Subzone control method of stratum ventilation for thermal comfort improvement

The conventional control method of a collective ventilation (e.g., stratum ventilation) controls the averaged thermal environment in the occupied zone to satisfy the averaged thermal preference of a group of occupants. However, the averaged thermal environment in the occupied zone is not the same as the microclimates of the occupants, because the thermal environment in the occupied zone is not absolutely uniform. Moreover, the averaged thermal preference of the occupants could deviate from the individual thermal preferences, because the occupants could have different individual thermal preferences. This study proposes a subzone control method for stratum ventilation to improve thermal comfort. The proposed method divides the occupied zone into subzones, and controls the microclimates of the subzones to satisfy the thermal preferences of the respective subzones. Experiments in a stratum-ventilated classroom are conducted to model and validate the Predicted Mean Votes (PMVs) of the subzones, with a mean absolute error between 0.05 scale and 0.14 scale. Using the PMV models, the supply air parameters are optimized to minimize the deviation between the PMVs of the subzones and the respective thermal preferences. Case studies show that the proposed method can fulfill the thermal constraints of all subzones for thermal comfort, while the conventional method fails. The proposed method further improves thermal comfort by reducing the deviation of the achieved PMVs of subzones from the preferred ones by 17.6%–41.5% as compared with the conventional method. The proposed method is also promising for other collective ventilations (e.g., mixing ventilation and displacement ventilation)

Finite-size scaling of pseudo-critical point distributions in the random transverse-field Ising chain

We study the distribution of finite size pseudo-critical points in a one-dimensional random quantum magnet with a quantum phase transition described by an infinite randomness fixed point. Pseudo-critical points are defined in three different ways: the position of the maximum of the average entanglement entropy, the scaling behavior of the surface magnetization, and the energy of a soft mode. All three lead to a log-normal distribution of the pseudo-critical transverse fields, where the width scales as $L^{-1/\nu}$ with $\nu=2$ and the shift of the average value scales as $L^{-1/\nu_{typ}}$ with $\nu_{typ}=1$, which we related to the scaling of average and typical quantities in the critical region.Comment: 4 pages, 2 figure

Prototype Development For a Leak-Preventive Toilet Flush System- An Met Senior Design (Capstone) Project

A senior design (Capstone) project for three mechanical engineering technology students at Old Dominion University is described. A prototype design is presented to perform the functional test of a leak-preventive toilet system. There are two major leaks in the toilet water tank. In the first case, leaking occurs when the seal in the water tank becomes aged. The leak is very easy to detect visually, since the outside of the tank and the floor becomes wet. In the second case, leak occurs when the flapper valve can\u27t complete shut off the water, due to corrosion or damage of the rubber components. Water will flow down to the toilet through stand-up tube. The leaking may be very difficult to detect, since it may not be noisy and can\u27t be detected visually. Although there have been several ideas proposed to solve the leaking problem, they are either impractical or need critical adjustments during the installation. Also, the operation is usually different from regular flush systems. In this project, students are asked to develop a leak-preventive prototype by modifying the concept of a dual-valve system. In addition to functional analysis, students also consider the factors of manufacturing, installation, operation, design reliability, and adaptability to typical flush systems. Results show that the prototype can prevent the leak very effectively and can be applied to two major toilet flush systems. By using a magnetic activating mechanism in this design, the user won\u27t feel any difference when compared to the operation of either of the flush systems

Response-surface-model-based system sizing for nearly/net zero energy buildings under uncertainty

Properly treating uncertainty is critical for robust system sizing of nearly/net zero energy buildings (ZEBs). To treat uncertainty, the conventional method conducts Monte Carlo simulations for thousands of possible design options, which inevitably leads to computation load that is heavy or even impossible to handle. In order to reduce the number of Monte Carlo simulations, this study proposes a response-surface-model-based system sizing method. The response surface models of design criteria (i.e., the annual energy match ratio, self-consumption ratio and initial investment) are established based on Monte Carlo simulations for 29 specific design points which are determined by Box-Behnken design. With the response surface models, the overall performances (i.e., the weighted performance of the design criteria) of all design options (i.e., sizing combinations of photovoltaic, wind turbine and electric storage) are evaluated, and the design option with the maximal overall performance is finally selected. Cases studies with 1331 design options have validated the proposed method for 10,000 randomly produced decision scenarios (i.e., users’ preferences to the design criteria). The results show that the established response surface models reasonably predict the design criteria with errors no greater than 3.5% at a cumulative probability of 95%. The proposed method reduces the number of Monte Carlos simulations by 97.8%, and robustly sorts out top 1.1% design options in expectation. With the largely reduced Monte Carlo simulations and high overall performance of the selected design option, the proposed method provides a practical and efficient means for system sizing of nearly/net ZEBs under uncertainty

Optimization on fresh outdoor air ratio of air conditioning system with stratum ventilation for both targeted indoor air quality and maximal energy saving

Stratum ventilation can energy efficiently provide good inhaled indoor air quality with a proper operation (e.g., fresh outdoor air ratio). However, the non-uniform CO2 distribution in a stratum-ventilated room challenges the provision of targeted indoor air quality. This study proposes an optimization on the fresh outdoor air ratio of stratum ventilation for both the targeted indoor air quality and maximal energy saving. A model of CO2 concentration in the breathing zone is developed by coupling CO2 removal efficiency in the breathing zone and mass conservation laws. With the developed model, the ventilation parameters corresponding to different fresh outdoor air ratios are quantified to achieve the targeted indoor air quality (i.e., targeted CO2 concentration in the breathing zone). Using the fresh outdoor air ratios and corresponding ventilation parameters as inputs, energy performance evaluations of the air conditioning system are conducted by building energy simulations. The fresh outdoor air ratio with the minimal energy consumption is determined as the optimal one. Experiments show that the mean absolute error of the developed model of CO2 concentration in the breathing zone is 1.9%. The effectiveness of the proposed optimization is demonstrated using TRNSYS that the energy consumption of the air conditioning system with stratum ventilation is reduced by 6.4% while achieving the targeted indoor air quality. The proposed optimization is also promising for other ventilation modes for targeted indoor air quality and improved energy efficiency

Heat removal efficiency of stratum ventilation for air-side modulation

Stratum ventilation has significant thermal non-uniformity between the occupied and upper zones. Although the non-uniformity benefits indoor air quality and energy efficiency, it increases complexities and difficulties in the air-side modulation. In this study, a heat removal efficiency (HRE) model is first established and validated, and then used for the air-side modulation. The HRE model proposed is a function of supply air temperature, supply airflow rate and cooling load. The HRE model proposed has been proven to be applicable to stratum ventilation and displacement ventilation for different room geometries and air terminal configurations, with errors generally within ±5% and a mean absolute error less than 4% for thirty-three experimental cases and five simulated cases. Investigations into the air-side modulation with the proposed HRE model reveal that for both the typical stratum-ventilated classroom and office, the variable-air-volume system can serve a wider range of cooling load than the constant-air-volume system. The assumption of a constant HRE used in the conventional method could lead to errors in the room temperature prediction up to ±1.3 °C, thus the proposed HRE model is important to the air-side modulation for thermal comfort. An air-side modulation method is proposed based on the HRE model to maximize the HRE for improving energy efficiency while maintaining thermal comfort. Results show that the HRE model based air-side modulation can improve the energy efficiency of stratum ventilation up to 67.3%. The HRE model based air-side modulation is also promising for displacement ventilation