Recognizing that many universities put their faculty hiring on hold due to uncertainties created by the pandemic, NSF has launched a new postdoctoral program for recently-graduated PhD students who want to stay in academia. Applications will be accepted from June 21 through July 6, 2021. We hope that this new Engineering Postdoctoral Fellows (eFellows) program enables highly qualified PhDs to gain more experience in academic research and be competitive for future faculty positions. Diverse candidates are encouraged to apply. Note that this program complements the Innovative Postdoctoral Entrepreneurial Research Fellowship (I-PERF) program that gives recent PhD graduates an opportunity to do a postdoc in an NSF-funded startup or small business. For details, see https://iperf.asee.org/ and https://efellows.asee.org/
Announcements
Based on the current decision from the Provost, UMD is returning to normal in-person instructional mode, starting in Fall 21.
To be consistent with this transition, Graduate School has instructed that Thesis and Dissertation Defense exams should also resume their traditional in-person format.
Details of their guidelines can be found here: https://gradschool.umd.edu/resumption-person-thesis-and-dissertation-defenses
Since we have traditionally followed Graduate School Defense format as guidance for Ph.D. Qualifier Exams and Dissertation Proposal Presentations, those events will also resume their traditional in-person format starting in Fall 21. Waivers for special situations will require prior approval and will be based on the guidelines provided by Graduate School in their website above.
Proposal Presentations and Defenses scheduled in Summer 2021 can be conducted in either format or in a hybrid mode, depending on the situation. Prior approval is not needed for any of these formats in Summer 2021.
Title: Fluid Dynamics of Extensional Deformation and Capillary-Driven Breakup of Drops at Low Reynolds Number.
Author: Aditya N. Sangli
Day/Time: June 22nd, 12:00 pm – 2:00 pm
List of committee members
Professor David I. Bigio, Chair & Advisor
Professor Amir Riaz
Professor James H. Duncan
Professor Kenneth Kiger
Professor Richard V. Calabrese, Dean’s Representative
Abstract:
In this dissertation, extensional deformation and capillary-driven breakup of drops at low Reynolds number is investigated using a combination of theoretical, experimental, and numerical techniques. The dissertation introduces a new non-dimensional measure for drop deformation, rationalizes previously unseen drop breakup behavior, and extends our overall understanding of the fluid dynamics behind drop deformation and breakup.
First, non-stagnant extensional deformation of Silicone oil drops in Castor oil is experimentally studied over a wide range of capillary numbers by injecting the drops along the centerline of a flow through a hyperbolic converging channel. The unique design of the channel is capable of imposing a constant extensional rate and is validated using lubrication theory. Based on a careful analysis of drop deformation at both small and large capillary numbers compared to the critical capillary number, a new measure called the semi-minor capillary number is introduced to characterize drop behavior. Critical semi-minor capillary number is presented for a wide range of viscosity ratios and the significance of the new measure over the conventional capillary number measure is discussed.
During the course of the experiments, it was observed that drops undergoing non-stagnant extension exhibited a lag in velocity compared to the background flow velocity at the same point. This lag in velocity is attributed to flow induced deformation of the drops and the phenomenon is rationalized for a wide range of capillary numbers.
When drops are injected offset of the centerline of the channel, an anomalously large degree of deformation is observed even at low flow rates. A careful investigation of the phenomenon revealed that the strain rates along offset lines were at least an order of magnitude larger than the extensional rates along the centerline. A model is developed based on lubrication theory to predict the large deformation of drops and is successfully validated with experimental measurements.
Finally, when slender drops are allowed to develop under the effect of interfacial tension, they either retract into a sphere or breakup into multiple drops. This phenomenon is investigated using direct numerical simulations in a previously unexplored part of the parametric space where both inertial and viscous effects in the outside fluid are considered. A stability diagram is presented that shows a transition of drop states from asymptotically unstable to asymptotically stable states at different viscosity ratios. The drop behavior in different regimes is discussed and the significance of the balance between inertial and viscous forces is thoroughly described.
