One of the major reasons for the formation of a heat-affected zone during laser processing of carbon fiber-reinforced plastics (CFRP) with repetitive picosecond (ps) laser pulses is heat accumulation. A fraction of every laser pulse is left as what we termed residual heat in the material also after the completed ablation process and leads to a gradual temperature increase in the processed workpiece. If the time between two consecutive pulses is too short to allow for a sufficient cooling of the material in the interaction zone, the resulting temperature can finally exceed a critical temperature and lead to the formation of a heat-affected zone. This accumulation effect depends on the amount of energy per laser pulse that is left in the material as residual heat. Which fraction of the incident pulse energy is left as residual heat in the workpiece depends on the laser and process parameters, the material properties, and the geometry of the interaction zone, but the influence of the individual quantities at the present state of knowledge is not known precisely due to the lack of comprehensive theoretical models. With the present study, we, therefore, experimentally determined the amount of residual heat by means of calorimetry. We investigated the dependence of the residual heat on the fluence, the pulse overlap, and the depth of laser-generated grooves in CRFP. As expected, the residual heat was found to increase with increasing groove depth. This increase occurs due to an indirect heating of the kerf walls by the ablation plasma and the change in the absorbed laser fluence caused by the altered geometry of the generated structures.

Mass transport in textiles is crucial. Knowledge of effective mass transport properties of textiles can be used to improve processes and applications where textiles are used. Mass transfer in knitted and woven fabrics strongly depends on the yarn used. In particular, the permeability and effective diffusion coefficient of yarns are of interest. Correlations are often used to estimate the mass transfer properties of yarns. These correlations commonly assume an ordered distribution, but here we demonstrate that an ordered distribution leads to an overestimation of mass transfer properties. We therefore address the impact of random ordering on the effective diffusivity and permeability of yarns and show that it is important to account for the random arrangement of fibers in order to predict mass transfer. To do this, Representative Volume Elements are randomly generated to represent the structure of yarns made from continuous filaments of synthetic materials. Furthermore, parallel, randomly arranged fibers with a circular cross-section are assumed. By solving the so-called cell problems on the Representative Volume Elements, transport coefficients can be calculated for given porosities. These transport coefficients, which are based on a digital reconstruction of the yarn and asymptotic homogenization, are then used to derive an improved correlation for the effective diffusivity and permeability as a function of porosity and fiber diameter. At porosities below 0.7, the predicted transport is significantly lower under the assumption of random ordering. The approach is not limited to circular fibers and may be extended to arbitrary fiber geometries.

Quality Control is crucial when it comes to fine and technical knits. Digital Twins are common in product design and are necessary for heat and mass flow simulations of textile fabrics. In both cases primarily, the exact geometry of the knitted loop is necessary for following processes. Wale spacing W and course spacing C are the essential geometrical characteristics of the representative unit cell of single jersey fabrics. The loop parameters can be obtained manually by counting loops per unit length or by microscopic measurements, which both are time consuming and are not applicable in integrated digital processes. Therefore, a new method for automatic extraction of major loop geometry parameters is described. A state-of-the-art method, which analyzes the microscopic images automatically, works with Fourier-Transformation of the image brightness and is used as a benchmark. The new loop-based method extracts the geometrical data from the distances between the center points of the loops. The methods are evaluated on single jersey fabrics of three different yarns. In addition, the impact of magnification on the measurement is shown for one fabric. The new method gives same results as manual measurements and even more precise results as the benchmark method.

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