Defenses

Title: INFLATABLE ACOUSTIC METAMATERIAL

Author: Haafiz Husker

Committee Members:
Dr. Amr Baz (Adviser – Chair)
Dr. Balakumar Balachandran
Dr. Hosam Fathy

Exam Time:  May 20, 2021 (Thursday) at 9:30AM

Abstract: Acoustic metamaterials thus far have been either passive or employed stacking to produce wide range of results. With the advent of advanced additive manufacturing techniques, the ability to create novel metamaterials have increased. Usually these Acoustic Meta Material are passive like in case of Membrane-type and Plate-type metamaterials. They are usually thin membranes or plates consisting of periodic unit cells with added masses. Numerous studies have shown these metamaterials exhibit tunable anti resonances with transmission loss greater than their corresponding mass-law. In these studies, the tunability is usually produces with complex electrical architecture and furthermore, in most of the investigations it is assumed that the unit cell edges of the metamaterial are fixed.

In this study, an innovative method is explored to create an active metamaterial that can be easily tunned. The proposed method distinguishes itself from past contributions by employs a unique unit cell design that is fabricated via advanced additive manufacturing to create a meta-material that exhibits negative Poison’sratio with adjustable unit cell edges for greater transmission loss than its mass-law would otherwise suggest. The membrane like Meta-material is tuned by inflating itself with pressurized air. The pressurization leads to large non-linear deformation and geometric stiffing in the membrane apart from adding mass by expanding its elastic unit cell edges. Which is exploited to adjust the eigen-modes and sound loss of the structure.

The veracity of this proposed design is then investigated analytically and experimentally. The metamaterial is manufactured using elastic material called Agilus- 30 via Multi-jet Manufacturing and is tested in an impedance tube to see its trans- mission loss. Finite elemental analysis is done to reduce the computational effort in creating an analytical model. The finite element analysis is compared with the experimental results to arrive at a consensus. The proposed metamaterial is then tested in real life application by conducting frequency response on a headphone with the IAMM installed to truly understand, the performance of such a setup. The results of these tests indicate the range of performance across low and high frequency as well as the versatility of the metamaterial to be adapted into any size as per the                                               requirement.

Title: Temperature Dependent Characterization of Polymers for Accurate Prediction of Stresses in Electronic Packages

Author: Hyun Seop Lee

Date/Time : May 18, 1~3 pm

Committee members:
Prof. Bongtae Han (Chair)
Prof. Abhijit Dasgupta
Prof. Patrick McCluskey
Prof. Peter Sandborn
Prof. Sung W. Lee (Dean’s representative)

Abstract: Epoxy molding compound (EMC) is a thermosetting polymer filled with inorganic fillers such as fused silica.  EMC has been used extensively as a protection layer in various semiconductor packages.  The warpage and the residual stress of packages are directly related to the thermomechanical properties of EMC.  As the size of semiconductor packages continues to shrink, prediction of the warpage and residual stress becomes increasingly important.  The viscoelastic properties of EMC are the most critical input data required for accurate prediction.  In spite of the considerable effort devoted to warpage prediction, accurate prediction of warpage remains a challenging task.  One of the critical reasons is the inappropriate assumption about the bulk modulus – time and temperature “independent” bulk modulus, which is not valid at high temperatures.  

In this thesis, a novel experimental method, based on an embedded fiber Bragg grating (FBG) sensor, is developed, and implemented to measure a complete set of linear viscoelastic properties of EMC just from a single configuration.  A single cylindrical EMC specimen is fabricated, and it is subjected to constant uniaxial compression and hydrostatic pressure at various temperatures.  Two major developments to accommodate the unique requirements of EMC testing include: (1) a large mold pressure for specimen fabrication; and (2) a high gas pressure for hydrostatic testing while minimizing a temperature rise.  The FBG embedded in the specimen records strain histories as a function of time.  Two linear viscoelastic properties, Young’s modulus and Poisson’s ratio, are first determined from the strain histories, and the other two elastic properties, Shear modulus and Bulk modulus, are calculated from the relationship among the constants.  The master curves are produced, and the corresponding shift factors are determined.  Validity of three major assumptions associated with the linear viscoelasticity – thermorheological simplicity, Boltzmann superposition and linearity – are verified by supplementary experiments.  The effect of the time-dependent bulk modulus on thermal stress analysis is also discussed.

