智能建筑的虚拟测试

Julien Bruneau, C. Consel, M. O'Malley, Walid M. Taha, Wail Masry Hannourah
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引用次数: 11

摘要

智能建筑有望彻底改变我们的生活方式。从气候控制到火灾管理的各种应用都可能对这些服务的质量和成本产生重大影响。然而,智能建筑和任何对人类安全和生活有直接影响的技术都必须经过广泛的测试。通过计算机模拟进行的虚拟测试可以显著降低测试成本,从而加速新应用的开发。不幸的是,构建物理精确的模拟代码可能是一项劳动密集型工作。为了解决这个问题,我们提出了一个快速、物理精确的虚拟测试框架。所提出的框架既支持离散分布式系统的分析建模,也支持承载它的物理环境。所支持的离散模型足够精确,可以自动生成专门的编程框架,帮助开发人员实现这些系统。所支持的物理环境模型是精确到足以生成运行仿真代码的等式规范。结合起来,这两个框架可以模拟活动系统和物理环境。这些模拟可用于在精确的虚拟实验环境中监视应用程序的行为并收集有关其性能的统计数据。为了说明这种方法,我们提出了供暖、通风和空调(HVAC)系统的模型。利用这些模型,我们构建了虚拟实验,说明了该方法如何用于优化建筑物的能源和气候控制成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Virtual Testing for Smart Buildings
Smart buildings promise to revolutionize the way we live. Applications ranging from climate control to fire management can have significant impact on the quality and cost of these services. However, smart buildings and any technology with direct effect on human safety and life must undergo extensive testing. Virtual testing by means of computer simulation can significantly reduce the cost of testing and, as a result, accelerate the development of novel applications. Unfortunately, building physically-accurate simulation codes can be labor intensive. To address this problem, we propose a framework for rapid, physically-accurate virtual testing. The proposed framework supports analytical modeling of both a discrete distributed system as well as the physical environment that hosts it. The discrete models supported are accurate enough to allow the automatic generation of a dedicated programming framework that will help the developer in the implementation of these systems. The physical environment models supported are equational specifications that are accurate enough to produce running simulation codes. Combined, these two frameworks enable simulating both active systems and physical environments. These simulations can be used to monitor the behavior and gather statistics about the performance of an application in the context of precise virtual experiments. To illustrate the approach, we present models of Heating, Ventilating and Air-Conditioning (HVAC) systems. Using these models, we construct virtual experiments that illustrate how the approach can be used to optimize energy and cost of climate control for a building.
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