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.

Friday, May 29

Implicit Finite Volume Approximation of Nonlinear Advection-Diffusion Equations

Friday, May 29, 2020 from 10AM to 11AM | Zoom Meeting

  • Additional Information

    Hosted by Stefan Henneking

    Sponsor: Oden Institute Virtual Seminar - Babuška Forum Series

    Speaker: Todd Arbogast

    Speaker Affiliation: Professor, Department of Mathematics and Core Faculty, Oden Institute, UT Austin

  • Abstract

    We consider approximation of nonlinear advection-diffusion equations, which express conservation principles for systems exhibiting transport and diffusion processes evolving in time. These systems are often advection dominated, and so display hyperbolic behavior, which means that shocks, or at least steep fronts, can develop in the solution. In the general finite volume framework, the conservation principles are reduced to the mesh element level, and one solves for an approximation to the average value of the solution. Two issues must be addressed by any finite volume scheme. First, one must accurately reconcile the difference between average and point values of the solution. We present weighted essentially non oscillatory methods with adaptive order (WENO-AO) to provide high order accurate reconstructions of point values from averages, when the true solution may have a shock. That is, they limit the oscillatory behavior of the reconstruction near shocks. The second issue to be resolved is the time stepping, which is normally implemented through the method of lines. We present implicit time stepping Runge-Kutta methods. Unfortunately, these can introduce oscillations into the solution, so we propose adaptive methods that can reduce to, say, backward Euler. We then turn to an improvement of the backward Euler method by considering carefully the possibility of a shock in the solution, which results in a self-adaptive theta time stepping scheme.

    BIO
    Todd Arbogast earned his Ph.D. in mathematics from the University of Chicago. He is professor of mathematics, chair of the Computational Sciences, Engineering and Mathematics Graduate Studies Committee, and a founding member and associate director of the Center for Subsurface Modeling at the Oden Institute for Computational Engineering and Sciences at UT Austin. He is the faculty co-adviser of the university’s student chapter of the Society for Industrial and Applied Mathematics. He is the current holder of the W. A. "Tex" Moncrief, Jr. Simulation-Based Engineering and Sciences Professorship I. His research contributes to the development and analysis of numerical algorithms for the approximation of partial differential systems, high performance and parallel scientific computation, and multi-scale mathematical modeling, as applied to fluid flow and transport in geologic porous media. Important applications include petroleum production, groundwater contamination, carbon sequestration, and mantle dynamics.

    NOTE
    For those new to the CSEM Program, the Babuška Forum is a seminar series started by Professor Ivo Babuška several years ago to expose students to interesting and curious topics relevant to computational engineering and science with technical content at the graduate student level (i.e. the focus of the series is on main ideas with some technical content). The forum is regularly attended by students and faculty in interdisciplinary fields held together by the common link of computational methods and mathematical modeling. The general idea is to keep the forum approachable to a diverse audience, so a certain level of pedagogy is appreciated. This is what distinguishes the forum from a typical seminar that a faculty member or researcher gives in a conference, which contains more technical material.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video).

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Thursday, May 28

Transmission of Respiratory Diseases

Thursday, May 28, 2020 from 3:30PM to 5PM | Zoom Meeting

  • Additional Information

    Hosted by Thomas Yankeelov

    Sponsor: Oden Institute Virtual Seminar

    Speaker: Lydia Bourouiba

    Speaker Affiliation: Esther and Harold E. Edgerton Professor, Civil and Environmental Engineering and Mechanical Engineering, and Institute for Medical Engineering and Science, MIT

  • Abstract

    The fundamental mechanisms governing disease transmission of and contamination by most pathogens remain poorly understood, with repeated confusion and debate about routes of transmission and mitigation at the emergence of each novel pathogen, including for COVID-19. Fluid processes and physical laws at various scales combined with biological processes are key in filling this gap. We will discuss how the underlying biophysics governing the dynamics of transmission shape a shift in paradigm in the definition of transmission routes, particularly for respiratory infectious diseases. If time allows, we will discuss how such shift can reshape our approach to multiscale modeling of epidemic dynamics.

    This seminar is jointly sponsored by the Oden Institute for Computational Engineering & Sciences, the J. Mike Walker Department of Mechanical Engineering, and the Department of Population Health, Dell Medical School.

