Urban morphology plays a crucial role in affecting pedestrian level wind velocity and air temperature. Most existing studies utilized the CFD method to simulate environmental parameters at the pedestrian level, while using statistical analysis to assess the impact of urban morphology. Simulation has high requirements in computational time, input parameters, and modeler expertise. Statistical analysis results highly rely on the pre-designed scenarios while lacking a profound interpretation. The study addressed these gaps by using CFD simulation data to establish two separate machine learning models for quickly predicting pedestrian level wind velocity and air temperature. Results showed that XGBoost_based models achieved better performance than LightGB_based models. Then, explainable SHAP was applied to the optimal prediction models for investigating the effect of urban morphology on pedestrian level wind velocity and air temperature. SHAP results revealed that the location of sidewalks from the building array center has a more significant impact on wind velocity and air temperature than the street width, building height and width, and orientation angle. In addition, the study explored the interaction effect of urban morphology-related design variables on pedestrian level wind velocity and air temperature.

To facilitate the design and analysis related to indoor air quality (IAQ) and ventilation in buildings, a plug-in named ANT (contam-in-ANT) has been developed for Rhino/Grasshopper, an algorithm aided design platform. ANT is a whole-building IAQ and ventilation analysis tool based on CONTAM. ANT can be utilized to perform multizone simulations to assess airborne transmission risks, estimate health impacts due to inhalation exposure, perform parametric analyses, and optimize performance-driven building design and system settings. Optimizing the use and systems of existing buildings will support the renovation efforts necessary for all such structures to meet sustainability goals by 2050. A case study of a medium office building is used to demonstrate ANT and the post-processing of simulation results within Rhino/Grasshopper.

The growth of the logistics industry is resulting in a significant increase in the number of distribution centers. This study aimed to conduct a comparative analysis of the thermal comfort performance of traditional RTU+HVLS HVAC design schemes and air rotation units (ARU) design schemes in a distribution center. Computational fluid dynamic (CFD) was applied to visualize airflow velocity magnitude and temperature distribution. The findings can be summarized as follows: (1) the CFD simulation results indicated that during the heating season, indoor conditions were generally perceived as thermally comfortable for both the RTU+HVAC case and ARU case. (2) The CFD simulation results for the ARU case showed improved cooling season thermal comfort conditions at occupied elevations with respect to the RTU+HVLS case. (3) The ARU case reached the cooling setpoint faster on most of the sample points on the occupied plane. Furthermore, the scheme in which HVAC equipment supplies airflow along the obstacles has higher conditioning efficiency. (4) The thermal comfort in certain areas can be significantly affected by the overall airflow patterns created by different HVAC equipment location schemes. The study aims to assist distribution center owners and designers in evaluating multiple HVAC design schemes.

Thermal comfort in chemotherapy environments has been a crucial but neglected factor in the past, and these environments continue to be uncomfortable spaces for patients. In order to provide a safe indoor space, the study of the diffusion of pathogens and the interface between pathogens and thermal comfort becomes important. This paper talks about two ventilation strategies that are used to understand thermal comfort and relate it to pathogen survival. Findings from the research indicate a strong relationship between environmental design factors and thermal comfort at the patient level in relation to metabolic activity.

Short-term thermal history may have a substantial impact on how a person feels when traversing through urban spaces, especially in the context of global warming, as increasing temperatures and heat wave frequency will limit the quality and safety of their experience. While dynamic thermal comfort models such as Dynamic Thermal Sensation (DTS) are available, most analysis methodologies currently applied in urban design rely on steady state models and tend to overlook the thermal history of occupants. This paper implements a DTS-based thermal comfort analysis workflow to predict the evolving thermal sensations of occupants along a path. The workflow is then applied in the analysis of a design project in Southeast Asia, to assess its effectiveness in evaluating design scenarios in comparison with a steady state Universal Thermal Climate Index (UTCI) model.