Ventilation Performance Indices with Elevated Air Movement for Health, Thermal Comfort, and Energy Efficiency

Inhaltsverzeichnis

1. Frontmatter

2. 1. Overview of Ventilation Performance Indices for Thermal Comfort, Indoor Air Quality, and Energy Efficiency

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   Convective ventilation systems are pivotal for creating thermally comfortable, healthy, and energy-efficient built environments. While advanced air distribution strategies have emerged to meet stringent demands for energy saving and airborne infection control, their development is hindered by inadequate evaluation tools. Traditional ventilation performance indices fail to account for the cooling effects of elevated air movement on both thermal comfort and energy efficiency, and cannot accurately assess the airborne infection risk of diseases like COVID-19. This book systematically addresses these gaps by presenting a comprehensive framework of novel ventilation performance indices. It is structured into three parts: Part I develops indices for thermal comfort that fully incorporate the effects of air temperature, velocity, and humidity; Part II introduces indices for indoor air quality, focusing on models and metrics for airborne infection risk control; Part III proposes indices for energy efficiency that explicitly quantify the impact of air movement. Collectively, these indices provide essential tools for the optimized design and operation of advanced air distribution systems, facilitating the creation of sustainable and livable indoor spaces.

3. 2. Predicted Mean Vote with Skin Temperature from Standard Effective Temperature Model

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   Precise prediction of thermal comfort holds significant importance for the optimal design of buildings that aim to balance thermal comfort and energy efficiency. The Predicted Mean Vote (PMV) is broadly accepted and integrated into numerous national and international thermal comfort standards. However, across various contextual conditions, multiple studies have criticized the PMV for its less-than-ideal accuracy. Considering the pivotal role of skin temperature in thermal comfort and its oversimplified representation in the PMV, this chapter modifies the PMV by replacing the simplified skin temperature with values derived from the standard effective temperature model, with the goal of enhancing the model’s predictive performance. The simplified skin temperature only takes into account the influence of activity level, while disregarding the effects of clothing insulation and environmental factors. By incorporating a more intricate human thermoregulatory mechanism, the skin temperature obtained from the standard effective temperature model offers greater precision. The revised PMV is validated using the ASHRAE Global Thermal Comfort Database II, which shows a reduction in the original PMV’s overestimation of warm and cold discomforts across different contextual scenarios, such as climate types, building categories, and HVAC systems. Overall, the modified PMV enhances the accuracy and robustness of thermal sensation prediction by 62% and 56%, respectively. With its notably improved predictive capability, the revised PMV contributes to the updating of thermal comfort standards and the development of energy-efficient and thermally comfortable buildings.

4. 3. Predicted Mean Vote with Skin Wettedness from Standard Effective Temperature Model

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   The Predicted Mean Vote (PMV) serves to forecast the thermal sensation of a group by examining human thermal load, a methodology widely recognized and embraced by thermal comfort standards in the design of energy-efficient buildings that aim for optimal thermal comfort. Despite its utility, the excessively simplistic portrayal of skin evaporative heat loss in thermal load computations has frequently led to reported discrepancies between PMV predictions and real-world thermal sensation votes. This chapter endeavors to enhance the PMV model by integrating the concept of skin wettedness from the standard effective temperature model. The standard effective temperature model, which incorporates advanced human thermoregulatory mechanisms, can reasonably predict skin wettedness based on key physiological parameters such as core temperature, skin temperature, and peripheral blood flow. This skin wettedness parameter is subsequently utilized to calculate skin evaporative heat loss, substituting the oversimplified method conventionally employed in PMV calculations. The modified PMV with an improved representation of skin evaporative heat loss is validated against the ASHRAE Global Thermal Comfort Database II, the largest of its kind, encompassing diverse climate types, building categories, and HVAC systems. In comparison to the original PMV, the modified version demonstrates significant enhancements in the overall accuracy and robustness of thermal sensation prediction, with improvements of 64% and 32%, respectively. This chapter makes a valuable contribution to the ongoing refinement of PMV and paves the way for updates to thermal comfort standards.

