Development of a fast local analysis tool for optimized laser assisted tape winding

Continuous fiber reinforced thermoplastic (FRTP) lightweight composite products have become more and more popular for many engineering applications. Laser-assisted tape winding and placement processes (LATW and LATP) are some of the promising manufacturing techniques to produce advanced thermoplastic composite components. A fully automated single step manufacturing can be achieved in LATW and LATP processes when the FRTP prepreg tapes are consolidated “in situ”, which can reduce the production costs and eliminate post consolidation or curing steps. Despite the advantages of these manufacturing techniques, it is a difficult task to predict and control the process temperature which is driven by the laser irradiation, the reflections, the local tooling geometry and the process parameters. It is vital to thoroughly analyze the process temperature, which is critical for the resulting part properties and performance. The focus in this thesis is on the winding of pipes and pressure vessels made of FRTP composites. The performed research was a part of the EU funded ambliFibre project with an ambition of developing a model-based in-line process control for LATW processes. The long term objective of this thesis is to achieve a robust LATW process by compensating the variability in the manufacturing process resulting in repetitive and predictable part properties and performance. The work presented in this thesis takes the first steps towards the long term objective by developing the key building blocks

Spectral, Combinatorial, and Probabilistic Methods in Analyzing and Visualizing Vector Fields and Their Associated Flows

In this thesis, we introduce several tools, each coming from a different branch of mathematics, for analyzing real vector fields and their associated flows. Beginning with a discussion about generalized vector field decompositions, that mainly have been derived from the classical Helmholtz-Hodge-decomposition, we decompose a field into a kernel and a rest respectively to an arbitrary vector-valued linear differential operator that allows us to construct decompositions of either toroidal flows or flows obeying differential equations of second (or even fractional) order and a rest. The algorithm is based on the fast Fourier transform and guarantees a rapid processing and an implementation that can be directly derived from the spectral simplifications concerning differentiation used in mathematics. Moreover, we present two combinatorial methods to process 3D steady vector fields, which both use graph algorithms to extract features from the underlying vector field. Combinatorial approaches are known to be less sensitive to noise than extracting individual trajectories. Both of the methods are extensions of an existing 2D technique to 3D fields. We observed that the first technique can generate overly coarse results and therefore we present a second method that works using the same concepts but produces more detailed results. Finally, we discuss several possibilities for categorizing the invariant sets with respect to the flow. Existing methods for analyzing separation of streamlines are often restricted to a finite time or a local area. In the frame of this work, we introduce a new method that complements them by allowing an infinite-time-evaluation of steady planar vector fields. Our algorithm unifies combinatorial and probabilistic methods and introduces the concept of separation in time-discrete Markov chains. We compute particle distributions instead of the streamlines of single particles. We encode the flow into a map and then into a transition matrix for each time direction. Finally, we compare the results of our grid-independent algorithm to the popular Finite-Time-Lyapunov-Exponents and discuss the discrepancies. Gauss\'' theorem, which relates the flow through a surface to the vector field inside the surface, is an important tool in flow visualization. We are exploiting the fact that the theorem can be further refined on polygonal cells and construct a process that encodes the particle movement through the boundary facets of these cells using transition matrices. By pure power iteration of transition matrices, various topological features, such as separation and invariant sets, can be extracted without having to rely on the classical techniques, e.g., interpolation, differentiation and numerical streamline integration

Nlcviz: Tensor Visualization And Defect Detection In Nematic Liquid Crystals

Visualization and exploration of nematic liquid crystal (NLC) data is a challenging task due to the multidimensional and multivariate nature of the data. Simulation study of an NLC consists of multiple timesteps, where each timestep computes scalar, vector, and tensor parameters on a geometrical mesh. Scientists developing an understanding of liquid crystal interaction and physics require tools and techniques for effective exploration, visualization, and analysis of these data sets. Traditionally, scientists have used a combination of different tools and techniques like 2D plots, histograms, cut views, etc. for data visualization and analysis. However, such an environment does not provide the required insight into NLC datasets. This thesis addresses two areas of the study of NLC data---understanding of the tensor order field (the Q-tensor) and defect detection in this field. Tensor field understanding is enhanced by using a new glyph (NLCGlyph) based on a new design metric which is closely related to the underlying physical properties of an NLC, described using the Q-tensor. A new defect detection algorithm for 3D unstructured grids based on the orientation change of the director is developed. This method has been used successfully in detecting defects for both structured and unstructured models with varying grid complexity

