Browsing by Author "Andre Mazzoleni, Committee Member"

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Design, Fabrication and Experimental Characterization of PZT Membranes for Passive Low Frequency Vibration Sensing
(2008-12-16) Zohni, Omar Shariff; Andre Mazzoleni, Committee Member; Richard Siergiej, Committee Member; Richard Keltie, Committee Member; Gregory Buckner, Committee Chair; Yong Zhu, Committee Member
Low frequency vibration sensing is being used increasingly to monitor the health of machinery and civil structures, enabling â€œneed-basedâ€ maintenance scheduling and reduced operating costs. Passive sensors are of particular interest because they donâ€™t require input energy to monitor vibration. Modern vibration sensors are often micro electromechanical systems (MEMS), and are usually very basic in design consisting of a cantilevered beam with some type of deflection sensing circuit. Under the influence of acceleration the beam deflects from its nominal position and its deflection is measured using optical, capacitive or piezoelectric techniques. MEMS sensors tend to exhibit very large stiffness to mass ratios, making them best suited to high frequency vibration sensing. Sensors utilizing the piezoelectric effect can achieve direct energy conversion from the mechanical domain (strain) to the electrical domain (charge) via piezoelectric coupling coefficients. To maximize the electrical output, lead zirconate titanate (PZT) is an excellent piezoelectric material due to its high coupling coefficients. However, the introduction of PZT into standard MEMS processes is problematic because lead is considered a contaminant in most silicon based fabrication facilities. Additional complications with stresses and delamination in thin film stacks have hindered the development of robust fabrication processes for these devices. This dissertation investigates candidate MEMS sensor geometries and fabrication processes for passive low frequency vibration sensing. The addition of silicon nitride (Si3N4) thin films into sol-gel deposited PZT stacks is studied, and the effects of various adhesion layers on delamination and ferroelectric characteristics are quantified. A fabrication process is developed allowing for both front and back side contact for electrical measurements. The effects of thin film stresses on the frequency response of PZT membranes are investigated using experimental, analytical, and computational techniques. Results indicate that thin film stresses in silicon dioxide (SiO2) and Si3N4 can shift the natural frequencies of sensor membranes by as much as 20%. Optimization of sensor membranes is conducted using available numerical methods, particularly finite element analysis (FEA). Coupled electromechanical measurements of fabricated membranes are conducted and experimental results are compared with numerical and analytical solutions. The research outlined in this dissertation represents the first known investigation of passive MEMS vibration sensors specifically targeting such a low frequency range. Also, the integration of PZT into a standard MEMS process requiring low pressure chemical vapor deposition (LPCVD) Si3N4 has not been reported previously. A robust integrated PZT fabrication process is developed which can be used for future work in this field. This process includes a reliable adhesion layer which can be used when deep wet etching of silicon is required. Recommendations for future work and for incorporating these results into packaged sensors are presented.
Failure Bounding and Sensitivity Analysis Applied to Monte Carlo Entry, Descent, and Landing Simulations
(2009-12-04) Gaebler, John Alexander; Andre Mazzoleni, Committee Member; Fred DeJarnette, Committee Member; Robert Tolson, Committee Chair
In the study of entry, descent, and landing (EDL) scenarios, Monte Carlo sampling methods are often employed to study uncertainties in the designed trajectory. The large number of uncertain inputs and outputs, coupled with complicated non-linear models, can make interpretation of the results difficult. Often it is desirable to reduce the uncertainty of an output or to understand why a failure occurred. Methods are sought that can provide this information, thereby increasing the value of performing Monte Carlo analyses. The specific insights desired are the statistics of the inputs causing failure, the sensitivity of failed cases to input statistics, and the sensitivities of output statistics to input statistics. Three methods that provide statistical insights were identified and applied to both a simple projectile trajectory simulation and an EDL simulation. The projectile trajectory was included to help understand and describe the methods. To test the merits of the methods a two dimensional ballistic EDL simulation was developed. The EDL simulation included a temperature varying atmosphere model, a rotating atmosphere with wind, and correlated entry states. This simulation had seventeen statistical inputs composed of initial states, atmospheric parameters, and vehicle properties. The first technique studied was failure domain bounding. If during an analysis of a large sample set a case fails, i.e. by consuming all the propellant before engine shut down, it is imperative to understand the cause. This method identifies an upper bound on the failure region by utilizing an optimizer to locate the most probable failed case in the design space. With this knowledge, randomly generated cases within the complement safe region can be assumed successful, thus reducing the number of cases that need to be simulated when studying failure. This allows the generation of more failed cases for study which increases the accuracy of the failure probability approximation with less computational expense. Next a global variance-based sensitivity analysis developed by I.M. Sobol was tested. The sensitivities provided are based on how the total variance of the output can be segmented into components due to individual or combinations of inputs. This knowledge allows an engineer to identify which input will have the greatest impact on reducing the variance, or uncertainty, on an output. This method has the additional benefit of identifying which inputs are interacting, or coupling. Finally a method that provides local probabilistic sensitivities was studied. These are sensitivities of an output mean or variance to an input mean or variance. The information provided is the same as approximating the partial derivative of the output statistics with respect to the input statistics by finite differencing. Instead LeibnizÃ¢â‚¬â„¢s rule is introduced to approximate certain partial derivatives with the benefit of requiring fewer simulations than finite differencing. These benefits are realized when calculating the sensitivities to inputs with infinite bounds on their probability density function. The advantages and disadvantages of each method are discussed in terms of the insights gained versus the computational cost. Models with fewer input dimensions and small probabilities of failure can benefit from application of the failure domain bounding method. Variance-based sensitivities give many statistical insights, but potentially at high computational cost. Finally if the inputs are uncorrelated with probability density functions having infinite bounds, the probabilistic sensitivity analysis gives statistical insights without requiring many simulations.
