Matching Items (56)

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Thermochemical Humidity Detection in Harsh or Non-Steady Environments

Description

We present a new method of chemical quantification utilizing thermal analysis for the detection of relative humidity. By measuring the temperature change of a hydrophilically-modified temperature sensing element vs. a

We present a new method of chemical quantification utilizing thermal analysis for the detection of relative humidity. By measuring the temperature change of a hydrophilically-modified temperature sensing element vs. a hydrophobically-modified reference element, the total heat from chemical interactions in the sensing element can be measured and used to calculate a change in relative humidity. We have probed the concept by assuming constant temperature streams, and having constant reference humidity (~0% in this case). The concept has been probed with the two methods presented here: (1) a thermistor-based method and (2) a thermographic method. For the first method, a hydrophilically-modified thermistor was used, and a detection range of 0–75% relative humidity was demonstrated. For the second method, a hydrophilically-modified disposable surface (sensing element) and thermal camera were used, and thermal signatures for different relative humidity were demonstrated. These new methods offer opportunities in either chemically harsh environments or in rapidly changing environments. For sensing humidity in a chemically harsh environment, a hydrophilically-modified thermistor can provide a sensing method, eliminating the exposure of metallic contacts, which can be easily corroded by the environment. On the other hand, the thermographic method can be applied with a disposable non-contact sensing element, which is a low-cost upkeep option in environments where damage or fouling is inevitable. In addition, for environments that are rapidly changing, the thermographic method could potentially provide a very rapid humidity measurement as the chemical interactions are rapid and their changes are easily quantified.

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Date Created
  • 2017-05-24

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Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation

Description

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents

Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.

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Date Created
  • 2016-08-16

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Big Data Analytics for Pipe Damage and Risk Identification

Description

In this thesis, Inception V3, a convolutional neural network model from Google, was partially retrained to categorize pipeline images based on their damage modes. The images for different damage modes

In this thesis, Inception V3, a convolutional neural network model from Google, was partially retrained to categorize pipeline images based on their damage modes. The images for different damage modes of the pipeline were simulated through MATLAB to represent image data collected from in-line pipe inspection. The final convolutional layer of the model was retrained with the simulated pipeline images using TensorFlow as the base platform. First, a small-scale retraining was done with real images and simulated images to compare the differences in performance. Then, using simulated images, a 2^5 full factorial design of experiment and individual parametric studies were performed on five different chosen parameters, including training steps, learning rate, batch size, training data size and image noise. The effect of each parameter on the performance of the model was evaluated and analyzed. It is crucial to understand that due to the nature of the experiment, the learnings may or may not apply to neural network models trained for other tasks. After analyzing the results, the effects and trade-offs for each parameter are discussed in detail. In addition, a method of predicting the training time was proposed. Based on the findings, an optimized model was proposed for this training exercise, with 1180 training steps, a learning rate of 0.01, a batch size of 100 and a training data set of 200 images. The optimized model reached 87.2% accuracy with a training time of 2 minutes and 6 seconds. This study will enhance our understanding in applying machine learning techniques in damage and risk identification.

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  • 2018-05

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In situ SEM Testing for Fatigue Crack Growth: Mechanical Investigation of Titanium

Description

Widespread knowledge of fracture mechanics is mostly based on previous models that generalize crack growth in materials over several loading cycles. The objective of this project is to characterize crack

Widespread knowledge of fracture mechanics is mostly based on previous models that generalize crack growth in materials over several loading cycles. The objective of this project is to characterize crack growth that occurs in titanium alloys, specifically Grade 5 Ti-6Al-4V, at the sub-cycle scale, or within a single loading cycle. Using scanning electron microscopy (SEM), imaging analysis is performed to observe crack behavior at ten loading steps throughout the loading and unloading paths. Analysis involves measuring the incremental crack growth and crack tip opening displacement (CTOD) of specimens at loading ratios of 0.1, 0.3, and 0.5. This report defines the relationship between crack growth and the stress intensity factor, K, of the specimens, as well as the relationship between the R-ratio and stress opening level. The crack closure phenomena and effect of microcracks are discussed as they influence the crack growth behavior. This method has previously been used to characterize crack growth in Al 7075-T6. The results for Ti-6Al-4V are compared to these previous findings in order to strengthen conclusions about crack growth behavior.

