In this study, we test the performance of Guideline 36-compliant sequences of operation for the air system relative to sequences of operation that predate Guideline 36. For this study, the air system comprises air handling units (AHUs) that serve variable air volume terminal units (VAVs). We present a platform that can be used to study the impact on building operations of changing the control system in a building, while holding constant any other aspect of that building, such as equipment upgrades, internal load variations, and changes to weather. We use the Virtual Cybernetic Building Testbed (VCBT), which contains commercial BACnet-enabled controllers and an operator workstation, as well as the Intelligent Building Agents Laboratory (IBAL), which uses chillers to meet the loads in the AHU-VAV system and can generate repeatable weather conditions and zone loads. These facilities use a hardware-in-the-loop approach, which combines a simulation of a building with hardware. This is the first demonstration of the combined VCBT-IBAL platform, which provides a method to evaluate potential sequences of operation in hardware before deploying them in real buildings.

This paper presents an experimental study on the development of low-cost globe thermometers made from polyethylene, focusing on the effects of globe diameter and mean radiant temperature (MRT) estimation methods on measurement accuracy in an office environment with natural and forced convection. Two globe diameters (220 mm and 120 mm) were tested, and MRT was calculated using approaches defined in ISO 7726, including methods based on globe, surrounding surface temperature, and operative temperature. Under natural convection, statistical tests showed that neither the globe diameter nor the calculation method had a statistically significant influence on MRT, and all methods yielded results close to the view-factor reference. Under forced convection, however, methods that explicitly account for convection yielded good results with the 220 mm globe, keeping the MRT estimates within the uncertainty limits proposed by ISO 7726:2001. Whereas the smaller 120 mm globe was highly sensitive to air velocity. Compliance with ISO 7726:2025 and benchmarking against the standard 150 mm globe are recommended for future performance assessments of these polyethylene globe thermometers in evaluating indoor thermal environments.

In this study, we developed and validated a novel tracer gas method that can quantify ventilation performance in continuously occupied indoor environments, such as medical, welfare, and educational facilities. We selected hydrogen gas as the tracer because of its low and stable ambient concentration (∼0.5 ppm) and zero global warming potential and designed a portable measurement device—hydrogen ventilation logger (HVL). The HVL showed high stability during measurements and exhibited linearity (y = 1.006x + 0.002, R2 = 0.9997) over 0.5–51.1 ppm, with a reproducibility of 3.2%, zero-point drift of only 0.19 ppm, and relative error of <0.4%. Ventilation rates calculated from tracer decay curves in a sealed wooden room (0.76 h−1) and mechanically ventilated workspace (13.5 h−1) showed close agreement with the exponential decay model based on the Seidel equation (R2 = 0.998). In an occupied university classroom, HVL reliably measured the ventilation rate at 1.15 h−1, while CO2-based estimates ranged from 1.25 to 2.69 h−1, which were up to 2.5 times higher depending on the assumed metabolic rate. These results demonstrate that the proposed method can obtain stable and accurate ventilation measurements independent of metabolic CO2 production, rendering it suitable for dynamic, continuously occupied indoor environments.

High thermal mass radiant systems have strong potential for energy flexibility, but key parameter relationships remain unclear. This study conducts a comprehensive parameter sensitivity analysis of thermally activated building systems (TABS) and embedded surface systems (ESS) using hundreds of thousands of simulations. Two representative cases, Hangzhou, China (humid subtropical) and San Francisco, California, USA (marine), are analyzed in depth, followed by cross-climate testing in eight additional cities spanning hot to mild climates. Results show that start/stop is the primary driver of load shifting potential, while start time has little effect on cooling energy supply. For floor ESS, however, operation duration is critical: Extending operation from 8 to 24 h increases daily cooling supply by 25.9% in Hangzhou and by 35.4% in San Francisco, compared to only 5–9% in other terminal types. Using San Francisco as an example, a comparison of fixed nighttime precooling and flexible scheduling reveals key design levers, such as window-to-wall ratios and optimal orientations, that strengthen energy flexibility. Overall, the findings support a two-stage optimization: first, tuning operation timing and durations to maximize load shifting without excess cooling, and second, refining design parameters to enhance flexibility. These insights provide guidance for designing grid-interactive radiant cooling systems.

Advanced model-predictive and reinforcement learning controls have demonstrated potential in building energy efficiency. However, limited interpretability of such controls for facility managers hinder their widespread use. This study proposes a graphical and interpretable control guidance for facility operators. The target real-life factory building is located in Busan, South Korea, being served by five chillers, five chilled water pumps, six cooling water pumps, and seven cooling towers. First, the authors developed hybrid models for the chillers and cooling towers by combining physical principles, specifications, and measured data. Next, the authors visually presented the total power according to feasible control options (including the number of chillers, chilled water pumps, cooling water pumps, and cooling tower fans) while meeting cooling demand and operational constraints. The developed models demonstrated sufficient predictive performance, achieving an MAE of 0.04–0.35 for the five chiller’s COP and 0.53 °C for the cooling towers’ outlet temperature. The authors compared the graphical results at three time points—two with similar cooling loads and one under a high cooling load. The visually presented control guidance displays multiple feasible control options, providing efficient strategies based on operational and outdoor conditions as well as enhancing interpretability for facility managers.

