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- All Subjects: Mechanical Engineering
- All Subjects: robotics
- Creators: Mignolet, Marc
Description
This thesis focuses on the continued extension, validation, and application of combined thermal-structural reduced order models for nonlinear geometric problems. The first part of the thesis focuses on the determination of the temperature distribution and structural response induced by an oscillating flux on the top surface of a flat panel. This flux is introduced here as a simplified representation of the thermal effects of an oscillating shock on a panel of a supersonic/hypersonic vehicle. Accordingly, a random acoustic excitation is also considered to act on the panel and the level of the thermo-acoustic excitation is assumed to be large enough to induce a nonlinear geometric response of the panel. Both temperature distribution and structural response are determined using recently proposed reduced order models and a complete one way, thermal-structural, coupling is enforced. A steady-state analysis of the thermal problem is first carried out that is then utilized in the structural reduced order model governing equations with and without the acoustic excitation. A detailed validation of the reduced order models is carried out by comparison with a few full finite element (Nastran) computations. The computational expedience of the reduced order models allows a detailed parametric study of the response as a function of the frequency of the oscillating flux. The nature of the corresponding structural ROM equations is seen to be of a Mathieu-type with Duffing nonlinearity (originating from the nonlinear geometric effects) with external harmonic excitation (associated with the thermal moments terms on the panel). A dominant resonance is observed and explained. The second part of the thesis is focused on extending the formulation of the combined thermal-structural reduced order modeling method to include temperature dependent structural properties, more specifically of the elasticity tensor and the coefficient of thermal expansion. These properties were assumed to vary linearly with local temperature and it was found that the linear stiffness coefficients and the "thermal moment" terms then are cubic functions of the temperature generalized coordinates while the quadratic and cubic stiffness coefficients were only linear functions of these coordinates. A first validation of this reduced order modeling strategy was successfully carried out.
ContributorsMatney, Andrew (Author) / Mignolet, Marc (Thesis advisor) / Jiang, Hanqing (Committee member) / Spottswood, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
As robots are increasingly migrating out of factories and research laboratories and into our everyday lives, they should move and act in environments designed for humans. For this reason, the need of anthropomorphic movements is of utmost importance. The objective of this thesis is to solve the inverse kinematics problem of redundant robot arms that results to anthropomorphic configurations. The swivel angle of the elbow was used as a human arm motion parameter for the robot arm to mimic. The swivel angle is defined as the rotation angle of the plane defined by the upper and lower arm around a virtual axis that connects the shoulder and wrist joints. Using kinematic data recorded from human subjects during every-day life tasks, the linear sensorimotor transformation model was validated and used to estimate the swivel angle, given the desired end-effector position. Defining the desired swivel angle simplifies the kinematic redundancy of the robot arm. The proposed method was tested with an anthropomorphic redundant robot arm and the computed motion profiles were compared to the ones of the human subjects. This thesis shows that the method computes anthropomorphic configurations for the robot arm, even if the robot arm has different link lengths than the human arm and starts its motion at random configurations.
ContributorsWang, Yuting (Author) / Artemiadis, Panagiotis (Thesis advisor) / Mignolet, Marc (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
Description
Shock loading is a complex phenomenon that can lead to failure mechanisms such as strain localization, void nucleation and growth, and eventually spall fracture. Studying incipient stages of spall damage is of paramount importance to accurately determine initiation sites in the material microstructure where damage will nucleate and grow and to formulate continuum models that account for the variability of the damage process due to microstructural heterogeneity. The length scale of damage with respect to that of the surrounding microstructure has proven to be a key aspect in determining sites of failure initiation. Correlations have been found between the damage sites and the surrounding microstructure to determine the preferred sites of spall damage, since it tends to localize at and around the regions of intrinsic defects such as grain boundaries and triple points. However, considerable amount of work still has to be done in this regard to determine the physics driving the damage at these intrinsic weak sites in the microstructure. The main focus of this research work is to understand the physical mechanisms behind the damage localization at these preferred sites. A crystal plasticity constitutive model is implemented with different damage criteria to study the effects of stress concentration and strain localization at the grain boundaries. A cohesive zone modeling technique is used to include the intrinsic strength of the grain boundaries in the simulations. The constitutive model is verified using single elements tests, calibrated using single crystal impact experiments and validated using bicrystal and multicrystal impact experiments. The results indicate that strain localization is the predominant driving force for damage initiation and evolution. The microstructural effects on theses damage sites are studied to attribute the extent of damage to microstructural features such as grain orientation, misorientation, Taylor factor and the grain boundary planes. The finite element simulations show good correlation with the experimental results and can be used as the preliminary step in developing accurate probabilistic models for damage nucleation.