5. 4. Improving Predicted Mean Vote with Inversely Determined Metabolic Rate

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   Ineffective thermal comfort prediction can lead to challenges, including discomfort for building occupants and substantial energy waste caused by unnecessary excessive cooling or heating in buildings. The Predicted Mean Vote (PMV) model has been widely applied for thermal comfort management in air-conditioned buildings due to its theoretical validity and practical applicability. Among the critical inputs required for PMV calculations, the metabolic rate of occupants is identified as the most crucial parameter, as it directly influences the heat balance model that forms the foundation of the framework. However, existing methods for measuring metabolic rate encounter significant obstacles, such as operational difficulties in real-world situations or technical inaccuracies arising from oversimplified assumptions. This chapter presents an innovative approach to enhance the PMV model’s precision in thermal sensation prediction by indirectly estimating the metabolic rate. Specifically, the metabolic rate is formulated as a linear function of two key environmental variables: room air temperature and air velocity, with the model explicitly considering the effects of physiological adaptation mechanisms. To optimize the model parameters, a variable metric algorithm is used as an optimizer, which systematically minimizes the difference between the PMV predictions and the subjective thermal sensation votes collected from human subjects. The proposed method is validated through a series of experimental setups, including controlled tests in environmental chambers designed to simulate a stratum-ventilated classroom and an aircraft cabin, as well as field experiments conducted in an actual air-conditioned building using data from the ASHRAE database. The results demonstrate notable improvements: the method enhances the accuracy and robustness of PMV in thermal sensation prediction by over 52.5% and 41.5%, respectively. Fundamentally, this approach develops a grey-box modeling framework through model calibration, which outperforms traditional black-box models based on machine learning algorithms in terms of interpretability and generalizability.

6. 5. Extended Predicted Mean Vote of Thermal Adaptations Reinforced Around Thermal Neutrality

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   The predicted mean vote (PMV), a widely adopted thermal comfort standard model, incorporates an extension factor to enhance its capacity for explaining thermal adaptations. Nevertheless, the original extended PMV (ePMV) fails to address thermal adaptations near thermal neutrality, leading to prediction deviations in this critical zone and consequently compromising accuracy for neutral-range thermal sensation. Recognizing the paramount importance of this sensation range for energy-efficient indoor comfort delivery, this chapter enhances the ePMV through introduction of a thermal neutrality factor. Specifically, both the extension factor and thermal neutrality factor are formulated as explicit functions of field datasets (PMV, thermal sensation vote (TSV), and ambient temperature). Validation demonstrates 73% maximum improvement in prediction accuracy—particularly within the TSV range of -0.5 to 0.5—achieved by reducing thermal neutrality deviation across global building types and climates. Furthermore, the explicit formulation ensures practical applicability.

7. 6. Extending Effective Draft Temperature to Cover Full Range of Air Velocity

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   The effective draft temperature (EDT) is commonly employed to assess air distribution performance in terms of thermal comfort. The traditional EDT’s applicability is restricted to air velocities below 0.35 m/s. Nevertheless, air velocities can be increased to as much as 0.80 m/s to achieve energy efficiency. This chapter expands the EDT to cover the entire spectrum of air velocities. The conversion factor of air velocity to air temperature for the proposed extended EDT is determined by the cooling impact of air movement (calculated from the standard effective temperature). Meanwhile, the reference state and the upper/lower limits of the proposed extended EDT are defined based on thermal neutrality and the thermal comfort boundaries (calculated from the Predicted Mean Vote), respectively. Experiments conducted in a stratum-ventilated office with higher air velocities are utilized to validate the proposed extended EDT. The results demonstrate that the conventional EDT has an average accuracy rate of 69.6%. The existing extended EDT (with an average accuracy of 71.7%) outperforms the conventional version by 3.1%, while the proposed extended EDT (with an average accuracy of 97.8%) shows a 40.6% improvement. The proposed extended EDT values for Categories I–III of thermal comfort under both cooling and heating modes are presented in tables to facilitate practical applications.

