The serious consequence of ship collisions necessitates the development of regulations and requirements for the subdivision and structural design of ships to reduce damage and environmental pollution from collision, and improve safety. The on-going revision of IMO regulations on oil outflow performance and damage stability in grounding and collision is focused on a transition to probabilistic performance-based standards. This thesis addresses one aspect of this problem, a simplified collision model sufficient to predict collision damage, and fast enough to be used in probabilistic analysis requiring thousands of collision simulations. The simplified collision model (SIMCOL) developed and evaluated in this thesis is based on a time domain simultaneous solution of external dynamics and internal deformation mechanics. The external sub-model uses a three-degree of freedom system for ship dynamics. The internal sub-model determines reacting forces from side and bulkhead structures using mechanisms adapted from Rosenblatt and McDermott, and absorbed energy by decks, bottoms and stringers calculated using the Minorsky correlation as modified by Reardon and Sprung. SIMCOL is applied to a series of collision scenarios. Results are compared with MIT's DAMAGE, a Danish Technical University (DTU) model and ALPS/SCOL. SIMCOL provides a fast, consistent and reasonable result for ship collision analysis. An actual collision case is used in an initial attempt to validate the model. This research is sponsored by the Society of Naval Architects and Marine Engineers (SNAME) and the Ship Structure Committee (SSC). / Master of Science

The serious consequence of ship collisions necessitates the development of regulations and requirements for the subdivision and structural design of ships so that damage and environmental pollution is reduced, and safety is improved. A simplified collision model (SIMCOL) is currently being developed at Virginia Tech to conduct probabilistic analysis of damage in ship collisions and ultimately optimize ship structural designs to improve crashworthiness. Collision data for validation of SIMCOL is very difficult to obtain, and model testing is very costly. Finite Element Analysis (FEA) provides an alternative to physical validation that can be used to increase confidence and insight in simplified model results. This thesis develops a complete methodology for ship-to-ship collision simulations using the explicit non-linear FE code LS-DYNA3D. Various modeling alternatives are considered. The ability to model a complete ship-to-ship collision is developed incrementally starting with bow collisions with a rigid wall. A super-element (intersection model) approach is considered to increase the calculation speed of bow models. A conventional fine mesh finite element bow model is also developed. Results from both models are compared with each other, and with a closed-form calculation from Pedersen. A fine mesh model is developed for a struck tanker cargo section and integrated in a total ship framework modeling external dynamics and ship-to-ship contact. A series of collision scenarios is simulated using the conventional bow model and a rigid bow model striking a double hull tanker. Results are compared with SIMCOL, DAMAGE, DTU and ALPS/SCOL models. LS-DYNA provides detailed and reasonable results for ship collision analysis and comparison to increase confidence in simplified models. / Master of Science