ContributorsKrishnan, Kapil (Author) / Peralta, Pedro (Thesis advisor) / Mignolet, Marc (Committee member) / Sieradzki, Karl (Committee member) / Jiang, Hanqing (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation presents methods for addressing research problems that currently can only adequately be solved using Quality Reliability Engineering (QRE) approaches especially accelerated life testing (ALT) of electronic printed wiring boards with applications to avionics circuit boards. The methods presented in this research are generally applicable to circuit boards, but the data generated and their analysis is for high performance avionics. Avionics equipment typically requires 20 years expected life by aircraft equipment manufacturers and therefore ALT is the only practical way of performing life test estimates. Both thermal and vibration ALT induced failure are performed and analyzed to resolve industry questions relating to the introduction of lead-free solder product and processes into high reliability avionics. In chapter 2, thermal ALT using an industry standard failure machine implementing Interconnect Stress Test (IST) that simulates circuit board life data is compared to real production failure data by likelihood ratio tests to arrive at a mechanical theory. This mechanical theory results in a statistically equivalent energy bound such that failure distributions below a specific energy level are considered to be from the same distribution thus allowing testers to quantify parameter setting in IST prior to life testing. In chapter 3, vibration ALT comparing tin-lead and lead-free circuit board solder designs involves the use of the likelihood ratio (LR) test to assess both complete failure data and S-N curves to present methods for analyzing data. Failure data is analyzed using Regression and two-way analysis of variance (ANOVA) and reconciled with the LR test results that indicating that a costly aging pre-process may be eliminated in certain cases. In chapter 4, vibration ALT for side-by-side tin-lead and lead-free solder black box designs are life tested. Commercial models from strain data do not exist at the low levels associated with life testing and need to be developed because testing performed and presented here indicate that both tin-lead and lead-free solders are similar. In addition, earlier failures due to vibration like connector failure modes will occur before solder interconnect failures.
ContributorsJuarez, Joseph Moses (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie M. (Thesis advisor) / Gel, Esma (Committee member) / Mignolet, Marc (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2012
Description
Ingestion of high temperature mainstream gas into the rotor-stator cavities of a gas turbine is one of the major problems faced by the turbine designers. The ingested gas heats up rotor disks and induces higher thermal stresses on them, giving rise to durability concern. Ingestion is usually reduced by installing seals on the rotor and stator rims and by purging the disk cavity by secondary air bled from the compressor discharge. The geometry of the rim seals and the secondary air flow rate, together, influence the amount of gas that gets ingested into the cavities. Since the amount of secondary air bled off has a negative effect on the gas turbine thermal efficiency, one goal is to use the least possible amount of secondary air. This requires a good understanding of the flow and ingestion fields within a disk cavity. In the present study, the mainstream gas ingestion phenomenon has been experimentally studied in a model single-stage axial flow gas turbine. The turbine stage featured vanes and blades, and rim seals on both the rotor and stator. Additionally, the disk cavity contained a labyrinth seal radially inboard which effectively divided the cavity into a rim cavity and an inner cavity. Time-average static pressure measurements were obtained at various radial positions within the disk cavity, and in the mainstream gas path at three axial locations at the outer shroud spread circumferentially over two vane pitches. The time-average static pressure in the main gas path exhibited a periodic asymmetry following the vane pitch whose amplitude diminished with increasing distance from the vane trailing edge. The static pressure distribution increased with the secondary air flow rate within the inner cavity but was found to be almost independent of it in the rim cavity. Tracer gas (CO2) concentration measurements were conducted to determine the sealing effectiveness of the rim seals against main gas ingestion. For the rim cavity, the sealing effectiveness increased with the secondary air flow rate. Within the inner cavity however, this trend reversed -this may have been due to the presence of rotating low-pressure flow structures inboard of the labyrinth seal.
