As movies, television shows, and other forms of media have progressed over the last century, the use of destruction sequences as a form of entertainment have seemingly grown exponentially. From ginormous explosions to cities collapsing, more destruction sequences have drawn people’s attention in ways that are quite captivating. However, as content producers continue to push the limit of what is possible, the reliance on practical effects starts to dwindle in comparison to the usage of computer generated scenes. This thesis acknowledges the trend and dissects the entire process of how a general destruction sequence is made, from the research and planning process to the actual simulation of the effects. Various methods are discussed in how to attempt the creation of destruction with a singular project in mind. The goal is to not only to complete the sequence, but to do so in an efficient manner that can rival a professional workflow.

Engineering Dynamics (ED) courses are known as challenging and demanding for undergraduate students majored in many engineering fields, such as mechanical and aerospace engineering and civil and environmental engineering. The course is built upon the foundation and framework of mathematics and physics and requires students to have strong abstract thinking and reasoning skills. Rigid body dynamics (RBD), the second part of ED, investigates kinematics and kinetics of rigid bodies and is considered as a difficult subject by many undergraduate students because the course requires them to visualize abstract objects in motions. Although there have been many studies reporting the uses of interactive computer simulation and animation (CSA) modules as visual learning tools in RBD instruction, the effectiveness of the CSA modules on student learning of RBD were not rigorously and adequately investigated. This study employs a mixed method (QUAN – qual) approach and nonequivalent comparison group design to investigate the effectiveness of CSA modules on student learning of RBD, and to explore students’ attitudes towards and experiences with these modules. One hundred and sixty-one students in two recent semesters participated in this study: 74 in one semester participated in the comparison group and 87 in another semester participated in the intervention group. While the intervention group students studied RBD with CSA modules along with traditional lectures, the comparison group students studied RBD with traditional lectures only. Students in both groups were assessed with pretests and posttests using 10 bonus homework assignments developed to address core knowledge areas of RBD. The study uses a set of nonparametric statistical tools to analyze the pretest and posttest scores, mean differences, and magnitudes of the differences in learning gains between the two groups. Research findings from this study reveal that the intervention group students showed a significant increase in learning gains of overall knowledge, conceptual understanding, and procedural skills with Cliff’s effect sizes of 0.49, 0.41, and 0.47, respectively. CSA modules increased the intervention group students’ confidence, but they did not increase students’ motivation of learning RBD. This study supports the use of CSA modules as an instructional intervention to improve students’ conceptual understanding and procedural skills in learning engineering dynamics.

The purpose of this research is to present a class of Self-Retracting Fully-compliant Bistable Micromechanisms (SRFBM). Fully-compliant mechanisms are needed to overcome the inherent limitations of microfabricated pin joints, especially in bistable mechanisms. The elimination of the clearances associated with pin joints will allow more efficient bistable mechanisms with smaller travel. Small travel, in a linear path facilitates integration with efficient on-chip actuators. Tensural pivots are developed and used to deal with the compressive loading to which the mechanism is subject. SRFBM are modeled using the Pseudo-Rigid-Body Model and finite element analysis. Suitable configurations of the SRFBM concept have been identified and fabricated using the MUMPs process. Complete systems, including external actuators and electrical contacts are 1140 μm by 625 μm (individual SRFBM are less than 300 μm by 300 μm). These systems have been tested, demonstrating on-chip actuation of bistable mechanisms. Power requirements for these systems are approximately 150 mW. Testing with manual force testers has also been completed and correlates well with finite element modeling. Actuation force is approximately 500 μN for forward actuation. Return actuation can be achieved either by external actuators or by thermal self-retraction of the mechanism. Thermal self-retraction is more efficient, but can result in damage to the mechanism. Fatigue testing has been completed on a single device, subjecting it to approximately 2 million duty cycles without failure. Based on the SRFBM concept a number of improvements and adaptations are presented, including systems with further power and displacement reductions and a G-switch for LIGA fabrication.

Haptic interfaces are robotic force-feedback devices that give the user a sense of touch as they interact with virtual or remote environments. These interfaces act as input devices, mapping the 3-dimensional (3D) motions of the user's hand into 3D motions in a slave system or simulated virtual world. A major challenge in haptic interfaces is ensuring that the user's experience is a realistic depiction of the simulated environment. This requires the interface's design to be such that it does not hinder the user's ability to feel the forces present in the environment. This "transparency" is achieved by minimizing the device's physical properties (e.g., weight, inertia, friction). The primary objective of the work is to utilize compliant mechanisms as a means to improve transparency of a haptic interface. This thesis presents work toward the design of a fully compliant mechanism that can be utilized in haptic interfaces as a means to reduce parasitic forces. The approach taken in this work is to design a series of mechanisms that when combined act as a statically balanced compliant joint (SBCJ). Simulated and experimental results show that the methods presented here result in a joint that displays a significant decrease in return-to-home behavior typically observed in compliant mechanisms. This reduction in the torque needed to displace the joint and the absence of friction suggest that the joint design is conducive to the methods previously proposed for increasing transparency in haptic interfaces.

