Experimental and Numerical Study of Healing Effect on Delamination Defect in Infusible Thermoplastic Composite Laminates.

The integrity of delaminated composite structures can be restored by introducing a thermally-based healing effect on continuous fiber-reinforced thermoplastic composites (CFRTPC). The phenomenon of thermoplastics retaining their properties after melting and consolidation has been applied by heating the delaminated composite plates above their glass transition temperature under pressure. In the current investigation, the composite is comprised of Methyl methacrylate (MMA)-based infusible lamination resin combined with benzoyl peroxide initiator, which polymerizes into a Polymethyl methacrylate (PMMA) matrix. For the reinforcement, unidirectional 220 gr/m2 glass filament fabric was used. Delamination damage is artificially induced during the fabrication of laminate plates. The distributed delamination region before and after thermally activated healing was determined by using non-destructive testing with active thermography. An experimental approach is employed to characterize the thermal healing effect on mechanical properties. Experimentally determined technological parameters for thermal healing have been successfully applied to repair delamination defects on composite plates. Based on the compression-after-impact (CAI) test methodology, the intact, damaged, and healed composite laminates were loaded cyclically to evaluate the healing effect on stiffness and strength. During the CAI test, the 3D digital image correlation (DIC) technique was used to measure the displacement and deformation fields. Experimental results reveal the difference between the behavior of healed and damaged specimens. Additionally, the numerical models of intact, damaged, and healed composite laminates were developed using the finite element code LS-Dyna. Numerical models with calibrated material properties and tie-break contact constants provide good correlation with experimental results and allow for the prediction of the mechanical behavior of intact, damaged, and healed laminated plates. The comparison analysis based on CAI test results and modal characteristics obtained by the 3D Laser Doppler Vibrometer (Polytec GmbH, Karlsbad, Germany) proved that thermal healing partially restores the mechanical properties of damaged laminate plates. In contrast, active thermography does not necessarily indicate a healing effect.

Investigation of the Robotized Incremental Metal-Sheet Forming Process with Ultrasonic Excitation.

During the single-point incremental forming (SPIF) process, a sheet is formed by a locally acting stress field on the surface consisting of a normal and shear component that is strongly affected by friction of the dragging forming tool. SPIF is usually performed under well-lubricated conditions in order to reduce friction. Instead of lubricating the contact surface of the sheet metal, we propose an innovative, environmentally friendly method to reduce the coefficient of friction by ultrasonic excitation of the metal sheet. By evaluating the tool-workpiece interaction process as non-linear due to large deformations in the metal sheet, the finite element method (FEM) allows for a virtual evaluation of the deformation and piercing parameters of the SPIF process in order to determine destructive loads.

Investigation of Advanced Robotized Polymer Sheet Incremental Forming Process.

The aim of this work is to evaluate the possibility of inexpensively producing small-batch polymer sheet components using robotized single point incremental forming (SPIF) without backing plate support. An innovative method of thermal and ultrasound assisted deformation of a polymer sheet is proposed using a tool with a sphere mounted in a ring-shaped magnetic holder, the friction of which with the tool holder is reduced by ultrasound, and the heating is performed by a laser. The heated tool moving on the sheet surface locally increases the plasticity of the polyvinyl chloride (PVC) polymer in the contact zone with less deforming force does not reducing the stiffness of the polymer around the tool contact area and eliminating the need for a backing plate. The free 3D rotating ball also changes the slip of the tool on the surface of the polymer sheet by the rolling, thereby improving the surface quality of the product. The finite element method (FEM) allowed the virtual evaluation of the deformation parameters of the SPIF. Significant process parameters were found, and the behavior of the heated polymer sheet was determined.

Piezoelectric Transducer-Based Diagnostic System for Composite Structure Health Monitoring.

This paper focuses on the investigation of the diagnostic system for health monitoring and defects, detecting in composite structures using a piezoelectric sensor. A major overview of structural defects in composite materials that have an influence on product performance as well as material strength is presented. Particularly, the proposed diagnostic (health monitoring) system enables to monitor the composite material plate defects during the exploitation in real-time. The investigated health monitoring system can indicate the material structure defects when the periodic test input signal is provided to excite the plate. Especially, the diagnostic system is useful when the defect placement is hard to be identified. In this work, several various numerical and experimental studies were carried out. Particularly, during the first study, the piezoelectric transducer was used to produce mechanical excitation to the composite plate when the impact response is measured with another piezoelectric sensor. The second study focuses on the defect identification algorithms of the raw hologram data consisting of the recorded oscillation modes of the affected composite plate. The main paper results obtained in both studies enable us to determine whether the composite material is characterized by mechanical defects occurring during the response to the periodic excitation. In case of damage, the observed response amplitude was decreased by 70%. Finally, using the time-domain experimental results, the frequency response functions (FRFs) are applied to damage detection assessment and to obtain extra damage information.

Comparative Analysis of Machine Learning Methods for Predicting Robotized Incremental Metal Sheet Forming Force.

This paper proposes a method for extracting information from the parameters of a single point incremental forming (SPIF) process. The measurement of the forming force using this technology helps to avoid failures, identify optimal processes, and to implement routine control. Since forming forces are also dependent on the friction between the tool and the sheet metal, an innovative solution has been proposed to actively control the friction forces by modulating the vibrations that replace the environmentally unfriendly lubrication of contact surfaces. This study focuses on the influence of mechanical properties, process parameters and sheet thickness on the maximum forming force. Artificial Neural Network (ANN) and different machine learning (ML) algorithms have been applied to develop an efficient force prediction model. The predicted forces agreed reasonably well with the experimental results. Assuming that the variability of each input function is characterized by a normal distribution, sampling data were generated. The applicability of the models in an industrial environment is due to their relatively high performance and the ability to balance model bias and variance. The results indicate that ANN and Gaussian process regression (GPR) have been identified as the most efficient methods for developing forming force prediction models.