Dans de nombreux pays, le taux de mortalité des motocyclistes est beaucoup plus élevé que celui des autres conducteurs de véhicules. Parmi de nombreux autres facteurs, les collisions arrière des motocyclettes contribuent fortement à ces décès de motards. Les systèmes de détection de collision peuvent être utilisés pour minimiser ces accidents mortels. Cependant, la plupart des systèmes de détection de collision existants n'identifient pas le type de danger potentiel auquel sont exposés les motocyclistes. Chaque système d'alerte de collision utilise une technique de détection de collision distincte, ce qui limite ses performances et rend impératif l'étude de son efficacité. Malheureusement, aucun travail de ce type n'a été signalé dans ce domaine particulier pour les motocyclistes. Par conséquent, il est important d'étudier la réponse physiologique du motocycliste contre ces systèmes d'alerte de collision. Dans cette recherche, une méthode de détection et de classification des véhicules approchant par l'arrière est présentée. Pour la détection de collision, une approche basee vision et la technique basee sur le son ont été utilisées. Pour les techniques visuelles et acoustiques, des caractéristiques d'apparence et de spectre de puissance ont été utilisées, respectivement, pour détecter le véhicule qui s'approche à l'extrémité arrière de la motocyclette. En ce qui concerne la classification des véhicules, seule une technique acoustique est utilisée; un spectre de puissance acoustique et des caractéristiques énergétiques sont utilisés pour classer les véhicules qui approchent. Deux types d'ensembles de données, à savoir des ensembles de données acquises durant ce travail (obtenues en plaçant une caméra à l'arrière d'une motocyclette) et des ensembles de données disponibles telechargeables (pour la détection visuelle et pour la classification audio des véhicules) sont utilisés pour la validation. La méthodologie proposée a permis de détecter et de classer les véhicules pour des ensembles de données acquises durent cette these. De même, pour les ensembles de données disponibles , le taux positif vrai le plus élevé et le taux de détection faux le plus faible ont été atteints par rapport aux méthodes de l etat de l art. En outre, une étude physiologique basée sur le potentiel lié à l'événement (ERP) a été réalisée sur les motocyclistes afin d'étudier leurs réponses vis-à-vis du système d'alerte de collision arrière. Deux types d'avertissements auditifs (c'est-à-dire verbal et buzzer) sont utilisés pour ce système d'avertissement. Pour étudier la réponse des motocyclistes, les composantes N1, N2, P3 et N400 ont été extraits des données d'électroencéphalographie (EEG). Ces systèmes d avertissement ont montré des effets positifs au niveau des neuronal sur les motocyclistes et réduisent leur temps de réaction et les ressources attentionnelles nécessaires pour traiter correctement la cible. En résumé, le système d'avertissement de collision par l'arrière proposé avec des avertissements verbaux auditifs augmente considérablement la vigilance du motocycliste et peut être utile pour éviter les scénarios possibles de collision arrière. / In many countries, motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. Collision detection systems can be used to minimize these fatalities. However, most of the existing collision detection systems do not identify the type of potential hazard faced by motorcyclists. Every collision warning system used a distinctive collision detection technique, which limits its performance and makes it imperative to study its effectiveness. Unfortunately, no such work has been reported in that particular domain for motorcyclists. Therefore, it is important to study the physiological response of the motorcyclist against these collision warning systems. In this research, a rear end vehicle detection and classification method is presented for motorcyclists. For collision detection, vision technique and acoustic technique have been used. For visual and acoustic techniques, appearance features and power spectrum have been used, respectively, to detect the approaching vehicle at the rear end of the motorcycle. As for the vehicle classification, only an acoustic technique is utilized; an acoustic power spectrum and energy features are used to classify the approaching vehicles. Two types of datasets which are comprised of self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and online datasets (for vision-based vehicle detection and for audio based vehicle classification techniques) are used for validation. Proposed methodology successfully detected and classified the vehicle for self-recorded datasets. Similarly, for online datasets, the higher true positive rate and less false detection rate has been achieved as compared to the existing state of the art methods. Moreover, an event-related potential (ERP) based physiological study has been performed on motorcyclists to investigate their responses towards the rear end collision warning system. Two types of auditory warnings (i.e., verbal and buzzer) are used for this warning system. To study the response of the motorcyclists, the N1, N2, P3, and N400 components have been extracted from the Electroencephalography (EEG) data. These introduced systems have shown positive effects at neural levels on motorcyclists and reduce their reaction time and attentional resources required for processing the target correctly. In summary, the proposed rear-end collision warning system with auditory verbal warnings significantly increases the alertness of the motorcyclist and can be helpful to avoid the possible rear-end collision scenarios.

We consider the problem of moving a three dimensional solid object among polyhedral obstacles. The traditional formulation of configuration space for this problem uses three translational parameters and three angles (typically Euler angles), and the constraints between the object and obstacles involve transcendental functions. We show that a quaternion representation of rotation yields constraints which are purely algebraic in a higher-dimensional space. By simple manipulation, the constraints may be projected down into a six dimensional space with no increase in complexity. Using this formulation, we derive an efficient exact intersection test for an object which is translating and rotating among obstacles.

No description available.

