165,709 research outputs found

    Doctor of Philosophy

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    dissertationThree major catastrophic failures in photovoltaic (PV) arrays are ground-faults, line-to-line faults, and arc faults. Although the number of such failures is few, recent fire events on April 5, 2009, in Bakersfield, California, and April 16, 2011, in Mount Holly, North Carolina suggest the need for improvements in present fault detection and mitigation techniques, as well as amendments to existing codes and standards to avoid such accidents. A fault prediction and detection technique for PV arrays based on spread spectrum time domain reflectometry (SSTDR) has been proposed and was successfully implemented. Unlike other conventional techniques, SSTDR does not depend on the amplitude of the fault-current. Therefore, SSTDR can be used in the absence of solar irradiation as well. However, wide variation in impedance throughout different materials and interconnections makes fault locating more challenging than prediction/detection of faults. Another application of SSTDR in PV systems is the measurement of characteristic impedance of power components for condition monitoring purposes. Any characteristic variations in one component will simultaneously alter the operating conditions of other components in a closed-loop system, resulting in a shift in overall reliability profile. This interdependence makes the reliability of a converter a complex function of time and operating conditions. Details of this failure mode, mechanism, and effect analysis (FMMEA) have been developed. By knowing the present state of health and the remaining useful life (RUL) of a power converter, it is possible to reduce the maintenance cost for expensive high-power converters by facilitating a reliability centered maintenance (RCM) scheme. This research is a step forward toward power converter reliability analysis since the cumulative effect of multiple degraded components has been considered here for the first time in order to estimate reliability of a power converter

    Evaluation of Safety of Reinforced Concrete Buildings to Earthquakes

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    National Science Foundation Grant GK-3637

    Protein structural variation in computational models and crystallographic data

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    Normal mode analysis offers an efficient way of modeling the conformational flexibility of protein structures. Simple models defined by contact topology, known as elastic network models, have been used to model a variety of systems, but the validation is typically limited to individual modes for a single protein. We use anisotropic displacement parameters from crystallography to test the quality of prediction of both the magnitude and directionality of conformational variance. Normal modes from four simple elastic network model potentials and from the CHARMM forcefield are calculated for a data set of 83 diverse, ultrahigh resolution crystal structures. While all five potentials provide good predictions of the magnitude of flexibility, the methods that consider all atoms have a clear edge at prediction of directionality, and the CHARMM potential produces the best agreement. The low-frequency modes from different potentials are similar, but those computed from the CHARMM potential show the greatest difference from the elastic network models. This was illustrated by computing the dynamic correlation matrices from different potentials for a PDZ domain structure. Comparison of normal mode results with anisotropic temperature factors opens the possibility of using ultrahigh resolution crystallographic data as a quantitative measure of molecular flexibility. The comprehensive evaluation demonstrates the costs and benefits of using normal mode potentials of varying complexity. Comparison of the dynamic correlation matrices suggests that a combination of topological and chemical potentials may help identify residues in which chemical forces make large contributions to intramolecular coupling.Comment: 17 pages, 4 figure

    A stochastic framework for multiscale strength prediction using adaptive discontinuity layout optimisation (ADLO)

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    The prediction of strength properties of matrix-inclusion materials, which in general are random in nature due to their spatial distribution and variation of pores, particles, and matrix-inclusion interfaces, plays an important role with regard to the reliability of materials and structures. The recently developed discontinuity layout optimisation (DLO) [18] and adaptive discontinuity layout optimisation (ADLO) [4], which can be used for determination of strength properties of materials [3, 4] and structures [9], are included in a stochastic framework, using random variables. Therefore different material properties, influencing the overall strength of the matrix-inclusion material (e.g. matrix and inclusion strength, number and distribution of pores/particles) in a considered RVE are assumed to follow certain probability distributions [12]. A sensitivity study for the identification of material parameters showing the largest influence on the strength of the considered matrix-inclusion materials is performed. The obtained results provide first insight into the nature of the reliability of strength properties of matrix-inclusion materials, paving the way to a better understanding and finally improvement of the effective strength properties of matrix-inclusion materials

    A Probabilistic Study Of Safety Criteria For Design

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    National Science Foundation Under Grant GK-1812

    A Structural Safety Analysis of Buildings During Construction

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    The safety of steel buildings, constructed by the tier method, is evaluated. The probability of failure of steel frames supported on temporary connections is examined during the different stages of completion. The principal loading of concern is the maximum wind load over the critical stages of construction.National Science Foundation Grants ENG 77-02007, ENV 77-09090, and PFR 80-0258

    Reduced-order modeling of transonic flows around an airfoil submitted to small deformations

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    A reduced-order model (ROM) is developed for the prediction of unsteady transonic flows past an airfoil submitted to small deformations, at moderate Reynolds number. Considering a suitable state formulation as well as a consistent inner product, the Galerkin projection of the compressible flow Navier–Stokes equations, the high-fidelity (HF) model, onto a low-dimensional basis determined by Proper Orthogonal Decomposition (POD), leads to a polynomial quadratic ODE system relevant to the prediction of main flow features. A fictitious domain deformation technique is yielded by the Hadamard formulation of HF model and validated at HF level. This approach captures airfoil profile deformation by a modification of the boundary conditions whereas the spatial domain remains unchanged. A mixed POD gathering information from snapshot series associated with several airfoil profiles can be defined. The temporal coefficients in POD expansion are shape-dependent while spatial POD modes are not. In the ROM, airfoil deformation is introduced by a steady forcing term. ROM reliability towards airfoil deformation is demonstrated for the prediction of HF-resolved as well as unknown intermediate configurations

    A compositional method for reliability analysis of workflows affected by multiple failure modes

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    We focus on reliability analysis for systems designed as workflow based compositions of components. Components are characterized by their failure profiles, which take into account possible multiple failure modes. A compositional calculus is provided to evaluate the failure profile of a composite system, given failure profiles of the components. The calculus is described as a syntax-driven procedure that synthesizes a workflows failure profile. The method is viewed as a design-time aid that can help software engineers reason about systems reliability in the early stage of development. A simple case study is presented to illustrate the proposed approach

    Effects of near wall modeling in the Improved-Delayed-Detached-Eddy-Simulation (IDDES) methodology

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    The present study aims to assess the effects of two different underlying RANS models on overall behavior of the IDDES methodology when applied to different flow configurations ranging from fully attached (plane channel flow) to separated flows (periodic hill flow). This includes investigating prediction accuracy of first and second order statistics, response to grid refinement, grey area dynamics and triggering mechanism. Further, several criteria have been investigated to assess reliability and quality of the methodology when operating in scale resolving mode. It turns out that irrespective of the near wall modeling strategy, the IDDES methodology does not satisfy all criteria required to make this methodology reliable when applied to various flow configurations at different Reynolds numbers with different grid resolutions. Further, it is found that using more advanced underlying RANS model to improve prediction accuracy of the near wall dynamics results in extension of the grey area, which may delay the transition to scale resolving mode. This systematic study for attached and separated flows suggests that the shortcomings of IDDES methodology mostly lie in inaccurate prediction of the dynamics inside the grey area and demands further investigation in this direction to make this methodology capable of dealing with different flow situations reliably
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