8. 7. Effective Moisture Temperature: Ventilation Performance Index Accounting for Effects of Air Temperature and Relative Humidity on Thermal Comfort

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   Relative humidity plays a dominant role in determining thermal comfort for occupants. The existing ventilation performance metric associated with thermal comfort, namely the Effective Draft Temperature (EDT), fails to incorporate the influence of relative humidity on thermal comfort. This chapter introduces a novel ventilation performance indicator termed the Effective Moisture Temperature (EMT) to account for the combined effects of air temperature and relative humidity on thermal comfort. The proposed EMT is defined by establishing an analogy with the EDT framework, and its quantification is achieved through theoretical analyses of thermal neutrality principles, the thermal comfort zone boundaries, and the equivalent transfer mechanisms between relative humidity and air temperature. For practical applications, the EMTs are systematically tabulated under both cooling and heating, considering different thermal comfort requirements. The results derived from Monte Carlo simulation experiments and the ASHRAE Global Thermal Comfort Database II indicate that under low air movement conditions, the accuracy range of the original EDT is 23.8%–88.0%, whereas the proposed EMT demonstrates a significantly higher accuracy ranging from 98.6% to 99.5%. Furthermore, this chapter extends the framework by developing the Effective Draft and Moisture Temperature (EDMT) for elevated air movement conditions, integrating the EMT model with the cooling effect of air velocity. Under such enhanced air movement scenarios, the extended EDT exhibits an accuracy of 84.1%–95.5%, while the EDMT achieves an accuracy level of 96.7%–99.2%. These newly proposed indices, EMT and EDMT, contribute significantly to the design and optimization of thermally comfortable built environments.

9. 8. Ventilation Performance Index Fully Considering Effects of Ventilation Air Parameters on Thermal Comfort: Effective Draft—Moisture Temperature

   Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

   Abstract

   For the creation of livable indoor environments, ventilation strategies are widely implemented. When utilizing ventilation methods to attain thermal comfort indoors, the ventilation performance index related to thermal comfort holds significant importance. Air temperature, air velocity, and relative humidity are the three critical environmental air parameters of ventilation methods that affect thermal comfort. Nevertheless, the existing ventilation performance indices, namely the Effective Draft Temperature (EDT) and Effective Moisture Temperature (EMT), cannot simultaneously incorporate these three parameters for thermal comfort assessment. This chapter introduces a new ventilation performance index, the Effective Draft–Moisture Temperature (EDMT), which is designed to consider the aforementioned three environmental air parameters concurrently for evaluating thermal comfort. The EDMT is proposed based on the equivalent transfer of the thermal comfort effects of air velocity and relative humidity to air temperature. Two algorithms of cascaded equivalent thermal comfort transfers are developed. Using these algorithms, the EDMT is quantified and tabulated, providing practical convenience for diverse thermal comfort requirements during cooling and heating operations. The outcomes of Monte Carlo simulations and the analysis of ASHRAE Thermal Comfort Database II reveal that the thermal comfort evaluation accuracies of the EDT and EMT are 88.7%–95.5% and 70.9%–89.0%, respectively. In contrast, the accuracies of the proposed EDMTs for Algorithm 1 and Algorithm 2 are 97.3%–99.3% and 97.7%–99.3%, respectively. The proposed EDMTs of Algorithm 1 and Algorithm 2 are reliable and practical for real-world applications.

