Dynamics Simulation Engine is the foundation of the whole system. The engine maintains a realistic dynamics scene in either automatic planning or haptic guided planning. It serves as an off-line verification of the planned motion so that the generated scheme can be 'played' with the engine. In this thesis, we developed a three-dimensional dynamics simulation engine based on an extension of the explicit time-stepping scheme and an application of the differential inclusion process introduced by J. J. Moreau. In the engine, we developed the contact propagation method for a general three-dimensional rigid-body system with multiple unilateral contacts without any bilateral constraints. / In our approach, a sequence of applied forces on the mass center of the workpiece is planned. The applied forces will push the workpiece to get in contact with all the locators. For this purpose, we developed a system with two engines, Motion Planning Engine and Dynamics Simulation Engine. / The goal of Motion Planning Engine is to make the workpiece in contact with all the six locators. Here, the workpiece is initially at an arbitrary place with not contact with any locator. The planning follows a simple scheme of monotonously increase the number of contacts with locators. Here we use a two-step scheme. First, finding the velocity of the workpiece that can approach the new locator while maintaining contacts with old locators. This can be formulated as a linear programming problem. Second, finding the applied force to realize such motion. This step is a central issue in the planning because for the rigid-body model, the solution to multiple frictional contacts is generally indeterministic. One possibility is jamming, that is, the applied force cannot move the workpiece even with less than six contacts. In this thesis, we will give criteria to determine whether the jamming will happen, and we will also derive an algorithm to generate the non-jamming applied force. / The thesis presents an approach to the fixture loading planning problem. That is, to plan the applied forces on the workpiece in order for it to be loaded into a manufacturing fixture. / Liu Tong. / "June 2005." / Adviser: Michael Yu Wang. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 4067. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 115-124). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

The main object of this thesis is to give a introductory study of the longitudinal motion of an aircraft, including some effects of nonuniform motion. Because this subject is connected with practical problems of importance in the domain of applied aerodynamics and control, a great effort has been given to setting up the physics of unsteady aerodynamics and its effects on the aircraft longitudinal modes. Numerical examples are given for both the two-dimensional and three-dimensional rigid wing, subsonic case. In this research, from the unsteady aerodynamic theory, through the frequency response calculation, system identification and the augmentation of the aircraft dynamic system, a carefully derived theory and a computer algorithm have been presented and used. It is our main purpose that a suitable unsteady aerodynamic transfer function be obtained and be coupled to the aircraft quasi-steady dynamic system. A new modified model which includes the unsteady aerodynamic effects has been constructed and been compared with the conventional model and the differences between them have been discussed. / Master of Science

In this study, a new engineering model is presented which treats the motions of a rigid body to ground shock. A rigid body is defined as one whose deformations are small compared to the deformations of the surrounding media. The new model treats non-planar normal loads on the structure, tensile cut-off constraints at the upstream and downstream faces of the structure, and shear forces on the lateral surfaces of the structure. It assumes linear elastic material properties for all materials, and collinearity between reflected and transmitted particle velocities and stresses. An important feature of the model is that it incorporates the effects of wave diffraction around the rigid body through simple bounding arguments on the conditions which prevail in the shadow zone of the structure at early-times, intermediate-times, and late-times after the wave has engulfed the rigid body. The resulting expressions are uncomplicated, and provide bounds on the structure’s motion. The model was tested against a series of linear elastic finite element calculations and was found to be accurate, and able to explain the velocity overshoot which, while not widely known, accompanies the motions of rigid bodies under certain circumstances. The model was also tested against the results of a high-explosive test in sand, and a high explosive test in a competent shale, by treating the ground motion instrument canisters on the tests as rigid bodies. Again the model was found to be accurate, and accounted for the differences observed between finite difference predictions of the flow fields and the measured canisters’ responses. The model is expected to find application in aiding in the interpretation of ground motion measurements from explosion tests, in the design of ground motion transducers, and as an aid in the vulnerability analysis of underground Structures to the effects from large explosions. / Ph. D.

This thesis describes a comprehensive study of understanding the mechanism of rigidity sensing by quantitative analysis using submicron pillar array substrates. From mechanobiology perspective, we explore and study molecular pathways involved in rigidity and force sensing at cell-matrix adhesions with regard to cancer, regeneration, and development by quantification methods. In Chapter 2 and 3, we developed fabrication and imaging techniques to enhance the performance of a submicron pillar device in terms of spatial and temporal measurement ability, and we discovered a correlation of rigidity sensing forces and corresponding proteins involved in the early rigidity sensing events. In Chapter 2, we introduced optical effect arising from submicron structure imaging, and we described a technique to identify the correct focal plane of pillar tip by fabricating a substrate with designed-offset pillars. From calibration result, we identified the correct focal plane that was previously overlooked, and verified our findings by other imaging techniques. In Chapter 3, we described several techniques to selectively functionalize elastomeric pillars top and compared these techniques in terms of purposes and fabrication complexity. Techniques introduced in this chapter included direct labeling, such as stamping of fluorescent substances (organic dye, nano-diamond, q-dot) to pillars top, as well as indirect labeling that selectively modify the surface of molds with either metal or fluorescent substances. In Chapter 4, we examined the characteristics of local contractility forces and identified the components formed a sarcomere like contractile unit (CU) that cells use to sense rigidity. CUs were found to be assembled at cell edge, contain myosin II, α-actinin, tropomodulin and tropomyosin (Tm), and resemble sarcomeres in size (~2 μm) and function. Then we performed quantitative analysis of CUs to evaluate rigidity sensing activity over ~8 hours time course and found that density of CUs decrease with time after spreading on stiff substrate. However addition of EGF dramatically increased local contraction activity such that about 30% of the total contractility was in the contraction units. This stimulatory effect was only observed on stiff substrate not on soft. Moreover, we find that in the early interactions of cells with rigid substrates that EGFR activity is needed for normal spreading and the assembly of local contraction units in media lacking serum and any soluble EGF. In Chapter 5, we performed high temporal- and spatial-resolution tracking of contractile forces exerted by cells on sub-micron elastomeric pillars. We found that actomyosin-based sarcomere-like CUs simultaneously moved opposing pillars in net steps of ~2.5 nm, independent of rigidity. What correlated with rigidity was the number of steps taken to reach a force level that activated recruitment of α-actinin to the CUs. When we removed actomyosin restriction by depleting tropomyosin 2.1, we observed larger steps and higher forces that resulted in aberrant rigidity sensing and growth of non-transformed cells on soft matrices. Thus, we conclude that tropomyosin 2.1 acts as a suppressor of growth on soft matrices by supporting proper rigidity sensing.

