Matching Items (11)
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- All Subjects: Aerospace Engineering
- All Subjects: Nanoparticles
- Creators: Dai, Lenore
Description
Although high performance, light-weight composites are increasingly being used in applications ranging from aircraft, rotorcraft, weapon systems and ground vehicles, the assurance of structural reliability remains a critical issue. In composites, damage is absorbed through various fracture processes, including fiber failure, matrix cracking and delamination. An important element in achieving reliable composite systems is a strong capability of assessing and inspecting physical damage of critical structural components. Installation of a robust Structural Health Monitoring (SHM) system would be very valuable in detecting the onset of composite failure. A number of major issues still require serious attention in connection with the research and development aspects of sensor-integrated reliable SHM systems for composite structures. In particular, the sensitivity of currently available sensor systems does not allow detection of micro level damage; this limits the capability of data driven SHM systems. As a fundamental layer in SHM, modeling can provide in-depth information on material and structural behavior for sensing and detection, as well as data for learning algorithms. This dissertation focusses on the development of a multiscale analysis framework, which is used to detect various forms of damage in complex composite structures. A generalized method of cells based micromechanics analysis, as implemented in NASA's MAC/GMC code, is used for the micro-level analysis. First, a baseline study of MAC/GMC is performed to determine the governing failure theories that best capture the damage progression. The deficiencies associated with various layups and loading conditions are addressed. In most micromechanics analysis, a representative unit cell (RUC) with a common fiber packing arrangement is used. The effect of variation in this arrangement within the RUC has been studied and results indicate this variation influences the macro-scale effective material properties and failure stresses. The developed model has been used to simulate impact damage in a composite beam and an airfoil structure. The model data was verified through active interrogation using piezoelectric sensors. The multiscale model was further extended to develop a coupled damage and wave attenuation model, which was used to study different damage states such as fiber-matrix debonding in composite structures with surface bonded piezoelectric sensors.
ContributorsMoncada, Albert (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Rajadas, John (Committee member) / Yekani Fard, Masoud (Committee member) / Arizona State University (Publisher)
Created2012
Description
This research focuses on the benefits of using nanocomposites in aerospace structural components to prevent or delay the onset of unique composite failure modes, such as delamination. Analytical, numerical, and experimental analyses were conducted to provide a comprehensive understanding of how carbon nanotubes (CNTs) can provide additional structural integrity when they are used in specific hot spots within a structure. A multiscale approach was implemented to determine the mechanical and thermal properties of the nanocomposites, which were used in detailed finite element models (FEMs) to analyze interlaminar failures in T and Hat section stringers. The delamination that first occurs between the tow filler and the bondline between the stringer and skin was of particular interest. Both locations are considered to be hot spots in such structural components, and failures tend to initiate from these areas. In this research, nanocomposite use was investigated as an alternative to traditional methods of suppressing delamination. The stringer was analyzed under different loading conditions and assuming different structural defects. Initial damage, defined as the first drop in the load displacement curve was considered to be a useful variable to compare the different behaviors in this study and was detected via the virtual crack closure technique (VCCT) implemented in the FE analysis.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
Experiments were conducted to test T section skin/stringer specimens under pull-off loading, replicating those used in composite panels as stiffeners. Two types of designs were considered: one using pure epoxy to fill the tow region and another that used nanocomposite with 5 wt. % CNTs. The response variable in the tests was the initial damage. Detailed analyses were conducted using FEMs to correlate with the experimental data. The correlation between both the experiment and model was satisfactory. Finally, the effects of thermal cure and temperature variation on nanocomposite structure behavior were studied, and both variables were determined to influence the nanocomposite structure performance.
