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Speaker: Mahmoud Hussein

Affiliation: Professor, Ann and H.J. Smead Department of Aerospace Engineering Sciences, �鶹ӰԺ

Date / Time: Wednesday, December 4, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract:

Flow control is a many-decades old engineering problem of a multi-disciplinary nature. It aims at “altering the natural flow state or developing path into a more desired state (or path)” [Collis et al., Prog. Aerosp. Sci., 2002]. For streamlined bodies cruising through a flow, such as air, there has been a particular interest in the control of flow instabilities as a means to delay laminar-to-turbulent transition, and hence reduce skin-friction drag. A reduction in drag enables improvements in fuel efficiency.

In collaborative work with Prof. Sedat Biringen’s group, we have shown that “phonon” motion underneath a surface interacting with a flow may be tuned to cause the flow to stabilize, or destabilize, as desired [Hussein et al., Proc. R. Soc. A, 2015]. The underlying control mechanism utilizes two core concepts from crystal physics, namely, the principle of destructive interferences and the notion of symmetry breaking. This approach represents an unprecedented capability to passively synchronize wave propagation across the interface of a structure and a flowing fluid, and achieve favorable, and predictable, alterations to the flow properties.

Bio:

Mahmoud I. Hussein received his PhD degree from the University of Michigan-Ann Arbor in 2004. After spending two years at the University of Cambridge as a postdoctoral research associate, he joined CU �鶹ӰԺ as a faculty member in 2007.

Dr. Hussein’s research focuses on the dynamics of materials and structures, especially phononic crystals and locally resonant phononic metamaterials, at both the continuum and atomistic scales. His approach to phononics is rather broad ranging from vibrations of aerospace structures and passive flow control to lattice dynamics and thermal transport in silicon-based nanostructured materials. His studies are concerned with physical phenomena governing these systems, relevant theoretical and computational treatments, and analysis of the effects of dispersion, resonance, dissipation, and nonlinearity. Dr. Hussein is a Fellow of ASME and the founding vice president of the International Phononics Society.

Speaker: Karen Mulleners

Affiliation: Assistant Professor, Institute of Mechanical Engineering, EPFL, Switzerland

Date / Time: Friday, November 22, 2019, 12:30 - 1:30 pm

​Location: AERO 120

Abstract: 

Dynamic stall on pitching airfoils is an important practical problem that affects for example rotary wing aircraft and wind turbines. It also comprises a number of interesting fundamental fluid dynamical phenomena such as unsteady flow separation, vortex formation and shedding, unsteady flow reattachment, and dynamic hysteresis. Experimental time-resolved velocity field and surface pressure data for two-dimensional pitching airfoils with various reduced frequencies was analysed using different Eulerian, Lagrangian, and modal decomposition methods. These complementary analyses resulted in the identification of the chain of events that play a role in the stall onset and the stall recovery process. The individual events will be characterised by their governing time-scales and flow features and recent modelling attempts will be presented.

Bio: 

Karen Mulleners is an assistant professor in the institute of mechanical engineering at EPFL in Switzerland since 2016. She is the head of the unsteady flow diagnostics laboratory (UNFoLD) and focusses on unfolding the origin and development of unsteady flow separation. Karen studied physics in Belgium and the Netherlands and received her PhD in mechanical engineering from the Leibniz Universität Hannover in Germany.