    BIO
    Lydia Bourouiba is an Associate Professor at the Massachusetts Institute of Technology, where she directs the Fluid Dynamics of Disease Transmission Laboratory. Her research leverages advanced fluid dynamics experiments at various scales, biophysics, and applied mathematics to elucidate interfacial flow and fluid fragmentation processes driving mixing, transport, and persistence of particles and microorganisms relevant to disease transmission in human, animal, and plant populations. Prof. Bourouiba founded the Fluids and Health Conference, creating an international forum for exchange on frontier research and challenges in health, where fluid dynamic concepts are at the core, including infectious diseases, drug delivery, food safety, and related policy. Prof. Bourouiba is the recipient of many awards, including the Tse Cheuk Ng Tai’s Prize for Innovative Research in Health Sciences, the Ole Madsen Mentoring Award, and the Smith Family Foundation Odyssey Award for high-risk/high-reward basic science research.

    NOTE: Please join this Zoom seminar online with the "Audio Only" function (no video)

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Tuesday, May 26

Towards DNS of Turbulent Combustion in Complex Flows at the Exascale

Tuesday, May 26, 2020 from 3:30PM to 5PM | Zoom Meeting

  • Additional Information

    Hosted by Robert Moser

    Sponsor: Oden Institute Virtual Seminar

    Speaker: Jacqueline Chen

    Speaker Affiliation: Senior Scientist, Combustion Research Facility, Sandia National Laboratories

  • Abstract

    Direct numerical simulation methodology and computing power have progressed to the point where it is feasible to perform DNS in mildly complex geometries representative of flow configurations encountered in practical combustors. These complex flows encompass effects of mean shear, flow recirculation, and wall boundary layers together with turbulent fluctuations which affect entrainment, mixing and combustion. Examples of recent DNS studies with complex flows relevant to gas turbine and internal combustion engines will be presented and the turbulence-chemistry interactions described. These include sequential reheat combustion in the presence of mixed combustion modes – hydrogen/air autoignition and flame propagation in a rectangular duct-in-a-duct configuration, stabilization of a turbulent premixed ethylene/air flame behind a backwards facing step, turbulent piloted premixed methane/air jet flames at high Karlovitz conditions, and multi-injection mixing and ignition of prevaporized n-dodecane jets at diesel conditions. In many of these complex flows there are regions of low-intensity turbulence with mean recirculation, flame-wall interaction in boundary layers, and shear generated turbulence interacting with ignition kernels or a flame brush. The mean shear and boundary layer provide sources of turbulence generation which interact with the flame brush. These complex flows may induce turbulence-chemistry interactions distinct from those observed in isotropic decaying or forced homogeneous turbulence. New numerical diagnostics have been developed to delineate the mixed combustion regimes based on extensions of the chemical explosive mode analysis (CEMA). Finally, through the DOE Exascale Computing Project, prospects for computation of complex flows at the exascale with in situ data driven reduced order surrogate models and anomaly detection will be discussed.

    BIO
    Jacqueline H. Chen is a Senior Scientist at the Combustion Research Facility at Sandia National Laboratories. Prior to 2018, she was a Distinguished Member of Technical Staff. She has contributed broadly to research in petascale direct numerical simulations (DNS) of turbulent combustion focusing on fundamental turbulence-chemistry interactions. These benchmark simulations provide fundamental insight into combustion processes and are used by the combustion modeling community to develop and validate turbulent combustion models for engineering CFD simulations. In collaboration with computer scientists and applied mathematicians she is the founding Director of the Center for Exascale Simulation of Combustion in Turbulence (ExaCT). She leads an interdisciplinary team to co-design DNS algorithms, domain-specific programming environments, scientific data management and in situ uncertainty quantification and analytics, and architectural simulation and modeling with combustion proxy and production applications. She received the DOE INCITE Award in 2005, 2007, 2008-2014, the Asian American Engineer of the Year Award in 2009, and the Sandia OE Adams Award in 2012. She is a member of the DOE Advanced Scientific Computing Research Advisory Committee (CASCARA) and Subcommittees on Exascale Computing, and Synergies of Big Data and Exascale. She is the editor of Flow, Turbulence and Combustion, the co-editor of the Proceedings of the Combustion Institute, volumes 29 and 30, and is a member of the Board of Directors of the Combustion Institute.

