A large-scale scientific facility uses constant-temperature air conditioning (CTAC) to control the air temperature fluctuation at an ultrahigh precision, i.e., ≤±0.1 ℃, which implies that the temperature of the chiller water must also be maintained at an ultrahigh precision level. Traditional CTACs depend on electric heating to maintain the chilled water temperature. However, such methods usually fail to address the issue of high-frequency oscillations and typically are not applied to ultrahigh-precision control. In this study, by conducting a reduced-scale experiment, we first validated the feasibility of two water chillers, one using a plate heat exchanger and another using a mixed water pump, to provide chilled water at an ultrahigh precision. Simulations using Modelica models based on these two approaches were established and experimentally verified. Finally, the steady-state and dynamic performances of these two systems were compared. Both approaches can achieve ±0.1 ℃ temperature fluctuation control when the hardware meets specific criteria, with the plate heat exchanger approach exhibiting superior steady-state performance. Under both schemes the root mean square error (RMSE) for the entire time period is below 0.1 ℃. The settling times for the plate heat exchanger and mixed water pump approaches are 5000 s and 600 s, respectively. The mixed water pump approach exhibits better dynamic performance. Both plate heat exchanger and mixed water pump approaches are capable of actively dampening high-frequency oscillations in the water supply temperature, with damping coefficients of 0.07 and 0.4, respectively.

Maintaining constant temperature is critical in large-scale scientific facilities, such as circular or linear tunnel-shaped facilities (TSFs) used for high-energy physics experiments (e.g., particle acceleration or collision). Traditional ventilation designs with vertical unidirectional airflow and uniform air supply rates are better suited for regular rooms and are less practical for TSFs. After evaluating four typical tunnel ventilation schemes, this study proposed achieving effective constant temperature control in TSFs using the most feasible approach, i.e., supply-air-based semi-transverse ventilation. First, two simplified analytical models were developed to determine the steady-state longitudinal temperature profile and the response time to temperature fluctuations. Two air supply distribution approaches, i.e., uniform and pressure-driven, can be incorporated. The latter was developed based on fluid dynamics. Second, a 400-meter-long TSF from a Shanghai-based scientific facility (SHINE) served as the case study. Fluctuation sources and their ways of causing various temperature fluctuations were analyzed, including air handling units (e.g., supply air temperature or flow rates), cables, and scientific instruments. Third, the performance of uniform and pressure-driven air supply distributions was compared in overcoming single and coupled fluctuation sources. The thresholds for each source were summarized for SHINE. Results indicated that while uniform air supply reduces longitudinal temperature difference and mitigates double-source fluctuations better, pressure-driven distribution is more effective against single sources. Finally, the theoretical methods were compared and agreed with steady-state and transient CFD simulations. This study provides a rapid and practical method for designing ventilation schemes to achieve constant temperature in TSFs and minimize reliance on CFD.

COVID-19 and its impact on society have raised concerns about scaling up mechanical ventilation (MV) systems and the energy consequences. This paper attempted to combine MV and portable air cleaners (PACs) to achieve acceptable indoor air quality (IAQ) and energy reduction in two scenarios: regular operation and mitigating the spread of respiratory infectious diseases (RIDs). We proposed a multi-objective optimization method that combined the NSGA-II and TOPSIS techniques to determine the total equivalent ventilation rate of the MV-PAC system in both scenarios. The concentrations of PM_2.5 and CO₂ were primary indicators for IAQ. The modified Wells-Riley equation was adopted to predict RID transmissions. An open office with an MV-PAC system was used to demonstrate the method’s applicability. Meanwhile,a field study was conducted to validate the method and evaluate occupants’ perceptions of the MV-PAC system. Results showed that optimal solutions of the combined system can be obtained based on various IAQ requirements,seasons,outdoor conditions,etc. For regular operation,PACs were generally prioritized to maintain IAQ while reducing energy consumption even when outdoor PM_2.5 concentration was high. MV can remain constant or be reduced at low occupancies. In RID scenarios,it is possible to mitigate transmissions when the quanta were < 48 h⁻¹. No significant difference was found in the subjective perception of the MV and PACs. Moreover,the effects of infiltration on the optimal solution can be substantial. Nonetheless,our results suggested that an MV-PAC system can replace the MV system for offices for daily use and RID mitigation.

Chamber testing is a common method to evaluate volatile organic compound (VOC) emissions from building materials. Empirical models based on short-term testing (typically less than 28 days) are frequently used to estimate long-term emissions (up to years). However, the applicability of the empirical models for long-term prediction remains unclear in practice. Four empirical models, i.e., two constant models with and without a prerequisite (M1 and M2), a power-law model (M3), and an exponential model (M4), were used to test the applicability of predicting year-long emissions using emission data that were less than one month. The diffusion-based mass-transfer model was used to generate reference emission data with random variations involved to represent measurement errors, etc. For M1 and M2, the discrepancy ratios between the constant emissions and the characteristic average emissions are quantified. For M3 and M4, an additional measure, i.e., normalized mean square error (NMSE), was adopted to statistically study the applicability of using empirical models to predict long-term emissions. The results shown that, first, the NMSE values indicate that M3 prefers slow emissions and generally performs better than M4. However, M4 performs better for predicting year-long emissions for cases with characteristic emission time of one year. Second, both M3 and M4 predict the average life-long emissions reasonably well for most scenarios. Third, while the effects of test duration are less significant for M3 than M4, the early-stage sampling points are more important for better long-term predictions. Additionally, experimental data by National Research Council Canada (NRC) were used to validate the applicability of the empirical models in year-long emission predictions, with the results similar to those from the simulated data. This paper can be used as a reference to select appropriate empirical model(s), as well as the testing duration, to simulate long-term VOC emissions from building materials using short-term testing data.