Browsing by Subject "dynamic modeling"

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    Dynamic Modeling For Simulation And Experimentation Tools Used In The Analysis Of Space Vehicle Trajectories
    (2023-08) Elke, William
    Current and future missions to send humans to the Moon and beyond will have increasingly strict requirements on the performance and robustness of the mission vehicles. These requirements will push all aspects of the vehicles to advance to ensure mission safety and success. This includes the guidance, navigation, and control (GNC) systems operating on board. Novel GNC systems must be matured in an environment analogous to those they operate in, but these operating conditions are difficult to replicate. The first part of this dissertation presents the Cost- and Risk-Reducing Quadcopter System (CRQS, pronounced "circus"), a platform proposed to provide a low-cost, low-risk setting to mature novel GNC systems. The system is modeled, then implemented in numerical simulations to analyze a control system's ability to track a generated trajectory. The work done to fabricate a physical flying inverted pendulum, a necessary step to reach the complete CRQS, is then presented. As spacecraft grow to accommodate larger payloads and more distant destinations, the amount of liquid propellant on board grows. The interactions between a spacecraft and the liquid propellant can have detrimental effects on the performance of the spacecraft's GNC systems. The second part of this dissertation develops a low-order approximate dynamic model of a spacecraft and its liquid onboard propellant in a low-g environment. The model is then implemented in numerical simulations to analyze the trajectory of the Apollo-era service module (SM) for the probability of recontact after jettison from the command module (CM).
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    Modeling the dynamics of the plant immune response
    (2022-03) Liu, Xiaotong
    Dynamic modeling is essential for understanding the temporal behavior of a system. Deriving dynamic models from biological omics data can enable effective information reduction by leveraging a few interpretable parameters and capturing the hidden structure in the data. Thanks to the availability of RNA-seq, temporal transcriptomes have been widely profiled as dynamic snapshots of biological responses. My PhD study focuses on dynamic modeling of plant immunity, a plant defense response induced by pathogens. There are two well-defined modes of inducible immunity of plant to overcome pathogen attack, namely pattern triggered immunity (PTI) and effector triggered immunity (ETI). Researchers have generated rich sources of temporal transcriptome data in plants upon challenge of pathogens or pathogen derivatives during both PTI and ETI. My contribution to dynamic modeling of plant immunity comes primarily with two projects. In my main project, I developed a novel computational approach based on an ordinary differential equation system to interpreting the transcriptome dynamics during ETI. The modeling results uncovered intrigue data patterns that direct deep insights into the transcriptional regulation of transcription factors during ETI. In my other project, I developed mechanistic models based on the transcript response of CBP60g, a marker gene of pattern-triggered immunity. The model not only interpreted the dynamics of CBP60g response but also predicted the mechanistic roles of three plant immunity genes in regulating CBP60g transcription. Overall, my efforts on dynamic modeling of plant immunity bring novel mathematical frameworks for transcript/transcriptome data interpretation and derive valuable biological predictions that shed light on transcriptional mechanisms of plant immunity.