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You searched for subject:(2 point statistics). Showing records 1 – 3 of 3 total matches.

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Georgia Tech

1. Turner, David M. Construction of representative 3D microstructures from complete and partial statistics.

Degree: PhD, Mechanical Engineering, 2016, Georgia Tech

The principle concern of the material scientist is the connection between microstructure, properties, and processing. Microstructure is characterized via experimental measurements of geometry at the appropriate length scale. This is usually followed by a quantification of microstructure via statistics for which there are a broad base of possibilities including classical stereological measures such as grain size and higher order descriptions like the N-point spatial correlations. Despite advances in 3D characterization of microstructures such as X-ray tomography and serial sectioned SEM, most techniques still capture measurements only in 2D sections. Even when 3D datasets are available they are typically measuring only small volumes leading to uncertainty about their statistical significance. Can we build statistically representative reconstructions of 3D microstructure from the partial information gathered on a collection of 2D cross sections? The proposed work introduces new approaches to these problems for two phase composites with complex anisotropic geometries. Efficient algorithms for the computation of "higher order" statistics, such as N-point correlations and chord length distributions, will be explored. These higher order metrics will form the basis for establishing structure based representative volume elements (RVEs) in both cases where microstructure geometry information is complete and incomplete. Advisors/Committee Members: Kalidindi, Surya R (advisor), McDowell, David L (committee member), Garmestani, Hamid (committee member), Song, Le (committee member), Jacob, Karl I (committee member).

Subjects/Keywords: Microstructure; 2-point statistics; Reconstruction; Solid Texture Synthesis

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APA (6th Edition):

Turner, D. M. (2016). Construction of representative 3D microstructures from complete and partial statistics. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56337

Chicago Manual of Style (16th Edition):

Turner, David M. “Construction of representative 3D microstructures from complete and partial statistics.” 2016. Doctoral Dissertation, Georgia Tech. Accessed March 22, 2019. http://hdl.handle.net/1853/56337.

MLA Handbook (7th Edition):

Turner, David M. “Construction of representative 3D microstructures from complete and partial statistics.” 2016. Web. 22 Mar 2019.

Vancouver:

Turner DM. Construction of representative 3D microstructures from complete and partial statistics. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Mar 22]. Available from: http://hdl.handle.net/1853/56337.

Council of Science Editors:

Turner DM. Construction of representative 3D microstructures from complete and partial statistics. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56337

2. Do, Van Long. Sequential detection and isolation of cyber-physical attacks on SCADA systems : Détection et localisation séquentielle d’attaques cyber-physiques aux systèmes SCADA.

Degree: Docteur es, Optimisation et Sûreté des Systèmes, 2015, Troyes

Cette thèse s’inscrit dans le cadre du projet « SCALA » financé par l’ANR à travers le programme ANR-11-SECU-0005. Son objectif consiste à surveiller des systèmes de contrôle et d’acquisition de données (SCADA) contre des attaques cyber-physiques. Il s'agit de résoudre un problème de détection-localisation séquentielle de signaux transitoires dans des systèmes stochastiques et dynamiques en présence d'états inconnus et de bruits aléatoires. La solution proposée s'appuie sur une approche par redondance analytique composée de deux étapes : la génération de résidus, puis leur évaluation. Les résidus sont générés de deux façons distinctes, avec le filtre de Kalman ou par projection sur l’espace de parité. Ils sont ensuite évalués par des méthodes d’analyse séquentielle de rupture selon de nouveaux critères d’optimalité adaptés à la surveillance des systèmes à sécurité critique. Il s'agit donc de minimiser la pire probabilité de détection manquée sous la contrainte de niveaux acceptables pour la pire probabilité de fausse alarme et la pire probabilité de fausse localisation. Pour la tâche de détection, le problème d’optimisation est résolu dans deux cas : les paramètres du signal transitoire sont complètement connus ou seulement partiellement connus. Les propriétés statistiques des tests sous-optimaux obtenus sont analysées. Des résultats préliminaires pour la tâche de localisation sont également proposés. Les algorithmes développés sont appliqués à la détection et à la localisation d'actes malveillants dans un réseau d’eau potable

This PhD thesis is registered in the framework of the project “SCALA” which received financial support through the program ANR-11-SECU-0005. Its ultimate objective involves the on-line monitoring of Supervisory Control And Data Acquisition (SCADA) systems against cyber-physical attacks. The problem is formulated as the sequential detection and isolation of transient signals in stochastic-dynamical systems in the presence of unknown system states and random noises. It is solved by using the analytical redundancy approach consisting of two steps: residual generation and residual evaluation. The residuals are firstly generated by both Kalman filter and parity space approaches. They are then evaluated by using sequential analysis techniques taking into account certain criteria of optimality. However, these classical criteria are not adequate for the surveillance of safety-critical infrastructures. For such applications, it is suggested to minimize the worst-case probability of missed detection subject to acceptable levels on the worst-case probability of false alarm and false isolation. For the detection task, the optimization problem is formulated and solved in both scenarios: exactly and partially known parameters. The sub-optimal tests are obtained and their statistical properties are investigated. Preliminary results for the isolation task are also obtained. The proposed algorithms are applied to the detection and isolation of malicious attacks on a simple SCADA water network

Advisors/Committee Members: Fillatre, Lionel (thesis director), Nikiforov, Igor Vladimirovitch (thesis director).

