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Amorphous, porous materials represent by far the largest proportion of natural and men-made materials. Their pore networks consists of a wide range of pore sizes, including mesoand macropores. Within such a pore network, material moisture plays a crucial role in almost all transport processes. In the hygroscopic range, the pores are partially saturated and liquid water is only located at the pore fringe due to physisorption. Therefore, material parameters such as porosity or median pore diameter are inadequate to predict material moisture and moisture transport. To quantify the spatial distribution of material moisture, Hillerborg’s adsorption Theory is used to predict the water layer thickness for different pore geometries. This is done for all pore sizes, including those in the lower nanometre range. Based on this approach, it is shown that the material moisture is almost completely located in mesopores, although the pore network is highly dominated by macropores. Thus, mesopores are mainly responsible for the moisture storage capacity, while macropores determine the moisture transport capacity, of an amorphous material. Finally, an electrical analogical circuit is used as a model to predict the diffusion coefficient based on the pore-size distribution, including physisorption.
Detection of surface breaking cracks using flying line laser thermography: A Canny-based algorithm
(2021)
In this work, we introduce a new algorithm for effectual crack detection using flying line laser thermography, based on the well-known Canny approach. The algorithm transforms the input thermographic sequence into an edge map. Experimental measurements are performed on a metallic component that contains surface breaking cracks due to industrial use. The specimen is tested using flying line thermography at different scanning speeds and laser input powers. Results obtained with the proposed algorithm are additionally compared with a previously established algorithm for flying spot thermography. The proposed Canny-based algorithm can be used in automated systems for thermographic non-destructive testing.
Phosphoric acid as the electrolyte in high-temperature polymer electrolyte membrane fuel cell plays an essential role in ist performance and lifetime. Maldistribution of phosphoric acid in the catalyst layer (CL) may result in performance degradation. In the present study, pore-scale simulations were carried out to investigate phosphoric acid’s multiphase flow in a cathode CL. A reconstructed CL model was built using focused ion beam-SEM images, where distributions of pore, carbon support, binder, and catalyst particles can be identified. The multi-relaxation time lattice Boltzmann method was employed to simulate phosphoric Acid invading and leaching from the membrane into the CL during the membrane electrode assembly fabrication process. The predicted redistribution of phosphoric acid indicates that phosphoric acid of low viscosity or low wettability is prone to leaching into the CL.
The effective transport properties and the active electrochemical active surface area (ECSA) were computed using a pore-scale model. They were subsequently used in a macroscopic model to evaluate the cell performance. A parametric study shows that cell performance first increases with increasing phosphoric acid content due to the increase of ECSA. However, further increasing phosphoric acid content results in performance degradation due to mass transfer limitation caused by acid flooding.
The mechanical compression of metal foam flow-field based polymer electrolyte fuel cells (PEFCs) is critical in determining the interfacial contact resistance with gas diffusion layers (GDLs), reactant flow and water management.
The distinct scale between the pore structure of metal foams and the entire flow-field warrant a multilength scale characterization that combines ex-situ tests of compressed metal foam samples and in-operando analysis of operating PEFCs using X-ray computed tomography (CT) and neutron radiography. An optimal ‘medium’ compression was found to deliver a peak power density of 853 mW/cm². The X-ray CT data indicates that the compression process significantly decreases the mean pore size and narrows the pore size distribution of metal foams. Simulation results suggest compressing metal foam increases the pressure drop and gas velocity, improving the convective liquid water removal. This is in agreement with the neutron imaging results that demonstrates an increase in the mass of accumulated liquid water with minimum compression compared to the medium and maximum compression cases. The results show that a balance between Ohmic resistance, water removal capacity and parasitic power is imperative for the optimal performance of metal foam based PEFCs.
Digital Coplanar Translational Laminography (CTL) is a radiographic imaging technique that permits the visualization of structural details and discontinuities in the object of interest after 3D reconstruction from multiple projections. This technique becomes quite competitive regarding to computed tomography in situations of arrangements in which no complete rotation of the X-ray source - detector system around the object of interest is accessible or in cases where the part to be inspected has a high geometric asymmetry. The literature does not show many studies about image quality for different laminographic reconstructions and scan geometries.
Different methodologies for measuring the Modulation Transfer Function (MTF) as a key image quality parameter for the aforementioned technique are applied. The MTF was measured using different approaches, presampled MTF or sampled MTF, both based on the Fourier Transform-Magnitude Spectrum or the square wave
MTF using line pattern gauges. A sample known as Siemens Star with a converging line pattern was used to measure the circular square wave MTF. This circular MTF provides information on the direction dependent contrast transfer related to the measurement conditions, the reconstruction algorithms and the translational scan direction. For this purpose, several MTF measurements were performed in multiple angular directions. Beyond it, reconstructions were performed using different algorithms (Filtered Shifted Average) and an iterative one (MART – Multiplicative Algebraic Reconstruction Technique). Image quality analysis were done for both reconstruction methods. MART showed an image quality improvement for challenging conditions for laminographic arrangements, such as for a low number of projections (down to 25 for this study, considered as limited view, limited
angle reconstruction). Additionally, a Gadolinium gauge with parallel line patterns within a range from 10 μm to 1000 μm was used to compare the square wave MTF with the sine MTFs, measured by the different techniques mentioned above. The results show that the MTF techniques presented are equivalent in this study. The results obtained for this Gadolinium plate showed a good agreement between MTF10% and SRb image measurements. The methodology presented here is used for the characterization of the frequency dependent spatial resolution of measurements obtained from different laminographic reconstruction techniques and scan geometries. Finally, from the acquisitions and reconstructions obtained with the Siemens Star, cross laminographic images were calculated in order to improve the direction dependent sensitivity. The results showed a better detectability for cross laminographic images in comparison to unidirectional coplanar translational laminographic images covering dead zones.
