Search Results (19)

Achieving sustainability in the manufacturing sector calls for systemic reductions in energy consumption and carbon emissions without compromising productivity. In the global energy consumption landscape, the manufacturing sector accounts for a significant proportion and is a major source of carbon emissions, with manufacturing systems and HVAC (Heating, Ventilation, and Air Conditioning) systems being the principal energy consumers. Existing research typically optimizes these two systems independently, neglecting their dynamic coupling; production scheduling determines equipment power and heat dissipation, which alters building thermal loads and consequently affects HVAC energy consumption. To address this problem and advance sustainable manufacturing practices, this study proposes an energy-aware scheduling framework integrating manufacturing and HVAC control. A WOA-XGBoost energy consumption prediction model is constructed, employing the Whale Optimization Algorithm to tune XGBoost hyperparameters, achieving a prediction accuracy of R² = 0.937 on the Shanghai typical meteorological year dataset. The HVAC decision variables are defined as five operational control variables—supply air flow rate, fan total pressure, ERV sensible/latent heat recovery effectiveness, and ventilation air flow rate—ensuring the physical realizability of scheduling solutions. An integrated scheduling-and-control model incorporating production capacity constraints and electricity demand response is then formulated and solved using a hybrid Particle Swarm Optimization algorithm. Validation on a five-machine, four-buffer flow shop demonstrates that the proposed framework reduces total electricity cost by 8.85% and total energy consumption by 14.88% in summer compared with a physics-based coupling baseline, with all metrics exhibiting coefficients of variation below 4% across ten independent runs. These results demonstrate that the proposed data-driven framework provides a practical and scalable pathway toward sustainable manufacturing by jointly reducing energy use and associated carbon emissions while maintaining full production throughput. Full article

Intelligent ventilation is positioned as a key axis for reconciling energy efficiency and indoor air quality (IAQ) in residential and non-residential buildings. This review synthesizes 51 recent publications covering control strategies (DCV, MPC, reinforcement learning), IoT architectures and sensor validation, energy recovery (HRV/ERV, anti-frost strategies, low-loss exchangers, PCM-air), active envelope solutions (thermochromic windows) and passive solutions (EAHE), as well as evaluation methodologies (uncertainty, LCA, LCC, digital twin) and smart readiness indicator (SRI) frameworks. Evidence shows ventilation energy savings of up to 60% without degrading IAQ when control is well-designed, but also possible overconsumption when poorly parameterized or contextualized. Performance uncertainty is strongly influenced by occupant emissions and pollutant sources (bioeffluents, formaldehyde, PM2.5). The integration of predictive control, scalable IoT networks, and robust energy recovery, together with life-cycle evaluation and uncertainty analysis, enables more reliable IAQ-energy balances. Gaps are identified in VOC exposure under DCV, robustness to sensor failures, generalization of ML/RL models, and standardization of ventilation effectiveness metrics in natural/mixed modes. Full article

As the importance of both indoor air quality (IAQ) and energy efficiency grows in residential buildings, the application of air filters in energy recovery ventilators has become essential. However, high-efficiency filters such as MERV 12 inevitably increase the pressure drop, adversely affecting the airflow, fan energy use, and heat exchange balance. This study quantitatively investigates how different levels of filter resistance—from clean conditions to 200% dust loading—affect system airflow, static pressure, exhaust air transfer, and power consumption. A standardized dust loading procedure was adopted to simulate long-term use conditions. The results show a 37% reduction in net supply airflow under heavily clogged filters, while the unit exhaust air transfer ratio increased from 7.2% to 17.7%, exceeding compliance limits. Surprisingly, electrical energy consumption decreased as the fan load dropped with the airflow. Despite an increase in the apparent heat exchange efficiency, this gain was driven by return air recirculation rather than true thermal effectiveness. These findings highlight the need for filter performance-based ERV certification and operational strategies that balance IAQ, energy use, and system compliance. Full article

