A Hierarchical Approach to Control of Complex Energy and Power Systems for Air Vehicles
Presented by Professor Andrew Alleyne
Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign
Modern aircraft are highly complex systems. This talk will present a particular hierarchical approach to energy and power flow in air vehicles that accommodates multiple power modes. These modes include thermal, fluid, electrical, or mechanical since these are all available in larger aircraft. In particular, with the current drive towards increased electrification, the management of power onboard aircraft has become an enabler or a bottleneck depending on the point of view. A key challenge in working across various modes of power flow is the widely varying time scales. The hierarchy allows for systems operating on different time scales to be coordinated in a controllable manner. It also allows for different dynamic decision making tools to be used at different levels of the hierarchy based on the needs of the physical systems under control. Additional advantages include the modularity and scalability inherent in the hierarchy. Additional modules can be added or removed without changing the basic approach. In addition to the hierarchical control, a particularly useful graph-based approach will be introduced for the purpose of modeling the system interactions. The graph approach, like the hierarchy, has benefits of modularity and scalability along with being an efficient framework for representing systems of different time scales. Recent results will be presented representing both generic interconnected complex systems as well as specific examples and resulting benefits.
Professor Alleyne received his Mechanical and Aerospace Engineering B.S.E. from Princeton University in 1989. He received his M.S. and Ph.D. degrees in Mechanical Engineering in 1992 and 1994, respectively, from UC Berkeley. He joined the University of Illinois, Urbana-Champaign in 1994. He currently holds the Ralph M. and Catherine V. Fisher Professorship in the College of Engineering and is the Director for the NSF Engineering Research Center on Power Optimization for Electro-Thermal Systems (POETS). He is the recipient of an NSF CAREER award, has been an IEEE Distinguished Lecturer, and a National Research Council (NRC) Associate. He is a Fellow of IEEE and ASME. He has received the Gustus Larson Award, the Charles Stark Draper Award for Innovative Practice, The Yasundo Takahashi Education Award and the Henry Paynter Outstanding Investigator Award from ASME. The American Automatic Control Council awarded him the Control Engineering Practice Award. He was a Fulbright Fellow to the Netherlands and has held visiting Professorships at TU Delft, University of Colorado, ETH Zurich, and Johannes Kepler University. He has held several editorial positions for ASME, IEEE, and the International Federation of Automatic Control and been active in external advisory boards for universities, industry and government including the Scientific Advisory Board for the U.S. Air Force and the National Academies Board on Army Research and Development. He chaired the ASME Dynamic Systems and Controls Division and is a member of the IEEE Controls Systems Society Board of Governors. His record of campus service includes the Associate Dean for Research in the College of Engineering and the Associate Head for Undergraduate Programs in Mechanical Science and Engineering. In addition to research and service, he has a keen interest in education and has earned the UIUC College of Engineering Teaching Excellence Award, the UIUC Campus Award for Excellence in Undergraduate Education and the UIUC Campus Award for Excellence in Graduate Student Mentoring.
4:10 pm Presentation
“An Input-Output Approach to Investigate the Effects of Actuator Geometry”
Presented by IGAL GLUZMAN (Adviser: Prof. Gayme)
In this work, an input-output approach is used to study actuated boundary layers arising from different types of input signals and actuator geometries. The manipulated flow fields are modeled using the Navier-Stokes equations linearized about a given base flow due to localized forcing. The actuated fields are then obtained by superposing the response of each localized source in a spatial pattern representing the actuation geometry, e.g., a serpentine geometry plasma actuator whose signal varies in intensity over the geometry. This framework allows the investigation of an array of actuation signals including a single pulse, a train of pulses, and a continuous input are modeled through analytical solutions of the LNS system. This talk will focus on the steady-state step response that is used to reproduce the stationary actuated flow-fields due to different plasma actuator configurations in transitional boundary layers. The model is found to reproduce the vortical and streamwise velocity structures obtained in experimental and simulation studies qualitatively well. Our results demonstrate the promise of such an analytical tool in determining beneficial actuator configurations prior to costly high-fidelity numerical simulations, and to reduce trial and error based parametric experimental studies.
