Energy renovation in historic buildings requires balancing architectural, historical, and esthetic preservation with eco-friendly and sustainable refurbishment. This study develops a novel bio-based polyurethane (bio-PUR) foam and evaluates its thermal and mechanical properties through laboratory tests, real-scale applications, and numerical simulations. Laboratory tests show that bio-PUR has higher mechanical strength than conventional PUR and comparable thermal performance, with a thermal conductivity of 0.036 W/mK, confirmed using nitrogen thermal control. A real-scale test, conducted in a laboratory at the University of Sannio in wintertime, validated the material's performance, showing only a 4% deviation from theoretical thermal transmittance values and consistent heat flux data. Numerical simulations applied bio-PUR foam in two historical buildings in Milan and Naples, comparing it to traditional insulation materials. Primary energy demand for heating is reduced in both climates, with a slight higher efficacy for traditional PUR, because of its lower thermal conductivity. Similar trends were observed in summer season. Indoor air temperature analysis revealed improved thermal stability with bio-PUR in winter, while potential overheating in summer can occur under free-running conditions. Overall, bio-based PUR foam provides competitive thermal properties and environmental benefits, resulting in a promising solution for the green, resilient, and sustainable renovation of heritage buildings.

Integrating PV, BESS, and SOFC technologies offers a pathway to resilient, low-carbon residential energy. This study utilizes a multi-objective optimization framework incorporating real-world SOFC data, battery health indices, and climate projections for 2050/2080. Focusing on a Southern Italian dwelling, it evaluates building retrofits, varying system capacities, and four SOFC operational strategies. Findings reveal that building retrofitting is paramount, reducing energy demand by up to 48%, surpassing the impact of expanded PV capacity. The most energy-autonomous setup features a 3.3 kW PV array, 30 kWh BESS, and a variable winter-only SOFC strategy, successfully balancing grid independence with minimized battery degradation. Economically, current hydrogen prices favor maximizing solar and battery storage while minimizing fuel cell use, underscoring the need for hydrogen incentives. Climate change is projected to escalate cooling loads, shifting optimal designs and marginally reducing battery health over time. By bridging real-world performance data with climate-responsive, health-aware optimization, this work provides critical insights for designing hydrogen-compatible residential systems. The results emphasize that policy support and climate-adaptive designs are essential for ensuring the long-term sustainability and resilience of integrated residential energy solutions.

Cancer is still one of the most dangerous threats to public health. Particularly, among others, hepatocellular carcinoma is one of the most recurrent. Since surgical resection and transplantation are often not viable solutions, and chemotherapy or radiotherapy have several drawbacks for patients' health, new alternatives are spreading. A promising example is hyperthermia-mediated drug delivery using thermo-sensitive liposomes (TSLs), which allows targeting drug concentrations within the tumor, avoiding its spread in healthy tissue. To ensure the proper temperature range in the target and avoid thermal damage, it is fundamental to control the heat administration in the tissue, which is here provided by means of a microwave heating device. Different heating strategies-namely continuous, pulsed, and PID-controlled-have been numerically simulated to find the most effective thermal management protocol. A Computational Fluid Dynamics model is developed, coupling Pennes' bioheat equation for heat transfer, a convection-diffusion model for drug delivery, and Maxwell's equations to simulate microwave propagation. The results show that PID-controlled heating ensures optimal temperature regulation, avoids overheating, and maximizes drug internalization. Compared to traditional fixedpower protocols, the PID controller dynamically adjusts power input based on real-time feedback, ensuring a consistent thermal profile. This minimizes thermal damage to healthy tissue while enhancing the therapeutic effect. The comparison highlights that PID-based control achieves a more uniform spatial drug distribution, limits necrotic effects, and improves overall treatment efficiency. This approach demonstrates significant promise for improving the safety and efficacy of hyperthermia-enhanced chemotherapy in hepatocellular carcinoma treatments.

The sustainability objective in the building sector requires that the design of the built environment would address not only the environmental and energy aspects, but also the human dimension of its operation. On the other side, the operative phase of the building covers the longest time in its whole life cycle and thus it is important to evaluate the global quality after the construction taking into consideration the occupants' perspective. At this aim, the paper introduces a new multi-domain approach for studying the global quality of the buildings certified as nearly zero energy and it is applied to verify the feasibility of a case study in Mediterranean climate. The method is based on five criteria about both indoor comfort that energy aspects and it introduces a weighing procedure based on the answers of occupant's sample about the relative importance of criteria for residential usage. About it, the size and one-vote veto effects of individual factor satisfaction on overall quality are discussed. Results indicate that occupants are more sensible sensitive to indoor air quality and thermo-hygrometric aspects than renewable integration or building energy consumption. The maximum score reached for the analysed nearly zero energy building is 8.4 (up to 10) but there is a remarkable variation with the weight attributed to each criterion.