ContributorsHasan, Zeaid (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2014
Description
A method of determining nanoparticle temperature through fluorescence intensity levels is described. Intracellular processes are often tracked through the use of fluorescence tagging, and ideal temperatures for many of these processes are unknown. Through the use of fluorescence-based thermometry, cellular processes such as intracellular enzyme movement can be studied and their respective temperatures established simultaneously. Polystyrene and silica nanoparticles are synthesized with a variety of temperature-sensitive dyes such as BODIPY, rose Bengal, Rhodamine dyes 6G, 700, and 800, and Nile Blue A and Nile Red. Photographs are taken with a QImaging QM1 Questar EXi Retiga camera while particles are heated from 25 to 70 C and excited at 532 nm with a Coherent DPSS-532 laser. Photographs are converted to intensity images in MATLAB and analyzed for fluorescence intensity, and plots are generated in MATLAB to describe each dye's intensity vs temperature. Regression curves are created to describe change in fluorescence intensity over temperature. Dyes are compared as nanoparticle core material is varied. Large particles are also created to match the camera's optical resolution capabilities, and it is established that intensity values increase proportionally with nanoparticle size. Nile Red yielded the closest-fit model, with R2 values greater than 0.99 for a second-order polynomial fit. By contrast, Rhodamine 6G only yielded an R2 value of 0.88 for a third-order polynomial fit, making it the least reliable dye for temperature measurements using the polynomial model. Of particular interest in this work is Nile Blue A, whose fluorescence-temperature curve yielded a much different shape from the other dyes. It is recommended that future work describe a broader range of dyes and nanoparticle sizes, and use multiple excitation wavelengths to better quantify each dye's quantum efficiency. Further research into the effects of nanoparticle size on fluorescence intensity levels should be considered as the particles used here greatly exceed 2 ìm. In addition, Nile Blue A should be further investigated as to why its fluorescence-temperature curve did not take on a characteristic shape for a temperature-sensitive dye in these experiments.
ContributorsTomforde, Christine (Author) / Phelan, Patrick (Thesis advisor) / Dai, Lenore (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2011
Description
Plasmon resonance in nanoscale metallic structures has shown its ability to concentrate electromagnetic energy into sub-wavelength volumes. Metal nanostructures exhibit a high extinction coefficient in the visible and near infrared spectrum due to their large absorption and scattering cross sections corresponding to their surface plasmon resonance. Hence, they can serve as an attractive candidate for solar energy conversion. Recent papers have showed that dielectric core/metallic shell nanoparticles yielded a plasmon resonance wavelength tunable from visible to infrared by changing the ratio of core radius to the total radius. Therefore it is interesting to develop a dispersion of core-shell multifunctional nanoparticles capable of dynamically changing their volume ratio and thus their spectral radiative properties. Nanoparticle suspensions (nanofluids) are known to offer a variety of benefits for thermal transport and energy conversion. Nanofluids have been proven to increase the efficiency of the photo-thermal energy conversion process in direct solar absorption collectors (DAC). Combining these two cutting-edge technologies enables the use of core-shell nanoparticles to control the spectral and radiative properties of plasmonic nanofluids in order to efficiently harvest and convert solar energy. Plasmonic nanofluids that have strong energy concentrating capacity and spectral selectivity can be used in many high-temperature energy systems where radiative heat transport is essential. In this thesis，the surface plasmon resonance effect and the wavelength tuning ranges for different metallic shell nanoparticles are investigated, the solar-weighted efficiencies of corresponding core-shell nanoparticle suspensions are explored, and a quantitative study of core-shell nanoparticle suspensions in a DAC system is provided. Using core-shell nanoparticle dispersions, it is possible to create efficient spectral solar absorption fluids and design materials for applications which require variable spectral absorption or scattering.
ContributorsLv, Wei (Author) / Phelan, Patrick E (Thesis advisor) / Dai, Lenore (Committee member) / Prasher, Ravi (Committee member) / Arizona State University (Publisher)
Created2012
Description
Current economic conditions necessitate the extension of service lives for a variety of aerospace systems. As a result, there is an increased need for structural health management (SHM) systems to increase safety, extend life, reduce maintenance costs, and minimize downtime, lowering life cycle costs for these aging systems. The implementation of such a system requires a collaborative research effort in a variety of areas such as novel sensing techniques, robust algorithms for damage interrogation, high fidelity probabilistic progressive damage models, and hybrid residual life estimation models. This dissertation focuses on the sensing and damage estimation aspects of this multidisciplinary topic for application in metallic and composite material systems. The primary means of interrogating a structure in this work is through the use of Lamb wave propagation which works well for the thin structures used in aerospace applications. Piezoelectric transducers (PZTs) were selected for this application since they can be used as both sensors and actuators of guided waves. Placement of these transducers is an important issue in wave based approaches as Lamb waves are sensitive to changes in material properties, geometry, and boundary conditions which may obscure the presence of damage if they are not taken into account during sensor placement. The placement scheme proposed in this dissertation arranges piezoelectric transducers in a pitch-catch mode so the entire structure can be covered using a minimum number of sensors. The stress distribution of the structure is also considered so PZTs are placed in regions where they do not fail before the host structure. In order to process the data from these transducers, advanced signal processing techniques are employed to detect the presence of damage in complex structures. To provide a better estimate of the damage for accurate life estimation, machine learning techniques are used to classify the type of damage in the structure. A data structure analysis approach is used to reduce the amount of data collected and increase computational efficiency. In the case of low velocity impact damage, fiber Bragg grating (FBG) sensors were used with a nonlinear regression tool to reconstruct the loading at the impact site.
