Author: Orlando E

David Pierce receives the 2017 NSF CAREER award for his work on collagen microcracks.

This is the National Science Foundation’s most prestigious award to support early-career faculty to become role models in integrating outstanding research and educational objectives to advance the mission of their departments.

Osteoarthritis afflicts nearly 20% of the US population; costs over $185.5BN a year (2007); and causes pain, functional limitations, lost earnings and depression – yet we understand neither its cause nor progression. Researchers have extensively characterized microcracks in bone and sub-millimeter-scale fissures in osteoarthritis, but Dr. Pierce’s lab recently discovered that impact usually considered non-injurious in fact causes micrometer-scale cracks in collagen of human cartilage. These microcracks may lead to pre-clinical osteoarthritis, but the extent to which they grow under repetitive loads during normal daily activities is unknown.

Prof. Pierce’s project, titled “Understanding Collagen Microcracks in Soft Tissues Under Normal Body Loads,” proposed to perform fundamental research to understand growth of collagen microcracks in soft tissues by validating novel computer simulations with new experimental data. Understanding and modeling cartilage microcracks will likely lead to new therapies and/or lifestyle modification strategies for osteoarthritis patients. The research will not only investigate the characterization of one of the earliest observable signs of deterioration likely related to osteoarthritis, but also facilitate studies of other tissues and engineering materials.

 

Prof. Julian Norato awarded the 2017 ONR Young Investigator Award

UConn assistant professor Julian Norato is part of an exclusive group pf 34 scientists nationwide that have been selected to receive The Office of Naval Research Young Investigator Award, which supports early career academic scientists and engineers that “show exceptional promise for doing creative research.”

Prof. Norato’s project, titled “Computational Synthesis of Composable-Material Structures from Manufacturing-Friendly Primitives”, will advance topology optimization methods for the design of structures made with composite materials with consideration for their manufacturing.   Topology optimization is a computational technique that determines the optimal distribution of material within a given space to, for example, design the lightest structure that will not mechanically fail under applied loads. Existing topology optimization methods excel at exploring designs made of homogeneous, isotropic materials—that is, materials that have uniform, direction-independent properties throughout the structure.  However, there is a substantial need to advance topology optimization techniques that render designs that are made of heterogeneous, anisotropic materials, such as composite materials, and that take into consideration the geometric requirements of existing composite manufacturing processes.  By exploring designs that take advantage of the unique properties of composite materials and that can be more readily translated to fabrication, the techniques advanced by this project have the potential to render significant weight savings and improve the mission performance of Naval aircraft and ship structures.

 

Prof. Norato leads UConn’s Structural Optimization Laboratory where he and his graduate students develop computational state-of-the-art computational approaches to:

  • Incorporate realistic failure mode criteria
  • Render designs that are cost-effective and/or close-to-fabrication for a given manufacturing process
  • Simultaneously consider the design of a structure and a material system

These capabilities will expand the role of computational design of structures and material systems in the early concept design and advance our ability to push the limits of physical performance (including multifunctional systems), lightweight, and cost effectiveness beyond what is possible today.

 

 

Prof Jiong Tang honored by the ASME Hartford chapter.

Prof. Jiong Tang is honored with the Distinguished Engineer of the Year Award presented by the ASME Hartford Section during 2017 Annual Engineer’s Night Awards Banquet.

From left: Profs. Xu Chen, Horea Ilies, ZhanZhan Jia, Xinyu Zhao, Jiong Tang, Vito Moreno, Dianyun Zhang, Thanh Nguyen, Abhishek Dutta.
ASME 31st Annual Engineer’s Night and Awards Dinner

Celebrating women’s contributions to aerospace history and technology with Prof. Dianyun Zhang.

On March 11th 2017, Prof. Dianyun Zhang, graduate student Weijia Chen, and senior Mechanical Engineering students Meagan Ferreira and Nomin Munkhbat attended the “Women Take Flight” event hosted by the New England Air Museum located in Windsor Locks, CT. The event featured activities and presentations celebrating women’s contributions to aerospace history and technology.


Dr. Zhang represented UConn’s Mechanical Engineering department at the event to promote engineering to young children by showing new advancements. Specifically, the group demonstrated how composites are manufactured to the young boys and girls (as well as adults) who attended the event. Curious guests were shown that carbon fiber and the glass fiber are flexible and soft. Then they were asked if they could assess the composite panels, and if they believed they were made from those same materials. Guests were then told about the VARTM (vacuum assisted resin transfer molding) process, and exactly how those flexible fibers can become as tough as metal through curing. It was also explained how the composites are replacing airplane parts that generally use metal. (Contributed by Nomin Munkhbat and Meagan Ferreira)

Prof. Xinyu Zhao receives funding from NSF:CISE:CRII to perform large-scale fire simulations.

The project entitled “Efficient Radiative Heat Transfer Modeling in Large-Scale Combustion Systems” will optimize the a legacy radiative heat transfer code from Prof. Zhao’s lab on the Intel Xeon Phi Knights Landing processors. Currently Prof. Zhao is working with a graduate student (Peiyu Zhang) and an undergraduate student (Andrew Caratenuto) on test problems that are representative of the full-scale problems. Significant speedup has already been observed on knights landing using these test problems.

