Enhancement of Phase-Change Thermal Management of Microelectronics Using Engineered Surface Structures Sushil H. Bhavnani Associate Chair, Department of Mechanical Engineering Professor and Henry M. Burt Jr. Endowed Chair Auburn University Room 1010 DOW Tuesday, December 6, 2022 4:00 p.m. ME Seminar Zoom link Passcode 309714 Add ME Seminar to Google Calendar Abstract The dramatic increase […]
Nanoscale dual-phase alloys composed of alternate metal (soft) and intermetallic or covalently bonded (hard) strengthening phase exhibit high strength, high strain hardening rate, and measurable plasticity at ambient and elevated temperatures. Here we report unusual plasticity carriers in intermetallic Al 2 Cu and covalently bonded Silicon in Al-Si and Al-Cu alloys based on multiscale experiments and modeling.
Therapeutic tissue regeneration using stem cells has been hampered by the controversial identity of resident stem cells, low cell retention/engraftment, tumorigenecity and immunogenicity issues. Taking a bioengineering/biomaterials approach, this lecture will introduce the uses of drug delivery and biomaterials strategies to generate more potent cell therapies for heart and lung diseases.
We are working to accomplish for cells something akin to what a shepherd and sheepdogs bring to flocks of sheep: control over large-scale collective cellular motion. As coordinated cellular motion is foundational to many forms of multicellular life, being able to ‘herd’ or program large-scale cell migration raises exciting possibilities for accelerated healing, tissue engineering, and novel biomaterials.
The ability to move is a trait of all animals. Yet how do animals, including ourselves, get around in this complex and uncertain world with an ease and agility we find hard to recreate in engineered systems?
We present a framework of predictive modeling of unknown system from measurement data. The method is designed to discover/approximate the unknown evolution operator behind the data. Deep neural network (DNN) is employed to construct such an approximation. Once an accurate DNN model for evolution operator is constructed, it serves as a predictive model for the unknown system and enables us to conduct system analysis.
High-speed shear flows are often characterized by some kind of aeroacoustic resonance phenomenon. Supersonic jets, particularly those that contain shock structures, produce high-intensity and discrete-frequency acoustic tones associated with an aeroacoustic feedback loop. While these jets and their associated resonances have been the subject of study for seventy years, our understanding of what physical mechanisms underpin the resonance has changed drastically in the past decade.
Midwest Mechanics Seminar Series Data-Driven Nonlinear Reduced-Order Modeling for Solid and Fluid Mechanics George Haller Chair in Nonlinear Dynamics ETH Zurich Monday, March 27, 2023 Johnson Room, LEC 4:00 p.m. Midwest Mechanics Zoom Link Passcode 465648 Add to calendar Abstract Machine learning has been a major development in applied science and engineering, with impressive success […]
Architected materials are lightweight with high specific strength and excellent energy absorption, holding great promise for a range of applications, including automobiles, aerospace, and space. However, the absolute strength of such materials is low due to the removal of base material. To enhance the strength, stretch-dominated architectures are used, but they suffer post-yield collapses, severely limiting their energy absorption and post-yield stability, which are critical for structural applications.
Mechanical Engineering Seminar Series Tailoring Surface Chemistry and Surface Roughness to enable the Long-Term Stable Dropwise Condensation of Steam and Refrigerant Working Fluids Nenad Miljkovic Professor; Kritzer Faculty Scholar Mechanical Science & Engineering University of Illinois at Urbana-Champaign Room 1200 EECS Tuesday, April 4, 2023 3:00 PM ME Seminar Zoom link Passcode 309714 Add ME […]
The use of sound has a long history in medicine. Dating back to 350 BC, the ancient Greek physician Hippocrates, regarded as “the father of medicine,” devised a diagnostic method for detecting fluid in the lungs by shaking patients by their shoulders and listening to the resulting sounds emanating from their chest. As acoustic technology has advanced, so too has our ability to “listen” to the body and better understand underlying pathologies.
Peng Chen is currently a tenure-track assistant professor in the School of Computational Science and Engineering at Georgia Tech. In this talk, he will present a novel machine learning framework for solving optimization problems governed by large-scale partial differential equations (PDEs) with high-dimensional random parameters.