Thank you to everyone who attended our Annual Spring Award Reception and congratulations again to all of our awardees on your many achievements! You can explore photos from the event by clicking here and a link to the program from the event is listed below.
Author: Jacob Welch
Date/Time/Location: April 24th, 1:30-3PM, ERF 1207.
Title of Thesis: Spectral Methods of Modeling and Calculating Fatigue in Electronic Interconnects
List of Committee Members:
Abhijit Dasgupta (Chair)
Michael Osterman
Avik Dutt
Abstract:
The purpose of this thesis is to provide a predictive estimate of fatigue damage accumulation in PWA interconnects using purely frequency-domain (spectral) information such as the PSD of the input excitation. This method is used to predict fatigue damage accumulation rate in the critical interconnects, for broad-band random vibration excitation on a PWA with LQFP components. Results are compared with those obtained from a direct time-domain approach. The modeling is achieved using a two-stage global-local modeling process in Abaqus, where the dominant mode shapes of the dynamic global model are applied to a 3D quasi-static local model, using multi-point constraint equations. The transfer function from PWB strain to interconnect strain is then estimated for each of the dominant modes. The PWB response PSD from the global model is then used in conjunction with these strain transfer functions, to estimate the PSD of the strain response in the critical lead/solder for each dominant mode, and summed over each mode, and then used to reconstruct a pseudo-time history of lead strain. This pseudo time history is then used to perform a Rainflow cycle count. From this point established methods are able to be used to estimate fatigue damage accumulation using either the cyclic count or with competing methods such as Rayleigh method or Dirlik method. Results are compared to corresponding fatigue damage estimates from a time-domain analysis method.
Author: Drew Hohenhaus
Title: Prediction and Closed-Loop Control of Blood Pressure for Hemorrhage Resuscitation
Date/Time: April 17th at 11:00 am
Location: EGR 2162
Committee:
Dr. Jin-Oh Hahn, Chair
Dr. Hosam Fathy
Dr. Yancy Diaz-Mercado
Abstract:
Hemorrhage is responsible for a large percentage of mortality worldwide and the majority of fatalities on the battlefield. Resuscitation procedures for hemorrhage trauma patients are critical for their recovery. Currently, during resuscitation physicians manually monitor blood pressure and use intuition to determine when fluid should be administered and how much. Due to many factors such as exhaustion, distraction, and inexperience, this method of resuscitation has often been reported as fallible. This thesis proposes two methods to assist in automating hemorrhage resuscitation. The first is a blood pressure prediction algorithm for decision support systems. The algorithm individualizes itself to different subjects using extended Kalman filtering, to account for high inter-subject variability, before accurately forecasting future blood pressure. The second method is an observer-based feedback controller which regulates blood pressure from a hypotensive state back to a healthy setpoint. The controller was designed using linear matrix inequality techniques to ensure it was absolutely stable, which let a portion of the hemodynamic plant model remain unspecified and allowed for performance over a range of physiologies. Both strategies were evaluated in-silico on a cohort of 100 virtual patients generated from an experimental dataset. The prediction algorithm showed superior accuracy to conventional assumptions. The controller tracked the given setpoint with an accuracy and performance comparable to more complex adaptive methods while outperforming empirical controllers. Further work, with respect to the prediction algorithm, includes developing it into a full decision-support system and incorporating disturbance rejecting components to account for common issues such as rebleed. The controller’s performance deteriorates for low setpoints, suggesting further study is required to increase its situational flexibility.
Author: Mohamed Mohsen Ahmed
Title of Dissertation: Development of a Lagrangian-Eulerian Modeling Framework to Describe Thermal
Degradation of Porous Fuel Particles in Simulations of Wildland Fire Behavior at Flame Scale
Date and time: April 14, 2023, at 8:30 AM
Location: Fire and Risk Alliance Conference Room, 3106 J.M. Patterson Building
Zoom link: https://umd.zoom.us/j/7685207098 | Zoom meeting ID: 768 520 7098
Committee Members:
Abstract:
Wildland fire is a multi-scale problem in which different length-scales are believed to play a role in fire behavior. These length-scales range from sub-millimeter representative of small vegetation particles, to several kilometers’ representative of meteorological scales. Computational Fluid Dynamics (CFD) models have the potential to describe wildland fire behavior at different scales. Our objective in the present study is to develop a computational tool to better describe the coupling between solid phase and gas phase processes that control the dynamics of flame spread in wildland fire problems. We focus on a modelling approach that resolves processes occurring at flame and vegetation scales, i.e., the formation of flammable vapors from the biomass vegetation due to pyrolysis, the subsequent combustion of these fuel vapors with ambient air, the establishment of a turbulent flow because of heat release and buoyant acceleration, and the thermal feedback to the solid biomass through radiative and convective heat transfer. The modelling capability is based on a general-purpose Computational Fluid Dynamics (CFD) library called OpenFOAM and an inhouse Lagrangian Particle Burning Rate (PBR) model that treats drying, thermal pyrolysis, oxidative pyrolysis and char oxidation using a one-dimensional porous medium formulation that allows descriptions of thermal degradation processes occurring during both flaming and smoldering combustion. We also introduce a novel diagnostic called Pseudo Incident Heat Flux (PIHF) to characterize the particle external heat loading.