Speaker: Riccardo Balin

Affiliation: PhD Candidate, Aerospace Mechanics Research Center (AMReC), Ann and H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado at �鶹ӰԺ

Date / Time: Wednesday, November 13, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract: 

Computations of turbulent flow can either resolve all the scales, only the most relevant ones, or resolve none of them. As fewer scales are resolved, additional modeling of the effects of the unresolved scales must be introduced, leading to a reduction in the accuracy of the computation. In a direct numerical simulation (DNS), all scales are resolved and no modeling is required, however, due to the large separation of scales in turbulence, the computational cost is often prohibitive. On the other end of the spectrum, none of the turbulent scales are resolved when the governing equations for the mean flow are solved, namely the Reynolds-averaged Navier-Stokes (RANS) equations. RANS computations can give solutions to complicated flows in hours, but the amount of modeling required leads to a level of confidence in the predictions that is often not acceptable for many important engineering flows. A compromise between resolution and modeling of turbulent scales can be achieved with Large Eddy Simulation (LES), wherein the larger eddies are resolved by the grid and the smaller, unresolved (sub-grid) eddies are modeled. LES of many engineering flows is still impractical, with most of the expense of the computation coming from the need to resolve the near-wall eddies. Significant savings are thus obtained by not resolving the scales in the inner layer, and instead modeling their effects with a strategy referred to as wall-modeled LES (WMLES). This reduced cost makes WMLES attractive to a wide range of aerodynamic problems, and has been shown to provide more accurate solutions relative to RANS for complex flows. However, wall-models have also been shown to fail to reproduce the relevant physics in some important flow problems. By studying a simplified but representative flow case, this research aims at challenging WMLES allowing us to study its failures as well as offer improvements to current  near-wall models. The turbulent boundary layer over a smooth Gaussian-shaped bump is computed with DNS and WMLES, and results are compared to outline the deficiencies of WMLES. The two-dimensional bump causes a rapid succession of favorable-to-adverse pressure gradients that leads to shallow separation on the downstream side, both of which are characteristic of many aeronautical flows.

Bio:

Riccardo Balin is a PhD student in the Ann and H. J. Smead Aerospace Sciences Department at the �鶹ӰԺ working with Prof. Ken Jansen. Native of Italy, he moved to �鶹ӰԺ to pursue a degree in Aerospace Engineering. He graduated with a BS/MS in 2016, with his masters thesis work focusing on turbulence modeling and high-lift flows also under Prof. Jansen. He then decided to continue his studies with a Doctorate, diving deeper into turbulence modeling, and in particular hybrid RANS-LES and wall-modeling for aeronautical flows. 

Speaker: Subhayan De

Affiliation: Post-doctoral Research Associate, Aerospace Mechanics Research Center (AMReC), Ann and H.J. Smead Department of Aerospace Engineering Sciences, University of Colorado at �鶹ӰԺ

Date / Time: Wednesday, November 6, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract:

In simulation-based engineering, models, often in the form of discretized differential equations, are used for purposes such as design space exploration, uncertainty quantification, and design optimization. In general, many linear and nonlinear models are available to describe a physical phenomenon. For effective usage, these models must also incorporate the ubiquitous presence of uncertainties in material properties and geometry of a structure. However, the number of models and model classes available to the modeler to represent a physical phenomenon can be very large. This poses a significant problem of identifying valid models to be used for further studies because retaining all available models throughout a study can be computationally burdensome. In this talk, a probabilistic hybrid framework for validating models by intertwining the concepts of model falsification and Bayesian model selection will be discussed. Further, in the presence of uncertainty, we most often seek robust design of structures that provide a compromise between average performance and insensitivity to variation in geometry, material properties. To achieve this, a novel approach of using stochastic gradients for topology optimization of structures under uncertainty will also be discussed.

Bio:

Dr. Subhayan De is a postdoctoral associate at CU-�鶹ӰԺ. His research at CU focuses on design optimization under uncertainty and physics-based machine learning. Subhayan received his Ph.D. in Civil Engineering from the University of Southern California in 2018, where he was supported by the Viterbi Ph.D. Fellowship and Gammel Scholarship. At USC, he worked on probabilistic model validation, machine learning, uncertainty quantification, and structural control design. Subhayan also holds an MS in Electrical Engineering from USC and an MEng in Structural Engineering from the Indian Institute of Science, Bangalore. He received his B.Eng. in Civil Engineering from Jadavpur University, Kolkata.