Systematic Integration of PHM and PRA for Risk and Reliability Analysis of Complex Engineering Systems
Author: Ramin Moradi
Date/Time: Wednesday, June 16th. | 2 pm – 4 pm
Examining Committeee:
Dr. Katrina Groth, Chair/Advisor
Dr. Mohammad Modarres
Dr. Enrique Lopez Droguett
Dr. Michelle Bensi
Dr. Shapour Azarm
Dr. Greg Baecher, Dean’s Representative
“Complex Engineering Systems (CES) such as power plants, process plants,
manufacturing plants, etc. have numerous, interrelated, and heterogeneous subsystems with different characteristics and risk and reliability analysis requirements. On the other hand, with the advancements in sensing and computing technology, abundant monitoring data is being collected which is a rich source of information for a more accurate assessment and management of these systems. The current risk and reliability analysis approaches and practices are inadequate in incorporating various sources of information, providing a system-level perspective, and performing a dynamic assessment of the operation condition and operation risk of CES.
In this dissertation, this challenge is addressed by integrating techniques and models from two of the major subfields of reliability engineering, which are Probabilistic Risk Assessment (PRA) and Prognostics and Health Management (PHM). PRA is very effective at modeling complex hardware systems, and approaches have been designed to incorporate the risks introduced by humans, software, organizational, and other contributors into quantitative risk assessments. However, PRA has largely been used as a static technology and in the design stage of the systems. On the other hand, PHM has developed powerful new algorithms for understanding
and predicting mechanical and electrical devices’ health. Yet, PHM lacks the system-level perspective, relies heavily on the operation data, and its outcomes are not risk-informed.
We propose a novel framework at the intersection of PHM and PRA which provides a forward-looking, model- and data-driven analysis paradigm for assessing and predicting the operation risk and condition of CES. We operationalize this framework by developing two mathematical architectures and applying them to real-world systems. The First architecture is focused on enabling online system-level condition monitoring. While the second architecture improves upon the first and realizes the objectives of using various sources of information and monitoring
operation condition together with operational risk.”
Categories
Dissertation Defense – Qian Jiang
Anisotropic Multi-scale Modeling for Steady-state Creep Behavior of Polycrystalline Coarse-grain SnAgCu (SAC) Solder Joints
Author: Qian Jiang
Day/Time: June 10, 12:00 noon – 2:00 pm
List of committee members
Professor Abhijit Dasgupta, Chair
Professor Hugh Alan Bruck
Professor Teng Li
Professor Patrick McCluskey
Professor Lourdes G. Salamanca-Riba, Dean Representative
Abstract:
Heterogeneous integration is leading to unprecedented miniaturization of solder joints. The overall size of solder interconnections in current-generation microelectronics assemblies has length-scales that are comparable to that of the intrinsic heterogeneities of the solder microstructure. In particular, there are only a few highly anisotropic grains in each joint. This makes the mechanical response of each joint quite unique. Rigorous mechanistic approaches are needed for quantitative understanding of the response of such joints, based on the variability of the microstructural morphology.
The discrete grain morphology of as-solidified coarse-grain SAC (SnAgCu) solder joints is explicitly modeled in terms of multiple length scales (four tiers of length scales are used in the description here). At the highest length-scale in the joint (Tier 3), there are few highly anisotropic viscoplastic grains in each functional solder joint, connected by visoplastic grain boundaries. At the next lower tier (Tier 2), the primary heterogeneity within each grain is due to individual dendrites of pro-eutectic β-Sn. Additional microscale intermetallic compounds of Cu6Sn5 rods are located inside individual grains. Packed between the dendrite lobes is a eutectic Ag-Sn alloy. The next lower length-scale (Tier 1), deals with the microstructure of the Ag-Sn eutectic phase, consisting of nanoscale Ag3Sn IMC particles dispersed in a β-Sn matrix. The characteristic length scale and spacing of the IMC particles in this eutectic mix are important features of Tier 1. Tier 0 refers to the body-centered tetragonal (BCT) anisotropic β-Sn crystal structure, including the dominant slip systems for this crystal system.
The objective of this work is to provide the mechanistic framework to quantify the mechanical viscoplastic response of such solder joints. The anisotropic mechanical behavior of each solder grain is modeled with a multiscale crystal viscoplasticity (CV) approach, based on anisotropic dislocation mechanics and typical microstructural features of SAC crystals. Model constants are calibrated with single crystal data from the literature and from experiments. This calibrated CV model is used as single-crystal digital twin, for virtual tests to determine the model constants for a continuum-scale compact anisotropic creep model for SAC single crystals, based on Hill’s anisotropic potential and an associated creep flow-rule.
