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Upcoming Seminars

Seminars are held Tuesdays and Thursdays in POB 6.304 from 3:30-5:00 pm, unless otherwise noted. Speakers include scientists, researchers, visiting scholars, potential faculty, and ICES/UT Faculty or staff. Everyone is welcome to attend. Refreshments are served at 3:15 pm.

 

ICES Seminar
Thursday, Apr 27, 2017 from 3:30PM to 5PM
POB 6.304

Probabilistic Models for Inference and Design in Complicated Problems
by Roger Ghanem

Professor, Department of Aerospace and Mechanical Engineering and Sonny Astani Department of Civil and Environmental Engineering, University of Southern California

Details

Stochastic models entail packaging knowledge in a way that enhances its relevance to decision making. Specifics of this task clearly depend on 1) what knowledge is available, 2) which decisions are of interest, and 3) what tools are available for packaging knowledge. While decision-making undoubtedly benefits from anticipating the future, the value of the associated inference is limited by the confidence in this anticipation. A distinguishing feature of today's scientific exploration is the ability to not only observe physical phenomena at their smallest constituents, but also to resolve their behavior with mathematical models. This was enabled by technological advances in sensing and computing, and matched by advances in theoretical and computational mathematics. As a result of these developments, new perspectives have recently emerged on the substance of scientific knowledge that have critical significance to uncertainty quantification. Specifically, we are constantly faced with the need to integrate, on the one hand, streams of information associated with a hierarchy of fundamental principles (presuming causality) and on the other hand information associated with joint observations. Distinct mathematical constructs have typically been associated with these flavors of knowledge, yielding, respectively, advances in computational science and data analytics. There is a pressing need to develop rational and credible concepts and algorithms for fusing these manifestations of knowledge in a way that best leverages the value of technological developments.

This talk will describe recent advances in my group for tackling design-relevant predictions in applications where characterization of extremes is crucial notwithstanding multiscale and multiphysics effects.

Hosted by Tan Bui-Thanh





 

ICES Seminar-Numerical Analysis Series
Friday, Apr 28, 2017 from 1PM to 2PM
POB 6.304

Massively parallel radiation transport simulations: current status and challenges ahead
by Jean Ragusa

Texas A & M University

Details

In this talk, I will provide an overview of solution techniques and iterative techniques employed to solve the first-order form of the radiation transport equation on massively parallel machines. A review of scaling efficiency for transport sweeps (up to order 1-million processes) will be provided for logically Cartesian grids. Challenges posed by the need to move to unstructured (load-unbalanced) grids and ongoing research will be discussed. Diffusion-based synthetic accelerators for the one-speed (within-group) and multi group transport equations will be presented and issues related to massively parallel diffusion-accelerated transport sweeps be analyzed.

Bio
Dr. Jean Ragusa specializes in computational methods for radiation (neutron, photon, coupled electron-photon) transport, radiative transfer, and multiphysics applications (e.g., radiation-hydrodynamics and two-phase flow modeling using a seven-equation model). Dr. Ragusa obtained his PhD from the University of Grenoble in 2001 and was a visiting assistant professor in the scholar of nuclear engineering at Purdue in 2001. From 2002 until 2004, he was a research engineer at the CEA-Saclay, France, in the reactor physics and applied mathematics division. In September 2004, he joined Texas A&M University where he is a professor of Nuclear Engineering and, since 2009, the associate director of the Institute for Scientific Computation.

Hosted by Kui Ren





 

ICES Seminar-PECOS Series
Monday, May 1, 2017 from 3PM to 4:30PM
POB 4.304

Event Update Notification: Note: Different Room

Modulation of Cillia-like Micro-Surface on the Flow Evolution of a Wind Turbine Blade
by Luciano Castillo