    Her areas of research interests are in the development and application of massively parallel petascale direct numerical simulations (DNS) of turbulent combustion with complex chemistry. These DNS are used to understand fundamental chemistry-turbulence interactions in combustion, and to develop and validate predictive combustion models ultimately used to design efficient and clean engines reliably burning a diverse range of fuels, from bio-derived and synthesized fuels to fossil fuels from evolving feeds.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video)

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  • Additional Information

    Hosted by Thomas Yankeelov

    Sponsor: Oden Institute Virtual Seminar

    Speaker: John Lowengrub

    Speaker Affiliation: Chancellor's Professor of Mathematics, Biomedical Engineering, Chemical Engineering & Materials Science Director, Interdisciplinary Graduate Program in Mathematical, Computational & Systems Biology, University of California, Irvine

  • Abstract

    In this talk, we will show through two examples how mathematical and statistical modeling can provide insight on tumor progression that can be leveraged to improve treatment outcomes and design new therapy strategies. In the first example, we focus on chronic myeloid leukemia— a blood cancer in which there is dysregulation of maturing myeloid cells driven by a chromosomal mutation which creates the fusion gene, BCR-ABL1. Although there has been much progress in the treatment of CML by the application of tyrosine kinase inhibitors (TKI), there are still unmet clinical needs, e.g. (i) 10-15% of patients exhibit primary resistance and (ii) nearly all patients experience remission upon stopping treatment. Here, we explore how more physiologically accurate, data-driven mathematical models of CML hematopoiesis that incorporate feedback control and lineage branching can address these needs and improve treatment outcomes. In the process, we develop Bayesian methods for optimal experimental design for parameter inference. In the second example, we focus on glioblastoma (GBM), which is the most aggressive brain tumor in humans. Here, we develop highly efficient Bayesian probabilistic methods to calibrate mechanistic mathematical models using data from multimodal medical scans (MRI, FET-PET) at a single, pre-operative time point. We demonstrate how these can be used to aid in the rational design of personalized radiotherapy plans that can more efficiently target infiltrative GBM cells and provide guidance for personalized dose escalation.

    This is a Joint Seminar: Oden Institute for Computational Engineering and Science / Livestrong Cancer Institute / Dell Medical School (Department of Oncology)

    BIO
    John Lowengrub is a Chancellor's Professor at the University of California at Irvine with appointments in the departments of Mathematics and Biomedical Engineering. He is the inaugural director of the interdisciplinary graduate program in Mathematical, Computational and Systems Biology. Prof. Lowengrub is also a co-leader of the Systems, Pathways and Targets program at the Chao Family Comprehensive Cancer Center at UC Irvine. Prof. Lowengrub’s research interests include applied and computational mathematics, mathematical and computational biology, mathematical oncology, complex fluids and materials science. Prof. Lowengrub has published over 150 journal articles, several book chapters, and a book on multiscale modeling of cancer. Among his awards are a Sloan Fellowship, the Francois Frenkiel award by the American Physical Society, the Chancellor's award for excellence in fostering undergraduate research at UCI, and he was recently elected a fellow of the AAAS. Prof. Lowengrub holds a B.A. from Cornell University (1985) and a Ph.D. from the Courant Institute of Mathematical Sciences at New York University (1988).

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video)

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  • Additional Information

    Hosted by Michael Sacks and Thomas Yankeelov

    Sponsor: Oden Institute Virtual Seminar

    Speaker: C. Alberto Figueroa

    Speaker Affiliation: Edward B. Diethrich M.D. Professor in Biomedical Engineering and Vascular Surgery, University of Michigan

  • Abstract

    Despite great initial promise and numerous academic efforts, the use of image-based, patient-specific computer modelling of hemodynamics in clinical settings has been limited. Cardiovascular diagnosis still relies on simple anatomic metrics based on imaging and invasive measurements. Disease research relies heavily on animal models, which often exhibit dramatic differences in physiology and pathophysiology when compared to humans. Medical device manufacturers rely mostly on in-vitro models to investigate the anatomic variations, arterial deformations, and biomechanical forces needed for the design of medical devices. Lastly, computer-guided surgical planning has been used exclusively in academic medical centers, and is critically hampered by un-optimized workflows, uncertainties in the data, and lack of cross-disciplinary expertise between the engineering and medical teams.

    Our laboratory has over a decade of experience in conducting translational cardiovascular research embedded in clinical settings. During this time, we have trained nine clinical fellows in three different specialties -- cardiac surgery, vascular surgery, and cardiology -- in the use of advanced tools for image-based computational analysis of hemodynamics.