This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler systems. The proposed platform features a dual-mode sensor array for early fire recognition, motorized ventilation units for rapid smoke extraction, and a 360° directional nozzle for targeted agent discharge using a residue-free clean extinguishing agent. Experimental trials demonstrated an average fire detection time of 5.8 s and complete flame suppression within 13.2 s, with 90% smoke clearance achieved in under 95 s. No false positives were recorded during non-fire simulations, and the system remained fully functional under simulated cloud communication failure, confirming its edge-resilient architecture. A probabilistic risk analysis based on ISO 31000 and NFPA 551 frameworks showed risk reductions of 75.6% in life safety, 58.0% in property damage, and 67.1% in business disruption. The system achieved a composite risk reduction of approximately 73%, shifting the operational risk level into the ALARP region. These findings demonstrate the system’s capacity to provide proactive, energy-efficient, and spatially targeted fire response suitable for high-value infrastructure. The modular design and SmartThings Edge integration further support scalable deployment and real-time system intelligence, establishing a strong foundation for future adaptive fire protection frameworks. Full article

Indoor air quality (IAQ) impacts human health, productivity, and well-being. As buildings become more energy-efficient and tightly sealed, the need for effective ventilation systems that maintain adequate IAQ grows. Energy Recovery Ventilators (ERVs) ensure adequate IAQ by bringing fresh outdoor air indoors while minimizing costly energy wastage. ERVs provide major economic, health, and well-being benefits and are a critical technology in the fight against climate change. However, little is known about the impact of ERV operation on the generation and fate of particulate and gaseous indoor air pollutants, including toxic, carcinogenic, allergenic, and infectious air pollutants. Specifically, the air pollutant crossover, aerosol deposition within ERVs, the chemical identity and composition of aerosols and volatile organic compounds emitted by ERVs themselves and by the accumulated pollutants within them, and the effects on bioaerosols must be investigated. To fill these research gaps, both field and laboratory-based experimental research that closely mimics real-life conditions within a controlled environment is needed to explore critical aspects of ERVs’ effects on indoor air pollution. Filling the research gaps identified herein is urgently needed to alert and inform the industry about how to optimize ERVs to help prevent air pollutant generation and recirculation from these systems and enhance their function of pollutant removal from residential and commercial buildings. Addressing these knowledge gaps related to ERV design and operation will enable evidence-based recommendations and generate valuable insights for engineers, policymakers, and heating, ventilation and air conditioning (HVAC) professionals to create healthier indoor environments. Full article

The temperature frequency method is used to analyze the energy savings of the wall-type energy recovery fresh air ventilator in three different typical regions, namely Guangzhou, with a tropical monsoon climate; the sub-temperate Wuhan; and Beijing, with a temperate monsoon climate, throughout the year. The influence of different temperature efficiencies and resistance levels of the energy recovery ventilator (ERV) on annual energy efficiency is also analyzed. The control temperature of the auxiliary heating device used in the winter is discussed, and the indoor temperature variation trend in the inter-wall-type energy recovery fresh air ventilator operating 24 h on four typical days of the year under different control modes is analyzed in the tropical monsoon climate of Guangzhou. The conclusions obtained can provide a reference for the application and selection of inter-wall-type energy recovery fresh air ventilators. Full article

After the COVID-19 pandemic in South Korea, residential buildings are equipped with an energy recovery ventilator for ventilation and building energy efficiency. During summer, it is required to operate both the ERV system and air conditioners to maintain thermal comfort as well as ensure indoor air quality. The ventilation efficiency of the ERV system can be varied by various layouts of the inlet and outlet vents. Moreover, cooling can be wasted through the exhaust of the ERV system. Considering this, the present study assessed thermal comfort by applying various layouts of the supply and exhaust of ERV systems with different supply air temperatures and air volumes of the air conditioners. Using CFD (computational fluid dynamics) simulation, the ventilation and thermal performance with the PMV (predicted mean vote) were analyzed. As a result, the PMV was highly affected by the supply air temperature and ventilation flow rates of the air conditioners. While additional installations of the inlet or outlet vents showed improved ventilation performance, the PMV index presented “slightly cold” or “cold”. Considering energy saving, this proves that it can provide an opportunity to reduce cooling energy consumption through the intermittent operation mode of the air conditioners. Full article

Improving indoor air quality (IAQ) in daycare centers is essential due to children’s vulnerability to pollutants and prolonged indoor exposure. To address these challenges, energy recovery ventilators (ERVs) with varying filtration efficiencies were evaluated through field measurements and CONTAM simulations. Baseline assessments of CO₂ and PM_2.5 levels revealed significant impacts from outdoor pollutant infiltration. ERVs successfully reduced CO₂ concentrations, maintaining levels below 1000 ppm during most occupancy periods. However, low-efficiency filters (MERV 8 or lower) permitted outdoor particulate matter infiltration, increasing indoor PM_2.5 levels. High-performance filters (MERV 13 or higher) reduced indoor PM_2.5 concentrations by up to 50%, significantly improving air quality. Findings emphasize the necessity of combining high-efficiency filtration with ERVs to mitigate pollutant infiltration and ensure healthy indoor environments. Policymakers and practitioners are urged to implement ventilation systems equipped with MERV 13 or higher filters, particularly in regions with high outdoor pollution. These strategies are critical for safeguarding children’s health and meeting IAQ standards in daycare facilities. Full article