Texas Tech University

Details

Surface roughness can result from mosquitoes and other debris that are impacted on the surface of wind turbine blades, creating a layer of random roughness. This is known to negatively impact the performance of wind turbines, increasing form drag by moving the separation point toward the leading edge, thus increasing the external loads that negatively affect the drive-train and energy production. In this seminar, we will discuss how a bio-inspired micro-scale surface of a mushroom type that modulates the flow dynamics of a wind turbine airfoil. Our experimental results from an index-matched facility provide evidence that this bio-inspired surface does not produce additional turbulence as normally encountered on rough surfaces. By employing this micro-scale surface on an airfoil (see figure below), we showed that drag is mitigated and the separation point moved toward the trailing edge. Although this bio-inspired surface modulates the flow evolution, the behavior of the flow is quite opposite to the typical surface roughness. Moreover, the theory developed by Castillo and collaborators in the early 2000’s using the equations of motion suggest that the flow, although separated, remains in equilibrium. The mechanism by which the flow dynamics changes and reduces separation is due to injection and blowing along the surfaces, producing regions of high speed along the surface. Consequently, the bio-inspired surface produces an effective slip velocity near the wall region contrary to surface roughness. Besides wind energy applications, this unique surface offers benefits of drag reduction for hydrodynamic bodies, airplanes, trans-continental pipes and cars. Furthermore, there is evidence that similar surfaces possess self-cleaning properties, and the micro-pillar coating works on water under wetted conditions.

Bio
Prior to joining Texas Tech University in 2011 as the inaugural Center Director of the National Wind Resource Center and Don-Kay-Clay Cash Distinguished Engineering Chair in Wind Energy, he was Professor at Rensselaer Polytechnic Institute in the Mechanical & Aerospace Department. His areas of research interest include: turbulence, renewable energy and bioengineering. He has published over 100 publications, edited several books on renewable energy and co-authored several patents (e.g., energy, health care, etc.). Some of his awards include: Fellow ASME, the NASA Faculty Fellowship, the Martin Luther King Faculty Award, the Robert T. Knapp Award Best Paper Award from the ASME, the Best Paper Award from the Journal of Renewable Energy, the Best Paper Award from IEEE, and the Rensselaer Faculty Award (twice). He gave several keynotes lectures, plenary lecture, and distinguished lectures on wind energy. Currently, he serves as Associate Editor of Wind Engineering & Science, and serves in various scientific committees on renewable energy in Europe. He is passionate about inclusiveness and mentoring students and young faculty, and founded and organized two summer research institutes on renewable energy & medicine, which included students, faculty and K-12 teachers. For his contributions and impacts on inclusiveness he received in 2016 the McDonald Mentoring Award from ASME, and was nominated for a Presidential Award given by the President of the USA.

Hosted by Robert Moser





 

ICES Seminar
Tuesday, May 2, 2017 from 3:30PM to 5PM
POB 6.304

Microstructural Evolution during Plastic Flow
by John L. Bassani

Professor, Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania

Details

Essentially all solid materials deformed at moderate to large strains undergo changes in microstructure that can significantly affect macroscopic response. Reasonably tractable computational models are lacking, which explains limited success in predicting plastic instabilities and limits to formability. A macroscopic continuum theory is developed for a class of anisotropic elastic-plastic solids in which the orthotropic triad that characterizes material symmetry evolves with deformation. In essence, microstructural evolution arises from non-coaxiality between the plastic rate of stretching and the instantaneous orthotropic triad, which intuitively makes sense. That key result is established rigorously from representation theory for tensor-valued functions. The resulting phenomenological model agrees well with experimental data for metallic polycrystals. A finite element implementation predicts significant effects of microstructural evolution both quasi-static and dynamic strain localization, in particular for necking, shear banding, and buckling. This finding likely explains why analyses that neglect those effects have proven inadequate in many critical applications. This knowledge is proving to be crucial in a DOE grand-challenge to greatly improve automotive efficiency through light-weighting. Simulations of sheet forming and tube crushing show promise in developing new design concepts.

Bio
John L. Bassani is the Richard H. and S. L. Gabel Professor of Mechanical Engineering at Penn (BS ME Lehigh 1973; Fairchild-Republic Aviation 1973; MS ME Lehigh 1975, PhD Harvard 1978; Assistant Professor MIT, 1979-80; at Penn since 1980 in Mechanical Engineering and Applied Mechanics with a secondary appointment in Materials Science and Engineering). He was Chair of MEAM for 11 years (from 1997-2005 and 2008-2011). He is a member of Penn’s Laboratory for Research on the Structure of Matter and the Institute for Computational Science. He has held visiting professorships UCSB, Harvard, and Brown, was President of the Society of Engineering Science (2008), and has served on several editorial boards. Professor Bassani’s research interests include: interfacial mechanics; nanostructures; adhesion of shells; plastic deformation, material stability; and fracture.