Muon Spin Relaxation Study of MnGe and Development of Pair Distribution Function Methods

The first half of the thesis presents our experimental study of a helical magnet MnGe. We apply μSR technique to study the dynamic as well as the static magnetism in MnGe. Our key findings are as follows. From the muon dynamic relaxation 1/T1 results, no apparent critical behavior or anomaly was observed at the boundary between param- agnetic and the induced-ferromagnetic regions. Our study revealed linear relation between the transverse field relaxation rate and the static magnetization. Furthermore, their ratio, which can be regarded a form of hyperfine coupling constant, is very similar in the induced ferromagnetic region and the paramagnetic region. This suggest that the Z component of the Mn moment is static in both regions. On the other hand, the single relaxation rate in the transverse spectra suggest that the internal field is highly homogeneous in the induced ferromagnetic region. We therefore speculate that the induced ferromagnetic region and the paramagnetic region are not separate phases, but rather a single phase with different tendencies as temperature decrease. With decreasing temperature, the paramagnetic region is marked with the winning of the tendency towards ferromagnetic ordering over random ordering, and the induced ferromagnetic region is marked with the winning of the tendency towards the helical order over ferromagnetic order.At lower temperature, we observed dynamic critical behavior in the boundary between the induced ferromagnetic region and the Skyrmion region. Specifically, in low fields, the 1/T1 relaxation rate behaves qualitatively different from the prediction of SCR theory for itinerant ferromagnet for large temperature regime above Tc. In high fields, on the other hand, the system recovers the SCR itinerant ferromagnetic behavior. Through analyzing field effect on spin fluctuation and phase transition in the low and high field regimes, we speculate that this could be due to the suppression of helical fluctuation into ferromagnetic-like fluc- tuation by large magnetic fields. Our μSR results, which show 2nd order signature for the transition between the induced ferromagnetic region into the Skyrmion region, is consistent with considerations based on the topology of the magnetic structure in each phase. At low temperatures within the Skyrmion region of MnGe, our analysis of the transverse field data shows that all the three components of the Mn moment is frozen. The quadratic tempera- ture dependence of 1/T1 at low temperatures suggest the two-magnon spin wave to be the dominant spin excitation in the Skyrmion region. This is similar to those seen in local- ized moment magnets and is qualitatively different from the linear temperature dependence predicted from SCR theory for itinerant ferromagnets. The second half of the thesis present our derivation of the structure function and the pair distribution function (PDF) for textured materials. We also derive the analytical form of the PDF for a few special cases of texture. In this study, we start from the general form of a 3D structure function and derive the general and orientationally averaged form of the structure function and PDF for textured samples. In particular for a thin film sample with fibre texture, our formalism gives the result known as the 2 dimensional PDF. We developed open-software that calculates the 2 dimensional PDF for a textured thin film, and showed that the experimental PDF was well fitted using the model. On the other hand, the PDF method could be extended to an energy-dependent form, which could reveal explicitly the effect of lattice dynamics on the local arrangement of the atoms. This is usually called the dynamic PDF method. In this thesis we derive the analytical form of the dynamic PDF for a simple molecule that contains two identical atoms. And we interpret the mathematical results with physical consideration of the lattice dynamics. In addition, we also propose a new definition for the dynamic PDF which can be shown to reduce to the atomic PDF by integrating over energy. This new definition of the dynamic PDF incorporates the contribution from multi-phonon scattering effects, and can be computed conveniently from inelastic neutron scattering

