1,191 research outputs found

    Modeling, analysis, and simulation for aqueous-based ceramic pastes in freeze-form extrusion fabrication process

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    During the freeze-form extrusion fabrication process, both the extrusion and freezing processes are complex due to the aqueous-based ceramic pastes\u27 non-Newtonian behavior, large latent heat of the water contained in the paste, and the small temperature difference between the ambient and the paste. In this study, the steady-state relationship between plunger velocity and extrusion force is developed based on a modified Herschel-Bulkley viscosity model and the Navier-Stokes equations, and the dynamic response of the extrusion force is described by a first-order nonlinear equation when plunger velocity is taken as an input. It is shown that the extrusion response time depends on the amount of air inside the extruder and the magnitude of the extrusion force. Air bubble release and pre-loading are then analyzed based on the developed constitutive model. The freezing process is modeled by a simplified one-dimensional heat transfer model and a lumped method. As the layer number increases, the paste freezing time increases and finally reaches a steady state. A non-dimensional analytical solution for the freezing time of parts with large numbers of layers was obtained using the lumped method. The effects of both non-dimensional and dimensional factors on the critical freezing time were studied. The critical freezing time is the time when the steady-state freezing time equals the total time between layers, which is the sum of the deposition time for the current layer and the dwell time between the current and next layers. A series of simulations and experiments were conducted to validate the predictive capabilities of the constitutive model for the extrusion force and the critical freezing time for parts with large numbers of layers. Good agreements between the simulation and experimental results were obtained. --Abstract, page iii

    Ternary system of pyrolytic lignin, mixed solvent, and water: phase diagram and implications

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    Bio-oil from biomass fast pyrolysis is considered to be an important feedstock for the production of renewable fuels and green chemicals. Fast pyrolysis bio-oil generally contains a water-soluble fraction (excluding water), a water-insoluble fraction (i.e., pyrolytic lignin, PL), and water in a single phase. However, phase separation can occur during bio-oil transport, storage, and processing. In this study, a mixed solvent (MS) is developed based on the compositions of various fast pyrolysis bio-oils produced from a wide range of feedstocks and reactor systems. Experiments are then carried out to investigate the phase behavior of the PL/MS/water ternary system. Several ternary phase diagrams are constructed for PL and its fractions, and the PL solubilities in various MS/water mixtures are also estimated. Under the experimental conditions, the PL solubility in the MS is high, i.e., ∼112 g per 100 g of MS. In the PL/MS/water system, an increase in water content to ∼17 wt % in the MS/water mixture leads to a slight increase in the PL solubility to a maximal value of ∼118 g per 100 g of MS/water mixture, followed by a gradual decrease in the PL solubility when the water content further increases. It is found that the phase stability of the PL/MS/ water system is strongly determined by the composition of the system. For example, the PL/MS/water system is always stable when the MS content is \u3e50 wt %, while the system is always phase-separated when the PL content is \u3e54 wt %. A comparison of the results for various PL fractions indicates that the molecular weight of PL can affect the ternary phase diagram, with the PL of a lower molecular weight having a higher solubility in the same MS/water mixture. The presence of free sugar (i.e., levoglucosan, present in bio-oil as solute) also influences the ternary phase diagram of the PL/MS/system, but only at a low water content (i.e., \u3c 20 wt %). The results suggest that such ternary diagrams may be potentially an important tool for predicting the phase separation of bio-oil, as a result of changes in the bio-oil chemistry in various processes (e.g., cold-water precipitation and aging). Please click Additional Files below to see the full abstract

    HETEROGENEOUS UNCERTAINTY QUANTIFICATION FOR RELIABILITY-BASED DESIGN OPTIMIZATION

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    Uncertainty is inherent to real-world engineering systems, and reliability analysis aims at quantitatively measuring the probability that engineering systems successfully perform the intended functionalities under various sources of uncertainties. In this dissertation, heterogeneous uncertainties including input variation, data uncertainty, simulation model uncertainty, and time-dependent uncertainty have been taken into account in reliability analysis and reliability-based design optimization (RBDO). The input variation inherently exists in practical engineering system and can be characterized by statistical modeling methods. Data uncertainty occurs when surrogate models are constructed to replace the simulations or experiments based on a set of training data, while simulation model uncertainty is introduced when high-fidelity simulation models are built through idealizations and simplifications of real physical processes or systems. Time-dependent uncertainty is involved when considering system or component aging and deterioration. Ensuring a high level of system reliability is one of the critical targets for engineering design, and this dissertation studies effective reliability analysis and reliability-based design optimization (RBDO) techniques to address the challenges of heterogeneous uncertainties. First of all, a novel reliability analysis method is proposed to deal with input randomness and time-dependent uncertainty. An ensemble learning framework is designed by integrating the Long short-term memory (LSTM) and feedforward neural network. Time-series data is utilized to construct a surrogate model for capturing the time-dependent responses with respect to input variables and stochastic processes. Moreover, a RBDO framework with Kriging technique is presented to address the time-dependent uncertainty in design optimization. Limit state functions are transformed into time-independent domain by converting the stochastic processes and time parameter to random variables, and Kriging surrogate models are then built and enhanced by a design-driven adaptive sampling scheme to accurately identify potential instantaneous failure events. Secondly, an equivalent reliability index (ERI) method is proposed for handling both input variations and surrogate model uncertainty in RBDO. To account for the surrogate model uncertainty, a Gaussian mixture model is constructed based on Gaussian process model predictions. To propagate both input variations and surrogate model uncertainty into reliability analysis, the statistical moments of the GMM is utilized for calculating an equivalent reliability index. The sensitivity of ERI with respect to design variables is analytically derived to facilitate the surrogate model-based product design process, lead to reliable optimum solutions. Thirdly, different effective methods are developed to handle the simulation model uncertainty as well as the surrogate model uncertainty. An active resource allocation framework is proposed for accurate reliability analysis using both simulation and experimental data, where a two-phase updating strategy is developed for reducing the computational costs. The framework is further extended for RBDO problems, where multi-fidelity design algorithm is presented to ensure accurate optimum designs while minimizing the computational costs. To account for both the bias terms and unknown parameters in the simulation model, Bayesian inference method is adopted for building a validated surrogate model, and a Bayesian-based mixture modeling method is developed to ensure reliable system designs with the consideration of heterogeneous uncertainties

