26-28 March 2018
Stuttgart, Germany
Europe/Berlin timezone

Michael Ortiz


Wednesday, 28 March 2018

2:45pm - 3:30pm

Campus Stuttgart-Vaihingen, Pfaffenwaldring 47

Room V 47.03


Data-Driven Computing

We develop a new computing paradigm, which we refer to as Data-Driven Computing, according to which calculations are carried out directly from experimental material data and pertinent kinematic constraints and conservation laws, such as compatibility and equilibrium, thus bypassing the empirical material modeling step of conventional computing altogether. Data-driven solvers seek to assign to each material point the state from a prespecified data set that is closest to satisfying the conservation laws. Equivalently, data-driven solvers aim to find the state satisfying the conservation laws that is closest to the data set. The resulting Data-driven problem thus consists of the minimization of a distance function to the data set in phase space subject to constraints introduced by the conservation laws. We demonstrate the Data-driven paradigm and investigate the performance of Data-driven solvers by means of several examples of application, including statics and dynamics of nonlinear three-dimensional trusses, and linear and nonlinear elasticity. In these tests, the Data-driven solvers exhibit good convergence properties both with respect to the number of data points and with regard to local data assignment, including noisy material data sets containing outliers. The variational structure of the Data-driven problem also renders it amenable to analysis. We find that the classical solutions are recovered in the case of linear elasticity. We identify conditions for convergence of Data-Driven solutions corresponding to sequences of approximating material data sets. Specialization to constant material data set sequences in turn establishes an appropriate notion of relaxation. We find that relaxation within the Data-Driven framework is fundamentally different from the classical relaxation of energy functions. For instance, we show that in the Data-Driven framework the relaxation of a bistable material leads to effective material data sets that are not graphs. I will finish my presentation with highlights on work in progress, including closed-loop Data-Driven analysis and experiments, Data-Driven molecular dynamics, Data-Driven inelasticity and publicly-editable material data repositories and data management from a Data-Driven perspective.



Professor Michael Ortiz received a BS degree in Civil Engineering from the Polytechnic University of Madrid, Spain, and MS and PhD degrees in Civil Engineering from the University of California at Berkeley.

From 1984-1995 he held a faculty position in the Division of Engineering of Brown University, where he carried out research activities in the fields of mechanics of materials and computational solid mechanics. He is currently the Dotty and Dick Hayman Professor of Aeronautics and Mechanical Engineering at the California Institute of Technology, where he has been in the faculty since 1995.

Professor Ortiz is or has been a Fulbright Scholar, a Sherman Fairchild Distinguished Scholar at Caltech, Midwest and Southwest Mechanics Seminar Series Distinguished Speaker, a Fellow and an elected member-at large of the US Association for Computational Mechanics, Hans Fischer Senior Fellow of the Institute of Advanced Studies of the Technical University of Munich, an elected Fellow of the American Academy of Arts & Sciences and an elected member of the US National Academy of Engineering.

Furthermore he is the recipient of the Alexander von Humboldt Research Award for Senior US Scientists, the IACM International Computational Mechanics Awards for Research, the USACM Computational Structural Mechanics Award, the ISI Highly Cited Researcher Award, the inaugural 2008 Rodney Hill Prize conferred every four years by the IUTAM and the Timoshenko Medal of the American Association of Mechanical Engineers.

He has served in the University of California Office of the President Science and Technology Panel and in the Lawrence Livermore National Laboratory Predictive Science Panel. He has been editor of the Journal of Engineering Mechanics of ASCE and of the Journal of Applied Mechanics of the ASME, associate editor of the journal Modeling and Simulation in Materials Science and Engineering and of the Journal for Computational Mechanics, and is presently associate editor of the Journal for the Mechanics and Physics of Solids and of the Archive for Rational Mechanics and Analysis.

Actually, he holds an h-index of 78 at Thomson Reuter’s ISI Web of knowledge.


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