To meet the requirements for the next generation of space missions, a paradigm shift is required from current structures that are static, heavy and stiff, to innovative structures that are adaptive, lightweight, versatile, and intelligent. This work proposes the use of a novel morphing structure, the thermally actuated anisogrid morphing boom, to meet the design requirements by making the primary structure actively adapt to the on-orbit environment. The proposed concept achieves the morphing capability by applying local and global thermal gradients and using the resulting thermal strains to introduce a 6 Degree of Freedom (DOF) morphing control. To address the key technical challenges associated with implementing this concept, the work is broken into four sections. First, the capability to develop and reduce large dynamic models using the Data Based Loewner-SVD method is demonstrated. This reduction method provides the computationally efficient dynamic models required for evaluation of the concept and the assessment of a vast number of loading cases. Secondly, a sensitivity analysis based parameter ranking methodology is developed to define parameter importance. A five parameter model correlation effort is used to demonstrate the ability to simplify complex coupled problems. By reducing the parameters to only the most critical, the resulting morphing optimization computation and engineering time is greatly reduced. The third piece builds the foundation for the thermal morphing anisogrid structure by describing the concept, defining the modeling assumptions, evaluating the design space, and building the performance metrics. The final piece takes the parameter ranking methodology, developed in part two, and the modeling capability of part three, and performs a trust-region optimization to define optimal morphing geometric configuration. The resulting geometry, optimized for minimum morphing capability, is evaluated to determine the morphing workspace, the frequency response capability, and the minimum and maximum morphing capability in 6 DOF. This work has demonstrated the potential and provided the technical tools required to model and optimize this novel smart structural concept for a variety of applications. / Ph. D. / To meet the requirements for the next generation of space missions, a paradigm shift is required from current structures that are static, heavy and stiff, to innovative structures that are adaptive, lightweight, versatile, and intelligent. This work proposes the combination of a unique structure with a new control method to provide a novel way to achieve smart structural adaptive (morphing) capability. This concept takes advantage of the natural expansion and contraction of materials caused by temperature changes (Coefficient of Thermal Expansion) to bend and twist the structure of interest into the desired configuration. By applying local heat (thermal energy) to induce temperature differences in the structure, the temperature induced material expansion (thermal strain) can be used to control and direct the structure into all different planes and rotations(X, Y, and Z displacements as well as the rotations in the X, Y, and Z axis). This structure is called an anisogrid boom. The potential applications of model range from passive thermal mitigation system to an active precision low frequency vibration control system. The anisogrid boom is a low mass and efficient structural configuration with a long history in aerospace applications. The thermally morphing anisogrid structure is made up of helical members (these members are heated and cooled to actively bend and twist the structure) and circumferential members (these members provide stability and rigidity to the structure). This work details the methods used to move and control the structure as well as the development of the technical capabilities required to effectively demonstrate the limits of the concept. To address the key technical challenges associated with implementing this concept, the work is broken into four sections. First, the method is detailed that is used to generate the large dynamic computer models and the method to reduce them using a model reduction method, Data Based Loewner-SVD. This reduction method provides the computationally-efficient dynamic models required for evaluation of the concept. Secondly, a novel methodology is discussed identifying the impact of an input parameter change on the resulting output, such that the parameters of importance can be ranked. This ranking provides insight into what parameters should be the focus for further evaluation and optimization. The last two sections address how these tools are used to demonstrate the performance of this novel morphing structure as a function of the geometric input parameters relative to multiple developed performance metrics. Finally, the structure is optimized to achieve the most accurate morphing possible so that the limits of the capability can be better understood. This work has demonstrated the potential and provided the technical tools required to model and optimize this novel smart structural concept for a variety of applications.