Heat and moisture simulation for buildings (HAM simulation) has been increasingly used in recent years to suggest appropriate retrofitting and operational methods. This simulation requires various information, including material properties related to heat and moisture in the building structure, and flow characteristics related to ventilation and leakage. However, estimating these characteristics is not easy to estimate. The final goal of our study is to estimate these characteristics using a neural network trained by environmental measurement data in buildings.

As we know that air flow in buildings can be observed by tracer gases such as CO₂, but the air flow itself is derived from differences in air pressure and temperature between rooms. Therefore, this paper focuses on how to estimate the ventilation rates in a single room using a neural network with constraints based on a mathematical model, as a first step. In this paper, we proposed two kinds of neural network model. One estimates the CO₂ concentration changes in buildings from time data. The other estimates ventilation rates using the estimated results of CO₂ concentration. The former neural network is optimized using data constraints based on measurement data, while the latter neural network is optimized using physical constraints based on a mathematical theory, such as law of conservation of mass, to ensure the validity of the output, called as Physics Informed Neural Networks (PINNs). The trained results are as follows. The accuracy of the estimated CO₂ concentration changes in buildings is enough, and the estimated ventilation rates are mostly consistent with the analytical solution. Based on these results, we will consider the multi-room ventilation rates and estimate the flow characteristics by adding the temperature data in buildings.

Italian university students spend a significant part of their daytime inside classrooms without controlled mechanical ventilation. Poor Indoor Air Quality (IAQ) can lead to both long-term and short-term health issues. Carbon dioxide (CO2) concentrations are usually used as a key indicator of IAQ in buildings and numerous scientific studies reported that prolonged exposure to relevant CO2 levels can cause headaches, drowsiness and concentration difficulties (which are crucial in learning environments). In this study CO2 concentrations inside three different classrooms of the Department of Architecture and Industrial Design of the University of Campania Luigi Vanvitelli (Aversa, southern Italy) have been measured with a time-step of 1 minute during lectures (lasting between 2 and 5 hours) carried out during spring and winter. The analyses have been carried out in classrooms without mechanical ventilation differing in terms of floor area, volume, number and area of openings, number of occupants per unit area (between 0.19 and 0.29 persons/m2) and per unit volume (between 0.03 and 0.06 persons/m3). The effects of natural ventilation via manual opening of windows and doors on CO2 concentration-time data have been also evaluated. The measurements showed that the presence of occupants increases CO2 concentrations with a rate ranging between 230 and 476 ppm after 30 minutes, achieving absolute values larger than 800 ppm after about 16÷38 minutes. The experimental data also showed that manual airing via opening doors and windows for a period of about 13÷26 minutes can be an effective strategy to mitigate CO2 concentrations down to outdoor values.

This paper examines the effectiveness of different window opening configurations for single-sided ventilation. The study's results were obtained through monitoring in a test building located in Lower Austria. Initial findings from the summer and winter testing periods in 2024 are presented and used to evaluate various models employed in simulation tools to estimate air change rates in single-sided window ventilation. These models are commonly used in simulations that assess indoor thermal comfort, air quality, and overall building performance. While ventilation plays a critical role in these simulations, few studies have focused on validating ventilation models. Ventilation issues are often suspected to contribute to the performance gap between simulated results and actual outcomes. A range of standards and recent scientific research offer different models for estimating air change rates, requiring various input parameters related to room and outdoor conditions. This paper assesses the reliability of air change rates derived from common estimation methods, using data from a test room in the study building. Tracer gas measurements were conducted across multiple window opening configurations, and air change rates were calculated based on the concentration decay of the tracer gas. The findings provide validation and verification of simulation results, offering recommendations for selecting the most accurate models based on the study's experiments.

This paper presents the ventilation effectiveness of a novel sliding window, based on tracer gas measurement results and corresponding CFD simulations for single-sided ventilation. Monitoring efforts in a test building in Lower Austria formed the foundation for evaluating CFD models in OpenFOAM. The study assesses the accuracy of simulated air exchange using data collected from short-duration single-sided ventilation in a test room during the 2024/2025 heating season. Building on this knowledge, a virtual test room was utilized to analyze air movement, air exchange, and the resulting thermal comfort in detail. Additionally, the study thoroughly examines the placement of air quality sensors, considering automated window ventilation

Data-driven Automated Fault Detection and Diagnosis (AFDD) has emerged as an innovative solution for optimizing the performance of heating, ventilation, and air-conditioning (HVAC) systems. This study presents a comprehensive dataset generated through a series of experiments conducted on a typical single-duct dual-fan constant air volume air-handling unit (AHU) serving a test room in southern Italy. The AHU performance has been analyzed under both faulty and normal scenarios during winter and summer. Eight artificially induced fan faults have been investigated: supply air fan (SAF) stuck at (i) 0%, (ii) 25%, (iii) 75% and (iv) 100% of its maximum velocity as well as return air fan (RAF) stuck at (v) 0%, (vi) 25%, (vii) 75% and (viii) 100% of its maximum velocity. The faulty AHU performance has been compared to the fault-free scenarios (with both fans operating at 50% of their maximum velocity) under identical boundary conditions to quantify deviations in terms of indoor thermo-hygrometric conditions, electric energy consumption, equivalent global CO2 emissions, and operational costs. With respect to normal operation, fans’ faults can cause an increase of daily total electricity demand, equivalent global CO2 emissions, and operating costs from a minimum of about 3% up to a maximum of approximately 110%. Moreover, they can reduce the time percentage during which indoor air relative humidity or temperature remains within the desired range from a minimum of about 0.2% up to a maximum of approximately 62.0%.

Air tightness in buildings is a critical parameter in the pursuit of energy-efficient and sustainable homes. Ensuring that a building envelope is airtight minimizes energy loss, reduces heating and cooling demands, mitigates the risk of moisture damage, and enhances indoor environmental quality. Currently, the construction industry predominantly relies on tapes and adhesives to achieve air tightness at overlaps and joints. However, field surveys have documented instances where these tape joints have failed, leading to slippage and compromised air tightness and resulting in increased air leakage. The failures origin could be mechanical loads working on the joint or poor workmanship while installing the tape and joining the foil layers.

This project aims to systematically investigate the small but persistent loads that tape joints endure over extended periods due to ventilation and wind exposure. By characterizing these loads, we can better predict the long-term performance and durability of tape and adhesive systems used in building construction. Our methodology involves independent testing of various material combinations, including both foil and tape, under both laboratory-scale and full-scale wall conditions. This dual-scale approach allows for a comprehensive evaluation of material performance under controlled conditions and realistic scenarios. In addition to the testing of materials, an interview study among craftsmen regarding tape installation instructions provides valuable insight into real conditions.

The results from material tests show significant differences in air tightness between the investigated systems in both wall-sized scale and laboratory-scale. The interview study reveals a major deficiency in the use and compliance with the installation instructions.

The empirical data from the project will be utilized to develop a risk evaluation tool. This tool will enable builders and contractors to assess the potential risks associated with different tape and adhesive products, facilitating more informed material selection decisions. Furthermore, we are developing a digital educational package specifically designed for builders of single-family homes.

By integrating rigorous empirical testing with practical educational resources, this project aims to enhance the overall quality and sustainability of building construction. The goal is to mitigate air leakage, improve energy efficiency, minimize moisture damage, and contribute to the development of sustainable residential buildings. Through this initiative, we seek to equip builders with the knowledge and tools necessary to achieve superior air tightness and construct homes that are both energy-efficient and sustainable.