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Energy Recovery: Connecting Core Performance to Building Systems

Energy Recovery: Connecting Core Performance to Building Systems
能量回收:将核心性能与建筑系统联系起来
批准号:
573018-2022
负责人:
Rogak, StevenSN
金额:
$1.66万
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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中文摘要
翻译
UBC的研究人员与CORE合作,开发了通过膜、ERV通道和全ERV核心的运输过程的预测模型。这些模型包括膜偏转效应、变渗透率效应和冷凝效应。然而,这些核心模型还没有被整合到通风系统的系统模型中,更不用说整个建筑模型了。在过去7年的合作中出现了一些重要的系统级问题,我们建议在下一阶段的工作中解决这些问题。CORE可以设计定制膜材料。气候和建筑运行如何影响膜的选择?什么是最好的方法,以减轻凝结和结霜的影响在erv ?最近我们研究了流诱导的膜偏转对ERV性能的影响。在系统级别,不平衡的流量和构建压力偏差是如何影响系统性能的?在此之前,我们研究了膜污染的影响。考虑到整个建筑物的运作,包括渗透和再循环比率,如何使用过滤器来改善空气质量、ERV寿命和能源效率?这些问题既与极端污染事件(如野火)有关,也与疾病的室内空气传播(如:COVID-19)。该计划将资助2名博士生开发和验证ERV模型并建立规模。
英文摘要
UBC researchers working with CORE have developed predictive models of transport processes through membranes, in ERV flow passages, and of full ERV cores. These models include the effects of membrane deflection, variable permeability and condensation. However, these models of the core have not yet been integrated into a systems model of the ventilation system, let alone a whole building model. Some important systems-level questions arise from our collaborations in the last 7 years, which we propose to address in the next phase of work. CORE can engineer custom membrane materials. How do climate and building operation affect the choice of the membrane?What is the best way to mitigate the effects of condensation and frosting in ERVs?Recently we have investigated the effect of flow-induced membrane deflections on ERV performance. At the systems level, how do unbalanced flows and building pressure biases affect system performance?Previously, we investigated the effect of fouling of membranes. Considering whole-building operation, including infiltration and recirculation ratios, how should filters be used to improve air quality, ERV life, and energy efficiency? These issues are relevant to both extreme pollution events (such as wildfires) and indoor airborne transmission of disease (eg. COVID-19).The program would fund a 2 PhD students developing and validating models at the ERV and building scales.
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