Hosted by George Biros





 

ICES Seminar
Thursday, May 4, 2017 from 3:30PM to 5PM
POB 6.304

Optimization and Learning Algorithms for Survival and Schooling Hydrodynamics
by Petros Koumoutsakos

Professor, Computational Science, ETH Zurich

Details

The aqueous environment of natural swimmers mediates the fascinating patterns of schooling as well as their escape and attack routines. We study the fluid mechanics of single and multiple swimmers through simulations that rely on wavelet adapted vortex methods. Stochastic optimization and reinforcement learning algorithms are used to identify optimal shapes and motions for single and synchronized patterns for multiple swimmers. I will discuss how the orchestration of body deformations and vortex dynamics can result in thrust and energy savings for these artificial swimmers and compare these findings with swimming patterns of natural organisms. Lessons learned can assist the design and operation of energy efficient swimming devices.

Bio:
Petros Koumoutsakos is Professor of Computational Science at ETH Zurich. He received his Diploma (1986) in Naval Architecture at the National Technical University of Athens and a Master’s (1987) at the University of Michigan, Ann Arbor. He received his Master’s (1988) in Aeronautics and his PhD (1992) in Aeronautics and Applied Mathematics from the California Institute of Technology. He is Fellow of the American Society of Mechanical Engineers, the American Physical Society and the Society of Industrial and Applied Mathematics. He is recipient of the ACM Gordon Bell prize in Supercomputing and the Advanced Investigator Award by the European Research Council (2013). He is presently a Fellow at the Radcliffe Institute of Advanced Study at Harvard University.

Hosted by George Biros





 

ICES Seminar-Molecular Biophysics Series
Thursday, May 4, 2017 from 2PM to 3PM
POB 6.304

NEET proteins – a novel class of 2Fe-2S proteins with a unique fold and function
by Rachel Nechushtai

The Hebrew University of Jerusalem

Details

Metalloproteins (MPs) comprise one-third of all known protein structures. Among them, a unique class of iron-sulfur (2Fe-2S) proteins, the NEET proteins, were recently discovered. In human, the NEET family consists of three members. Two of them, mitoNEET and NAF-1, encoded by the CISD1 and CISD2 genes, respectively, are homo-dimers, containing two domains; a beta-cap, and a cluster binding domain. The 2Fe-2S clusters of NEET proteins, are coordinated by a 3Cys:1His structure which allows them to be both relatively stable, as well as transferred to apo-acceptor protein(s). This unique feature of NEET proteins is likely controlled by the NEET's 2Fe-2S's coordinating His that is positioned at the protein surface and can undergo protonation that destabilizes the cluster and enables its transfer. Most of the well-studied MPs are generally viewed as being very rigid in structure, and it is widely believed that the properties of their metal centers are primarily determined by the small fraction of amino acids that make up the local center environment. To challenge that, we initially used a globular plant-type ferredoxin (Fd) to investigate the functional landscape of a single-domain 2Fe-2S protein and the effect of a distal loop on its electron-transfer 2Fe-2S cluster. We found that the global stability and structure are minimally perturbed by a deletion mutation, whereas the functional properties are altered. Specifically, truncating the Fd-L1,2 loop does not lead to large-scale changes in the structure, determined via X-ray crystallography. In addition, the overall thermal stability of the protein is only marginally perturbed by the mutation. However, even though the mutation is distal to the iron–sulfur cluster, it leads to a significant change in the redox potential of the iron–sulfur cluster (57 mV). Structure-based all-atom simulations revealed correlated dynamical changes between the surface-exposed loop and the iron–sulfur cluster-binding region, suggesting that intrinsic communication channels within the ferredoxin fold, composed of many short-range interactions, lead to the propagation of long-range signals. We also examined both theoretically and experimentally whether distal regions can influence the metal centers in the diabetes drug target mitoNEET. A loop 20 Å away from the metal centers exerts allosteric control over the cluster binding domain and regulates multiple properties of the metal centers. Mutagenesis therefore resulted in significant shifts in the redox potential of the [2Fe-2S] cluster and orders-of-magnitude effects on the rate of [2Fe-2S] cluster transfer to an apo-acceptor protein. These surprising effects occur in the absence of any significantly-observed structural changes. Our findings suggest that long-range dynamical changes in the protein backbone can have a significant effect on the functional properties of MPs. We further used an integrated approach involving peptide array, deuterium exchange mass spectrometry (DXMS), and functional studies aided by the power of sufficient constraints from direct coupling analysis (DCA) to determine the dominant docked conformation of the NAF-1–Bcl-2 complex. NAF-1 binds to both the pro- and antiapoptotic regions (BH3 and BH4) of Bcl-2, as demonstrated by a nested protein fragment analysis in a peptide array and DXMS analysis. These studies together with our recent findings of the NEET function in Cancer, Genetic neurodegenerative disease and the importance of their transmembrane domains will be discussed.