4:35 pm Presentation
“Heaving Stall Flutter of Blade in a Linear Cascade at Transonic Flow Speed”
Presented by AYUSH SARASWAT (Adviser: Prof. Katz)
Aeroelastic flutter is a dynamic instability of a structure in a flow. When the structure undergoes flutter, the unsteady aerodynamic loads generated over it results in amplification of small oscillations. The flutter of turbomachine blades has been studied for decades but it has been difficult to fully understand it because of its sensitivity to a wide range of parameters and its occurrence over various conditions of turbomachine operation. To understand this phenomenon in the transonic regime, experiments were carried out on a linear cascade of compressor blades in a blowdown tunnel at M=1.3. The center blade was oscillated in heaving mode to simulate first bending mode oscillation of the near tip region of a rotor stage of an axial compressor. A barrel cam mechanism was employed to oscillate the blade up to 220 Hz. The parameters varied in the study were the reduced frequency of the blade and the pressure ratio of the cascade. It was observed that at low-pressure ratios the flutter map of the transonic cascade is qualitatively similar to subsonic stall flutter. However, at a high-pressure ratio, the observed trend was considerably different. Furthermore, shadowgraphs were used to visualize the flow, cascade periodicity, and passage shock structures.
COMPUTATION ACCELERATED DESIGN OF MATERIALS AND INTERFACES FOR SOLID-STATE BATTERIES
Presented by Professor Yifei Mo
Department of Materials Science and Engineering,
University of Maryland, College Park
All-solid-state Li-ion battery based on solid electrolytes is a promising next-generation battery technology with high energy density, intrinsic safety, long cycle life, and wide operational temperatures. However, multiple challenges, such as low ionic conductivity of solid electrolytes and poor interfacial compatibility at the solid electrolyte-electrode interfaces, are impeding the development of this new battery technology. To resolve these materials challenges, we develop and leverage an array of computation techniques to provide unique materials insights into the fundamental materials limitations and to establish general design principles of materials and solid interfaces. Our first-principles atomistic modeling studies reveal the origin of ultra-fast Li+ diffusion in lithium super-ionic conductors. On the basis of the newly gained understanding, we establish design principles for fast ion-conductor materials and demonstrate these design principles for the computation discovery and design of new lithium super-ionic conductors. In addition, we developed thermodynamic calculations based on the materials-genome database for investigating the compatibility of heterogeneous interfaces between solid electrolytes and electrodes. Key factors affecting the compatibility of the solid electrolyte-electrode interfaces are identified, and interfacial design strategies are proposed from our thermodynamic computation. The demonstrated computation capabilities represent a transferable model in designing new materials and interfaces for emerging technologies.
Professor Yifei Mo is an Associate Professor of Materials Science and Engineering at the University of Maryland, College Park, USA. Dr. Mo’s research aims to advance the understanding, design, and discovery of engineering materials through cutting-edge computational techniques. His current research projects target critical materials problems in energy storage and conversion technologies, with current emphases on beyond Li-ion and all-solid-state batteries. Dr. Mo obtained his B.S. degree in Physics from Peking University and Ph.D. degree in Materials Science from the University of Wisconsin, Madison, USA (2005-2010). He performed his postdoctoral research at Massachusetts Institute of Technology (2010-2013). His research has been published in peer-reviewed journals including Nature, Nature Materials, Nature Communications, Journal of the American Chemical Society, Advanced Energy Materials, Joule, Angewandte Chemie, Nano Letter, Chemistry of Materials, and Physical Review B, etc.
4:10 pm Presentation
“Cavitation Inception and Associated Pressure Field in a Turbulent Shear Layer”
Presented by KARUNA AGARWAL (Adviser: Prof. Katz)
Cavitation inception in the near field of the shear layer occurs in the core of quasi-streamwise vortices that develop between the main spanwise vortices. These located between 45 to 75% of the reattachment length and form 1-2mm diameter and 5-7 mm long cavities that form and collapse in less than 200 µs. The frequency of events at the same cavitation index increases rapidly with velocity, suggesting yet-unknown scaling trends. Hence, it is essential to measure and characterize the instantaneous pressure fields generated in the core of the quasi-streamwise vortices. Tomographic imaging followed by 3D particle tracking using the Shake-the-Box method are used for calculating the instantaneous velocity and acceleration fields. The experimental results are interpolated using Constrained Cost Minimization to generate divergence-free velocity and curl-free material acceleration at a spatial resolution of 250 µm. The pressure is obtained by spatially integrating the material acceleration. The procedure is tested for synthetic data based on the Johns Hopkins Turbulence Database. The measurements are performed at Reynolds numbers based on separating boundary layer height of Re=7100 and 17700 to characterize the effect of Reynolds number on the frequency, time evolution, size, strength and the pressure in the quasi streamwise vortices. Ultra-high speed imaging is being used to characterize the explosive growth and collapse of the cavities and the effect of nuclei.