Title: Parametric Design and Experimental Validation of Conjugate Stress Sensors for Structural Health Monitoring

Author: Jonathan Kordell

Date/Time: Date/Time – May 13, 2021 at 10am EDT

Examining Committee:
Dr. Abhijit Dasgupta
Dr. Miao Yu
Dr. Bongtae Han
Dr. Amr Baz
Dr. Hugh Bruck
Dr. Inderjit Chopra

Abstract:
In this dissertation, conjugate stress (CS) sensing is advanced through a parametric evaluation of a surface-mounted design and through experimental validation in monotonic and cyclic tensile tests. The CS sensing concept uses a pair of sensors of significantly different mechanical stiffness for direct query of the instantaneous local stress-strain relationship in the host structure, thus offering measurement of important health indicators such as stiffness (modulus), yield strength, strain hardening, and cyclic hysteresis. In this study, surface-mounted CS sensor designs are parametrically evaluated with finite element modeling, with respect to the sensors’ location, thickness, and modulus and the external loading state. An analytic pin-force model is developed to infer the host structure’s stress-strain state, based on the strain outputs of the CS sensor-pair.  Two CS sensor designs are fabricated – the first employs resistive foil strain gauges and the second employs fiber optic sensors – and paired with the pin-force model for experimental demonstration of the measurement of: (i) stress-strain history of three different metal bars (aluminum, copper, and steel) as they experience monotonic tensile loads well into plasticity and (ii) stress-strain hysteresis of a steel bar as it is subject to cyclic tensile fatigue. In the cyclic tests, two machine learning algorithms – anomaly detection and neural net classification – are used in conjunction with the estimated host stiffness from the CS sensor and pin force model to predict the failure time of the steel beams.

Title: THERMODYNAMIC AND INFORMATION ENTROPY-BASED PREDICTION  AND DETECTION OF FATIGUE FAILURES IN METALLIC AND COMPOSITE  MATERIALS USING ACOUSTIC EMISSION AND DIGITAL IMAGE  CORRELATION

Author: Seyed Fouad Karimian

Date: Thursday, May 6th, 2:00 – 4:00 PM. 

Zoom Link: https://umd.zoom.us/j/9968970907

Examining Committee:
Professor Mohammad Modarres, Advisor and Chair  
Professor Hugh Bruck, Co-Advisor 
Professor Aris Christou 
Professor Abhijit Dasgupta 
Professor Katrina Groth 
Professor Norman Wereley, Dean’s Representative

Abstract:
Although assumed to be identical, manufactured components always present some  variability in their performance while in service. This variability can be seen in their  degradation path and time to failure as they are tested under identical conditions. In  engineering structures and some components, fatigue is among the most common  degradation mechanisms and has been under extensive study over the past century. A  common characteristic of the fatigue life models is to rely on some observable or  measurable markers of damage, such as crack length or modulus reduction. However, these  markers become more pronounced and detectable toward the end of the component or  structure’s life. Therefore, more advanced techniques would be needed to better account for a structure’s fatigue degradation. Several methods based on non-destructive testing  techniques have developed over the past decades to decrease the uncertainty in fatigue  degradation assessments. These methods seek to exploit the data collected by sensors  during the operational life of a structure or component. Hence, the assessment of the health  state can be constantly updated based on the operational conditions that allow for  condition-based monitoring and maintenance. However, these methods are mostly context dependent and limited to specific experimental conditions. Therefore, a method to  effectively characterize and measure fatigue damage evolution at multiple length scales  based on the fundamental concept of entropy is studied in this dissertation. The two  entropic-based indices used are: Thermodynamic entropy, and, Information entropy. 

The objectives of this dissertation are to develop new methods for fatigue damage detection  and failure prediction in metallic and FRP laminated composite materials by using AE and  DIC techniques and converting them to information and thermodynamic entropy gains  caused by fatigue damage.  

1. Develop and experimentally validate fatigue damage detection, failure prediction,  and prognosis approaches based on the information entropy of AE signal waveforms  in both metallic and FRP laminated composite materials. 