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  • 2018-05

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Efficient extended finite element algorithms for strongly and weakly discontinuous entities with complex internal geometries

Description

The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials

The objective of this research is to develop robust, accurate, and adaptive algorithms in the framework of the extended finite element method (XFEM) for fracture analysis of highly heterogeneous materials with complex internal geometries. A key contribution of this work is the creation of novel methods designed to automate the incorporation of high-resolution data, e.g. from X-ray tomography, that can be used to better interpret the enormous volume of data generated in modern in-situ experimental testing. Thus new algorithms were developed for automating analysis of complex microstructures characterized by segmented tomographic images.

A centrality-based geometry segmentation algorithm was developed to accurately identify discrete inclusions and particles in composite materials where limitations in imaging resolution leads to spurious connections between particles in close contact.To allow for this algorithm to successfully segment geometry independently of particle size and shape, a relative centrality metric was defined to allow for a threshold centrality criterion for removal of voxels that spuriously connect distinct geometries.

To automate incorporation of microstructural information from high-resolution images, two methods were developed that initialize signed distance fields on adaptively-refined finite element meshes. The first method utilizes a level set evolution equation that is directly solved on the finite element mesh through Galerkins method. The evolution equation is formulated to produce a signed distance field that matches geometry defined by a set of voxels segmented from tomographic images. The method achieves optimal convergence for the order of elements used. In a second approach, the fast marching method is employed to initialize a distance field on a uniform grid which is then projected by least squares onto a finite element mesh. This latter approach is shown to be superior in speed and accuracy.

Lastly, extended finite element method simulations are performed for the analysis of particle fracture in metal matrix composites with realistic particle geometries initialized from X-ray tomographic data. In the simulations, particles fracture probabilistically through a Weibull strength distribution. The model is verified through comparisons with the experimentally-measured stress-strain response of the material as well as analysis of the fracture. Further, simulations are then performed to analyze the effect of mesh sensitivity, the effect of fracture of particles on their neighbors, and the role of a particles shape on its fracture probability.

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Date Created
  • 2015

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A generalized orthotropic elasto-plastic material model for impact analysis

Description

Composite materials are now beginning to provide uses hitherto reserved for metals in structural systems such as airframes and engine containment systems, wraps for repair and rehabilitation, and ballistic/blast mitigation

Composite materials are now beginning to provide uses hitherto reserved for metals in structural systems such as airframes and engine containment systems, wraps for repair and rehabilitation, and ballistic/blast mitigation systems. These structural systems are often subjected to impact loads and there is a pressing need for accurate prediction of deformation, damage and failure. There are numerous material models that have been developed to analyze the dynamic impact response of polymer matrix composites. However, there are key features that are missing in those models that prevent them from providing accurate predictive capabilities. In this dissertation, a general purpose orthotropic elasto-plastic computational constitutive material model has been developed to predict the response of composites subjected to high velocity impacts. The constitutive model is divided into three components – deformation model, damage model and failure model, with failure to be added at a later date. The deformation model generalizes the Tsai-Wu failure criteria and extends it using a strain-hardening-based orthotropic yield function with a non-associative flow rule. A strain equivalent formulation is utilized in the damage model that permits plastic and damage calculations to be uncoupled and capture the nonlinear unloading and local softening of the stress-strain response. A diagonal damage tensor is defined to account for the directionally dependent variation of damage. However, in composites it has been found that loading in one direction can lead to damage in multiple coordinate directions. To account for this phenomena, the terms in the damage matrix are semi-coupled such that the damage in a particular coordinate direction is a function of the stresses and plastic strains in all of the coordinate directions. The overall framework is driven by experimental tabulated temperature and rate-dependent stress-strain data as well as data that characterizes the damage matrix and failure. The developed theory has been implemented in a commercial explicit finite element analysis code, LS-DYNA®, as MAT213. Several verification and validation tests using a commonly available carbon-fiber composite, Toyobo’s T800/F3900, have been carried and the results show that the theory and implementation are efficient, robust and accurate.

