State-of-the-art methods for inverse design of an enclosed environment

Transmission mitigation of COVID-19: Exhaled contaminants removal and energy saving in densely occupied space by impinging jet ventilation

The pandemic of COVID-19 and its transmission ability raise much attention to ventilation design as indoor-transmission outstrips outdoor-transmission. Impinging jet ventilation (IJV) systems might be promising to ventilate densely occupied large spaces due to their high jet momentum. However, their performances in densely occupied spaces have rarely been explored. This study proposes a modified IJV system and evaluates its performance numerically in a densely occupied classroom mockup. A new assessment formula is also proposed to evaluate the nonuniformity of target species CO₂. The infector is assumed as the manikin with the lowest tracer gas concentration in the head region. The main results include: a) Indoor air quality (IAQ) in the classroom is improved significantly compared with a mixing ventilation system, i.e., averaged CO₂ in the occupied zone (OZ) is reduced from 1287 ppm to 1078 ppm, the OZ-averaged mean age of air is reduced from 439 s to 177 s; b) The mean infection probability is reduced from 0.047% to 0.027% with an infector, and from 0.035% to 0.024% with another infector; c) Cooling coil load is reduced by around 21.0%; d) Overall evaluation indices meet the requirements for comfortable environments, i.e., the temperature difference between head and ankle is within 3 °C and the OZ-averaged predictive mean vote is in the range of -0.5 - 0.5; e) Thermal comfort level and uniformity are decreased, e.g., overcooling near diffuser at ankle level. Summarily, the target system effectively improves IAQ, reduces exhaled-contaminant concentration in head regions, and saves energy as well.

Optimization of air supply parameters for stratum ventilation based on proper orthogonal decomposition

Under the current COVID-19 epidemic conditions, stratum ventilation can provide treated fresh air directly into the human breathing zone, improving the air quality for inhalation. However, in the design of air supply parameters for stratum ventilation, the traditional trial-and-error and experimental methods are inefficient and time consuming, and they cannot be used to identify the optimal air supply parameters from a large number of parameters. Therefore, in this paper, the inverse design method based on proper orthogonal decomposition (POD) was applied to the design of ventilation parameters for a room with stratum ventilation. Predicted mean vote (PMV), predicted percentage dissatisfied (PPD) and droplet nuclei concentration in the human breathing zone were selected as design objectives to optimize air supply parameters. The transmission of COVID-19 was controlled by reducing the concentration of droplet nuclei in the respiratory area. The results show that, compared with the trial-and-error method, the inverse design method based on POD is more than 90% faster. POD method can greatly expand the sample size. Considering the dispersion of exhaled droplet nuclei in the room, the appropriate stratum ventilation parameters can reduce the concentration of fine droplet nuclei by more than 20% compared with the traditional design parameters.

Inverse design of indoor environment using an adjoint RNG k-ε turbulence model

The adjoint method can determine design variables of an indoor environment according to the optimal design objective, such as minimal predicted mean vote (PMV) for thermal comfort. The method calculates the gradient of the objective function over the design variables so that the objective function can be minimized along the fastest direction using an optimization algorithm. Since the objective function is controlled by the Reynolds-averaged Navier-Stokes (RANS) equations with the RNG k-ε model during the optimization process, all the corresponding adjoint equations should be solved, rather than the "frozen turbulence" assumption used in previous studies. This investigation developed adjoint equations for the RNG k-ε turbulence model and applied it to a two-dimensional ventilated cavity and a three-dimensional, two-person office. Design processes with the adjoint RNG k-ε turbulence model led to a near-zero design function for the two cases, while those with the "frozen turbulence" assumption did not. This investigation has successfully used the new method to design a two-person office with optimal thermal comfort level around the two occupants.