This study investigates the thermal performance of various counterflow air-to-air heat exchangers under unbalanced flow conditions, aiming to enhance the efficiency of heat recovery systems. Mechanical ventilation with heat recovery is critical in energy-efficient buildings to reduce heat loss, which can reach up to 60% in air exchange processes. This research focuses on the effects of flow imbalance on the heat transfer efficiency of three specific heat exchangers: two commercially available models (Recair Sensitive RS160 and Core ERV366) and a custom 3D-printed prototype (GV PROTO). Experimental tests measured temperature efficiency under both balanced and unbalanced flow conditions, with results indicating that flow imbalance significantly impacts thermal efficiency. Among the exchangers, the RS160 displayed the highest temperature efficiency, maintaining performance better than the others as flow rates increased. The results of the study show that even small differences in the thermal efficiency of different heat exchangers under balanced airflow conditions transform into significant differences under unbalanced conditions. These findings contribute to a better understanding of how real-world ventilation imbalances affect heat exchanger performance, offering insights to optimize energy efficiency in ventilation systems. Full article

Residential buildings in South Korea have equipped an energy recovery ventilation (ERV) system to improve energy efficiency as well as dilute indoor air pollution. While most studies have focused on the efficiency of energy exchange or the ventilation performance of the ERV itself, the ventilation performance can be improved by the proper location of inlet and outlet vents. For the present study, the ventilation performance of the inlet and outlet vents of the ERV was investigated by using CFD simulation. By varying the locations of inlet and outlet vents, the airflow distributions and the age of air were assessed. In addition, the air exchange effectiveness was analyzed by using the mean age of air quantitatively. As a result, a higher age of air was observed when inlet vents were moved to the center of the plan along the wall and an additional inlet or outlet vent was installed in the kitchen. In addition, the highest air exchange effectiveness was obtained when the inlet vents were located in the center of the plan along the wall. Considering the economic perspective, it is recommended to locate the inlet vents in the center to at least improve the ventilation performance. Full article

In this study, we investigated the performance of air-to-water heat pump (AWHP) and energy recovery ventilator (ERV) systems combined with photovoltaics (PV) to achieve the energy independence of a dormitory building and conducted an analysis of the energy independence rate and economic feasibility by using energy storage devices. Our data were collected for 5 months from July to November, and the building energy load, energy consumption, and system performance were derived by measuring the PV power generation, purchase, sales volume, AWHP inlet and outlet water temperature, and ERV outdoor, supply, and exhaust temperature. When analyzing representative days, the PV–AWHP integrated system achieved an energy efficiency ratio (EER) of 4.49 and a coefficient of performance (COP) of 2.27. Even when the generated electrical energy exceeds 100% of the electricity consumption, the energy self-sufficiency rate remains at 24% due to the imbalance between energy consumption and production. The monthly average energy self-sufficiency rate changed significantly during the measurement period, from 20.27% in November to 57.95% in September, highlighting the importance of energy storage for self-reliance. When using a 4 kWp solar power system and 4 kWh and 8 kWh batteries, the annual energy self-sufficiency rate would increase to 67.43% and 86.98%, respectively, and our economic analysis showed it would take 16.5 years and more than 20 years, respectively, to become profitable compared to the operation of an AWHP system alone. Full article

