This study investigates the effect of hot isostatic pressing (HIPping) on the static and fatigue properties of sand-casting A356 aluminium alloys. HIPping is a method to improve the fatigue properties in aluminium cast material by reducing or eliminating the inner porosities. Investigation of the complex interaction between the microstructural features on mechanical properties before and after the HIPping process was examined using computed tomography and scanning electron microscopy (SEM). Castings generally contain pores and defects that have a detrimental impact on the fatigue properties. The HIPping process closes the porosities in all investigated samples with an increase in density. Without significant defects, the mechanical performance improved in the finer microstructure. However, a considerable variation in the results was found between the different conditions, whereas the coarser microstructure with larger porosities before HIPping showed remarkably reduced results. The high-cycle fatigue-tested samples showed reduced fatigue propagation zone in the coarser microstructure. Moreover, large cleavage areas containing bifilms in the fracture surfaces indicate that the healing process of porosities is inefficient. These porosities are closed but not healed, resulting in a detrimental effect on the static and dynamic properties.

This study has aimed to determine the effects of surface quality and pore size, obtained by different levels of hydrogen content of the liquid metal, on the fatigue behavior of an Al–7%Si–3%Cu–Mg casting alloy. Three surface conditions have been studied: as-cast rough, as-cast smooth, and standard machined and polished surface. The S–N curves have shown that surface roughness and hydrogen content individually impact fatigue strength. Surprisingly, the fatigue strength of machined and polished samples, which aligns with standard testing practices, is significantly reduced, compared to other conditions. Fatigue cracks have been observed to initiate at the pores just below the as-cast surface or on the machined surfaces. In all cases, pores have been observed to be surrounded by bifilms. Moreover, hydrogen content and roughness of the as-cast surface have been found to interact to determine the fatigue performance. These findings necessitate a re-evaluation of fatigue testing procedures for cast aluminum components.

The effectiveness of rotary degassing on the defect formation and mechanical properties of the final casting of aluminium alloy EN AC 46000 was investigated, along with its impact on the energy consumption in the casting furnace. In the melt preparation prior to casting, the molten metal is usually transported from the melting furnace to the casting furnace with rotary degassing as a cleaning procedure. Under the conditions of this specific study, negligible degradation was observed in the mechanical properties of the final cast component in an aluminium EN AC 46000 alloy after removing the rotary degassing step in the process. Furthermore, removing the rotary degassing step led to a reduced temperature drop in the melt, thus minimizing the need for reheating (energy consumption) by up to 75% in the casting furnace. The reduced energy consumption was up to 124,000 kWh in yearly production in a 1500 kg casting furnace. The environmental impact showed a similar to 1500 kg reduction in CO2 for one 1500 kg electrical casting furnace in a year.

During in situ cyclic testing of hot isostatically pressed and heat-treated Al-5Si-0.5 Mg-1Cu alloy castings, cracks were observed to open up in places far away from the area of stress concentration. Cyclic testing was interrupted to assess these cracks. Analysis showed that these cracks originated from oxide bifilms that were entrained in the liquid state. Moreover, Si and Fe-rich intermetallics were observed to have precipitated on these bifilms. These finding makes it necessary to re-evaluate how damage is interpreted in mechanical studies. Entrainment damage, which takes place in the liquid state, may remain invisible in non-destructive inspection and can significantly affect fatigue properties when bifilms open up under low tensile stresses and present the propagating crack a path of low resistance during propagation.

Castings generally contain pores and defects that can have a detrimental impact on mechanical properties. The hot isostatic pressing (HIP) process is usually applied to reduce internal porosities, which improves the mechanical properties because of the closed porosities. Therefore, this study investigates the effect of the HIP process on the mechanical properties of sand casting A356 aluminum alloys. This investigation was performed in collaboration with Unnaryd Modell, Quintus Technologies, and IAC Ankarsrum. Investigation of the complex interaction between the microstructural features on mechanical properties before and after the HIP process was examined using computed tomography scanning, in-situ cyclic testing, and scanning electron microscope. In the absence of large defects, the fatigue performance was improved. However, a significant variation in the result was found between the different conditions, whereas the coarser microstructure with larger porosities before the HIP process showed decreased ultimate tensile strength and elongation to failure. The samples tested under high cycle fatigue showed a reduced fatigue propagation zone in that the coarser microstructure. Moreover, large cleavage areas containing oxides in the fracture surfaces indicated that the HIP process closes all the porosities, but the oxide films are not creating a strong bonding. Furthermore, the samples tested under low cycle fatigue showed a difference in the crack propagation, whereas the coarser microstructure showed large cracks opened up away from the notch that assists the propagation leading to reduced fatigue life.

