending moment capacity of elastic–plastic and bi-modular-layered particleboard materials. Photo-elastic testing revealed neutral axis shifting toward the compressive side, resulting from the face layer’s significantly higher mean modulus of elasticity in compression than in tension. Additionally, the core material above the centerline of PB thickness contributed to tensile resistance. The proposed mechanical models require inputs such as the tensile and compressive strengths and thickness of each layer, accounting for the asymmetric strength profile and neutral axis shifting. The main conclusion was that the bending moment resistance of the particleboard depends on the combined effect of tensile and compressive strengths of all layers. A 3D plot visualized the PB’s mechanical design space, displaying feasible tensile–compressive strength combinations of particleboard layers. This enables determination of optimal strength properties for each layer. For M2 grade particleboard, the most cost-effective design occurred when the face layer reached a 5.38 MPa tensile strength, with the compressive strength ranging between 13.00 and 18.59 MPa.
Source: Forests
DOI: 10.3390/f16081315
Authors: Yan Wang, Samet Demirel, Wengang Hu, Franklin Quin, Jilei Zhang, Shunyao Sun, Xiaohong Yu
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Funder: Mississippi State University
OpenAlex ID: W4413127814
