Atmospheric Flight Mechanics (AFM) is one of the cornerstones of aeronautical engineering and includes subjects like aerodynamic prediction, stability and control, dynamics, and vehicle design. These topics are critical to the success of aircraft development, so AFM is considered one of the most important foundational knowledge areas for aerospace engineering. Unfortunately, students graduating from aerospace engineering programs are often underprepared to perform in AFM jobs. This ongoing research focuses on developing a blueprint for assessing conceptual understanding of AFM concepts. Since existing literature suggests that novices and experts organize knowledge differently, comparing students' and experts' mental models can shine a light on the alternative conceptions that students retain post-instruction. As such, framing the study around synthetic mental models can be advantageous. To explore these mental models, three types of data have been collected and analyzed. Document analysis was done on course documents to identify what concept relationships were being presented to the students. Class observations were conducted to analyze how concepts are introduced to students and what relationships are highlighted by the instructor. Finally, a concept mapping activity was facilitated to study the mental models that the students built after instruction. The results show a lack of synthetization between the knowledge introduced in the classroom and students' prior knowledge which translated into student mental models that do not meet some of the expectations of the course. Moreover, this study highlights the importance of the instructor's awareness of their own expectations for learning and knowledge synthetization in the design of an AFM course. / Doctor of Philosophy / Conceptual understanding research has often focused on how students develop their understanding of scientific concepts that are difficult to grasp. Through this research, many assessment techniques have been developed and implemented in the design of STEM courses. However, many of these techniques and implementations have been limited to K-12 or introductory engineering courses. Atmospheric Flight Mechanics (AFM) is an important part of the aerospace curriculum that has yet to be studied under the conceptual understanding lens. The goal of this study was to investigate how students develop AFM conceptual understanding using a synthetic mental model framework. This study focused on answering three questions, how are students being introduced to AFM concepts?, how do students' mental models develop throughout the semester?, and how do the students' and instructor's mental models compare?. Through the exploration of class documents, class observations, and concept mapping activities, this research found that students are having a hard time making sense of new knowledge based on their previous understanding of similar topics. By trying to integrate this new knowledge with their previous mental models, students are developing synthetic mental models that do not align with the scientific explanations of the topic. This study also found that instructors are often unaware of their own knowledge and expectations for learning which makes knowledge synthetization harder for the students. Therefore, addressing these issues during course design could make an AFM course easier to understand for students.

Um método para avaliação do uso de ganho adequado em ensaios de verificação de PIO (Pilot Induced Oscillations) é apresentado. As tarefas de manobra sintética (Synthetic Tracking Task) são utilizadas para demonstração. A teoria é baseada no conceito de entropia estatística proveniente da teoria da informação e no modelo estrutural do piloto humano. O método é apresentado para manobras executadas no eixo lateral e oferece uma medida do ganho humano utilizado durante a sua execução em malha-fechada. Para a modelagem da planta é utilizado modelo black-box com equacionamento de espaço de estados e identificação de parâmetros. Dados de ensaios em voo provenientes de uma aeronave de transporte certificada FAR-25 são utilizados para medir a razão entre o tempo gasto pelo piloto humano em uma malha fechada em posição versus o tempo em uma malha de derivada da posição (roll vs. roll rate). Esta medida é proposta como validadora da execução correta do ensaio. / A method is proposed to verify losed-loop adequate flight test piloting gain in PIO aircraft certification. The synthetic tracking task PIO flight test is used. The theory is based on the entropy concept from information theory and on the structural pilot model of the human pilot. The method is presented for single axis pilot tracking maneuvers and offers a measure of the human pilot gain employed during its execution. A black-box, state-space, parameter-identified model is used for the plant. Flight test data from a FAR-25 transport aircraft is used to verify the theory of how to determine a measure of the ratio between time spent by the human pilot in the error loop versus in the error rate loop to control the aircraft. This measure is proposed as a test point validation method for PIO flight testing.

Um método para avaliação do uso de ganho adequado em ensaios de verificação de PIO (Pilot Induced Oscillations) é apresentado. As tarefas de manobra sintética (Synthetic Tracking Task) são utilizadas para demonstração. A teoria é baseada no conceito de entropia estatística proveniente da teoria da informação e no modelo estrutural do piloto humano. O método é apresentado para manobras executadas no eixo lateral e oferece uma medida do ganho humano utilizado durante a sua execução em malha-fechada. Para a modelagem da planta é utilizado modelo black-box com equacionamento de espaço de estados e identificação de parâmetros. Dados de ensaios em voo provenientes de uma aeronave de transporte certificada FAR-25 são utilizados para medir a razão entre o tempo gasto pelo piloto humano em uma malha fechada em posição versus o tempo em uma malha de derivada da posição (roll vs. roll rate). Esta medida é proposta como validadora da execução correta do ensaio. / A method is proposed to verify losed-loop adequate flight test piloting gain in PIO aircraft certification. The synthetic tracking task PIO flight test is used. The theory is based on the entropy concept from information theory and on the structural pilot model of the human pilot. The method is presented for single axis pilot tracking maneuvers and offers a measure of the human pilot gain employed during its execution. A black-box, state-space, parameter-identified model is used for the plant. Flight test data from a FAR-25 transport aircraft is used to verify the theory of how to determine a measure of the ratio between time spent by the human pilot in the error loop versus in the error rate loop to control the aircraft. This measure is proposed as a test point validation method for PIO flight testing.