10. 9. Dilution-Based Evaluation of Airborne Infection risk—Thorough Expansion of Wells-Riley Model

    Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

    Abstract

    To formulate appropriate strategies against infectious respiratory diseases like COVID-19, accurately evaluating airborne infection risk in both spatial and temporal aspects is critical. The non-uniform spread of aerosol-borne pathogens across different areas and time periods highlights the need for such precise assessment. Nevertheless, the classic Wells-Riley model and its variant, the rebreathed-fraction model, are limited to well-mixed conditions. Their incapability to assess airborne infection risk with spatial and temporal factors can lead to inaccurate estimations, either overemphasizing or downplaying the actual risk. This chapter introduces a new dilution-based approach for evaluating airborne infection risk. Through a comparative study with the Wells-Riley model and its modified version, it is evident that the proposed method represents a significant advancement over the original Wells-Riley model. It enables researchers and professionals to assess airborne infection risk with both spatial and temporal precision. Experimental tests conducted in a simulated hospital ward have provided strong evidence that the new method can effectively measure airborne infection risk from spatial and temporal viewpoints. Moreover, its user-friendly characteristic makes it a valuable tool in the design and creation of healthy built environments.

11. 10. Contaminant Removal and Contaminant Dispersion of Air Distribution for Overall and Local Airborne Infection Risk Controls

    Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

    Abstract

    Optimal air distribution is pivotal for managing airborne infection risk in infectious respiratory diseases such as COVID-19. While existing studies evaluate and contrast the effectiveness of various air distribution systems in reducing airborne infection risk, the underlying mechanisms through which air distribution regulates these risks remain unclear. This chapter explores the mechanisms by which air distribution mitigates both overall and local airborne infection risks. Experimentally validated CFD models simulate contaminant concentration fields in a hospital ward, forming the basis for evaluating COVID-19 airborne infection risks using a dilution-based extension of the Wells-Riley model. Diverse air distribution systems—including stratum ventilation, displacement ventilation, and mixing ventilation—at different supply airflow rates are assessed. Findings reveal that variations in overall and local airborne infection risks across different air distributions and supply airflow rates exhibit complex and nonlinear trends. Contaminant removal and contaminant dispersion are identified as the respective mechanisms for overall and local airborne infection risk control, applicable irrespective of airflow patterns or supply rates. A strong contaminant removal capacity enhances overall risk control, as demonstrated by a 0.96 coefficient of determination between the contaminant removal index and the reciprocal of overall airborne infection risk. A high contaminant dispersion capacity improves local risk control, with a 0.99 coefficient of determination between the contaminant dispersion index and local airborne infection risk.

12. 11. Ventilation Indices for Evaluation of Airborne Infection Risk Control Performance of Air Distribution

    Sheng Zhang, Jinghua Jiang, Yong Cheng, Zhang Lin

    Abstract

    The management of airflow distribution is crucial in preventing respiratory infections like COVID-19, with ventilation metrics serving as key indicators to assess airborne infection risks and evaluate the effectiveness of air distribution systems. This chapter examines the correlation between ventilation metrics and airborne infection risk, proposing new indices to measure the efficacy of infection control strategies within these systems. Alongside traditional metrics such as age of air (AoA), air change effectiveness (ACE), and contaminant removal effectiveness (CRE), this chapter introduces air utilization effectiveness (AUE) and contaminant dispersion index (CDI) as innovative indices. Computational fluid dynamics (CFD) simulations are carried out in hospital wards and classrooms to apply different ventilation strategies, compute these indices, and evaluate airborne infection risk. A three-stage correlation analysis, using statistical methods, is developed to validate these ventilation indices. The results support the combined use of AUE and CDI as a comprehensive indicator of airborne infection risk, with CDI particularly emphasized for local risk assessment, regardless of factors like the influence of air distribution, airflow rates, infectiousness levels, room configurations, and occupant distributions. This chapter makes a significant contribution to enhancing control measures against the airborne spread of respiratory diseases by optimizing air distribution strategies.