In this study, a design of Mamdani type fuzzy inference systems is presented to predict tensile properties of as-cast alloy. To improve manufacturing of light weight cast components, understanding of mechanical properties of cast components under load is important. The ability of deterministic models to predict the performance of a cast component is limited due to the uncertainty and imprecision in casting data. Mamdani type fuzzy inference systems are introduced as a promising solution. Compared to other artificial intelligence approaches, Mandani type fuzzy models allow for a better result interpretation. The fuzzy inference systems were designed from data and experts’ knowledge and optimized using a genetic algorithm. The experts’ knowledge was used to set up the values for the inference engine and initial values for the database parameters. The rule base was automatically generated from the data which were collected from casting and tensile testing experiments. A genetic algorithm with real-valued coding was used to optimize the database parameters. The quality of the constructed systems was evaluated by comparing predicted and actual tensile properties, including yield strength, Y.modulus, and ultimate tensile strength, of as-case alloy from two series of casting and tensile testing experimental data. The obtained results showed that the quality of the systems has satisfactory accuracy and is similar to or better than several machine learning methods. The evaluation results also demonstrated good reliability and stability of the approach.

The study aimed to investigate crack initiation and propagation at the micro-scale in heat-treated Al–7Si–Mg cast alloys with different copper (Cu) contents. In-situ cyclic testing in a scanning electron microscope coupled with electron back-scattered diffraction and digital image correlation was used to evaluate the complex interaction between the crack path and the microstructural features. The three-nearest-neighbour distance of secondary particles was a new tool to describe the crack propagation in the alloys. The amount of Cu retained in the α-Al matrix after heat treatment increased with the Cu content in the alloy and enhanced the strength with a slight decrease in elongation. During cyclic testing, the two-dimensional (2D) crack path appeared with a mixed propagation, both trans- and inter-granular, regardless of the Cu content of the alloy. On fracture surfaces, multiple crack initiation points were detected along the thickness of the samples. The debonding of silicon (Si) particles took place during crack propagation in the Cu-free alloy, while cracking of Si particles and intermetallic phases occurred in the alloy with 3.2 wt% Cu. Three-dimensional tomography using focused ion beam revealed that the improved strength of the α-Al matrix changes the number of cracked particles ahead of the propagating crack with Cu concentration above 1.5 wt%.

The aims of the present work are to evaluate the overaging behaviour of the investigated Cu-enriched alloy and to assess its mechanical behaviour, in terms of the tensile and fatigue strength, at room temperature and at 200 °C, and to correlate the mechanical performance with its microstructure, in particular with the secondary dendrite arm spacing (SDAS). The mechanical tests carried out on the overaged alloy at 200 °C indicate that the addition of about 1.3 wt.% Cu to the A357 alloy enables to maintain ultimate tensile strength and yield strength values close to 210 and 200 MPa, respectively, and fatigue strength at about 100 MPa. Compared to the quaternary (Al−Si−Cu−Mg) alloy C355, the A357−Cu alloy has greater mechanical properties at room temperature and comparable mechanical behaviour in the overaged condition at 200 °C. The microstructural analyses highlight that SDAS affects the mechanical behaviour of the peak-aged A357−Cu alloy at room temperature, while its influence is negligible on the tensile and fatigue properties of the overaged alloy at 200 °C. 

Uncertain and imprecise data are inherent to many domains, e.g. casting lightweight components. Fuzzy logic offers a way to handle such data, which makes it possible to create predictive models even with small and imprecise data sets. Modelling of cast components under fatigue load leads to understanding of material behaviour on component level. Such understanding is important for the design for minimum warranty risk and maximum weight reduction of lightweight cast components. This paper contributes with a fuzzy logic-based approach to model fatigue-related mechanical properties of as-cast components, which has not been fully addressed by the current research. Two fuzzy logic models are constructed to map yield strength to the chemical composition and the rate of solidification of castings for two A356 alloys. Artificial neural networks are created for the same data sets and then compared to the fuzzy logic approach. The comparison shows that although the neural networks yield similar prediction accuracy, they are less suitable for the domain because they are opaque models. The prediction errors exhibited by the fuzzy logic models are 3.53% for the model and 3.19% for the second, which is the same error level as reported in related work. An examination of prediction errors indicated that these are affected by parameters of the membership functions of the fuzzy logic model.

The optimisation of heat treatment parameters for Al–Cu–(Mg–Ag) cast alloys (2xxx) having different microstructural scales was investigated. Thermo-Calc software was used to design optimal alloy compositions. Differential scanning calorimetry (DSC), scanning electron microscopy and wavelength-dispersive spectroscopy technique were employed to determine proper solution heat treatment temperature and homogenisation time as well as incidence of incipient melting. Proper artificial ageing temperature for each alloy was identified using DSC analysis and hardness measurement. Microstructural scale had a pronounced influence on time and temperature required for complete dissolution of Al2Cu and homogenisation of Cu solute atoms in the α-Al matrix. Refined microstructure required only one-step solution treatment and relatively short solution treatment of 10 h to achieve dissolution and homogenisation, while coarser microstructures desired longer time. Addition of Mg to Al–Cu alloys promoted the formation of phases having a rather low melting temperature which demands multi-step solution treatment. Presence of Ag decreases the melting temperature of intermetallics (beside Al2Cu) and improvement in age-hardening response. Peak-aged temperature is primarily affected by the chemical composition rather than the microstructural scale.