ContributorsCoelho, Clyde (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Wu, Tong (Committee member) / Das, Santanu (Committee member) / Rajadas, John (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2011
Description
Materials with unprecedented properties are necessary to make dramatic changes in current and future aerospace platforms. Hybrid materials and composites are increasingly being used in aircraft and spacecraft frames; however, future platforms will require an optimal design of novel materials that enable operation in a variety of environments and produce known/predicted damage mechanisms. Nanocomposites and nanoengineered composites with CNTs have the potential to make significant improvements in strength, stiffness, fracture toughness, flame retardancy and resistance to corrosion. Therefore, these materials have generated tremendous scientific and technical interest over the past decade and various architectures are being explored for applications to light-weight airframe structures. However, the success of such materials with significantly improved performance metrics requires careful control of the parameters during synthesis and processing. Their implementation is also limited due to the lack of complete understanding of the effects the nanoparticles impart to the bulk properties of composites. It is common for computational methods to be applied to explain phenomena measured or observed experimentally. Frequently, a given phenomenon or material property is only considered to be fully understood when the associated physics has been identified through accompanying calculations or simulations.
The computationally and experimentally integrated research presented in this dissertation provides improved understanding of the mechanical behavior and response including damage and failure in CNT nanocomposites, enhancing confidence in their applications. The computations at the atomistic level helps to understand the underlying mechanochemistry and allow a systematic investigation of the complex CNT architectures and the material performance across a wide range of parameters. Simulation of the bond breakage phenomena and development of the interface to continuum scale damage captures the effects of applied loading and damage precursor and provides insight into the safety of nanoengineered composites under service loads. The validated modeling methodology is expected to be a step in the direction of computationally-assisted design and certification of novel materials, thus liberating the pace of their implementation in future applications.
The computationally and experimentally integrated research presented in this dissertation provides improved understanding of the mechanical behavior and response including damage and failure in CNT nanocomposites, enhancing confidence in their applications. The computations at the atomistic level helps to understand the underlying mechanochemistry and allow a systematic investigation of the complex CNT architectures and the material performance across a wide range of parameters. Simulation of the bond breakage phenomena and development of the interface to continuum scale damage captures the effects of applied loading and damage precursor and provides insight into the safety of nanoengineered composites under service loads. The validated modeling methodology is expected to be a step in the direction of computationally-assisted design and certification of novel materials, thus liberating the pace of their implementation in future applications.
ContributorsSubramanian, Nithya (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2018
Description
With the maturity of advanced composites as feasible structural materials for various applications there is a critical need to solve the challenge of designing these material systems for optimal performance. However, determining superior design methods requires a deep understanding of the material-structure properties at various length scales. Due to the length-scale dependent behavior of advanced composites, multiscale modeling techniques may be used to describe the dominant mechanisms of damage and failure in these material systems. With polymer matrix fiber composites and nanocomposites it becomes essential to include even the atomic length scale, where the resin-hardener-nanofiller molecules interact, in the multiscale modeling framework. Additionally, sources of variability are also critical to be included in these models due to the important role of uncertainty in advance composite behavior. Such a methodology should be able to describe length scale dependent mechanisms in a computationally efficient manner for the analysis of practical composite structures.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
In the research presented in this dissertation, a comprehensive nano to macro multiscale framework is developed for the mechanical and multifunctional analysis of advanced composite materials and structures. An atomistically informed statistical multiscale model is developed for linear problems, to estimate and scale elastic properties of carbon fiber reinforced polymer composites (CFRPs) and carbon nanotube (CNT) enhanced CFRPs using information from molecular dynamics simulation of the resin-hardener-nanofiller nanoscale system. For modeling inelastic processes, an atomistically informed coupled damage-plasticity model is developed using the framework of continuum damage mechanics, where fundamental nanoscale covalent bond disassociation information is scaled up as a continuum scale damage identifying parameter. This damage model is coupled with a nanocomposite microstructure generation algorithm to study the sub-microscale damage mechanisms in CNT/CFRP microstructures. It is further integrated in a generalized method of cells (GMC) micromechanics model to create a low-fidelity computationally efficient nonlinear multiscale method with imperfect interfaces between the fiber and matrix, where the interface behavior is adopted from nanoscale MD simulations. This algorithm is used to understand damage mechanisms in adhesively bonded composite joints as a case study for the comprehensive nano to macroscale structural analysis of practical composites structures. At each length scale sources of variability are identified, characterized, and included in the multiscale modeling framework.