ContributorsThiagarajan, Jayanth kumar (Author) / Roy, Ramendra P (Thesis advisor) / Lee, Taewoo (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2013
Description
The technology and science capabilities of SmallSats continue to grow with the increase of capabilities in commercial off the shelf components. However, the maturation of SmallSat hardware has also led to an increase in component power consumption, this poses an issue with using traditional passive thermal management systems (radiators, thermal straps, etc.) to regulate high-power components. High power output becomes limited in order to maintain components within their allowable temperature ranges. The aim of this study is to explore new methods of using additive manufacturing to enable the usage of heat pipe structures on SmallSat platforms up to 3U’s in size. This analysis shows that these novel structures can increase the capabilities of SmallSat platforms by allowing for larger in-use heat loads from a nominal power density of 4.7 x 10^3 W/m3 to a higher 1.0 x 10^4 W/m3 , an order of magnitude increase. In addition, the mechanical properties of the SmallSat structure are also explored to characterize effects to the mechanical integrity of the spacecraft. The results show that the advent of heat pipe integration to the structures of SmallSats will lead to an increase in thermal management capabilities compared to the current state-of-the-art systems, while not reducing the structural integrity of the spacecraft. In turn, this will lead to larger science and technology capabilities for a field that is growing in both the education and private sectors.
ContributorsAcuna, Antonio (Author) / Das, Jnaneshwar (Thesis advisor) / Phelan, Patrick (Thesis advisor) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2022
Description
Aromatic polymers, with benzene-like rings in their main chains, include materials such as polyurea, an amorphous elastomer capable of dissipating large amounts of energy under dynamic loading, which makes it a promising coating for defensive systems. Although computational research exists that investigates the atomic-level response of polyurea and other amorphous aromatic polymers to extreme conditions, there is little experimental work to validate these models 1) at the atomic-scale and 2) under high pressures characteristic of extreme dynamic loading. Understanding structure-property relationships at the atomic-level is important for polymers, considering many of them undergo pressure and temperature-induced structural transformations, which must be understood to formulate accurate predictive models. This work aims to gain a deeper understanding of the high-pressure structural response of aromatic polymers at the atomic-level, with emphasis into the mechanisms associated with high-pressure transformations. Hence, atomic-level structural data at high pressures was obtained in situ via multiangle energy dispersive X-ray diffraction (EDXD) experiments at the Advanced Photon Source (APS) for polyurea and another amorphous aromatic polymer, polysulfone, chosen as a reference due to its relatively simple structure. Pressures up to 6 GPa were applied using a Paris Edinburgh (PE) hydraulic press at room temperature. Select polyurea samples were also heated to 277 °C at 6 GPa. The resulting structure factors and pair distribution functions, along with molecular dynamics simulations of polyurea provided by collaborators, suggest that the structures of both polymers are stable up to 6 GPa, aside from reductions in free-volume between polymer backbones. As higher pressures (≲ 32 GPa) were applied using diamond anvils in combination with the PE press, indications of structural transformations were observed in both polymers that appear similar in nature to the sp2-sp3 hybridization in compressed carbon. The transformation occurs gradually up to at least ~ 26 GPa in PSF, while it does not progress past ~ 15 GPa in polyurea. The changes are largely reversible, especially in polysulfone, consistent with pressure-driven, reversible graphite-diamond transformations in the absence of applied temperature. These results constitute some of the first in situ observations of the mechanisms that drive pressure-induced structural transformations in aromatic polymers.