4:35 pm Presentation
“Simulation Prediction and Adjoint-Based Sensitivity of Laser-Based Ignition in High-Speed Flows”
Presented by DAVID BUCHTA (Adviser: Prof. Zaki)
Large-scale numerical simulations are starting to enable the prediction of multi-physics phenomena. Their interactions are usually so complex that theory and models alone have a limited predictive capacity. Thus, the Center for Exascale Simulation of Plasma-coupled Combustion (XPACC), a Multidisciplinary Simulation Center within the Predictive Science Academic Alliance Program II (PSAAP II), is developing high-fidelity numerical simulations in conjunction with Exascale-aimed computer science tools and uncertainty quantification (UQ) analyses, such as adjoint-based sensitivity, to provide a route to prediction. Specifically, our prediction is space-time transient ignition kernel (TIK) characteristics in plasma-coupled, high-speed flow turbulence applications, like those anticipated on scramjets. Ignition is seeded using the breakdown of a focused laser beam in fuel-oxidizer mixtures, which dissociates the local mixture into elemental species, generates vorticity, and heats the gas above 10000 Kelvin, activating combustion within 1 nanosecond. Depending on the flow, the kernel can develop into a sustained flame or extinguish completely. To help identify mechanisms of successful or failed ignition, the solution of the discrete-exact adjoint equations for the corresponding compressible reacting flow equations provides input-output sensitivity to our quantity of interest, like the TIK. This sensitivity guides optimization and reduces parameter space to support UQ.
Thao (Vicky) Nguyen will deliver a lecture titled “Biomechanics of the optic nerve head in glaucoma” as part of the Don P. Giddens Inaugural Professorial Lecture Series. Nguyen is a professor in the Department of Mechanical Engineering and the Marlin U. Zimmerman, Jr. Faculty Scholar.
Glaucoma is a neurodegenerative disease characterized by damage to the optic nerve axons and remodeling of the connective tissues in the optic nerve head. High pressure in the the eye is a major risk factor for the disease, and lowering this pressure is currently the only effective way to slow the disease’s progression. Nguyen seeks to understand the fundamental biomechanical mechanisms through which changes in the intraocular pressure alter the physiological function of cells and remodel the collagen structures of the optic nerve head. In this presentation, she will describe ongoing work to measure the deformation response of the cellular and connective tissue structures of the optic nerve head to pressure, characterize alterations with age and glaucoma, model the effects of structural variations on the deformation and stress response, and investigate the mechanisms through which stress can direct connective tissue growth and remodeling.
The Don P. Giddens Inaugural Professorial Lecture Series began in 1993 as a way to honor newly promoted full professors. Professor Giddens, originator of the series, served as the fifth dean of Engineering at Johns Hopkins.
Safety-Critical Autonomous Systems: What is Possible? What is Required?
Presented by Professor Richard Murray
Thomas E. and Doris Everhart Professor of Control & Dynamical Systems and Bioengineering California Institute of Technology
The last 20 years have seen enormous progress in autonomous vehicles, from planetary rovers, to unmanned aerial vehicles, to the self-driving cars that we are starting to see on the roads around us. An open question is whether we can we make self-driving cars that are safer than human-driven cars, how much safer they need to be, and what advances will be required to bring them to fruition. In this talk, I will discuss some of the approaches used in the aerospace industry, where flight critical subsystems must achieve probability of failure rates of less than 1 failure in 10^9 flight hours (i.e. less than 1 failure per 100,000 years of operation). Systems that achieve this level of reliability are hard to design, hard to verify, and hard to validate, especially if software is involved. I will describe some of the challenges that the aerospace community faces in designing systems with this level of reliability, how they are designed and implemented done today, and what is being done for the next generation of (much more complex, software-driven) aerospace systems. I will also speculate about whether similar approaches are needed in self-driving cars, and whether these levels of safety are achievable.
Richard M. Murray received the B.S. degree in Electrical Engineering from California Institute of Technology in 1985 and the M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1988 and 1991, respectively. He is currently the Thomas E. and Doris Everhart Professor of Control & Dynamical Systems and Bioengineering at Caltech. Murray’s research is in the application of feedback and control to networked systems, with applications in biology and autonomy. Current projects include analysis and design of biomolecular feedback circuits, synthesis of discrete decision-making protocols for reactive systems, and design of highly resilient architectures for autonomous systems.