Speaker: Ryan King

Affiliation: Senior Scientist, Computational Science Center, National Renewable Energy Laboratory (NREL)

Date / Time: Wednesday, October 23, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract: 

In recent years, machine learning techniques have experienced a surge in popularity with particular interest being paid to the integration of data-driven methods with first-principles scientific approaches.  In this talk, we discuss physics-informed deep learning techniques leading to new architectures and training methods that are well suited for turbulent flow simulations arising in renewable energy.  We demonstrate our physics-informed framework on in-situ data compression with an autoencoder, generation of new turbulent inflow realizations with adversarial training, and super resolution of coarse simulations with convolutional neural nets.  Our autoencoder is generalizable across a range of canonical flows and compares favorably against single pass SVD approaches for in-situ compression of large datasets.  We also achieve a 50x super resolution of climatological wind and solar data from recent IPCC studies that enables renewable energy resource assessments in future climate scenarios.  We conclude with a discussion of how these advances are made possible by the development of novel scientific perceptual loss networks that provide sophisticated and physics-informed training objectives.

Bio:

Dr. Ryan King is a senior scientist in the Computational Science Center at the National Renewable Energy Laboratory (NREL).  His research focuses on optimization, machine learning, and uncertainty quantification (UQ) applied to complex energy systems and turbulent flows.  At NREL he leads projects on physics-informed deep learning, wind farm surrogate modeling and layout optimization, and multi-fidelity UQ.  Ryan received his PhD in Mechanical Engineering from CU �鶹ӰԺ where he developed adjoint optimization techniques to improve wind plant design, and developed a new data-driven machine learning closure for turbulence modeling in large eddy simulations.  Ryan received a BS in Mechanical Engineering from MIT and later worked as an engineer at RES Americas where he was involved in the design and construction of over 750 MW of operational wind energy. 

Speaker: Massimo Ruzzene

Affiliation: Professor, Mechanical Engineering & Associate Dean for Graduate Programs, �鶹ӰԺ

Date / Time: Wednesday, October 9, 2019, 2:30 - 3:30 pm

​Location: AERO N240

Abstract:

The presentation will provide an overview of research activities in the broad areas of structural dynamics and wave propagation, with emphasis on applications related to structural health monitoring, vibration and noise control, and wave steering and guiding. Novel concepts related to the theme of metastructures will be specifically described in relation to fundamental principles inspired by solid state physics analogues and their potential engineering applications. These novel structural assemblies feature unprecedented performance in terms of stress wave mitigation, wave guiding for information transport, acoustic absorption, and vibration isolation, and generally rely on complex arrangements of materials and geometrical features. Beyond structural dynamics, the geometric complexity of these components has inspired novel transducers for non-destructive evaluation and strain sensing, and is currently being investigated in the context of aerodynamic flow control where interactions between lifting surfaces and actively controlled air bleed are exploited to affect the aerodynamic and aeroelastic performance of wing structures.

Bio:

Massimo Ruzzene is the Slade Professor of Mechanical Engineering at CU �鶹ӰԺ. He joined CU in the summer of 2019, after serving as the Pratt and Whitney Professor in the Schools of Aerospace and Mechanical Engineering at Georgia Institute of Technology. M. Ruzzene received a PhD in Mechanical Engineering from the Politecnico di Torino (Italy) in 1999. He is author of 2 books, more than 180 journal papers and 240 conference papers. He has participated as a PI or co-PI in various research projects funded by the Air Force Office of Scientific Research (AFOSR), the Army Research Office (ARO), the Office of Naval Research (ONR), NASA, the US Army, US Navy, DARPA, the National Science Foundation (NSF), as well as companies such as Boeing, Eurocopter, Raytheon, Corning and TRW. Most of his current and past research work has focused on solid mechanics, structural dynamics and wave propagation with application to structural health monitoring, metamaterials, and vibration and noise control. M. Ruzzene is a Fellow of ASME, an Associate Fellow of AIAA, and a member of AHS, and ASA. He served as Program Director for the Dynamics, Control and System Diagnostics Program of CMMI at the National Science Foundation between 2014 and 2016.

