Alabama Space Grant Consortium

Prognostic Health Management (PHM) is the disciplined application of measurement, monitoring, and support strategies to protect structural, electrical, or data entities precluding the failure of measured systems in all phases of operation. Model-Based Systems Engineering (MBSE) can be used to formalize system structure, operations, behavior, and requirements using an Architecture Framework (AF), Process Framework (PF), modeling language, and ontology; whereas the AF, PF, and modeling language may be specific to the program or mission employing MBSE, ontologies may be developed specific to a given domain. The PHM domain considers failure modes, effects, and criticality, and ontological system analysis in this domain can inform system structure, operations, behavior, or requirements. A reference ontology for the PHM domain in spacecraft avionics is presented here including aspects of existing ontologies such as the Basic Formal Ontology (BFO), a Top-Level Ontology (TLO) newly recognized by the International Organization for Standardization (ISO), the Information Artifact Ontology (IAO), and the Space Object Ontology (SOO). A distinction is made between a full PHM domain ontology, which would include many mechanical or electrical systems with myriad purposes, and a PHM domain ontology specific to spacecraft avionics. Present ontological development originated using the parlance and format of BFO and IAO in Stanford University’s Protégé software but diverged to include International Union of Pure and Applied Chemistry (IUPAC) terminology and classifications. When interacting with this ontology, engineers seeking to characterize system-specific failure modes, effects, and criticality can query the ontology with their hardware or software entities to obtain failure information specific to the operation of their system in a given operational environment. While this domain ontology is robust, the authors do not claim it to be complete or validated for all spacecraft avionics. It should be considered version one of a useful PHM tool with continual updates occurring after peer review and feedback.

View Video Presentation: https://doi.org/10.2514/6.2021-1792.vid Bent SMA flat plates as solar array hinge actuators were fabricated, heat treated, and DSC tested to determine phase transition properties for a predictive model framework that includes Gauss-Siedel thermomechanical, free energy constitutive, and rotational kinematic relations. The inclusion of pseudoelastic and bending stresses to the phase transition model were found to prevent accurate prediction of transition temperatures. System considerations are presented for addressing erroneous bending phase transition models, optimizing actuation, and validating the model against empirical data.

Course-based undergraduate research experiences (CUREs) have grown as an influential pedagogical tool which supports student learning, bolstering STEM student retention, and fostering a scientific identity among learners. The evolution of CUREs has transitioned from individual faculty integrating their research into teaching laboratories to the establishment of comprehensive systems sustaining faculty engagement in these experiences. Within this landscape, the MDH CURES Community (MCC) exemplifies a robust system composed of a community of faculty that supports the sustained implementation of CUREs, with a protein-centric approach focused on malate dehydrogenase. Within the MCC there are several scientific themes designed to execute an MDH-focused CURE, one of which explores protein-protein interactions (PPI) and the impact of post-translational modifications (PTM) on protein function and regulation. We will showcase diverse implementations of a PPI/PTM CURE across diverse courses, from first-year gateway courses to upper-division laboratory courses. Moreover, we'll highlight our success in fostering external collaborations-both between students and faculty and faculty to faculty across different universities. Prior research indicates that such external collaborative CUREs significantly extend student learning and promote positive attitudes towards STEM fields. Our presentation will provide some of the different approaches, such as molecular modeling, site-directed mutagenesis, kinetic analysis, and pull-down assays that we've employed to investigate PPIs and PTMs within the CURE framework. We will discuss different approaches that we have successfully implemented to investigate PPIs in the CURE setting while sharing examples of new opportunities for implementing a CURE focused on PPIs and PTMs. Funded by NSF RCN UBE 2119918.