Numerical modelling of indoor environment for energy-efficient bio-manufacturing facilities

节能生物制造设施室内环境数值模拟

• 批准号: 570405-2021
• 负责人: Bitsuamlak, Girma
• 金额: $ 2.19万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=719052
• 关键词: Numerical; modelling; indoor; environment; energy

Aspire Food Group begins constructing the world's largest cricket farm in London, Ontario. This facility will have a smart farming by deploying a proprietary sensor, autonomous robotics, centralized distribution systems, and custom assemblies to farm insects from hatch to harvest. Controlling the complex facility systematically in real-time elevates the success of the farming technology. The main anticipated challenge is to model, simulate, collect data, and predict the optimum indoor environment of the farm facility that contains around 95,000 cubic meter of plastic totes storage, which houses crickets, their food, and water. The crickets stay in the container from hatch to harvest for 28 days under a controlled environment in a very densely packed space. Considering the size and density of the facility, ensuring air circulation around all the totes, providing enough oxygen, controlling temperature and relative humidity for optimal productivity is the challenging part of the project. The cricket's respiratory system and drinking water produce a large amount of humidity inside the facility, hence dehumidifying the indoor condition consumes high electric energy. Further, due to the outdoor climate, energy constraint, and air filtration process to maintain the required air quality, there is a limitation on the implementation of natural ventilation and maintenance of the zero-waste system. Therefore, this research study endeavors to provide high-performance-computing-based Computational fluid dynamics (CFD) modelling and simulation of indoor temperature and airflow to provide input that will be useful for determining optimal livable condition for the insects from hatch to harvest. This modeling and simulation will be used to identify the optimal location of temperature, oxygen level detectors, and relative humidity control sensors that will be used to monitor the environment during the operation of the facility. This research will pave the ground for creating a digital twin of the smart-farming in the future by combining Building Information Modeling integrated CFD, with sensor technology and internet-of-things (IoT), which can be beneficial to control and monitor the temperature, airflow, and humidity of the farm real time.

Aspire Food Group开始在安大略的伦敦建造世界上最大的板球农场。该设施将通过部署专有传感器，自主机器人，集中分配系统和自定义组件来实现智能农业，以从孵化到收获来养殖昆虫。实时系统地控制复杂的设施提升了农业技术的成功。预计的主要挑战是建模、模拟、收集数据和预测农场设施的最佳室内环境，该设施包含约95，000立方米的塑料手提袋存储，其中包含蟋蟀、食物和水。蟋蟀在一个非常密集的空间中，在受控的环境下，从孵化到收获，在容器中停留28天。考虑到设施的规模和密度，确保所有手提箱周围的空气流通，提供足够的氧气，控制温度和相对湿度以实现最佳生产率是该项目的挑战部分。蟋蟀的呼吸系统和饮用水在设施内产生大量的湿度，因此除湿室内条件消耗高电能。此外，由于室外气候、能源限制及维持所需空气质量的空气过滤过程，自然通风的实施及零废弃物系统的维护存在限制。因此，这项研究致力于提供基于高性能计算的计算流体动力学（CFD）建模和室内温度和气流模拟，以提供输入，这将有助于确定昆虫从孵化到收获的最佳宜居条件。该建模和模拟将用于确定温度、氧气水平检测器和相对湿度控制传感器的最佳位置，这些传感器将用于在设施运行期间监测环境。这项研究将为未来通过将建筑信息建模集成CFD，传感器技术和物联网（IoT）相结合，创建智能农业的数字孪生模型奠定基础，这有助于控制和监测农场的温度，气流和湿度真实的时间。