ContributorsRai, Ashwin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Jiang, Hanqing (Committee member) / Rajadas, John (Committee member) / Fard, Masoud Yekani (Committee member) / Arizona State University (Publisher)
Created2018
Description
In recent years, a new type of ionic salt based solid propellant, considered inert until the application of an electric current induces an electro-chemical reaction, has been under investigation due to its broad range of possible uses. However, while many electric propellant formulations and applications have been explored over the years, a fundamental understanding of the operational mechanisms of this propellant is necessary in order to move forward with development and implementation of this technology. It has been suggested that the metallic additive included in the formulation studied during this investigation may be playing an additional, currently unknown role in the operation and performance of the propellant. This study was designed to examine variations of an electric propellant formulation with the purpose of investigating propellant bulk volume electrical resistivity in order to attempt to determine information regarding the fundamental science behind the operation of this material. Within a set of fractional factorial experiments, variations of the propellant material made with tungsten, copper, carbon black, and no additive were manufactured using three different particle size ranges and three different volume percentage particle loadings. Each of these formulations (a total of 21 samples and 189 specimens) were tested for quantitative electrical resistivity values at three different pulse generator input voltage values. The data gathered from these experiments suggests that this electric propellant formulation’s resistivity value does change based upon the included additive. The resulting data has also revealed a parabolic response behavior noticeable in the 2D and 3D additive loading percentage versus additive particle size visualizations, the lowest point of which, occurring at an approximately 2.3% additive loading percentage value, could be indicative of the effects of the percolation phenomena on this material. Finally, the investigation results have been loosely correlated to power consumption testing results from previous work that may indicate that it is possible to relate propellant electrical resistivity and operating requirements. Throughout this study, however, it is obvious based on the data gathered that more information is required to be certain of these conclusions and in order to fully understand how this technology can be controlled for future use.
ContributorsBrunacini, Lauren (Author) / Middleton, James (Thesis advisor) / Dai, Lenore (Committee member) / Langhenry, Mark T (Committee member) / Arizona State University (Publisher)
Created2019
Stochastic multiscale modeling and statistical characterization of complex polymer matrix composites
Description
There are many applications for polymer matrix composite materials in a variety of different industries, but designing and modeling with these materials remains a challenge due to the intricate architecture and damage modes. Multiscale modeling techniques of composite structures subjected to complex loadings are needed in order to address the scale-dependent behavior and failure. The rate dependency and nonlinearity of polymer matrix composite materials further complicates the modeling. Additionally, variability in the material constituents plays an important role in the material behavior and damage. The systematic consideration of uncertainties is as important as having the appropriate structural model, especially during model validation where the total error between physical observation and model prediction must be characterized. It is necessary to quantify the effects of uncertainties at every length scale in order to fully understand their impact on the structural response. Material variability may include variations in fiber volume fraction, fiber dimensions, fiber waviness, pure resin pockets, and void distributions. Therefore, a stochastic modeling framework with scale dependent constitutive laws and an appropriate failure theory is required to simulate the behavior and failure of polymer matrix composite structures subjected to complex loadings. Additionally, the variations in environmental conditions for aerospace applications and the effect of these conditions on the polymer matrix composite material need to be considered. The research presented in this dissertation provides the framework for stochastic multiscale modeling of composites and the characterization data needed to determine the effect of different environmental conditions on the material properties. The developed models extend sectional micromechanics techniques by incorporating 3D progressive damage theories and multiscale failure criteria. The mechanical testing of composites under various environmental conditions demonstrates the degrading effect these conditions have on the elastic and failure properties of the material. The methodologies presented in this research represent substantial progress toward understanding the failure and effect of variability for complex polymer matrix composites.
ContributorsJohnston, Joel Philip (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2016
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 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.
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.
ContributorsGao, Wei (Author) / Dai, Lenore (Thesis advisor) / Jiao, Yang (Committee member) / Liu, Yongming (Committee member) / Green, Matthew (Committee member) / Emady, Heather (Committee member) / Arizona State University (Publisher)
Created2017