Magnetic Quantum Walks of Neutral Atoms in Optical Lattices

This thesis focuses on the simulation of the physics of a charged particle under an external magnetic field by using discrete-time quantum walks of a spin-1/2 particle in a two-dimensional lattice. By Floquet-engineering the quantum-walk protocol, an Aharonov–Bohm geometric phase is imprinted onto closed-loop paths in the lattice, thus realizing an abelian gauge field—the analog of a magnetic flux threading a two-dimensional electron gas. I show that in the strong-field regime, i.e. when the flux per plaquette of the lattice is a sizable fraction of the flux quantum, magnetic quantum walks give rise to nearly flat energy bands. I demonstrate that the system behaves like a Chern insulator by computing the Chern numbers of the energy bands and studying the excitation of the midgap topologically protected edge modes. These modes are extended all along the boundaries of the magnetic domains and remain robust against perturbations that respect the gap closing conditions. Furthermore, I discuss a possible experimental implementation of this scheme using neutral atoms trapped in two dimensional spin-dependent optical lattices. The proposed scheme has a number of unique features, e.g. it allows one to generate arbitrary magnetic-field landscapes, including those with sharp boundaries along which topologically protected edge states can be localized and probed. Additionally, I introduce the scattering matrix approach in discrete-time quantum walks to probe the Hofstadter spectrum and compute its topological invariants. By opening up a discrete-time quantum walk system and connecting it to metallic leads, I demonstrate that the reflection/transmission probabilities of a particle from the scattering region give information on the energy spectrum and topological invariants of the system. Although the work presented here focuses on the physics of a single particle in a clean system, it sets the stage for studies of many-body topological states in the presence of interactions and disorder

Muon Spin Relaxation Study of MnGe and Development of Pair Distribution Function Methods

The first half of the thesis presents our experimental study of a helical magnet MnGe. We apply μSR technique to study the dynamic as well as the static magnetism in MnGe. Our key findings are as follows. From the muon dynamic relaxation 1/T1 results, no apparent critical behavior or anomaly was observed at the boundary between param- agnetic and the induced-ferromagnetic regions. Our study revealed linear relation between the transverse field relaxation rate and the static magnetization. Furthermore, their ratio, which can be regarded a form of hyperfine coupling constant, is very similar in the induced ferromagnetic region and the paramagnetic region. This suggest that the Z component of the Mn moment is static in both regions. On the other hand, the single relaxation rate in the transverse spectra suggest that the internal field is highly homogeneous in the induced ferromagnetic region. We therefore speculate that the induced ferromagnetic region and the paramagnetic region are not separate phases, but rather a single phase with different tendencies as temperature decrease. With decreasing temperature, the paramagnetic region is marked with the winning of the tendency towards ferromagnetic ordering over random ordering, and the induced ferromagnetic region is marked with the winning of the tendency towards the helical order over ferromagnetic order.At lower temperature, we observed dynamic critical behavior in the boundary between the induced ferromagnetic region and the Skyrmion region. Specifically, in low fields, the 1/T1 relaxation rate behaves qualitatively different from the prediction of SCR theory for itinerant ferromagnet for large temperature regime above Tc. In high fields, on the other hand, the system recovers the SCR itinerant ferromagnetic behavior. Through analyzing field effect on spin fluctuation and phase transition in the low and high field regimes, we speculate that this could be due to the suppression of helical fluctuation into ferromagnetic-like fluc- tuation by large magnetic fields. Our μSR results, which show 2nd order signature for the transition between the induced ferromagnetic region into the Skyrmion region, is consistent with considerations based on the topology of the magnetic structure in each phase. At low temperatures within the Skyrmion region of MnGe, our analysis of the transverse field data shows that all the three components of the Mn moment is frozen. The quadratic tempera- ture dependence of 1/T1 at low temperatures suggest the two-magnon spin wave to be the dominant spin excitation in the Skyrmion region. This is similar to those seen in local- ized moment magnets and is qualitatively different from the linear temperature dependence predicted from SCR theory for itinerant ferromagnets. The second half of the thesis present our derivation of the structure function and the pair distribution function (PDF) for textured materials. We also derive the analytical form of the PDF for a few special cases of texture. In this study, we start from the general form of a 3D structure function and derive the general and orientationally averaged form of the structure function and PDF for textured samples. In particular for a thin film sample with fibre texture, our formalism gives the result known as the 2 dimensional PDF. We developed open-software that calculates the 2 dimensional PDF for a textured thin film, and showed that the experimental PDF was well fitted using the model. On the other hand, the PDF method could be extended to an energy-dependent form, which could reveal explicitly the effect of lattice dynamics on the local arrangement of the atoms. This is usually called the dynamic PDF method. In this thesis we derive the analytical form of the dynamic PDF for a simple molecule that contains two identical atoms. And we interpret the mathematical results with physical consideration of the lattice dynamics. In addition, we also propose a new definition for the dynamic PDF which can be shown to reduce to the atomic PDF by integrating over energy. This new definition of the dynamic PDF incorporates the contribution from multi-phonon scattering effects, and can be computed conveniently from inelastic neutron scattering

