在办公楼中使用混凝土核心系统可以实现显著的冷却节能。虽然这项技术被广泛用于冷却房间，但在潮湿气候地区使用它可能对表面冷凝问题至关重要。一种很有前途的表面冷凝控制方法是模型预测控制（MPC）。本研究提出了基于MPC的表面冷凝控制框架。在现有热湿传递模型的基础上建立了动态模型，并用实验数据对模型进行了标定。采用曲线拟合过程作为校准方法。通过曲线拟合过程，测量数据和模拟数据之间的差距被最小化。然后根据最佳拟合曲线得出最可能的物理参数值，并输入到动态模型中，生成表面冷凝预测图。 通过将表面凝结预测图集成到MPC框架中，可以提前估计第二天的表面凝结风险。根据表面凝结风险信息，混凝土芯系统可以在混凝土表面没有凝结的情况下运行。无论气候区如何，当混凝土核心系统由MPC框架控制时，该系统比传统的机械通风系统实现了更大的冷却能量需求减少。引用:2019年冬季会议，佐治亚州亚特兰大，会议论文

Utilization of a concrete core system in office buildings can achieve significant cooling energy savings. Although this technique is widely used for the purpose of cooling rooms, utilizing it in humid climate regions can be critical for surface condensation problems. A promising approach to the surface condensation control is Model Predictive Control (MPC). In this study, MPC based surface condensation control framework is presented. The dynamic model was developed based on existing heat and moisture transfer models, and the developed model was calibrated with experimental data. The curve fitting process was adopted as a calibration method. With the curve fitting process, a gap between measured data and simulated data is minimized. The most probable physical parameter values were then derived from the best fit curve, and input into the dynamic model to generate the surface condensation prediction chart. By integrating the surface condensation prediction chart into the MPC framework, the risk of surface condensation for the following day can be estimated in advance. Based on the surface condensation risk information, the concrete core system can be operated without having the condensation on the concrete surface. Regardless of climate zone, when the concrete core system was governed by the MPC framework, the system achieved greater cooling energy demand reduction than the conventional mechanical ventilation system.