Building Services Engineering Research & Technology

Ground source heat pumps (GSHPs) are increasingly used in cold-climate retrofits of multi-apartment buildings (MABs), yet empirical knowledge of their design and sizing remains limited. This study presents an exploratory analysis of a national survey of Finnish GSHP contractors, examining system design, sizing, configuration, and controllability in MAB retrofits. Respondents (n = 7) were categorised by experience level and together reported 605 projects, covering about 21% of the Finnish GSHP-equipped MAB stock, although the distribution was markedly uneven. Results show that GSHPs were typically sized to cover 75–85% of peak heating demand, with backup and top-up heating almost exclusively electric. The electrical grid connection was increased in 70% of these projects, although earlier studies based on historical consumption data suggest that the need for such enlargements is uncertain. Control functionalities based on electricity use or power demand appeared in fewer than 10% of systems. Despite broadly similar design outcomes, calculation tools, input data, and sizing rationales varied widely between contractors, reflecting the absence of shared standards and the predominance of investment-cost considerations. Findings highlight a gap between modelling-based optimisation and contractor practice and indicate directions for more consistent design guidance and assessment of grid-level impacts of GSHP retrofits in cold-climate MABs.

The outbreak of cold waves often causes a rapid decrease in temperature and a sharp increase in the heating load demand of urban buildings, imposing enormous pressure on the energy and power systems of megacities. In this study, the spatiotemporal variations in cold waves were analyzed over a 30-year period (1991–2020) in Tianjin, China. Based on the above study, three typical cold wave (CW) events were selected, the rural weather stations were selected using satellite-based methodology, and the impacts of UHI effect on heating loads of residential buildings during CW periods were evaluated by simulating the hourly heating loads during CW and non-CW periods. The results show that the UHI intensity (UHII) was lower during CW periods than non-CW periods. The UHI effect reduced urban heating loads by 8.72% compared to rural areas during CW periods. During high-load periods (18:00 (Beijing time) to 07:00 the following day), urban heating loads were 10.24% lower than rural areas, while urban heating loads were 11.65–16.04% lower than rural areas during non-CW periods. Therefore, during CW periods, the UHII weakens, and its impacts on residential building loads are reduced.

With the progression of urban renewal, the functional transformation of numerous old industrial heritage buildings has imposed new demands on their indoor physical environments. This paper focuses on the adaptive renovation of thermal environments in old industrial buildings, using two case studies: Welding Workshop (Before Renovation) and the Cylinder Casting Workshop (After Renovation) of Hefei Motor Factory and Diesel Engine Factory. By integrating on-site thermal environment measurements and subjective thermal sensation questionnaires, we employs statistical regression methods to analyze the relationship between operative temperature and actual thermal sensation (MTS) and subjective thermal discomfort. The study identifies the acceptable temperature range and duration proportion in old industrial buildings, and further compares objective and subjective differences in human thermal comfort between summer and transitional seasons in the same workshop. Based on the acceptable duration proportion, a quantitative relationship between subjective sensations and operative temperature is established. These findings offer theoretical and empirical support for green renovation strategies of existing industrial buildings and design optimization of new constructions.

Occupant window interaction is a critical component in optimizing energy consumption and indoor environmental quality (IEQ). Understanding the influence of environmental and behavioral factors on window state decisions remains a significant challenge in building management systems (BMS). We present a hybrid probabilistic model to assess thermal comfort and predict the probability of the occupant opening or closing the window. The data was acquired from an open-source platform that provided yearly university dormitory window interactions. Bayesian networks (BNs) and logistic regression (LR) models were applied to predict the window-opening behavior of the occupants. An average accuracy of 92% for Bayesian and 94% for LR were obtained. The results were further enhanced by combining these models through weighted methods, with weights extrapolated through generative recursive iterations generating an average accuracy of 95% and Area Under the Curve (AUC) of 98%. The proposed hybrid approach significantly improves over existing predictive models in thermal comfort and window state prediction.

Our purpose was to examine the effect of working under the collided supply jets from active chilled beams on occupants’ perception, work performance, and stress. A repeated measures design with 36 participants was implemented with two test conditions: a reference condition, where active chilled beams were functioning appropriately, and a test condition, where supply jets from the active chilled beams collided and fell down to the workstation. Individual factors, such as gender and draught sensitivity are considered. Working under the collided supply jets resulted in lower thermal sensation, higher percentage of dissatisfied with the thermal environment and warmer thermal preference. The reference condition was perceived to be better for concentration, performance, and working efficiently for a long period of time. The Draught sensitive groups’ 0-back accuracy was lower when working under increased air movement and they had lower perceived performance and higher perceived workload than Draught neutral group at the end of exposure time. The present results indicate that working under the influence of the collided supply jets might generate stronger negative effects among females and draught sensitive persons. Self-rated draught sensitivity is an important parameter, and it is recommended to be used whenever air movement is studied with humans.

Excessive use of fossil fuel-based energy has led to significant environmental problems, primarily due to greenhouse gas emissions. In regions with hot and dry climates, natural ventilation strategies, such as wind catchers, can reduce the demand for cooling and ventilation, thereby improving thermal comfort and indoor air quality. This study evaluates the performance of a wind catcher in the hot, dry climate of Mexicali, Mexico, using Computational Fluid Dynamics (CFD) to analyze ventilation efficiency and thermal comfort across nine different air inlet and outlet configurations. The results indicate that configurations promoting cross-ventilation, particularly air inlets and outlets positioned at the bottom and top of the room, respectively, achieve the most efficient air renewal (with an average 18.32% reduction in stagnation time compared to the others) and improved thermal comfort, resulting in a predicted dissatisfaction percentage of 35.1%. These findings highlight the potential of wind catchers as a passive cooling strategy to reduce electricity consumption in hot and dry climates.