A new methodology leverages virtual casting process simulations to predict the statistical distribution of local mechanical properties, based on computed local microstructures and defects. The extensive result sets generated from each simulation can be statistically evaluated in a manner similar to numerous individual tensile tests. By incorporating process variability into the simulation, this innovative approach enables probabilistic modeling of expected local properties. Consequently, this method supports designers during the design phase for reliable component development and assists casters in achieving robust process designs.

Tensile tests have been conducted on die-cast coupons of an Al-Si-Cu alloy, which have been found to contain no pores via X-ray inspection. Due to the digital image correlation used during tensile testing, either single or multiple strain concentrations have been detected and subsequently characterized. In all cases, oxide films have been found on fracture surfaces at the site of the strain concentrations. The analysis of a crack away from the fracture surface has also shown it to be an oxide bifilm. These results pour doubt on the effectiveness of quality assurance practices employed in industry.

The competition between pores and hidden entrainment defects during tensile testing of specimens from Al-Si-Cu alloy high-pressure die castings has been characterized. In all tests, multiple strain concentrations have been identified by using the digital image correlation technique and the final fracture has been preceded by a competition between pores and hidden damage, later identified as oxide bifilms. The results have confirmed previous findings that overall damage to the metal during its liquid state is much more extensive than what can be assessed via X-ray inspection, which looks only for pores. It is concluded that current quality assurance techniques need to be updated.

An approach to evaluate and quantify process variability in the mechanical performance of castings is explored. The process variability describes the effect of hidden damage given to the metal before solidification on the material performance measured by elongation to failure. The approach is demonstrated on a casting produced by high-pressure die casting (HPDC) with different filling conditions in serial production. Statistical analyses have been conducted on data obtained from several positions throughout the casting to determine whether a position is performing differently from other positions. The results show that elongation in most positions follows the same Weibull distribution. However, the local evaluation shows that one position stands out and follows a separate distribution. Casting simulations, Digital Image Correlation (DIC), and Scanning Electron Microscopy (SEM) reveal that this position displays an increased amount of hidden damage that causes the local reduction in elongation. The investigated changes in prefill amount do not significantly affect the material quality, which is more controlled by the quality of the melt and the nature of mold filling.

In the last decades, the automotive industry has increased the usage of cast aluminum. To enhance the quality of their products, foundries must focus on minimizing casting entrainment defects during the production process. Defects can be divided into visible and hidden damage to the structural component. The visible defects, such as pores and bubbles, have been the primary focus of quality assurance in foundries. Yet, recent evidence shows that most of the damage given to liquid metals remain hidden, only to reduce tensile properties and fatigue performance in service.This work presents ways to identify the hidden damage in cast aluminium using in-situ cyclic testing in a scanning electron microscope equipped with a Focused Ion Beam. Moreover, applying Digital Image Correlation to cyclic tests and tensile tests showed the hidden damage in an early stage.The combined results show that the hidden damage impacts the mechanical properties significantly.

In this work, an integrated simulation approach previously developed for static FE analyses is extended to microstructure- and defect-based fatigue life assessments of castings. The approach, the closed chain of simulations for cast components, combines casting process simulation with microstructure modelling and local material characterisation to generate heterogeneous material data for FE analysis and fatigue life assessment. The method is demonstrated on a High-Pressure Die Cast aluminium component. Areas with a high risk of defects are identified based on the simulated solidification conditions, and heterogeneous material data for the fatigue life analysis is generated. Fatigue testing has been performed with different levels of porosities to quantify the effect of defects on the element-specific Wöhler curves. Pore characteristics are assessed using 2D X-ray, fracture surface analysis and Kitagawa diagram. The results highlight the importance of taking the risk of defect formation into consideration when designing industrial aluminium castings subjected to fatigue loads.

Pores have been the main focus of quality assurance in castings. Latest research has shown that in aluminium castings pores can form only if there is existing entrainment damage, i.e., pores are merely the visible parts of the entrainment damage, and usually invisible damage is much more extensive. However, its effect on deformation behaviour has not been previously established or observed in-situ. This work applies 2D Digital Image Correlation (DIC) to an in-situ full-field stress-strain analysis of tensile samples with a non-conventional heterogeneous stress distribution. The observations reveal that the effect of hidden damage extends far beyond its impact on fracture behaviour and is responsible for initiating local strain concentrations during deformation. By extracting local stress-strain data, FE simulations have been performed to mimic the effect of local hidden damage on the heterogeneous stress-strain field. SEM and FIB-SEM analysis has been applied to investigate the cause for the strain concentrations. The combined results show that hidden damage in the form of oxide films is not only responsible for premature fracture, but also affects the deformation behaviour of tensile samples by introducing dispersed strain concentrations.

The pandemic has forced teaching as well as as the Software Development industry, to be performed remotely. The educational institutions are therefore facing the situation of training and steering the students in, not only complex work, but also in remote-based work and it processes. Specific challenges here relate to project work with larger groups of developers, with testing, and integration of technical components for complete solutions, but the psychosocial factors come into play as well. This paper considers the situation that has arisen as a consequence of the pandemic and regards how project-based courses should be adapted to ‘The New Normal’. In focus is a course in Software Engineering, where a large-scaled project shall be developed remotely. Representatives from IT-companies act at the course remote, and at specific occurrences. The course is observed by the teachers to see its outcome, as well as different aspects on attitudes towards future remote work. Interviews and surveys regarding attitudes of students, as well as involved company representatives are presented, where the focus is on process, productivity, work environment, interest in remote work, as well as social aspects. The main findings, based on the surveys, motivates hybrid solutions for university courses, to meet the corresponding companies’ way of future working style.