Author: Segen Sara A. Habte

Author: Edwin Fishman

Title: The Natural Response of Uniform in Air and Partially Submerged in a Quiescent Water Body

Date/time: April 24th at 10:00am

Location: 3179K Aerospace Engineering Conference Room, Glenn L. Martin Hall.

Committee members:
Professor James Duncan, Advisor & Chair
Professor Miao Yu
Professor Kenneth Kiger

Abstract:

The free vibration of three aluminum plates (.4 m wide, 1.08 m long) oriented horizontally is studied experimentally under two fluid conditions, one with the plate surround by air and the other with the bottom plate surface in contact with a large undisturbed pool of water.  Measurements of the out of plane deflection of the upper surfaces of the plates are made using cinematic Digital Image Correlation (DIC) over the center portion of the surface  and optical tracking of the center point. Three plate geometries and boundary conditions are studied: A uniform plate with 6.35 mm thickness pinned at the two opposite narrrow ends (UP), a uniform plate with 4.83 mm thickness simply supported at one narrow end and clamped at the opposite end (UC), and a stepped plate with thickness varying from 12.7 mm to 6.35 mm pinned at two opposite narrow ends (SP). The plate’s free response is induced using an impact hammer at three locations along the center-line of the plate. Video frames of the plate’s motion are collected from stereoscopic cameras and processed using DaVis-Strainmaster and MATLAB to extract full-field displacements as a function of time. 2-degree-of-freedom displacements of the plate center are collected from tracking the center target’s motion. Time and frequency response plots are presented for comparison between the half-wet and air cases and analysis of their dynamics. It is found that the added mass of the water results in lower measured natural frequencies and modified mode shapes. These results are compared to mode shapes/frequencies produced in Creo Simulate and found to agree. Further experiments are discussed.

Author: Zahra Nozarijouybari

Title: Optimal Probing of Battery Cycles for Machine Learning-Based Model Development 

Date/time: April 29th at 2:00pm

Location: 2162 DeWALT Conference Room, Glenn L. Martin Hall.

Committee members:
Professor Hosam Fathy, Advisor & Chair
Professor Mark Fuge
Professor Steven A. Gabriel
Professor Teng Li
Professor Chunsheng Wang, Dean’s Representative

Abstract:

Author: Matthew Keeler

Title: DESIGN NOVELTY EVALUATION THROUGH ORDINAL EMBEDDING: COMPARISON OF NOVELTY AND TRIPLET ERRORS

Date/time: April 19th at 12:00pm

Location: 2164 DeWALT Seminar Room, Glenn L. Martin Hall.

Committee members:
Professor Mark D. Fuge, Chair/Advisor
Professor Shapour Azarm
Professor Nikhil Chopra

Abstract:
A practical and well-studied method for computing the novelty of a design is to construct an ordinal embedding via a collection of pairwise comparisons between items (called triplets), and use distances within that embedding to compute which designs are farthest from the center. Unfortunately, ordinal embedding methods can require a large number of triplets before their primary error measure—the triplet violation error—converges. But if our goal is accurate novelty estimation, is it really necessary to fully minimize all triplet violations? Can we extract useful information regarding the novelty of all or some items using fewer triplets than classical convergence rates might imply? This thesis addresses this question by studying the relationship between triplet violation error and novelty score error when using ordinal embeddings.

We find that estimating the novelty of a set of items via ordinal embedding can require significantly fewer human provided triplets than is needed to converge the triplet error, and that this effect is modulated by the type of triplet sampling method (random versus uncertainty sampling). Having learned this, we propose the use of a custom metric we call the ‘Expected Model Change’ (EMC) which we use to observe when novelty information in the embedding has stopped updating under newly labeled triplets, so that conservative bounding functions need not be used. Moreover, to avoid the dangers of low accuracy in selecting the dimension of the ordinal embedding, we propose use of the Expected Model Change for tuning the embedding dimension to an appropriate value. In this framework, we explore the convergence properties of ordinal embeddings reconstructed from triplets taken from a variety of synthetic and real-world design spaces.

Author: Cashen Diniz

Title: Denoising the Design Space: Diffusion Models for Accelerated Airfoil Shape Optimization

Date/time: April 16th at 9:30am

Location: 2164 DeWALT Seminar Room, Glenn L. Martin Hall.

Committee members:
Professor Mark D. Fuge, Chair/Advisor
Professor James Baeder
Professor Michael Otte

Abstract:

Generative models offer the possibility to accelerate and potentially substitute parts of the often expensive traditional design optimization process. We present Aero-DDM, a novel application of a latent denoising diffusion model (DDM) capable of generating airfoil geometries conditioned on flow parameters and an area constraint. Additionally, we create a novel, diverse dataset of optimized airfoil designs that better reflects a realistic design space than has been done in previous work. Aero-DDM is applied to this dataset, and key metrics are assessed both statistically and with an open-source computational fluid dynamics (CFD) solver to determine the performance of the generated designs. We compare our approach to an optimal transport GAN, and demonstrate that our model can generate designs with superior performance statistically, in aerodynamic benchmarks, and in warm-start scenarios. We also extend our diffusion model approach, and demonstrate that the number of steps required for inference can be reduced by as much as ~86%, compared to an optimized version of the baseline inference process, without meaningful degradation in design quality, simply by using the initial design to start the denoising process.

Author: Anthony Fabbri

Title of dissertation: Second Wave Mechanics

Date/time: April 16th, 2024 at 2:00pm

Location: 2162 DeWALT Conference Room, Glenn L. Martin Hall.

Committee members:

• Dr. Jeffrey Herrmann, Advisor and Chair
• Dr. Cole Miller
• Dr. Yi Xu

Abstract:

The COVID-19 pandemic experienced very well-documented “waves” of the virus’ progression, which can be analyzed to predict future wave
behavior. Common wave shape patterns can be identified in real-time
data, to predict the pattern of mutations that have recently occurred,
but have not become popularly known as yet, to predict the remaining
future outcome of the wave. By only considering the patterns in the
data that could possibly have acted in tandem to generate the observed
results, many false patterns can be eliminated, and, therefore, hidden
variables can be estimated to a very high degree of probability.
Similar mathematical relationships can reveal hidden variables in
other underlying differential equations.

Author: Matthew Weiner

Title of dissertation: A Framework For Remaining Useful Life Prediction and Optimization For Complex Engineering Systems

Date/time: April 15th, 2024 at 10:00am

Zoom: https://umd.zoom.us/j/6365088363

Location: 2164 DeWALT Conference Room, Glenn L. Martin Hall.

Committee members:

• Dr. Shapour Azarm, Advisor and Chair
• Dr. Katrina Groth, Co-Advisor
• Dr. Yunfei Zhao

Abstract: