Abstract: Advances in electrical energy storage systems are critical for vehicle electrification, renewable energy integration into the electric grid, and electric aviation. Recent years have witnessed an urgent need to accelerate innovation toward realizing improved and safe utilization of high energy and power densities, for example, in lithium-ion and advanced battery chemistries. These are complex, dynamical systems that include coupled processes encompassing electronic, ionic, and solid-state diffusive transport, electrochemical reactions at electrode/electrolyte interfaces, mechanical stress generation, and thermal transport in porous electrodes. This presentation will highlight the importance of the underlying mechanistic interactions at scale in the design of novel paradigms in exemplar energy storage architectures.

Biographical Sketch: Partha P. Mukherjee is a Professor of Mechanical Engineering and a University Faculty Scholar at Purdue University. His prior appointments include Assistant Professor and Morris E. Foster Faculty Fellow of Mechanical Engineering at Texas A&M University (2012-2017), Staff Scientist at Oak Ridge National Laboratory (2009-2011), Director’s Research Fellow at Los Alamos National Laboratory (2008-2009), and Engineer at Fluent India (currently Ansys Inc., 1999-2003). He received his Ph.D. in Mechanical Engineering from Pennsylvania State University in 2007. His awards include Scialog Fellows’ recognition for advanced energy storage, University Faculty Scholar and Faculty Excellence for Early Career Research awards from Purdue University, The Minerals, Metals & Materials Society Young Leaders Award, and invited presentations at the U.S. National Academy of Engineering Frontiers of Engineering symposium and Gordon Research Conference – Batteries, to name a few. His research interests are focused on mesoscale physics and stochastics of transport, chemistry, and materials interactions, including an emphasis on the broad spectrum of energy storage and conversion.

Abstract: The characterization and quantification of the coupling between flow and flexible structures and dominant oscillation modes remain open problems. Environmental science, energy, structural design, and locomotion applications require a comprehensive understanding of these phenomena. Canopy flows, encompassing extensive arrays of rigid or flexible structures, hold significant interest. Ubiquitous in natural environments and spanning multiple scales, they are instrumental in the transport of scalar and inertial particles. This presentation will provide insights from both theoretical perspectives and controlled laboratory experiments. I will discuss the role of key parameters modulating the unsteady dynamics of flows, individual structures, and canopies. These parameters comprise flow velocity, turbulence, structural stiffness, aspect ratio, tip effects, layout, and submergence within open channel flows. For this purpose, I will present data from particle image velocimetry (PIV), particle tracking velocimetry (PTV), and force balance analyses, highlighting turbulence, motion patterns, and unsteady loads on selected structures.

Biographical Sketch: Dr. Chamorro is an Associate professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign and is affiliated with the Departments of Aerospace Engineering, Civil and Environmental Engineering, and Geology. His research interests include turbulence, particle dynamics, boundary layer processes, aerodynamics, turbulence and structure interaction, wind energy, marine and hydrokinetic energies, and the development of advanced flow diagnostics. He has published 135 peer-reviewed articles in leading journals, has participated in over 140 presentations in technical symposia, and serves as scientific chair on Energy, Electrical Eng, Electronics and Mechanics (W&T7) at the Research Foundation Flanders (FWO) in Belgium. Chamorro is Associate Editor of the Journal of Renewable and Sustainable Energy, the Journal Frontiers in Energy Research, and the Journal of Energy Engineering. He leads the Renewable Energy and Turbulent Environment group, which uses a versatile experimental approach that combines state-of-the-art techniques, including 2D/3D particle image velocimetry, computer vision, and 3D particle tracking velocimetry.

Abstract: Deep learning approaches have become crucial tools across numerous engineering domains. However, they face various challenges, as they typically depend on representative data and large training datasets. Conversely, condition monitoring data for complex systems often lacks labels and representativeness, posing significant challenges for purely data-driven approaches. Additionally, deep learning models generally struggle in extrapolation regimes, which are common for assets characterized by long service lives and the frequent emergence of new operating regimes. 

