In a quest to reduce fuel consumption and emissions of automotive combustion engines, friction losses from many different sources need to be minimized. For modern designs of turbochargers commonly used in the automotive industry, reduction of friction losses results in better efficiency and also contributes to a faster transient response. The thrust bearing is one of the main contributors to the mechanical losses of a turbocharger. Therefore, it is crucial to optimize the design of the thrust bearing so that it has minimum friction losses while keeping sufficient thrust carrying capacity. One of the main challenges of turbocharger thrust bearing design, is that rotation speed is not fixed: the turbocharger may have a rotation speed which varies between 0 to as much as 250 kRPM. Moreover, the thrust bearing generates considerable heat, which changes the temperature of the oil film and its surroundings. In the present work, the design of the thrust bearing of an automotive turbocharger has been optimized. A CFD-based Thermohydrodynamic (THD) computational approach has been developed, taking into consideration heat dissipation, conjugate heat transfer throughout the bearing domain including the surrounding parts, as well as shear thinning and cavitation in the lubricant domain. An optimizer has been coupled to the CFD solver, with the aim of identifying bearing designs with reduced friction losses. Two bearing concepts have been evaluated: a taper-land design-which is a commonly applied thrust bearing concept-as well as a pocket bearing design. The resulting optimum pocket designs exhibit improved performance, in comparison to the optimum taper-land design. The present results indicate that (a) the pocket design concept can substantially contribute to further reducing the friction losses of a turbocharger, and (b) optimal design parameters of pocket bearings depend on the specific application (size, operating conditions), therefore detailed calculations should be performed to verify optimum performance.

Athena is the European Space Agency's next flagship X-ray telescope, scheduled for launch in the 2030s. Its 2.5-m diameter mirror will be segmented and comprise more than 600 individual Silicon Pore Optics (SPO) grazing-incidenceangle imagers, called mirror modules. Arranged in concentric annuli and following a Wolter-Schwartzschild design, the mirror modules are made of several tens of primary-secondary mirror pairs, each mirror made of mono-crystalline silicon, coated to increase the collective area of the system, and shaped to bring the incoming photons to a common focus 12 m away. Aiming to deliver a half-energy width of 5", and an effective area of about 1.4 m 2 at 1 keV, the Athena mirror requires several hundred m 2 of super-polished surfaces with a roughness of about 0.3 nm and a thickness of just 110 µm. SPO, using the highest-grade double-side polished 300 mm wafers commercially available, were invented for this purpose and have been consistently developed over the last several years to enable next-generation X-ray telescopes like Athena. SPO makes it possible to manufacture cost-effective, high-resolution, large-area X-ray optics by using all the advantages that mono-crystalline silicon and the mass production processes of the semiconductor industry provide. Ahead of important programmatic milestones for Athena, we present the status of the technology, and illustrate not only recent X-ray results but also the progress made on the environmental testing, manufacturing and assembly aspects of the technology.

Athena is the European Space Agency's next flagship telescope, scheduled for launch in the 2030s. Its 2.5 m diameter mirror will be segmented and comprise more than 600 individual Silicon Pore Optics (SPO) mirror modules. Arranged in concentric annuli and following a Wolter-Schwartzschild design, the mirror modules are made of several tens of grazing incidence primary-secondary mirror pairs, each mirror made of silicon, coated to increase the effective area of the system, and shaped to bring the incoming photons to a common focus 12 m away. The mission aims to deliver a half-energy width of 5" and an effective area of about 1.4 m 2 at 1 keV.We present the status of the optics technology, and illustrate recent X-ray results and the progress made on the environmental testing, manufacturing and assembly aspects of the optics.

The application of machine learning based decision making systems in safety critical areas requires reliable high certainty predictions. Reject options are a common way of ensuring a sufficiently high certainty of predictions. While being able to reject uncertain samples is important, it is also of importance to be able to explain why a particular sample was rejected. However, explaining reject options is still an open problem. We propose a model-agnostic method for locally explaining reject options by means of interpretable models and counterfactual explanations.

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