<div>Wireless sensor networks are highly integrated across numerous industries from industrial</div><div>manufacturing to personal health monitoring. They provide several key benefits over</div><div>traditional wired systems including positioning flexibility, modularity, interconnectivity, and</div><div>robust data routing schemes. However, their adoption into certain sectors such as vacuum</div><div>and aerospace has been slow due to tight regulation, data security concerns, and device</div><div>reliability.</div><div>Lyophilization is a desiccation technique used to stabilize sensitive food and drug products</div><div>using vacuum sublimation. A series of wireless devices based on the Pirani architecture are</div><div>developed to quantify the spatial variations in pressure and temperature throughout this</div><div>process. The data is coupled to computational fluid dynamics simulations to estimate the</div><div>sublimation rate over time. This information is then used to quantify the heat and mass</div><div>transfer characteristics of the product, allowing estimates of product temperature and mass</div><div>flux to be obtained for an arbitrary cycle. This capability is significant, having the ability</div><div>to accelerate process development and reduce manufacturing time.</div><div>Drying performance during lyophilization is highly sensitive to the dynamics of the freezing</div><div>process. This work therefore also develops a wireless network to monitor both gas</div><div>pressure and temperature throughout the controlled ice nucleation process, a technique used</div><div>to improve batch uniformity by inducing simultaneous and widespread ice nucleation via</div><div>adiabatic decompression. The effects of initial charge pressure, ballast composition, and vial</div><div>size are investigated. Experimental data is supported by numerical modeling to describe the</div><div>evolution of the true gas temperature during the discharge event.</div><div>Finally, The mechanisms governing the lyophilization process are directly applied to the</div><div>aerospace industry in the form of a novel milliNewton-class evaporation-based thruster concept.</div><div>The device was tested under vacuum using a torsional balance and demonstrated peak</div><div>thrust magnitudes on the order of 0.5 mN. A state observer model was then implemented</div><div>to decouple the dynamics of the balance with the time-dependent thrust input. With this</div><div>model the true time-dependent thrust output and corresponding thruster performance are</div><div>analyzed.</div>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/14474076 |
| Date | 06 May 2021 |
| Creators | Andrew Strongrich (10691970) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/MEMS_Wireless_Sensor_Networks_for_Spacecraft_and_Vacuum_Technology/14474076 |
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