A model predictive control (MPC) system with an adaptive building model based on thermal-electrical analogy for the hybrid air conditioning system using the radiant floor and all-air system for heating is proposed in this paper to solve the heating supply control difficulties of the railway station on Tibetan Plateau. The MPC controller applies an off-line method of updating the building model to improve the accuracy of predicting indoor conditions. The control performance of the adaptive MPC is compared with the proportional-integral-derivative (PID) control, as well as an MPC without adaptive model through simulation constructed based on a TRNSYS-MATLAB co-simulation testbed. The results show that the implementation of the adaptive MPC can improve indoor thermal comfort and reduce 22.2% energy consumption compared to the PID control. Compared to the MPC without adaptive model, the adaptive MPC achieves fewer violations of constraints and reduces energy consumption by 11.5% through periodic model updating. This study focuses on the design of a control system to maintain indoor thermal comfort and improve system efficiency. The proposed method could also be applied in other public buildings.

Smoke control is a crucial issue in a long-distance subway tunnel fire, and a two-point extraction ventilation system is an effective way to solve this problem, due to the characteristics of controlling the smoke in a limited area and removing high-temperature and toxic smoke in time. In this study, the ceiling temperature distribution and the critical exhaust volumetric flow rate to control the smoke in the zone between two extraction vents were investigated in a long-distance subway tunnel fire with a two-point extraction ventilation system. Experiments were carried out in a 1/20 reduced-scale tunnel model based on Froude modeling. Factors, including the heat release rate (HRR), the extraction vent length, the internal distance between two extraction vents and exhaust volumetric flow rate, were studied. Smoke temperature below the ceiling, exhaust volumetric flow rate and smoke spreading configurations were measured. The ceiling temperature distribution was analyzed. Meanwhile, an empirical equation was developed to predict the critical exhaust volumetric flow rate based on the one-dimensional theory, experimental phenomenon and the analysis of forces acting at the smoke underneath the extraction vent. The coefficients in the empirical equation were determined by experimental data. Compared with the experimental results, the developed empirical equation can predict the critical exhaust volumetric flow rate well. Research outcomes in this study will be beneficial to the design and application of two-point extraction ventilation system for a long-distance subway tunnel fire.

A chilled water system transports cooling functionality from refrigerators to users via heating, ventilation, and air conditioning (HVAC) systems. This paper investigated an optimal control strategy to regulate the volume flow rate of each user branch in a chilled water system, considering the minimum resistance operation to reduce energy consumption. An artificial neural network (ANN) was adopted to establish the nonlinear relationship between the volume flow rate of each user branch, pump frequency, and valve opening of each user branch. An optimal control strategy for a chilled water HVAC system is proposed in this article, according to the pump-valve combined control (PVCC) principle and an ANN model, i.e., pump-valve combined control using an artificial neural network model (PVCC-ANN). A series of tests were conducted to collect data to train the ANN model and analyze the performance of the PVCC-ANN in an experimental chilled water system. The results show that the trained ANN model has good prediction performance. A minimum resistance operation can be achieved to control the volume flow rate of each user branch independently by using the PVCC-ANN model. Moreover, the proposed PVCC-ANN method shows good energy-saving performance in chilled water systems, which can be attributed to the minimum resistance operation. Taking the energy consumption of the pump’s constant frequency operation as the reference, the energy saving rate using the PVCC-ANN is between 14.3% and 58.6% under 10 operating conditions, as reported in this paper.

The organic Rankine cycle (ORC) is widely used to recover industrial waste heat. For an ORC system using industrial waste hot water as a heat source, a novel hot water split-flow dual-pressure organic Rankine cycle (SFD-ORC) system is developed to improve the performance of the ORC. The maximum net power output was selected to compare three ORC systems, including basic ORC (B-ORC), conventional dual-pressure ORC (CD-ORC) and SFD-ORC. A genetic algorithm (GA) was used to optimize the parameters to search the maximum net power output of ORCs. The maximum net output power was taken as the standard of performance evaluation. The results show that, under the same hot water inlet temperature condition, the optimal hot water outlet temperature of B-ORC is much higher than that of CD-ORC and SFD-ORC, which indicates that less thermal energy could be utilized to convert to power in B-ORC. The optimal hot water temperature at the outlet of evaporator 1 in SFD-ORC is higher than that in CD-ORC, which means SFD-ORC could make more efficient use of the high-grade thermal energy of hot water. The SFD-ORC could obtain the highest net output power under the optimal parameter conditions, followed by the CD-ORC system, while the B-ORC has the lowest net output power. Moreover, with the increase in the hot water inlet temperature, the advantage of SFD-ORC becomes increasingly obvious. When the hot water inlet temperature is 90 °C, the net output power of SFD-ORC at is 6.22% higher than that of CD-ORC. The net output power of SFD-ORC at 130 °C increases to 9.7% higher than that of CD-ORC. The SFD-ORC presents better system performance and has great engineering application potential.

Tunnels with natural ventilation and extraction have become the focus of ventilation research in recent years. It is significant to study the characteristics of smoke in tunnel fires to ensure the safety of people and the tunnel structure. Previous research has mainly focused on natural ventilation in horizontal tunnels, and there are few studies on sloped tunnels. In this paper, we studied the smoke characteristics of natural ventilation extraction in slope tunnel fires both experimentally and theoretically. The small-scale experimental results showed that the position of the fire source, heat release rate (HRR), and the size of the shaft had little effect on the deflection angle of the fire plume. The deflection angle of fire plume was only related to the tunnel slope and increased with the tunnel slope. The slope had no effect on the smoke temperature distribution on the downside of the tunnel, while the smoke temperature on the upside decreased with the increase in the slope. The calculation models of the maximum smoke temperature rise and the smoke temperature distribution were obtained based on the experimental results and theoretical analysis. Compared with the experimental data, the developed semi-empirical models could provide a reliable prediction of smoke temperature.