Speaker: John Farnsworth

Affiliation: Assistant Professor, Ann and H.J. Smead Department of Aerospace Engineering Sciences, �鶹ӰԺ

Date / Time: Wednesday, October 2, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract:

The field of flow control is nearly as old as the study of aeronautics. Prandtl utilized wall suction to modify flow separation and study the physics of boundary layers in 1904. Yet active flow control techniques have seen limited implementation in aeronautical systems throughout the last century. This talk will review the theory and implementation of flow control from the classical to the modern era. Specific attention will be paid to the implementation of separation control, including the application of reducing structural vibrations in wind turbine blades and the role of synthetic jet vortex dynamics in reattaching flow over a vertical tail-rudder assembly.

Bio:

Dr. Farnsworth is an Assistant Professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences at the �鶹ӰԺ. Prior to joining the faculty in 2014, he served as a Postdoctoral Research Associate in the Department of Aeronautics at the United States Air Force Academy for three years. Dr. Farnsworth received his Ph.D. in Aeronautical Engineering from the Rensselaer Polytechnic Institute (RPI) in 2011. He also received both his B.S. and M.S. in Aeronautical Engineering from RPI in 2006 and 2007, respectively. Dr. Farnsworth is the director of the Experimental Aerodynamics Laboratory, and his research is focused in the areas of understanding and controlling complex three-dimensional unsteady flow fields for aerodynamic applications. These topics include, but are not limited to: fluid-structure interactions, turbulence, highly three-dimensional regions of flow separation, and the design of novel fluidic actuators for flow control.

Speaker: Kai James

Date / Time: Friday, September 27, 2019, 12:30 - 1:30 pm

​Location: AERO 120

Abstract:

Topology optimization is a powerful and well-established tool for generating optimal structural designs. Unlike the sizing and shape optimization approaches that preceded it, this method simultaneously optimizes both the shape and topology of the structure, thus creating the potential to algorithmically generate novel design concepts and configurations with minimal input from human designers. This capability makes topology optimization a potential key ingredient in the quest to achieve automated design of complex mechanical systems. This talk will discuss our ongoing efforts to expand the capability of the topology optimization method to enable computational synthesis of kinetic structures. This unique class of structures is designed to exhibit precisely tailored motion, while maintaining structural integrity. The talk will present our general methodology and results from several example problems including optimal design of a bi-stable airfoil, multimaterial design of self-actuating mechanisms containing shape memory polymers, and topology optimization of multi-body mechanisms. The talk will conclude with a discussion of ongoing and future research projects in which we explore the use of topology optimization for the design of soft robots and compound machines.

Bio:

Kai James is an Assistant Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign, and the Principal Investigator of the Computational Design Innovation Lab at UIUC. From 2012 to 2015, he was a postdoc in the Computational Mechanics Group at Columbia University, and he earned his PhD in aerospace engineering from the University of Toronto in 2012. His research focuses on computational solid mechanics and computational design optimization with an emphasis on problems involving various sources of nonlinearity, such as viscoelastic creep, superelasticity, and large deformations. He is especially interested in developing novel algorithms that leverage high-fidelity computational models and topology optimization methods for conceptual design and synthesis of complex engineering structures. Some of his major research projects include aerostructural optimization of transonic aircraft wings, structural design optimization of a cardiovascular stent, optimal design of a bi-stable airfoil, and computational synthesis of multi-body systems. Dr. James is the recipient of the NSF CAREER award and has also received several teaching honors, including being named “Teacher of the Year” by the UIUC chapter of AIAA in 2017.