The modelling capability is calibrated for cardboard and pine wood using available micro-and bench-scale experimental data obtained. The model is applied to simulations of the fire spread across idealized fuel beds made of laser-cut cardboard sticks that have been studied experimentally at the Missoula Fire Sciences Laboratory. The simulations are conducted at prescribed particle and environmental properties (i.e., fuel bed height, fuel bed packing, particle size, moisture content, and wind velocity) that match the experimental conditions. The model is first validated against experimental measurements and observations such as the rate of spread of the fire and the flame residence time. The modeling capability is then used to provide insights into local as well as global behavior at individual particle level and at the fuel bed level with the fuel packing. The modelling capability is also applied to simulations of fire spread across idealized vegetation beds corresponding to thin, mono-disperse or bi-disperse, cylindrical-shaped sticks of pine wood under prescribed wind conditions. Depending on the particle size distribution, the simulations feature complete fuel consumption with successful transition from flaming to smoldering combustion or partial fuel consumption with no or limited smoldering. These simulations show the existence of either a mixed mode of heat transfer through convection and radiation for small particles or a radiation dominant heat transfer mode for larger particles. The results are interpreted using maps that characterize single particle burning behavior as a function of intensity and duration of the thermal loading process.
Author: Eesh Kamrah
Date: Monday, April 10th, 2023 at 1:30 pm
Location: EGR-4164B
Committee Members:
Title of Thesis: ‘A STUDY TO EVALUATE WHEN TO NOT USE DIVERSE EXAMPLES
Abstract:
Design researchers have struggled to provide quantifiable forecasts on whether diversity helps or hinders the design search process. [1] This thesis studies this problem by answering the following question “how and when do diverse initial stimuli lead to better quality designs?” It does so by presenting a design research study on a modular ND test problem and Delta Design Game [2].
During our investigation some methods were developed as they couldn’t be found in popular literature. For example, a sampling method that can sample both relatively less and highly diverse initial data; we addressed this by developing a fast DPP rank based diversity method. Next, we could not find a modular test function that has parameters that would allow us to control the function’s ruggedness/complexity, we addressed this by creating a modular test function based on an existing concept that can be used to generate test functions of similar and varying complexity.
The thesis is thus laid out in a manner so that initially we address the methods that are necessary to understand the study. This begins with Chapter 2, where we look at how the diversity data sampling method can be used to generate diverse and less-diverse examples. In Chapter 3, we look at the different test problems that have been developed that are used in the study. Once familiar with this, the latter part of the thesis shows the results that provide evidence that initializing an optimizer with diverse examples is not always beneficial. We also identify the conditions in which the less diverse initial examples perform better. In the last chapter we identify the limitations of the provided results and how further experiments can be designed to investigate the identified limitations.
[1] Fu, Katherine, Joel Chan, Jonathan Cagan, Kenneth Kotovsky, Christian Schunn, and Kristin Wood. “The Meaning of ‘Near’ and ‘Far’: The Impact of Structuring Design Databases and the Effect of Distance of Analogy on Design Output.” Journal of Mechanical Design 135, no. 2 (January 7, 2013). https://doi.org/10.1115/1.4023158.
[2] Nepf, Heidi, Herbert Einstein, and Louis Buicciarelli. “Delta Game | Introduction to Civil and Environmental Engineering Design I | Civil and Environmental Engineering | MIT OpenCourseWare.” MIT – Course Information. INTRODUCTION TO CIVIL AND ENVIRONMENTAL ENGINEERING DESIGN I, Fall 2016. https://ocw.mit.edu/courses/1-101-introduction-to-civil-and-environmental-engineering-design-i-fall-2006/pages/delta-game/.