4:10 pm Presentation
“A Population Balance Model for Large Eddy Simulation of Polydisperse Droplet Evolution”
Presented by ADITYA K. AIYER (Adviser: Prof. Meneveau)
In the context of oil spills, knowledge of the dispersed phase droplet size distribution and its evolution is critical for accurate prediction of many macroscopic features of the oil plumes. In this study, we adopt a population dynamics model for polydisperse droplet size distributions and implement it in a Large Eddy Simulation framework. We model the number density fields using an Eulerian approach for each bin of the discretized droplet size distribution. The droplet breakup due to turbulent fluctuations is modelled by treating droplet–eddy collisions as in kinetic theory of gases. Existing models assume the scale of droplet-eddy collision to be in the inertial scale of turbulence. In this work we extend the breakup kernels to the entire spectrum of turbulence using generalized structure functions. The model includes a dimensionless coefficient that is fitted by comparing predictions in a one-dimensional version of the model with a laboratory experiment of oil droplet breakup below breaking waves. After initial comparisons of the one-dimensional model to measurements of oil droplets in an axisymmetric jet, it is then applied in a three-dimensional LES of a jet in cross-flow with large oil droplets of a single size being released at the source of the jet. The resulting droplet size distributions are compared with published experimental data, and good agreement for the relative size distribution is obtained. The LES results also enable us to quantify size distribution variability. We find that the probability distribution functions of key quantities such as the total surface area and the Sauter mean diameter of oil droplets are highly variable, some displaying strong non-Gaussian intermittent behaviour.
4:35 pm Presentation
“Effect of Chemical Herders on Wave Breaking”
Presented by LAKSHMANA D. CHANDRALA (Adviser: Prof. Katz)
Chemical surface-active agents (oil herders) could be used to concentrate oil slicks to facilitate in-situ burning after an oil spill. The water-insoluble but oil-soluble surfactants in commercial oil herders accumulate on the air-water interface and might alter the wave breaking process. In this study, the characteristics of mechanically generated breaking waves of varying energies are visualized in clean seawater and water treated with a herder containing 65% Span-20 and 35% 2-ethyl butanol at a concentration of 5.5 ml/m2. The experiments are performed in a 6×0.3×0.6 m transparent tank and the waves are generated by translating a paddle. Multiple high-speed cameras follow the evolution of both waves. For a plunging breaker in clean water, prior to impact, the wave front contains multiple ripples and small fingers. In contrast, in treated water the wave-front is smooth, resulting in entrainment of a larger volume of air, and deeper subsequent penetration of the bubble cloud. Conversely, for relatively weak spilling breakers, adding the surfactant delays the wave breaking, and dampens the formation of capillary waves on the wave crest. Once breaking occurs, visually, there is no significant difference in the appearance and penetration of the waves.
“Emerging Interface Problems in Soft Matter, Cell and Neuromechanics – Concussions and Traumatic Brain Injury”
Presented by Professor Christian Franck
Grainger Institute for Engineering, University of Wisconsin-Madison
Current prediction, prevention and diagnosis strategies for mild traumatic brain injuries, including concussions, are still largely in their infancy due to a lack of detailed understanding and resolution of how physical forces give rise to tissue injury at a cellular level. In this talk I will present some recent work on our current understanding of the origin of concussions and traumatic brain injuries and how cells in the brain interpret and react to the physical forces of trauma. Specifically, I will show that the path to a better understanding of traumatic injuries involves addressing a variety of soft matter and cell mechanics problems along the way. Finally, I hope to motivate and propose some solutions on how we might improve our prevention and diagnosis of these injuries by working together across disciplines.
Professor Christian Franck is a mechanical engineer specializing in cellular biomechanics and new experimental mechanics techniques at the micro and nanoscale. He received his B.S. in aerospace engineering from the University of Virginia in 2003, and his M.S. and Ph.D. from the California Institute of Technology in 2004 and 2008. Dr. Franck held a post-doctoral position at Harvard investigating brain and neural trauma. He was an assistant and associate professor in mechanics at Brown University from 2009 – 2018, and is now the Grainger Institute for Engineering Associate Professor in Mechanical Engineering at the University of Wisconsin, and the Director of Panther, an ONR funded research hub for addressing next generation protection solutions against traumatic brain injuries. His lab at the University of Wisconsin-Madison has developed unique three-dimensional full-field imaging capabilities based on confocal microscopy and digital volume correlation. Current application areas of these three-dimensional microscopy techniques include understanding the 3D deformation behavior of neurons in the brain during traumatic brain injuries, the adhesion and migration behavior of human neutrophils in 3D environments, and the role of non-linear material deformations in soft matter.