    In this talk, we will provide an overview of the translational research performed by such clinical fellows. Specific examples will include:
    - Computer-guided surgical planning for Fontan correction surgeries: An overview of different cases performed at the University of Michigan Mott Children’s Hospital will be presented and discussed.
    - Biomechanics of complex Thoracic Endovacular Aortic Repair (TEVAR) cases. We will present comparative analyses of different fenestrated devices for Zone 0 repair, as well as different case studies of complex hybrid aortic repairs.
    - The use of computational and machine learning tools to develop optimized workflows for near real-time estimation of arterial occlusive disease, specifically coronary artery disease.

    This is a Joint Seminar: Oden Institute/Department of Biomedical Engineering/Dell Medical School (Department of Surgery and Perioperative Care and Department of Internal Medicine, Division of Cardiology)

    BIO
    Dr. C. Alberto Figueroa received his PhD in Mechanical Engineering at Stanford University, where he developed computational methods fluid structure interaction simulation of hemodynamics. His first academic appointment was a King’s College London in the UK, where he was Senior Lecturer in the Division of Biomedical Engineering and Imaging Sciences.

    Dr. Figueroa is currently the Edward B. Diethrich M.D. Professor in Biomedical Engineering and Vascular Surgery at the University of Michigan. His laboratory is focused on three main areas: 1) developing tools for advanced modeling of blood flow. His group develops the modeling software CRIMSON (http://www.crimson.software); 2) studying the link between abnormal biomechanical stimuli and cardiovascular diseases such as hypertension and thrombosis; 3) simulation-based surgical planning to aid with the optimal planning of cardiovascular surgeries.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video)

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Tuesday, Apr 28

Time-parallel wave propagation in heterogeneous media aided by deep learning

Tuesday, Apr 28, 2020 from 3:30PM to 5PM | Zoom Meeting

  • Additional Information

    Hosted by Karen Willcox

    Sponsor: Oden Institute Virtual Seminar

    Speaker: Richard Tsai

    Speaker Affiliation: Professor, Department of Mathematics, and Core Faculty, Oden Institute, UT Austin

  • Abstract

    We present a deep learning framework for learning multiscale wave propagation in heterogeneous media. The framework involves the construction of linear feed-forward networks (experts) that specialize in different media groups and a nonlinear "committee" network that gives an improved approximation of wave propagation in more complicated media. The framework is then applied to stabilize the "parareal" schemes of Lions, Maday, and Turinici, which are time-parallelization schemes for evolutionary problems.

    BIO
    Richard Tsai earned his Ph.D. in mathematics from the University of California, Los Angeles. He is a professor in mathematics, a member of the Oden Institute's Core Faculty, a member of the Oden Institute Graduate Studies Committee (GSC), and affiliated with the Oden Institute Center for Numerical Analysis. His current research interests include multiscale modeling and computation, inverse source problems, interface problems, robotic path planning problems involving visibility optimization, and image processing. His current works involve applications in crystal growth, porous media flow, seismic imaging, robotics, oscillatory mechanical systems, and endoscopic image analysis. He is a recipient of an Alfred Sloan Research Fellowship, a FEMLAB prize, and a 2018 Peter O’Donnell Distinguished Research Award.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video)

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Thursday, Apr 23

Computational Methods for Collisional Transport: from Gas Dynamics to Mean Field Theory

Thursday, Apr 23, 2020 from 3:30PM to 5PM | Zoom Meeting

  • Additional Information

    Hosted by Karen Willcox

    Sponsor: Oden Institute Virtual Seminar

    Speaker: Irene Gamba

    Speaker Affiliation: Professor, Department of Mathematics and leader of the Oden Institute's Applied Mathematics Group

  • Abstract

    The Boltzmann and Landau transport equation are at the core of statistical mechanics and physics when modeling meso-scales modeling the rarefied transport of particle undergoing interactions or collisions between particles of single or different species. Such collision operator are non-local with a bi-linear structure that enables particle mixing as much as classical conservation laws and entropy inequalities that control the decay rate to their steady equilibrium states. These models are naturally linked to classical fluid dynamics models that arise when their solutions are close to the statistical equilibrium given by Maxwell-Boltzmann distributions.

    We will discuss two deterministic alternative computational techniques, namely a conservative-spectral scheme and a Galerkin-Petrov one, as much as their ability to capture phenomena due to boundary data that may not be well address neither by DSMC schemes nor by classical Navier Stokes equations for different problems raising from Mean Field Theory when coupling to the transportVlasov-Poisson system.

    In addition, we will focus on error estimates for these collisional schemes and their applications to the Boltzmann for knock-on collisions, or Landau for Coulomb collisions operators and the ability to capture the expected decay rate to equilibrium as a function of intramolecular potentials. In addition we present a nw entropy stabilized method for a lid-driven cavity flow model with nonequilibrium conditions by a collisional solver in an approximation to Boltzmann moment closure yielding the Navier Stokes Fourier system with wall thermalization boundary conditions.