This thesis develops robotic skills for manipulating novel articulated objects. The degrees of freedom of an articulated object describe the relationship among its rigid bodies, and are often relevant to the object's intended function. Examples of everyday articulated objects include scissors, pliers, doors, door handles, books, and drawers. Autonomous manipulation of articulated objects is therefore a prerequisite for many robotic applications in our everyday environments. Already today, robots perform complex manipulation tasks, with impressive accuracy and speed, in controlled environments such as factory floors. An important characteristic of these environments is that they can be engineered to reduce or even eliminate perception. In contrast, in unstructured environments such as our homes and offices, perception is typically much more challenging. Indeed, manipulation in these unstructured environments remains largely unsolved. We therefore assume that to enable autonomous manipulation of objects in our everyday environments, robots must be able to acquire information about these objects, making as few assumption about the environment as possible. Acquiring information about the world from sensor data is a challenging problem. Because there is so much information that could be measured about the environment, considering all of it is impractical given current computational speeds. Instead, we propose to leverage our understanding of the task, in order to determine the relevant information. In our case, this information consists of the object's shape and kinematic structure. Perceiving this task-specific information is still challenging. This is because in order to understand the object's degrees of freedom, we must observe relative motion between its rigid bodies. And, as relative motion is not guaranteed to occur, this information may not be included in the sensor stream. The main contribution of this thesis is the design and implementation of a robotic system capable of perceiving and manipulating articulated objects. This system relies on Interactive Perception, an approach which exploits the synergies that arise when crossing the boundary between action and perception. In interactive perception, the emphasis of perception shifts from object appearance to object function. To enable the perception and manipulation of articulated objects, this thesis develops algorithms for perceiving the kinematic structure and shape of objects. The resulting perceptual capabilities are used within a relational reinforcement learning framework, enabling a robot to obtain general domain knowledge for manipulation. This composition enables our robot to reliably and efficiently manipulate novel articulated objects. To verify the effectiveness of the proposed robotic system, simulated and real-world experiments were conducted with a variety of everyday objects.

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The nonlinear interactions between aerodynamic forces and wing structures are numerically investigated as integrated dynamic systems, including structural models, aerodynamics, and control systems, in the time domain. An elastic beam model coupled with rigid-body rotation is developed for the wing structure, and the natural frequencies and mode shapes are found by the finite-element method. A general unsteady vortex-lattice method is used to provide aerodynamic forces. This method is verified by comparing the numerical solutions with the experimental results for several cases; and thereafter applied to several applications such as the inboard-wing/twin-fuselage configuration, and formation flights. The original thought that the twin fuselage could achieve two-dimensional flow on the wing by eliminating free wing tips appears to be incorrect. The numerical results show that there can be a lift increase when two or more wings fly together, compared to when they fly alone. Flutter analysis is carried out for a High-Altitude-Long-Endurance aircraft wing cantilevered from the wall of the wind tunnel, a full-span wing mounted on a free-to-roll sting at its mid-span without and with a center mass (fuselage). Numerical solutions show that the rigidity added by the wall results in a higher flutter speed for the wall-mounted semi-model than that for the full-span model. In addition, a predictive control technique based on neural networks is investigated to suppress flutter oscillations. The controller uses a neural network model to predict future plant responses to potential control signals. A search algorithm is used to select the best control input that optimizes future plant performance. The control force is assumed to be given by an actuator that can apply a distributed torque along the spanwise direction of the wing. The solutions with the wing-tip twist or the wing-tip deflection as the plant output show that the flutter oscillations are successfully suppressed with the neural network predictive control scheme. / Ph. D.

In this study we investigate the propagation of uncertainties in the input forces through a mechanical system. The system of interest was a wheel loader, but the methodology developed can be applied to any multibody systems. The modeling technique implemented focused on efficiently modeling stochastic systems for which the equations of motion are not available. The analysis targeted the reaction forces in joints of interest. The modeling approach developed in this thesis builds a foundation for determining the uncertainties in a Caterpillar 980G II wheel loader. The study begins with constructing a simple multibody deterministic system. This simple mechanism is modeled using differential algebraic equations in Matlab. Next, the model is compared with the CAD model constructed in ProMechanica. The stochastic model of the simple mechanism is then developed using a Monte Carlo approach and a Linear/Quadratic transformation method. The Collocation Method was developed for the simple case study for both Matlab and ProMechanica models. Thus, after the Collocation Method was validated on the simple case study, the method was applied to the full 980G II wheel loader in the CAD model in ProMechanica. This study developed and implemented an efficient computational method to propagate computational method to propagate uncertainties through "black-box" models of mechanical systems. The method was also proved to be reliable and easier to implement than traditional methods. / Master of Science