Turbulent flows can exhibit extreme events, which are characterized by sudden bursts in the system observables. These events pose significant challenges for prediction and control owing to their intermittent, high-dimensional, and strongly nonlinear nature. In this work we present a predominantly data-driven control framework for the suppression of extreme events in turbulent flows, leveraging reduced-order modeling for nonlinear compression of high-dimensional flow fields and a data-driven clustering algorithm for the identification of precursors to extreme events. A control law is defined in the low-dimensional latent space and is optimized to efficiently mitigate extreme events through actuation values associated with the preidentified clusters. To address issues in the latent space structure that arise from invariance transformations present in many nonlinear systems, leading to an inflated latent space, we employ symmetry-aware autoencoders to establish a more structured and compact latent space. By analyzing high-fidelity simulations of a canonical chaotic flow (Kolmogorov flow), we demonstrate how the resulting closed-loop dynamics exhibit a substantial reduction (up to ca. 99.4%) in the frequency and intensity of extreme events. The framework exhibits scalability to a more chaotic flow regime characterized by higher Reynolds number without encountering numerical instabilities, achieving a 96.9% reduction in the occurrence of extreme events. The ability to incorporate controller limitations, including actuator latency relevant to practical applications of the framework, has also been demonstrated. This study highlights the efficacy of data-driven methods that require little to no prior knowledge of the underlying system dynamics to achieve effective flow control, thereby providing a pathway for general real-time suppression of extreme events in turbulent flows.

Within the framework of European Union-funded Clean Aviation and TheMa4HERA (Thermal Management for the Hybrid Electric Regional Aircraft) projects, a preliminary performance prediction and design tool for centrifugal compressors has been developed, targeting the turbomachinery components used in environmental control systems (ECS) in short/medium-range types of aircraft. This tool is an integral part of the objective to establish a complete optimization methodology for the performance assessment and sizing of air generation systems for next-generation aircraft. The methodology is based on mean-line analysis for the impeller, vaneless and vaned (including variable-vaned) diffusers, and volute, with a two-zone approach for the flow analysis in the vaned diffuser passage. The results of the model are validated against experimental data related to two different open-source compressor designs with both diffuser types. It is concluded from these cases that, for the purpose of the design tool, the model provides accurate results for the impeller and both diffuser types. Extreme conditions such as stall and choke remain difficult to accurately predict due to the complex three-dimensional nature of these phenomena. Future developments of the tool will include modeling capabilities for radial turbines and heat exchangers.

Liquid hydrogen-powered aircraft (LH₂ aircraft) offer the potential for a zero-carbon footprint when hydrogen is produced from renewable sources. However, integrating LH₂ aircraft into the air transport system is complex due to differences in LH₂ supply availability and varying levels of airport readiness. To address these disparities and comply with anticipated sustainability regulations, hydrogen tankering can serve as a temporary strategy by carrying additional hydrogen to avoid refueling at destinations lacking LH₂ capabilities. This study presents a novel model that evaluates the potential of tankering while accounting for its interaction with strategic LH₂ infrastructure placement, tactical flight scheduling, and operational aircraft routing. Applying the framework to a real-world case in the Baltic Sea region reveals trade-offs between system costs and environmental benefits under different regulatory measures.

Despite the popularity of multidirectional laminates in many fatigue-prone design applications, there is still little understanding of how the adjacent plies’ fibre orientation affects interfacial crack (delamination) fatigue propagation. To expand our knowledge on this matter, we present a systematic experimental investigation of the delamination growth behaviour for different interfaces and under different opening modes. In mode I, off-axis plies (as in 90//0 and 45//0 interfaces) increase the effects of fibre bridging, shifting the Paris curves to higher strain energy release rates (SERR), and thus making the 0//0 results (highly) conservative. Instead, in the presence of mixed mode, the Paris curves of 0//0 interfaces were not conservative in case of low SERR and low crack growth rates. These effects need to be accounted for when predicting the fatigue behaviour of a multidirectional laminate.