    This is is work from several contributions in collaboration with R. Alonso, S.H. Tharkabhushanam, C. Zhang and J. Haack and C. Pennie for the conservative-spectral methods on Boltzmann and Landau models, and M. Abedelmalik, F. Baidoo, T. Hughes, T. Kessler and S. Rjasanow for the Galerkin-Petrov approach.

    BIO
    Irene M. Gamba is Professor of Mathematics and leader of the Oden Institute's Applied Mathematics Group. She holds the W.A. “Tex” Moncrief, Jr. Chair in Computational Engineering and Sciences III. She earned her Ph.D. in mathematics at the University of Chicago in 1989 and held a National Science Foundation (NSF) postdoctoral fellowship at the Courant Institute at New York University, where she later became assistant and associate professor before coming to The University of Texas at Austin in 1997. Her scientific interests are analytical and computational issues in collisional kinetic theory include the evolution Boltzmann and Landau type equations in mean field regimes, gas mixture systems and quantum Boltzmann condensation in low temperatures regimes. Applications of these models range from plasma dynamics such as electron runaway transport, charged transport in nanodevices, approximations to classical fluid dynamics models and coupling of quantum gas system in the formation of condensates.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video)

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Friday, Apr 17

Challenges in the Predictive Simulation of an Inductively Coupled Plasma Torch

Friday, Apr 17, 2020 from 10AM to 11AM | Zoom Meeting

  • Additional Information

    Hosted by Stefan Henneking

    Sponsor: Oden Institute Virtual Seminar - Babuska Forum series

    Speaker: Robert Moser

    Speaker Affiliation: Professor, Department of Mechanical Engineering and Deputy Director, Oden Institute for Computational Engineering and Sciences, UT Austin

  • Abstract

    An inductively coupled plasma (ICP) torch is a device used in a number of industrial and research applications, including surface heat treatment, materials testing, cutting and welding, nanopowder synthesis, synthesis of gas products, and deposition of functional coatings. It produces a plasma by inducing a large amplitude oscillating electro-magnetic field in a gas flow, which has the practical advantage of not requiring electrodes in the plasma flow.

    A large new multi-disciplinary research project to develop high fidelity predictive simulation models of ICP torches is starting at the Oden Institute. Simulation of an ICP torch requires integrated models for plasma dynamics, chemical kinetics, thermodynamic non-equilibrium, turbulence, electromagnetism, and radiative heat transfer. Further, a high-fidelity ICP simulation will require extraordinary computing resources. So the simulator development will drive research in advanced algorithms for use on next-generation high-performance computing architectures, as well as computer language and software tools to enable effective use of these architectures. Finally, predictive simulation requires rigorous validation and uncertainty quantification (UQ), and the development advanced UQ algorithms required for use with high-dimensional uncertainties and such expensive models. For validation, a closely coupled set of advanced experiments on an ICP torch will be conducted.

    In this talk, we will discuss the ICP torch and its simulation, with particular attention to the modeling, algorithmic, computer science, validation and uncertainty quantification challenges we will be addressing to enable such simulations.

    This seminar will cover joint work by Robert Moser and George Biros.

    NOTE
    This seminar is a part of Babuška Forum series. For those new to the CSEM Program, the Babuška Forum is a seminar series started by Professor Ivo Babuska several years ago to expose students to interesting and curious topics relevant to computational engineering and science with technical content at the graduate student level (i.e. the focus of the series is on main ideas with some technical content).

    BIO
    Robert D. Moser holds the W. A. "Tex" Moncrief Jr. Chair in Computational Engineering and Sciences and is Professor of Mechanical Engineering in thermal fluid systems. He serves as the Director of the Center for Predictive Engineering and Computational Sciences (PECOS) and Deputy Director of the Oden Institute for Computational Engineering and Sciences. Moser received his PhD in mechanical engineering from Stanford University. Before coming to the University of Texas, he was a research scientist at the NASA-Ames Research Center and then a Professor of Theoretical and Applied Mechanics at the University of Illinois. Moser conducts research on the modeling and numerical simulation of turbulence and other complex fluid flow phenomena. He also uses direct numerical simulation to investigate and model turbulent flows, particularly the development and evaluation of large eddy simulation models. Moser has also been working to develop new approaches for the validation of and quantification of uncertainty in computational models and to assess their reliability. He has pursued applications to such diverse systems as reentry vehicles, solid propellant rockets, micro-air vehicles, turbulent combustion, tokamak fusion and energy harvesting. He is a Fellow of the American Physical Society, and was awarded the NASA Medal for Exceptional Scientific Achievement.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video).