Ventilation is becoming increasingly important to improve indoor air quality and prevent the spread of COVID-19. This study analyzed the indoor air quality of office spaces, where occupants remain for extended periods, among multi-use facilities with an increasing need for ventilation system application. A “tool for office space CO₂ prediction and indoor air quality improvement recommendation” was developed. The research method was divided into four steps. Step 1: Analysis of indoor air quality characteristics in office spaces was carried out with a questionnaire survey and indoor air quality experiment. Based on the CO₂ concentration, which was found to be a problem in the indoor air quality experiment in the office space, Step 2: CO₂ concentration prediction tool for office spaces, which requires inputs of regional and spatial factors and architectural and equipment elements, was developed. In Step 3: Development and verification of prediction tool considering economic feasibility, the cost of energy recovery ventilation systems based on the invoices of the energy recovery ventilation manufacturers was analyzed. In Step 4: Energy recovery ventilation proposal and indoor CO₂ forecast, Office Space B, which can accommodate up to 15 people, was derived as an example of the proposed tool. As a result of the prediction, the optimal air volume of the energy recovery ventilation was determined according to the “office CO₂ prediction and indoor air quality improvement recommendations”. This study introduced simple tools, which can be used by non-experts, that are capable of showing changes in indoor air quality, CO₂ concentration and cost according to activities. Full article

The present study provides insights into the energy-saving potential of a membrane energy recovery ventilator (ERV) for the management of building air-conditioning loads. This study explores direct (DEC), Maisotsenko cycle (MEC) evaporative cooling, and vapor compression (VAC) systems with ERV. Therefore, this study aims to explore possible air-conditioning options in terms of temperature, relative humidity, human thermal comfort, wet bulb effectiveness, energy saving potential, and CO₂ emissions. Eight different combinations of the above-mentioned systems are proposed in this study i.e., DEC, MEC, VAC, MEC-VAC, and their possible combinations with and without ERVs. A building was modeled in DesignBuilder and simulated in EnergyPlus. The MEC-VAC system with ERV achieved the highest temperature gradient, wet bulb effectiveness, energy-saving potential, optimum relative humidity, and relatively lower CO₂ emissions i.e., 19.7 °C, 2.2, 49%, 48%, and 499.2 kgCO₂/kWh, respectively. Thus, this study concludes the hybrid MEC-VAC system with ERV the optimum system for the management of building air-conditioning loads. Full article

The purpose of this study was to provide a guideline for the selection of technologies suitable for ASHRAE international climate zones when designing high-performance buildings. In this study, high-performance technologies were grouped as passive, active, and renewable energy systems. Energy saving technologies comprising 15 cases were categorized into passive, active, and renewable energy systems. EnergyPlus v9.5.0 was used to analyze the contribution of each technology in reducing the primary energy consumption. The energy consumption of each system was analyzed in different climates (Incheon, New Delhi, Minneapolis, Berlin), and the detailed contributions to saving energy were evaluated. Even when the same technology is applied, the energy saving rate differs according to the climatic characteristics. Shading systems are passive systems that are more effective in hot regions. In addition, the variable air volume (VAV) system, combined VAV–energy recovery ventilation (ERV), and combined VAV–underfloor air distribution (UFAD) are active systems that can convert hot and humid outdoor temperatures to create comfortable indoor environments. In cold and cool regions, passive systems that prevent heat loss, such as high-R insulation walls and windows, are effective. Active systems that utilize outdoor air or ventilation include the combined VAV-economizer, the active chilled beam with dedicated outdoor air system (DOAS), and the combined VAV-ERV. For renewable energy systems, the ground source heat pump (GSHP) is more effective. Selecting energy saving technologies that are suitable for the surrounding environment, and selecting design strategies that are appropriate for a given climate, are very important for the design of high-performance buildings globally. Full article

Thermal comfort, indoor air quality (IAQ), and energy use are closely related, even though these have different aspects with respect to building performance. We analyzed thermal comfort and IAQ using real-time multiple environmental data, which include indoor air temperature, relative humidity, carbon dioxide (CO₂), and particulate matter (e.g., PM₁₀ and PM_2.5), as well as electricity use from an energy recovery ventilation (ERV) system for a childcare center. Thermal comfort frequency and time-series analyses were conducted in detail to thoroughly observe real-time thermal comfort and IAQ conditions with and without ERV operation, and to identify energy savings opportunities during occupied and unoccupied hours. The results show that the highest CO₂ and PM₁₀ concentrations were reduced by 51.4% and 29.5%, respectively, during the occupied hours when the ERV system was operating. However, it was also identified that comfort frequencies occurred during unoccupied hours and discomfort frequencies during occupied hours. By analyzing and communicating the three different types of real-time monitoring data, it is concluded that the ERV system should be controlled by considering not only IAQ (e.g., CO₂ and PM_2.5) but also thermal comfort and energy use to enhance indoor environmental quality and save energy based on real-time multiple monitoring data. Full article