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Date Created
  • 2016

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Molecular Dynamic Simulations of Diffusion and Phase Behaviors of Colloidal Particles in Two-Component Liquid Systems

Description

A comprehensive and systematic investigation on the diffusion and phase behaviors of nanoparticles and macromolecules in two component liquid-liquid systems via Molecule Dynamic (MD) simulations is presented in this dissertation.

The

A comprehensive and systematic investigation on the diffusion and phase behaviors of nanoparticles and macromolecules in two component liquid-liquid systems via Molecule Dynamic (MD) simulations is presented in this dissertation.

The interface of biphasic liquid systems has attracted great attention because it offers a simple, flexible, and highly reproducible template for the assembly of a variety of nanoscale objects. However, certain important fundamental issues at the interface have not been fully explored, especially when the size of the object is comparable with the liquid molecules. In the first MD simulation system, the diffusion and self-assembly of nanoparticles with different size, shape and surface composition were studied in an oil/water system. It has been found that a highly symmetrical nanoparticle with uniform surface (e.g. buckyball) can lead to a better-defined solvation shell which makes the “effective radius” of the nanoparticle larger than its own radius, and thus, lead to slower transport (diffusion) of the nanoparticles across the oil-water interface. Poly(N-isopropylacrylamide) (PNIPAM) is a thermoresponsive polymer with a Lower Critical Solution Temperature (LCST) of 32°C in pure water. It is one of the most widely studied stimulus-responsive polymers which can be fabricated into various forms of smart materials. However, current understanding about the diffusive and phase behaviors of PNIPAM in ionic liquids/water system is very limited. Therefore, two biphasic water-ionic liquids (ILs) systems were created to investigate the interfacial behavior of PNIPAM in such unique liquid-liquid interface. It was found the phase preference of PNIPAM below/above its LCST is dependent on the nature of ionic liquids. This potentially allows us to manipulate the interfacial behavior of macromolecules by tuning the properties of ionic liquids and minimizing the need for expensive polymer functionalization. In addition, to seek a more comprehensive understanding of the effects of ionic liquids on the phase behavior of PNIPAM, PNIPAM was studied in two miscible ionic liquids/water systems. The thermodynamic origin causes the reduction of LCST of PNIPAM in imidazolium based ionic liquids/water system was found. Energy analysis, hydrogen boding calculation and detailed structural quantification were presented in this study to support the conclusions.

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Date Created
  • 2017

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Subcycle fatigue crack growth formulation for constant and variable amplitude loading

Description

A previously developed small time scale fatigue crack growth model is improved, modified and extended with an emphasis on creating the simplest models that maintain the desired level of accuracy

A previously developed small time scale fatigue crack growth model is improved, modified and extended with an emphasis on creating the simplest models that maintain the desired level of accuracy for a variety of materials. The model provides a means of estimating load sequence effects by continuously updating the crack opening stress every cycle, in a simplified manner. One of the significant phenomena of the crack opening stress under negative stress ratio is the residual tensile stress induced by the applied compressive stress. A modified coefficient is introduced to determine the extent to which residual stress impact the crack closure and is observed to vary for different materials. Several other literature models for crack closure under constant loading are also reviewed and compared with the proposed model. The modified model is then shown to predict several sets of published test results under constant loading for a variety of materials.

The crack opening stress is formalized as a function of the plastic zone sizes at the crack tip and the current crack length, which provided a means of approximation, accounting for both acceleration and retardation effects in a simplified manner. A sensitivity parameter is introduced to modify the enlarged plastic zone due to overload, to better fit the delay cycles with the test data and is observed to vary for different materials. Furthermore, the interaction effect induced by the combination of overload and underload sequence is modeled by depleting the compressive plastic zone due to an overload with the tensile plastic zone due to an underload. A qualitative analysis showed the simulation capacity of the small time scale model under different load types. A good agreement between prediction and test data for several irregular load types proved the applicability of the small time scale model under variable amplitude loading.