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Thursday, Apr 16

Atomically Detailed Simulations of Heterogeneous Membranes

Thursday, Apr 16, 2020 from 3:30PM to 5PM | Zoom Meeting

  • Additional Information

    Hosted by Karen Willcox

    Sponsor: Oden Institute Virtual Seminar

    Speaker: Ron Elber

    Speaker Affiliation: Professor, Department of Chemistry and Biochemistry, and Core Faculty, Oden Institute, UT Austin

  • Abstract

    Biological Membranes are extremely heterogeneous materials. They are made of thousand types of phospholipid molecules and many inserts such as cholesterol molecules and transmembrane proteins. Membranes are also dynamics. Transient microdomain formations and the controversial concept of “rafts” are essential for biological functions such as signaling and transport. Atomically detailed simulations may shed light on these cooperative phenomena. However, Molecular Dynamics is too slow to observe significant assembly and dismantling events. Moreover, the acceptance probability of the usual Monte Carlo moves is also low in these dense systems. Therefore, the standard technologies for particle simulations fail to address membrane diversity.

    I will present our new approach (MDAS) to simulate membranes, which is based on gradual Monte Carlo moves in which we accept or reject mutation trajectories. Provided that such trajectories can be designed, MDAS simulations are more efficient than conventional Molecular Dynamics by factors of thousands. I will illustrate the application of MDAS on a few model systems and discuss the phase diagram of a membrane that consists of DPPC and DLPC mixture.

    BIO
    Ron Elber is a W.A. “Tex” Moncrief Chair in Computational Life Sciences and Biology. He has been conducting Molecular Dynamics simulations of biological systems for as long as he remembers. He has been influential in the field and introduced several widely recognized and used algorithms for particle simulations. Among those are algorithms to compute reaction paths based on a whole curve optimization, and the use of phase space partitions to conduct simulations of rare events. He is working on proteins, RNA molecules, and membranes, but so far did not touch sugars. The talk will describe a recent algorithmic addition to the simulations of heterogeneous material and its applications.

    NOTE
    Please join this Zoom seminar online with the "Audio Only" function (no video).

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Thursday, Apr 9

How molecular machines break the symmetry between forward and backward motion

Thursday, Apr 9, 2020 from 3:30PM to 5PM | Zoom Meeting

  • Additional Information

    Hosted by Karen Willcox

    Sponsor: Oden Institute Virtual Seminar

    Speaker: Dmitrii Makarov

    Speaker Affiliation: Professor, Department of Chemistry, and Core Faculty, Oden Institute, UT Austin

  • Abstract

    According to Purcell’s “scallop theorem”, a bacterium cannot swim the way a much larger organism – scallop – does, i.e. via reciprocal or time-reversible periodic motion. The mechanical motion of scallops, bacteria or humans is ultimately generated by nanometer-sized molecular machines, whose action, in contrast to the more familiar macroscopic engines, relies on the randomness of thermal motion and on microscopic reversibility. For example, a car’s internal combustion engine cannot consume its exhaust products and propel the car backwards while synthesizing fresh gasoline and depositing it into its gas tank. Yet some of the molecular machines in living organisms have the ability to operate in the backward direction and to synthesize their “fuel” molecules when doing so.

    In this talk I will discuss whether the forward step of a molecular machine is the time reverse of its backward step. To answer this question, I will introduce two simple models for the action of such a machine: one is based on the Einstein-Smoluchowski theory of Brownian motion and the other views a machine’s dynamics as a continuous-time random walk on a network. I will show that forward/backward symmetry violation for any collective variable describing the motor dynamics occurs only if two conditions are met simultaneously: (1) the dynamics of this variable is non-Markovian and (2) the system is not in equilibrium. This talk is meant to be a pedagogical introduction into the subject, and use of any biological lingo will be expressly avoided.

    BIO
    Dmitrii E Makarov is a Professor of Chemistry and core faculty at the Oden Institute, UT Austin. His research is in the field of computational and theoretical chemical physics, with current focus on molecular biophysics, mechanochemistry, and single-molecule phenomena.

    Note: Please join this Zoom seminar online with the "Audio Only" function (no video)

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