Additive manufacturing (AM) has become an increasingly attractive production method due to its design flexibility and reduced material waste. Nevertheless, the limited build volume often necessitates the joining of printed components to form larger or more complex structures. In this context, adhesive bonding represents a promising solution, although its mechanical performance remains insufficiently explored. This study presents an experimental and numerical investigation of adhesively bonded joints manufactured from AM thermoplastics, focusing on a direct comparison between conventional single-lap joints (SLJ) and step (SJ) joints. The adherends were produced using Polylactic Acid (PLA), Polyethylene Terephthalate Glycol-modified (PETG), and Acrylonitrile Butadiene Styrene (ABS) while two structural adhesives, namely Araldite® 2015 and Sikaforce® 7752, were employed. Tensile tests were conducted to evaluate joint strength, stiffness, energy dissipation, and failure mechanisms for both joint configurations. The experimental results were complemented by numerical simulations based on a Cohesive Zone Modelling (CZM) framework. The findings indicate that joint configuration has a significant effect on overall performance.
Self-sensing cementitious composites (SSCCs) endow pavements with smart functionality, including strain and crack detection, thermal and moisture monitoring, and traffic/load sensing, by incorporating conductive fillers such as carbon nanotubes, carbon black, graphene derivatives, and steel or other metallic fibers. These capabilities are drawing strong interest for next-generation, eco-efficient, serviceable, reliable, and durable pavement systems that enhance traffic safety and operational efficiency. Reported applications cover structural health monitoring, traffic detection and weigh-in-motion, surface-condition sensing (temperature, moisture, icing), durability/damage evaluation, and maintenance planning. This paper reviews recent advances in SSCCs for cementitious composites and pavement applications, with emphasis on the materials employed, the resulting mechanical strength, and their combined effects on electrical resistivity and conductivity.
This work studies mechanical fracture parameters, including the Stress Intensity Factor (SIF), J-Integral (JIT), and critical crack length, using a finite element analysis of a three-point bending specimen. The material used is a Ti-6Al-4V alloy produced by additive manufacturing. The influence of mechanical properties, fracture parameters and the manufacturing direction on structural integrity is the focus of this research. The loading conditions were studied, both with and without contact, while accounting for additive manufacturing directions. The mesh-convergence study was also conducted. The simulations were performed for a three-dimensional (3D) model. In conclusion, the finite element analysis using the Contour Integral Method is applicable to parts produced by additive manufacturing; however, special attention should be given to the expected direction of crack propagation.
This paper conducts a comprehensive investigation into the utilization of the Particle Swarm Optimization (PSO) algorithm for crack detection in beam structures. The primary aim is to precisely forecast both the size and location of an open-edge crack in functionally graded beams. The chosen modeling approach involves a rotating spring, with its stiffness determined by the crack’s size. The PSO algorithm is employed as an optimization technique to address this problem. The objective function is formulated as the weighted sum of squared errors between measured and calculated natural frequencies. The PSO algorithm systematically explores the solution space to identify optimal values for crack size and location, minimizing the defined objective function. The obtained results illustrate the efficacy of the PSO algorithm in accurately predicting crack size and location. This methodology provides a viable alternative for addressing crack detection challenges, opening avenues for potential applications in predictive maintenance of beam structures. In conclusion, the application of the PSO algorithm underscores its relevance and effectiveness in resolving crack detection issues, offering a promising solution for safeguarding structural integrity and averting future failures.
The purpose of this paper is to develop a theoretical analysis of longitudinal fracture in a moving functionally graded beam structure under conditions of creep. Analyzing fracture in moving functionally graded beams is important since functionally graded materials are frequently used for manufacturing components of various mechanisms and devices performing different kinds of motion. The beam considered here rotates around a vertical axis. The axis itself moves vertically. The beam hosts a longitudinal crack. The strain energy release rate (SERR) is derived with considering the non-linear creep in the beam under inertia loads. The parameters of creep equation used in the analysis change continuously along the thickness since the beam is functionally graded in the thickness direction. The SERR is verified by the method of J integral. A detailed evaluation of the effects of acceleration of the beam structure on the SERR is carried-out. The influence of various parameters on the SERR - time curve is studied.