Subjects/Keywords: Analyse séquentielle; Détection du signal; Rupture (statistique); Modèles linéaires (statistique); Criminalité informatique; Sequential analysis; Signal detection; Change-point problems; Linear models (Statistics); Computer crimes; 621.382 2

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Do, V. L. (2015). Sequential detection and isolation of cyber-physical attacks on SCADA systems : Détection et localisation séquentielle d’attaques cyber-physiques aux systèmes SCADA. (Doctoral Dissertation). Troyes. Retrieved from http://www.theses.fr/2015TROY0032

Chicago Manual of Style (16th Edition):

Do, Van Long. “Sequential detection and isolation of cyber-physical attacks on SCADA systems : Détection et localisation séquentielle d’attaques cyber-physiques aux systèmes SCADA.” 2015. Doctoral Dissertation, Troyes. Accessed March 22, 2019. http://www.theses.fr/2015TROY0032.

MLA Handbook (7th Edition):

Do, Van Long. “Sequential detection and isolation of cyber-physical attacks on SCADA systems : Détection et localisation séquentielle d’attaques cyber-physiques aux systèmes SCADA.” 2015. Web. 22 Mar 2019.

Vancouver:

Do VL. Sequential detection and isolation of cyber-physical attacks on SCADA systems : Détection et localisation séquentielle d’attaques cyber-physiques aux systèmes SCADA. [Internet] [Doctoral dissertation]. Troyes; 2015. [cited 2019 Mar 22]. Available from: http://www.theses.fr/2015TROY0032.

Council of Science Editors:

Do VL. Sequential detection and isolation of cyber-physical attacks on SCADA systems : Détection et localisation séquentielle d’attaques cyber-physiques aux systèmes SCADA. [Doctoral Dissertation]. Troyes; 2015. Available from: http://www.theses.fr/2015TROY0032


Georgia Tech

3. Paulson, Noah H. Structure-property linkages for polycrystalline materials using materials knowledge systems.

Degree: PhD, Mechanical Engineering, 2017, Georgia Tech

Computational tools that are capable of rapidly exploring candidate microstructures and their associated properties are required to accelerate the rate of development and deployment of novel materials. In this work, a suite of computationally efficient protocols, based on the materials knowledge system (MKS) framework, are developed to evaluate the properties and performance of polycrystalline microstructures. In the MKS approach, physics-capturing coefficients (calibrated with microstructures and their responses obtained via experiments or simulations) store the microstructure-sensitive response of the material system of interest. Once calibrated, the linkages may be employed to predict the local responses (through localization) or effective properties (through homogenization) of new microstructures at low computational expense. Specifically, protocols are developed to predict bulk properties (elastic stiffness and yield strength), local cyclic plastic strains and resistance to fatigue crack formation and early growth (in the high cycle fatigue and transition fatigue regimes). These protocols are demonstrated on a diverse set of α-titanium microstructures, which exhibit heterogeneous microstructure features, in addition to anisotropy on multiple length-scales. Advisors/Committee Members: Kalidindi, Surya R. (advisor), McDowell, David L. (committee member), Shih, Donald S. (committee member), Neu, Richard W. (committee member), Garmestani, Hamid (committee member).

Subjects/Keywords: Microstructure; Structure-property relationship; Polycrystalline; Titanium alloys; High cycle fatigue; Transition fatigue; Yield strength; Elastic modulus; Data science; Materials informatics; High-throughput; 2-point correlations; Computational model; Crystal plasticity; Reduced-order model; Extreme value statistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Paulson, N. H. (2017). Structure-property linkages for polycrystalline materials using materials knowledge systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/60113

Chicago Manual of Style (16th Edition):

Paulson, Noah H. “Structure-property linkages for polycrystalline materials using materials knowledge systems.” 2017. Doctoral Dissertation, Georgia Tech. Accessed March 22, 2019. http://hdl.handle.net/1853/60113.

MLA Handbook (7th Edition):

Paulson, Noah H. “Structure-property linkages for polycrystalline materials using materials knowledge systems.” 2017. Web. 22 Mar 2019.

Vancouver:

Paulson NH. Structure-property linkages for polycrystalline materials using materials knowledge systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2019 Mar 22]. Available from: http://hdl.handle.net/1853/60113.

Council of Science Editors:

Paulson NH. Structure-property linkages for polycrystalline materials using materials knowledge systems. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/60113

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