The potential benefits that automation could bring to a wide variety of real-world tasks are numerous and well recognised. There has been significant research undertaken into automation in general, but for real-time automation of complex systems (involving complex geometries and dynamics) the problem is far from a solved one. One of the key tasks in a surface mining operation is that of using shovels or excavators to load material onto haul trucks for transportation. Since it is such a crucial task to a number of production cycles, it is a clear area where the productivity and safety benefits of automation could have a large impact. A number of projects are being undertaken concurrently to move towards first partial, and then full, automation of this mining subsystem. This thesis focusses on the collision avoidance problem, specifically on forming a collision hull that distinguishes between intersecting and non-intersecting configurations of two objects. Techniques from computer graphics are leveraged to develop a data structure that stores and organises relevant information about real-world systems for motion-planning tasks, ensuring that the necessary data is available and in a form suited to the task at hand. The Minkowski Sum operation, which can be used fairly directly to form the collision hull of two convex objects under translation, is extended to develop an operation to form the exact collision hull of two arbitrary objects to determine the applicability of such a scheme to complex systems in real-time. A level of detail solution is then proposed, where the Minkowski Hull of bounding hierarchies allows unnecessary parts of the hull to be calculated only in a coarse manner, thus offsetting a lot of the computational cost for any given test. This approach is investigated for both translational motion and joint-space motion. Collision detection is not collision avoidance, and so the algorithms developed in the thesis are tested in a number of applications, to demonstrate their suitability to the collision avoidance task. The applications (discrete collision prediction, visibility graph path planning, and the formulation of a Model Predictive Controller) are restricted versions of the true problems with some simplifying assumptions, but they show the algorithms to be capable both in their execution speed and the information that they provide.

Le processus de réalisation des pièces de formes complexes par usinage est un processus essentiel dans les domaines de l'aéronautique, de l'automobile, des moules et des matrices. Alors que l'usinage 5 axes grande vitesse est maintenant répandu dans les grands groupes industriels, il reste plusieurs problématiques à traiter. L'évitement de collisions le long de la trajectoire outil programmée en alors traité, notamment au niveau des interférences globales représentant une collision entre l'outil et son environnement. Classiquement, l'évitement de collisions dans le domaine de l'usinage 5 axes grande vitesse peut être programmé à l'aide d'une analyse géométrique de la situation. Si une collision est détecté, alors une phase de correction et d'optimisation peuvent être utilisée afin d'obtenir une nouvelle trajectoire hors collision. Le but des travaux est alors d'utiliser une modélisation physique afin d'obtenir une trajectoire corrigée hors collision le plus lisse possible. Pour ce faire le mouvement de l'outil est alors étudié d'un point de vue dynamique afin d'éviter les réorientation brutal post correction. De plus, les éléments constituants les obstacles émettent une action répulsive à distance. Cela permet, au cours de la programmation, d'anticiper l'approche d'un obstacle et ainsi d'entamer les corrections d'orientation outil en prévision d'une possible collision. Cette démarche de modélisation du mouvement étudiée permet alors de réaliser des simulations sur des pièces classiquement usinées dans les domaines énoncés précédemment. Dans le but de généraliser la programmation réalisée, il est alors important de comprendre comment les éléments obstacles sont représentés ainsi que la modélisation retenu pour l'outil utilisé au cours de la simulation. Enfin, la résolution de la dernière problématique mise en avant au cours de cette thèse concerne les temps de calcul obtenus. Il a été montré, après de multiples simulations, que ces derniers peuvent exploser d'un point de vue combinatoire pour des utilisateurs exigeants (modélisation fine de l'outil et de l'environnement). Une méthode de pré calcul est alors présentée utilisant la voxelisation permettant de diminuer les temps de calcul de manière très importante sans pour autant perdre de manière importante sur la solution obtenue. Le dernier objectif présenté est de proposer une approximation permettant de diminuer nettement les temps de calcul tout en conservant une assurance de non-collision. Cette méthode notée voxelisation consiste en utilisant une interpolation à diminuer le temps de calcul. L’important est alors de comprendre quels inconvénients se rattachent à la voxelisation et à partir de quand cette dernière apporte un résultat acceptable / Although 5-axis free form surfaces machining is commonly proposed in CAD/CAM software, several issues still need to be addressed and especially collision avoidance between the tool and the part. Indeed, advanced user skills are often required to define smooth tool axis orientations along the tool path in high speed machining. In the literature, the problem of collision avoidance is mainly treated as an iterative process based on local and geometrical collision tests. In this paper, an innovative method based on potential fields is used to generate 5-axis collision-free smooth tool paths. In the proposed approach, The ball-end tool is considered as a rigid body moving in 3D space on which repulsive force, deriving from a scalar potential field attached to the check surfaces, and attractive forces are acting. The resolution of the differential equations of the tool motion ensure smooth variations of the tool axis orientation. The proposed algorithm is applied on open pocket parts such as an impeller and a pocket corner to emphasize the effectiveness of this method to avoid collision. After that, it is possible to see that de calculation time can be very importante for a delicate mesh. It is for that, a voxelisation method is developed to decrease these.