Speaker: Demet Ulker

Date / Time: Wednesday, September 18, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract:

Decision-making in design and operation of complex systems requires (a) description of the system and its operating environment using multi-disciplinary, multi-fidelity models, (b) quantification and modeling of uncertainties with our descriptions, (c) definition of objectives such as performance, reliability and robustness, and (d) design of decision-making policies. Typically, the decision-making process involves sequential feedback loop, where we keep track of the objectives and evolution of uncertainties using the response of the system to actions. In design, while a resource allocation problem can be considered as a decision-making process, where exploration and exploitation tradeoffs are assessed quantitatively. In operation, decision-making process can be our very familiar feedback control system loop.  In this talk, I will present a formulation and a solution of decision-making process for two interesting problems. The first one is the resource allocation problem in design of wind energy systems in mountainous terrains, and the second one is active vibration control of helicopters for smooth flight. We will discuss the challenges in formulations and the consequences of our beliefs in uncertainties in the system and its operating environment.

Bio:

Demet Ulker received her degrees in Aerospace Engineering,  BS and MS degrees from Middle East Technical University, Turkey and PhD from Carleton University, Canada and Post-Doc at Massachusetts Institute of Technology (MIT), USA. She worked in Aeroacoustic and Structural Dynamics Lab., at National Research Council, Helicopter division of Turkish Aviation Industry (TAI), and Envision Energy, �鶹ӰԺ, CO.

Speaker: Kurt Maute

Affiliation: Professor, Palmer Endowed Chair, Ann and H.J. Smead Department of Aerospace Engineering Sciences, �鶹ӰԺ

Date / Time: Wednesday, September 11, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract:

In the past 25 years, topology optimization methods have made significant progress, evolving into practical design tools. Initially restricted to two-phase, solid-void design problems in linear elasticity, optimization approaches for multi-physics and multi-phase problems have emerged. This talk will provide an overview of topology optimization approaches for problems in solid and fluid mechanics, discussing density and level set methods. The potential of topology optimization for studying fundamental problems in engineering sciences and for practical engineering problems will be demonstrated with a few cases studies.

Bio:

Since 2000, Dr. Maute is a professor of aerospace engineering in the Department of Aerospace Engineering Sciences at the �鶹ӰԺ. Dr. Maute and his research group focus on the development of design optimization methods for fundamental problems in solid mechanics, fluid mechanics, and heat transfer with applications to aerospace and mechanical engineering systems. For the past 25 years, Dr. Maute has worked on topology and shape optimization methods for a broad range of problems, including coupled multi-physics and multi-scale problems. His research has been supported by NSF, AFOSR, DOE, and industry.

Speaker: James G. Brasseur

Affiliation: Research Professor, Ann and H.J. Smead Department of Aerospace Engineering Sciences, �鶹ӰԺ

Date / Time: Wednesday, September 4, 2019, 4:30 - 5:30 pm

​Location: AERO 114

Abstract: 

Dissolution and absorption occur within the intestines, enhanced and driven by contractions of the intestinal wall muscles (motility). The complex hydrodynamic environment of the human intestines is driven by a wide range of motility patterns associated with “fed” vs. “fasting” physiological states. We contrast the hydrodynamic influences on dissolution and absorption from distributions of drug particles in vivo with the hydrodynamic and non-absorptive environment of in vitro testing devices. To this end, we developed a “high-performance computing” framework in which computational fluid dynamics (CFD) is integrated with a first-principles-based mathematical model to predict dissolution from thousands of drug particles as they are transported with the flow and absorption. Using high-resolution CFD we developed a set of empirical relationships for shear-rate-enhanced drug dissolution that were validated at the University of Michigan using a Couette-flow device. We show that the shear hydrodynamic effect is important both in vivo and in vitro, that the shear effect strongly dominates convection in vivo, and that shear-rate differences distinguish in vitro from in vivo dissolution. Using an intestinal CFD model we show that the hydrodynamic shear effect leads to up to 65% enhancement in absorption in vivo with peristaltic motility, and that the local balance between drug release and absorption in vivo is strongly influenced by hydrodynamic effects.

