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  1. Electric Aircraft have the potential to revolutionize short-distance air travel with lower operating costs and simplified maintenance. However, due to the long lead-time associated with procuring batteries and the maintenance challenges of replacing and repairing batteries in electric aircraft, there are still unanswered questions related to the true long-term operating costs of electric aircraft. This research examines using a load-sharing system in electric aircraft to optimally tune battery degradation in a multi-battery system such that the battery life of a single battery is extended. The active optimization of energy drawn from multiple battery packs means that each battery pack reaches its optimal replacement point at the same time; thereby simplifying the maintenance procedure and reducing cost. This work uses lithium iron phosphate batteries experimentally characterized and simulated in OpenModelica for a flight load profile. Adaptive agents control the load on the battery according to factors such as state of charge, and state of health, to respond to potential faults. The findings in this work show the potential for adaptive agents to selectively draw more power from a healthy battery to extend the lifespan of a degraded battery such that the remaining useful life of both batteries reaches zero at the same time. Simulations show that dual battery replacement can be facilitated using the proposed method when the in-service battery has a remaining useful life of greater than 0.5; assuming that the replacement battery it is paired with has a remaining useful life of 1.0. Limitations of the proposed method are discussed within this work. 
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    Free, publicly-accessible full text available January 4, 2025
  2. Free, publicly-accessible full text available December 1, 2024
  3. In high-rate structural health monitoring, it is crucial to quickly and accurately assess the current state of a component under dynamic loads. State information is needed to make informed decisions about timely interventions to prevent damage and extend the structure’s life. In previous studies, a dynamic reproduction of projectiles in ballistic environments (DROPBEAR) testbed was used to evaluate the accuracy of state estimation techniques through dynamic analysis. This paper extends previous research by incorporating the local eigenvalue modification procedure (LEMP) and data fusion techniques to create a more robust state estimate using optimal sampling methodologies. The process of estimating the state involves taking a measured frequency response of the structure, proposing frequency response profiles, and accepting the most similar profile as the new mean for the position estimate distribution. Utilizing LEMP allows for a faster approximation of the proposed model with linear time complexity, making it suitable for 2D or sequential damage cases. The current study focuses on two proposed sampling methodology refinements: distilling the selection of candidate test models from the position distribution and applying a Kalman filter after the distribution update to find the mean. Both refinements were effective in improving the position estimate and the structural state accuracy, as shown by the time response assurance criterion and the signal-to-noise ratio with up to 17% improvement. These two metrics demonstrate the benefits of incorporating data fusion techniques into the high-rate state identification process. 
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    Free, publicly-accessible full text available June 28, 2024
  4. Wildfires are increasing in size, frequency, and intensity, releasing increased amounts of contaminants, including magnetic particles, into the surrounding environment. The aim of this paper is to develop a sensing method for the detection and quantification of magnetic particles (MPs) in fire ash and fire runoff using a compact Time-Domain Nuclear Magnetic Resonance (TD-NMR) system. The system is made up of custom NMR electronics with a compact and rugged permanent magnet array designed to enable future deployment as an in situ sensor. A signal-to-noise ratio of 25 dB was measured for a single scan, and sufficient data can be acquired in one minute. A linear relationship with an R 2 value of 0.9699 was established between transverse relaxation rates and MP concentrations in ash samples. This was validated by testing known dilutions of pure magnetite particles and showing that they fit within the same linear curve. The developed approach was then applied to detect MPs in surface water, where changes in the relaxation rates as high as 400% were observed before and after a wildfire event. MPs were removed from the surface water using a magnetic particle separator to confirm that observed changes were solely due to the presence of MPs. The compact NMR system can be used as a simple and rapid approach to track and quantify the concentrations of magnetic particles released from fire ashes and also from other sources such as discharges from coal ash and other combustion ashes. 
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  5. Free, publicly-accessible full text available July 1, 2024