Numerical investigation for turbulent flow of nanofluid (Ethylene glycol/water-Al2O3) is carried out with a volume fraction of 0.5%, 1%, and 1.5%. The diameter of solid nanoparticles is equal to 20 nm. The range of Reynolds number in this simulation is from 6300 to 27500 through a three-dimensional steel corrugated spirally tube. For enhancement of the heat transfer performance in internal flow through the horizontal tube, the tube is combined with aluminum twist tape of a thickness of 0.8 mm and a width of 10 mm along the spirally corrugated tube. In the present work, the same twisted ratios TR=(y/w) are implemented for corrugated tube and tape. The predicted results showed that there is a clear increase in the values of heat transfer and the pressure drop in the direction of flow. Furthermore, the friction factor is increased because of the grooved and twisted tape which rise the resistance of the fluid flow. The values of Nusselt number are increased with the VOF of nanofluid. These numerical results are compared with the experiment found in the literature and showed a good agreement.

The importance of mitigating energy intensity in the building sector is widely recognized by most stakeholders, and different strategies are proposed for minimizing fossil fuel dependency. This paper presents a complex study assessing the possibility of integrating an air-source heat pump (ASHP) into the retrofitting process of a typical Romanian residential building. Mathematical simulations were conducted to estimate the energy reduction potential of a complex renewable-energy-based HVAC system. The results showed that a more than 50% increase in energy efficiency could be obtained by using the right insulation materials, and the building’s fossil fuel dependency could be curbed by 75% by integrating the proposed renewable energy systems.

An optimization model that may be applied to analyze building retrofit strategies is presented in this research. The aim of this research paper is to identify the optimal thermal envelope configuration that will assure the minimum energy requirement for heating in the case of a residential building, while also considering price restrictions obtained through a specific market survey. To achieve this, several values for the following parameters are considered: thermal insulation materials’ conductivities and thicknesses, windows’ overall heat transfer coefficients and total solar energy transmittance and doors’ thermal proprieties. Additionally, this paper presents a method used to find the best option from among the available heat pumps that could cover most of the energy requirements for heating and domestic hot water systems, also considering the products’ prices. The proposed method is based on a Non-dominated Sorting Genetic Algorithm II (NSGA-II) model developed in the Pymoo (Multi-Objective Optimization in Python) library. The result shows that the energy requirement for heating can be reduced by up to approximately 75% compared to that obtained in the case of a non-insulated building by using suitable insulation materials and doors and windows with superior thermal proprieties chosen by the NSGA-II.

The European Legislation is very strict regarding the importance of reducing the energy consumption in buildings sector. The importance of achieving nearly zero energy consumption levels for both new and existing buildings is also highlighted in each Members’ national legislation. Moreover, the high percentage of existing buildings across European Union, indicates that they need to be adequately approached in order to achieve the ambitious energy efficiency goals. This implies creating the optimal technical and financial retrofit strategies regarding minimizing the energy consumption without lowering the interior comfort levels. In Romania, there is no unitary strategy aiming to maximize the energy efficiency in buildings which also takes into consideration the financial part of the process. Moreover, there are no known national guidelines and strategies for buildings retrofit which takes into consideration a wide range of equipment. The Romanian Energy Efficiency Strategy presents few possibilities resulted from integrating renewable energy sources within typical Romanian buildings, while the Buildings Performance Institute Europe conducted a research regarding the potential of nearly Zero Energy Buildings implementation across Romanian territory. Both studies refer only to typical buildings and do not present a large perspective for retrofitting action, while the financial study is not properly presented. Thus, this paper develops a comprehensive financial study which could be used as guideline by stakeholders, in order to find the best technical solution for decreasing the final energy consumption in Romanian residential buildings. Using the RETScreen software and its economical features, there were developed several energy efficiency solutions, and by analyzing the financial benefits implied, the best solution was chosen. By adopting the solutions presented within this feasibility study, the energy consumption of buildings should be significantly reduced.

This paper presents the HESTIA Digital Twin (DT), a control-oriented digital-physical architecture for real-time state estimation of a multi-source hybrid HVAC system. This experimental infrastructure integrates an air-source heat pump (ASHP), a methane gas condensing boiler, a puffer storage tank, and a rooftop photovoltaic array. The DT is organized as a four-layer hierarchical architecture encompassing physical instrumentation, data acquisition, model computation, and data visualization. The Model and Decision Layer is composed of three independent predictive sub-models: a Physics-Informed Neural Network (PINN) for ASHP performance prediction, a semi-empirical model for the gas boiler analysis, and three-node stratified ordinary differential equation model for the puffer tank. For the PV energy production data from the inverted was considered. A total seven-mode finite state machine encodes the economic dispatch logic, dynamically adapting the heat pump competitiveness threshold to prevailing electricity and gas tariffs. The ASHP PINN enforces four structural thermodynamic constraints, and the model was trained on 7,389 datapoints and 3,060 EN 14511 certified references obtained from two open-source databases. On the held-out test set, the model achieves R² = 0.796, MAE = 0.351, and RMSE = 0.515 for COP prediction, R² = 0.957 (MAE = 0.219 kW) for thermal output, and R² = 0.917 (MAE = 0.126 kW) for electrical power consumption, with zero violations of the Carnot upper bound recorded across all test samples. The gas boiler model reproduces manufacturer- declared efficiencies of 97% and 105% at the rated condensing and non-condensing operating conditions, with deviations below 2%.