2. Develop and experimentally validate fatigue damage detection, failure prediction,  and prognosis approaches based on thermodynamic entropy using the DIC technique  in both metallic and FRP laminated composite materials. 

3. Develop a framework for RUL estimation of metallic and FRP laminated composite  structures based on the two entropic measures.

Title: The Effects of Gravity on Flow Boiling Heat Transfer

Author: Caleb Hammer

Day/Time: Thursday, April 15th, 2021 | 10:00-11:30AM

Zoom Link: https://umd.zoom.us/j/91747518263

Committee Members:
Professor Jungho Kim, Chair
Professor Christopher Cadou, Dean’s Representative
Professor Kenneth Kiger
Professor Reinhard Radermacher
Professor Amir Riaz

Abstract: Flow boiling is a method of phase change heat transfer used widely in electronics cooling, refrigeration, air conditioning, and other areas where stable temperatures are needed. An area of interest is spaceflight systems, where efficient heat transfer is desired to minimize mass, power requirements, and cost. When compared to terrestrial gravity conditions, the heat transfer of flow boiling in microgravity typically depreciates. This depreciation has been documented across multiple experimental studies performed by teams using different fluids, tube geometries, and flow regimes over the past three decades. Though select experimental microgravity flow boiling heat transfer data are available in the literature, holistic results are sparse due to the cost and limited availability of microgravity research.  The two-phase heat transfer mechanisms responsible for the depreciation are therefore not well known, and so heat transfer models for variable gravity flow boiling do not exist.

The goal of the proposed study is to develop models for flow boiling heat transfer through a tube as a function of gravity by identifying the effect of gravity on different heat transfer mechanisms. The scope of this proposal involves modeling three microgravity flow regimes (bubbly, slug, and annular flow) to serve as baseline predictions for flow boiling heat transfer without the influence of gravity. Additional gravity effects can be identified using partial and hyper-gravity data.

Experiments have been performed aboard parabolic flights and on the ground at various flow rates, heating rates, and inlet subcoolings in microgravity, hyper-gravity, Lunar gravity, Martian gravity, and terrestrial gravity. Results from the experiments showed that negligible slip velocity plays an important role in modeling flow boiling heat transfer. Simulations using modified single-phase models of an accelerating flow were performed which predicted microgravity flow boiling heat transfer well in the nucleate boiling regime.

Additional experiments concerning terrestrial gravity quenching heat transfer have been performed to address research gaps in microgravity cryogen chilldown studies. Quenching heat transfer coefficients were recorded in the nucleate boiling regime and compared with correlations. The correlations were able to predict heat transfer for room temperature fluids much more accurately than for cryogenic fluids. Scaling parameters must be tuned to match cryogen data to examine the large disparity between cryogenic quenching heat transfer data and correlations observed in the literature.

Title: Data Requirements to Enable PHM for Liquid Hydrogen Storage Systems from a Risk Assessment Perspective

Author: Camila Correa Jullian

Day/Time: April 15, 2021 | 1:00pm (Eastern)

Zoom Link: https://umd.zoom.us/j/7492613806

Examining Committee
Dr. Katrina M. Groth, Chair
Dr. Mohammad Modarres
Dr. Reinhard Radermacher
Dr. William Buttner, Special Member 

Abstract: Quantitative Risk Assessment (QRA) provides tools to aid the development of risk-informed safety codes and standards that reduce risk in a variety of complex technologies, such as hydrogen systems. Currently, the lack of reliability data limits the use of QRAs for fueling stations equipped with bulk liquid hydrogen storage systems. In turn, this hinders the ability to develop the necessary rigorous safety codes and standards to allow worldwide deployment of these stations. Prognostics and Health Management (PHM) and the analysis of condition-monitoring data emerge as an alternative to support risk assessment methods. Through the QRA-based analysis of a liquid hydrogen storage system, the core elements for the design of a data-driven PHM framework are addressed from a risk perspective. This work focuses on identifying the data collection requirements to strengthen current risk analyses and enable data-driven approaches to improve the safety and risk assessment of a liquid hydrogen fueling infrastructure