Magnetic hyperthermia (MHT) is a promising cancer treatment that exploits the heating capabilities of magnetic nanoparticles (MNPs) when exposed to alternating magnetic fields. The primary challenge in optimizing MHT lies in understanding the influence of MNP distribution within the tumor microenvironment. This study presents realistic simulations of MNP distribution within a tumor, accounting for diffusion, convection, and internalization dynamics, alongside the presence of a necrotic core. Additionally, a vascular network was modeled based on diagnostic images to assess its impact on nanoparticle behavior and heat generation within the tumor. Our results show that uneven MNP distribution, particularly in areas influenced by the tumor's vasculature and necrotic regions, results in highly variable temperature profiles and irregular thermal damage. By contrast, a more uniform distribution of MNPs leads to a consistent rise in temperature and a broader region of thermal damage, with maximum temperatures reaching 47 degrees C and 99 % tumor cell death after 60 min of treatment. Key quantitative findings indicate that the tumor's vascular architecture plays a crucial role in determining the heat distribution and treatment efficacy. This study highlights the importance of fine-tuning MNP delivery and distribution to maximize therapeutic outcomes in MHT. The approach offers significant potential for applications in treating deep-seated or inoperable tumors, where precise and localized therapy is critical.

The use of highly efficient cogeneration systems fueled by pure hydrogen, such as Solid Oxide Fuel Cells (SOFCs) in the residential sector, is one of the new frontiers for achieving the net zero greenhouse gas emissions transitions. The lack of experimental studies in this area prompted the authors to propose the present paper. It refers to hydrogen-fueled SOFC 1 kW-sized, integrated into the plant system of a single-family villa configurated as a nearly Zero Energy Building. The multiple objectives are: show the technical feasibility of this technology in building; analyse the data of a continuous monitoring campaign in wintertime; highlight the real performance compared to the manufacturer's declaration. The results demonstrate that, in particular conditions of photovoltaic production, it is possible to meet the home electric loads and have a surplus of energy to store or send to the national power grid. The calculated electrical efficiency is equal to 0.47 : 0.48, while the maximum overall efficiency is 0.93.

To achieve the ambitious decarbonisation targets of 2030 and 2050, there is a need to diversify energy sources and apply a multi-technological approach aware of the different characteristics of buildings. In this context, the introduction of hydrogen technologies plays a key role, especially if the on-site production of green hydrogen is considered, by means of an electrolyser, and its storage and use by means of fuel cells. This system is identified as a power-to-power system. The presented work focuses on the definition of photovoltaic producibility and electrical load curves describing the behavior of residential buildings, to be used as input data in a simulation model describing the power-to-power system. The starting point is the in-field measurements collected at the Hydrogen Zero Emission Building laboratory owned by the University of Sannio. These measurements concern a whole year of monitoring (from summer 2023 to summer 2024) during which the building was occupied by one or two PhD students. Based on these measurements, a numerical model of the HVAC-building system can be created using dynamic energy simulations, by means of dynamic energy simulations (using EnergyPlus engine). The second step is to calibrate the building model with methods based on standardized protocols, according to ASHRAE Guideline 14. Finally, it is possible to obtain photovoltaic production and electrical load curves, by varying parameters such as climate zone or occupancy. The results are a starting point for developing optimization analyses on the power-to-power system.

To face buildings overheating during the summer season a very promising alternative is represented by the ventilated facades. In this work, it is analyzed a special ventilated facade whose external layer consists of photovoltaic panels. Such a solution combines the advantage of an opaque ventilated facade (OVF) with the increase of the photovoltaic (PV) performance due to lower operating temperature. Indeed, the efficiency of the photovoltaic modules decreases with their temperature. The critical aspects concerning the modeling of this component are investigated, and alternative cases are also compared, by considering both winter and summer conditions. The radiative characteristics of the photovoltaic panels are not typically reported on technical data sheets. The solar radiation absorption coefficient is an unprovided data that however profoundly affects the behavior of the system. Hereinafter a CFD model is presented to replicate the configuration of the wall of the new lab called H-MOLISE. Thermal, fluid-dynamics, and energy analyses demonstrate the effects of the radiative characteristics and environmental conditions (global incident radiation and outdoor air temperature) on system temperature (PV and air gap), air movement and PV efficiency. With a solar radiation of 600 W/m(2) and an outdoor temperature of 35 degrees C the average temperature of the modules increases of around 7 degrees C while the efficiency reduces from 0.185 to 0.179 by changing their absorption coefficient from 0.7 to 0.9.