Author: He (Andy) Yun
Title of dissertation:
Manufacturability and Reliability of Additively Manufactured Planar Transformer Windings using Silver-based Paste
Date, time, & location of defense:
Monday, 4/10, from 1 – 3 PM, at 1131B Martin Hall
Committee members:
Prof. F. Patrick McCluskey (Advisor & Chair)
Prof. Aris Christou
Prof. Abhijit Dasgupta
Prof. Hugh Bruck
Prof. Alireza Khaligh (Dean’s Representative)
Abstract:
This dissertation is primarily concerned with the integration of additive manufacturing (AM) techniques into planar magnetics to achieve more efficient designs for power modules, which are in high demand. The two main focuses of this dissertation are: (1) the use of a paste-based AM technique called syringe-printing to create planar transformer windings without the need for pressure, using silver-based paste. The dissertation will address manufacturing considerations such as trace width, gaps, and heights that are printable, as well as the impact of electrical resistivity on the sintering process for the syringe-printed silver-based windings; and (2) the evaluation of the reliability of the syringe-printed silver-based windings, which will involve assessing adhesion performance between the metal/ceramic interface, conducting accelerated life tests (including thermal aging and thermal cycling tests), and identifying failure modes, failure sites, failure mechanisms, and developing degradation/failure models.
In order to achieve the desired printing geometry in terms of width and gaps between segments, printing settings were studied parametrically by fitting targeted values with actual values. A low-temperature sintering profile was optimized, with a dwell time of 8 hours at 350°C resulting in a resistivity as low as 4.39E-8 ohm.m, which was approximately 2.5 times higher than bulk silver. To improve bonding prior to syringe-printing the silver-based windings, it was suggested that an adhesive layer consisting of titanium (Ti) and silver (Ag) be deposited onto the alumina substrate. A degradation model was developed for thermal aging tests. Two batches of single layer 7-turn syringe-printed windings were subjected to thermal cycling tests, and the corresponding failure modes and mechanisms were investigated. The failure data was used to combine with the strain-energy density extracted from the finite element simulation to develop the fatigue model, with the Coffin-Mason model being fitted for comparison. A more conservative model was recommended for real-world applications. Finally, the silver-based paste was syringe-printed onto a cooler with limited footprint area, which served as the primary and secondary planar transformer board, and was successfully used in a 10 kW DC-DC full-bridge power converter with 97% efficiency. Corresponding thermal and electrical performance were discussed.
Author: Kendyl Waddell
Title: NEAR-LIMIT SPHERICAL DIFFUSION FLAMES AND COOL DIFFUSION FLAMES
Committee Members:
Dr. Peter Sunderland, Chair
Dr. Christopher Cadou, Dean’s Representative
Dr. Fernando Raffan-Montoya
Dr. Stanislav Stoliarov
Dr. Arnaud Trouve
Date and time: April 10, 2023 at 1:00 pm
Location: Fire and Risk Alliance Conference Room, 3106 J.M. Patterson Building
Zoom link:https://umd.zoom.us/j/7068085301?pwd=MEpuemxyOStaN0h2MkZ6Sno1ZG1vUT09
Abstract: To combat the rising threats of climate change, current combustion technologies must evolve to become cleaner and more efficient. This requires a better understanding of the fundamental properties of combustion. One way to gain this is through microgravity experiments, where the lack of buoyancy reduces flames to their most basic components, simplifying modeling efforts. The low-temperature combustion of warm and cool flames, which has applications in advanced engine technologies and implications in terrestrial and spacecraft fire safety, is favored in microgravity. In this work, microgravity spherical diffusion flames are generated aboard the International Space Station using a spherical porous burner. A transient numerical model with detailed chemistry, transport, and radiation is used to simulate the flames. This incorporates the UCSD mechanism with 57 species and 270 reactions. Hot, warm, and cool diffusion flames are all studied. Experimental flame temperature was measured using thin-filament pyrometry, which was calibrated using a blackbody furnace. The measured temperatures agreed reasonably well with numerical simulations for a wide range of conditions, and were in the range of 950-1600 K, with an estimated uncertainty of ± 100 K. The temperatures of the porous spherical burner were measured by a thermocouple embedded in its surface. These measured temperatures, combined with numerical simulations of the gas phase, yield insight into the complex heat transfer processes that occur in and near the porous sphere.
Previous work has found that ethylene microgravity spherical diffusion flames extinguish near 1130 K at atmospheric pressure, regardless of the level of reactant dilution. The chemical kinetics associated with this consistent extinction temperature are explored using the transient numerical model. Species concentrations, reaction rates, and heat release rates are examined. Upon ignition, the peak temperature is above 2000 K, but this decreases until extinction due to radiative losses. This allows the kinetics to be studied over a wide range of temperatures for the same fuel and oxidizer. At high temperature, the dominant kinetics are similar to those reported for typical normal-gravity hydrocarbon diffusion flames. There are well defined zones of pyrolysis and oxidation, and negligible reactant leakage through the reaction zone. As the flame cools, there is increased reactant leakage leading to higher O, OH, and HO2 concentrations in the fuel-rich regions. The pyrolysis and oxidation zones overlap, and most reactions occur in a narrow region near the peak temperature. Reactions involving HO2 become more significant and warm flame chemistry appears. At atmospheric pressure, this low-temperature chemistry delays extinction, but does not produce enough heat to prevent it.