No description available.

Existing robotic arms have limited or no ability to avoid collisions with their environment due mainly to the lack of a suitable sensing system. A collision avoidance capability should be incorporated into every robot so that injuries to people and damage to equipment from collisions are prevented. Important applications that could benefit from robot collision avoidance include: manufacturing, robot-assisted surgery, robotic handling of hazardous waste, and personal robots. Creating a full-coverage, fast, reliable and cost effective sensing system for sensor-based robotic arm collision avoidance is a challenging problem. Capacitive sensors were selected based on their promising potential. Capacitive sensors have the limitations of nonlinearity and being influenced by the environment. In this thesis, their sensing behaviour, and solutions to these limitations, were investigated. A forward model predicts the capacitance for a given electrode geometry. The conventional method, Method of Moments (MoM) and Finite Element Method (FEM) were investigated and compared. The MoM demonstrated that the fringing electric field ignored by the conventional forward model is significant for the robotic arm application due to the relatively large ratio of electrode gap to electrode area. Two forward modeling cases were simulated by writing macro code for a commercial FEM package. The first consisted of two parallel cylindrical robotic arms. The second consisted of two cylindrical shell electrodes wrapped around a pair of robot links that rotated relative to each other. The results for this case were compared with experimental results. The FEM results were a poor predictor of the experimental results. The failure of the FEM model to include the true environmental conditions (e.g. air humidity and surrounding electric fields) is the most likely cause of its inaccuracy. An inverse capacitance model outputs the electrode geometry for a given capacitance. In this research the desired geometric output was the seven robot link pose variables, (x, y, z, q_x, q_y, q_z, q_0), describing the position and the orientation of the link of a robotic arm. A Cerebellar Model Articulation Controller (CMAC) neural network was chosen for the inverse modeling based its ability to model nonlinear behaviour and its efficiency. One CMAC network was trained for each pose variable. The sensor was built using capacitance sensing circuit and a multiplexor board with the potential for 16 by 16 electrode combinations. Note that an n by n combination produces n^2 separate capacitance values. For the inverse modeling experiments, four aluminum foil electrodes were mounted on a CRS-F3 robotic arm and four aluminum foil electrodes were placed on a wooden box used to simulate a second stationary robotic arm. A pair of reference electrodes was mounted on the back of the CRS-F3 arm. This reference measurement was used to normalize the measured capacitances in order to minimize environmental effects. The normalized capacitance data were used to train and test the CMAC neural networks. The CMAC learning factors were dynamically changed to reduce the training errors. A new fuzzy logic approach was developed that allowed the range of the CMAC input data to be increased without significantly increasing the training error. After evaluating eleven combinations of electrodes, it was determined that only the 3 by 3 and 4 by 4 combinations converged with small training errors. Three methods were used to analyze the CMAC testing errors: comparison plots, error plots and error metrics. Over a 15 cm range, pose variable y had maximum absolute errors of 2.1 mm for the 4 by 4 electrode combination and 7.2 mm for the 3 by 3 electrode combination. For the 4 by 4 combination the maximum relative errors were less than 3% for the x, y, and z variables, and less than 15% for the quaternion variables. For the 3 by 3 combination, these values increased to 13% and 20%, respectively. The larger relative errors for the quaternion variables were due to their smaller ranges of variation. Using the same hardware, a simple collision avoidance system was implemented using one pair of electrodes to detect the potential collision between a robotic arm moving in the vertical plane and a second stationary robot. The robot was shown to successfully avoid the potential collision and then continue its motion. / Thesis / Master of Applied Science (MASc)

No description available.