Towards biaxial fatigue experiments of elastomers using square and cruciform geometries in planar tension conditions

Soft materials such as natural rubber, hydrogels, and biological tissues have anisotropic properties and are subject to cyclic biaxial loading during their service lives. This requires biaxial loading rather than uniaxial; however, no agreed standard protocol exists. Therefore, the aim of this study is to provide preliminary suggestions for reliable and consistent biaxial fatigue tests so that a good degree of biaxiality and efficiency can be thoroughly achieved. Several biaxial loading tests (equi-biaxial and unequal-biaxial) were conducted on natural rubber and ecoflex using different geometries including cruciform and square configurations. Three criteria were defined to evaluate the equi-biaxiality performance: (i) test function related to homogeneous strain distribution in the field of interest, (ii) degree of efficiency corresponding to the ratio of strain in the field of interest (gauge section located in the middle regions) to the maximum strain far from the middle area, and (iii) strain ratio, used for fatigue test. Results showed that cruciform geometry underperformed in equi-biaxiality criteria, i.e., samples possessed high uniaxial strain in the arm whereas the simple square geometry could reach a higher degree of biaxiality and efficiency. The highest equi-biaxiality performance was obtained for the optimized square geometry in such a way that a maximum equi-biaxial strain of 65 % was achieved in the field of interest while possessing a degree of efficiency of 0.66 and strain ratio of 1.96. A successful unequal-biaxial fatigue test of up to two million cycles was conducted on the optimized square specimen made of ecoflex. Finally, a new square configuration with circular cavity in the middle was suggested for future biaxial characterization and standardization of biaxial tests in which the numerical study yielded a degree of efficiency of 1 and strain ration of 2.12 manifesting a considerable improvement in the biaxiality performance

Boat noise alters behaviour of two coral reef macroinvertebrates, Lambis lambis and Tridacna maxima

Boat noise has been shown to distract and cause harm to many marine organisms. Most of the study effort has focused on fish & marine mammals, even though invertebrates represent over 92 % of all marine life. The few studies conducted on invertebrates have demonstrated clear negative effects of anthropogenic noise pollution. The small giant clam Tridacna maxima and the spider conch Lambis lambis are two invertebrate species which play key roles in coral reef ecosystems, and are little studied for the effects of noise disturbance. T. maxima functions as prey for many fish species, contributes up to 9 % of the reef's calcium carbonate budget, and plays a role in nutrient cycling. The herbivorous strombid L. lambis can occur in large numbers on reef flats and is prey for other snails and several elasmobranchs. Using two case study reefs, we show that both boat noise and biotic sounds are prominent sound sources in Red Sea reef habitats. In-situ controlled exposure experiments were conducted on two shallow central Red Sea reefs, where Daily Diary smart tags were used to measure the reactions of T. maxima and L. lambis during underwater playback of boat noise and ambient reef sound. Both macroinvertebrates exhibited behavioral changes during the boat noise treatment. Our results suggest that L. lambis and T. maxima individuals may spend energy averting the invisible “threat” of boat noise, rather than feeding or staying open for symbiotic algae to perform photosynthesis, in the case of T. maxima. As boat noise is prevalent on Red Sea reefs, invertebrates may be affected on a large scale in the Red Sea

Towards state of the art vacuum locks for a novel continuous PVD galvanising process

Physical Vapour Deposition (PVD) is used in various industries to create thin coatings ranging from aluminizing crisp packaging through to thin ZnO films on solar cells and glass windows providing thermochromic control [1]. Vacuum locks are used during manufacturing to transport material into and out of the coating chamber, sometimes as a continuous process.In 2012, POSCO installed a wide PVD pilot plant [2] and in 2017 Arcelor Mittal opened a €63 million commercial air to air coating line, therefore demonstrating the technology is commercially viable [3]. The advantage of PVD coating over more traditional methods such as a galvanising bath is a greater control on the coating thickness, excellent corrosion resistant properties and uniform coating across the substrate. A review of patents and publications on the state-of-the-art in vacuum lock design for the PVD steel coating technology showed that air bearings had the potential for an improved design with a greater flexibility in dealing with variable strip width and thickness.A new vacuum lock for a continuous steel strip process has been designed and prototyped by using a combination of computational modelling, continuum fluid dynamics and discrete molecular models, validated against benchmarks and experimentation. Using a set pump speed (198 m3/hr) at the outlet, the lock was designed to maintain a pressure drop of -79.3kPa and would form the first of a sequence of vacuum locks ultimately reducing the vacuum level to the pressure of 0.01 Pa required within the PVD chamber.Whilst no single computational model was able to capture the entire flow regime, the continuum models were able to suggest possible pressure drops from changing outlet mass flow rates, which was used to develop the design. By using an air bearing system at the lock entrance with thin slider blocks to adjust the gap, the lock can accommodate a steel strip with a reduced or increased thickness and width