The additional contribution from grain boundary sliding, for polycrystalline structures, is investigated by the use of a grain-boundary phase, and the properties of the grain boundary phase are parametrically calibrated by comparing the model results with creep test results of joint-scale few-grained solder specimens. This methodology enables user-friendly computationally-efficient finite element simulations of multi-grain solder joints in microelectronic assemblies and facilitates parametric sensitivity studies of different grain configurations.
This proposed grain-scale modeling approach is explicitly sensitive to microstructural features such as the morphology of: (i) the IMC reinforcements in the eutectic phase; (ii) dendrites; and (iii) grains. Thus, this model is suited for studying the effect of microstructural tailoring and microstructural evolution. The developed multiscale modeling methodology will also empower designers to numerically explore the worst-case and best-case microstructural configurations (and corresponding stochastic variabilities in solder joint performance and in design margins) for creep deformation under monotonic loading, for creep-fatigue under thermal cycling as well as for creep properties under isothermal aging conditions.
Title: Integrating Human Performance Models into Early Design Stages to Support Accessibility
Author: Benjamin Knisely
Day/Time: June 8th, 1-3 pm
List of committee members
Assistant Professor Monifa Vaughn-Cooke, Chair
Assistant Professor Mark Fuge
Professor Jeffrey Herrmann
Assistant Professor John Dickerson
Professor Michel Wedel, Dean Representative
Day/Time: June 8th, 1-3 pm
Abstract:
Humans have heterogeneous physical and cognitive capabilities. Engineers must cater to this heterogeneity to minimize opportunities for user error and system failure. Human factors considerations are typically evaluated late in the design process, risking expensive redesign when new human concerns become apparent. Evaluating user capability earlier could mitigate this risk. One critical early-stage design decision is function allocation – assigning system functions to humans and machines. Automating functions can eliminate the need for users to perform risky tasks but increases resource requirements. Engineers require guidance to evaluate and optimize function allocation that acknowledges the trade-offs between user accommodation and system complexity. In this dissertation, a multi-stage design methodology is proposed to facilitate the efficient allocation of system functions to humans and machines in heterogeneous user populations. The first stage of the methodology introduces a process to model population user groups to guide product customization. User characteristics critical to performance of several generalized product interaction tasks are identified and corresponding variables from a national population database are clustered. In stage two, expert elicitation is proposed as a cost-effective means to quantify risk of user error for the user group models. Probabilistic estimates of user group performance are elicited from internal medicine physicians for generalized product interaction tasks. In the final stage, the data (user groups, performance estimations) are integrated into a multi-objective optimization model to allocate functions in a product family when considering user accommodation and system complexity. The methodology was demonstrated on a design case study involving self-management technology use by diabetes patients, a heterogeneous and safety-critical population. The population modeling approach produced quantitatively and qualitatively validated clusters. For the expert elicitation, experts provided internally validated, distinct estimates for each user group-task pair. To validate the utility of the proposed method (acquired data, optimization model), engineering students (n=16) performed the function allocation task manually. Results indicated that participants were unable to allocate functions as efficiently as the model despite indicating user capability and cost were priorities. This research demonstrated that the proposed methodology can provide engineers valuable information regarding user capability and system functionality to drive accessible early-stage design decisions.
TITLE: Morphology evolution of droplets in a polymer based extensional flow.
Date/Time: Friday, May 28 – 2PM-4PM
Committee Members:
Dr. David Bigio (Advisor)
Dr. James Duncan
Dr. Ryan Sochol
Zoom Link: https://umd.zoom.us/j/93032464600
Abstract: Fused Deposition Modelling (FDM) is one of the most widely used Additive Manufacturing (AM) methods to bring products to life. This thesis examines the incorporation of liquid additives into the nozzle region of an FDM system and attempts to understand their behavior in the polymer melt flow. The current computational work provides a background for a novel method wherein liquid additives can be injected into the melted polymer. A converging nozzle providing a near constant extension rate along the center-line is modelled. The deformation of droplets inside a polymer undergoing a purely extensional flow is studied for a range of exit (V) to platen velocities (U) and viscosity ratios (λ). It is observed that the behavior of droplets for a λ = 1 is found to be drastically different from that of lower λ’s, which is attributed to the balance of shear stresses at the interface of the inner and outer flow fields. Finally, the morphology of the deposited plastic strands is also predicted. It is seen that as the velocity ratio is increased the cross-section of the deposited strand changes from being almost spherical to an oblong.
Categories
Thesis Defense – Haafiz Husker
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.
Categories
Thesis Defense – Hyun Seop Lee
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.