Investigating the Significance of "One-to-many" Mappings in Multiobjective Optimization.
(2010-11-03) Simov, Peter; Scott Ferguson, Committee Chair; Robert Nagel, Committee Chair; Andre Mazzoleni, Committee Member; Gregory Buckner, Committee Member
LIDAR-Aided Inertial Navigation over Rough Terrain.
(2011-01-28) Busnardo, David; Robert Tolson, Committee Chair; Fred DeJarnette, Committee Member; Andre Mazzoleni, Committee Member
Lidar-Aided Inertial Navigation with Extended Kalman Filtering for Pinpoint Landing
(2009-07-23) Aitken, Matthew Lawrence; Andre Mazzoleni, Committee Member; Robert Tolson, Committee Chair; Fred DeJarnette, Committee Member
In support of NASAÃ¢â‚¬â„¢s Autonomous Landing and Hazard Avoidance Technology project, an extended Kalman filter (EKF) routine has been developed for estimating the position, velocity, and attitude of a spacecraft during the landing phase of a planetary mission. The EKF is a recursive algorithm for obtaining the minimum variance estimate of a nonlinear dynamic process from a sequence of noisy observations. The proposed filter combines measurements of acceleration and angular velocity from an inertial measurement unit with range and range-rate observations from an onboard light detection and ranging (LIDAR) system. These high-precision LIDAR measurements of distance to the ground and approach velocity will enable both robotic and manned vehicles to land safely and precisely at scientifically interesting sites. The robustness and accuracy of the Kalman filter were first established using a simplified simulation of the final translation and touchdown phase of the Apollo lunar landings. In addition, experimental results from a helicopter flight test performed at NASA Dryden in August 2008 demonstrate the merit in employing LIDAR for pinpoint landing in future space missions.
Methods for the Determination of Aerodynamic Parameters and Trajectory Reconstruction of the Orion Command Module from Scale Model Aeroballistic Flight Data
(2008-12-05) Sebastian, Thomas Jr.; Fred DeJarnette, Committee Member; Robert Tolson, Committee Chair; Andre Mazzoleni, Committee Member
Determination of aerodynamic coeffcients and stability derivatives is necessary in defning a model of the Orion CEV dynamics. This involves reducing experimental data, which can include acceleration, angular rate, or orientation data. This sort of extraction of dynamics from experimental data is often performed on data gathered from experiments conducted on uninstrumented models at indoor ballistics ranges. The US Army Research Laboratory (ARL) has developed a high-g survivable stand-alone instrumentation package that can transmit in-flight measurements of acceleration, angular rate, and local magnetic field. This telemetry module (TM) was installed in a scale model of the Orion CEV, which was fired from a 175mm cannon at the ARL range. The instrumentation package was upgraded to include pressure transducers to measure forebody pressures. A minimum variance with a priori method was formulated to solve for both the "local" flight parameters of Mach number, angle of attack, and sideslip angle at each timestamp and the "global" parameters of scale factor and bias for each pressure transducer. Results using both simulated and experimental data indicates that these parameters may be estimated and used to compute stability coeffcients. Low pressure differentials between symmetrically-opposed pressure transducers, however, increased uncertainty in the parameter estimates. Validation of this method of data generation and analysis supports a low-cost method of vehicle testing.