Accurately estimating a building’s energy demand is fundamental for optimizing energy management and promoting energy efficiency. This study focuses on an in-house developed method for annual energy demand estimation, which relies on 30 key input parameters to predict energy consumption. While this approach is effective for long-term assessments, it lacks the temporal resolution required for applications that demand a more dynamic analysis, such as the creation of energy communities and smart energy systems. To address this limitation, an alternative methodology has been developed by scaling down an in-house annual estimation method and adapting it for hourly calculations, specifically for heating demand. In addition to comparing the results of the annual and hourly approaches, this study further investigates each individual contribution to heating demand—namely, heat transmission, ventilation losses, internal heat gains, and solar gains—by disaggregating them and scaling them on an hourly basis. This detailed analysis allows for a more precise representation of short-term variations in energy demand and highlights the limitations of aggregated annual estimates, to support the development of renewable energy communities, based on hour-ahead thermal and electric loads’ estimation. The findings demonstrate the advantages of a higher-resolution approach and represent the first step in developing a flexible and robust tool capable of estimating both annual and hourly energy needs. Such a tool can be particularly useful for integrating renewable energy sources, optimizing demand-side management strategies, and supporting the development of energy communities, where precise energy profiling is crucial for improving efficiency and sustainability.

Indoor environmental quality is a key objective in the building performance improvement. After the COVID-19 emergency, a lot of healthcare facilities are working to improve the design of air emitter and their management. However, in the existing structure, the scientific literature underlines the lack of methodologies for the evaluation of the state of fact in term of air quality and influence of position or adoption of heating, cooling and ventilation systems mainly in the patient rooms. Thus, the paper, by means of a case study, is aimed to highlight the potentialities of computational fluid dynamic based map for studying the air distribution and the incidence of external and internal forcing in the patient rooms focusing on the positive role that the mechanical ventilation could have in the reduction of infections and in the improvement of environmental conditions. Starting form monitored data in a patient’s room of “A. Cardarelli” hospital of Campobasso (city of central Italy) a numerical model was calibrated through the Design Builder graphic interface of Energy Plus. According to the results of the study, the type of diffusers and the location of the exhaust fans influence the airflow patterns. Since there is a wide variety of parameters that define each room, among these also the outdoor conditions, it is not possible to reach a general conclusion on the optimal room design and supply and exhaust locations.

Blood flow and thermal analyses in biological tissues are utterly important to better understand the transport phenomena in human tissues with reference to cardiovascular diseases, drug delivery, and thermal ablation. In the existing literature, there is room for new computationally lighter numerical analyses, including both fluid flow and heat transfer. This paper presents an analysis of blood thermo-fluid dynamics within an automatically generated two-dimensional (2D) vascular network, employing the constrained constructive optimization algorithm for structure generation, the porous media assumption for outflow boundary conditions, and heat transfer coefficient analysis for terminal vessels. Through comparisons with theoretical results, the model demonstrates mathematical robustness. Results of the simulations show that blood velocity decreases with increasing number of bifurcations, offering quantitative insights into its decay in magnitude and on its impact on heat transfer. Blood temperature rises in vessels with low velocity, hindering its cooling effects in the surrounding tissues. The study highlights the influence of bifurcation levels on heat transfer coefficient reduction, suggesting longer pathways and time periods to reach high temperature within the blood vessels, due to the cooling effect of pulsating blood flow in larger vessels. The quantitative analysis of the heat transfer coefficient and Nusselt number provides insights into heat transfer between blood and the surrounding tissue, offering also valuable information for numerical bioheat models in thermal therapy simulations.