“Robust Decision and Control of Autonomous Robotic Vehicles”
Presented by Professor Marin Kobilarov
Department of Mechanical Engineering, Johns Hopkins University
This talk will consider the problem of reliable autonomous navigation of robotic vehicles, such as unmanned aerial vehicles, autonomous underwater vehicles, or self-driving cars. The decision and control algorithms for such systems must be designed to efficiently achieve a mission objective, such as reaching a goal location in a cluttered and dynamic environment, but also remain safe and robust to the uncertainties of the real world. We will propose computational-theoretic methods to analyze this trade-off and discuss ongoing development of algorithms with built-in robustness based on statistical learning theory.
Marin Kobilarov is an assistant professor in mechanical engineering and computer science at the Johns Hopkins University, and the director of the Autonomous Systems, Control and Optimization Lab. He received his Ph.D. from University of Southern California in 2008 and was the Keck post-doctoral fellow in control and dynamical systems at the California Institute of Technology during 2009-2012. His group focuses on computational theory, algorithms and software development, for decision making, planning, control and system integration of robotic systems operating in complex environments. Their work has been nominated for best papers at RSS and ICRA. Current applications are: unmanned aerial vehicles operating through contact with the environment, self-driving robotic vehicles, autonomous underwater vehicles for environmental assessment, and robot-assisted eye surgery.
4:10 pm Presentation
“Transition Delay in High-Speed Boundary Layers by Thermal Texture”
Presented by REZA JAHANBAKHSHI (Adviser: Prof. Zaki)
Delay of transition to turbulence in the boundary layer that forms on hypervelocity vehicles remains one of the key difficulties in achieving reliable long-range manned hypersonic flight. Since the environmental conditions are often uncertain, the main challenge is how we can guarantee robust flow design in such applications. Previous attempts to attenuate the flow disturbances and sustain the laminar state in the boundary layer have been ad hoc and their robustness unconfirmed. In the present effort, the surface heat-flux in a transitional zero-pressure-gradient high-speed boundary layer is optimized using an ensemble-variational (EnVar) algorithm in order to guarantee transition delay, when the environmental disturbance is the most dangerous condition from the standpoint of transition. The control vector is parametrized using a two-dimensional basis function on the wall which allows to target specific parts of the flow-field upstream of the fully turbulent region. The EnVar algorithm is able to identify regions of the flow that are most sensitive to thermal treatment and apply most of the heating and cooling to these regions. This leads to appreciable power saving as a result of reducing the drag forces associated with turbulent region. The results indicate that in order to attenuate instability waves using heating and cooling, the thermal roughness must be placed upstream of the synchronization point of the slow and the fast modes. On the other hand, the first-mode instability wave and the second-mode instability whose synchronization point is downstream of the thermal roughness, are minimally affected in our computational setup.
4:35 pm Presentation
“Experimental Evidence of Amplitude Modulation in Permeable-Wall Turbulence”
Presented by TAEHOON KIM (Adviser: Prof. Ni)
The dynamic interplay between surface and subsurface flow in the presence of a permeable boundary layer was investigated using low and high frame-rate particle-image velocimetry (PIV) measurements in a refractive-index matching environment. Two idealized permeable wall models were considered. Both models contained five layers of cubically-packed spheres, but one exhibited a smooth interface with the flow, while the other embodied a hemispherical surface topography. The relationship between the large-scale and within the walls was explored using instantaneous and statistical analyses. Although previous studies have indirectly identified the potential existence of amplitude modulation in permeable-wall turbulence (a phenomenon previously reported in impermeable-wall turbulence), the present effort provides direct evidence of its existence in flow over both permeable walls. The spatio-temporal signatures of amplitude modulation were also characterized using conditional averaging based on zero-crossing events. This analysis highlights the connection between large-scale regions of high and low streamwise momentum in the surface flow, downwelling/upwelling across the permeable interface and enhancement/suppression of small-scale turbulence, respectively, just above and within the permeable walls.