Matching Items (68)

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Structural Health Monitoring of Fiber Reinforced Composite Structures under High Velocity Impact Loads

Description

This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates,

This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates, and evaluating the damage post-impact. To this end, various non-destructive evaluation techniques such as ultrasonic C-scan testing and flash thermography were utilized for post-impact analysis. MATLAB algorithms were written and refined for the localization and quantification of damage in plates using data from sensors such as piezoelectric and fiber Bragg gratings sensors. Throughout the thesis, the general plate theory and laminate plate theory, the operations and optimization of the gas gun, and the theory used for the damage localization algorithms will be discussed. Additional quantifiable results are to come in future semesters of experimentation, but this thesis outlines the framework upon which all the research will continue to advance.

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Created

Date Created
  • 2016-05

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STRUCTURAL HEALTH MONITORING OF FIBER REINFORCED COMPOSITE STRUCTURES UNDER HIGH VELOCITY IMPACT LOADS

Description

This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates,

This thesis encompasses research performed in the focus area of structural health monitoring. More specifically, this research focuses on high velocity impact testing of carbon fiber reinforced structures, especially plates, and evaluating the damage post-impact. To this end, various non-destructive evaluation techniques such as ultrasonic C-scan testing and flash thermography were utilized for post-impact analysis. MATLAB algorithms were written and refined for the localization and quantification of damage in plates using data from sensors such as piezoelectric and fiber Bragg gratings sensors. Throughout the thesis, the general plate theory and laminate plate theory, the operations and optimization of the gas gun, and the theory used for the damage localization algorithms will be discussed. Additional quantifiable results are to come in future semesters of experimentation, but this thesis outlines the framework upon which all the research will continue to advance.

Contributors

Created

Date Created
  • 2015-05

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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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Created

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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Created

Date Created
  • 2016-08-16

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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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Created

Date Created
  • 2018-05

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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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Created

Date Created
  • 2018-05

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Estimation of J-integral for a non-local particle model using atomistic finite element method and coupling between non-local particle and finite element methods

Description

In this paper, at first, analytical formulation of J-integral for a non-local particle model (VCPM) using atomic scale finite element method is proposed for fracture analysis of 2D solids. A

In this paper, at first, analytical formulation of J-integral for a non-local particle model (VCPM) using atomic scale finite element method is proposed for fracture analysis of 2D solids. A brief review of classical continuum-based J-integral and anon-local lattice particle method is given first. Following this, detailed derivation for the J-integral in discrete particle system is given using the energy equivalence and stress-tensor mapping between the continuum mechanics and lattice-particle system.With the help of atomistic finite element method, the J-integral is expressed as a summation of the corresponding terms in the particle system.

Secondly, a coupling algorithm between a non-local particle method (VCPM) and the classical finite element method (FEM) is discussed to gain the advantages of both methods for fracture analysis in large structures. In this algorithm, the discrete VCPM particle and the continuum FEM domains are solved within a unified theoretical framework. A transitional element technology is developed to smoothly link the 10-particles element with the traditional FEM elements to guaranty the continuity and consistency at the coupling interface. An explicit algorithm for static simulation is developed.

Finally, numerical examples are illustrated for the accuracy, convergence, and path-independence of the derived J-integral formulation. Discussions on the comparison with alternative estimation methods and potential application for fracture simulation are given. The accuracy and efficiency of the coupling algorithm are tested by several benchmark problems such as static crack simulation.

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Created

Date Created
  • 2016

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Numerical and experimental investigation of laser-induced optoacoustic wave propagation for damage detection

Description

An integrated experimental and numerical investigation for laser-generated optoacoustic wave propagation in structural materials is performed. First, a multi-physics simulation model is proposed to simulate the pulsed laser as a

An integrated experimental and numerical investigation for laser-generated optoacoustic wave propagation in structural materials is performed. First, a multi-physics simulation model is proposed to simulate the pulsed laser as a point heat source which hits the surface of an aluminum sheet. The pulsed laser source can generate a localized heating on the surface of the plate and induce an in-plane stress wave. ANSYS – a finite element analysis software – is used to build the 3D model and a coupled thermal-mechanical simulation is performed in which the heat flux is determined by an empirical laser-heat conversion relationship. The displacement and stress field-histories are obtained to get the time of arrival and wave propagation speed of the stress wave. The effect of an added point mass is investigated in detail to observe the local material perturbation and remote wave signals. Following this, the experimental investigation of optoacoustic wave is also performed. A new experimental setup and control is developed and assembled in-house. Various laser firing parameters are investigated experimentally and the optimal combination is used for the experimental testing. Matrix design for different testing conditions is also proposed to include the effect of wave path, sampling procedure, and local point mass on the optoacoustic wave propagation. The developed numerical simulation results are validated with experimental observations. It is shown that the proposed experimental setup can offer a potential fast scanning method for damage detection (local property change) for plate-like structural component.

