CFD

Indoor air quality in schools is of critical importance for the health and well-being of pupils and staff. The COVID-19 pandemic highlighted the essential role that ventilation systems play in limiting the spread of airborne diseases and consumer CO2 monitors were deployed in UK classrooms as a cost-effective tool to help manage the ventilation supply. In such settings, which are occupied for long periods by the same group of people, CO2 measurements have also been used to infer the risk of far-field airborne infection.

In recent years, earth-to-air heat exchanger (EAHE) systems, which is a method of pre-cooling and pre-heating outdoor air with earth-to-air heat, have been attracting attention as one of the technologies to achieve ZEB. However, at the operational phase, in order to achieve both energy saving and suppression of dew condensation control, EAHE control methods such as the timing or amount of outdoor air introduction have not been established.

The accurate estimation of the local wind pressure coefficient is crucial in the numerical modeling of natural or mixed ventilation in buildings subjected to wind. Building ventilation modeling typically relies on average wind pressure coefficient values specific to the building façade and wind direction. While the literature provides some correlations and standards for building wall-average pressure coefficients, these values are only useful in the absence of additional information or a database, as they can vary significantly based on urban forms.

In office buildings, an air-conditioning system with natural ventilation can reduce cooling loads and create a comfortable indoor environment. However, it is difficult to predict the performance of such systems and there is concern that the natural ventilation will create an uneven indoor thermal environment. In this paper, we propose a method for evaluating the performance of a natural-ventilation air-conditioning system by coupling a building energy simulation tool and computational fluid dynamics.

Due to the negative effects of Particulate Matter exposure, more and more inexpensive optical aerosol spectrometers and photometers (low-cost PM sensors) are coming to the market, which are often used to monitor air quality. In addition to the low acquisition costs, these commercial PM sensors are characterized by low maintenance effort, which enable very high data availability in continuous operation. However, questions about the quality of the generated data often remain unanswered.

Heating, ventilating, and air conditioning (HVAC) systems attempt to achieve a uniform indoor environment. However, this can be challenging, because the placement and control of HVAC systems and sensors are affected by many unpredictable factors. The efficacious exploitation of this nonuniformity can lead to an improvement of indoor environment around occupants. Of the many indoor environment variables, we focused on the CO2 concentration associated with ventilation.

The sudden global outbreak of coronavirus diseases 2019 (COVID-19) has infected over seventy million people and resulted in over one million deaths by the end of 2020, posing a significant threat to human health. As potential carries of the novel coronavirus, exhaled airflow of infected individuals via coughs, are significant in virus transmission. This study measures human coughs' airflow velocity in a chamber filled with stage fog employing a particle image velocimetry (PIV) system.

Respiratory infections are transmitted by droplets and droplet nuclei generated by human coughing, sneezing, and talking. Droplets and droplet nuclei come out of the mouth simultaneously with airflow, and their dispersion characteristics are important to understand the transmission route of infection. It is crucial to understand the dispersion characteristics of droplets and droplet nuclei dispersion and infection routes through numerical analysis.

The COVID-19 pandemic has prompted huge efforts to further the scientific knowledge of indoor ventilation and its relationship to airborne infection risk. Exhaled infectious aerosols are spread and inhaled as a result of room airflow characteristics. Many calculation methods and assertions on relative airborne infection risk assume ‘well-mixed’ flow conditions.

A smart ventilation system is able to continually adjust itself to provide the desired indoor air quality (IAQ) while minimizing energy use, utility bills, thermal discomfort and noise. A smart ventilation system is also responsive to e.g. occupancy, outdoor conditions, direct sensing of contaminants and can provide information about e.g. IAQ, energy use and the need for maintenance or repair. Technically, all components for such systems are available in the market.