Month: May 2021

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.

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.