BACKGROUND AND OBJECTIVES:Prostate cancer is the most common form of cancer in the male population. While the survival rate is high, many patients undergo surgical procedures for prostate cancer that might never progress to clinical significance. As a result, minimally invasive therapies are increasingly preferred over chemotherapy, radiotherapy, or surgical interventions. Laser-induced hyperthermia is emerging as a promising minimally invasive technique that targets tumoral tissue without damaging the surrounding healthy prostate. However, the lack of a standardized protocol makes the procedure highly dependent on the surgeon's expertise. Indeed, besides the cancerous tissue, also the healthy one could be heated and undergo a necrosis. Consequently, two contrasting objectives have to be considered during the treatment design: to treat cancer without damaging healthy tissue. Therefore, in this work, a thorough multi-objective optimization is carried out with reference to the laser-induced thermal ablation framework for prostate tumors. This is achieved by coupling finite element simulations with a genetic algorithm-based optimization to identify the best settings for the procedure. METHODS:A multi-objective optimization was conducted to determine the optimal settings for decision variables to achieve the best outcomes. The procedure was executed by the direct coupling between the genetic algorithm which continuously updated the decision variables, for the optimization, and a finite element commercial code to predict variables. The decision variables employed as input for the model were: procedure time, number of laser probes, their position, dimensions, delivered power, and the number of ON/OFF cycles. Pennes' bioheat equation was employed to obtain the desired objective functions, say thermal damage in the tumor tissue and healthy prostate, to be maximized and minimized, respectively. Additionally, linear regression and Bayesian artificial neural networks were developed to correlate the design variables with the objective functions, providing a tool for optimizing treatment planning. RESULTS:Results demonstrate that the multi-objective genetic algorithm is a powerful tool for selecting the optimal settings for treatment. By applying the utopian criterion, the best trade off is achieved, since the optimal solution is the one allowing for a complete tumor necrosis with an acceptable damage rate to the healthy prostate (188 mm3). Linear regressions proved ineffective for predicting the objective functions, while artificial neural networks yielded better results. CONCLUSIONS:This study introduces an effective methodology for optimizing laser-induced thermal ablation for prostate tumors. By coupling genetic algorithms with finite element simulations, a set of optimal protocols (in terms of time and laser settings) can be selected, ensuring maximal tumor necrosis with minimal damage to the healthy prostate. This approach assists surgeons in protocol planning and reduces uncertainty in outcomes.

This study presents an approach to the multi-objective optimization of hyperthermia-mediated drug delivery using thermo-sensitive liposomes (TSLs) for the treatment of hepatocellular carcinoma. The research focuses on addressing the non-optimal coupling methods that combine thermal treatments and chemotherapy by employing a Multi-Objective Genetic Algorithm (MOGA) optimization process, in order to identify the right combination of design variables to achieve better treatment outcomes. The proposed model integrates Computational Fluid Dynamics (CFD) analysis using the Pennes’ Bioheat equation for tissue heating and a convection-diffusion model for drug delivery. The goal is to maximize the fraction of killed cancer cells through the pharmaceutical treatment while minimizing thermal damage to the tissue, aiming to not hinder the drug feeding from the vascular system. The optimization considers several design variables, including heating power, timing, and the number of antenna slots for the microwave heating. Simulations results suggest that a two-slots antenna configuration with a specific heating schedule yields optimal therapeutic outcomes by maximizing drug concentration in the tumor while limiting damage to healthy tissue. The results of the CFD analysis also show a significant improvement in the treatment outcomes compared to non-optimized results proposed previously in the literature, leading to an increase from the 10 % up to the 33 % for the fraction of killed cells function. The proposed optimization through Genetic Algorithm framework could significantly improve patient-specific treatment planning for hyperthermia-mediated drug delivery.

Prostate cancer is one of the most recurrent forms of cancer in men, occurring in peripheral zones. Laser ablation is an emerging non-invasive protocol for this disease, offering the possibility to preserve the prostate proper functioning. However, due to shortage of in-vivo experiments, for ethical and practical reasons, it is difficult to properly design the treatment, leading to incomplete tumor destruction and metastasis development, owed to inappropriate exposure time or laser intensity. Consequently, it is of primary importance to develop accurate models to aid and provide guidelines to surgeons, towards a treatment optimization. For these reasons, in this paper an accurate model has been developed and solved through the finite elements commercial software Comsol Multiphysics. A 2D domain, representative of the tumor inside the prostate, has been investigated, using the porous media approach. According to the Local Thermal Non-Equilibrium (LTNE) assumption, the tissue and the blood are treated as two distinct entities having different thermal properties and behavior. The laser source has been described by means of the Beer-Lambert’s law, assuming a Gaussian laser distribution. To find the optimal laser setting to achieve the maximum tumor destruction, the effect of different laser intensity, and bare fiber diameter on temperature field and thermal damage is investigated.