ContributorsEastmond, Tyler (Author) / Peralta, Pedro (Thesis advisor) / Hoover, Christian (Committee member) / Hrubiak, Rostislav (Committee member) / Mignolet, Marc (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
Ultra-fast 2D/3D material microstructure reconstruction and quantitative structure-property mapping are crucial components of integrated computational material engineering (ICME). It is particularly challenging for modeling random heterogeneous materials such as alloys, composites, polymers, porous media, and granular matters, which exhibit strong randomness and variations of their material properties due to the hierarchical uncertainties associated with their complex microstructure at different length scales. Such uncertainties also exist in disordered hyperuniform systems that are statistically isotropic and possess no Bragg peaks like liquids and glasses, yet they suppress large-scale density fluctuations in a similar manner as in perfect crystals. The unique hyperuniform long-range order in these systems endow them with nearly optimal transport, electronic and mechanical properties. The concept of hyperuniformity was originally introduced for many-particle systems and has subsequently been generalized to heterogeneous materials such as porous media, composites, polymers, and biological tissues for unconventional property discovery. An explicit mixture random field (MRF) model is proposed to characterize and reconstruct multi-phase stochastic material property and microstructure simultaneously, where no additional tuning step nor iteration is needed compared with other stochastic optimization approaches such as the simulated annealing. The proposed method is shown to have ultra-high computational efficiency and only requires minimal imaging and property input data. Considering microscale uncertainties, the material reliability will face the challenge of high dimensionality. To deal with the so-called “curse of dimensionality”, efficient material reliability analysis methods are developed. Then, the explicit hierarchical uncertainty quantification model and efficient material reliability solvers are applied to reliability-based topology optimization to pursue the lightweight under reliability constraint defined based on structural mechanical responses. Efficient and accurate methods for high-resolution microstructure and hyperuniform microstructure reconstruction, high-dimensional material reliability analysis, and reliability-based topology optimization are developed. The proposed framework can be readily incorporated into ICME for probabilistic analysis, discovery of novel disordered hyperuniform materials, material design and optimization.
ContributorsGao, Yi (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Ren, Yi (Committee member) / Pan, Rong (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2021
Description
Uncertainty quantification is critical for engineering design and analysis. Determining appropriate ways of dealing with uncertainties has been a constant challenge in engineering. Statistical methods provide a powerful aid to describe and understand uncertainties. This work focuses on applying Bayesian methods and machine learning in uncertainty quantification and prognostics among all the statistical methods. This study focuses on the mechanical properties of materials, both static and fatigue, the main engineering field on which this study focuses. This work can be summarized in the following items: First, maintaining the safety of vintage pipelines requires accurately estimating the strength. The objective is to predict the reliability-based strength using nondestructive multimodality surface information. Bayesian model averaging (BMA) is implemented for fusing multimodality non-destructive testing results for gas pipeline strength estimation. Several incremental improvements are proposed in the algorithm implementation. Second, the objective is to develop a statistical uncertainty quantification method for fatigue stress-life (S-N) curves with sparse data.Hierarchical Bayesian data augmentation (HBDA) is proposed to integrate hierarchical Bayesian modeling (HBM) and Bayesian data augmentation (BDA) to deal with sparse data problems for fatigue S-N curves. The third objective is to develop a physics-guided machine learning model to overcome limitations in parametric regression models and classical machine learning models for fatigue data analysis. A Probabilistic Physics-guided Neural Network (PPgNN) is proposed for probabilistic fatigue S-N curve estimation. This model is further developed for missing data and arbitrary output distribution problems. Fourth, multi-fidelity modeling combines the advantages of low- and high-fidelity models to achieve a required accuracy at a reasonable computation cost. The fourth objective is to develop a neural network approach for multi-fidelity modeling by learning the correlation between low- and high-fidelity models. Finally, conclusions are drawn, and future work is outlined based on the current study.
ContributorsChen, Jie (Author) / Liu, Yongming (Thesis advisor) / Chattopadhyay, Aditi (Committee member) / Mignolet, Marc (Committee member) / Ren, Yi (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2022
Description
A finite element model that replicates the experimental procedure to test and certify soft body armor has been developed. The model consists of four components: bullet, clay, straps, and shoot pack with different material models that closely capture the behavior of each component when subjected to ballistic impact loading. To test the fidelity of the model, three metrics are used - back face signature (BFS), the number of penetrated shoot pack layers, and the number of damaged shoot pack layers on the clay side of the shoot pack assembly. In addition, the shape and size of the bullet, and the shape and size of the hole in the shoot pack are also considered as qualitative measures to assess the developed model. The focus of this research work is to improve the shoot pack material model, while the constitutive model for the components is taken from earlier work done at ASU. Results show considerable improvement in the model in terms of capturing the number of penetrated layers, the size and shape of the holes in the shoot pack layer, and the predicted BFS. The developed finite element models can be used to predict the behavior of soft body armor for different initial conditions, shoot pack materials, and arrangement of the layers.
ContributorsPechetti, Sateesh (Author) / Rajan, Subramaniam (Thesis advisor) / Mignolet, Marc (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2024