Acknowledgements: This research was carried out with Dr. Farhad Behafarid at the �鶹ӰԺ and with Dr. Yanxing Wang at Georgia Tech. Collaborations include Drs. Greg and Gordon Amidon and Deanna Mudie at the University of Michigan.

Speaker Bio: 

James Brasseur (Jim) is currently Research Professor of Aerospace Engineering Sciences at the �鶹ӰԺ after 27 years as Professor of Mechanical Engineering, Biomedical Engineering and Mathematics at the Pennsylvania State University, where he retains Emeritus and Adjunct Professor status. Dr. Brasseur is a fluid dynamist with extensive expertise in two general of research: (1) turbulence physics and simulation, and modeling within the large-eddy simulation framework, with applications to atmospheric turbulence, wind turbine aerodynamics and turbulent combustion; (2) fluid and solid mechanics integrated within physiology and function of the gastro-intestinal (GI) tract, as well as related issues in drug delivery, including dissolution, transport and absorption in the GI tract and in vitro devices. Dr. Brasseur has served on governing boards of the American Physical Society (APS), the APS Division of Fluid Dynamics, and two medical societies. was president of a medical society and was founding chair of the APS Topical Group on the Physics of Climate. Dr. Brasseur is a member of the Johns Hopkins Society of Scholars and is Fellow of the American Physical Society through the Division of Fluid Dynamics.

Speaker: Arun Majumdar
Affiliation: Director, Precourt Institute for Energy, Jay Precourt Professor and Professor of Mechanical Engineering and of Photon Science, Stanford University
​Location: AERO 114
Time: 11:30 a.m., Reception to follow at 12:30 p.m.

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Abstract: 

Part 1: Nanofluidics: From Ionic and Molecular Transport to Cryo-EM Imaging - The intermolecular forces - van der Waals, electrostatic or steric forces - between molecules and between molecules and solid surfaces fall in the range of 1-10 nm. Hence, when liquids are confined to these length scales, they undergo a variety of transitions that control the liquid, ionic and macromolecular transport, as well as liquid-vapor phase transitions. This 20-minute talk will discuss our past experimental and theoretical work on nanofluidic transport. This is now forming the basis of a new effort using cryo-electron microscopy to image ions and molecules and address some of the key knowledge gaps in this field that relate to phase transitions and separations as well as ion selectivity and correlation.

Part 2: Solving the Energy and Climate Simultaneous Equation - Energy use is the basis of all modern economies. With 80% of the primary energy still from fossil fuels, the environmental imperatives warrant fierce urgency to address them at scale. This is arguably the defining challenge of the 21st century. While technological innovations and cost reductions in unconventional oil and gas, renewable electricity from solar and wind, as well as lithium-ion batteries offer optimism, they are insufficient to decarbonize the global energy system to keep the global average temperature rise below 2°C. How can we accelerate transition to a more sustainable energy system? What new technologies or policies do we need to create? This 20-minute talk will offer a call to action in science, technology, policy and governance to provide a proportional response to address climate change.

Speaker Bio: 

Arun Majumdar is the Jay Precourt Provostial Chair Professor at Stanford, a faculty member of the Depts. of Mechanical Engineering and Materials Science and Engineering (by courtesy) and co-director of the Precourt Institute for Energy, which integrates and coordinates research and education activities across all seven Schools and the Hoover Institution at Stanford. He was previously the founding Director of the Advanced Research Projects Agency - Energy under Pres. Barack Obama, where he helped ARPA-E become a model of excellence with bipartisan support from Congress and other stakeholders. Dr. Majumdar's past research has involved the science and engineering of nanoscale materials and devices, especially in the areas of energy conversion, transport and storage as well as biomolecular analysis. His current work focuses on electrochemical and thermochemical redox reactions that are fundamental to a sustainable energy future, multidimensional nanoscale imaging and microscopy, and an effort to re-engineer the electricity grid using data science and deep learning.