Conceptual modeling allows abstraction, communication and consensus building in system development. It is challenging to expand and improve the accuracy of models in an iterative process, producing models able to facilitate analysis. Modeling and analysis can be especially challenging in early Requirements Engineering (RE), where high-level system requirements are discovered. In this stage, hard-to-measure non-functional requirements are critical; understanding the interactions between systems and stakeholders is a key to system success. Goal models have been introduced as a means to ensure stakeholder needs are met in early RE. Because of the high-level, social nature of early RE models, it is important to provide procedures which prompt stakeholder involvement (interaction) and model improvement (iteration). Most current approaches to goal model analysis require quantitative or formal information that is hard to gather in early RE, or produce analysis results automatically over models. Approaches are needed which balance automated analysis over complex models with the need for interaction and iteration. This work develops a framework for iterative, interactive analysis for early RE using agent-goal models. We survey existing approaches for goal model analysis, providing guidelines using domain characteristics to advise on procedure selection. We define requirements for an agent-goal model framework specific to early RE analysis, using these requirements to evaluate the appropriateness of existing work and to motivate and evaluate the components of our analysis framework. We provide a detailed review of forward satisfaction procedures, exploring how different model interpretations affect analysis results. A survey of agent-goal variations in practice is used to create a formal definition of the i* modeling framework which supports sensible syntax variations. This definition is used to precisely define analysis procedures and concepts throughout the work. The framework consists of analysis procedures, implemented in the OpenOME requirements modeling tool, which allow users to ask “What if?” and “Is this goal achievable, and how?” questions. Visualization techniques are introduced to aid analysis understanding. Consistency checks are defined over the interactive portion of the framework. Implementation, performance and potential optimizations are described. Group and individual case studies help to validate framework effectiveness in practice. Contributions are summarized in light of the requirements for early RE analysis. Finally, limitations and future work are described.

Conceptual modeling allows abstraction, communication and consensus building in system development. It is challenging to expand and improve the accuracy of models in an iterative process, producing models able to facilitate analysis. Modeling and analysis can be especially challenging in early Requirements Engineering (RE), where high-level system requirements are discovered. In this stage, hard-to-measure non-functional requirements are critical; understanding the interactions between systems and stakeholders is a key to system success. Goal models have been introduced as a means to ensure stakeholder needs are met in early RE. Because of the high-level, social nature of early RE models, it is important to provide procedures which prompt stakeholder involvement (interaction) and model improvement (iteration). Most current approaches to goal model analysis require quantitative or formal information that is hard to gather in early RE, or produce analysis results automatically over models. Approaches are needed which balance automated analysis over complex models with the need for interaction and iteration. This work develops a framework for iterative, interactive analysis for early RE using agent-goal models. We survey existing approaches for goal model analysis, providing guidelines using domain characteristics to advise on procedure selection. We define requirements for an agent-goal model framework specific to early RE analysis, using these requirements to evaluate the appropriateness of existing work and to motivate and evaluate the components of our analysis framework. We provide a detailed review of forward satisfaction procedures, exploring how different model interpretations affect analysis results. A survey of agent-goal variations in practice is used to create a formal definition of the i* modeling framework which supports sensible syntax variations. This definition is used to precisely define analysis procedures and concepts throughout the work. The framework consists of analysis procedures, implemented in the OpenOME requirements modeling tool, which allow users to ask “What if?” and “Is this goal achievable, and how?” questions. Visualization techniques are introduced to aid analysis understanding. Consistency checks are defined over the interactive portion of the framework. Implementation, performance and potential optimizations are described. Group and individual case studies help to validate framework effectiveness in practice. Contributions are summarized in light of the requirements for early RE analysis. Finally, limitations and future work are described.

The past twenty years have seen the successful characterization and computational modeling efforts by the smart materials community to better understand the Shape Memory Alloy (SMA). Commercially available numerical analysis tools, coupled with powerful constitutive models, have been shown to be highly accurate for predicting the response of these materials when subjected to predetermined loading conditions. This thesis acknowledges the development of such an established analysis framework and proposes an expanded design framework that is capable of accounting for the complex coupling behavior between SMA components and the surrounding assembly or system. In order to capture these effects, additional analysis tools are implemented in addition to the standard use of the non-linear finite element analysis (FEA) solver and a full, robust SMA constitutive model coded as a custom user-defined material subroutine (UMAT). These additional tools include a computational fluid dynamics (CFD) solver, a cosimulation module that allows separate FEA and CFD solvers to iteratively analyze fluid-structure interaction (FSI) and conjugate heat transfer (CHT) problems, and the addition of the latent heat term to the heat equations in the UMAT to fully account for transient thermomechanical coupling. Procedures for optimizing SMA component and assembly designs through iterative analysis are also introduced at the highest level. These techniques are implemented using commercially available simulation process management and scripting tools. The expanded framework is demonstrated on example engineering problems that are motivated by real morphing structure applications, namely the Boeing Variable Geometry Chevron (VGC) and the NASA Shape Memory Alloy Hybrid Composite (SMAHC) chevron. Three different studies are conducted on these applications, focusing on component-, assembly-, and system-level analysis, each of which may necessitate accounting for certain coupling interactions between thermal, mechanical, and fluid fields. Output analysis data from each of the three models are validated against experimental data, where available. It is shown that the expanded design framework can account for the additional coupling effects at each analysis level, while providing an efficient and accurate alternative to the cost- and time-expensive legacy design-build-test methods that are still used today to engineer SMA actuated morphing aerostructures.

Researchers in the field of global leadership have reported a growing need for leaders able to perform from a global perspective, and the lack of qualified leadership candidates to fulfill these responsibilities. Adult education graduate programs represent a unique pool of aspirants to help fill this gap. In 2008, the Commission of Professors of Adult Education (CPAE) published Standards for Graduate Programs in Adult Education. Two of these standards addressed the incorporation of globalization and leadership studies into the planning, administration, and evaluation of adult education graduate programs. This study sought to explore the connection between the phenomenon of global leadership and the development of competencies, identified by Bird’s (2013) framework of nested global leadership competencies, in seven selected adult education graduate programs in the United States and Western Europe. The questions that guided this qualitative, multiple case study explored (a) which of the competencies were addressed in the selected adult education graduate programs, (b) which ones were perceived to be most and less important, (c) which curricular and co-curricular practices were identified in the development of these competencies, and (d) what were the similarities and differences between the adult education graduate programs located geographically in the United States and those located in Western Europe. Findings indicated all of the global leadership competencies were addressed across all seven cases, to varying levels of extent. The competencies of (a) valuing people, (b) inquisitiveness, (c) leading change, and (d) vision and strategic thinking emerged as most important among the participants across all seven cases, as well as within the two geographical locations. Multiple curricular and co-curricular themes emerged as best practices to facilitate development of the global leadership competencies, although they were primarily associated with good instructional practices discussed within the context of globalizing the curriculum. There was less discussion about the competencies within a unifying construct of leadership development. Similarities across all cases included a focus on student-centered learning, while differences were primarily associated with the independent foci of the adult education graduate programs. Implications of the findings were directed towards the CPAE, university administration, adult education faculty, and adult education graduate students.