    On 4-dimensional Ricci-flat ALE manifolds

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    In this paper, we prove: 1. There is a one-to-one correspondence between: Hermitian non-K\"ahler Ricci-flat ALE 4-manifolds (M,h)(M,h), and Bach-flat K\"ahler orbifolds (M^,g^)(\widehat{M},\widehat{g}) of complex dimension 2, with exactly one orbifold point qq, such that the scalar curvature sg^s_{\widehat{g}} satisfies sg^(q)=0s_{\widehat{g}}(q)=0 while being positive elsewhere. 2. There is no Hermitian non-K\"ahler Ricci-flat ALE 4-manifolds (M,h)(M,h) with structure group contained in SU(2)SU(2), except for the Eguchi-Hanson metric with reversed orientation.Comment: Version 3. Improvement on arrangement

    NONLINEAR DIELECTRIC BEHAVIOR OF FIELD-INDUCED ANTIFERROELECTRIC/PARAELECTRIC-TO-FERROELECTRIC PHASE TRANSITION FOR HIGH ENERGY DENSITY CAPACITOR APPLICATION

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    Electric field-induced antiferroelectric(AFE)/paraelectric(PE)-to-ferroelectric(FE) phase transitions are investigated for the associated nonlinear dielectric behavior, which could offer high dielectric capacity. The phenomenon in monolithic materials has been computed for Kittel antiferroelectric and BaTiO3 model systems using the Landau-Ginzburg-Devonshire theory. The general switching curves give values of the polarization as a function of external electric field. A similar computation is performed for particle-filled polymer-matrix composites where an internal depolarization field is considered. The polarization-electric field response changes with different depolarization factors, which demonstrate the shape and alignment of the dielectric particles embedded in polymer-matrix are key factors for the composite to achieve high dielectric capacity

    DNA Base Excision Repair and Double Strand Break Repair in Human Fibroblast

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    In eukaryotes, DNA repair mechanisms detect and repair damaged DNA. DNA damage is primarily caused by a variety of exogenous and endogenous sources. Several types of damage to DNA are repaired by different kinds of DNA repair pathways. This dissertation focused on repair of N-methylpurines (NMPs) and double-strand breaks (DSBs) in human fibroblasts. NMPs, including N7-methylguanine (7MeG) and N3-methyladenine (3MeA), can be induced by environmental methylating agents (e.g. the soil fumigant methyl bromide), chemotherapeutics (e.g. nitrogen mustards), and natural cellular methyl donors like S-adenosylmethionine. In human cells, NMPs are repaired by the multi-step base excision repair pathway initiated by human alkyladenine glycosylase (hAAG). Repair of NMPs has been shown to be affected by DNA sequence contexts. However, the nature of the sequence contexts has been poorly understood. We developed a sensitive method, LAF-Seq (Lesion-Adjoining Fragment Sequencing), which allows nucleotide-resolution digital mapping of DNA damage and repair in multiple genomic fragments of interest in human cells. We also developed a strategy that allows accurate measurement of the excision kinetics of NMP bases in vitro. We demonstrate that 3MeAs are induced to a much lower level by the SN2 methylating agent dimethyl sulfate (DMS) and repaired much faster than 7MeGs in human fibroblasts. Induction of 7MeGs by DMS is affected by nearest-neighbor nucleotides, being enhanced at sites neighbored by a G or T on the 3’ side, but impaired at sites neighbored by a G on the 5’ side. Repair of 7MeGs is also affected by nearest-neighbor nucleotides, being slow if the lesions are between purines, especially Gs, and fast if the lesions are between pyrimidines, especially Ts. Excision of 7MeG bases from the DNA backbone by hAAG in vitro is similarly affected by nearest-neighbor nucleotides, suggesting that the effect of nearest-neighbor nucleotides on repair of 7MeGs in the cells is primarily achieved by modulating the initial step of the base excision repair process. DSBs can be induced by hydrogen peroxide (H2O2), endonuclease I-PpoI and ionizing radiation. Senataxin is a putative RNA/DNA helicase. We demonstrate that senataxin facilitates repair of DSBs and modulates the activation of DNA damage response pathway of ATM-Chk2 and ATR-Chk1 upon DSB damage

    Turing Degrees and Randomness for Continuous Measures

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    We study degree-theoretic properties of reals that are not random with respect to any continuous probability measure (NCR). To this end, we introduce a family of generalized Hausdorff measures based on the iterates of the "dissipation" function of a continuous measure and study the effective nullsets given by the corresponding Solovay tests. We introduce two constructions that preserve non-randomness with respect to a given continuous measure. This enables us to prove the existence of NCR reals in a number of Turing degrees. In particular, we show that every Δ20\Delta^0_2-degree contains an NCR element.Comment: 22 page
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