3D microstructure reconstruction of heterogeneous material from slice descriptors using explicit neural network

Heterogeneous materials such as rocks, concrete, and composites exhibit random microstructures that strongly influence their physical properties. These structures can be captured using imaging techniques such as micro-Computed Tomography (micro-CT) and Scanning Electron Microscopy (SEM), but such methods are costly. As an alternative, digital reconstruction offers a way to generate synthetic microstructural images. Traditional reconstruction methods provide geometric control but lack flexibility and generality. In contrast, Computer Vision (CV) approaches offer strong generative capabilities, but often lack interpretability and material-specific constraints. Conditional generation introduces descriptors as labels, yet struggles with control during training. In this work, we enhance conditional generation by decomposing the loss into two parts: an implicit CV-based component and an explicit, descriptor-driven component inspired by traditional methods. The explicit loss includes a targeted loss for individual inputs and a distribution loss for overall output quality, ensuring both accuracy and diversity. To support fast training, a rapid descriptor regression model is developed and integrated into our digital reconstruction workflow. We validate our method on Fontainebleau sandstone, Polytetrafluoroethylene (PTFE), and SOFC electrodes, demonstrating improved reconstruction performance compared to the current state-of-the-art 2D-to-3D method. Our approach accurately captures statistical descriptors, even for complex geometries, and maintains strong consistency across multiple 2D slices representing 3D structures

A hybrid strategy of OTPA and machine learning for efficient root-cause analysis of NVH in multi-source systems

The growing awareness of health benefits, along with the competitive emphasis on vehicle comfort, has led automakers to place greater attention on reducing Noise, Vibration, and Harshness (NVH). One of the most beneficial techniques for NVH engineers to identify, rank, and eliminate dominant noise and vibration sources and paths is Transfer Path Analysis (TPA). Unlike traditional TPA, Operational Transfer Path Analysis (OTPA) requires neither the preliminary acquisition of the transfer matrix between excitation and response points nor the measurement of forces transferred through the active and passive side connection points. Although the OTPA method offers significant advantages over classical TPA methods, it still faces challenges such as data loss caused by the pseudo-inversion of the indicator matrix. In this paper, we estimate the transmissibility matrix using a machine learning-based regression algorithm (random forest). We demonstrated that machine learning is an effective alternative to the truncated Singular Value Decomposition (SVD) method for estimating the transmissibility matrix, as it is a swift solution that preserves essential information in the indicator matrix. The efficiency of the method has been verified by a 2.28 % improvement in the Sound Pressure Level (SPL) of the driver’s ear noise of a sedan-type vehicle through the modification of the most critical path found by this approach

Evaluation of the corrosion protection of organic-coated zinc-alloy galvanised steels using novel, environmentally-friendly corrosion inhibitor pigments

The corrosion behaviour of steel coated with either: a primarily zinc coating comprised of 0.15 wt% Al (HDG) or a zinc-aluminium-magnesium coating, 1.6 wt% Mg, 1.6 wt% Al, and 96.8 wt% Zn (ZAM) are investigated in the presence of industry standard and emerging, environmentally-friendly corrosion inhibitor technologies. With this paper evaluating the inhibitory performance of a functionalised oxy-amino-phosphate-salt of magnesium (OPMG), a hydrotalcite carbonate clay loaded with 4-aminobenzoic acid (HT-PABA), a calcium ion exchange pigment (Ca-Ex), and an inhibitor based on 2-(1,3-benzothiazol-2-ylithio) succinic acid (BTSA) dispersed in model poly-vinyl-butyral (PVB) coatings and 3.5 wt% NaCl (aq) solutions. With their inhibitory performance evaluated against two corrosion-driven coating failure mechanisms: cathodic disbondment (CD), and filiform corrosion (FFC) as a function of inhibitor loading. In the case of CD, an inhibitor ranking order of BTSA > HT-PABA > OPMG > Ca-Ex is observed, while OPMG and HT-PABA are the most effective at slowing rates of FFC. Potentiodynamic and scanning vibrating electrode (SVET) experiments were conducted to evaluate the efficiency of the most promising inhibitors at slowing rates of corrosion on the bare ZAM alloy surface and the exposed cut edges immersed in chloride solutions. With OPMG and BTSA both shown to act as net anodic inhibitors, resulting in an increase in the polarisation resistance by over an order of magnitude. Both inhibitors produced a derived 67 % reduction in total (zinc) metal loss at the exposed ZAM cut-edges over a 24 h immersion period against the control