Thermal therapies, such as laser ablation, are garnering interest for treating several diseases, in a non-invasive way, preventing surgical treatments and, for example, allowing the preservation of prostate functions in the case of prostate cancer. Nevertheless, approved therapies for cancer treatments are still missing, limiting the reliability of such methodologies, since an insufficient exposure time and thermal power settings could lead to incomplete tumor ablation, its redevelopment and metastasis occurrence. Consequently, it is fundamental to develop accurate bioheat transfer models providing guidelines to surgeons, helping to improve treatment effectiveness. However, as several models have been developed, the study aims to compare four bioheat transfer models, namely the simplified Pennes' approach, two porous media-based methods, i.e. the Local Thermal Equilibrium and the Local Thermal Non-Equilibrium equations, and the non-Fourier approach, namely Dual Phase Lag equation. The effects of laser power, tissue porosity and blood vessels diameter are investigated. The finite elements (FEM) commercial software Comsol Multiphysics is employed to investigate a 2D axisymmetric domain, consisting of two concentric spheres (the tumor and the healthy tissue). The laser source is modeled with the Beer-Lambert's law, assuming a laser source with a gaussian distribution. Results in terms of temperature field and necrotic region are presented, developing linear correlations by fitting FEM results. Finally, the difference among the necrotic areas predicted with the different approaches is reported, providing high discrepancies especially for highly vascularized tissue, with a lower damaged surface predicted in case of porous media approaches.

The definition and evaluation of thermo-hygrometric comfort conditions in a moderate environment is a topic to be addressed together with the building energy efficiency. Mainly in residential environments, the behavioral, physiological and psychological adaptations that people make to control indoor conditions greatly influence the thermal environment. However, their choices have direct impact on the HVAC system control strategies, often penalizing energy savings. In this paper these aspects are explored with reference to a bedroom of a real nZEB built in southern Italy. Based on an experimental campaign, the numerical model is calibrated and then a CFD analysis is carried out to calculate the air temperature and thermal comfort indices through a three-dimensional representation. On the basis of the extreme outdoor conditions observed during a typical winter month, the simulated traditional comfort results were compared with the 3D distributions. Different scenarios were also implemented for the operation of the HVAC system. The results show that the personal setpoint control can be a critical issue, especially during anomalous winter heat waves.

Indoor conditions in a confined space are the result of the interactions with the surrounding environments, air-conditioning effects, occupants' presence, and activities. The air-conditioning systems' role in controlling the microclimate became fundamental in the last years, but with the COVID-19 pandemic also their crucial task in contamination and infection diffusion emerged, especially in healthcare facilities. The idea of H-MOLISE (Healthcare Multi-Operative Lab for Innovative Structures and Equipment), whose setup is presented below, arose from these considerations. The new lab is under construction in Campobasso (Italy) at the University of Molise and it will aim to test innovative solutions for the envelope (ventilated facades, green roof, etc.) and active energy systems for advanced control of indoor conditions, as can be necessary in hospitals. In particular, it will be possible to simulate a real-scale operating block with an operating room compliant for the most advanced surgeries, or rooms of the civil sector. The lab will be equipped with a multitude of plants and terminals to evaluate their effects on indoor fluid dynamics, air quality, and thermal-hygrometric conditions. The lab plants will be reconfigurable and a dedicated monitoring and data acquisition system for the main quantities to be controlled will be installed.

Considering the current climatic and energy crisis, one of the simplest energy-saving practices most easily implemented during this winter is the reduction of operation hours of HVAC system and the reduction of set-point value of the room temperature. From an energy point of view the benefits are undoubted, but what does the occupants feel in terms of thermo-hygrometric comfort? Can other factors, such as lighting color or control affect it? In the literature discrepancies were found between the classic comfort assessment models (such as the Fanger static model) and the occupant’s sensations. This could, in fact, depend on other factors that influence the psychological and perceptive sphere of people. The present study aims to investigate in an experimental way these aspects that have not very been deep in the literature. The analysis is performed in a full-scale living-lab conceived as a nearly zero energy building, placed in Benevento, Southern Italy. It will be shown that the building occupant judges the environment warmer than the one described by a static thermal comfort model. If there are warm lights it is preferable to be controlled by the user while the cold lights are preferable to be controlled automatically.