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Date Created
  • 2016

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Corrosion and corrosion-fatigue behavior of 7075 aluminum alloys studied by in situ X-ray tomography

Description

7XXX Aluminum alloys have high strength to weight ratio and low cost. They are used in many critical structural applications including automotive and aerospace components. These applications frequently subject the

7XXX Aluminum alloys have high strength to weight ratio and low cost. They are used in many critical structural applications including automotive and aerospace components. These applications frequently subject the alloys to static and cyclic loading in service. Additionally, the alloys are often subjected to aggressive corrosive environments such as saltwater spray. These chemical and mechanical exposures have been known to cause premature failure in critical applications. Hence, the microstructural behavior of the alloys under combined chemical attack and mechanical loading must be characterized further. Most studies to date have analyzed the microstructure of the 7XXX alloys using two dimensional (2D) techniques. While 2D studies yield valuable insights about the properties of the alloys, they do not provide sufficiently accurate results because the microstructure is three dimensional and hence its response to external stimuli is also three dimensional (3D). Relevant features of the alloys include the grains, subgrains, intermetallic inclusion particles, and intermetallic precipitate particles. The effects of microstructural features on corrosion pitting and corrosion fatigue of aluminum alloys has primarily been studied using 2D techniques such as scanning electron microscopy (SEM) surface analysis along with post-mortem SEM fracture surface analysis to estimate the corrosion pit size and fatigue crack initiation site. These studies often limited the corrosion-fatigue testing to samples in air or specialized solutions, because samples tested in NaCl solution typically have fracture surfaces covered in corrosion product. Recent technological advancements allow observation of the microstructure, corrosion and crack behavior of aluminum alloys in solution in three dimensions over time (4D). In situ synchrotron X-Ray microtomography was used to analyze the corrosion and cracking behavior of the alloy in four dimensions to elucidate crack initiation at corrosion pits for samples of multiple aging conditions and impurity concentrations. Additionally, chemical reactions between the 3.5 wt% NaCl solution and the crack surfaces were quantified by observing the evolution of hydrogen bubbles from the crack. The effects of the impurity particles and age-hardening particles on the corrosion and fatigue properties were examined in 4D.

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Date Created
  • 2017

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Experimental Characterization and Finite Element Modeling of Composites to Support a Generalized Orthotropic Elasto-Plastic Damage Material Model for Impact Analysis

Description

An orthotropic elasto-plastic damage material model (OEPDMM) suitable for impact simulations has been developed through a joint research project funded by the Federal Aviation Administration (FAA) and the National Aeronautics

An orthotropic elasto-plastic damage material model (OEPDMM) suitable for impact simulations has been developed through a joint research project funded by the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA). Development of the model includes derivation of the theoretical details, implementation of the theory into LS-DYNA®, a commercially available nonlinear transient dynamic finite element code, as material model MAT 213, and verification and validation of the model. The material model is comprised of three major components: deformation, damage, and failure. The deformation sub-model is used to capture both linear and nonlinear deformations through a classical plasticity formulation. The damage sub-model is used to account for the reduction of elastic stiffness of the material as the degree of plastic strain is increased. Finally, the failure sub-model is used to predict the onset of loss of load carrying capacity in the material. OEPDMM is driven completely by tabulated experimental data obtained through physically meaningful material characterization tests, through high fidelity virtual tests, or both. The tabulated data includes stress-strain curves at different temperatures and strain rates to drive the deformation sub-model, damage parameter-total strain curves to drive the damage sub-model, and the failure sub-model can be driven by the data required for different failure theories implemented in the computer code. The work presented herein focuses on the experiments used to obtain the data necessary to drive as well as validate the material model, development and implementation of the damage model, verification of the deformation and damage models through single element (SE) and multi-element (ME) finite element simulations, development and implementation of experimental procedure for modeling delamination, and finally validation of the material model through low speed impact simulations and high speed impact simulations.

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Date Created
  • 2019