As ambient pressure is increased, low-temperature chemistry is enhanced, allowing the flame to extend into the warm flame and cool flame regimes. Experimental results show that increasing the pressure from 1 bar to 3 bar decreased the ethylene extinction temperature by almost 60 K. Numerical simulations showed similar behavior, as well as the emergence of cool flame behavior when the pressure was increased to 50 bar. This allows the kinetics of spherical warm and cool diffusion flames and the role of increased HO2 participation to be examined.There are few options for studying cool diffusion flames experimentally that do not require expensive facilities that are unavailable to the average researcher. A method is presented for observing cool diffusion flames inexpensively using a pool of liquid n-heptane and parallel plates heated to produce a stably stratified stagnation flow. The flames were imaged with a color camera and an intensified camera. Measurements included gas phase temperatures, fuel evaporation rates, and formaldehyde yields. These are the first observations of cool flames burning near the surfaces of fuel pools. The measured peak temperatures were between 705 – 760 K and were 70 K above the temperature of the surrounding air. Autoignition first occurred at 550 K.
Author: Andres Alfredo Ruiz-Tagle Palazuelos
Title: Exploiting Causal Reasoning to Improve the Quantitative Risk Assessment of Engineering Systems Through Interventions and Counterfactuals
Date and Time: 04/10/2023 at 11:30 AM
Location: Clark Memorial Conference Room 1117 in A. James Clark Hall
Zoom invite: https://umd.zoom.us/j/2803971669?pwd=SXZPazNZamczZ0xrMEVxV3MxTC9sQT09
Committee members:
Abstract:
The main strength of quantitative risk assessment (QRA) is to enable risk management by providing causal insights into the risk of an engineering system or process. Bayesian Networks (BNs) have become popular in QRA because they offer an improved causal structure that represents analysts’ knowledge of a system and enable reasoning under uncertainty. Currently, the use of BNs for risk-informed decisions is based solely on associative reasoning, answering questions of the form “If we observe X=x, how likely is it to observe Y=y?” However, risk management in the industry relies on understanding how a system could change in response to external influences (e.g., interventions and decisions) and identifying the causes and mechanisms that could explain the outcome of past events (e.g., accident investigations and lessons learned). This dissertation shows that associative reasoning alone is insufficient to provide these insights, and it provides a framework for obtaining more complex causal insight using BNs with intervention and counterfactual reasoning.
Intervention and counterfactual reasoning must be implemented along with BNs to provide more complex insights about the risk of a system. Intervention reasoning answers queries of the form “How does doing X=x change the likelihood of observing Y=y?” and can be used to inform the causal effect of interventions and decisions on the risk and reliability of a system. Counterfactual reasoning answers queries of the form “Had X been X=x’ in an event, instead of the observed X=x, could Y have been Y=y’, instead of the observed Y=y?” and can be used to learn from past events and improve safety management activities. BNs present a unique opportunity as a risk modeling approach that incorporates the complex causal dependencies present in a system’s variables and allows reasoning under uncertainty. Therefore, exploiting the causal reasoning capabilities of BNs in QRAs can be highly beneficial to improve modern risk analysis.
The goal of this work is to define how to exploit the causal reasoning capabilities of BNs to support intervention and counterfactual reasoning in the QRA of complex systems and processes. To achieve this goal, this research first establishes the mathematical background and methods required to model interventions and counterfactuals within a BN approach. Then, we demonstrate the proposed methods with two case studies concerning the risk of third-party excavation damage to natural gas pipelines in the U.S. The first case study showed that the intervention reasoning methods developed in this work produce unbiased causal insights into the effectiveness of implementing new excavation practices. The second case study showed how the counterfactual reasoning methods developed in this work can expand on the lessons learned from an accident investigation on the Sun Prairie 2018 gas explosion by providing new insights into the effectiveness of current damage prevention practices. Finally, associative, intervention, and counterfactual reasoning methods with BNs were integrated into a single model and used to assess the risk of a highly complex challenge for the future of clean energy: excavation damages to natural gas pipelines transporting hydrogen. The impact of this research is a first-of-its-kind approach and a novel set of QRA methods that provide expanded causal insights for understanding failures and accidents in complex engineering systems and processes.
Author: Bhargav Sai Chava
Title: Atomistic Exploration of Water and Salt Confined in Sub-Nanometer and Nanometer Wide Boron-Nitride Nanotubes
Advisory Committee:
Dr. Siddhartha Das, Chair/Advisor
Dr. Pratyush Tiwary
Dr. Amir Riaz
Dr. Po-Yen Chen
Dr. Yifei Mo, Dean’s Representative
Day/Time: April 6, 3:00 pm
Location: EGR 2162 (DeWALT Conference Room)