by Chi-Min Pang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 110-[115]). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Range Images --- p.1 / Chapter 1.2 --- Rigid Body Model --- p.3 / Chapter 1.3 --- Motivation --- p.4 / Chapter 1.4 --- Thesis Outline --- p.6 / Chapter 2 --- Object Recognition by Relaxation Processes --- p.7 / Chapter 2.1 --- An Overview of Probabilistic Relaxation Labelling --- p.8 / Chapter 2.2 --- Formulation of Model-matching Problem Solvable by Probabilistic Relaxation --- p.10 / Chapter 2.2.1 --- Compatibility Coefficient --- p.11 / Chapter 2.2.2 --- Match Score --- p.13 / Chapter 2.2.3 --- Iterative Algorithm --- p.14 / Chapter 2.2.4 --- A Probabilistic Concurrent Matching Scheme --- p.15 / Chapter 2.3 --- Formulation of Model-merging Problem Solvable by Fuzzy Relaxation --- p.17 / Chapter 2.3.1 --- Updating Mechanism --- p.17 / Chapter 2.3.2 --- Iterative Algorithm --- p.19 / Chapter 2.3.3 --- Merging Sub-Rigid Body Models --- p.20 / Chapter 2.4 --- Simulation Results --- p.21 / Chapter 2.4.1 --- Experiments in Model-matching Using Probabilistic Relaxation --- p.22 / Chapter 2.4.2 --- Experiments in Model-matching Using Probabilistic Concur- rent Matching Scheme --- p.26 / Chapter 2.4.3 --- Experiments in Model-merging Using Fuzzy Relaxation --- p.33 / Chapter 2.5 --- Summary --- p.36 / Chapter 3 --- Object Recognition by Hopfield Network --- p.37 / Chapter 3.1 --- An Overview of Hopfield Network --- p.38 / Chapter 3.2 --- Model-matching Problem Solved by Hopfield Network --- p.41 / Chapter 3.2.1 --- Representation of the Solution --- p.41 / Chapter 3.2.2 --- Energy Function --- p.42 / Chapter 3.2.3 --- Equations of Motion --- p.46 / Chapter 3.2.4 --- Interpretation of Solution --- p.49 / Chapter 3.2.5 --- Convergence of the Hopfield Network --- p.50 / Chapter 3.2.6 --- Iterative Algorithm --- p.51 / Chapter 3.3 --- Estimation of Distance Threshold Value --- p.53 / Chapter 3.4 --- Cooperative Concurrent Matching Scheme --- p.55 / Chapter 3.4.1 --- Scheme for Recognizing a Single Object --- p.56 / Chapter 3.4.2 --- Scheme for Recognizing Multiple Objects --- p.60 / Chapter 3.5 --- Simulation Results --- p.60 / Chapter 3.5.1 --- Experiments in the Model-matching Problem Using a Hopfield Network --- p.61 / Chapter 3.5.2 --- Experiments in Model-matching Problem Using Cooperative Concurrent Matching --- p.69 / Chapter 3.5.3 --- Experiments in Model-merging Problem Using Hopfield Network --- p.77 / Chapter 3.6 --- Summary --- p.80 / Chapter 4 --- Genetic Generation of Weighting Parameters for Hopfield Network --- p.83 / Chapter 4.1 --- An Overview of Genetic Algorithms --- p.84 / Chapter 4.2 --- Determination of Weighting Parameters for Hopfield Network --- p.86 / Chapter 4.2.1 --- Chromosomal Representation --- p.87 / Chapter 4.2.2 --- Initial Population --- p.88 / Chapter 4.2.3 --- Evaluation Function --- p.88 / Chapter 4.2.4 --- Genetic Operators --- p.89 / Chapter 4.2.5 --- Control Parameters --- p.91 / Chapter 4.2.6 --- Iterative Algorithm --- p.94 / Chapter 4.3 --- Simulation Results --- p.95 / Chapter 4.3.1 --- Experiments in Model-matching Problem using Hopfield Net- work with Genetic Generated Parameters --- p.95 / Chapter 4.3.2 --- Experiments in Model-merging Problem Using Hopfield Network --- p.101 / Chapter 4.4 --- Summary --- p.104 / Chapter 5 --- Conclusions --- p.106 / Chapter 5.1 --- Conclusions --- p.106 / Chapter 5.2 --- Suggestions for Future Research --- p.109 / Bibliography --- p.110 / Chapter A --- Proof of Convergence of Fuzzy Relaxation Process --- p.116