Domain generalization for chiller fault diagnosis requires balanced data, but automatic shutdowns cause fault data scarcity and class imbalance. We propose a simulation-based method that integrates simulated and real data to address this issue. First, a chiller simulation model is designed, and its heat transfer parameters are fine-tuned using operational data to reduce the discrepancy between the simulation model’s response and the actual unit’s response. Then, a mapping model is developed, employing an encoder-decoder network to further improve the similarity between simulated and real data. These two refinement steps ensure that the simulation model’s response closely approximates the behavior of the real system. Finally, a domain-invariant feature extraction model for chiller is developed. This model uses domain adversarial training to extract domain-invariant representations and incorporates a local domain discriminator to perform class-level domain differentiation, enhancing the feature extraction capability. The proposed method is validated on a laboratory chiller unit system. Comparative analysis with other domain generalization methods demonstrates that the proposed approach achieves higher diagnostic accuracy, with an average diagnostic rate reaching 88.97% across three tasks, while offering enhanced data interpretability.

In this article, the impact of low air volume fraction air-induced pressure losses in vertical pipes was studied experimentally in a recirculated hydronic system. The test loop is 0.8 m tall with a uniform inner pipe diameter of 19 mm. The maximum total air volume fraction in the test loop was 8.6%. The local average air volume fractions in the pipes with vertical upward and downward flow were measured using the differential pressure method. Two sources of extra pressure loss caused by air in the pipes with vertical flow were identified: (1) frictional pressure loss caused by phase slip between air and water flow; and (2) the density difference between the upward and downward flows. Our measurements show that the combined incremental pressure loss caused by air at 6.8% total air volume fraction at a flow velocity of 0.6 m/s can be four times as high as the single-phase flow pipe frictional pressure loss at the same flow velocity in vertical pipe sections. At a flow velocity of 0.6 m/s, the density-induced pressure loss is approximately seven times the air frictional pressure loss at the same flow velocity.

Thermal discomfort markedly impacts human productivity, determined mainly by environmental and personal factors. The proposed research evaluates thermal comfort and productivity based on standard effective temperature, which covers the occupants’ indoor thermal environmental and personal factors. Twenty-four college students were selected for experiments; they experienced four air temperatures (23 °C, 25 °C, 27 °C, and 30 °C), with relative humidity ranging from 60% to 80% and air velocity from 0 to 0.2 m/s. A subjective questionnaire assessed occupant thermal comfort, mental state, and mental workload, while their performance was quantitatively evaluated using neuro-behavioral tests. The results showed that the highest performance and thermal comfort were recorded at 27.2 °C mean SET, during which the occupant sensation ranged from ‘neutral’ to ‘slightly cool’, and the total mood disturbance and mental workload were relatively low. This underscores the crucial relationship between thermal comfort, psychological response, and performance, with the most significant changes observed in warm environments. It is evident that thermal comfort correlates with decreased total mood disturbance, reduced mental workload, heightened performance, and vice versa. The findings of this study would enable building HVAC operators to optimize the operation of HVAC systems by creating an indoor thermal environment that supports optimal human performance and ensures comfort.

This is the first journal article from the ASHRAE research project RP 1865, “Optimizing Supply Air Temperature Control for Dedicated Outdoor Air Systems,” focusing on the large-scale energy performance evaluation of the optimal control of dedicated outdoor air systems (DOAS). DOAS is a type of air handling system that is installed in buildings to ensure proper ventilation for the built environment. It is acknowledged that DOAS with proper operation strategies can provide sufficient ventilation and dehumidification while achieving energy efficiency. In this regard, there have been efforts to develop advanced control sequences (e.g., optimal control) for DOAS. Still, limited studies have demonstrated the effectiveness of such DOAS controls on a larger scale under varying climate zones with different DOAS configurations. To fill the research gap, this study aims to quantify the energy-saving potentials of applying an optimal supply air temperature (SAT) control strategy for DOAS considering diverse configurations of HVAC systems in various climate conditions across the United States. For this study, we first developed a total of 180 EnergyPlus models accommodating different types of buildings (i.e., detailed medium-sized office and primary school) and HVAC systems (i.e., DOAS types, DOAS sizes, and terminal units) under varying ASHRAE climate zones (i.e., 2A, 3B, 4A, 4C, 6A, and 6B). Next, genetic algorithm (GA)-based optimizations were conducted to determine the optimal DOAS SAT control that would minimize the energy cost of the entire HVAC system operation. Our study of comparing the optimal control to a typical rule-based control (i.e., outdoor air temperature-based reset control) revealed approximately 4–34% of energy cost saving potential by optimizing the DOAS SAT control sequence.

Air cleaning reduces indoor exposure to fine particulate matter (PM2.5) during wildfire smoke events. However, resource and cost constraints may limit access to air cleaning during such an event, as both commercial devices and the higher-rated MERV filters that do-it-yourself (DIY) assemblies typically rely upon tend to be expensive and in short supply. With these constraints in mind, we developed and evaluated several configurations of a novel, DIY air cleaner that uses common household fabrics as filtration media. Clean air delivery rates (CADRs) of the devices were experimentally evaluated in two ways: first, with independent measurements of flowrates and single pass removal efficiencies, and second, via pull-down testing in a large chamber. With two layers of cotton batting fabric and a flowrate-increasing cardboard shroud attached, the device achieved particulate matter CADRs of 162, 134, and 206 m3/h in 0.02–0.3, 0.3–1, and 1–2.5 µm particle diameter bins, respectively, during chamber testing. Results indicate that these simple, inexpensive, fabric configurations can meaningfully reduce PM2.5 levels in smaller zones of a home, and thus represent a viable option for improving indoor air quality during rapid-onset air pollution events, such as wildfires.