This article presents a new implicit coupling procedure for mechanical contact simulations using an implicit cell‐centred finite volume method. Both contact boundaries are treated as Neumann conditions, where the prescribed contact force is calculated using a penalty law, which is linearised and updated within the iterative solution procedure. Compared to the currently available explicit treatment, the implicit treatment offers better efficiency for the same accuracy. This is achieved with the proposed implicit linearisation, which replaces the explicit under‐relaxation of the contact force. The proposed procedure, intended for frictionless contact of Hookean solids, can handle non‐conformal contact interface discretisations and faces in partial contact. The accuracy and efficiency of the implicit approach are compared with the explicit procedure on four benchmark problems, where it is shown that the proposed method can significantly improve efficiency and robustness.

This study employs a high-fidelity numerical approach to simulate fluid–structure interaction phenomena for the dynamic response of flexible hyperelastic morphing wing structures under low aerodynamic loads. The computations are performed using the open-source solids4Foam toolbox, employing a partitioned two-way fluid–structure interaction approach with a finite volume solver for both fluid and solid. The considered morphing wing is divided into a flexible and a rigid segment, with the flexible segment featuring a 60% chord length and being made of a hyperelastic rubber-like material. The concept of damping is incorporated into the solid momentum balance equation as a virtual force that opposes the velocity of the structure. Damping is employed to disperse energy from the system, hence mitigating the oscillations and reducing computational time. To understand morphing wing aerodynamics and aeroelasticity behavior, a series of tests are conducted at low and medium Reynolds numbers, specifically 2×105 and 5×105. The results show that, for low Reynolds number, the morphing structure has a negligible impact on aerodynamic behavior. However, at higher Reynolds numbers, morphing results in improved aerodynamic efficiency at low angles of attack. Overall, the study highlights the aero-structural behavior of hyperelastic morphing wings and their potential for developing efficient and adaptive wing structures, highlighting their promise for future aircraft design innovations.

Air-to-water heat pumps (ASHPs) are a key technology for residential heating decarbonization; however, their seasonal performance is highly sensitive to outdoor temperature variability. Although thermal energy storage (TES) is widely recognized as a means of improving system efficiency, reported performance gains vary due to differences in climatic datasets, control strategies, and modeling assumptions. This study presents a systematic multi-year assessment of the impact of a water-based TES tank on the seasonal performance of a residential ASHP under measured microclimatic conditions. Hourly simulations were conducted for a single-family house at three locations in eastern Croatia using eight years (2018–2025) of measured meteorological data. Building characteristics, system configuration, and operating strategy were kept identical to isolate the influence of storage volume. TES integration reduced annual electricity consumption by 4.8–9.1%, with a multi-year average reduction of 7.02%, and consistently increased the seasonal coefficient of performance (SCOP) across all analyzed years and locations. The highest relative improvements occurred under less favorable microclimatic conditions, emphasizing the importance of diurnal temperature distribution rather than seasonal averages alone. A parametric analysis identified an optimal storage volume of approximately 1000–1500 L when both energy and economic indicators are considered. The results demonstrate that stable and reproducible seasonal efficiency gains can be achieved through a simple, non-predictive operating strategy under continental climatic variability.