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

Aspire食品集团开始在安大略省伦敦市建设世界上最大的板球养殖场。该设施将部署专有传感器、自主机器人、集中分配系统和定制组件，从昆虫孵化到收获，从而实现智能农业。系统地实时控制复杂的设施，提高了农业技术的成功率。主要的预期挑战是对农场设施的最佳室内环境进行建模、模拟、收集数据和预测，该设施拥有约9.5万立方米的塑料手提箱存储空间，其中存放着蟋蟀、它们的食物和水。在一个非常拥挤的空间里，蟋蟀在受控的环境下从孵化到收获在集装箱里呆了28天。考虑到设施的大小和密度，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，是该项目具有挑战性的部分。蟋蟀的呼吸系统和饮用水在设施内产生了大量的湿度，因此除湿室内条件消耗很高的电能。此外，由于室外气候、能源限制和空气过滤过程要保持所需的空气质量，自然通风和维护零废物系统的实施受到限制。因此，本研究致力于提供高性能的基于计算的计算流体动力学(CFD)室内温度和气流的建模和模拟，以提供有助于确定昆虫从孵化到收获的最佳宜居条件的输入。这种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控环境。这项研究将建筑信息建模与传感器技术和物联网(IoT)相结合，为未来创建智能农业的数字孪生兄弟奠定了基础，有利于实时控制和监测农场的温度、气流和湿度。

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.