Towards Cognitive Design Assistants

Friday, February 17 • 2:30 PM – BPB, Rm. 130

Towards cognitive design assistants and mixed-initiative design of complex systems

Daniel Selva, Assistant Professor

Sibley School of Mechanical and Aerospace Engineering
Cornell University, Ithaca, New York 14853

 

Abstract: Much research in engineering design has focused on making design tools more intelligent by means of optimization, machine learning, and artificial intelligence. The Holy Grail has been to one day be able to do automatic design of complex systems such as spacecraft. This line of research essentially casts design tools as intelligent agents. We thus identify an opportunity to turn into the Intelligent Systems and Human-Agent Interaction fields to get insights about what proved effective in other application areas. Traditionally, the intelligent systems field emphasized fully automated and autonomous agents to tackle complex but structured tasks in well-characterized environments. Increasingly, however, a significant portion of the research has shifted towards human-machine collaboration in order to solve more unstructured tasks in unpredictable environments. This emphasis on mixed teams raises new challenges and questions, such as how to give design agents self-explaining abilities, explore new roles for humans and machines in these collaborations, and facilitate knowledge discovery.

In this talk, I will focus on how to discover and leverage knowledge in mixed-initiative design. First, I will show how the effectiveness of design space exploration algorithms can be improved by using adaptive operator selection algorithms that use domain-independent operators in combination with heuristics encoding expert knowledge. Then, I will show how visual and data analytics can be used to foster discovery and generalization of patterns that appear consistently in good designs. Finally, I will share my thoughts on what I think lies ahead in the exciting new field of design.

 

Biographical Sketch: Daniel Selva received a PhD in Space Systems from MIT in 2012, and he is an Assistant Professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University and in the Systems program, where he directs the Systems Engineering, Architecture, and Knowledge (SEAK) Lab. His research interests focus on the application of knowledge engineering, global optimization and machine learning techniques to systems engineering, design, and architecture, with a strong focus on space systems. Prior to MIT, Daniel worked for four years in Kourou (French Guiana) as an avionics specialist within the Ariane 5 Launch team. Daniel has a dual background in electrical engineering and aeronautical engineering, with degrees from Universitat Politecnica de Catalunya in Barcelona, Spain, and Supaero in Toulouse, France. He is also a Faculty Fellow at the Mario Einaudi Center for International Studies, and a member of the AIAA Intelligent Systems Technical Committee.

 

For additional information, please contact Prof. Ying Li at (860) 486-7110, yingli@engr.uconn.edu or

Laurie Hockla at (860) 486-2189, hockla@engr.uconn.edu

Prof. Julian Norato develops topology optimization with welded plate structures.

Prof. Julian Norato is developing computational techniques for welded plate structures in conjunction with Caterpillar, Inc. These techniques can be a powerful design tool to explore the design of structures from a blank sheet.

Dr. Norato with his student Shanglong Zhang, with funding from Caterpillar, are developing computational techniques for the design of structures made of welded plates, such as those encountered in large structures for heavy machinery and ship structures.

Their work is focused on topology optimization — a computational technique that determines the optimal spatial distribution of material within a space envelope to, for example, design the lightest structure that will not mechanically fail under applied loads.  This technique is a powerful engineering design tool to explore the design of structures starting from a blank sheet. Existing topology optimization techniques produce complex, organic designs that cannot be readily fabricated by welding plates.  In order to be most economical, this current process in many cases results in the production of large, strong structures typically made of steel. This is the case with the main structures of heavy machinery and ships.  Dr. Norato’s topology optimization method renders designs that are made exclusively of constant-thickness plates which can be welded, which greatly facilitates the translation of the topology optimization result to a design concept of the structure that is amenable to fabrication.

Transport of Heat & Momemtum in Non-Equilibrium Wall-Bounded Flows

Friday, November 18 • 2:30 PM – UTEB, Rm. 175

 

Christopher White, Associate Professor of Mechanical Engineering

University of New Hampshire, Durham, NH 03824

Abstract: Non-equilibrium wall-bounded flows, in which perturbation time scales are comparable to turbulent flow time scales, do not exhibit universal behaviors and cannot be characterized only in terms of local parameters. Pressure gradients, fast transients and complex geometries are among the sources that can perturb a flow from an equilibrium state to a non-equilibrium state. Since all or some of these perturbation sources are present in many engineering application relevant flow systems and geophysical flows, understanding and predicting the non-equilibrium flow dynamics is essential to reliably analyze and control such flows. This talk will describe zongoing work using complementary numerical and physical experiments to better understand the underlying physics, transition dynamics, and appropriate flow scaling in non-equilibrium, periodic wall-bounded flows. The overarching goal is to use the results from these scientific investigations to improve upon the robustness of engine computational fluid dynamics (CFD) models so that they can be used for engineering design of low emission, high-efficiency piston engines.

Biographical Sketch: Dr. White received his Ph.D. in Mechanical Engineering from Yale University in 2001. From 2001-2004 he was Postdoctoral Research Fellow at Stanford University. Following his post-doctoral work, he joined Sandia National Laboratories as a Senior Member of the Technical Staff in the Combustion Research Facility. His principal duties at Sandia included lead investigator in the Advanced Hydrogen Fueled Engine Laboratory. In 2006, he joined the Mechanical Engineering Faculty at the University of New Hampshire.

Dr. White’s research is broadly motivated by applications related to the production, storage, distribution, conversion, and end-use applications of energy. His research to date is of both fundamental and applied nature in the areas of combustion, piston engines, biomass, ocean energy, and turbulent drag reduction. His 2006 paper “The hydrogen-fueled internal combustion engine: a technical review” is designed as a Highly Cited Paper (top 1% in the field of engineering) by the Thompson Reuters Essential Science Indicators. He co-authored an Annual Review of Fluid Mechanics paper in 2008 titled “Mechanics and prediction of turbulent drag reduction with polymer additives”. In 2009, he received an NSF CAREER award to study the flow properties and rheology of liquefied biomass suspensions. He currently has funding from NSF, DOE, and ONR.

For additional information, please contact Prof. Ying Li at (860) 486-7110, yingli@engr.uconn.edu or Laurie Hockla at (860) 486-2189, hockla@engr.uconn.edu