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Agent

Created

Date Created
  • 2016

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Microstructural Quantification, Property Prediction, and Stochastic Reconstruction of Heterogeneous Materials Using Limited X-Ray Tomography Data

Description

An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for quantitative structure-property relations establishment and its performance prediction and optimization. X-ray tomography has provided a non-destructive

An accurate knowledge of the complex microstructure of a heterogeneous material is crucial for quantitative structure-property relations establishment and its performance prediction and optimization. X-ray tomography has provided a non-destructive means for microstructure characterization in both 3D and 4D (i.e., structural evolution over time). Traditional reconstruction algorithms like filtered-back-projection (FBP) method or algebraic reconstruction techniques (ART) require huge number of tomographic projections and segmentation process before conducting microstructural quantification. This can be quite time consuming and computationally intensive.

In this thesis, a novel procedure is first presented that allows one to directly extract key structural information in forms of spatial correlation functions from limited x-ray tomography data. The key component of the procedure is the computation of a “probability map”, which provides the probability of an arbitrary point in the material system belonging to specific phase. The correlation functions of interest are then readily computed from the probability map. Using effective medium theory, accurate predictions of physical properties (e.g., elastic moduli) can be obtained.

Secondly, a stochastic optimization procedure that enables one to accurately reconstruct material microstructure from a small number of x-ray tomographic projections (e.g., 20 - 40) is presented. Moreover, a stochastic procedure for multi-modal data fusion is proposed, where both X-ray projections and correlation functions computed from limited 2D optical images are fused to accurately reconstruct complex heterogeneous materials in 3D. This multi-modal reconstruction algorithm is proved to be able to integrate the complementary data to perform an excellent optimization procedure, which indicates its high efficiency in using limited structural information.

Finally, the accuracy of the stochastic reconstruction procedure using limited X-ray projection data is ascertained by analyzing the microstructural degeneracy and the roughness of energy landscape associated with different number of projections. Ground-state degeneracy of a microstructure is found to decrease with increasing number of projections, which indicates a higher probability that the reconstructed configurations match the actual microstructure. The roughness of energy landscape can also provide information about the complexity and convergence behavior of the reconstruction for given microstructures and projection number.

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Created

Date Created
  • 2017

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Reduced order modeling with variable spatial fidelity for the linear and nonlinear dynamics of multi-bay structures

Description

This investigation develops small-size reduced order models (ROMs) that provide an accurate prediction of the response of only part of a structure, referred to as component-centric ROMs. Four strategies to

This investigation develops small-size reduced order models (ROMs) that provide an accurate prediction of the response of only part of a structure, referred to as component-centric ROMs. Four strategies to construct such ROMs are presented, the first two of which are based on the Craig-Bampton Method and start with a set of modes for the component of interest (the β component). The response in the rest of the structure (the α component) induced by these modes is then determined and optimally represented by applying a Proper Orthogonal Decomposition strategy using Singular Value Decomposition. These first two methods are effectively basis reductions techniques of the CB basis. An approach based on the “Global - Local” Method generates the “global” modes by “averaging” the mass property over α and β comp., respectively (to extract a “coarse” model of α and β) and the “local” modes orthogonal to the “global” modes to add back necessary “information” for β. The last approach adopts as basis for the entire structure its linear modes which are dominant in the β component response. Then, the contributions of other modes in this part of the structure are approximated in terms of those of the dominant modes with close natural frequencies and similar mode shapes in the β component. In this manner, the non-dominant modal contributions are “lumped” onto the dominant ones, to reduce the number of modes for a prescribed accuracy. The four approaches are critically assessed on the structural finite element model of a 9-bay panel with the modal lumping-based method leading to the smallest sized ROMs. Therefore, it is extended to the nonlinear geometric situation and first recast as a rotation of the modal basis to achieve unobservable modes. In the linear case, these modes completely disappear from the formulation owing to orthogonality. In the nonlinear case, however, the generalized coordinates of these modes are still present in the nonlinear terms of the observable modes. A closure-type algorithm is then proposed to eliminate the unobserved generalized coordinates. This approach, its accuracy and computational savings, was demonstrated on a simple beam model and the 9-bay panel model.

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Agent

Created

Date Created
  • 2017