Automated feature extraction in oceanographic visualization

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (leaves 141-147).The ocean is characterized by a multitude of powerful, sporadic biophysical dynamical events; scientific research has reached the stage that their interpretation and prediction is now becoming possible. Ocean prediction, analogous to atmospheric weather prediction but combining biological, chemical and physical features is able to help us understand the complex coupled physics, biology and acoustics of the ocean. Applications of the prediction of the ocean environment include exploitation and management of marine resources, pollution control such as planning of maritime and naval operations. Given the vastness of ocean, it is essential for effective ocean prediction to employ adaptive sampling to best utilize the available sensor resources in order to minimize the forecast error. It is important to concentrate measurements to the regions where one can witness features of physical or biological significance in progress. Thus automated feature extraction in oceanographic visualization can facilitate adaptive sampling by presenting the physically relevant features directly to the operation planners. Moreover it could be used to help automate adaptive sampling. Vortices (eddies and gyres) and upwelling, two typical and important features of the ocean, are studied.(cont.) A variety of feature extraction methods are presented, and those more pertinent to this study are implemented, including derived field generation and attribute set extraction. Detection results are evaluated in terms of accuracy, computational efficiency, clarity and usability. Vortices, a very important flow feature is the primary focus of this study. Several point-based and set-based vortex detection methods are reviewed. A set-based vortex core detection method based on geometric properties of vortices is applied to both classical vortex models and real ocean models. The direction spanning property, which is a geometric property, guides the detection of all the vortex core candidates, and the conjugate pair eigenvalue method is responsible for filtering out the false positives from the candidate set. Results show the new method to be analytically accurate and practically feasible, and superior to traditional point-based vortex detection methods. Detection methods of streamlines are also discussed. Using the novel cross method or the winding angle method, closed streamlines around vortex cores can be detected.(cont.) Therefore, the whole vortex area, i.e., the combination of vortex core and surrounding streamlines, is detected. Accuracy and feasibility are achieved through automated vortex detection requiring no human inspection. The detection of another ocean feature, upwelling, is also discussed.by Da Guo.S.M

Doctor of Philosophy

dissertationWith modern computational resources rapidly advancing towards exascale, large-scale simulations useful for understanding natural and man-made phenomena are becoming in- creasingly accessible. As a result, the size and complexity of data representing such phenom- ena are also increasing, making the role of data analysis to propel science even more integral. This dissertation presents research on addressing some of the contemporary challenges in the analysis of vector fields--an important type of scientific data useful for representing a multitude of physical phenomena, such as wind flow and ocean currents. In particular, new theories and computational frameworks to enable consistent feature extraction from vector fields are presented. One of the most fundamental challenges in the analysis of vector fields is that their features are defined with respect to reference frames. Unfortunately, there is no single ""correct"" reference frame for analysis, and an unsuitable frame may cause features of interest to remain undetected, thus creating serious physical consequences. This work develops new reference frames that enable extraction of localized features that other techniques and frames fail to detect. As a result, these reference frames objectify the notion of ""correctness"" of features for certain goals by revealing the phenomena of importance from the underlying data. An important consequence of using these local frames is that the analysis of unsteady (time-varying) vector fields can be reduced to the analysis of sequences of steady (time- independent) vector fields, which can be performed using simpler and scalable techniques that allow better data management by accessing the data on a per-time-step basis. Nevertheless, the state-of-the-art analysis of steady vector fields is not robust, as most techniques are numerical in nature. The residing numerical errors can violate consistency with the underlying theory by breaching important fundamental laws, which may lead to serious physical consequences. This dissertation considers consistency as the most fundamental characteristic of computational analysis that must always be preserved, and presents a new discrete theory that uses combinatorial representations and algorithms to provide consistency guarantees during vector field analysis along with the uncertainty visualization of unavoidable discretization errors. Together, the two main contributions of this dissertation address two important concerns regarding feature extraction from scientific data: correctness and precision. The work presented here also opens new avenues for further research by exploring more-general reference frames and more-sophisticated domain discretizations