13. 12. Empirical Model of Heat Removal Efficiency for Energy Efficient Air-Side Modulation

    Sheng Zhang

    Abstract

    Heat removal efficiency (HRE) is a widely used ventilation performance index regarding energy efficiency. This chapter develops an empirical model of HRE and demonstrates its convenient and effective applications in energy-efficient air-side modulation approaches. The proposed HRE model is constructed as a mathematical function integrating supply air temperature, supply airflow rate, and cooling load as key variables. Extensive validation across thirty-three experimental scenarios and five simulated cases demonstrates its applicability to both stratum and displacement ventilation systems in diverse room geometries and air terminal configurations. The model’s prediction errors remain within 5% for most cases, with a mean absolute error below 4%, underscoring its reliability. Investigations into air-side modulation using this HRE model reveal that variable-air-volume systems can effectively manage a broader spectrum of cooling loads compared to constant-air-volume systems in typical stratum-ventilated classroom and office environments. The conventional assumption of a constant HRE value in traditional methods can lead to significant room temperature prediction errors, reaching up to ±1.3 °C, which highlights the critical role of the proposed model in ensuring occupant thermal comfort during air-side control. An optimized air-side modulation strategy based on maximizing HRE is introduced, aiming to enhance energy efficiency while maintaining acceptable thermal conditions. Results indicate that this approach can improve the energy efficiency of stratum ventilation systems by up to 67.3%, with promising implications for displacement ventilation applications as well.

14. 13. Energy Performance Index of Air Distribution: Thermal Utilization Effectiveness

    Sheng Zhang

    Abstract

    The metric for evaluating energy performance holds significant importance in the design and operation of air distribution systems aimed at energy efficiency. Heat Removal Efficiency (HRE) stands as a commonly adopted index in this context, with the Energy Utilization Coefficient (EUC) and Effectiveness of Heat Removal (EHR) serving as alternative options. This chapter investigation highlights the inadequacies of these existing indices, demonstrating that they are both unreasonable and incompetent when functioning as energy performance indicators. Additionally, this chapter puts forward a novel index termed Thermal Utilization Effectiveness (TUE), whose efficacy as an energy performance metric is validated through theoretical examinations and experimental tests conducted on stratum ventilation, displacement ventilation, and underfloor air distribution systems. The EUC is deemed unsuitable as an energy performance index because it fails to take into account the relative impacts that the occupied and unoccupied zones have on the overall energy performance of air distribution. In the case of EHR, its inability to qualitatively differentiate the energy performance of various air distribution systems stems from the fact that it relies on a benchmark point that is not fixed but rather floats or varies under different conditions. HRE, on the other hand, encounters challenges in quantitatively distinguishing energy performance due to its unequal weighting of the thermal energy associated with the air temperature in the occupied zone. In contrast, TUE effectively addresses these shortcomings: it accounts for the relative contributions of the occupied and unoccupied zones by incorporating the exit air temperature, enables qualitative differentiation through the use of two stable benchmark points, and ensures quantitative distinction by applying equal weighting to the thermal energy of the air temperature in the occupied zone. As a result, TUE overcomes the limitations inherent in EUC, EHR, and HRE and is a rational and capable energy performance index for air distribution systems.

15. 14. Index of Ventilation Effectiveness Regarding Energy Performance Considering Cooling Effect of Air Movement: Equivalent Thermal Utilization Effectiveness

    Sheng Zhang

    Abstract

    Assessment of ventilation system efficiency in terms of energy performance is crucial for their optimal design and operation. Current energy performance metrics lack consideration for the cooling effect of air movement, a key aspect encouraged by regulations to enhance energy-efficient thermal comfort. To address this gap, a novel index named Equivalent Thermal Utilization Effectiveness (ETUE) is proposed by this chapter. ETUE incorporates the cooling effect of air movement by quantifying it through the standard effective temperature, leading to a corresponding reduction in the occupied zone’s air temperature. By integrating this equivalent reduction in air temperature into the existing Thermal Utilization Effectiveness (TUE) index, ETUE provides a more comprehensive assessment of ventilation system performance. Experiments focusing on stratum ventilation, a system known for leveraging air movement for cooling, have demonstrated the necessity of replacing TUE with ETUE. Failure to do so could lead to a significant decline in accuracy rates in energy performance evaluations (0–38.5%). The cooling effect of air movement contributes substantially (up to 86.8%) to the overall energy performance of ventilation systems. The proposed ETUE index represents a significant step forward in promoting the adoption of ventilation systems that harness air movement to enhance energy efficiency and thermal comfort in building environments.