In response to these challenges, the integration of physical laws and principles with deep learning methodologies has shown tremendous promise. This presentation will explore a variety of approaches that combine physics-based concepts with deep learning techniques. One focus will be on how incorporating structural inductive biases into learning architectures, such as through physics-enhanced graph neural networks, can address the aforementioned challenges.

To close the loop and bridge machine learning with physics, the talk will delve into novel approaches of symbolic regression through reinforcement learning to uncover symbolic equations.

Biographical Sketch: Olga Fink has been assistant professor of Intelligent Maintenance and Operations Systems at EPFL since March 2022.  Olga’s research focuses on Hybrid Algorithms Fusing Physics-Based Models and Deep Learning Algorithms, Hybrid Operational Digital Twins, Transfer Learning, Self-Supervised Learning, Deep Reinforcement Learning and Multi-Agent Systems for Intelligent Maintenance and Operations of Infrastructure and Complex Assets.

Before joining EPFL faculty, Olga was assistant professor of intelligent maintenance systems at ETH Zurich from 2018 to 2022, being awarded the prestigious professorship grant of the Swiss National Science Foundation (SNSF). Between 2014 and 2018 she was heading the research group “Smart Maintenance” at the Zurich University of Applied Sciences (ZHAW).

Olga received her Ph.D. degree from ETH Zurich with the thesis on “Failure and Degradation Prediction by Artificial Neural Networks: Applications to Railway Systems”, and Diploma degree in industrial engineering from Hamburg University of Technology. She has gained valuable industrial experience as reliability engineer with Stadler Bussnang AG and as reliability and maintenance expert with Pöyry Switzerland Ltd.

Olga has been a member of the BRIDGE Proof of Concept evaluation panel since 2023. Moreover, Olga is serving as an editorial board member of several prestigious journals, including Mechanical Systems and Signal Processing, Engineering Applications of Artificial Intelligence, Reliability Engineering and System Safety and IEEE Sensors Journal.

In 2018, Olga was honored as one of the “Top 100 Women in Business, Switzerland”. Additionally, in 2019, earned the distinction of being recognized as a young scientist of the World Economic Forum. In 2020 and 2021, she was honored r as a young scientist of the World Laureate Forum. In 2023, she was distinguished as a fellow by the Prognostics and Health Management Society.

Abstract: Water management is one of the most critical issues in proton exchange membrane fuel cells (PEMFCs). The water generated in catalyst layer as a product of the electrochemical reaction is mainly transported through porous media by diffusion if it’s vapor, or by capillarity in case of liquid. In flow channels, the liquid water is removed primarily by inertial force of the gas flows. In my research group (Multiscale Transport Process Laboratory) at Michigan Technological University, one of our focused research areas is the gas-liquid two-phase transport processes in PEMFCs.

In various aspects of the two-phase transport phenomena, this presentation is focused on the impact of land-channel geometry. If we look at the cross-section of PEMFC, land-channel geometry causes the difference in transport distance between the flow channel to the catalyst layer, and results in the uneven distribution of various factors, such as transport resistance, species concentration, and current generation. In order to investigate the distributions of various parameters in the land-channel direction, we developed a small-scale segmented cell with about 350-micron resolution, and successfully measured the current and high-frequency resistance distribution in the land-channel direction for two different flow fields.

Biographical Sketch: Dr. Kazuya Tajiri is an associate professor of Department of Mechanical Engineering-Engineering Mechanics at Michigan Technological University. He has obtained his Bachelor degree in Aeronautics and Astronautics from University of Tokyo, Master degree in Aerospace Engineering from Georgia Institute of Technology, and Ph. D in Mechanical Engineering from The Pennsylvania State University. After obtaining a Ph.D degree, he worked at Argonne National Laboratory as a postdoctoral researcher, and then in 2010 he joined Michigan Technological University as an assistant professor. He also has work experience at Nissan Research Center in Yokosuka, Japan. In 2013, he was selected as one of the finalists for the Distinguished Teaching Award at Michigan Technological University.