Laser-based additive manufacturing methods allow the production of complex metal structures within a single manufacturing step. However, the localized heat input and the layer-wise manufacturing manner give rise to large thermal gradients. Therefore, large internal stress (IS) during the process (and consequently residual stress (RS) at the end of production) is generated within the parts. This IS or RS can either lead to distortion or cracking during fabrication or in-service part failure, respectively. With this in view, the knowledge on the magnitude and spatial distribution of RS is important to develop strategies for its mitigation. Specifically, diffraction-based methods allow the spatial resolved determination of RS in a non-destructive fashion. In this review, common diffraction-based methods to determine RS in laser-based additive manufactured parts are presented. In fact, the unique microstructures and textures associated to laser-based additive manufacturing processes pose metrological challenges. Based on the literature review, it is recommended to (a) use mechanically relaxed samples measured in several orientations as appropriate strain-free lattice spacing, instead of powder, (b) consider that an appropriate grain-interaction model to calculate diffraction-elastic constants is both material- and texture-dependent and may differ from the conventionally manufactured variant. Further metrological challenges are critically reviewed and future demands in this research field are discussed.
An approach to adhesive bond characterisation using guided acoustic waves in multi-layered plates
(2021)
An approach for the non-destructive characterisation of adhesive bonds using guided ultrasonic waves is presented. Pulsed laser radiation is used to thermoacoustically excite broadband ultrasonic waves in a multi-layered sample, consisting of a metal plate adhesively joined to a polymeric layer using synthetic resin. The resulting signals are received by a purpose-built piezoelectric transducer. Varying the distance between excitation and detection yields spatio-temporal measurement data, from which the dispersive properties of the propagating waves can be inferred using a two-dimensional Fourier transform, assuming the plates to act as coupled waveguides. Coupled multi-layered waveguides show an effect referred to as mode repulsion, where the distance between certain modes in the frequency-wavenumber domain is assumed to be a measure of coupling strength. Measurements at different stages of curing of the adhesive layer are performed and evaluated. A comparison of the results shows changes in the dispersive properties, namely an increased modal bandwidth for the fully cured sample as well as an increased modal distance.
Industrial processes release substantial quantities of waste heat, which can be harvested to generate electricity. At present, the conversion of low grade waste heat to electricity relies solely on thermoelectric materials, but such materials are expensive and have low thermodynamic efficiencies. Although thermomagnetic materials may offer a promising alternative, their performance remains to be evaluated, thereby hindering their real-world application. Here, the efficiency and cost effectiveness of thermomagnetic materials are evaluated for the usage in motors, oscillators, and generators for converting waste heat to electricity. The analysis reveals that up to temperature differences of several 10 K, the best thermomagnetic materials have the potential to compete with thermoelectric materials. Importantly, it is found that the price per watt of some thermomagnetic materials is much lower compared to that of present-day thermoelectrics, which can become competitive with conventional power plants. This materials library enables the selection of the best available thermomagnetic materials for harvesting waste heat and gives guidelines for their future development.
Additive manufacturing (AM) is developing rapidly due to itsflexibility in producing complex geometries and tailored material compositions. However, AM processes are characterized by intrinsic limitations concerning their resolution and surface finish, which are related to the layer-by-layer stacking process. Herein, a self-organization process is promoted as an approach to improve surface quality and achieve optimization of 3D minimal surface lightweight structures. The self-organization is activated after the powder bed 3D printing process via local melting, thereby allowing surface tension-driven viscous flow.The surface roughness Ra (arithmetic average of the roughness profile) could bedecreased by a factor of 1000 and transparent lenses and complex gyroid structures could be produced for demonstration. The concept of self-organization is further elaborated by incorporating external magnetic fields to intentionally manipulate magnetic particles, which are mixed with the polymer before printing and self-organization. This concept can be applied to develop programmable materials with specific microtextures responding to the external physical conditions.
The determination of the anisotropy of materials’ microstructure and morphology (pore space) in diesel particulate filter (DPF) materials is an important problem to solve, since such anisotropy determines the mechanical, thermal, and filtration properties of such materials. Through the use of a dedicated (and simple) segmentation algorithm, it is shown how to exploit the information yielded by 3D X-ray computed tomography data to quantify the morphological anisotropy. It is also correlated that such anisotropy of the pore space Such anisotropy of the pore space is also correlated with the microstructure and crystallographic anisotropy of the material in several showcases: a microstructurally isotropic material, such as SiC, and some morphologically and microstructurally anisotropic cordierite materials. In the later case, the finer the grain size, the more isotropic the microstructure.