Hosted by Ron Elber





 

ICES Seminar-Numerical Analysis Series
Friday, May 5, 2017 from 1PM to 2PM
POB 6.304

High Resolution Solution of Inverse Scattering Problems
by Carlos Borges

ICES, UT Austin

Details

I describe a fast, stable framework for the solution of the inverse acoustic scattering problem. Given full aperture far field measurements of the scattered field for multiple angles of incidence, the recursive linearization is used to obtain high resolution reconstructions of properties of the scatterer. Despite the fact that the underlying optimization problem is formally ill-posed and non-convex, recursive linearization requires only the solution of a sequence of linear least squares problems at successively higher frequencies. By seeking a suitably band-limited approximation of the sound speed prole, each least squares calculation is well-conditioned and involves the solution of a large number of forward scattering problems. For two dimension problems we employ spectrally accurate, fast direct solvers. For the largest problems considered, approximately one million partial differential equations were solved, requiring approximately two days to compute using a parallel MATLAB implementation on a multi-core workstation.

Hosted by Kui Ren





 

ICES Seminar-Babuska Forum Series
Friday, May 5, 2017 from 10AM to 11AM
POB 6.304

A Convex Primal Formulation for Convex Hull Pricing
by Ross Baldick

Professor, Department of Electrical & Computer Engineering, UT Austin

Details

In certain electricity markets, because of non-convexities that arise from their operating characteristics, generators that follow the independent system operator’s (ISO’s) decisions may fail to recover their cost through sales of energy at locational marginal prices. The ISO makes discriminatory side payments to incentivize the compliance of generators. Convex hull pricing is a uniform pricing scheme that minimizes these side payments. The Lagrangian dual problem of the unit commitment problem has been solved in the dual space to determine convex hull prices. However, this approach is computationally expensive. We propose a polynomially-solvable primal formulation for the Lagrangian dual problem. This formulation explicitly describes for each generating unit the convex hull of its feasible set and the convex envelope of its cost function. We cast our formulation as a second-order cone program when the cost functions are quadratic, and a linear program when the cost functions are piecewise linear. A 96-period 76-unit transmission-constrained example is solved in less than fifteen seconds on a personal computer.

Bio
Dr. Ross Baldick is a Professor in the Department of Electrical & Computer Engineering at The University of Texas at Austin and holds the Leland Barclay Fellowship in Engineering. He earned his Ph.D. in electrical engineering from the University of California, Berkeley in 1990. He joined the faculty of The University of Texas at Austin in 1994. He won a National Science Foundation Young Investigator Award that same year. Dr. Baldick is a Fellow of the IEEE and the recipient of the 2015 IEEE PES Outstanding Power Engineering Educator Award. His research is related to analysis of restructured electricity markets and electric transmission and very large-scale integration circuit analysis. His current research is focused on optimization, economic theory, and statistical analysis applied to electric power system operations.

Hosted by Amir Gholaminejad