Added resistance in waves is one of the main causes of an increase in required power when a ship operates in actual service conditions. The assessment of added resistance in waves is important from both an economic and environmental point of view, owing to increasingly stringent rules set by the International Maritime Organization (IMO) with the aim to reduce CO₂ emission by ships. For that reason, it is desirable to evaluate the added resistance in waves already in the preliminary ship design stage both in regular and irregular waves. Ships are traditionally designed and optimized with respect to calm water conditions. Within this research, the effect of prismatic coefficient, longitudinal position of the centre of buoyancy, trim, pitch radius of gyration, and ship speed on added resistance is investigated for the KCS (Kriso Container Ship) container ship in regular head waves and for different sea states. The calculations are performed using the 3D panel method based on Kelvin type Green function. The results for short waves are corrected to adequately take into account the diffraction component. The obtained results provide an insight into the effect of variation of ship characteristics on added resistance in waves.

One of the short-term operational measures for fuel savings and reducing CO₂ emissions from ships at sea is sailing at reduced speed, i.e., slow steaming, while the gasification of the ship represents an important mid-term technical measure. In this study, the energetic and ecological benefits of slow steaming and gasification are studied for a container ship sailing between Shanghai and Hamburg. Resistance and propulsion characteristics in calm water are calculated using computational fluid dynamics based on the viscous flow theory for a full-scale ship, while the added resistance in waves is calculated by applying potential flow theory. The propeller operating point is determined for the design and slow steaming speeds at sea states with the highest probability of occurrence through the investigated sailing route. Thereafter, the fuel consumption and CO₂ emissions are calculated for a selected dual fuel engine in fuel oil- and gas-supplying modes complying with IMO Tier II and Tier III requirements. The results demonstrate a significant reduction in fuel consumption and CO₂ emissions for various slow steaming speeds compared to the design speed at different sea states, and for the gasification of a container ship. For realistic weather conditions through the investigated route, the potential reduction in CO₂ emissions per year could be up to 11.66 kt/year for fuel oil mode and 8.53 kt/year for gas-operating mode. CO₂ emission reduction per year due to gasification under realistic weather conditions could be up to 22 kt/year.

The paper discusses the possibility of applying the trigeneration energy concept (cogeneration + absorption cooling) on diesel-powered refrigerated ships, based on systematic analyses of variable energy loads during the estimated life of the ship on a predefined navigation route. From a methodological point of view, mathematical modeling of predictable energy interactions of a ship with a realistic environment yields corresponding models of simultaneously occurring energy loads (propulsion, electrical and thermal), as well as the preferred trigenerational thermal effect (cooling and heating). Special emphasis is placed on the assessment of the upcoming total heat loads (refrigeration and heating) in live cargo air conditioning systems (unfrozen fruits and vegetables) as in ship accommodations. The obtained results indicate beneficiary energy, economic and environmental effects of the application of diesel engine trigeneration systems on ships intended for cargo transport whose storage temperatures range from −25 to 15 °C. Further analysis of trigeneration system application to the passenger ship air conditioning system indicates even greater achievable savings.

This paper analyzes the process of energy transition from traditional solid fuel heating to an air-to-air (A2A) heat pump-based heating system. Special emphasis was placed on the implementation of new technologies for improved management of energy systems aiming to elevate both comfort levels and energy efficiency. This paper explores the use of open-source Home Assistant software as an integration platform for home automation, designed to manage smart home devices while preserving local control, user privacy and increasing cybersecurity. The proposed hardware platform includes a Raspberry Pi with appropriate IoT modules, providing a flexible and economically viable solution for household needs.

This paper analyzes the process of energy transition from traditional solid fuel heating to an air-to-air (A2A) heat pump-based heating system. Special emphasis was placed on the implementation of new technologies for improved management of energy systems, aiming to elevate both comfort levels and energy efficiency. This paper explores the use of the open-source software Home Assistant as an integration platform for home automation, designed to manage smart home devices while preserving local control, user privacy, and increasing cybersecurity. The proposed hardware platform includes a Raspberry Pi with appropriate IoT modules, providing a flexible and economically viable solution for household needs.

Air-to-air heat pumps are a key technology for improving energy efficiency and reducing carbon emissions in residential buildings, yet their optimal control remains challenging under real-world conditions. This study evaluates the performance of a hybrid physical–LSTM model for controlling an air-to-air heat pump in a residential building in Zadar, Croatia. The hybrid framework integrates a first-order energy balance model of the building envelope with LSTM-based temperature correction using adaptive weighting. The physical model was calibrated and validated against 52,128 real IoT measurements collected during the 2024/2025 heating season, achieving high accuracy (RMSE ≈ 0.076 °C). Rolling one-day and continuous multi-day closed-loop simulations (up to 15 days) show that the hybrid model yields slightly lower RMSE in long-term runs compared to the pure physical model. However, this apparent statistical improvement is accompanied by systematic underestimation of indoor temperature and significantly higher simulated energy consumption. The results indicate that the observed effect originates from an implicit virtual heat flux introduced by the LSTM correction, which affects thermodynamic consistency in closed-loop operation. The findings highlight that short-term error metrics such as RMSE alone are insufficient for evaluating hybrid models intended for model predictive control (MPC). The main contribution of this study is the explicit demonstration and quantification of an implicit virtual heat flux generated by the LSTM correction in closed-loop multi-day operation, which leads to misleading statistical improvements while causing significant thermodynamic inconsistency and energy overconsumption. In 15-day continuous simulations the hybrid model (ω = 0.05–0.10) caused an indoor temperature underestimation of 1.25–1.31 °C and increased simulated electricity consumption by more than 300% (316 kWh vs. 72 kWh) compared to the physical model. These results have direct implications for the development of reliable digital twins and model predictive control strategies in residential HVAC systems.